Soil Nitrogen Dynamics Under Adjacent Native Forest … · Soil Nitrogen Dynamics Under Adjacent...

Soil Nitrogen Dynamics Under Adjacent Native

Forest and Hoop Pine Plantations

Joanne Mary Burton B.Sc. (Hons)

Griffith School of Environment

Griffith University, Nathan, Queensland

Submitted in fulfillment of the requirements for the degree of

Doctor of Philosophy

January 2007

Perhaps our most precious and vital source, both physical

and spiritual, is the most common matter underfoot which

we scarcely even notice and sometimes call “dirt”, but which

is in fact the mother-lode of terrestrial life and the purifying

medium wherein wastes are decomposed and recycled, and

productivity is generated.

Daniel Hillel, Out of the Earth

v

Declaration of Originality

The experimentation, analyses, presentation and interpretation of results

in this thesis represent original work that has not been previously

submitted for a degree or diploma in any university. To the best of my

knowledge and belief, this thesis contains no material previously

published or written by another person except where due reference is

made within the thesis itself.

__________________________

Joanne M. Burton

vi

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Abstract Single-species plantation forests have become the dominant source of inputs

for the Queensland forest industry. Almost a quarter (50,000 ha) of the Queensland

plantation estate is accounted for by plantations of the nitrogen (N) demanding

species, hoop pine (Araucaria cunninghamii). The majority of the hoop pine estate

was originally native forest, and is currently moving into the second rotation phase.

The future of plantations of this N demanding species is dependent on the long-term

maintenance of soil N cycling and availability. Land-use change can impact soil N

dynamics; however there is currently limited knowledge of how the land-use change

from native forest (NF) to first rotation (1R) hoop pine plantation and subsequent

second rotation (2R) hoop pine plantation, and the associated disturbance due to site

preparation have influenced soil N transformations and availability. The objectives of

this study were to examine the impact of land-use change from 1) NF to 1R hoop pine

plantation, and 2) 1R hoop pine plantation to 2R hoop pine plantation on soil N

dynamics. The impact of the current 2R residue management strategy was also

examined. The study was conducted in adjacent NF, 1R hoop pine plantation, and 2R

hoop pine plantation (5-year old) in Yarraman State Forest, south-east Queensland.

A laboratory incubation using the 15N isotope dilution method was undertaken

in order to examine the impact of land-use change and residue management on gross

N transformations. Results showed that land-use change had a significant impact on

soil N transformations. The conversion of the NF to the 1R hoop pine plantation

significantly reduced the availability of NH4+-N and NO3

- -N. It also decreased the

rate of gross N mineralisation (measured under anaerobic conditions) and gross

nitrification (measured under aerobic conditions). This result was related to lower

soil, litter and root C:N ratios in the NF compared to the 1R hoop pine plantation,

indicating a reduction in organic matter quality associated with the land-use change.

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The conversion of 1R to 2R hoop pine plantation resulted in an increase in the gross

rate of ammonification. This was attributed to an increase in mineralisation of native

organic N associated with changes in soil physical conditions and microclimate as a

result of harvesting. Residue management was found to have no significant influence

on the soil N transformations in the 2R plantation approximately five years after

establishment.

A second study focused on quantifying the impact of land use and residue

management on soil soluble organic N (SON) pools using a variety of extraction

methods, including water, hot water, 0.5 M K2SO4, 2 M KCl and hot KCl. Both land

use and residue management were found to have a significant influence on the size of

soil SON pools. The conversion of NF to 1R hoop pine plantation tended to result in

a decrease in the amount of soil SON and the potential to produce SON. This

reduction coincided with increased soil, litter and root C:N ratios, and may therefore

be the result of a decline in organic matter quality and quantity. The conversion of 1R

to 2R hoop pine plantation generally resulted in a reduction in the amount of SON.

Residue management also had a significant influence on soil SON pools, which

tended to be higher in windrows of harvest residues than in tree rows.

The impact of land-use change on the size, activity, and composition of the

soil microbial community was examined using fumigation-extraction, CO2

respiration, and community level physiological profiling (CLPP) techniques. Land-

use change from NF to 1R hoop pine plantation resulted in a reduction in microbial

biomass and activity, and a shift in soil microbial community composition. While the

conversion from 1R to 2R hoop pine plantation appeared to have no significant

influence on the size and activity of the soil microbial community, there were some

indications of a difference in community composition. Soil microbial biomass and

ix

activity tended to increase as the quality and quantity of organic matter input

increased.

An 18-month field-based study was conducted using the in-situ incubation

method to examine the impact of land-use change on seasonal N dynamics. The

results of this study were consistent with results from the laboratory studies. In

general, the rate of N transformations and size of soil mineral N pools and microbial

biomass were lower in the 1R soil compared to the NF soil. The 1R soils tended to

have lower total C and total N, and higher C:N ratios compared to the NF soil,

indicating that lower rates of N transformation and N availability in the 1R soil may

be a result of significant reductions in organic matter quality and quantity. While the

difference in the rates of net N mineralisation and net nitrification among the

plantation soils were statistically insignificant, over the 18-month sampling period

more N was mineralised and nitrified in the 2R soil compared to the 1R soil. Residue

management also influenced the total amount of N transformed over the sampling

period, with more N tending to be mineralised and nitrified in soil under windrowed

residues compared to soil under tree rows. Seasonal fluctuations in soil N dynamics

tended to be controlled by temperature and soil moisture.

From these results, it was concluded that land-use change and residue

management had a significant impact on soil N dynamics. This was possibly

associated with shifts in the quality and quantity of organic inputs, soil microbial

properties and microclimate conditions. Results from this study indicate that land-use

change and residue management may have implications for the long-term productivity

of the soil resource. Future studies are required to improve the understanding of the

chemical and biological mechanisms driving changes in soil N dynamics.

x

Acknowledgements I am deeply grateful to my supervisors, Professor Zhihong Xu, Associate Professor

Hossein Ghadiri and Dr Chengrong Chen, for their guidance, enthusiasm and

encouragement during my candidature. I sincerely appreciate the time and effort each

of them has given to help me reach this milestone.

This PhD was undertaken with a Griffith University Postgraduate Research

Scholarship and a top-up scholarship from the Co-operative Research Centre for

Sustainable Production Forestry. Funding for various aspects of this project was also

provided by the Centre for Forestry and Horticultural Research, the Australian Rivers

Institute and Forestry Plantations Queensland.

Forestry Plantations Queensland allowed me to conduct this research in Yarraman

State Forest. In particular I thank Mr Richard Jackson and staff members of the

Yarraman Forestry Office for providing me with climate records and historical

information.

Dr Tim Blumfield (Centre for Forestry and Horticultural Research, Griffith

University), and Mr Paul Keay, (Forestry Plantations Queensland) spent many long

hours helping me with fieldwork. The 18-month field study would not have been

possible without their help and I would like to thank them for their hard work and

friendship. I am also grateful to Dr Chengrong Chen, Dr Rui Yin, Mr Yu Huang, Mr

Zhiquan Huang, Mr Stephen Faggotter and Mrs Elizabeth Watt for their assistance

with soil sampling and processing.

I thank the academic staff and students of the Australian Rivers Institute, the Centre

for Forestry and Horticultural Research, and the Griffith School of Environment, for

sharing their expertise, and offering their support and friendship throughout the period

of my candidature. Thanks also to technical, workshop and administration staff, who

helped to make life run as smoothly as possible, particularly: Mr Scott Burns, Mrs

Deslie Smith, Mr David Henstock, Mr Bob Coutts, and Mr Bruce Mudway. I would

also like to acknowledge the contribution of Mr Rene Diocares, Technical Officer, for

his assistance with isotope ratio and flow injection analyses. It has been my absolute

pleasure and privilege to work with this fantastic group of people.

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For sharing the daily grind I thank my office mates, past and present (in order of

appearance): Tim, Megan, Naema and Paula.

My thanks also to:

Mr Cyril Ciesiolka, whose passion and knowledge of landscape formation, soil

science and catchment processes inspired my appreciation of and enthusiasm for

studying environmental sciences, particularly the complex and wondrous world of

soil. I am extremely grateful that he is here to share this achievement with me.

Associate Professor Janet Chaseling and Dr James McBroom who provided me with

invaluable guidance in all things statistical.

Dr Richard Hindmarsh, whose words of advice at a crucial time in my candidature are

part of the reason I made it to the end.

When I began this journey I had no idea of the challenges ahead of me. Fortunately I

have a wonderful family and many good friends who have helped me along the way.

I thank them all for their laughter, love and patience and look forward to spending

more time with them when I become human again. Special thanks to: Jessie, Liz,

Katie, Kylie, Ro and Egguardo for assistance with formatting and proof reading, and

for always knowing the right thing to say. To mum and dad, who have offered

support in so many ways. I thank them for their generosity and love, and for being the

wonderful people that they are.

Finally, I would like to thank my husband Stephen, for his love, support and

unwavering belief in me. When my spirits were faltering, you were the one who

reminded me of the purpose of this tumultuous journey. I am forever grateful.

xii

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Parts of this thesis that have been accepted or submitted for publication in

advance of submission for examination are listed below:

1. Gross nitrogen transformations in adjacent native and plantation forests of

subtropical Australia. JM Burton, CR Chen, ZH Xu, H Ghadiri. 2007. Soil

Biology and Biochemistry 39: 426-433. (Derived from data presented in

Chapter 3).

2. Soluble organic nitrogen pools in adjacent native and plantation forests of

subtropical Australia. JM Burton, CR Chen, ZH Xu, H Ghadiri. 2007. Soil

Biology and Biochemistry 39: 2723-2734. (Derived from data presented in

Chapter 4).

xiv

Table of Contents

DECLARATION OF ORIGINALITY..................................................................................V

ABSTRACT ......................................................................................................................... VII

ACKNOWLEDGEMENTS....................................................................................................X

TABLE OF CONTENTS................................................................................................... XIV

LIST OF TABLES........................................................................................................... XVIII

LIST OF FIGURES............................................................................................................ XXI

CHAPTER 1 INTRODUCTION............................................................................................ 1

1.1 HOOP PINE PLANTATIONS......................................................................................... 1

1.2 SOIL NITROGEN DYNAMICS IN FOREST ECOSYSTEMS............................................... 2

1.3 RESEARCH PROGRAM............................................................................................... 6

1.3.1 Hypotheses........................................................................................................... 7

1.3.2 Objectives ............................................................................................................ 8

CHAPTER 2 MATERIALS AND METHODS .................................................................. 10

2.1 MATERIALS ............................................................................................................ 10

2.1.1 Study site............................................................................................................ 10

2.1.2 Experimental design .......................................................................................... 14

2.2 METHODS ............................................................................................................... 16

2.2.1 Treatment of samples......................................................................................... 16

2.2.2 Soil analyses ..................................................................................................... 17

CHAPTER 3 GROSS NITROGEN TRANSFORMATIONS IN ADJACENT NATIVE

AND PLANTATION FORESTS OF SUBTROPICAL AUSTRALIA............................. 21

3.1 INTRODUCTION....................................................................................................... 21

3.2 MATERIALS AND METHODS ................................................................................... 23

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3.2.1 Sample collection............................................................................................... 23

3.2.2 Aerobic and anaerobic incubations................................................................... 23

3.2.3 Steam distillation and chemical analysis........................................................... 25

3.2.4 Calculations and statistical analysis ................................................................. 26

3.3. RESULTS................................................................................................................. 27

3.3.1 Soil chemical properties .................................................................................... 27

3.3.2 Characteristics of forest litter material and tree roots...................................... 27

3.3.3 Aerobic incubation ............................................................................................ 30

3.3.4 Anaerobic incubations ....................................................................................... 32

3.4. DISCUSSION............................................................................................................ 32

3.4.1 Impacts of land-use change on soil N mineralisation and immobilisation........ 32

3.4.2 Impacts of land-use change on soil nitrification ............................................... 34

3.4.3 Comparison of aerobic and anaerobic results .................................................. 36

3.4.4 Comparison of net and gross transformation rates ........................................... 37

3.5 CONCLUSION ................................................................................................................. 37

CHAPTER 4 SOLUBLE ORGANIC NITROGEN POOLS IN ADJACENT NATIVE

AND PLANTATION FORESTS OF SUBTROPICAL AUSTRALIA............................. 39

4.1 INTRODUCTION....................................................................................................... 39


4.2.1 Sample collection............................................................................................... 41

4.2.2 Preparation of soil extracts ............................................................................... 42

4.2.3 Analysis of soluble N in soil extracts ................................................................. 42

4.2.4 Potential production of SON and SOC.............................................................. 43

4.2.5 Statistical analysis ............................................................................................. 44

4.3. RESULTS................................................................................................................. 44

4.3.1 Water extractable organic N ............................................................................. 44

4.3.2 Hot water extractable organic N ....................................................................... 47

4.3.3 KCl and K2SO4 extractable organic N............................................................... 48

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4.3.4 Hot KCl extractable organic N.......................................................................... 52

4.3.5 Potential production of SON.................................................................................. 54

4.3.6 Relationships among SON pools............................................................................ 54

4.4 DISCUSSION............................................................................................................ 59

4.4.1 Pool size of SON measured by the different procedures.................................... 59

4.4.2 The effect of land-use change on SON pools ..................................................... 61

4.4.3 The effect of land-use change on PPSON.......................................................... 65

4.5 CONCLUSIONS ........................................................................................................ 66

CHAPTER 5 SOIL MICROBIAL BIOMASS, ACTIVITY AND COMMUNITY

COMPOSITION IN ADJACENT NATIVE AND PLANTATION FORESTS OF

SUBTROPICAL AUSTRALIA............................................................................................ 68

5.1 INTRODUCTION.............................................................................................................. 68


5.2.1 Sampling ............................................................................................................ 71

5.2.2 Microbial biomass C and N............................................................................... 71

5.2.3 Soil respiration .................................................................................................. 71

5.2.4 Community level physiological profiles............................................................. 72

5.2.5 Statistical analysis ............................................................................................. 75

5.3 RESULTS ........................................................................................................................ 76

5.3.1 Microbial Biomass................................................................................................. 76

5.3.2 Soil respiration and metabolic quotients ........................................................... 79


5.3.3.1 BiologTM....................................................................................................................................... 80

5.3.3.2 MicroRespTM ................................................................................................................................ 84

5.4 DISCUSSION............................................................................................................ 88

5.4.1 Soil microbial biomass and respiration............................................................. 88


5.5 CONCLUSION ................................................................................................................. 94

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CHAPTER 6 SEASONAL INFLUENCES ON SOIL NITROGEN POOLS AND

TRANSFORMATIONS IN ADJACENT NATIVE FOREST AND HOOP PINE

PLANTATIONS .................................................................................................................... 95

6.1 INTRODUCTION....................................................................................................... 95 6.2 METHODS ............................................................................................................... 96

6.2.1 Sampling ............................................................................................................ 96 6.2.2 Soil analysis ....................................................................................................... 98 6.2.3 Calculations....................................................................................................... 99

6.3 RESULTS............................................................................................................... 100 6.3.1 Rainfall, temperature and soil moisture .......................................................... 101 6.3.2 Soil C and N..................................................................................................... 101 6.3.3 Seasonal dynamics of mineral N pools ............................................................ 105 6.3.4 Net N transformations...................................................................................... 107 6.3.5 Microbial biomass ........................................................................................... 111 6.3.6 Potential N loss................................................................................................ 113

6.4 DISCUSSION.......................................................................................................... 113 6.4.1 Impact of land use on measured soil properties .............................................. 114 6.4.2 Seasonal trends of soil mineral N pools .......................................................... 116 6.4.3 Seasonal trends of soil N transformations....................................................... 118 6.4.3 Seasonal trends of soil microbial biomass C and N ........................................ 119 6.4.4 Potential N loss................................................................................................ 120

6.5 CONCLUSION ........................................................................................................ 120

CHAPTER 7 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS FOR

FUTURE WORK ................................................................................................................ 122

7.1 SUMMARY ............................................................................................................ 122 7.2 CONCLUSIONS ...................................................................................................... 127 7.3 FUTURE WORK...................................................................................................... 128

REFERENCES .................................................................................................................... 132

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List of Tables Table 2.1: Basic soil physical properties in adjacent native forest (NF), first rotation hoop

pine plantation (1R), second rotation tree row (2R-T) and second rotation windrow (2R-

W) at the Yarraman site, subtropical Australia............................................................... 18

Table 3.1: Soil properties (0-10 cm) for adjacent native forest (NF), 53 y-old first rotation

hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T), and second rotation

windrow (2R-W) at the Yarraman site, subtropical Australia.. ...................................... 28

Table 3.2: Basic chemical properties of litter (L) and fermentation (F) layer of adjacent native

forest (NF) and 53 y-old first rotation hoop pine plantation (1R) at the Yarraman site,

subtropical Australia.. ..................................................................................................... 29

Table 3.3: Gross and net N mineralisation, ammonification and NH4+ consumption rates in the

0-10 cm soil layer of adjacent native forest (NF), 53 y-old first rotation hoop pine

plantation (1R), 5 y-old second rotation tree row (2R-T), and second rotation windrow

(2R-W) at the Yarraman site, subtropical Australia.. ..................................................... 31

Table 4.1: Soil total carbon (C), total nitrogen (N) and C:N ratios for adjacent native forest

(NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree row

(2R-T), and second rotation windrow (2R-W) at the Yarraman site, subtropical

Australia.......................................................................................................................... 41

Table 4.2: Soluble inorganic N (SIN) and organic N (SON) extracted by water (w) from soils

of adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old

second rotation tree row (2R-T), and second rotation windrow (2R-W) at the Yarraman

site, subtropical Australia. .............................................................................................. 46

Table 4.3: Soluble inorganic N (SIN) and organic N (SON) extracted by hot water (hw) from

soils of adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5

y-old second rotation tree row (2R-T), and second rotation windrow (2R-W) at the

Yarraman site, subtropical Australia. ............................................................................. 49

Table 4.4: Soluble inorganic N (SIN) and organic N (SON) extracted by KCl (KCl) from soils


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Table 4.5: Soluble inorganic N (SIN) and organic N (SON) extracted by K2SO4 (ps) from soils




Table 4.6: Soluble inorganic N (SIN) and organic N (SON) extracted by hot KCl (hKCl) from

soils of adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5



Table 4.7: Potential production of inorganic N (PPSIN) and potential production of soluble

organic N (PPSON) calculated based on a seven day anaerobic incubation from soils of

adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old



Table 4.8. Spearman rank correlation coefficients between soluble organic nitrogen (SON)

pools and soluble organic carbon (SOC) pools in adjacent native forest (NF), 53 y-old

first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T), and

second rotation windrow (2R-W) at the Yarraman site, subtropical Australia............... 56

Table 5.1: Carbon (C) sources used in the MicroRespTM method .......................................... 74

Table 5.2: Microbial biomass carbon (MBC) and nitrogen (MBN) contents in the adjacent

native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second

rotation tree row (2R-T), and second rotation windrow (2R-W) at the Yarraman site,

subtropical Australia. ...................................................................................................... 77

Table 5.3: Spearman rank correlation coefficients between soil microbial and nutrient

parameters in the 0-10 cm layer of adjacent native forest (NF), 53 y-old first rotation

hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T) and second rotation

windrow (2R-W) at the Yarraman site, subtropical Australia. ....................................... 78

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Table 5.4: Average well colour development (AWCD), total plate activity, Shannon’s

diversity index (SDI) and substrate richness calculated from Biolog optical density data

(OD>0.1) of the soil extracts from the 0-10 cm soil layer of the adjacent native forest

(NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree row

(2R-T), and second rotation windrow (2R-W) at the Yarraman site, subtropical

Australia.......................................................................................................................... 81

Table 5.5: MicroResp C source substrate induced respiration (SIR) in the 0-10 cm soil layer

of the adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-

old second rotation tree row (2R-T), and second rotation windrow (2R-W) at the


Table 6.1: Range and mean values for soil properties determined for the 0-10 cm soil layer of

adjacent native forest (NF), first rotation hoop pine plantation (1R), second rotation tree

row (2R-T) and second rotation windrow (2R-W) over the period August 2002 –

January 2004, at the Yarraman site, subtropical Australia. .......................................... 104

Table 6.2: Percent 15N lost from the 0-20 cm soil layer in adjacent native forest (NF), 53 y-old

first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T) and

second rotation windrow (2R-W), in sampling cycles of moderate (sampling cycle 3 –

October 2002, mid spring) and high (sampling cycle 7 – February 2003, late summer)

rainfall........................................................................................................................... 113

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List of Figures Fig 1.1: Soil N cycle ................................................................................................................. 5

Fig. 1.2: Conceptual model of the key factors influencing soil N dynamics following land-

use changes from native forest to first roation (1R) hoop pine plantation, and subsequent

conversion to second rotation hoop pine plantation with associated residue management

strategy.............................................................................................................................. 9

Fig. 2.1: Map of Queensland showing areas of forestry reserve and the location of Yarraman

State Forest (inset). . ....................................................................................................... 12

Fig. 2.2: Location of adjacent native forest (NF), first rotation hoop pine plantation (1R), and

second rotation hoop pine plantation (2R) (Experiment 2407 YMN) within Pocket

Logging Area 289 of Yarraman State Forest in subtropical Australia. .......................... 13

Fig. 2.3: Photograph of the first rotation (1R) hoop pine plantation (a), and the second

rotation (2R) hoop pine plantation showing the second rotation tree-rows (2R-T), and

second rotation windrows (2R-W), with the adjacent native forest (NF) in the

background (b). Both photographs were taken at the Yarraman study site in August

2002. ............................................................................................................................... 15

Fig. 2.4: Eurovector Elemental Analyser (Isoprime-EuroEA 3000, Milan, Italy).................. 18

Fig. 2.5: The LACHAT Quickchem Automated Ion Analyser used for analysis of mineral N.

........................................................................................................................................ 19

Fig. 2.6: SHIMADZU TOC-VCPH/CPN analyser (fitted with TN unit) ....................................... 20

Fig 3.1: Velp distillation unit .................................................................................................. 25

Fig. 3.2: Gross and net nitrification and NO3- consumption rates in the 0-10 cm soil layer of




Fig. 4.1: Differences between SONhw and SONw (black bars) and between SONhKCl and

SONKCl (grey bars) in NF, 1R, 2R-T and 2R-W forest soils in (a) 0-10 cm; (b) 10-20 cm;

and (c) 20-30 cm............................................................................................................. 57

xxii

Fig. 4.2: Relationships (a) between the potential production of soluble organic nitrogen

(PPSON) and SON extracted using the hot KCl method (SONhKCl), or NH4+ extracted

using the hot KCl method (NH4+

hKCl); and (b) between PPSON and SON extracted using

the hot water method (SONhw), or NH4+

extracted using the hot water method (NH4+

hw).

........................................................................................................................................ 58

Fig 5.1: MicroRespTM plate system comprising a deep-well microtiter plate to hold soil, an

interconnecting gasket, and a top plate containing detection gel.................................... 74

Fig. 5.2: Respiration rate (black bars) and metabolic quotient (grey bars) in the 0-10 cm soil

layer of adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5


Yarraman site, subtropical Australia .............................................................................. 79

Fig. 5.3: Cumulative respiration rate in the 0-10 cm soil layer of adjacent native forest (NF),

53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-

T), and second rotation windrow (2R-W) at the Yarraman site, subtropical Australia. . 80

Fig. 5.4: Average well colour development (AWCD) over the 96 h incubation period of

BiologTM GN plates inoculated with soil extracts from the 0-10 cm soil layer of the




Fig. 5.5: Principal component analysis (PCA) of the normalized absorbance data of the 95 C-

sources from the BiologTM profiles of the soil extracts from the 0-10 cm soil layer of the

adjacent native forest (NF) (numbers 16-20), 53 y-old first rotation hoop pine plantation

(1R) (numbers 11-15), 5 y-old second rotation tree row (2R-T) (numbers 1-5), and

second rotation windrow (2R-W) (numbers 6-10), at incubation time of 72 h. ............. 82

Fig. 5.6: Non-metric multidimensional scaling (NMS) ordination plot of the normalized

absorbance data of the 95 C-sources from the BiologTM profiles of the soil extracts from

the 0-10 cm soil layer of the adjacent native forest (NF) (numbers 16-20), 53 y-old first

rotation hoop pine plantation (1R) (numbers 11-15), 5 y-old second rotation tree row

xxiii

(2R-T) (numbers 1-5), and second rotation windrow (2R-W) (numbers 6-10), at

incubation time of 72 h. .................................................................................................. 83

Fig. 5.7: Cluster analysis of BiologTM profiles of the soil extracts from the 0-10 cm soil layer

of the adjacent native forest (NF) (numbers 16-20), 53 y-old first rotation hoop pine

plantation (1R) (numbers 11-15), 5 y-old second rotation tree row (2R-T) (numbers 1-5),

and second rotation windrow (2R-W) (numbers 6-10), at incubation time of 72 h. Scale

indicates Bray-Curtis distance with graphical representations based on complete linkage

for the hierarchical clustering. ........................................................................................ 83

Fig. 5.8: Principal component analysis (PCA) of the normalized absorbance data of the 12 C-

sources from the MicroRespTM profiles of the 0-10 cm soil layer of the adjacent native

forest (NF) (numbers 16-20), 53 y-old first rotation hoop pine plantation (1R) (numbers

11-15), 5 y-old second rotation tree row (2R-T) (numbers 1-5), and second rotation

windrow (2R-W) (numbers 6-10), at incubation time of 6 h. ......................................... 87

Fig 5.9: Non-metric multidimensional scaling (NMS) ordination plot of the normalized

absorbance data of the 12 C-sources from the MicroRespTM profiles of the 0-10 cm soil

layer of the adjacent native forest (NF) (numbers 16-20), 53 y-old first rotation hoop

pine plantation (1R) (numbers 11-15), 5 y-old second rotation tree row (2R-T) (numbers

1-5), and second rotation windrow (2R-W) (numbers 6-10), at incubation time of 6 h..87

Fig 5.10: Cluster analysis of MicroRespTM profiles of the 0-10 cm soil layer of the adjacent

native forest (NF) (numbers 16-20), 53 y-old first rotation hoop pine plantation (1R)

(numbers 11-15), 5 y-old second rotation tree row (2R-T) (numbers 1-5), and second

rotation windrow (2R-W) (numbers 6-10), at incubation time of 6 h. Scale indicates

Bray-Curtis distance with graphical representations based on complete linkage for the

hierarchical clustering..................................................................................................... 88

Fig. 6.1: Picture of in-situ incubation cores. ........................................................................... 98

Fig. 6.2: Total rainfall within each 28 d sampling cycle within the sampling period.......... 102

Fig. 6.3: Minimum and maximum daily temperatures within the sampling period............. 103

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Fig. 6.4: Soil moisture content in adjacent native forest (NF), first rotation hoop pine

plantation (1R), second rotation tree row (2R-T), and second rotation windrow (2R-W)

for the sampling period. ................................................................................................ 103

Fig. 6.5: Ammonium dynamics in adjacent native forest (NF), first rotation hoop pine

plantation (1R), second rotation tree row (2R-T) and second rotation windrow (2R-W)


Fig. 6.6: Nitrate dynamics in adjacent native forest (NF), first rotation hoop pine plantation

(1R), second rotation tree row (2R-T), and second rotation windrow (2R-W) for the

sampling period. ........................................................................................................... 106

Fig. 6.7: Net nitrogen (N) mineralisation dynamics in adjacent native forest (NF), first

rotation hoop pine plantation (1R), second rotation tree row (2R-T), and second rotation

windrow (2R-W) for the sampling period. ................................................................... 108

Fig. 6.8: Net nitrification dynamics in adjacent native forest (NF), first rotation hoop pine



Fig. 6.9: Cumulative N mineralisation in adjacent native forest (NF), first rotation hoop pine



Fig. 6.10: Cumulative nitrification in adjacent native forest (NF), first rotation hoop pine



Fig. 6.11: Soil microbial biomass carbon (MBC) and (MBN), and microbial biomass

carbon:microbial biomass nitrogen (MBC:MBN) ratios, determined in summer and

winter in adjacent native forest (NF), first rotation hoop pine plantation (1R), second

rotation tree row (2R-T), and second rotation windrow (2R-W).................................. 112

Chapter 1 1

Chapter 1

Introduction The Australian forest industry is currently experiencing a growth in demand for its products in

both the domestic and export markets. Increasing social awareness of the need for biodiversity

conservation and sustainable resource management has limited the ability of the forestry industry to

expand the forest estate (Burger and Kelting, 1999; Doran and Zeiss, 2000). As a result, the Australian

forest industry has become increasingly reliant on existing single-species plantations to meet demand.

This essentially means that the longevity of the Australian forest industry depends largely on the

ability of the current soil resource to provide for and support forestry operations into the future.

Maintenance of soil health is vital if this is to occur (Doran and Zeiss, 2000; Herrick, 2000). An

essential component in maintaining soil quality and sustaining productivity is the conservation of soil

fertility. In order to devise and implement management strategies that will do this effectively a sound

understanding of how ecosystems function in their natural state (i.e. the physical, chemical,

biochemical, and biological processes involved in soil nutrient cycling), and the factors that influence

ecosystem function is required.

1.1 Hoop pine plantations

In Queensland, the forest industry has made a significant contribution to the state’s economy

since European settlement in the early 1800’s (QDPI&F, 2006). Of the 56 million hectares that is the

Queensland forest estate, approximately 0.4% (216, 500 hectares) is devoted to exotic pine and native

species plantations, which supply a large proportion of the timber inputs for the Queensland forest

industry. The plantation estate is dominated by softwood species including slash (Pinus elliottii var.

elliottii) and Caribbean (Pinus caribaea var hondurensis) pine, slash and Caribbean hybrids, and the

native species, hoop pine (Araucaria cunninghamii) (QDPI&F, 2006).

Hoop pine is a nitrogen (N) demanding native rainforest species, with its natural range

extending between northern New South Wales and Papua New Guinea (Holzworth, 1999, 2000; Xu et

Chapter 1 2

al., 2002). It was originally selectively logged from native forests by early settlers for use in

construction and as furniture timber (Webb and Tracey, 1967). The first hoop pine plantations were

established in the 1920’s in the fertile soils of the Mary and Brisbane Valleys of south-east Queensland

(Holzworth, 1999). Hoop pine plantations currently account for approximately one quarter of the

Queensland plantation estate (approximately 50,000 ha). Around 90% of the plantations are situated in

the Mary and Brisbane Valleys of south-east Queensland, with the remaining 10% in central and north

Queensland (QDPI&F, 2006). The majority of the plantations were established on land that was

previously native forest. Despite its high demand for N, hoop pine is prized for its high quality, knot

free timber and drought tolerance and is one of the few examples of a native species successfully

grown in commercial plantations. Today, hoop pine plantations form the basis of the Australian

plywood industry (Holzworth, 2000; QDPI&F, 2006).

Ensuring the long-term productivity of the hoop pine plantations is particularly important due

to the significant economic contribution they make to the Queensland forest industry. However, no

new areas will be cleared to establish hoop pine plantation and hence their future is dependent on the

continuing productivity of the current soil resource, particularly the availability of N. Land-use change

from mixed-species native forests to single-species plantations and the conversion to subsequent

rotations is likely to alter soil chemical, physical and biological properties. Such alterations may have

important implications for the soil nutrient dynamics and hence the long-term health or productivity of

the soil resource.

1.2 Soil nitrogen dynamics in forest ecosystems

Nitrogen is an essential element for plant growth and its cycling and availability is particularly

important in soils supporting hoop pine (Carlyle, 1986; Xu et al., 2002). Up to 90% of the N in all

forest soils is organically bound. Although some tree species are capable of the direct uptake of soluble

organic forms of N from the soil (e.g. Näsholm et al., 1998), the majority of a tree’s N requirement is

Chapter 1 3

obtained from inorganic forms of N (Carlyle, 1986). The long-term fertility of the soil resource

therefore relies on mineralisation of organic forms of N and the continued recycling of N through the

forest ecosystem.

Forest soil N cycling has been discussed in detail by a number of authors, including Carlyle

(1986), Attiwill and Leeper (1987), Attiwill and Adams (1993) and Hart et al. (1994a). The major

pools and processes involved in soil N cycling that are considered in this study are outlined in Fig. 1.1.

Important soil N pools include soil mineral N (NH4+-N and NO3

--N), soluble organic N (SON), and

other recalcitrant organic N pools that are associated with organic matter. The major processes

through which soil N is transformed are decomposition, mineralisation, immobilisation, and

nitrification. The soil N cycle is regulated by complex interactions between plants, soil organisms, soil

physical and chemical properties and climate conditions, which can be affected by land-use change

and management (Parfitt et al., 2003; Raynaud et al., 2006).

Tree species and tree species diversity can influence: nutrient uptake; the quality and quantity

of above and belowground organic matter input; root activity; soil microbial community size, activity

and composition; plant-microbe specific interactions; and microclimate (Grayston et al., 1997; Priha

and Smolander, 1997; Li et al., 2004; Landi et al., 2006). Changes in these factors can in turn alter soil

N dynamics. For example, compared to leaf litter from hardwoods, conifer needles have a greater

concentration of recalcitrant compounds (e.g. phenolic compounds) and are therefore more resistant to

decomposition (Priha and Smolander, 1997; Li et al., 2004). The difference in organic matter quality

between conifers and hardwoods has, in some cases, been found to influence the size of the soil

microbial biomass, which may in turn impact soil N cycling (Zhong and Makeschin, 2006; Priha et al.,

2001).

In forests of the same species, litterfall, root activity and nutrient uptake can be influenced by

stand age and development, which has ensuing affects on soil N dynamics. For example, comparison

of soil nitrogen and litterfall dynamics across a chronosequence of first rotation hoop pine plantation

Chapter 1 4

soils indicated that there is considerably less litterfall and less N recycled through the litterfall in

young stands compared to mature stands (Bubb et al., 1998b). Furthermore, the rate of N

mineralization, and N uptake tended to increase with stand maturity (Bubb et al., 1998a).

Disturbance associated with the harvesting and subsequent establishment of forest stands

impacts the soil N cycle through alterations to soil physical, chemical and biological properties

including soil organic matter availability and distribution as well as microclimate (Chen et al., 2000;

Mao et al., 2002). Forest harvesting is often followed by a temporary increase in N transformations

and availability (Smethurst and Nambiar, 1990; Li et al., 2003). This is likely to be a result of the

stimulation of microbially mediated N mineralisation processes by soil aeration, mixing of forest floor

material into surface soil, and higher soil temperatures resulting from loss of canopy cover (Carlyle,

1986; Frazer et al. 1990; Li et al., 2003; Grenon et al. 2004).

Residue management controls the quantity of substrate and nutrients available for leaching and

decomposition by soil organisms (Blumfield and Xu, 2003, Chen and Xu, 2005). It has also been

found to influence the quality of soil organic matter (Mathers and Xu, 2003a,b). Furthermore, it also

impacts the spatial distribution of soil nutrient resources and may influence soil moisture and

temperature conditions and therefore the size, activity and distribution of the soil microbial community

(Chen and Xu, 2005).

Environmental conditions also influence soil N dynamics. Soil moisture and temperature affect

the size and activity of the microbial community and hence the rate of N transformation processes and

the availability of N. The frequency of drying and rewetting has been found to have a significant

influence on the soil N dynamics (Pulleman and Tietema, 1999; Fierer and Schimel, 2002; Miller et

al., 2005). Loss of N from the soil system via leaching, denitrification and volatilization is also

regulated by environmental conditions (Carlyle, 1986; Stevenson and Cole, 1999).

Fi

g 1.

1: S

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Chapter 1 6

1.3 Research Program

Soil N dynamics in forest ecosystems have been widely and intensively

studied. A significant proportion of this research has been undertaken in temperate

and boreal forest ecosystems of the northern hemisphere. The different climatic

conditions as well as the high input of N from anthropogenic sources in the

aforementioned forest ecosystems, mean that the results from such studies may not be

applied with certainty to soil N cycling in subtropical forest ecosystems.

The importance of N availability in soils of the subtropical, N demanding

species hoop pine, has led to a number of investigations into soil N dynamics in hoop

pine plantations. The influence of the age and development of first rotation (1R) hoop

pine plantation on litterfall and soil nutrient dynamics was investigated by Bubb et al.

(1998a,b). Pu et al., (2001, 2002, 2005) examined the affect of residue management

in young second rotation (2R) hoop pine plantations on losses of soil N. Other studies

have assessed the impact of residue management in young 2R hoop pine plantations

on soil organic matter quality, (Mathers et al., 2003b) and N transformations and

availability (Blumfield and Xu, 2003; Blumfield et al., 2004). The effects of

harvesting and compaction on soil N dynamics in the inter-rotation period were also

investigated (Blumfield et al., 2005).

Previous studies comparing adjacent native forest (NF), 1R and 2R hoop pine

plantations indicate that the land-use change from NF to 1R caused a reduction in

organic matter quality and quantity (Chen et al., 2004). The land-use change was also

associated with reductions in the size and diversity of the soil microbial biomass

(Chen et al., 2004; He 2004; He et al., 2005). As organic matter input and the soil

microbial community influence soil N dynamics, the land-use change may have also

had an impact on soil N transformations and availability.

Chapter 1 7

To date, the impact of the initial land-use change from NF to 1R hoop pine

plantations on soil N dynamics has not been investigated. Furthermore, soil N

dynamics in the 1R and 2R plantations have not been compared. Knowledge of soil N

dynamics across this sequence of land-use changes will enable us to determine

whether or not the land-use changes have had a significant impact on N losses or

availability and hence the long-term productivity of the soil resource. This

information can help to determine whether or not the hoop pine industry is sustainable

under the current conditions. The focus of this study was to examine the influence of

land-use change and residue management on soil N dynamics and associated

chemical, biochemical and biological pools and processes.

1.3.1 Hypotheses

This research program examined the impact of the land-use change from a

mixed-species NF to a single-species 1R hoop pine plantation and subsequent 2R

plantation and associated residue management practices on soil N dynamics. It was

based on the following hypotheses:

1) Land-use change from the mixed-species NF to the 1R hoop pine

plantation altered plant species diversity and caused disturbance to the soil

system. These changes are expected to have a significant effect on the

chemical, biochemical, and biological processes involved in soil N

dynamics, resulting in differences in soil N transformations and

availability between the two forest ecosystems.

2) The conversion of 1R hoop pine plantation to 2R hoop pine plantation

disturbs the soil system and changes the quantity (and quality) of organic

matter input to the soil system. This is expected to alter the chemical,

biochemical, and biological processes involved in soil N dynamics,

Chapter 1 8

resulting in differences in soil N transformations and availability between

the two plantation forest ecosystems.

3) Residue management alters the quantity (and quality) of organic matter

and physical cover on the soil surface, thereby affecting substrate

availability and soil microclimate conditions. As such, residue

management is expected to have a significant influence on the chemical,

biochemical, and biological processes involved in soil N dynamics. This

may result in differences in soil N transformations and availability

between tree rows (2R-T) and windrows (2R-W) of the second rotation

hoop pine plantation.

The key factors associated with land-use change and residue management that

were considered to influence soil N dynamics were: alteration of tree species

diversity, disturbance to the soil system, and differences in substrate quantity. These

factors are outlined in Fig. 1.2.

1.3.2 Objectives

The main objectives of the research program were to quantify the effects of the land-

use change from NF to 1R hoop pine plantation and subsequent 2R hoop pine

plantation, as well as residue management on:

i) mineral N pools and transformations as well as indicators of organic

matter quality (Chapter 3).

ii) soil SON pools through the soil profile (0-10, 10-20 and 20-30 cm layers)

using a variety of extraction methods (Chapter 4).

iii) the size, activity and composition of the soil microbial community

(Chapter 5).

iv) seasonal trends of N cycling and availability (Chapter 6).

Fig.

1.2

: C

once

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l mod

el o

f th

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y fa

ctor

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fluen

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l N d

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oop

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t dev

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t ef

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s on

root

s an

d lit

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as w

ell a

s nu

trien

t upt

ake

soil

mic

robi

al c

omm

unity

Pop

ulat

ion,

act

ivity

, div

ersi

ty /c

ompo

sitio

n

soil

N tr

ansf

orm

atio

ns a

ndav

aila

bilit

y

Land

-use

cha

nge

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due

man

agem

ent

•di

ffere

nces

in

subs

trate

qua

ntity

(a

nd q

ualit

y)•

diffe

renc

es in

m

icro

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ate

resi

due

man

agem

ent

•di

ffere

nces

in

subs

trate

qua

ntity

(a

nd q

ualit

y)•

diffe

renc

es in

m

icro

clim

ate

nativ

e fo

rest

1R h

oop

pine

pl

anta

tion

2R h

oop

pine

pl

anta

tion

plan

t spe

cies

•al

tera

tions

in p

lant

roo

t /

mic

robe

inte

ract

ions

•su

bstra

te q

ualit

y an

d qu

antit

y ar

e al

tere

d vi

a ch

ange

s in

ab

ove

(litte

r) a

nd b

elow

gro

und

(root

s an

d ro

ot e

xuda

tes)

or

gani

c m

atte

r inp

ut•

nutri

ent u

ptak

e•

mic

rocl

imat

e –

shor

t and

long

te

rm d

iffer

ence

s in

can

opy

and

litte

r cov

er

plan

t spe

cies

•al

tera

tions

in p

lant

roo

t /

mic

robe

inte

ract

ions

•su

bstra

te q

ualit

y an

d qu

antit

y ar

e al

tere

d vi

a ch

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s in

ab

ove

(litte

r) a

nd b

elow

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(root

s an

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xuda

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or

gani

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t ef

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s on

root

s an

d lit

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as w

ell a

s nu

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trat

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antit

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utrie

nts

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s in

mic

rocl

imat

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plan

t dev

elop

men

t ef

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s on

root

s an

d lit

ter

as w

ell a

s nu

trien

t upt

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soil

mic

robi

al c

omm

unity

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ulat

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act

ivity

, div

ersi

ty /c

ompo

sitio

n

soil

N tr

ansf

orm

atio

ns a

ndav

aila

bilit

y

Land

-use

cha

nge

resi

due

man

agem

ent

•di

ffere

nces

in

subs

trate

qua

ntity

(a

nd q

ualit

y)•

diffe

renc

es in

m

icro

clim

ate

resi

due

man

agem

ent

•di

ffere

nces

in

subs

trate

qua

ntity

(a

nd q

ualit

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diffe

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es in

m

icro

clim

ate

Chapter 2 10

Chapter 2

Materials and Methods

2.1 Materials

2.1.1 Study site

The study site is located in Yarraman State Forest, southeast Queensland,

Australia (26° 52’ S, 151° 51’ E) (Fig. 2.1). The altitude is 620 m and annual rainfall

at the site ranges between 433 and 1110 mm, with an average of 816 mm. On

average, winter temperatures range from 4 to 20 ºC, and summer temperatures from

17 to 29 ºC. The soil is a freely draining, Snuffy (Acidic) Mesotrophic Red Ferrosol

(Isbell, 1996), equating to a Typic Durustalf (Soil Survey Staff, 1999), with a clayey

texture (Chen et al., 2004). The experimental area incorporated adjacent native forest

(NF), first rotation (1R) hoop pine plantation, and second rotation (2R) hoop pine

plantation in Pocket Logging Area of State Forest 289 Yarraman (Fig. 2.2). The slope

was approximately 2°.

The NF site is classified as a mixed rainforest/scrub and is dominated by

bunya pine (Araucaria bidwilli Hook.), yellowwood (Terminalia oblongata F. Muell.

Suubsp. Oblongata), crows ash (Pentaceras australis R.B) and lignum-vitae (Premna

lignum-vitae), with emergent hoop pine (Araucaria cunninghamii). Prior to the

establishment of the first rotation hoop pine plantation, merchantable timber (i.e. hoop

and bunya pine, lignum-vitae, yellowwood and crows ash) were harvested from the

native forest using bullock teams and a small dozer. The understorey scrub was then

brushed and burnt. Strips of native forest up to 120 m wide were retained as fire

breaks and to act as wildlife corridors through the plantation. The first rotation of

hoop pine plantation was established at the 1R and 2R plantation sites in 1952 at

approximately 1400 stems ha-1, but was later thinned to a final stocking rate of

Chapter 2 11

approximately 391 stems ha-1. The first rotation of hoop pine at the 2R site was

clearfall harvested in 1999 using a D4 dozer with a stick-rake blade. Post harvest

residues were formed into windrows approximately 6 m apart, using a D6 bulldozer

with shear blade. The areas between windrows were cultivated using a New Holland

9030 wheel tractor and Savannah TP3 plough and used as tree-planting rows for the

2R hoop pine plantation. The 2R plantation was established in November 2000 at

approximately 620 stems ha-1.

The three adjacent sites used for this study were located on the same position

of the slope, had the same vegetative cover prior to the establishment of hoop pine

plantations, and the soils were developed from the same basaltic parent material. As

such, differences in soil N transformations among the sites are assumed to be the

result of the land-use change and site management practices. Differences in soil N

dynamics between the NF and the 1R soils may reflect the impact of the shift in tree

species, the ensuing difference in the quality of organic matter input and the soil

microbial community, the effect of disturbance during 1R establishment and

subsequent silvicultural practices, and changes in microclimate. Differences in soil N

transformations and availability between the 1R and 2R hoop pine plantations may

reflect the short- term impact of stand development, harvesting and site preparation

on: organic matter quantity (and quality); the soil microbial community; and soil

microclimate. Finally, differences in soil N dynamics between the 2R-T and 2R-W

may reflect the impact of residue management on the quantity (and quality) of organic

matter, the soil microbial community, and soil microclimate.

Chapter 2 12

Fig. 2.1: Map of Queensland showing areas of forestry reserve and the location of Yarraman State

Forest (inset). (Source: Paul Keay, Forestry Plantations Queensland).

Chapter 2 13

Fig. 2.2: Location of adjacent native forest (NF), first rotation hoop pine plantation (1R), and second

rotation hoop pine plantation (2R) (Experiment 2407 YMN) within Pocket Logging Area 289 of

Yarraman State Forest in subtropical Australia. (Source: Paul Keay, Forestry Plantations Queensland).

Chapter 2 14

2.1.2 Experimental design

Experimental sites measuring 0.2 ha in area were located in adjacent NF, 1R

hoop pine plantation and 2R hoop pine plantation (Fig 2.2). The 2R plantation

experimental area was divided into two treatments based on the residue management

practices. These were: 1) tree planting row (2R-T), and 2) windrow of harvest

residues (2R-W) (Fig. 2.3). A buffer area of at least 50 m was left between

experimental areas to avoid edge effects. Each of the four treatments (NF, 1R, 2R-T

and 2R-W), had five 24 m2 (12 m x 2 m) replicate plots. A projected ANOVA was

conducted on data previously collected from this study site to ensure that the number

of field replicates would achieve the appropriate degrees of freedom (minimum of 12,

personal comment Associate Professor Janet Chaseling) for statistical analysis.

Studies on the impact of land-use change on gross N transformations (Chapter 3),

soluble organic nitrogen pools (Chapter 4) and the soil microbial community size and

composition (Chapter 5), were conducted on soils collected from this site in July

2005. The field study of seasonal soil N dynamics in adjacent NF, 1R and 2R hoop

pine plantation was carried out at this field site between August 2002 and January

2004.

It is understood that a limitation of this experimental design is the fact that

replicates of forest type are not randomly located and hence forest type is confounded

by location and is therefore pseudo-replicated (Hurlbert, 1984). As such, caution

must be exercised when extrapolating conclusions to sites other than this one. It

should be noted, however, that this design is common in forest soil research (e.g.

Luizao et al., 1992; Chen et al., 2003a; Idol et al., 2003; Chen et al., 2004).

Chapter 2 15

a

b

Fig. 2.3: Photograph of the first rotation (1R) hoop pine plantation (a), and the second rotation (2R)

hoop pine plantation showing the second rotation tree-rows (2R-T), and second rotation windrows (2R-

W), with the adjacent native forest (NF) in the background (b). Both photographs were taken at the

Yarraman study site in August 2002.

2R-W2R-T

NF

Chapter 2 16

2.2 Methods

2.2.1 Treatment of samples

Soil samples

All soil samples (from both field and laboratory experiments) were well mixed

and sieved (< 2 mm) with fine roots and organic matter removed. Samples were then

separated into two sub-samples that were: 1) air-dried; and 2) fresh. The air-dried

samples were finely ground (< 150 μm) and stored at room temperature prior to

analysis of soil total carbon (C), carbon isotope composition (δ13C), total N and 15N

natural abundance (δ15N). Fresh samples were stored at 4 ºC prior to chemical,

biochemical and biological analyses.

Root samples

The roots removed from the 0-10 cm soil layer in samples collected from the

NF and 1R site for the laboratory components of this thesis (Chapters 3, 4 and 5),

were washed and oven-dried at 70 ºC. They were then finely ground for analysis of

total C, carbon isotope composition (δ13C), total N and 15N natural abundance (δ15N).

Forest floor material

In July 2005, litter (L) layer and fermentation (F) layer samples were collected

from the plots at the NF and 1R sites using a 0.25 m2 steel quadrat. Five samples

were taken from each plot and bulked together. A sub-sample was oven-dried at 70ºC

and finely ground for analysis of total C, carbon isotope composition (δ13C), total N

and 15N natural abundance (δ15N). A humus layer was not clearly distinguished in

either the native forest or plantation forests.

Chapter 2 17

2.2.2 Soil analyses

Cation exchange capacity, soil texture and pH

Analysis of soil cation exchange capacity (CEC), bulk density and particle size

distribution was conducted by the Queensland Forestry Research Institute (QFRI)

laboratory using methods described by Hesse (1971) and Kalra and Manyard (1991)

for CEC and PSA respectively. Soil pH was determined in the Griffith University

Forest Soils laboratory using a 1:2.5 (v/v) soil:H2O extract according to the method

described by Rayment and Higginson (1992). These basic properties are listed in

Table 2.1.

Soil moisture

At the time of each sampling a sub-sample of soil was pre-weighed, then dried

at 105 ˚C for 48 h. It was then weighed a second time and soil moisture was

determined.

Total C and N

Soil, root and litter total C and total N, as well as carbon isotope composition

(δ13C) and 15N natural abundance (δ15N) were analysed using an isotope ratio mass

spectrometer with a Eurovector Elemental Analyser (Isoprime-EuroEA 3000, Milan,

Italy) (Fig 2.4).

Chapter 2 18

Table 2.1: Basic soil physical properties in adjacent native forest (NF), first rotation hoop

pine plantation (1R), second rotation tree row (2R-T) and second rotation windrow (2R-W) at

the Yarraman site, subtropical Australia.

Bulk density

pH CEC Sand Silt Clay Forest type

(g cm-3) (1:2.5 H2O) (c mol kg-1) g kg-1

0-10 cm

NF 0.61 6.2 56.9 327 189 484 1R 0.65 6.6 50.9 334 306 360 2R-T 0.88 6 38 284 265 400 2R-W 0.86 6.2 36.5 290 305 450

10-20 cm

NF 0.86 5.9 48 352 315 333 1R 0.93 6.3 48.4 251 356 393 2R-T 0.84 6.4 2R-W 0.99 5.8

33.7

276

243

481

20-30 cm (20-40 cm for all except pH)

NF 1.03 5.8 34.6 209 220 571 1R 1.14 6.2 35.2 183 226 592 2R-T 1.04 5.5 2R-W 0.94 5.2

29.6

275

152

573

Note: Separate samples were not taken from the 2R-T and 2R-W plots for analysis of cation exchange

capacity (CEC) and particle size analysis (i.e. sand, silt and clay) in the 10-20 and 20-30 cm layers.

Fig. 2.4: Eurovector Elemental Analyser (Isoprime-EuroEA 3000, Milan, Italy).

Chapter 2 19

Mineral N

Inorganic N was extracted from soil samples by mixing 5 g (dry weight

equivalent) of field moist soil with 50 ml of 2 M KCl, shaking on an end–to–end

shaker for 1 h and filtering through a Whatman 42 paper. For each batch of 2 M KCl

used to extract mineral N from the soil samples, three blank samples were collected,

shaken and filtered. The concentrations of NH4+-N and NO3

--N in the extracts and

blanks were determined using a LACHAT Quickchem Automated Ion Analyser (Fig.

2.5 – photo of FIA). Mean mineral N in the blanks was subtracted from the sample

values to determine the actual concentration of NH4+-N and NO3

—N in the samples.

The concentrations of NO2- -N at the study site were below the detection limit and

therefore no values are reported.

Fig. 2.5: The LACHAT Quickchem Automated Ion Analyser used for analysis of mineral N.

Microbial biomass C and N

Microbial biomass C and N were measured using the fumigation-extraction

method described by Vance et al. (1987). In brief, fumigated and non-fumigated soils

(10 g dry weight equivalent) were extracted with 40 ml of 0.5 M K2SO4

Chapter 2 20

(soil:extractant ratio 1:4). Samples were shaken for 30 min, and filtered through a

Whatman 42 filter paper and frozen until further analysis could be conducted.

Soluble organic C and total N in the fumigated and non-fumigated samples were

determined using a SHIMADZU TOC-VCPH/CPN analyser (fitted with TN unit) (Fig.

2.6). Microbial biomass C (MBC) and microbial biomass N (MBN), were calculated

using a conversion factor for C (Ec) of 2.64 (Vance et al., 1987), and for N (En) of

2.22 (Brookes et al., 1985; Jenkinson, 1988) (see equations 2.1 and 2.1).

Fig. 2.6: SHIMADZU TOC-VCPH/CPN analyser (fitted with TN unit)

MBC = TOC (μg g-1) x Ec (2.1)

where:

MBC = microbial biomass carbon (μg g-1)

TOC = total organic carbon (μg g-1)

MBN = TON (μg g-1) x En (2.2)

where:

MBC = microbial biomass carbon (μg g-1)

TOC = total organic carbon (μg g-1)

Chapter 3 21

Chapter 3

Gross nitrogen transformations in adjacent native and plantation

forests of subtropical Australia

3.1 Introduction

As a result of growing demands for forest products and a reduced forest land

base, the Australian forestry industry is becoming increasingly reliant on single tree

species plantations to meet its timber needs. At present in Queensland, Australia,

about 216, 500 hectares are devoted to both exotic pine and native species plantations

which supply a large proportion of the timber inputs for the Queensland forestry

industry (QDPI&F, 2006). In order to maintain the long-term productivity of these

forest soils, and hence a sustainable forestry industry, it is essential to understand the

impact of land-use change from native forest to forest plantations on soil nutrient

cycling.

Nitrogen (N) is an essential element for plant growth and N deficiency

frequently limits forest productivity (Binkley and Hart, 1989; Paul and Clark, 1996;

Reich et al., 1997). Soil N transformations are microbially mediated processes, which

are influenced by a number of factors, including composition and diversity of the soil

microbial community, substrate quality and quantity, and environmental conditions

(Stevenson and Cole, 1999; Compton and Boone, 2002; Templer et al., 2003; Grenon

et al., 2004). These factors are likely to be influenced by land-use change. For

instance, land-use change from native forest to plantation forest results in a shift in

plant species, which directly influences the quality and quantity of organic matter input

from both plant residues and root exudates. This in turn may lead to changes in soil

microbial communities, which subsequently influence soil N transformations (Van

Miegroet and Cole, 1988; Verchot et al., 2001; Ross et al., 2004; Patra et al., 2006;

Ste-Marie and Houle, 2006). Land-use change also causes disturbance to the soil

Chapter 3 22

ecosystem through harvesting and site preparation, which may have an impact on soil

microbial communities and subsequently N availability and long-term site productivity

(Cole, 1995; McMurtrie and Dewar, 1997; O'Connell et al., 2004; Tan et al., 2005).

Finally, environmental conditions such as temperature and moisture also influence soil

N transformations, particularly losses of N from the soil through leaching or

denitrification.

To date, a large proportion of research into soil N dynamics has been

conducted in the northern hemisphere, where N deposition is an issue affecting soil N

transformations and the climate is quite different from that in south-east Queensland,

Australia (Ross et al., 2004; Ste-Marie and Houle, 2006). Hence, there is a paucity of

information relating to gross N transformations in subtropical forest soils.

Furthermore, the effect of land-use change from native forest to plantation forest and

subsequent rotations on soil N transformations in subtropical zones has not been well

studied.

Hoop pine (Araucaria cunninghamii) is an N demanding native rainforest

species of south-east Queensland. At present, hoop pine plantations account for

approximately one quarter of Queensland’s plantation area (50,000 ha) and most of the

current plantations were established on land which was previously native forest. The

objective of this study was to examine the impact of land-use change from native

forest (NF) to first rotation (1R) hoop pine plantation and subsequent second rotation

(2R) hoop pine plantation and associated residue management strategy on soil N

transformations in subtropical Australia.

Chapter 3 23

3.2 Materials and Methods

3.2.1 Sample collection

In July 2005, fifteen soil cores (0-10 cm) were randomly collected from each of

the five 24 m2 plots within the NF, 1R, 2R tree row (2R-T) and 2R windrow (2R-W)

forests, using a 7.5 cm diameter auger and bulked. Replicate samples of the litter (L)

layer and fermentation (F) layer were collected from the plots at the NF and 1R sites as

described in Chapter 2.

All samples were transported to the laboratory where field moist soils were

well mixed and sieved (< 2 mm), and visible roots were removed. One sub-sample of

each soil was taken for air-drying and processed for the analysis of total C, carbon

isotope composition (δ13C), total N and 15N natural abundance (δ15N) as described in

Chapter 2. A second was stored at 4 °C until the 15N isotope dilution study was

conducted approximately 12 weeks later. . Roots, separated from soil during sieving,

L-layer and F-layer samples were prepared for analysis of total C and N, as well as

carbon isotope composition (δ13C) and 15N natural abundance (δ15N) as described in

Chapter 2.

3.2.2 Aerobic and anaerobic incubations

Gross and net ammonification, nitrification and ammonium and nitrate

consumption rates were determined in a 3 d aerobic incubation using the 15N pool

dilution method (Hart et al., 1994b). Traditionally, anaerobic incubations have been

used as an index of N mineralisation and availability (Keeney, 1982). They are also

useful in terms of understanding N transformation processes which may occur in soils

which are subjected to anaerobic conditions during periods of rainfall as well as

predicting N transformations which may occur in anaerobic micro-sites within the soil.

Chapter 3 24

As such, anaerobic incubations were also conducted using the 15N pool dilution

method to determine gross and net mineralisation and ammonium consumption rates.

Prior to the aerobic incubation, six portions of the field moist soils (5 g dry

weight equivalent) were weighed into 50 ml propylene falcon tubes. The soil moisture

was then adjusted to 45% of the water holding capacity and samples were conditioned

at 25 °C for 24 h in a humid environment to ensure that they would not dry out. After

conditioning, two soil samples were labelled with 600 μl of either (15NH4)2SO4

solution (4.76 μg N; ca. 98 atom % 15N excess), or K15NO3 solution (15 μg N; ca. 99

atom % 15N excess), which were applied evenly to the samples. An equivalent volume

of distilled water was applied to another two soil samples, to be used as the control.

Average soil moisture content of all samples after this addition was approximately

65% of the water holding capacity. Tubes were then capped and placed into the

incubator at 25 °C. After 3 h, as suggested in Murphy et al. (2003), the time zero (T0)

samples were removed from the incubator and extracted with 50 ml of 2 M KCl.

Samples were shaken for 1 h, centrifuged at 2000 rpm for 10 min and then filtered

through Whatman No. 42 filter paper and frozen until analysis. The remaining

samples (T1) were removed from the incubator after 72 h and extracted as above.

For the anaerobic incubation, four portions of field moist soils were prepared

and conditioned as above. After conditioning, two soil samples were labelled with 25

ml of (15NH4)2SO4 solution (4.76 μg N; ca. 98 atom % 15N excess). The equivalent

volume of distilled water was added to another two samples of fresh soil, to be used as

the control. Tubes were shaken gently for 3 min and then placed into the incubator at

25 °C. After 3 h, the T0 samples were removed from the incubator and extracted with

25 ml of 4 M KCl, so that the final ratio of soil:extract as well as the concentration of

the KCl extract was equivalent to that used for the aerobic incubation. Samples were

shaken for 1 h, centrifuged at 2000 rpm for 10 min and then filtered through Whatman

Chapter 3 25

No. 42 filter paper and frozen until further analysis could take place. The T1 samples

were removed from the incubator after 72 h and extracted as above.

3.2.3 Steam distillation and chemical analysis

Mineral N (NH4+-N and NO3

--N) concentrations in the extracts were

determined using the LACHAT Quickchem Automated Ion Analyser described in

Chapter 2 (QuikChem Method 10-107-06-04-D for NH4+-N and QuikChem Method

12-107-04-1-B for NO3--N). Samples were prepared for 15N analysis using steam

distillation (Keeney and Nelson, 1982). In brief, each sample was spiked with a

known NH4+ and NO3

- standard to provide sufficient total N for analysis. A 10 ml

aliquot of 3.5% NaOH was then added to convert the NH4+ in the sample to NH3 gas,

and the sample was steam distilled using a Velp semi-automatic distillation unit (Fig.

3.1). The NH3 gas was collected in 10 ml of 2% HCl. Subsequently, 0.2 mg of

Devarda’s alloy was added to reduce the NO3- to NH4

+ and the sample was redistilled

with the NO3- collected in the form of NH3 in 10 ml of 2% HCl. Distillates were dried

down to a powder at 50 °C, and isotope ratio analyses were performed using the

isotope ratio mass spectrometer with a Eurovector elemental analyser (Isoprime-

EuroEA 3000) described in Chapter 2.

Fig 3.1: Velp distillation unit

Chapter 3 26

3.2.4 Calculations and statistical analysis

Rates of N mineralisation and ammonium consumption (for anaerobic

incubation data), and ammonification, nitrification, ammonium consumption and

nitrate consumption (for aerobic incubation data) were calculated using equations 3.1

to 3.4 (below), which were developed by Kirkham and Bartholomew (1954), and

presented in Hart et al. (1994b).

[ ] [ ] ( )[ ] [ ]( )

10

1010

44

44

loglog

TT

TTTT

NHNHAPEAPE

t

NHNHm ++

++

÷

÷×

−= (3.1)

[ ] [ ]t

NHNHmc TT

A01 44

++ −−= (3.2)

[ ] [ ] ( )[ ] [ ]( )

10

1010

33

33

loglog

TT

TTTT

NONOAPEAPE

t

NONOn −−

−−

÷

÷×

−= (3.3)

[ ] [ ]t

NONOnc TT

N01 33

−− −−= (3.4)

where:

m = gross N mineralisation / ammonification rate (mg N kg-1d-1);

cA = NH4+ consumption rate (mg N kg-1d-1);

n = gross nitrification rate (mg N kg-1d-1);

cN = NO3- consumption rate (mg N kg-1d-1);

t = time (d);

0TAPE = atom % 15N excess of NH4+ or NO3

- pool at time-0

1TAPE = atom % 15N excess of NH4+ or NO3

- pool at time-t

where APE = the atom % 15N enrichment of a N pool enriched with 15N minus

the atom % 15N enrichment of that pool prior to 15N addition;

[ ]04 TNH + or [ ]

03 TNO − = total NH4+ or NO3

- concentration (mg kg-1) at time-0 (3 h)

[ ]14 TNH + or [ ]

13 TNO − = total NH4+ or NO3

- concentration (mg kg-1) at time-t (72 h)

Chapter 3 27

One-way analysis of variance (ANOVA) was carried out for all data in Statistix

for Window version 2.2 (Analytical Software, Tallahassee, FL). Least significant

difference (LSD, P<0.05) was used to separate treatment means when differences were

significant. Paired t-tests and Pearson linear correlations were also conducted in

Statistix for Windows version 2.2.

3.3. Results

3.3.1 Soil chemical properties

Basic chemical properties of the 0-10 cm soil layer under the adjacent NF, 1R,

2R-T and 2R-W are shown in Table 3.1. Soil total C and N were significantly higher

in the NF soils than in the plantation soils. Total C was higher in the 1R soils than in

the 2R soils. Concentrations of NH4+-N were higher in the NF soils than in the

plantation soils, while the concentration of NO3--N was approximately two times

higher in the NF soils than in the plantation soils (Table 3.1). However, there was no

significant difference in NH4+-N and NO3

--N concentrations between the 1R and the

2R soils, or between the 2R-T and the 2R-W soils. The same pattern was found for the

δ15N results, whilst δ13C was higher in the 2R-T soils than in the NF soils. The C:N

ratios ranged between 11.8 in the NF soils and 13.7 in the 1R soils. The NF soils had

significantly lower C:N ratios than the plantation soils, while the 1R soils had

significantly higher C:N ratios than the 2R soils.

3.3.2 Characteristics of forest litter material and tree roots

Total C and total N contents and δ13C and δ15N values were measured on L-

and F-layer, and root samples from the NF and 1R sites (Table 3.2). Total C and δ13C

values in the L-layer were lower at the NF site compared to the 1R site. Both the F-

and L-layers at the NF site had significantly higher total N and δ15N values than those

of the 1R site. Roots at the NF site were also found to have lower total C and δ15N but

Chapter 3 28

higher total N. The C:N ratios of both the F- and L-layers were significantly lower at

the NF site than in the 1R site. Roots at the NF site also had significantly lower C:N

ratio. Soil C:N ratios were positively correlated to the C:N ratios of the L layer (r =

0.76, P<0.01), F layer (r = 0.66, P<0.01) and roots (r = 0.83, P<0.01).

Table 3.1: Soil properties (0-10 cm) for adjacent native forest (NF), 53 y-old first rotation


windrow (2R-W) at the Yarraman site, subtropical Australia. Values are means (n=5) and if

followed by the same letter are not significant at the 5% level of significance.

Forest type Total C

(%)

Total N

(%)

C:N

ratio

NH4+

(mg N kg-1)

NO3-

(mg N kg-1)

NF 8.9a 0.75a 11.8c 2.5a 98.6a

1R 7.1b 0.52b 13.7a 2.1b 43.8b

2R-T 5.8c 0.46b 12.6b 2.1b 43.1b

2R-W 6.1c 0.47b 12.9b 2.2b 58.5b

Tab

le 3

.2: B

asic

che

mic

al p

rope

rties

of l

itter

(L) a

nd fe

rmen

tatio

n (F

) lay

er o

f adj

acen

t nat

ive

fore

st (N

F) a

nd 5

3 y-

old

first

rota

tion

hoop

pin

e

plan

tatio

n (1

R) a

t the

Yar

ram

an si

te, s

ubtro

pica

l Aus

tralia

. V

alue

s are

mea

ns (n

=5) a

nd if

follo

wed

by

the

sam

e le

tter a

re n

ot si

gnifi

cant

at t

he 5

% le

vel

of si

gnifi

canc

e.

Fe

rmen

tatio

n la

yer

Litte

r lay

er

Roo

ts (0

– 1

0 cm

)

Fore

st

type

δ13C

(‰)

δ15N

(‰)

Tota

l

C

(%)

Tota

l

N

(%)

C:N

ratio

δ13C

(‰)

δ15N

(‰)

Tota

l

C

(%)

Tota

l

N

(%)

C:N

ratio

δ13C

(‰)

δ15N

(‰)

Tota

l

C

(%)

Tota

l

N

(%)

C:N

ratio

NF

-27.

4a

6.4a

37

.6a

1.7a

23

.0b

-27.

5b

5.5a

37

.9b

1.4a

27

.8b

-26.

3a

1.3b

38

.7b

1.4a

11

.8b

1R

-27.

2a

4.9b

38

.6a

1.2b

32

.1a

-26.

9a

3.2b

42

.3a

0.64

b 69

.1a

-26.

5a

2.9a

46

.0a

0.7b

13

.7a

Chapter 3 30

3.3.3 Aerobic incubation

Gross ammonification rates in the aerobic incubation ranged between 0.62 in the

1R soils and 1.78 mg N kg-1 d-1 in the 2R-T soils, whilst the rate of NH4+ consumption

ranged between 0.82 in the 1R soils and 2.12 mg N kg-1 d-1 in the 2R-T soils (Table

3.3). Both gross ammonification and NH4+ consumption were significantly lower in the

NF and the 1R soils compared to the 2R-T and the 2R-W soils. Net ammonification

rates were all negative and no significant difference was found among the treatments

(Table 3.3).

Gross nitrification rates ranged between 2.1 mg N kg-1d-1 (equivalent to 120 mg

N m-2 d-1) in the 1R soil and 6.6 mg N kg-1d-1 (equivalent to 345 mg N m-2 d-1) in the NF

soil (Fig. 3.2). A paired t-test showed that the rate of gross nitrification was

significantly higher than the rate of gross ammonification in all soils (P = 0.002) (Table

3.3, Fig. 3.2). Both net and gross nitrification rates were significantly higher in the NF

soils than in the plantation soils. However, no significant differences in the nitrification

rates were found between the 1R and the 2R plantations soils. Gross and net

nitrification rates were negatively correlated to soil C:N ratio (r = –0.66 and –0.59

respectively, P<0.01).

Tab

le 3

.3:

Gro

ss a

nd n

et N

min

eral

isat

ion,

am

mon

ifica

tion

and

NH

4+ co

nsum

ptio

n ra

tes

in th

e 0-

10 c

m s

oil l

ayer

of

adja

cent

nat

ive

fore

st (

NF)

, 53

y-ol

d fir

st

rota

tion

hoop

pin

e pl

anta

tion

(1R

), 5

y-ol

d se

cond

rot

atio

n tre

e ro

w (

2R-T

), an

d se

cond

rot

atio

n w

indr

ow (

2R-W

) at

the

Yar

ram

an s

ite, s

ubtro

pica

l A

ustra

lia.

Val

ues a

re m

eans

(n=5

) and

if fo

llow

ed b

y th

e sa

me

lette

r are

not

sign

ifica

nt a

t the

5%

leve

l of s

igni

fican

ce.

Fore

st ty

pe

Ana

erob

ic in

cuba

tion

A

erob

ic in

cuba

tion

G

ross

min

eral

isat

ion

(mg

N k

g-1 d

-1)

NH

4+

cons

umpt

ion

(mg

N k

g-1 d

-1)

Net

min

eral

isat

ion

(mg

N k

g-1 d

-1)

G

ross

amm

onifi

catio

n

(mg

N k

g-1 d

-1)

NH

4+

cons

umpt

ion

(mg

N k

g-1 d

-1)

Net

amm

onifi

catio

n

(mg

N k

g-1 d

-1)

NF

9.1a

3.

68a

5.9a

0.74

b 0.

97b

-0.2

7a

1R

3.5c

-0

.23c

3.

3bc

0.

62b

0.82

b -0

.21a

2R-T

7.

2ab

4.01

a 2.

6c

1.

78a

2.12

a -0

.20a

2R-W

6.

7b

2.32

b 4.

0b

1.

50a

1.80

a -0

.20a

Chapter 3 32

Nitr

ifica

tion

(mg

N k

g-1

d-1 )

-4

-2

0

2

4

6

8

10

NF 1R 2R-T 2R-W

Gross nitrificationNet nitrificationNitrate consumption

Nitr

ifica

tion

(mg

N k

g-1

d-1 )

-4

-2

0

2

4

6

8

10

NF 1R 2R-T 2R-W

Gross nitrificationNet nitrificationNitrate consumption

Fig. 3.2: Gross and net nitrification and NO3- consumption rates in the 0-10 cm soil layer of adjacent

native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-

T), and second rotation windrow (2R-W) at the Yarraman site, subtropical Australia.

3.3.4 Anaerobic incubations

The rate of gross N mineralisation in the anaerobic incubation ranged between

3.5 mg N kg-1 d-1 in the 1R soils and 9.1 mg N kg-1 d-1 in the NF soils (Table 3.3). The

NF soils generally had higher rates of gross and net N mineralisation and NH4+

consumption than the plantation soils (Table 3.3). The 1R soils had significantly lower

gross N mineralisation and NH4+ consumption rates than the 2R soils. Significant

differences between the 2R-T soils and the 2R-W soils were found in the rates of

NH4+consumption and net N mineralisation. Gross and net N mineralisation were

negatively correlated to soil C:N ratio (r=-0.66 and –0.60 respectively, P<0.01).

3.4. Discussion

3.4.1 Impacts of land-use change on soil N mineralisation and immobilisation

Gross ammonification rates in the aerobic incubation were some of the lowest

reported and were accompanied by relatively low concentrations of NH4+. Similar rates

have been reported in a mature forest soil in Alberta, Canada (Carmosini et al., 2002).

Chapter 3 33

Rates of gross ammonification and NH4+ consumption were similar in the NF and 1R

soils, whilst rates of both processes were significantly higher in the 2R soils. Carmosini

et al. (2002) also found that gross ammonification and immobilisation of NH4+ were

higher in harvested soils compared to mature aspen-conifer mixed forest soils.

Ammonification is sensitive to disturbance and has been found to increase as

temperature increases (Carlyle, 1986; Frazer et al., 1990; Grenon et al., 2004).

Therefore, similar rates of ammonification in the NF and 1R soils may be related to the

fact that both ecosystems have been undisturbed for a substantial period of time.

Furthermore both ecosystems have closed canopies and therefore soil temperature is

likely to be similar. The 2R forest, however, does not have a closed canopy and

disturbance in the form of harvesting and site preparation was relatively recent. As

such, it is hypothesized that the larger rate of ammonification in the 2R soils compared

to the 1R soils may be the result of a pulse of increased mineralisation of native organic

N caused by soil disturbance, as well as higher soil temperature due to the lack of a

closed canopy.

In the anaerobic incubation, gross and net N mineralisation, as well as NH4+

consumption rates, were comparable to rates measured by Wang et al. (2001) in twenty

different soil types under waterlogged conditions. The NF soils had higher rates of

gross N mineralisation and NH4+ consumption than the plantation soils. Research has

shown that aerobic microbial biomass has the tendency to be lysed under anaerobic

conditions, which subsequently increases the amount of labile C and N (Bundy and

Meisinger, 1994; Wu and Brookes, 2005). Analysis of microbial biomass in these soils

(Chapter 5, Table 5.2) as well as previous work at this site (Chen et al., 2004) found that

a larger microbial biomass was present in the NF soils as compared to the plantation

soils. Hence, it is hypothesized that the differences in soil N transformations between

Chapter 3 34

the NF soil and the plantation soils under waterlogged conditions may partly reflect

differences in microbial biomass among the treatments.

3.4.2 Impacts of land-use change on soil nitrification

The change in land use from NF to forest plantations had an impact on net and

gross nitrification, as well as the NO3- pool, with rates and concentrations measured in

the NF soil more than double those in the plantation soils (Fig. 3.2). However, no

significant differences in rates of nitrification and the NO3- pool were found among 1R,

2R-T and 2R-W soils. Nitrification is a microbially mediated process and it is well

established that the quality of organic matter input, a factor associated with land-use

change, can affect the microbial community, and ultimately soil N transformations

(Cote et al., 2000; Chen et al., 2004; Grenon et al., 2004). In this study, C:N ratios were

significantly lower in NF litter (both F- and L- layer) and root material than in the 1R

litter and root material (Table 3.2). Generally, it is accepted that lower C:N ratios are

indicative of higher quality organic matter (Attiwill and Adams, 1993). Soil C:N ratios

were positively correlated to L-layer, F-layer and root C:N ratios, whilst gross

nitrification was negatively correlated to soil C:N ratio. Similar results were also found

by Breuer et al. (2002) and Ross et al. (2004). In addition to the differences in organic

matter quality, previous research at this study site found that microbial biomass was

greater in the NF soils and that both bacterial and fungal group diversity was higher in

the NF soil as compared with the plantation soils (Chen et al., 2004; He, 2004; He et al.,

2005). Hence, it is possible that the conversion from a mixed-species forest to a single-

species forest has changed the quality of organic matter input and subsequently

microbial population and diversity, which has ultimately resulted in lower nitrification

rates in the plantation soils compared to the NF soils.

In general, gross nitrification rates, particularly for the NF soils, were amongst

the highest reported and are comparable to rates found by Stark and Hart (1997), Neill

Chapter 3 35

et al. (1999) and Compton and Boone (2002). Such results indicate that nitrification is a

strong and important process in these soils. While other researchers have found small

NO3- pools coinciding with high nitrification rates and have attributed this to microbial

assimilation (Davidson et al., 1992; Stark and Hart 1997), NO3- concentrations in this

study were high and consumption negative (Table 3.1 and Figure 3.1). High

concentrations of NO3- at this particular site have been found by other workers (C.R.

Chen, personal communication). Such results suggest that NO3- is accumulating in

these soils. There are a number of explanations, which may individually or collectively

result in the high rates of nitrification as well as the accumulation of NO3- in these

soils. Research has established that root exudates can influence soil microbial activity

and that exudates from different tree species can affect the composition of microbial

populations (Grayston et al., 1997; Landi et al., 2006). It is therefore possible that root

exudates in these forest systems favour nitrifying communities, leading to high rates of

nitrification and large NO3- pools. Also, it is possible that the dry conditions prevalent

at this site may favour nitrification and prevent the loss of substantial quantities of NO3-

through leaching or denitrification.

It is interesting to note that gross nitrification was larger than gross

ammonification in this study, particularly as many researchers have found the opposite

to be true (Davidson et al., 1992; Silva et al., 2005). In the soil environment,

nitrification can be carried out by both autotrophs and heterotrophs. Autotrophic

nitrification is the process through which autotrophs convert inorganic NH4+ to NO3

-,

whereas heterotrophic nitrification is the conversion of organic N to NO3- by

heterotrophs (Stevenson and Cole, 1999). Traditionally, autotrophic nitrification is

believed to be the dominant nitrification process, although several studies have reported

heterotrophic nitrification in soils. For example, Schimel et al. (1984) found that the

potential for heterotrophic nitrification in a Sierran forest soil was greater than the

Chapter 3 36

potential for autotrophic nitrification, while Grenon et al. (2004) found that

heterotrophic nitrification accounted for 20 – 100% of total nitrification. Also, gross

nitrification rates in excess of gross ammonification were reported by Accoe et al.

(2005) for grassland soils. The higher rates of gross nitrification than gross

ammonification measured under aerobic conditions in this study may indirectly indicate

a significant role of heterotrophic nitrification in the N transformations of these soils. A

high rate of heterotrophic nitrification would explain the high rate of nitrification that

exists in these soils despite the relatively low ammonification rates and concentrations

of NH4+. The fact that the rate of nitrification is significantly larger in the NF soils than

in the plantation soils indicates that the change in land use has had a detrimental impact

on the (heterotrophic) nitrifying community.

3.4.3 Comparison of aerobic and anaerobic results

Wang et al. (2001) found that gross N mineralisation rates in aerobic and

anaerobic incubations were well correlated and that gross N mineralisation in anaerobic

incubations were not always higher. In this study, rates measured in the anaerobic

incubation were consistently higher, (with the exception of NH4+ consumption in the 1R

soils), and not correlated to rates measured in the aerobic incubation (Table 3.2). The

incubations in the study by Wang et al. (2001) were performed on air-dried soil. These

results may be somewhat artificial, as microbial population and activity are affected by

air drying and rewetting processes (Fierer and Schimel, 2002; De Nobili et al., 2006).

In this study, the higher rates of N mineralisation in the anaerobic incubation are likely

attributed to increased labile organic N and C as a result of lysis of aerobic microbial

biomass under waterlogged conditions (Bundy and Meisinger, 1994; Wu and Brookes,

2005). Also, it is expected that microbes at this site are suited to the prevailing dry

conditions and therefore may consist largely of aerobes, which would undergo lysis in

Chapter 3 37

anaerobic conditions. In a particularly dry site such as this, the anaerobic results may

not be as useful as aerobic results for predicting actual N transformations.

3.4.4 Comparison of net and gross transformation rates

In both aerobic and anaerobic incubations, soil net N transformation rates were

lower than the gross N transformation rates. Similar results have been found by other

researchers who have also concluded that soil net N transformation rates are only useful

as an index of N availability (Hart et al., 1994a; Schimel and Bennett, 2004). In the

aerobic incubation, rates of net ammonification were negative for all the soils and no

significant difference was found among the forest sites. Silva et al. (2005) also found

no differences in net N transformation rates between forest ecosystems, but differences

in gross N transformation rates were detected between the ecosystems. This suggests

that gross N transformation measurements may be a more sensitive indicator of land-use

change than the net N transformation rates and also that factors controlling N

consumption and production do not equally affect these processes (Hart et al., 1994a).

3.5 Conclusion

Results of the aerobic incubation suggest that the change in land-use from NF to

1R hoop pine plantation had no effect on ammonification and NH4+ consumption rates.

However, it did result in a significant decline in the rate of nitrification. Results of the

anaerobic incubation also suggest the land-use change from NF to 1R hoop pine

plantation decreased N mineralisation and availability. In contrast, the land-use change

from 1R hoop pine plantation to 2R hoop pine plantation increased the rate of

ammonification, but had little effect on rates of nitrification. Differences in the rate of

nitrification between the NF and 1R soils may be caused by the shift in tree species and

quality of organic matter input, which has subsequently caused changes in the size and

diversity of the soil microbial community. While differences in ammonification

Chapter 3 38

between the 1R and 2R soils may be a reflection of time since disturbance and

differences in soil temperature. Results of the aerobic incubation also found that in the

fifth year of the 2R hoop pine plantation, residue management practices did not affect

soil N transformations. Nitrification was found to be the dominant N transformation

process in these soils, despite relatively low NH4+ concentrations and rates of

ammonification. The significantly higher rates of nitrification compared to

ammonification suggests that heterotrophic nitrification may be significant. Future

studies focusing on characterisation of litter and microbial communities as well as root

exudates would enhance our understanding of the factors controlling soil N

transformations in these ecosystems.

Chapter 4 39

Chapter 4

Soluble organic nitrogen pools in adjacent native and plantation

forests of subtropical Australia.

4.1 Introduction

Research into soil nitrogen (N) pools and cycling has traditionally focused on

inorganic forms of N (e.g. NH4+ and NO3

-). Recent research indicates that soil soluble

organic nitrogen (SON) is present in substantial quantities in a wide range of

ecosystems and that it may in fact play an important regulatory role in the soil-plant N

cycle (Murphy et al., 2000; Neff et al., 2003; Chen et al., 2005b; Chen and Xu, 2006).

Not only is SON a labile source of N for micro-organisms, but also certain plant species

(with or without associated mychorriza) are capable of the direct uptake of simple

organic N (e.g. amino acids) present in the SON pool (Chapin et al., 1993; Lipson and

Monson, 1998; Näsholm et al., 1998; Lipson and Näsholm, 2001; Jones et al., 2005; Xu

et al., 2006). Furthermore, research in some forested watersheds has shown that organic

N can be the dominant form of N in the adjacent water bodies, suggesting that SON

from terrestrial sources may, in some cases, contribute to the pollution of waterways via

leaching and runoff (Sollins and McCorinson, 1981; Wissmar, 1991; Hedin et al.,

1995). Hence, soil SON may have greater ecological significance than once thought.

Soil SON can be defined as the organic N extracted from a soil by a water or salt

solution, and differs from dissolved organic nitrogen (DON), which can be defined as

the organic N in soil solution and is usually measured using leaching methods or suction

cups (Murphy et al., 2000; Zhong and Makeschin 2003; Chen et al., 2005b). To date

several different extraction techniques have been used to quantify soil SON pools

including water and various salt solutions, (e.g. CaCl2, KCl, and K2SO4), and

electroultrafiltration (EUF). Hot water and hot KCl extraction methods have also been

used by a few researchers (Gianello and Bremner, 1986a,b; Wang et al., 2001; Curtin et

Chapter 4 40

al., 2006). There is currently no standard method for measuring soil SON (Jones and

Willett, 2006). The amount and composition of soil SON in the mineral soil may be

influenced by abiotic and biotic factors including soil type, tree species, the quantity and

quality of organic matter returned to the soil, microbial communities, land management

practices, and environmental conditions such as rainfall and temperature (Chapman et

al., 2001; Qualls and Richardson, 2003; Chantigny, 2003; Chen and Xu, 2006; Xu and

Chen, 2006). Given this, land-use change is also likely to have a significant impact on

soil SON pools.

The long-term sustainability and productivity of forest plantations depend on the

maintenance of soil nutrient resources. In Queensland, plantations of hoop pine

(Araucaria cunninghamii), account for approximately one quarter (50 000 ha) of the

state’s plantation area. Hoop pine is a N demanding species and most of the current

plantations were established on land which was previously native forest (Chen et al.,

2002; Xu et al., 2002; Prasolova and Xu, 2003; Xu et al., 2003). To date there has been

little research on the impact of land-use change from mixed-species native forests to

single-species plantation forests on soil SON pools, particularly in subtropical zones.

Furthermore, most of the SON research that has been conducted is limited to the organic

horizon or the top fifteen to twenty centimeters (bulked rather than separated into

increments) of the mineral soil (Hannam and Prescott, 2003; Zhong and Makeschin

2003; Willett et al., 2004; Chen et al., 2005b). This is based on the assumption that

land-use change only affects the uppermost layer of the soil (Jinbo et al., 2006). Hence,

very little is known about the distribution of SON pools through the soil profile.

If, as the recent research suggests, SON pools have the potential to act not only

as a source of nutrients for plants but also as a regulator of the soil N cycle, it is

essential to the long-term sustainability of the Queensland forestry industry to

understand how land-use change from mixed-species native forest to single-species

Chapter 4 41

forest plantation, with the associated disturbances and silvicultural techniques, have

impacted upon this important soil N pool. The aim of this experiment was to quantify

the effect of land-use change from native forest (NF) to first rotation (1R) hoop pine

plantation and subsequent second rotation (2R) and the associated residue management

strategy, on soil SON pools through the soil profile (0-10, 10-20 and 20-30 cm layers)

using a variety of extraction methods.


4.2.1 Sample collection

In July 2005, fifteen soil cores were randomly collected from each plot within

the NF, 1R, 2R-T and 2R-W sites, at three depths (0-10, 10-20 and 20-30 cm), using a

7.5 cm diameter auger and bulked. All samples were transported to the laboratory and

processed as described in Chapter 2. A sub-sample of each soil was air-dried at room

temperature for analysis of soil total C and total N as described in Chapter 2 (Table 4.1),

and a second sub-sample was kept at 4˚C until the SON experiment was conducted

approximately eight weeks later.

Table 4.1: Soil total carbon (C), total nitrogen (N) and C:N ratios for adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T), and second rotation windrow (2R-W) at the Yarraman site, subtropical Australia.

Forest type Total C (%)

Total N (%)

C:N ratio

0-10 cm NF 8.9 0.75 12 1R 7.1 0.52 14 2R-T 5.8 0.46 13 2R-W 6.1 0.47 13

10-20 cm NF 5.7 0.50 11 1R 4.2 0.37 12 2R-T 4.5 0.38 12 2R-W 3.4 0.31 11

20-30 cm NF 3.5 0.31 11 1R 2.7 0.24 12 2R-T 2.6 0.22 12 2R-W 2.5 0.21 12

Chapter 4 42

4.2.2 Preparation of soil extracts

The water, hot water, 2 M KCl and 0.5 M K2SO4 extracts were obtained using

modifications of the methods described by Chen et al. (2005a). In brief, water (w)

extracts were prepared by mixing 10 g (dry weight equivalent) of field moist soil and 40

ml of distilled water on an end–to–end shaker for 1 h and filtering through a Whatman

42 paper and subsequently through a 0.45 μm filter membrane. For hot water (hw)

extracts, 10 g (dry weight equivalent) of field moist soil was mixed with 40 ml of water

in a falcon tube, which was placed into a hot water bath for 18 h at 70 °C. The tubes

were then shaken for 5 min on an end–to–end shaker and filtered through a Whatman 42

paper followed by a 0.45 μm filter membrane. The KCl (KCl) extracts were obtained by

mixing 5 g (dry weight equivalent) of field moist soil with 50 mL of 2 M KCl, shaking

on an end–to–end shaker for 1 h and filtering through a Whatman 42 paper. For the

K2SO4 (ps) extracts, 50 mL of 0.5 M K2SO4 was added to 10 g (dry weight equivalent) of

field moist soil and shaken on an end-to–end shaker for 30 min, then filtered through a

Whatman 42 paper. The hot KCl (hKCl) method used was adapted from Gianello and

Bremner (1986b) and Wang et al. (2001). In brief, 5 g (dry weight equivalent) of fresh

soil was placed in a capped digestion tube together with 50 mL of 2 M KCl. The tubes

were then placed in a digestion unit at 100 °C for 4 h after which they were allowed to

cool to room temperature before mixing the soil suspension for 1 min with a vortex

homogeniser. Finally they were filtered through Whatman 42 papers.

4.2.3 Analysis of soluble N in soil extracts

The concentrations of NH4+-N and NO3

--N in the extracts were determined using

the LACHAT Quickchem Automated Ion Analyser (QuikChem Method 10-107-06-04-

D for NH4+-N and QuikChem Method 12-107-04-1-B for NO3

--N) described in chapter

2. Soluble inorganic N (SIN) was calculated as the sum of NO3--N and NH4

+-N.

Chapter 4 43

Soluble organic carbon (SOC) and total soluble N (TSN) in the soil extracts were

measured with the SHIMADZU TOC-VCPH/CPN analyser (fitted with TN unit) described

in Chapter 2, using the high temperature catalytic oxidation method described by Chen

et al. (2005a). In order to avoid salt precipitation on the surface of the Pt/Al2O3

catalyst, all KCl, K2SO4 and hot KCl extracts were diluted five-fold before analysis.

The SON in the different extracts was calculated as the difference between TSN and the

sum of NO3--N and NH4

+-N (SIN). The ratio of SOC to SON (C:No) was also

calculated for each extract.

4.2.4 Potential production of SON and SOC

Potentially mineralisable N (PMN) is commonly measured using the method

originally described by Waring and Bremner (1964). In this standard method only

inorganic N (in the form of NH4+-N) is determined, and as such there is no information

about the potential production of SON during this incubation. Therefore, the term

potential production of SON (PPSON) was devised to describe the increase in SON

during the 7 d anaerobic incubation traditionally used to determine PMN. It is believed

that this measurement could be indicative of the decomposition of the moderately labile

pool of organic N into more labile forms of organic N (i.e. SON). For convenience, the

SIN and SOC formed during the incubation are described as the potential production of

SIN (PPSIN) and the potential production of SOC (PPSOC).

The anaerobic incubation method used was described by Bundy and Meisinger

(1994). In brief, 5 g (dry weight equivalent) of field moist soil was mixed with 25 ml of

deionised water and incubated at 40 ºC for 7 d. After the incubation each sample was

extracted with 25 ml of 4 M KCl, shaken on an end-to-end shaker for 1 h and filtered

through a Whatman 42 paper. Analysis of soluble forms of N in the samples at the end

of the 7 d incubation was conducted as described in section 4.2.3. The potential

production of TSN (PPTSN) was then calculated as the difference between TSN in the

Chapter 4 44

KCl extract after the 7 d incubation and the TSN in the original KCl extract (TSNKCl).

The value of PPSIN was calculated as the sum of NH4+-N and NO3

--N in the incubated

sample minus the sum of NH4+-N and NO3

--N in the original KCl extract. Finally,

PPSON was calculated as the difference between PPTSN and PPSIN. The value of

PPSOC was calculated as the difference between the concentration of SOC before the

incubation and the concentration of SOC after the 7 d incubation.

4.2.5 Statistical analysis

All data analysis was conducted in SAS Version 9.1.3 for Windows. Log

transformations were used to stabilize data variability and induce normality where

appropriate. A split-plot factorial analysis of variance (ANOVA) was used to explore

differences within each SON pool based on the factors forest type and soil depth.

Where significant differences were detected, pair-wise comparisons were made using

the Tukey adjustment for multiple-range testing. Spearman rank correlations were

performed to investigate relationships between different SON pools.

4.3. Results

A significant interaction between forest type and soil depth was found for the

majority of parameters measured in all extract types (results not shown), suggesting that

in most cases the extent to which forest type affects a particular parameter may vary

with soil depth.

4.3.1 Water extractable organic N

Concentrations of SONw in the 0-10 cm layer, ranged from 3.2 mg N kg-1 in the

1R and 2R-T soil to 8.7 mg N kg—1 in the NF soil (equivalent to approximately 2.0 - 5.3

kg N ha-1). This amount of SONw comprised 8.0-11.8% of the TSNw and less than

0.14% of soil total N (Table 4.2). At this depth the NF soil had a significantly higher

concentration of SONw than the 1R soil. The 1R soil had a similar concentration of

Chapter 4 45

SONw to the 2R-T soil, but both had significantly lower concentrations than the 2R-W

soil. In all forest types, the size of the SONw pool generally decreased with soil depth,

accounting for 4.8-10.3% of the TSN and up to 0.07% of soil total N in the 10-20 cm

layer, and up to 18.2% of TSNw and 0.07-0.08% of soil total N in the 20-30 cm layer.

Concentrations of SONw were similar between all forest types in the 10-20 and 20-30

cm layers.

Concentrations of SOCw in the 0-10 cm layer ranged from 54 mg C kg-1 in the

1R soil to 98 mg C kg-1 in the 2R-W soil and decreased with soil depth. In the 0-10 cm

layer, the NF soil had a higher concentration (although not significant) of SOCw than

the 1R soil. The 1R soil and 2R-T soil had similar concentrations of SOCw, however

the 2R-W soil had a significantly higher concentration of SOCw than both the 1R soil

and the 2R-T soil (Table 4.2). The C:No-w ratio ranged from 10 to 18 in the 0-10 cm

layer and was significantly lower in the NF soil than in the plantation soils (Table 4.2).

Concentrations of SINw ranged from approximately 35 mg N kg-1 in the 1R soil to 57

mg N kg-1 in the NF soil and decreased with soil depth. The majority of the SINw pool

in all forest types was accounted for by NO3--N. The NF soil had a significantly higher

concentration of SINw than the plantations soils in all depths. Of the plantation soils,

the 1R soil tended to have the lowest SINw concentrations, and the 2R-W tended to have

the highest SINw concentrations in all depths (Table 4.2).

Tab

le 4

.2:

Solu

ble

inor

gani

c N

(SI

N)

and

orga

nic

N (

SON

) ex

tract

ed b

y w

ater

(w)

from

soi

ls o

f ad

jace

nt n

ativ

e fo

rest

(N

F), 5

3 y-

old

first

rot

atio

n ho

op p

ine

plan

tatio

n (1

R),

5 y-

old

seco

nd ro

tatio

n tre

e ro

w (2

R-T

), an

d se

cond

rota

tion

win

drow

(2R

-W) a

t the

Yar

ram

an s

ite, s

ubtro

pica

l Aus

tralia

. M

ean

valu

es (n

=5) w

ere

com

pare

d am

ong

fore

st ty

pes w

ithin

eac

h de

pth

and

if fo

llow

ed b

y th

e sa

me

lette

r are

not

sign

ifica

nt a

t the

5%

leve

l of s

igni

fican

ce.

Fore

st ty

pe

SIN

w (m

g kg

-1)

SON

w

SOC

w γ (m

g kg

-1)

C:N

o-w

δ ratio

N

H4+ -N

NO

3- -N(m

g kg

-1)

% (T

SN) α

%

(TN

)β

0-10

cm

N

F 0.

43a

57a

8.7a

9.

2a

0.12

ab

82ab

10

b 1R

0.

55a

34c

3.2c

8.

6a

0.06

b 54

b 17

a 2R

-T

0.51

a 37

c 3.

2c

8.0a

0.

07b

57b

18a

2R-W

0.

74a

49b

6.7b

11

.8a

0.14

a 98

a 15

a 10

-20

cm

NF

0.36

a 46

a 2.

3a

4.8b

0.

05a

35ab

15

a 1R

0.

28a

14c

1.6a

10

.3a

0.04

a 26

b 17

a 2R

-T

0.50

a 19

bc

2.0a

9.

5ab

0.06

a 36

ab

19a

2R-W

0.

52a

26b

2.2a

7.

3ab

0.07

a 54

a 27

a 20

-30

cm

NF

0.34

a 35

a 2.

4a

6.6b

0.

08a

41a

19a

1R

0.21

a 8c

1.

8a

18.2

a 0.

08a

36a

18a

2R-T

0.

56a

15b

1.5a

8.

9b

0.07

a 40

a 27

a 2R

-W

0.24

a 20

b 1.

6a

7.3b

0.

07a

43a

27a

α Perc

enta

ge o

f SO

Nw o

ver t

otal

solu

ble

nitro

gen

(TSN

w).

β Perc

enta

ge o

f SO

Nw o

ver s

oil t

otal

nitr

ogen

(TN

). γ So

lubl

e or

gani

c ca

rbon

in w

ater

ext

ract

(SO

C w).

δ C:N

o-w ra

tio, t

he ra

tio o

f SO

Cw to

SO

Nw

.

Chapter 4 47

4.3.2 Hot water extractable organic N

In the 0-10 cm layer, concentrations of SONhw ranged from 60 mg N kg-1 in the

2R-T soil to 160 mg N kg-1 in the NF soil (equivalent to approximately 53 to 98 kg N

ha-1). This concentration of SONhw accounted for 60-74% of the TSNhw and 1.3-2.1%

of soil total N in the 0-10 cm layer of soil (Table 4.3). Concentrations of SONhw

generally decreased with soil depth, and in all forest types and depths were one to two

orders of magnitude higher than SONw. The land-use change from NF to 1R

significantly decreased the concentration of SONhw in all depths (Table 4.3). In the 0-

10 cm layer, the 1R soil had a higher concentration of SONhw than the 2R plantation

soils, however SONhw concentrations in the 10-20 and 20-30 cm layers were similar.

The 2R-T and 2R-W soils had similar SONhw concentrations in all depths (Table 4.3).

Concentrations of SOChw in the 0-10 cm layer ranged from 714 mg C kg-1 in the

2R-T soil to 1628 mg C kg-1 in the NF soil and decreased with soil depth. At all soil

depths, the NF soil had a significantly higher concentration of SOChw than the 1R soil.

In the 0-10 cm layer, the SOCw concentrations were similar in the 1R and 2R-W soil but

significantly lower in the 2R-T soil (Table 4.3). While in the lower depths there was no

significant difference in SOChw concentrations among the plantation soils. The C:No-hw

ratios ranged between 10 and 13 in the 0-10 cm layer. At this depth the NF soil had a

lower C:No-hw ratio than the plantation soils.

The SINhw concentrations were between 24 mg N kg-1 and 56 mg N kg-1 in the

0-10 cm layer and decreased with soil depth. While concentrations of SINhw were

similar to concentrations of SINw, it was interesting to find that NH4-N accounted for

the majority of SINhw. The land-use change from NF to 1R had little effect on SINhw in

all depths, however the conversion of 1R plantation to 2R plantation tended to decrease

SINw. The 2R-W had a higher concentration of SINhw than the 2R-T in the 0-10 cm

layer, but concentrations were similar at lower soil depths.

Chapter 4 48

4.3.3 KCl and K2SO4 extractable organic N

In the 0-10 cm layer, the SONKCl ranged from 20 mg N kg-1 in the 1R soil to 28

mg N kg-1 in the NF soil (equivalent to approximately 13 - 17 kg N ha-1) (Table 4.4).

The concentrations varied little with depth and in the 0-10 cm depth the SONKCl

accounted for 26-39% of the TSNKCl, and 0.4-0.5% of soil total N (Tables 4.4).

Concentrations of SONps were similar although often marginally lower than the SONKCl

concentrations (Table 4.5). The SONKCl and SONps pools were larger than the SONw

pool but smaller than the SONhw pool. In all depths, the NF soil tended to have higher

concentrations of both SONKCl and SONps than the 1R soil. The 1R soil had similar

concentrations of SONKCl and SONps to the 2R soils in the 0-10 cm layer but had

significantly lower concentrations of SONKCl and SONps than the 2R soils in the 10-20

and 20-30 cm layers. Concentrations of SONKCl and SONps in the 2R-T soil and the 2R-

W soil were similar (Tables 4.4 and 4.5).

In the 0-10 cm layer the concentrations of SOCKCl and SOCps ranged between

143 mg N kg-1 and 274 mg N kg-1, with the NF soil having a higher concentration of

SOCKCl than the 1R soil. At this depth no significant differences were found in SOCKCl

or SOCps concentrations among the plantation soils. The C:No-KCl ratios in the 0-10 cm

layer ranged between 6.9 and 8.3 and were lower than the C:No-ps ratios which ranged

between 11 and 12. Both the KCl and K2SO4 extracted greater concentrations of SIN

than SON, with NO3-N making up the majority of the SIN pool. The land-use change

affected the SINKCl and SINps pools in a similar way to the SOCKCl and SOCps pools

(Tables 4.4 and 4.5).

Tab

le 4

.3: S

olub

le in

orga

nic

N (S

IN) a

nd o

rgan

ic N

(SO

N) e

xtra

cted

by

hot w

ater

( hw) f

rom

soi

ls o

f ad

jace

nt n

ativ

e fo

rest

(NF)

, 53

y-ol

d fir

st ro

tatio

n

hoop

pin

e pl

anta

tion

(1R

), 5

y-ol

d se

cond

rot

atio

n tre

e ro

w (

2R-T

), an

d se

cond

rot

atio

n w

indr

ow (

2R-W

) at

the

Yar

ram

an s

ite, s

ubtro

pica

l Aus

tralia

.

Mea

n va

lues

(n=

5) w

ere

com

pare

d am

ong

fore

st t

ypes

with

in e

ach

dept

h an

d if

follo

wed

by

the

sam

e le

tter

are

not

sign

ifica

nt a

t th

e 5%

lev

el o

f

sign

ifica

nce.

Fore

st ty

pe

SIN

hw (m

g kg

-1)

SON

hw

SOC

hw γ

(mg

kg-1

) C

:No-

hw δ

ratio

NH

4+ -N

NO

3- -N

(mg

kg-1

) %

(TSN

hw) α

%

(TN

) β

0-10

cm

N

F 55

a 0.

5a

160a

74

a 2.

1a

1628

a 10

b 1R

56

a 0.

2a

81b

60a

1.6b

10

53b

13a

2R-T

22

b 1.

9a

60c

72a

1.3b

71

4c

12ab

2R

-W

44a

0.1a

77

bc

63a

1.6b

10

25b

13a

10-2

0 cm

N

F 20

a 8.

9ab

66a

69a

1.3a

66

1a

10a

1R

16a

2.6b

42

b 69

a 1.

2a

404b

10

a 2R

-T

10b

4.7a

b 38

b 72

a 1.

0a

422b

11

a 2R

-W

11b

12.2

a 39

b 63

a 1.

3a

476b

12

a 20

-30

cm

NF

8a

14.1

a 28

a 54

a 0.

9a

339a

13

a 1R

6a

b 3.

3b

19b

67a

0.8a

21

5b

11a

2R-T

4c

12

.2ab

16

b 50

a 0.

7a

230b

15

a 2R

-W

4bc

15.0

a 16

b 46

a 0.

8a

249b

16

a α Pe

rcen

tage

of S

ON

hw o

ver t

otal

solu

ble

nitro

gen

(TSN

hw).

β Perc

enta

ge o

f SO

Nhw

ove

r soi

l tot

al n

itrog

en (T

N).

γ Solu

ble

orga

nic

carb

on (S

OC

hw).

δ C:N

o-hw

ratio

, the

ratio

of S

OC

hw to

SO

Nhw

Tab

le 4

.4: S

olub

le in

orga

nic

N (S

IN) a

nd o

rgan

ic N

(SO

N) e

xtra

cted

by

KC

l (K

Cl)

from

soi

ls o

f adj

acen

t nat

ive

fore

st (N

F), 5

3 y-

old

first

rota

tion

hoop

pine

pla

ntat

ion

(1R

), 5

y-ol

d se

cond

rota

tion

tree

row

(2R

-T),

and

seco

nd ro

tatio

n w

indr

ow (2

R-W

) at t

he Y

arra

man

site

, sub

tropi

cal A

ustra

lia.

Mea

n

valu

es (n

=5) w

ere

com

pare

d am

ong

fore

st ty

pes w

ithin

eac

h de

pth

and

if fo

llow

ed b

y th

e sa

me

lette

r are

not

sign

ifica

nt a

t the

5%

leve

l of s

igni

fican

ce.

Fore

st ty

pe

SIN

KC

l (m

g kg

-1)

SON

KC

l SO

CK

Cl γ

(mg

kg-1

)C

:No-

KC

l δ ratio

N

H4+ -N

NO

3- -N(m

g kg

-1)

% (T

SNK

Cl) α

%

(TN

) β

0-10

cm

N

F 2.

7a

88a

28a

26b

0.4a

22

9a

8.3a

1R

3.

4a

31b

20a

38a

0.4a

14

7b

7.6a

2R

-T

3.0a

31

b 21

a 39

a 0.

5a

143b

6.

9a

2R-W

2.

7a

44b

24a

34a

0.5a

20

0ab

8.3a

10

-20

cm

NF

2.2b

42

a 25

a 36

b 0.

5ab

158a

6.

5a

1R

1.7b

13

c 13

b 47

ab

0.3b

80

b 6.

4a

2R-T

3.

7a

16bc

22

a 52

a 0.

6ab

147a

6.

7a

2R-W

3.

2a

24b

25a

46ab

0.

8a

182a

7.

4a

20-3

0 cm

N

F 2.

0a

33a

24a

41b

0.8b

18

2a

7.6a

1R

1.

8a

8c

14b

58a

0.6b

10

6b

8.3a

2R

-T

2.1a

14

b 25

a 60

a 1.

2a

183a

7.

2a

2R-W

2.

1a

20ab

25

a 53

ab

1.2a

19

9a

8.1a

α Pe

rcen

tage

of S

ON

KC

l ove

r tot

al so

lubl

e ni

troge

n (T

SNK

Cl).

β Pe

rcen

tage

of S

ON

KC

l ove

r soi

l tot

al n

itrog

en (T

N).

γ Solu

ble

orga

nic

carb

on (S

OC

KC

l).

δ C:N

o-K

Cl r

atio

, the

ratio

of S

OC

KC

l to

SON

KC

l.

Tab

le 4

.5: S

olub

le in

orga

nic

N (S

IN) a

nd o

rgan

ic N

(SO

N) e

xtra

cted

by

K2S

O4 ( ps

) fro

m so

ils o

f adj

acen

t nat

ive

fore

st (N

F), 5

3 y-

old

first

rota

tion

hoop

pine

pla

ntat

ion

(1R

), 5

y-ol

d se

cond

rota

tion

tree

row

(2R

-T),

and

seco

nd ro

tatio

n w

indr

ow (2

R-W

) at t

he Y

arra

man

site

, sub

tropi

cal A

ustra

lia.

Mea

n

valu

es (n

=5) w

ere

com

pare

d am

ong

fore

st ty

pes w

ithin

eac

h de

pth

and

if fo

llow

ed b

y th

e sa

me

lette

r are

not

sign

ifica

nt a

t the

5%

leve

l of s

igni

fican

ce.

Fore

st ty

pe

SIN

ps (m

g kg

-1)

SON

(ps)

SO

Cps

γ (mg

kg-1

)C

:No-

ps δ

ratio

N

H4+ -N

NO

3- -N(m

g kg

-1)

% (T

SN ps

) α

% (T

N) β

0-10

cm

N

F 1.

53a

80a

23a

23a

0.3a

27

4a

12ab

1R

0.

94b

33b

14a

31a

0.3a

17

7a

12a

2R-T

1.

62a

34b

18a

34a

0.4a

18

0a

10b

2R-W

1.

64a

44b

20a

30a

0.4a

21

9a

11ab

10

-20

cm

NF

0.55

a 43

a 20

a 31

b 0.

4b

222a

b 12

a 1R

0.

45a

13c

11b

46a

0.3b

12

0b

11a

2R-T

0.

59a

16c

20a

54a

0.5b

23

5ab

12a

2R-W

0.

58a

24b

23a

48a

0.7a

28

1a

12a

20-3

0 cm

N

F 0.

56a

32a

25ab

44

b 0.

8bc

311a

b 13

a 1R

0.

47a

7c

17b

69a

0.7c

20

1b

12a

2R-T

0.

60a

13b

28ab

64

a 1.

3ab

351a

13

a 2R

-W

0.57

a 18

b 32

a 63

a 1.

5a

394a

13

a α Pe

rcen

tage

of S

ON

ps o

ver t

otal

solu

ble

nitro

gen

(TSN

ps).

β Perc

enta

ge o

f SO

Nps

ove

r soi

l tot

al n

itrog

en (T

N).

γ Solu

ble

orga

nic

carb

on (S

OC

ps).

δ C:N

o-ps

ratio

, the

ratio

of S

OC

ps to

SO

Nps

.

Chapter 4 52

4.3.4 Hot KCl extractable organic N

Concentrations of SONhKCl were 2-3 times higher than SONhw, and in the 0-10

cm layer ranged from 127 mg N kg-1 in the 2R-T soil to 340 mg N kg-1 in the NF soil

(equivalent to approximately 112 - 340 kg N ha-1). The concentrations decreased with

soil depth, but the percentage of TSNhKCl accounted for by the SONhKCl was fairly

consistent with depth and was generally 60-70% in all forest soils. The proportion of

soil total N accounted for by SONhKCl ranged between 2.8% and 4.6% in the 0-10 cm

layer of soil (Table 4.6). The SONhKCl concentration was significantly higher in the NF

soil than in the 1R soil regardless of depth. In the 0-10 cm layer, the 1R soil had a

higher concentration of SONhKCl than the 2R-T soil and 2R-W soil, however the

concentrations were similar in the 10-20 and 20-30 cm layers. The 2R-T soil had less

SONhKCl than the 2R-W soil in the top 10 cm, however the concentrations were similar

in the lower depths (Table 4.6).

Concentrations of SOChKCl were approximately twice as high as the

concentrations measured in any other extract and were affected by forest type in a

similar way to SONhKCl (Table 4.6). The C:No-hKCl ratios ranged between 9 and 11 in all

depths and were not affected by land-use change (Table 4.6). The SINhKCl

concentration was also at least two times higher than in other extracts. This was due to

the fact that NH4-N was present in quantities equal to or greater than NO3--N. In the 0-

10 cm layer, the land-use change from NF to 1R reduced both the NH4-N and NO3--N

fractions of the SINhKCl pool. The change from 1R to 2R plantation, also reduced the

NH4-N fraction, while the NO3--N fraction remained similar. Concentrations of both

fractions of SINhKCl in the 0-10 cm layer were similar in the 2R-T and 2R-W soils.

Tab

le 4

.6: S

olub

le in

orga

nic

N (S

IN) a

nd o

rgan

ic N

(SO

N) e

xtra

cted

by

hot K

Cl (

hKC

l) fr

om so

ils o

f adj

acen

t nat

ive

fore

st (N

F), 5

3 y-

old

first

rota

tion

hoop

pin

e pl

anta

tion

(1R

), 5

y-ol

d se

cond

rot

atio

n tre

e ro

w (

2R-T

), an

d se

cond

rot

atio

n w

indr

ow (

2R-W

) at

the

Yar

ram

an s

ite, s

ubtro

pica

l Aus

tralia

.

Mea

n va

lues

(n=

5) w

ere

com

pare

d am

ong

fore

st t

ypes

with

in e

ach

dept

h an

d if

follo

wed

by

the

sam

e le

tter

are

not

sign

ifica

nt a

t th

e 5%

lev

el o

f

sign

ifica

nce.

Fore

st ty

pe

SIN

hKC

l (m

g kg

-1)

SON

hKC

l SO

ChK

Cl γ

(mg

kg-1

) C

:No-

hKC

l δ ratio

NH

4+ -N

NO

3- -N

(mg

kg-1

) %

(TSN

hKC

l) α

% (T

N) β

0-

10 c

m

NF

80a

82a

340a

68

a 4.

6a

3356

a 10

a 1R

60

b 33

b 22

5b

71a

4.4a

22

11b

10a

2R-T

34

c 32

b 12

7c

66a

2.8b

11

96c

9a

2R-W

42

c 41

b 17

7b

68a

3.8a

b 17

59b

10a

10-2

0 cm

N

F 45

a 44

a 15

9a

64a

3.2a

14

57a

9a

1R

41ab

14

c 11

2b

67a

3.1a

99

7b

9a

2R-T

32b

17c

106b

69

a 2.

9a

977b

9a

2R

-W

31b

25b

104b

65

a 3.

3a

1010

b 10

a 20

-30

cm

NF

24a

34a

81a

58b

2.6a

80

7.9a

10

a 1R

21

a 8c

55

b 66

a 2.

3a

533b

10

a 2R

-T

18a

14b

65b

67a

2.9a

67

7ab

10a

2R-W

17

a 18

b 61

b 64

a 3.

0a

659b

11

a α Pe

rcen

tage

of S

ON

hKC

l ove

r tot

al so

lubl

e ni

troge

n (T

SNhK

Cl).

β Pe

rcen

tage

of S

ON

hKC

l ove

r soi

l tot

al n

itrog

en (T

N).

γ Solu

ble

orga

nic

carb

on (S

OC

hKC

l).

δ C:N

o-hK

Cl r

atio

, the

ratio

of S

OC

hKC

l to

SON

hKC

l.

Chapter 4 54

4.3.5 Potential production of SON

The PPSON in the 0-10 cm layer ranged from 39 mg N kg-1 in the 2R-T soil to

99 mg N kg-1 in the NF soil (equivalent to approximately 34 - 61 kg N ha-1), accounting

for 41-58% of the TSN and up to 1.3% of soil total N (Table 4.7). The PPSON tended

to be higher in the NF soil than in the 1R soil in all depths. The 1R soil generally had

higher PPSON than the 2R soils. The 2R-W soil also tended to have higher PPSON

than the 2R-T soil (Table 4.7). Concentrations of PPSON, PPSIN, PPSOC and the ratio

of PPSON to PPSOC (C:No-PPSOC/SON) all decreased with depth (Table 4.7). PPSOC

exhibited similar patterns to PPSON, with the NF soil having higher PPSOC than the

1R soil. However, PPSIN was generally lower in the NF soil than the 1R soil. The 1R

soil tended to have higher PPSIN and PPSOC than the 2R soils, while the 2R-W soil

generally had higher PPSIN and PPSOC than the 2R-T soil.

4.3.6 Relationships among SON pools

Within all of the pools extracted, the concentration of SON was highly

correlated with the concentrations of SOC (r = 0.77-0.98, P<0.001) (Table 8).

Concentrations of SONw, SONhw and SONhKCl were highly correlated (r = 0.67-0.91,

P<0.001), while concentrations of SONKCl and SONps were also highly correlated to

each other (r = 0.73, P<0.001) (Table 4.8).

The difference between SONhw and SONw was smaller than the difference

between SONhKCl and SONKCl (Fig. 4.1). However, both differences decreased with soil

depth and in the 0-10 cm layer were higher in the NF soil than in the 1R soil, higher in

the 1R soil compared to 2R soils and higher in the 2R-W soil compared to the 2R-T soil

(Fig. 4.1). The PPSON was significantly correlated to SONw, SONhw and SONhKCl (r =

0.80 – 0.91, P<0.001), (Table 4.8). As shown in Figs. 4.2a and b, PPSON increased as

SONhw and SONhKCl increased. The PPSON was also significantly correlated with the

concentration of NH4+ in both the hot KCl and hot water extracts (P<0.001) (Figs. 4.2a

and b).

Tab

le 4

.7:

Pote

ntia

l pr

oduc

tion

of i

norg

anic

N (

PPSI

N)

and

pote

ntia

l pr

oduc

tion

of s

olub

le o

rgan

ic N

(PP

SON

) ca

lcul

ated

bas

ed o

n a

seve

n da

y

anae

robi

c in

cuba

tion

from

soils

of a

djac

ent n

ativ

e fo

rest

(NF)

, 53

y-ol

d fir

st ro

tatio

n ho

op p

ine

plan

tatio

n (1

R),

5 y-

old

seco

nd ro

tatio

n tre

e ro

w (2

R-T

),

and

seco

nd ro

tatio

n w

indr

ow (

2R-W

) at

the

Yar

ram

an s

ite, s

ubtro

pica

l Aus

tralia

. M

ean

valu

es (n

=5) w

ere

com

pare

d am

ong

fore

st ty

pes

with

in e

ach

dept

h an

d if

follo

wed

by

the

sam

e le

tter a

re n

ot si

gnifi

cant

at t

he 5

% le

vel o

f sig

nific

ance

.

Fore

st ty

pePP

SIN

α

PPSO

N β

PPSO

Cε (m

g kg

-1)

C:N

o ζ ra

tio

(mg

kg-1

)(m

g kg

-1)

% (T

SN) γ

% (T

N) δ

0-

10 c

m

NF

74.7

b 99

a 58

a 1.

3a

442a

4.

4a

1R

101.

4a

69b

41a

1.3a

32

1b

4.6a

2R

-T

35.7

d 39

d 53

a 0.

8b

155d

4.

0a

2R-W

59

.1c

62c

51a

1.3a

25

5c

4.0a

10

-20

cm

NF

14.0

a 40

a 74

a 0.

8a

147a

3.

6a

1R

28.6

a 25

a 47

b 0.

7a

100a

4.

1a

2R-T

13

.4a

19b

61a

0.5a

64

b 3.

3a

2R-W

12

.3a

23a

67a

0.7a

11

0ab

4.1a

20

-30

cm

NF

1.4b

27

a 95

a 0.

9a

71a

2.9a

1R

13

.6a

13b

49b

0.6a

32

b 2.

2a

2R-T

9.

3a

12b

55a

0.5a

23

b 2.

0a

2R-W

5.

6ab

19ab

78

a 0.

9a

35b

2.5a

α P

PSIN

= to

tal i

norg

anic

nitr

ogen

afte

r inc

ubat

ion

– to

tal i

norg

anic

nitr

ogen

bef

ore

incu

batio

n β P

PSO

N =

tota

l org

anic

nitr

ogen

afte

r inc

ubat

ion

– to

tal o

rgan

ic n

itrog

en b

efor

e in

cuba

tion

γ Perc

enta

ge o

f PPS

ON

ove

r pot

entia

l pro

duct

ion

of to

tal s

olub

le n

itrog

en (P

PTSN

). δ Pe

rcen

tage

of S

ON

ove

r soi

l tot

al n

itrog

en (T

N).

ε Pote

ntia

l pro

duct

ion

of so

lubl

e or

gani

c ca

rbon

(PPS

OC

). ζ C

:No r

atio

, the

ratio

of P

PSO

C to

PPS

ON

in e

xtra

cts.

Tab

le 4

.8.

Spea

rman

rank

cor

rela

tion

coef

ficie

nts

betw

een

solu

ble

orga

nic

nitro

gen

(SO

N) p

ools

and

sol

uble

org

anic

car

bon

(SO

C) p

ools

in a

djac

ent

nativ

e fo

rest

(NF)

, 53

y-ol

d fir

st ro

tatio

n ho

op p

ine

plan

tatio

n (1

R),

5 y-

old

seco

nd ro

tatio

n tre

e ro

w (2

R-T

), an

d se

cond

rota

tion

win

drow

(2R

-W) a

t the

Yar

ram

an si

te, s

ubtro

pica

l Aus

tralia

.

SO

Nw

SO

Cw

SO

Nhw

SO

Chw

SO

NK

Cl

SOC

KC

l SO

NhK

Cl

SOC

hKC

l SO

Nps

SO

Cps

PP

SON

PP

SOC

SO

Nw

1

SOC

w

0.77

***

1

SO

Nhw

0.

73**

* 0.

56**

* 1

SO

Chw

0.

76**

* 0.

66**

* 0.

97**

* 1

SON

KC

l 0.

17

0.35

**

0.08

0.

21

1

SOC

KC

l 0.

29*

0.50

***

0.10

0.

25

0.89

***

1

SO

NhK

Cl

0.67

***

0.52

***

0.94

***

0.94

***

0.18

0.

20

1

SOC

hKC

l 0.

69**

* 0.

56**

* 0.

91**

* 0.

94**

* 0.

28*

0.31

* 0.

98**

* 1

SON

ps

-0.0

3 0.

18

-0.2

9*

-0.1

5 0.

73**

* 0.

82**

* -0

.22

-0.2

2 1

SO

Cps

-0

.09

0.12

-0

.34*

* -0

.23

0.69

***

0.80

***

-0.2

8*

-0.2

8*

0.97

***

1

PP

SON

0.

80**

* 0.

65**

* 0.

90**

* 0.

91**

* 0.

15

0.24

0.

88**

* 0.

88**

* -0

.13

-0.1

9 1

PP

SOC

0.

76**

* 0.

61**

* 0.

93**

* 0.

94**

* 0.

08

0.16

0.

94**

* 0.

92**

* -0

.23

-0.3

0 0.

95**

* 1

*Sig

nific

ance

at P

< 0

.05;

**S

igni

fican

ce a

t P <

0.0

1; S

igni

fican

ce a

t ***

P <

0.00

1; n

= 6

0

Chapter 4 57

Fig. 4.1: Differences between SONhw and SONw (black bars) and between SONhKCl and SONKCl (grey

bars) in NF, 1R, 2R-T and 2R-W forest soils in (a) 0-10 cm; (b) 10-20 cm; and (c) 20-30 cm.

0

50

100

150

200

250

300

350

400

NF 1R 2R-T 2R-W

0

50

100

150

200

250

300

350

400

NF 1R 2R-T 2R-W

0

50

100

150

200

250

300

350

400

NF 1R 2R-T 2R-W

0-10 cma

b 10-20 cm

Diff

eren

ce (

mg

kg-1

)

c 20-30 cm

Forest Type

Diff

eren

ce (

mg

kg-1

)D

iffer

ence

(m

g kg

-1)

0

50

100

150

200

250

300

350

400

NF 1R 2R-T 2R-W

0

50

100

150

200

250

300

350

400

NF 1R 2R-T 2R-W

0

50

100

150

200

250

300

350

400

NF 1R 2R-T 2R-W

0-10 cma

b 10-20 cm

Diff

eren

ce (

mg

kg-1

)

c 20-30 cm

Forest Type

Diff

eren

ce (

mg

kg-1

)D

iffer

ence

(m

g kg

-1)

Chapter 4 58

Fig. 4.2: Relationships (a) between the potential production of soluble organic nitrogen (PPSON) and

SON extracted using the hot KCl method (SONhKCl), or NH4+ extracted using the hot KCl method

(NH4+

hKCl); and (b) between PPSON and SON extracted using the hot water method (SONhw), or NH4+

extracted using the hot water method (NH4+

hw).

y = 1.39x + 1.63R2 = 0.86

y = 0.67x - 3.60R2 = 0.83

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150

y = 2.88x + 27.78R2 = 0.87

y = 0.56x + 15.49R2 = 0.65

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150

a

b

• NH4+

hKCl∆ SONhKCl

■ NH4+hw

X SONhw

NH

4+ hK

Cl

/SO

NhK

CL

(mg

N k

g-1 )

NH

4+ h

w/S

ON

hw(m

g N

kg-

1)

PPSON (mg N kg-1)

y = 1.39x + 1.63R2 = 0.86

y = 0.67x - 3.60R2 = 0.83

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150

y = 2.88x + 27.78R2 = 0.87

y = 0.56x + 15.49R2 = 0.65

0

50

100

150

200

250

300

350

400

450

500

0 50 100 150

a

b

• NH4+

hKCl∆ SONhKCl

■ NH4+hw

X SONhw

NH

4+ hK

Cl

/SO

NhK

CL

(mg

N k

g-1 )

NH

4+ h

w/S

ON

hw(m

g N

kg-

1)

PPSON (mg N kg-1)

Chapter 4 59

4.4 Discussion

4.4.1 Pool size of SON measured by the different procedures

Size differences among the SON pools may reflect differences in the nature of the

soil SON pool extracted by each technique and may also partially reflect differences in

the actual extraction technique such as soil:extractant ratio, extraction time and filtering

techniques. Little is known about the biological and chemical nature of various SON

pools measured in this study (Chen et al., 2005a,b; Chen and Xu, 2006). However, it is

thought that the water extractable SON pool is comprised largely of the highly labile

organic N which exists in the soil solution or soil macropores and is available as an

immediate substrate for micro-organisms. It may also include a small fraction of SON

located in the smaller pores since the soil structure is disturbed by shaking (McGill et

al., 1986; Curtin and Wen, 1999; Chatigny, 2003).

The hot water extraction method is thought to extract the readily decomposable

fraction of SON that originates from soil microbial biomass, root exudates and lysates

and seems to represent a relatively labile part of the total organic N, although few

researchers have used the hot water method (Curtin et al., 2006). Salt extracts (e.g. KCl

and K2SO4) have the ability to liberate physically adsorbed SON from clay minerals

and/or soil organic matter and hence the SON in salt extracts may represent the

adsorbed or exchangeable fraction of SON.

Similar to the hot water extraction, the hot KCl extraction is also thought to

selectively release the most labile organic N into solution (Curtin and Wen, 1999). A

number of researchers have used hot KCl extracts to determine the potentially available

organic N in a soil by measuring the amount of organic N hydrolysed to NH4+ -N during

a 4 h incubation at 100ºC (Gianello and Bremner, 1986b; Wang et al., 2001; Curtin et

al., 2006). Using this method, Gianello and Bremner (1986b) measured eight of fifty

organic compounds detected in significant proportions in soils or soil hydrolysates. It is

Chapter 4 60

possible that the combination of heat and extractant used in this technique may also

release organic N previously bound in the soil lattice into solution. To our knowledge,

no study has reported the actual SON pool extracted by this method.

The size of the SON pool varied with extractant type and, regardless of soil

depth or forest type, generally followed the order: SONw < SONps < SONKCl < SONhw <

SONhKCl. Concentrations of SONw found in this study had a similar range to SONw

concentrations measured by Chen et al. (2005b) in forest soils of subtropical Australia,

and by Willett et al. (2004) in broadleafed and coniferous woodlands in Great Britain.

The results of this study were consistent with other research in that salt solutions

typically recovered more SON than water (Hannam and Prescott, 2003; Willett et al.,

2004; Chen et al., 2005b; Curtin et al., 2006; Jones and Willett; 2006). The sizes of the

SON pools extracted by KCl, K2SO4 and hot water in this study were comparable to

other studies (Zhong and Makeschin, 2003; Willett et al., 2004; Chen et al., 2005a,b;

Curtin et al., 2006).

In the past, researchers who have used the hot KCl method have generally only

reported the amount of NH4+ released during the extraction. It has been suggested that

hot KCl and hot water extract the same fraction of organic matter and, as such, were not

unique pools (Curtin et al., 2006). In this study the two pools were highly correlated

(Table 4.8), however the SONhKCl pool was generally two to three times larger than the

SONhw pool (Tables 4.3 and 4.6). Similarly, the SONhKCl – SONKCl pool was

approximately two times larger than the SONhw – SONw pool (Fig. 4.1). The

relationship between these two pools remained fairly consistent with soil depth and both

decreased in size with the depth. The SONw, SONhw and SONhKCl pools also generally

decreased in size with soil depth. Organic matter, including soil microbial biomass, is

concentrated in the top centimeters of soil (Sparling, 1997). Hence the decrease in the

Chapter 4 61

size of these pools with soil depth may be related to the decline in organic matter,

including soil microbial biomass, with depth.

Interestingly, the size of the SONKCl and SONps pools remained reasonably

constant with soil depth. Relationships were found between the SONps and SONKCl and

also among SONhKCl, SONhw, and SONw. This result suggests that these groups of

extracts may extract at least partly the same pool from soil (Chen et al., 2005b). The

contrasting effect of soil depth on the size of the SONps and SONKCl pools compared to

the SONhKCl, SONhw, and SONw is further evidence that there are differences in the

chemical and biological nature of these SON pools. Similar to Chen et al. (2005a,b),

this study showed that concentrations of SOC and SON in each pool were highly

correlated (Table 4.8), indicating that organic C and N are closely linked in soil

chemical and biological processes. Previous research has shown that the SON pool can

account for a significant proportion of the TSN in forest soils (Yu et al., 1994; Hannam

and Prescott, 2003; Chen et al., 2005a,b). In this study, the soil SON pool, extracted by

all methods other than water, represented a substantial proportion of the TSN regardless

of land-use, accounting for 23-69% (K2SO4 extracts), 26–60% (KCl extracts), 46–75%

(hot water extracts) and 58-71% (hot KCl extracts) of the TSN.

4.4.2 The effect of land-use change on SON pools

Soil SON enters the soil solution through processes including: 1) leaching from

forest floor and tree canopy; 2) microbial dissolution of soil organic matter (SOM); 3)

microbial debris and metabolites; and 4) root exudation and turnover (Neff et al., 2003;

Kalbitz et al., 2004; Chen and Xu, 2006). Tree species determine the quality and

quantity of organic matter input (e.g. litter, roots and root exudates), and consequently

the composition of leachate, and the size, activity and diversity of the mesofaunal and

microbial communities responsible for the incorporation of organic matter into the soil

system (Attiwill and Adams, 1993; Priha et al., 1999; Smolander and Kitunen, 2002;

Chapter 4 62

Landi et al., 2006). Disturbance and temperature have also been found to influence soil

microbial communities (Cole, 1995; McMurtrie and Dewar, 1997; O'Connell et al.,

2004; Tan et al., 2005). Hence, land-use change may influence soil SON pools through

disturbance to the soil system and changes in the quality and/or quantity of organic

matter input, microbial biomass and diversity, and microclimate.

In this study, the conversion of NF to 1R hoop pine plantation generally reduced

the size of all SON, SOC and SIN pools in all depths. The smaller SON pools in the 1R

soils coincided with higher C:N ratios of soil, litter and roots, which indicates a lower

quality of litter input (Attiwill and Adams, 1993; Chapter 3). Characterisation of the NF

soil and the 1R soil by nuclear magnetic resonance (NMR) spectroscopy found that the

NF soil had a lower alkyl C:O-alkyl ratio than the 1R soil, suggesting that hoop pine

litter materials may contain more recalcitrant components than the NF litter and are

therefore of lower quality (Chen et al., 2004). Furthermore, the higher concentrations of

SONw and SONhw found in the NF soil compared to the 1R soil corresponded to lower

(although not significant) C:No-w and C:No-hw values in the NF soil compared to the 1R

soil. The NF soil has also been found to have greater microbial biomass and diversity

than the 1R soil (Chen et al., 2004; He, 2004; He et al., 2005). This suggests that the

land-use change from a mixed-species native forest to a single-species plantation has

resulted in a reduction in the quality of organic matter and the microbial biomass, which

may have ultimately reduced the size of the soil SON pools. Differences in the maturity

of the organic matter pool in the different forest types may also have an impact on the

size of the SON pool. In comparison to the NF soil, the 1R and 2R plantation soils have

“immature” organic matter pools due to site preparation at the time of harvesting and

replanting. If the 1R forest was allowed to grow for many more years, it is possible that

the organic matter and SON pools in the 1R soil may be similar to those found in the

NF soil.

Chapter 4 63

In a comparison of cedar-hemlock forests and clearcuts, Hannam and Prescott

(2003) found that clearcuts tended to have lower SON contents than the control forests.

However, a comparison of SON in humus of adjacent Norway Spruce and clearcut

found that SON content increased following the forest harvest (Smolander et al., 2001).

In this study, the impact of land-use change from 1R plantation to 2R plantation (both

2R-T and 2R-W) varied slightly with the SON pool and soil depth. In the 0-10 cm

layer, the immediately available fraction of SON measured by the water extract was the

same in the 1R soil and the 2R-T soil, however the 2R-W soil had significantly higher

SONw than the 1R soil. The higher concentration of SONw in the 2R-W soil compared

to the 1R soil may be due to the greater input of labile organic matter in the 2R-W soil

resulting from the decomposition and leaching of organic matter from the windrow

residues.

Leaching of SON from litter and residues is an important source of soil SON.

Harvest residues have been found to be rich in DON (Qualls et al., 2000) and

unpublished data from this study site reveal that the harvest residues are also rich in

SON. Concentrations of SONhw and SONhKCl tended to be higher in the 1R soil than

both the 2R-T and the 2R-W soils, although the difference was only significant between

the 1R and the 2R-T soils. Litter, roots and root exudates are important sources of SON

and can influence the soil SON pool directly, through leaching of readily labile SON,

and indirectly as organic matter quality and quantity can influence the soil microbial

community which is responsible for the mineralization of SOM (Kalbitz et al., 2003;

Chen and Xu, 2006; Christou et al., 2006; Landi et al., 2006; Xu and Chen, 2006).

Compared to the 1R soil which has both litter and roots, the 2R-T soil had little to no

litter layer as litter was removed before planting. While the 2R-W soil would have

input from harvest residues, it is likely that there is little or no input from roots or root

Chapter 4 64

exudates. Therefore, the differences in SON pools between the 1R and 2R plantation

soils may be a result of differences in organic matter input.

Alternatively, the lower SON concentrations in the 2R soils compared to the 1R

soil may potentially be a result of higher gross ammonification rates in the 2R soils,

which were attributed to a flush of mineralisation of native organic N resulting from soil

disturbance, as well as higher soil temperature due to the lack of a closed canopy

(Chapter 3). It is interesting to note that while there was no difference in SONKCl and

SONps between 1R and 2R soils in the 0-10 cm layer, the 1R soil tended to have lower

concentrations of SONKCl and SONps than the 2R soils in the 10-20 and 20-30 cm

layers. Further study is required to explain this result. However the fact that the change

in land-use had contrasting effects on the SON pools extracted using the different

techniques is further indication that there may be differences in the chemical and

biological nature of the SON pools.

The results of this study showed that residue management had a significant

impact on the soil SON pools in the 0-10 cm layer, with the 2R-W soil tending to have

larger SON pools than the 2R-T soil in this layer. It is hypothesized that the difference

in SON pools is most likely due to the greater quantity of organic matter input from

harvest residues in the 2R-W soil compared to the 2R-T soil. The SON pools in the 2R-

T and 2R-W soils were quite similar in the 10-20 and 20-30 cm layers, which may

indicate that the effect of residue management is confined to the topsoil as reported by

Blumfield et al. (2004). As roots of newly established seedlings draw nutrients

primarily from the 0-10 cm soil layer, this result clearly indicates that the presence of

residues increases SON in the soil layer from which trees draw their nutrients. This

highlights the fact that windrowing of residues may not be a wise management practice,

as it effectively places nutrients where there are no trees, and hence wastes a valuable

Chapter 4 65

nutrient source. A better silvicultural technique would be to leave residues in place for

1-2 years and plant through them after windrowing the remaining large residues.

4.4.3 The effect of land-use change on PPSON

In this experiment we used PPSON to assess the ability of the different forest

soils to supply available forms of SON. Factors which influence a soil’s ability to

produce SON would include SOM quantity and quality, and the population and

composition of the soil microbial community. In this study, land-use change was found

to have a similar effect on the PPSON as on SON pools. The higher PPSON in the NF

soil compared to the1R soil is likely to be related to differences in litter quality and

microbial biomass between the two soils as discussed previously. Lower PPSON in the

2R-T soil compared to the 1R and 2R-W soils is likely the result of the presence of less

organic matter in the 2R-T site, which had been cleared of residues prior to planting,

compared to the 1R and 2R-W sites.

In order to assess the usefulness of the various SON pools as indicators of the

soil N supplying power, correlations were performed between the various pools and

PPSON. The PPSON was highly correlated with SONhw and SONhKCl (Table 4.8, Fig.

4.2). This supports the suggestions of other researchers that both pools represent

relatively labile components of TSN (Curtin and Wen, 1999; Curtin et al., 2006). While

the relationship between the SONw and PPSON was significant, it was not as good a

relationship as the others. In this study, SONKCl and SONps were not related to PPSON.

In previous studies, the amount of NH4+ hydrolysed in hot KCl extracts has been

used as a measure of the potentially mineralisable organic N (Gianello and Bremner,

1986b; Curtin et al., 2006). Gianello and Bremner (1986a) compared the NH4+

produced during a 7 d anaerobic incubation at 40ºC with the NH4+ hydrolysed by the hot

KCl method and found that the results were highly correlated. In this study, both

NH4+

hKCl and SONhKCl were highly correlated with PPSON (P<0.0001) and the size of

Chapter 4 66

the pools were affected similarly by land-use change (Table 4.6, Fig. 4.2a). Similarly,

both NH4+

hw and SONhw were highly correlated to PPSON (P<0.001) and were affected

similarly by land-use change (Table 4.3, Fig. 4.2b). It should be noted that the

differences between the NH4+

hKCl pool and the NH4+

KCl pool, and between the NH4+

hw

pool and the NH4+

w pool, were also highly correlated with PPSON (P<0.0001)(data not

shown). This suggests that although the SON pools sizes were different it is possible

that either of these methods may be used as indicators of potentially mineralisable

organic N. Further studies are needed to confirm this.

4.5 Conclusions

The results of this study demonstrate that at this site, the change in land-use

from NF to 1R hoop pine plantation significantly decreased the amount of soil SON as

well as the potential of the soil to produce SON. The major mechanism involved is

likely to be a reduction in organic matter quality resulting from the conversion of the

mixed-species NF compared to the single-species plantation. The conversion of 1R to

2R hoop pine plantation generally resulted in smaller SON pools. Factors contributing

to this reduction include the lack of organic residues and exudates in the 2R soil

compared to the 1R soils and time since disturbance. Residue management was also

found to influence the size and potential production of SON. Trends in the impact of

land use on the SON pools were either similar between soil depths or only noticeable in

the 0-10 cm layer. There were some differences in the effect of land-use on the SON

pools.

Future studies need to focus on gaining a better understanding of the chemical

and biological nature of SON pools in a wide range of soil types, as well as the

microbial processes involved in the dynamics of soil SON. This information would

allow further interpretation of how and why SON pools are influenced by land use and

Chapter 4 67

assist in determining a set of standard methods to measure SON pools and the potential

production of SON.

Chapter 5 68

Chapter 5

Soil microbial biomass, activity and community composition in

adjacent native and plantation forests of subtropical Australia

5.1 Introduction

The soil microbial community plays a central role in organic matter turnover

and the cycling of almost all major plant nutrients, including nitrogen (N) (Smith and

Paul, 1990; Doran and Zeiss, 2000). As such, it is a key factor influencing ecosystem

functioning and the sustainability of the soil resource (Sparling, 1997). Research has

shown that soil micro-organisms are sensitive to land use and management and can be

used to indicate soil health (Sparling, 1997; Chen et al., 2000; Gomez et al., 2000; Li

et al., 2004). Shifts in the soil microbial community (population, activity and/or

composition) associated with land-use change and management techniques may

influence soil N pools and dynamics.

In forest soils, the growth, activity, and composition (i.e. diversity) of the soil

microbial community are affected by abiotic and biotic factors including climate, tree

species, quality and quantity of organic matter input, nutrient availability, and

physical disturbance (Priha et al., 1999; Leckie et al., 2004; Grayston and Prescott,

2005; Hannam et al., 2006). These factors may in turn be influenced by land-use

change (e.g. harvesting and change in stand composition) and silvicultural techniques

(e.g. residue management). While there has been a substantial amount of research

focusing on the impact of tree species and stand composition, as well as harvesting

and residue management, on the soil microbial community in temperate and boreal

forests, there is still little information available for sub-tropical forests, particularly in

relation to a chronosequence of land-use change and management.

A number of soil microbiological parameters have been used to assess the impact

of land-use change and management on the size, activity and composition or diversity

Chapter 5 69

of the soil microbial community (Paul and Clark, 1996). Soil microbial biomass and

respiration can be used as indexes of the size and activity (i.e. CO2-C evolution or C

turnover) of the soil microbial community (Paul and Clark, 1996). Both parameters

tend to be sensitive to land-use change and management and have traditionally been

used as indicators of soil fertility, with decreases indicating a decline in soil quality or

health (Elliott et al., 1996; Chen et al., 2000). The metabolic quotient is used to

indicate the efficiency with which the soil microbial biomass uses organic C

compounds (Alvarez et al., 1995).

Recently, the importance of the soil microbial community composition as an

indicator of soil health has been realised (Yao et al., 2000). Common methods used to

assess shifts in the microbial community as a result of land use and management

include phospholipid fatty acid (PLFA) analysis, denaturing gradient gel

electrophoresis (DGGE), and community level physiological profiles (CLPP)

(Campbell et al., 2003; Bucher and Lanyon, 2005; Grayston and Prescott, 2005;

Cookson et al., 2007). The CLPP techniques are used as an indicator of community

functional diversity based on patterns of carbon (C) source utilization. These

techniques are essentially based on the premise that different micro-organisms have

different abilities to utilize different substrates, hence the response of the microbial

community to a number of different substrates effectively produces a catabolic

fingerprint of the community (Degens and Harris, 1997; Campbell et al., 2003). It is

worth noting that CLPP techniques are not without criticism, and there are a number

of publications in which this subject is discussed in detail (Garland, 1997; Hill et al.,

2000; Preston-Mafham et al., 2002). Essentially, it is important to note that CLPP’s

are only indicators of functional diversity or community composition based on the

ability of the soil microbial community to utilize a range of C substrates. The results

cannot be related to actual species composition and the degree to which they reflect

Chapter 5 70

actual functional diversity remains a question (Garland, 1997; Hill et al., 2000;

Widmer et al., 2001; Campbell et al., 2003; Preston-Mafham et al., 2002). Having

acknowledged that CLPP techniques have limitations, the advantages are that results

are obtained rapidly, and have been found to provide information about the microbial

community that is relevant to nutrient cycling in forest ecosystems (Bucher and

Lanyon, 2005; Grayston and Prescott, 2005).

The most common method of CLPP is BiologTM, in which soil extracts are

used to inoculate microplates containing 95 different C substrates. Colour

development of an indicator dye (tetrazolium) is measured over time to indicate the

rates of C substrate utilization, with changes in the overall patterns of C source

utilisation rates indicating differences in community composition (Garland and Mills,

1991; Campbell et al., 2003). The MicroRespTM method is based on the same

principles but using the whole soil instead of a soil extract, and has been developed

more recently (Campbell et al., 1997). The obvious advantage of MicroRespTM over

BiologTM is the fact that it is conducted on whole soil samples rather than soil

extracts, hence it does not discriminate against organisms which are not readily

extractable and so includes the entire soil microbial community. Furthermore, soil

microbial organisms are not removed from their native environment and subjected to

abnormal conditions as discussed by Campbell et al. (2003). Finally, in the

MicroRespTM method, ecologically relevant C sources are selected by the researcher.

It is possible that some microbial parameters will respond more readily to

land-use change and management than others (e.g. Hannam et al., 2007). In an effort

to obtain a wholistic understanding of the impact of land-use change and management

on the soil microbial community, the microbiological parameters chosen for this study

include measurements of biomass, activity, and community structure using both

BiologTM and MicroRespTM methods to obtain a CLPP.

Chapter 5 71

The objective of this study was to examine the impact of land-use change from

a mixed-species native forest (NF) to a single-species first rotation (1R) hoop pine

plantation and subsequent second rotation (2R) and associated residue management

practices on the soil microbial community.


5.2.1 Sampling

In July 2005, fifteen soil cores were randomly collected from each of the five

24 m2 plots within the NF, 1R, 2R tree row (2R-T) and 2R windrow (2R-W) forests at

three depths (0-10, 10-20 and 20-30 cm), using a 7.5 cm diameter auger and bulked.

All samples were transported to the laboratory where field moist soils were well

mixed and sieved (< 2 mm) and visible roots were removed. Samples were stored at

4 °C until the analysis could be conducted approximately three weeks later.

5.2.2 Microbial biomass C and N

Microbial biomass C and N were measured in all three soil depths (0-10 cm,

10-20 cm and 20-30 cm) using the method described in Chapter 2.

5.2.3 Soil respiration

Soil respiration was measured in the 0-10 cm soil layer using the method

described by Chen et al. (2000). Field moist sub-samples (20 g dry weight

equivalent) were placed in beakers and aerobically incubated at 22 °C and at constant

humidity in sealed 1 L glass jars. Carbon dioxide evolved from the soil was trapped

in 0.1 M NaOH and measured after 24 h, 3 d, 7 d, 14 d, 21 d and 28 d by titration with

0.05 M HCl to the phenolphthalein end point after the addition of 1 M BaCl2. A

number of controls (i.e. jars without soil) were subjected to the same conditions and

used as blanks. The amount of carbon dioxide evolved was calculated from the

Chapter 5 72

difference in molarity between the NaOH from blanks and samples. The metabolic

quotient (qCO2) was calculated as the ratio of respiration (µg CO2-C g-1 h-1) to MBC.

5.2.4 Community level physiological profiles

Carbon source utilisation patterns (often referred to as community level

physiological profiles or CLPP) in the 0-10 cm soil layer were assessed using both

BiologTM and whole soil MicroRespTM techniques. Analysis was performed soon

after sample processing. BiologTM profiles were obtained for each of the five

replicates within the NF, 1R, 2R-T and 2R-W forests using the method described by

Widmer et al. (2001). In brief, a 10 g sub-sample of field moist soil (dry weight

equivalent) was suspended in 90 ml of 0.9% NaCl and shaken at 300 rev min-1 for 30

min. Suspensions were allowed to settle for 10 min before 10-fold diluted samples

were prepared resulting in final dilutions of 10-2. BiologTM GN plates were directly

inoculated with 125 μl of the diluted suspensions after which plates were incubated at

20 ºC and absorbance measured with a BiologTM microplate reader (B62302A) at 595

nm a minimum of twice daily for 4 d (i.e. 96 h). Any negative readings were set to

zero and the average well colour development (AWCD) of the individual plates at

each measurement time was calculated according to Garland and Mills (1991). The

72 h readings were used to calculate total plate activity, substrate richness and

Shannon’s diversity index (SDI) according to Zak et al. (1994) with the threshold

absorbance value set to 0.1 to eliminate false positive readings (Garland, 1997). In

brief, substrate richness for each plate was calculated as the number of substrates used

by the microbial community (i.e. the number of readings > 0.1), and total plate

activity, used as an indicator of substrate utilisation, was calculated as the sum of all

absorbances >0.1. The SDI was calculated using equation 5.1:

H = -∑ pi(lnpi) (5.1)

where pi = the absorbance of each individual well divided by the sum of absorbances in

all wells.

Chapter 5 73

Prior to multivariate analysis, individual well absorbance values were normalised by

AWCD to account for possible differences in inoculation densities between samples

(Garland and Mills, 1991).

The MicroRespTM colourimetric detection plates were prepared and profiles

obtained according to Campbell et al. (2003). Briefly, soil samples, all of which were

at > 40% of the water holding capacity (WHC), were conditioned at 25˚C in a humid

environment for 2 d prior to analysis. Based on the work of Campbell et al. (1997

and 2003) fifteen ecologically relevant and easily dissolvable C sources were selected

(Table 5.1) and stock solutions were made from which 25 ml aliquots could be

dispensed to deliver 30 mg C per g of soil water to each deep well. MicroRespTM

analysis was carried out in triplicate. The C solutions and water (to be used as basal

respiration) were dispensed into a deep well plate before soil sub-samples, each with a

total volume of 300 μl (ca.1.5 g), and were placed into each well of the deep well

plate using the method described by Campbell et al. (2003). The deep well plate was

then immediately sealed with a gasket and detection plate (Fig. 5.1) and incubated at

25 °C for 6 h. In order to calculate colour development (C utilisation), the detection

plate colour was measured as absorbance at 590 nm immediately before and after the

6 h incubation using a BiologTM microplate reader (B62302A). The 6 h absorbance

data were normalised for any differences in detection plates recorded prior to

incubation. Basal respiration (for water) and substrate induced respiration (SIR) (for

individual C substrates) was calculated as CO2-C evolved according to Campbell et al.

(2003). For each plate, the average amount of CO2-C that evolved per sample was

calculated and used to normalise individual well responses before multivariate

analysis was conducted.

Chapter 5 74

Table 5.1: Carbon (C) sources used in the MicroRespTM method

Carbon Source

1. L-Alanine 9. L-Arabinose

2. Arginine 10. L-Cysteine hydrochloride

3. Citric Acid 11. D-Fructose

4. D-Galactose 12. D-Glucose

5. γ-Aminobutyric acid 13. L-Lysine

6. L-Malic acid 14. N-Acetylglucosamine (NAGA)

7. Oxalic acid 15. Trehalose

8. 3,4-Dihydroxybenzoic acid

Fig 5.1: MicroRespTM plate system comprising a deep-well microtiter plate to hold soil, an

interconnecting gasket, and a top plate containing detection gel.

Chapter 5 75


A split-plot factorial analysis of variance (ANOVA) was used to explore

differences within biomass measurements based on the factors forest type and soil

depth. Where significant differences were detected, pair-wise comparisons were made

using the Tukey adjustment for multiple range testing. One-way ANOVAs were used to

evaluate the soil respiration and metabolic quotient data. For the BiologTM profiles, a

one-way ANOVA was carried out on the whole plate metric data (i.e. AWCD, total

plate activity and SDI data), while a binomial logistic regression was conducted on the

substrate richness data. One-way ANOVAs were also conducted on the MicroRespTM

substrate induced respiration (SIR) data from individual C substrates. Least significant

difference (LSD, P<0.05) was used to separate treatment means when differences were

significant. The assumptions of normality and equal variance were satisfied prior to this

analysis being conducted in SAS version 9.1.3.

Patterns of C source utilisation among the forest types were examined by

principal components analysis (PCA) and non-metric multidimensional scaling (NMS)

using Bray-Curtis distance measure. For the NMS analysis the multiple response

permutations procedure (MRPP) was used to determine whether groups (i.e. forest

types) were statistically different, and Bonferroni adjustment was used to ensure the

overall error rate was 0.05. It should be noted that MRPP tests for differences among

groups based on both location and variation (Mielke and Berry, 2001). Hence,

significant differences found among the forest types may be due to either distance

between groups or variability within groups. Cluster analysis was also performed using

Bray-Curtis as the distance measure with graphical representations based on complete

linkage for the hierarchical clustering. For the MicroRespTM data, substrates that did

not induce respiration were removed for analysis. All multivariate analysis was carried

Chapter 5 76

out on normalised data from the BiologTM and MicroRespTM profiles using the statistical

package R version 2.4.0.

5.3 Results

5.3.1 Microbial Biomass

A significant interaction was found between forest type and soil depth for both

MBC and MBN (data not shown). Hence the extent to which forest type affected MBC

and MBN varied with depth. In the 0-10 cm layer, MBC ranged from 1186 μg g-1 in the

2R-T soils to 2156 μg g-1 in the NF soil, with values decreasing with soil depth (Table

5.2). The NF soil had significantly higher MBC than the 1R soil in the 0-10 cm layer,

but there was no significant difference in MBC between 1R and 2R soils or between

2R-T and 2R-W soils at any depth.

The MBN ranged between 130 μg g-1 in the 2R-T soil and 231 μg g-1 in the NF

soil, and also decreased with depth (Table 5.2). Although the NF soil tended to have

higher MBN than the 1R soil in all depths, the differences were not significant. In the

0-10 cm layer, the 1R soil had significantly higher MBN than the 2R-T soil, however

values were similar at lower depths. There was no significant difference in MBN values

between the 2R-T and 2R-W soils. The microbial C:N ratio (ratio of MBC to MBN),

ranged between 7.3 and 9.4 in the 0-10 cm layer and tended to increase with depth.

There were generally no differences in the microbial C:N ratio among the forest types.

The MBC constituted up to 2.5% of the soil total C, while MBN constituted up to 3.8%

of the soil total N, neither were significantly affected by forest type (Table 5.2).

Concentrations of MBC in the 0-10 cm were highly correlated with soil total C

and N, hot water extractable organic C and N and hot KCl extractable organic C and N.

There was a negative (although not significant) relationship between MBC and the soil

C:N ratio (Table 5.3). Concentrations of MBN in the 0-10 cm layer had similar

Chapter 5 77

relationships with total C and N, pools of SOC and SON and soil C:N ratio as

concentrations of MBC.

Table 5.2: Microbial biomass carbon (MBC) and nitrogen (MBN) contents in the adjacent

native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree

row (2R-T), and second rotation windrow (2R-W) at the Yarraman site, subtropical Australia.

Values are means (n=5) and if followed by the same letter are not significant at the 5% level of

significance.

Forest Type MBC

μg g-1

MBN

μg g-1

Microbial

C:N

Microbial C /

Total C (%)

Microbial N /

Total N (%)

0-10 cm

NF 2156a 231a 9.4a 2.5a 3.1a

1R 1365b 188ab 7.3a 2.0a 3.8a

2R-T 1186b 130c 9.3a 2.1a 2.8a

2R-W 1353b 156bc 8.9a 2.2a 3.3a

10-20 cm

NF 1160a 123a 9.6a 2.1 a 2.5a

1R 900ab 112ab 8.1a 2.2 a 3.1a

2R-T 684b 64b 11.0a 1.5 a 1.7a

2R-W 757b 74b 10.5a 2.2 a 2.4a

20-30 cm

NF 590a 56a 10.7ab 1.7a 1.8a

1R 424a 48a 9.0b 1.6a 2.0a

2R-T 544a 45a 13.1a 2.0a 1.9a

2R-W 403a 30a 13.1a 1.6a 1.5a

Tab

le 5

.3: S

pear

man

rank

cor

rela

tion

coef

ficie

nts

betw

een

soil

mic

robi

al a

nd n

utrie

nt p

aram

eter

s in

the

0-10

cm

laye

r of a

djac

ent n

ativ

e fo

rest

(NF)

, 53

y-ol

d fir

st

rota

tion

hoop

pin

e pl

anta

tion

(1R

), 5

y-ol

d se

cond

rota

tion

tree

row

(2R

-T) a

nd se

cond

rota

tion

win

drow

(2R

-W) a

t the

Yar

ram

an si

te, s

ubtro

pica

l Aus

tralia

.

MB

C

MB

N

Res

p. R

ate

TC

TN

C:N

ratio

SO

Nhw

SO

Chw

SO

NhK

CL

SOC

hKC

l

MB

C

1

MB

N

0.94

***

1

Res

p. R

ate

0.60

* 0.

57*

1

TC

0.83

***

0.81

***

0.51

* 1

TN

0.77

***

0.77

***

0.50

* 0.

96**

* 1

C:N

ratio

-0

.40

-0.4

2 -0

.46*

-0

.29

-0.4

3 1

SON

hw

0.85

***

0.75

***

0.61

**

0.70

***

0.67

***

-0.3

4 1

SOC

hw

0.88

***

0.77

***

0.71

***

0.74

***

0.69

***

-0.3

3 0.

95**

* 1

SON

hKC

L 0.

85**

* 0.

82**

* 0.

68**

* 0.

78**

* 0.

70**

* -0

.28

0.86

***

0.92

***

1

SOC

hKC

l 0.

85**

* 0.

79**

* 0.

70**

* 0.

75**

* 0.

67**

* -0

.26

0.88

***

0.93

***

0.99

***

1

*Sig

nific

ance

at P

< 0

.05;

**S

igni

fican

ce a

t P <

0.0

1; S

igni

fican

ce a

t ***

P <

0.00

1; n

= 2

0

MB

C is

mic

robi

al b

iom

ass

carb

on; M

BN

is m

icro

bial

bio

mas

s ni

troge

n; R

esp.

rate

is re

spira

tion

rate

; TC

is to

tal c

arbo

n; T

N is

tota

l nitr

ogen

; C:N

is th

e ra

tio o

f TC

to T

N; S

ON

hw is

hot

wat

er e

xtra

ctab

le s

olub

le o

rgan

ic n

itrog

en; S

OC

hw is

hot

wat

er e

xtra

ctab

le s

olub

le o

rgan

ic c

arbo

n; S

ON

hKC

l is

hot 2

M K

Cl e

xtra

ctab

le s

olub

le

orga

nic

nitro

gen;

SO

ChK

Cl i

s hot

2 M

KC

l ext

ract

able

solu

ble

orga

nic

carb

on.

Chapter 5 79

5.3.2 Soil respiration and metabolic quotients

The average soil respiration rate over the 28 d incubation ranged from 0.78 μg

CO2-C g-1 h-1 in the 2R-T soil to 1.12 CO2-C g-1 h-1 in the NF soil (Fig. 5.2), while

cumulative CO2-C production for the 28 d incubation period was between 530 μg CO2-

C g-1 in the 2R-T soil and 755 μg CO2-C g-1 in the NF soil (Fig 5.3). Both the average

respiration rate and the cumulative CO2-C production were consistently higher in the

NF soil compared to the 1R soil, however no significant differences were found among

the plantation soils (Figs. 5.2 and 5.3). Metabolic quotients ranged from 0.52 in the NF

soil to 0.74 in the 2R-W soil, and were not significantly different among the forest

types. The average respiration rate was positively correlated with soil total C and N

(P<0.05), negatively correlated with soil C:N ratio (P<0.05) and positively correlated

with pools of soluble organic C and N extracted by hot water and hot KCl (Table 5.3).

0

0.2

0.4

0.6

0.8

1

1.2

1.4

NF 1R 2R-T 2R-W

Res

pira

tion

(µg

CO

2-C

g-1

h-1 )

/ M

etab

olic

quo

tient

(µ

g C

O2-

C m

g-1

mic

robi

al C

h-1

)

Forest Type

0

0.2

0.4

0.6

0.8

1

1.2

1.4

NF 1R 2R-T 2R-W

Res

pira

tion

(µg

CO

2-C

g-1

h-1 )

/ M

etab

olic

quo

tient

(µ

g C

O2-

C m

g-1

mic

robi

al C

h-1

)

Forest Type

Fig. 5.2: Respiration rate (black bars) and metabolic quotient (grey bars) in the 0-10 cm soil layer of

adjacent native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree

row (2R-T), and second rotation windrow (2R-W) at the Yarraman site, subtropical Australia (standard

errors shown by vertical bars).

Chapter 5 80

0

100

200

300

400

500

600

700

800

900

0 5 10 15 20 25 30

NF

1R

2R-T

2R-WC

umul

ativ

e re

spira

tion

(µg

CO

2-C

g-1)

Time (d)

0

100

200

300

400

500

600

700

800

900

0 5 10 15 20 25 30

NF

1R

2R-T

2R-WC

umul

ativ

e re

spira

tion

(µg

CO

2-C

g-1)

Time (d)

Fig. 5.3: Cumulative respiration rate in the 0-10 cm soil layer of adjacent native forest (NF), 53

y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T), and

second rotation windrow (2R-W) at the Yarraman site, subtropical Australia (standard errors

shown by vertical bars).


5.3.3.1 BiologTM

Analysis of the BiologTM GN plate data after 72 h of incubation found that the

NF soils had significantly higher AWCD, total plate activity, SDI and substrate richness

than the 1R soils (Table 5.4). The AWCD, plate activity, SDI and substrate richness

were similar between the 1R and 2R-T soils, but were significantly higher in the 2R-W

soils than in the 1R soils. No significant difference was found between the 2R-T and

2R-W soils (Table 5.4). Colour began to develop in the plates after 24 h of incubation

and over the 96 h incubation period the AWCD tended to follow the order NF > 2R-W

> 2R-T > 1R (Fig. 5.4).

Chapter 5 81

Table 5.4: Average well colour development (AWCD), total plate activity, Shannon’s diversity

index (SDI) and substrate richness calculated from Biolog optical density data (OD>0.1) of the

soil extracts from the 0-10 cm soil layer of the adjacent native forest (NF), 53 y-old first rotation


windrow (2R-W) at the Yarraman site, subtropical Australia.

Forest Type AWCD Activity SDI Richness

NF 0.28a 26.2a 3.16a 65a

1R 0.16c 14.3c 2.63c 50b

2R-T 0.21bc 18.7bc 2.85bc 55b

2R-W 0.26ab 23.1ab 3.02ab 63a

Values for AWCD, activity and SDI are means (n=5) and if followed by the same letter are not significant at the 5% level of significance. Values for richness are means and if followed by the same letter have similar likelihood of colour development

0.0

0.1

0.2

0.3

0.4

0 24 48 72 96

NF

1R

2R-T

2R-W

AWC

D (O

.D.)

Time (h)

0.0

0.1

0.2

0.3

0.4

0 24 48 72 96

NF

1R

2R-T

2R-W

AWC

D (O

.D.)

Time (h)

Fig. 5.4: Average well colour development (AWCD) over the 96 h incubation period of

BiologTM GN plates inoculated with soil extracts from the 0-10 cm soil layer of the adjacent

native forest (NF), 53 y-old first rotation hoop pine plantation (1R), 5 y-old second rotation tree

row (2R-T), and second rotation windrow (2R-W) at the Yarraman site, subtropical Australia

(standard errors shown by vertical bars).

Chapter 5 82

Analysis of the patterns of substrate use in Biolog GN plates using PCA showed

that PC1 accounted for only 18.8% of the variation, while PC2 accounted for 14.7%

(collectively the first two PC’s only accounted for 33.5% of the total variation). It took

the first 11 PC’s to account for 90% of the variation. Neither PCA nor NMS analysis of

the BiologTM profile data showed clear separations among the treatments (Fig. 5.5 and

5.6). However, cluster analysis of the BiologTM profiles grouped replicates of the NF

soil and the 1R soil into individual clusters (Fig. 5.7). The 1R samples were linked

together at a lower Bray-Curtis distance (0.24) than the NF soils (0.32), indicating that

the 1R soil replicates were more closely related to each other than the NF soils

replicates. Replicates from the 2R plantation soils (with one exception – number 9)

tended to group together in two clusters, however the 2R-T and 2R-W soils were not

distinguished from each other (Fig. 5.7).

Fig. 5.5: Principal component analysis (PCA) of the normalized absorbance data of the 95 C-sources

from the BiologTM profiles of the soil extracts from the 0-10 cm soil layer of the adjacent native forest

(NF) (numbers 16-20), 53 y-old first rotation hoop pine plantation (1R) (numbers 11-15), 5 y-old second

rotation tree row (2R-T) (numbers 1-5), and second rotation windrow (2R-W) (numbers 6-10), at

incubation time of 72 h.

Chapter 5 83

Fig. 5.6: Non-metric multidimensional scaling (NMS) ordination plot of the normalized absorbance data

of the 95 C-sources from the BiologTM profiles of the soil extracts from the 0-10 cm soil layer of the

adjacent native forest (NF) (numbers 16-20), 53 y-old first rotation hoop pine plantation (1R) (numbers

11-15), 5 y-old second rotation tree row (2R-T) (numbers 1-5), and second rotation windrow (2R-W)

(numbers 6-10), at incubation time of 72 h.

Dis

tanc

eD

ista

nce

Fig. 5.7: Cluster analysis of BiologTM

profiles of the soil extracts from the 0-10 cm soil layer of the

adjacent native forest (NF) (numbers 16-20), 53 y-old first rotation hoop pine plantation (1R) (numbers

11-15), 5 y-old second rotation tree row (2R-T) (numbers 1-5), and second rotation windrow (2R-W)

(numbers 6-10), at incubation time of 72 h. Scale indicates Bray-Curtis distance with graphical

representations based on complete linkage for the hierarchical clustering.

NF soils

1R soils2R soils

Chapter 5 84

5.3.3.2 MicroRespTM

The mean basal respiration, (with no C source) measured from the wells

containing water only, were 1.03, 0.99, 0.86 and 0.79 μg CO2-C g-1h-1 in the 1R, NF,

2R-W and 2R-T soils respectively. The only significant difference in the basal

respiration was between the 1R soil and the 2R-T soil. Three of the fifteen C substrates,

namely γ-Aminobutyric acid, 3,4-Dihydroxybenzoic acid, and L-Cysteine hydrochloride

produced undetectable SIR in all soil samples. Table 5.5 displays mean SIR of the

remaining twelve C substrates. The highest level of SIR in all forest types was observed

with D-Fructose, while the lowest was observed with L-Lysine. The NF soil tended to

have higher SIR than the 1R soil, although the difference was not always significant

(Table 5.5). In most cases, the 1R soil had similar SIR to the 2R soils, however there

were some instances (e.g. D-Glucose, L-Alanine, Trehalose) where SIR was higher in the

1R soil than either or both of the 2R-T and 2R-W soils. No significant differences were

found between the 2R-T and 2R-W soils (Table 5.5).

PCA of the MicroRespTM data showed that PC 1 accounted for 71% of the

variation while PC 2 accounted for a further 12 % (a total of 83% for the first two PC’s

with 90% of the variation accounted for by the third PC). However, forest types were

not separated into distinct groups based on the PCA (Fig. 5.8). In contrast, NMS

analysis of the MicroRespTM profiles revealed replicates of the different forest types

tended to group together (Fig. 5.9). Further analysis using MRPP revealed that the

pattern of SIR in the NF soil was significantly different from the pattern produced for

the 1R soil (δ=0.0766, P=0.0080). The pattern of SIR in the 1R soil was significantly

different from that of the 2R-T soil (δ=0.1246, P=0.0060) and the 2R-W soil (δ=0.1548,

P=0.0070). However, no significant difference was found between the patterns

produced by the 2R-T and 2R-W soils (δ=0.1985, P=0.0170). These values are based

on the P value obtained using Bonferroni adjustment (P=0.0083).

Chapter 5 85

With the exception of one of the 2R-W replicates (sample number 6), cluster

analysis of the MicroRespTM SIR profiles separated the NF, 1R, 2R-T and 2R-W

replicates into distinguished clusters (Fig. 5.10). The degree of similarity/relatedness

within the NF and 1R clusters was higher in the MicroRespTM profiles than in the

BiologTM profiles, with replicates of the NF and the 1R soils linking together at Bray-

Curtis distances of approximately 0.10 and 0.11 respectively (Fig.5.10). Cluster

analysis of the MicroRespTM profiles yielded different basic dendogram topology to the

BiologTM profiles with the NF and 1R samples being most similar (linking together at a

distance of 0.25) followed by 2R-W which was linked with 1R and NF at a relative

distance of 0.3, while 2R-T was most different from the other soils (Fig.5.10).

Tab

le 5

.5:

Mic

roR

esp

C s

ourc

e su

bstra

te i

nduc

ed r

espi

ratio

n (S

IR)

in t

he 0

-10

cm s

oil

laye

r of

the

adj

acen

t na

tive

fore

st (

NF)

, 53

y-ol

d fir

st r

otat

ion

hoop

pin

e

plan

tatio

n (1

R),

5 y-

old

seco

nd ro

tatio

n tre

e ro

w (2

R-T

), an

d se

cond

rota

tion

win

drow

(2R

-W) a

t the

Yar

ram

an si

te, s

ubtro

pica

l Aus

tralia

. V

alue

s are

mea

ns (n

=5) a

nd

if fo

llow

ed b

y th

e sa

me

lette

r are

not

sign

ifica

nt a

t the

5%

leve

l of s

igni

fican

ce.

Fo

rest

Type

L-

Ala

nine

A

rgin

ine

Citr

ic

acid

D-G

alac

tose

L-

Mal

ic

aci

d

Oxa

lic

acid

L-

Ara

bino

se

D-F

ruct

ose

D-G

luco

se

L-Ly

sine

N

AG

A

Treh

alos

e

μg C

O2-

C g

-1 h

-1

NF

0.62

a 0.

27a

0.73

a 0.

87a

0.54

a 0.

66a

0.29

a 1.

1a

0.71

a 0.

27a

1.04

a 0.

60a

1R

0.60

a 0.

12b

0.66

ab

0.71

ab

0.28

b 0.

41b

0.18

ab

1.1a

0.

66a

0.08

b 1.

01a

0.63

a

2R-T

0.

50ab

0.

04b

0.50

b 0.

70ab

0.

16b

0.35

b 0.

08b

0.9a

0.

50b

0.01

b 0.

80ab

0.

23b

2R-W

0.

34b

0.11

b 0.

51b

0.60

b 0.

13b

0.28

b

0.13

ab

0.9a

0.

38b

0.05

b 0.

71b

0.38

ab

Chapter 5 87

Fig. 5.8: Principal component analysis (PCA) of the normalized absorbance data of the 12 C-sources

from the MicroRespTM profiles of the 0-10 cm soil layer of the adjacent native forest (NF) (numbers 16-

20), 53 y-old first rotation hoop pine plantation (1R) (numbers 11-15), 5 y-old second rotation tree row

(2R-T) (numbers 1-5), and second rotation windrow (2R-W) (numbers 6-10), at incubation time of 6 h.

Fig 5.9: Non-metric multidimensional scaling (NMS) ordination plot of the normalized absorbance data

of the 12 C-sources from the MicroRespTM profiles of the 0-10 cm soil layer of the adjacent native forest



incubation time of 6 h..

Chapter 5 88

Dis

tanc

eD

ista

nce

Fig 5.10: Cluster analysis of MicroRespTM profiles of the 0-10 cm soil layer of the adjacent native forest



incubation time of 6 h. Scale indicates Bray-Curtis distance with graphical representations based on

complete linkage for the hierarchical clustering.

5.4 Discussion

5.4.1 Soil microbial biomass and respiration

The mechanisms through which the land-use change from the NF to the hoop

pine plantation may affect the soil microbial community are related to the change in tree

species and the disturbance associated with logging of the NF as well as subsequent

establishment of the 1R plantation and ensuing silvicultural techniques. Shifts in tree

species may result in changes in the quality and quantity of both above ground (litter)

and below ground (roots) organic matter input, as well as changes in microclimate

(Priha and Smolander, 1997). The NF in this study is composed of a mixture of tree

species including both hardwood and conifer species, whilst the plantation is a single-

species conifer forest. It has been suggested that due to the presence of a waxy surface

layer and higher concentrations of recalcitrant compounds (e.g. phenolic compounds),

conifer needles are more resistant to decomposition than leaf litter from hardwoods

(Priha and Smolander., 1997; Li et al., 2004). Past studies have found a decline in

NF soils 1R soils

2R-W soils

2R-T soils

Chapter 5 89

microbial biomass associated with land-use change from native forest to plantation, as

well as differences in soil respiration associated with different stand types (Waldrop et

al., 2000; Priha et al., 2001; Chen et al., 2004). A comparison of beech (a northern

hemisphere hardwood) and conifers (Scots pine and Norway spruce) found that MBN

was significantly lower in the conifer stand compared to the beech stand (Zhong et al.,

2006). Similarly, Priha et al. (2001) found lower MBC and respiration under conifers

(Scots pine and Norway spruce) compared to hardwoods (silver birch). However, Priha

and Smolander (1997) compared hardwoods (silver birch) and conifers (Scots pine and

Norway spruce) and found that stand type had no clear effect on MBC and MBN after

24 years.

In this study, concentrations of MBC and MBN (in all depths) and respiration

rates in the NF and plantation sites were comparable to those reported for other

plantation soils in south-east Queensland (Chen et al., 2002; Chen and Xu, 2005). The

land-use change from NF to 1R hoop pine plantation was associated with a significant

reduction in the concentration of MBC in the 0-10 cm layer. Respiration rate, both on

an hourly basis and over the 28 d incubation period, was also reduced as a result of the

land-use change. The NF soil also tended to have higher MBN and lower metabolic

quotient, although the difference was not significant. Past research at this study site

found that the NF soil had a lower alkyl C:O-alkyl ratio than the 1R soil (Chen et al.,

2004). Also, analyses of litter, root and soil samples show that the NF had significantly

lower C:N ratios and higher SOC content than the 1R forest (results presented in

Chapter 3 and Chapter 4). Together, these results indicate that the higher MBC and

respiration in the NF compared to the 1R soil are associated with higher quality and

quantity of organic matter input in the NF.

As discussed in Chapter 4, the hot water and hot KCl extractable soluble organic

C (SOC) and N (SON) pools are believed to represent labile fractions of soil organic C

Chapter 5 90

and N pools (Curtin and Wen, 1999; Chen et al., 2004; Curtin et al., 2006). The MBC,

MBN and respiration were positively correlated with soluble organic C and N extracted

by hot water and hot KCl, as well as soil total C and total N, and were negatively related

to the soil C:N ratio (Table 5.3). Higher percentages of total C and total N and larger

pools of labile SON and SOC in the NF soil compared to the 1R soil (results presented

in Chapter 3 and 4), together with the strong positive relationship tend to suggest that

the NF has greater quantity and quality of organic matter available for decomposition by

the microbial community than the 1R forest. Smolander and Kitunen (2002) found that

microbial biomass and activity were correlated with DON, while Li et al. (2004) found

that MBC and MBN were correlated with soil total C and total N. The negative

relationship of microbial parameters with the soil C:N ratio indicates that in the

plantation soils, which have higher C:N ratios than the NF soil (Chapter 3), N is either

limiting or that there is competition between plants and microbes.

Plantation harvesting and the establishment of a subsequent hoop pine rotation

may cause disturbance and compaction of the soil system as well as changes in the

quantity and quality of organic matter and the microclimate, which may in turn affect

the soil microbial community (Breland and Hansen, 1996; Li et al., 2004). Research has

revealed varying effects of harvesting on the soil microbial community, with researchers

reporting no effect (e.g. Hannam et al., 2006), and decreases in biomass and respiration

(e.g. Luizao et al., 1992; Pietikäien and Fritze, 1993). Residue management may

control the availability of organic matter and soil microclimate and therefore may also

affect the soil microbial community (Chen and Xu, 2005). A study in hoop pine

plantations of subtropical Australia indicates that residue retention may decrease

nutrient loss and increase soil C and N (Blumfield and Xu, 2003). Furthermore, solid-

state 13C NMR analysis of soils in hoop pine and eucalypt plantations of subtropical

Australia revealed residue retention improved the quality of soil organic matter

Chapter 5 91

(Mathers and Xu, 2003 a,b). A study undertaken in six year old slash pine plantations

of subtropical Australia revealed that residue retention increased MBC and MBN, but

had no significant effect on soil respiration and metabolic quotient (qCO2) (Chen and

Xu, 2005).

In this study, there was some indication that harvesting and residue management

may influence the microbial community, however the lack of statistical significance

suggests that the impact is not highly significant five years into the 2R of the hoop pine

plantation. As discussed by Hannam et al. (2006) there is some evidence to suggest

that the soil microbial community may respond to harvesting immediately, but then

return to pre-harvest levels within 4-5 years.


Community level physiological profiles (CLPP), such as BiologTM and

MicroRespTM, although not without problems, produce results rapidly. BiologTM in

particular has been used regularly in forest soil research (e.g. Li et al., 2004; Bucher and

Lanyon, 2005; Grayston and Prescott, 2005) as a tool to indicate relative differences in

community composition or “functional diversity”, based on differences in patterns of C

substrate utilisation. In this study, substrate utilisation of the C sources in the BiologTM

GN plate was relatively low, with mean AWCDs ranging between 0.16 and 0.28. This

result may indicate that the C sources are being utilized by micro-organisms which are

present in the soil in low numbers or by slow growing bacteria (Campbell et al., 1997;

Hill et al., 2000). For the MicroRespTM profiles, SIR was also low when compared to a

study by Campbell et al. (2003), however similar to that study, the highest level of SIR

in all forest types of this study was observed with D-Fructose, while the lowest was

observed with L-Lysine. Results of the two profiling techniques indicate that the

MicroRespTM technique was better at separating the forest types based on patterns of C

substrate utilization. Campbell et al. (2003) reported similar results. Differences in the

Chapter 5 92

ability to separate the forest types (both NMS and cluster analysis) as well as

differences in the dendograms of the cluster analysis between the two methods may be

related to a number of factors. These include: 1) greater replication of samples in the

MicroRespTM technique; 2) BiologTM GN plates had more C sources than the

MicroRespTM plates, which were not necessarily as relevant as the sources used in the

MicroRespTM method; and 3) use of whole soils versus soil extracts. Furthermore, there

is a difference in the duration of the incubation between the methods (6 h for

MicroRespTM and greater than 24 h BiologTM). Hence, while BiologTM results are

usually considered to reflect microbial activity, when compared with MicroRespTM

results, they may actually be considered to reflect growth (Campbell et al., 2003).

While this possibility is acknowledged, the term “activity” will be used for BiologTM

results discussed in this paper. It is worth noting that although PCA is commonly used

to analyse CLPP data, in this and other studies (e.g. Priha et al., 2001), treatments were

not separated using PCA. Compared to PCA, which is based on measurements of

variance in the data, NMS and cluster analysis are based on distance measures

(Anderson, 1984), and both were more successful in separating forest types than PCA.

As discussed previously, land use and management may not only affect the size

and activity of the soil microbial community, but also influence its composition or

functional diversity. This may result in a change in physiological capacity of the soil

microbial community and may in turn affect organic matter decomposition and soil N

cycling (Garland, 1997; Waldrop et al., 2000; Larkin, 2003; Carney and Matson, 2006).

The BiologTM whole plate metric data (i.e. AWCD, activity, SDI and richness) indicated

that the conversion from the NF to the 1R hoop pine plantation was associated with

significant reductions in the activity, diversity and richness of the microbial community.

Results of the MicroRespTM analysis revealed that although the two forest types had

similar basal respiration, the NF soil tended to have a higher SIR than the 1R soil.

Chapter 5 93

Further analysis of the patterns of substrate utilization revealed separation of the NF and

1R soil into distinguished groups in both the BiologTM (cluster analysis only) and the

MicroRespTM profiles (NMS and cluster analysis). These results suggest that the

microbial community in the NF soil has greater diversity and activity, and a different

composition to the 1R soil. This result is supported by previous work at this study site

in which greater microbial and fungal diversity, based on the culture-independent,

DNA-fingerprinting method, was found in the NF soil compared to the 1R soil (He,

2004; He et al., 2005). As discussed previously, litter, root and soil data from this and

previous studies at this site tend to suggest that the change in tree species/stand

composition has reduced the quality and quantity of organic matter input, which may

have contributed to the shift in soil microbial community composition and diversity

(Chapters 3 and 4; Chen et al., 2004).

As discussed earlier, harvesting of the 1R forest and conversion to 2R plantation

and the ensuing residue management strategies, may affect the soil microbial

community (Breland and Hansen, 1996; Li et al., 2004; Chen and Xu, 2005).

Comparison of both BiologTM and MicroRespTM profiles among the 1R and 2R soils

indicates that there were some differences in the microbial community composition of

the 1R and 2R soils. However, the differences among the 1R and 2R soils were not as

clearly defined as the differences between the NF and 1R soils. Earlier chapters have

discussed differences in the quality and quantity of organic matter (e.g. root, litter and

soil C:N ratios, and some pools of SON and SOC) associated with the conversion of 1R

to 2R hoop pine plantation (Chapters 3 and 4). It is likely that these differences have

contributed to the difference in microbial community composition or functional

diversity between the 1R and 2R forests. Although the 2R-T and 2R-W appeared to be

reasonably well separated in the cluster and NMS analysis of the MicroRespTM data,

overall there was no significant difference in soil microbial community composition or

Chapter 5 94

diversity associated with residue management. This may be partly due to the large

variability within the 2R-W site that likely results from the spatial heterogeneity of

windrow material.

5.5 Conclusion

The results from this study indicate that the land-use change from the NF to

the1R hoop pine plantation is associated with reductions in soil microbial biomass and

activity, and changes in the composition of the soil microbial community. These

changes are likely a consequence of reductions in the quantity and quality of organic

matter inputs associated with the land-use change. Whilst there is no evidence of

changes in population size and respiration associated with the conversion of 1R to 2R

hoop pine plantation, there is some indication, from the CLPP data, of differences in the

microbial community composition between the 1R and 2R soils. Residue management

did not appear to have a significant influence on any of the microbial parameters,

suggesting that the soil microbial community is resistant to this management technique.

However, it is also possible that this result may be the consequence of the fact that

samples are only representative of one sampling time, which occurred approximately

five years after harvesting of the 1R plantation and establishment of the 2R plantation.

Further studies would be required before a difference in microbial community

composition associated with residue management could be confirmed or rejected.

Long-term experiments, with regular sampling would improve our understanding of the

impact of land use and residue management on the soil microbial community dynamics

in subtropical Australia.

Chapter 6 95

Chapter 6

Seasonal Influences on Soil Nitrogen Pools and Transformations in

Adjacent Native Forest and Hoop Pine Plantations

6.1 Introduction

Soil nitrogen (N) cycling and availability are driven by a number of factors

including the size, composition and activity of the soil microbial community, substrate

quality and quantity, and environmental conditions such as temperature, moisture, and

the frequency of drying and rewetting (Stevenson and Cole, 1999; Compton and Boone,

2002; Templer et al., 2003; Miller et al., 2005; Krave et al., 2007). These variables are

in turn influenced by seasonal conditions. Furthermore, soil N dynamics may vary

temporally in response to factors including time since harvesting (e.g. Bubb et al., 1998;

Piatek and Allen, 1999; Li et al., 2003; Xu and Chen, 2006) and the influence of plant

development and root activity on organic matter input and nutrient uptake (e.g.

Wheatley et al., 2001; Idol et al., 2003; Saynes et al., 2005). Research has shown that

seasonal trends in soil N dynamics and microbial biomass may vary with land-use and

management practices (Blumfield and Xu, 2003; Chen et al., 2003a,b; Idol et al., 2003;

Zhu and Carreiro, 2004; Chen et al., 2006; Waldrop and Firestone, 2006).

To date there have been a number of long-term field studies examining soil N

dynamics in hoop pine plantations of south-east Queensland. This work has included:

the study of soil N dynamics in a chronosequence of first rotation (1R) hoop pine stands

(Bubb et al., 1998a); mechanisms of soil N loss under windrowed harvest residues in

early second rotation (2R) hoop pine plantations (Pu et al., 2001, 2002, 2005); the

impact of harvest residue management after clearfall harvesting on soil N dynamics

(Blumfield and Xu, 2003, Blumfield et al., 2004), and the influence of compaction and

cultivation during the establishment of 2R hoop pine plantations on soil N

transformations (Blumfield et al., 2005). However, the impact of land-use change from

Chapter 6 96

native forest (NF) to 1R hoop pine plantation, and subsequent 2R plantation, on soil N

dynamics has not been studied. An understanding of the effects of land-use change and

subsequent rotations of hoop pine plantation on soil N dynamics, is important

information that will contribute to the development of long-term management solutions

which endeavour to maintain the sustainability of the soil resource and consequently the

productivity of the Queensland forestry industry.

Previous chapters have examined the impact of land use change from NF to

plantations on mineral and organic N pools, mineral N transformations, and the soil

microbial community. These comparisons were made based on a single sampling, and

under laboratory conditions, where soils had been disturbed and moisture and

temperature could be controlled. Hence, a longer-term field study was required to

capture the concurrent effects of season and land-use change on soil N dynamics in the

field. The objective of this study was to assess the impact of land-use change from NF

to 1R hoop pine plantation and subsequent 2R plantation and associated management

techniques on the temporal/seasonal trends of N cycling and availability in subtropical

Australia.

6.2 Methods

6.2.1 Sampling

The field experiment was established in August of 2002, when the 2R plantation

was approximately 2 y old. Rainfall and temperature records for the sampling period

were collected by the Yarraman Forestry Office. The in-situ soil core incubation

technique described by Raison et al. (1987) was used to study and compare the seasonal

dynamics of soil N pools and transformations in soils of the NF, 1R, second rotation

tree row (2R-T), and second rotation windrow (2R-W). The field incubations were

conducted over 18 consecutive sampling cycles (28 d per cycle) beginning in August

2002 and ending in January 2004. At the beginning of each sampling cycle, three in situ

Chapter 6 97

incubation tubes were installed in each of the five replicates of the NF, 1R, 2R-T and

2R-W sites (Fig. 6.1). All of the PVC tubes had an internal diameter of 10 cm, however

two of them were 15 cm in length, while the third was 25 cm in length. The lower part

of each tube was perforated with several 1-cm diameter holes to allow for equilibration

of moisture and gases with the soil outside the tube (Bubb et al., 1998a; Blumfield and

Xu, 2003). The point of installation was randomly selected within each plot and organic

matter on the soil surface was removed prior to installation.

The first two tubes (cores 1 and 2), were installed in the soil at a depth of 10 cm

and were used to measure net N dynamics in the 0-10 cm soil layer over the sampling

period. The third tube (core 3) was installed in the soil at a depth of 20 cm, and was

used to measure the potential loss of N from the 0-20 cm soil layer. In order to measure

potential loss, core 3 was labelled with 20 ml of (15NH4)2SO4 solution (2.9 mg N; ca. 98

atom % 15N excess). This amount of N was equivalent to 5 mg N kg-1 and based on

prior work at this site was approximately 10% of the total mineral N in all forest types.

The 15N solution was applied to the soil core by pouring it evenly over the surface.

After installation, core 1 was removed immediately to provide baseline data,

while cores 2 and 3 were left in situ for 28 d, at which time they were removed and

three cores were inserted to continue the cycle. In order to prevent leaching, the open

end of core 2 was covered with a PVC cap, and small wooden blocks were used to raise

the cap above the rim of the tube and enable free flow of air (Blumfield and Xu, 2003).

Core 3 was left uncapped so that leaching could occur. After each sampling, the tubes

were transported to the laboratory where they were stored at 4°C and processed within

two days after collection from the field.

Chapter 6 98

Fig. 6.1: Picture of in-situ incubation cores.

6.2.2 Soil analysis

Soil from cores 1 and 2 were removed from the tubes and processed according to

the methods described in Chapter 2. Soil mineral N (NH4+-N and NO3

-- N)

concentrations in 2 M KCl extracts were measured using the LACHAT Quikchem

Automated Ion Analyser, also described in Chapter 2 (QuikChem Method 10-107-06-

04-D for NH4+-N, and QuikChem Method 31-107-04-1-D for NO3

--N). Soil from core

3 was separated into the 0-10 and 10-20 cm soil depths, processed as decribed in

Chapter 2, with precautions taken to prevent 15N cross-contamination. Sub-samples of

each depth were then finely ground and isotope ratio analysis was conducted according

to the methods described in Chapter 2. Soil microbial biomass C (MBC) and N (MBN)

were measured in sampling cycle 6 (summer) and 13 (winter) using the method

described in Chapter 2.

Chapter 6 99

6.2.3 Calculations

For each sampling cycle soil net mineralisation and nitrification were estimated

using Equations 6.1, 6.2 and 6.3:

∆NH4+-N = NH4

+-N(Core 2) - NH4+-N(Core 1) (6.1)

∆NO3-- N / net nitrification = NO3

-- N(Core 2) - NO3-- N(Core 1) (6.2)

Net N mineralisation = ∆NH4+-N + ∆NO3

-- N (6.3)

For net N mineralisation, where this value was negative, it was assumed that the

rate of N loss through immobilisation, volatilisation or denitrification had exceeded the

rate of N mineralisation for that period. For net nitrifcation, negative values were

assumed to show losses through NO3--N immobilisation or denitrification.

Potential loss of N from the 0-20 cm soil layer was estimated using isotope ratio

analysis of the 0-10 and 10-20 cm soil layers of core 3 and Equation 6.4:

100)100)%(()100)%((

100 15)2010()2010(

15)100()100(

15

×⎟⎟⎠

⎞⎜⎜⎝

⎛ ÷×+÷×− −−−−

appliedNamounttotalNNxsatmtotalNNxsatm cmcmcmcm

(6.4)


As the field experiment was carried out over 18 consecutive cycles, there is the

likelihood that the data will be autocorrelated in time. In order to account for

correlation in the data a multiple linear regression model with correlated error terms was

fit to the data using a General Least Squares (GLS) algorithm. All response variables

were assumed to follow an autoregression (AR) of the order one. That is, all response

variables in all sampling cycles were only explicitly dependent on the sampling cycle

before it, however implicit correlations are induced with all prior sampling cycles. In

Chapter 6 100

order to determine if the relationship between the response variable and sampling cycle

was dependent on forest type (i.e. to determine whether or not all forest types followed

the same trend through time for a particular response variable), the model interacted

treatment and sampling cycle for all response variables. The covariates used in the

model for the response variable soil moisture were: forest type, sampling cycle, total

rainfall per sampling cycle, mean sampling cycle temperature, and season. For the

response variables soil total C, soil total N and C:N ratio, the covariates were: forest

type, sampling cycle, total rainfall per sampling cycle, mean sampling cycle

temperature, season, and soil moisture. The covariates used in the model for the

response variables NH4+-N, NO3

-- N, net and cumulative N mineralisation and net and

cumulative nitrification were: forest type, sampling cycle, total rainfall per sampling

cycle, mean sampling cycle temperature, soil moisture, season, soil total C, soil total N,

and C:N ratio. The response variables NH4+-N, NO3

-- N, soil total C, and soil total N

were transformed using a base –10 logarithim to achieve normality. All analyses were

conducted in R version 2.4.0. Data have been presented in 28 d increments to match the

sampling periods.

One-way analysis of variance (ANOVA) was used to examine differences in

potential N loss, MBC and MBN among the forest types within individual sampling

cycles. This analysis was conducted in SAS Version 9.1.3 for Windows.

6.3 Results

A multiple linear regression model was used to analyse this dataset because it

has the ability to account for temporal correlation in the data within the error term.

This form of statistics can be particularly useful when dealing with datasets with large

variability, such as this one, where it may be difficult to see overall trends in the visual

Chapter 6 101

representations of the data. All response variables were found to have significant

temporal correlation (P<0.05). That is, the value of the response variable in a particular

sampling cycle was correlated to the value of that response variable in the previous

sampling cycle.

6.3.1 Rainfall, temperature and soil moisture

Total rainfall for each 28 d sampling cycle and daily minimum and maximum

temperatures are displayed in Figs. 6.2 and 6.3 respectively. Total rainfall during the

year 2003 (sampling cycles 6 to 17) was within the normal rainfall range for this site

(433 and 1110 mm per annum) but lower than the average total rainfall of 816 mm.

Seasonal rainfall patterns were typical of the subtropical environment, with lower

rainfall in mid winter to early spring, and higher rainfall in late spring to summer (Fig.

6.2). Temperature ranges and fluctuations were typical for the region and followed a

similar pattern to rainfall (Fig. 6.3). Soil moisture was significantly influenced by

season (P<0.05) and rainfall (P<0.001) and tended to increase in mid to late summer as

rainfall increased (Figs. 6.2 and 6.4). Mean soil moisture for the entire sampling period

ranged from 27.9% in the 2R-T soil to 35.4% in the NF soil (Table 6.1). Although there

were significant differences in soil moisture among the forest types in some sampling

cycles (e.g. sampling cycles 5, 8 and 18), overall there was no significant difference in

soil moisture among the forest types.

6.3.2 Soil C and N

The mean soil total C for the sampling period ranged from 5.4% in the 2R-T soil

to 9.2% in the NF soil, and the mean total N ranged from 0.45% in the 2R-T soil to

0.80% in the NF soil (Table 6.1). The NF soil had significantly higher total C and total

N than the 1R soil (P<0.01 and P<0.001 for total C and total N respectively). The 1R

Chapter 6 102

soil had higher total C (P<0.01) and total N (P<0.01) than the 2R soils, however no

significant difference in total C or total N was found between the 2R soils.

The mean soil C:N ratio for the sampling period ranged from 11.3 in the NF soil

to 12.8 in the 1R soil (Table 6.1). Overall, the NF soil had lower soil C:N ratios than

the 1R soil (P<0.001). Soil C:N ratios were similar in the 1R and 2R-W soils but

significantly lower in the 2R-T soil compared to the 1R and 2R-W soils (P<0.01 and

P<0.05 respectively). There were no distinct seasonal trends for soil total C or N.

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Tota

l rai

nfal

l (m

m)

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Tota

l rai

nfal

l (m

m)

0

20

40

60

80

100

120

140

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Fig. 6.2: Total rainfall within each 28 d sampling cycle within the sampling period.

Chapter 6 103

-5

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Tem

pera

ture

o C

-5

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Tem

pera

ture

o C

Fig. 6.3: Minimum and maximum daily temperatures within the sampling period.

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Soi

l moi

stur

e (%

)

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Soi

l moi

stur

e (%

)

Fig. 6.4: Soil moisture content in adjacent native forest (NF), first rotation hoop pine plantation (1R), second rotation tree row (2R-T), and second rotation windrow (2R-W) for the sampling period.

Tab

le 6

.1:

Ran

ge a

nd m

ean

valu

es f

or s

oil p

rope

rties

det

erm

ined

for

the

0-10

cm

soi

l lay

er o

f ad

jace

nt n

ativ

e fo

rest

(N

F), f

irst r

otat

ion

hoop

pin

e

plan

tatio

n (1

R),

seco

nd ro

tatio

n tre

e ro

w (2

R-T

) an

d se

cond

rot

atio

n w

indr

ow (

2R-W

) ov

er th

e pe

riod

Aug

ust 2

002

– Ja

nuar

y 20

04, a

t the

Yar

ram

an

site

, sub

tropi

cal A

ustra

lia (n

= 18

exc

ept f

or so

lubl

e or

gani

c ni

troge

n (S

ON

) whe

re n

=10)

.

NF

1R

2R-T

2R

-W

Dep

ende

nt

varia

bles

R

ange

M

ean

Ran

ge

Mea

nR

ange

M

ean

Ran

ge

Mea

n

Soil

moi

stur

e (%

) 20

.6 –

56.

0 35

.4

19.1

– 5

5.5

34.5

12

.3 –

48.

6 27

.9

17.8

– 4

6.3

31.3

Tota

l C (%

) 5.

3 –

16.1

9.

2 4.

3 –

15.3

7.

5 3.

2 –

9.4

5.4

3.8

– 10

.2

5.5

Tota

l N (%

) 0.

59 –

1.2

0.

80

0.37

– 0

.97

0.58

0.

30 –

0.6

6 0.

45

0.35

– 0

.68

0.46

C:N

8.

5 –

15.3

11

.3

10.0

– 1

6.4

12.8

7.

6 –

16.7

11

.8

9.2

– 15

.0

11.9

NH

4+ -N (m

g kg

-1)

0 –

27.0

9.

5 0

– 33

.0

9.0

0 –

26.6

12

.0

0 –

29.7

9.

9

NO

3- -N (m

g kg

-1)

0 –

159.

2 41

.9

0 –

46.6

10

.5

0 –

80.6

13

.9

0 –

58.5

16

.2

Net

N m

iner

aliz

atio

n (m

g kg

-1 2

8 d-1

) -3

6.9

– 96

.320

.6

-15.

1 –

94.7

9.

0 -1

4.2

– 53

.110

.5

-19.

3 –

51.1

13.6

Net

nitr

ifica

tion

(mg

kg-1

28

d-1)

-36.

3 –

84.4

19.7

-1

3.5

– 79

.6

9.2

-9.1

– 4

5.8

11.3

-1

5.7

– 49

.513

.45

Cum

ulat

ive

N m

iner

aliz

atio

n (m

g kg

-1)

147

– 51

0

346

132

– 19

2

162

127

– 22

8

179

233

– 27

1

251

Cum

ulat

ive

nitri

ficat

ion

(mg

kg-1

) 16

5 - 4

92

332

14

0 –

190

16

5 16

3 –

249

20

4 23

4 –

280

25

5

Chapter 6 105

6.3.3 Seasonal dynamics of mineral N pools

Seasonal dynamics of NH4+-N and NO3

--N in the pre-incubation core (core 1)

are displayed in Figs. 6.5 and 6.6 respectively. The mean concentration of NH4+-N over

the sampling period ranged from 9.5 mg N kg-1 in the NF soil to 12.0 mg N kg-1 in the

2R-T soil (Table 6.1). Concentrations of NH4+-N over the sampling period were

significantly higher in the NF soil compared to the 1R soil (P<0.01). The 1R soil also

had significantly lower NH4+-N concentrations than the 2R plantations (P<0.01), while

the 2R-T soil had higher concentrations of NH4+-N than the 2R-W soil (P<0.01).

The mean concentration of NO3--N over the 18 sampling cycles ranged from

10.5 mg N kg-1 in the 1R soil to 41.9 mg N kg-1 in the NF soil (Table 6.1). The NF soil

tended to have higher concentrations of NO3--N than the 1R soil (Table 6.1, Fig. 6.6).

Although there were some differences among plantation soils in particular sampling

cycles (e.g. sampling cycle 15), overall, there was no significant difference in NO3--N

concentrations among the plantation soils.

There was no interaction between sampling cycle and forest type for the two

response variables over the sampling period, suggesting that the seasonal trends in

mineral N pool dynamics were similar among the forest types. However, there was a

significant interaction between sampling cycle and NH4+-N concentration in the 2R-T

soil (P<0.001), likely resulting from the fluctuations in NH4+-N concentration in the 2R-

T soil in the first six to eight sampling cycles (Fig 6.5). For the first seven sampling

cycles the NH4+-N concentration tended to fluctuate more in the 2R plantation soils than

in the 1R and NF soils (Fig 6.5). However, after this time the pattern of NH4+-N

dynamics tended to be similar among the forest types. In all forest types the

concentration of NH4+-N generally increased from late summer to mid winter 2003

(sampling cycle 7 to sampling cycle 12), after which it tended to decrease until early

summer (sampling cycle 12 to 17). Of the covariates used in the model, the NH4+-N

Chapter 6 106

pool dynamics was significantly influenced by soil total C (P<0.01), total N (P<0.01),

C:N ratio (P<0.05), season (P<0.05) and temperature (P<0.001).

Concentrations of NO3--N tended to be highest in summer 2003 (sampling cycle

6) (Fig. 6.6) and late spring 2003 (sampling cycle 16). Statistical analysis revealed that

of the covariates in the model, the NO3--N pool dynamics were significantly influenced

by mean monthly temperature (P<0.001), soil moisture (P<0.05), and season (P<0.05).

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

NH

4-N

(mg

N k

g-1)

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

NH

4-N

(mg

N k

g-1)

Fig. 6.5: Ammonium dynamics in adjacent native forest (NF), first rotation hoop pine plantation (1R),

second rotation tree row (2R-T) and second rotation windrow (2R-W) for the sampling period.

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

NO

3-N

(mg

N k

g -1)

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

NO

3-N

(mg

N k

g -1)

Fig. 6.6: Nitrate dynamics in adjacent native forest (NF), first rotation hoop pine plantation (1R), second

rotation tree row (2R-T), and second rotation windrow (2R-W) for the sampling period.

Chapter 6 107

6.3.4 Net N transformations

Net N mineralisation and nitrification dynamics over the 18 sampling cycles are

presented in Fig. 6.7 and 6.8. The mean rate of net N mineralisation over the sampling

period ranged from 9.0 mg N kg-1 28 d-1 (equivalent to approximately 5.9 kg N ha-1) in

the 1R soil to 20.6 mg N kg-1 28 d-1 (equivalent to approximately 12.6 kg N ha-1) in the

NF soil (Table 6.1). The mean rate of net nitrification over the sampling period ranged

from 9.2 mg N kg-1 28 d-1 (equivalent to approximately 5.6 kg N ha-1) in the 1R soil to

19.7 mg N kg-1 28 d-1 (equivalent to approximately12.0 kg N ha-1) in the NF soil (Table

6.1). Net N mineralisation and net nitrification rates for the 18-month sampling period

were significantly higher in the NF soil compared to the 1R soil (P<0.01 and P<0.001

respectively). While net N mineralisation and net nitrification rates among the

plantation soils were different in some of the sampling cycles (e.g. in sampling cycle 4,

net nitrification was higher in the 2R soils than in the 1R soil), no significant differences

were found over the entire sampling period.

Net N mineralisation and nitrification rates in all forest types followed similar

seasonal trends (i.e. there was no interaction between treatment and sampling cycle for

either response variable). Immobilisation was a significant process in the NF soil in

mid summer 2003 (sampling cycle 6) (Figs. 6.7 and 6.8). Statistical analysis revealed

that, of the co-variates in the model, mean monthly temperature and soil moisture at the

time of sampling had a significant influence on both net mineralisation (P<0.001) and

net nitrification (P<0.001). These influences are illustrated by the increase in the rate of

net N mineralisation and net nitrification in all forest types in early autumn 2003

(sampling cycle 8) and again in early and mid summer 2003/04 (sampling cycles 17 and

18). In the first instance, the increase in N transformation rates coincides with increases

in soil moisture (Figs. 6.4, 6.7 and 6.8). While in the second instance, the increase

coincides with increases in both temperature and soil moisture (Figs. 6.3, 6.4, 6.7 and

Chapter 6 108

6.8). The decrease in rates in early autumn 2003 (between sampling cycle 8 and 9)

corresponds with a decrease in soil moisture. Season also had a significant influence on

rates of net N mineralisation and net nitrification (P<0.05). While rates of net N

mineralisation and nitrification were also positively influenced by total C (P<0.001) and

negatively influenced by C:N ratio (P<0.001).

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Net

N m

iner

alis

atio

n (m

g N

kg-1

28d-1

)

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Net

N m

iner

alis

atio

n (m

g N

kg-1

28d-1

)

Fig. 6.7: Net nitrogen (N) mineralisation dynamics in adjacent native forest (NF), first rotation hoop pine

plantation (1R), second rotation tree row (2R-T), and second rotation windrow (2R-W) for the sampling

period.

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Net

nitr

ifica

tion

(mg

N k

g-128

d-1)

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Net

nitr

ifica

tion

(mg

N k

g-128

d-1)

Fig. 6.8: Net nitrification dynamics in adjacent native forest (NF), first rotation hoop pine plantation (1R),

second rotation tree row (2R-T), and second rotation windrow (2R-W) for the sampling period.

Chapter 6 109

Cumulative N mineralisation and nitrification over the 18 sampling cycles are

displayed in Figs. 6.9 and 6.10. Total cumulative N mineralisation for the 18 sampling

periods ranged from 162 mg N kg-1 (equivalent to 106 kg N ha-1) in the 1R soil to 346

mg N kg-1 (equivalent to 211 kg N ha-1) in the NF soil (Table 6.1). Total cumulative

nitrification for the 18 sampling cycles ranged from 165 mg N kg-1 (equivalent to 107

kg N ha-1) in the 1R soil to 332 mg N kg-1 (equivalent to 202 kg N ha-1) in the NF soil

(Table 6.1). Significant interactions between forest type and sampling cycle were found

for both cumulative N mineralisation and cumulative nitrification (P<0.01). This

interaction corresponded to both cumulative N mineralisation and cumulative

nitrification increasing at a significantly greater rate (i.e. steeper slope) in the NF soil

compared to the 1R soil (P<0.001), which resulted in more N being mineralised and

nitrified in the NF soil over the study period (Figs. 6.9 and 6.10). At the end of the

study period a greater amount of N had been mineralised and nitrified in the NF soil

compared to the 1R soil (Table 6.1, Figs. 6.9 and 6.10). Cumulative N mineralisation

increased at a significantly greater rate in the 2R-W soils than in the 1R soils (P<0.001).

However the rate of increase in net N mineralisation was similar between the 1R and

2R-T soils, and between the 2R-T and 2R-W soils. At the end of the study period a

greater amount of N had been mineralised in the 2R-W soil than in the 1R and 2R-T

soils (Table 6.1, Fig. 6.9).

Cumulative nitrification in the 1R soil increased at a significantly lower rate (i.e.

lower gradient) compared to the 2R soils (P<0.01). Statistical analysis revealed that

cumulative N mineralisation and nitrification increased at similar rates in the 2R-T and

2R-W soils. At the end of the 18 sampling cycles, the amount of N nitrified was largest

in the 2R-W soil, followed by the 2R-T soil, and was smallest in the 1R soil (Table 6.1,

Fig. 6.10).

Chapter 6 110

Of the covariates in the model, season influenced cumulative N mineralisation

(P>0.05) and nitrification (P<0.05), with steeper slopes (i.e. cumulative N

mineralisation and nitrification increasing at greater rates) tending to occur in the

summer months (e.g. sampling cycle 17 to 18) or shortly after periods of high rainfall

(e.g. sampling cycle 7 to 8) (Figs. 6.2, 6.9 and 6.10). While the rate of increase in

cumulative N mineralisation and nitrification tended to be slower in autumn and winter,

(sampling cycles 8 to 13) (Figs. 6.9 and 6.10).

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Cum

ulat

ive

net N

min

eral

isat

ion

(mg

N k

g-1)

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Cum

ulat

ive

net N

min

eral

isat

ion

(mg

N k

g-1)

Fig. 6.9: Cumulative N mineralisation in adjacent native forest (NF), first rotation hoop pine plantation

(1R), second rotation tree row (2R-T), and second rotation windrow (2R-W) for the sampling period.

-100

-50

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Cum

ulat

ive

net n

itrifi

catio

n (m

g N

kg-1

)

-100

-50

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

NF

1R

2R-T

2R-W

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Spring

2002

Autumn Spring

2003

Summer SummerWinter

2004

Cum

ulat

ive

net n

itrifi

catio

n (m

g N

kg-1

)

Fig. 6.10: Cumulative nitrification in adjacent native forest (NF), first rotation hoop pine plantation (1R),

second rotation tree row (2R-T), and second rotation windrow (2R-W) for the sampling period.

Chapter 6 111

6.3.5 Microbial biomass

The concentration of soil MBC ranged between 540 μg g-1 in the 1R soil to 1457

μg g-1 in the NF soil in the summer (sampling cycle 6), but were higher in the winter

(sampling cycle 13), ranging between 1014 μg g-1 in the 2R-W soil to 2682 μg g-1 in the

NF soil (Fig 6.11). In summer, soil MBC was significantly higher in the NF soil than in

the 1R soil, however both forest types had similar concentrations in the winter. The 1R

soil had significantly lower soil MBC concentrations than the 2R soils in the summer,

but significantly higher concentrations than the 2R soils in the winter. The 2R soils had

similar concentrations of soil MBC in both summer and winter (Fig 6.11).

The concentrations of soil MBN in summer ranged between 69 μg g-1 in the 2R-

T soil and 163 μg g-1 in the NF soil (Fig. 6.11). Similar to MBC, soil MBN also

increased in winter, ranging from 162 μg g-1 in the 2R-T soil to 279 μg g-1 in the NF

soil. As with soil MBC, the concentration of soil MBN was significantly higher in the

NF soil compared to the 1R soil in summer, but both forest types had similar

concentrations in winter. In the summer, MBN was lower in the 2R-T soil than in the

1R or 2R-W soil, however there was no significant difference in MBN among the

plantation soils in the winter (Fig 6.11).

The NF soil had a higher MBC:MBN ratio than the 1R soil in the summer, but

similar ratios were found between the NF soil and the 1R soil in the winter (Fig 6.11).

The 1R soil tended to have a lower MBC:MBN ratio than the 2R soils in the summer,

but higher in the winter. While the 2R-T soil had a higher MBC:MBN ratio than the

2R-W soil in the summer, but a similar ratio in the winter.

Chapter 6 112

0

5001000

1500

2000

25003000

3500

NF 1R 2R-T 2R-W

0500

10001500

20002500

30003500

NF 1R 2R-T 2R-W

050

100150

200250

300350

NF 1R 2R-T 2R-W

0

50

100

150

200

250

300

350

NF 1R 2R-T 2R-W

0

2

4

6

8

10

12

14

NF 1R 2R-T 2R-W 0

2

4

6

8

10

12

14

NF 1R 2R-T 2R-W

Fig. 6.11: Soil microbial biomass carbon (MBC) and (MBN), and microbial biomass carbon:microbial

biomass nitrogen (MBC:MBN) ratios, determined in summer and winter in adjacent native forest (NF),

first rotation hoop pine plantation (1R), second rotation tree row (2R-T), and second rotation windrow

(2R-W).

MB

C (μ

g/g)

M

BN

(μg/

g)

Mic

robi

al C

:N

Summer 2003 (Sampling Cycle 6) Winter 2003 (Sampling Cycle 13)

Chapter 6 113

6.3.6 Potential N loss

Results for one sampling cycle with low rainfall (sampling cycle 3, Spring 2002)

and one sampling cycle with high rainfall (sampling cycle 7, summer 2003) are

presented in Table 6.2. In sampling cycle 3, up to 29% of the 15N originally applied was

lost from the 0-20 cm soil layer. Loss of N increased in sampling cycle 7, with up to

81% of 15N lost from the 0-20 cm layer (Table 6.2). No significant difference in N loss

among the forest types was found in these sampling cycles.

Table 6.2: Percent 15N lost from the 0-20 cm soil layer in adjacent native forest (NF), 53 y-old

first rotation hoop pine plantation (1R), 5 y-old second rotation tree row (2R-T) and second

rotation windrow (2R-W), in sampling cycles of moderate (sampling cycle 3 – October 2002,

mid spring) and high (sampling cycle 7 – February 2003, late summer) rainfall.

Forest Type Sampling cycle 3

(total rainfall = 10.2)

Sampling cycle 7

(total rainfall = 127)

NF 29%a 81%a

1R 27%a 69%a

2R-T 5%a 66%a

2R-W 22%a 78%a

6.4 Discussion

There are inherent difficulties in the interpretation of seasonal data collected

from long-term field trials. This has been acknowledged by various workers (e.g. Idol

et al. 2003). Not only do the pools and processes measured have large spatial and

temporal variability, compounding the problem is the difficulty in monitoring

concurrent changes in all environmental factors influencing the size and rates of the

pools and processes. For example, the frequency of drying and rewetting has been

found to have a significant influence on soil N cycling (Pulleman and Tietema, 1999;

Fierer and Schimel, 2002; Miller et al., 2005), but is a more complicated variable to

Chapter 6 114

measure than other environmental variables such as temperature and soil moisture. The

difficulty in interpretation is further exaggerated by the fact that there may be a lag time

between changes in environmental conditions and the response of a particular pool or

process. As difficult as interpretation can be, understanding seasonal trends in soil N

dynamics across different land-uses is an integral component of understanding how soil

N cycling responds to land-use change. Furthermore, the data may be used to validate

results obtained from studies conducted under laboratory conditions, and to

parameterize and test N cycling models.

6.4.1 Impact of land use on measured soil properties

The results of the field study were generally consistent with the results of the

three laboratory studies (Chapters 3,4 and 5). The land-use change from the NF to the

1R hoop pine plantation was associated with reductions in the rate and total amount of

N mineralised and nitrified. This, in turn, resulted in less available N in the 1R soil

compared to the NF soil. The lower N transformation rates and availability in the 1R

soil compared to the NF soil may be a consequence of the lower quality and quantity of

organic matter in the 1R soil, as indicated by the higher C:N ratios, and lower

percentages of total C and N. There were also some differences in MBC and MBN

between the two forest types, with the 1R soils having smaller MBC and MBN pools

than the NF soil in the summer sampling cycle. It is worth noting that there is a lack of

research relating specifically to the impact of land-use change from mixed-species NF

to single-species plantations on seasonal soil N dynamics, particularly for the

subtropical environment. However, the results of this study were consistent with the

results of Hackl et al. (2004), who found that seasonal soil N dynamics in Austrian

forest stands with different species compositions were related to the size of the soil total

N stores, with N mineralisation and microbial biomass generally higher in forest types

with larger N pools. The results of this study are also generally consistent with the

Chapter 6 115

traditional theory that reductions in the quantity and quality of organic matter input may

result in lower soil microbial biomass, lower rates of N transformation and less N

availability (Carlyle, 1986; Attiwill and Adams, 1993; Sparling 1997).

Conversion of the 1R hoop pine plantation to the 2R hoop pine plantation

significantly increased NH4+-N availability. The influence of the change in land use on

NH4+-N concentration was particularly obvious during the first 6 sampling cycles when

concentrations tended to be higher and fluctuations greater in the 2R soils compared to

both the NF and the 1R soils (Fig 6.5). However, after this time concentrations of NH4+

-N in the 2R soils followed similar trends to the NF and 1R soils for the last 12

sampling cycles (Figure 6.5). A temporary increase in nutrient availability following

harvest has been reported in many forest ecosystems and has been referred to as the

assart effect (Smethurst and Nambiar, 1990; Li et al., 2003). Such increases have been

attributed to stimulation of microbially mediated N mineralisation processes due to

factors including disturbance, mixing of forest floor material into surface soil and higher

soil temperatures resulting from loss of canopy cover (Carlyle, 1986; Frazer et al. 1990;

Li et al., 2003; Grenon et al. 2004). This period has been found to last 1-3 years, after

which N mineralisation rates can be expected to return to levels at or below pre-harvest

rates (Aber et al., 1991). Hence the difference in temporal patterns of NH4+-N

concentrations between the 1R and the 2R soils may be explained by the assart effect.

Further evidence of the assart effect can be seen in Figs. 6.9 and 6.10, where

cumulative N mineralisation and nitrification tend to increase at a faster rate (i.e. steeper

slope) in the 2R soils compared to the 1R soils in the first 6 to 8 sampling cycles (Figs

6.9 and 6.10). When compared to mature forest stands, young forest stands have often

been found to have higher rates of N mineralisation and nitrification (e.g. Hazlett et al.,

2007). In this study, the rates of net N mineralisation and nitrification were not

significantly different among the plantations soils, however, at the end of the study

Chapter 6 116

period more N had been mineralised and nitrified in the 2R soils (particularly the 2R-W

soil) compared to the 1R soil (Table 6.1, Figs. 6.9 and 6.10). These results seem

contradictory, however it is believed that the faster rate of increase in cumulative N

mineralisation and nitrification in the 2R soils in the early months contributed to the

overall larger amount of N being mineralised and nitrified.

Previous research found that nitrification was an important process in the soils of

hoop pine plantations in south-east Queensland, (Bubb et al., 1998a; Blumfield and Xu,

2003; Blumfield et al., 2005). In this study, nitrification was not only important, but

was actually the dominant N transformation process. Given this fact, it is possible that

any differences in net ammonification rates would be masked when net N mineralisation

was calculated. It is interesting to note that the plantation soils had slightly higher total

cumulative nitrification than total cumulative N mineralistion (Table 6.1). This may

indicate that overall there was some immobilisation of NH4+-N in these soils.

Previous studies in hoop pine plantation soils of south-east Queensland indicate

higher rates of immobilisation under windrows than between windrows in the first 18-

months to 2 years after windrow formation (Pu et al., 2001, 2002; Blumfield and Xu,

2003). In this study, residue management had no significant influence on N

transformations and availability in the period between 2 and 3.5 years after plantation

establishment. However, at the end of the sampling period there was more N

mineralised and nitrified in the 2R-W soil compared to the 2R-T soil. Factors

contributing to the difference in results of previous studies and this study include time

since harvest and windrow establishment, the presence of trees in this study compared

to previous studies, and differences in site characteristics.

6.4.2 Seasonal trends of soil mineral N pools

Seasonal trends in soil N availability have implications for plant growth and

nutrition as well as the environment. Ideally, higher concentrations of available N

Chapter 6 117

would coincide with the growing season. In situations where the two do not coincide,

or alternatively, when concentrations of available N exceed plant uptake, there is the

potential for N (particularly in the form of NO3--N) to be lost from the system (Carlyle,

1986; Stevenson and Cole, 1999; Raubauch and Joergensen, 2002; Zhu and Carreiro,

2004). Furthermore, loss of available N from the system through leaching and runoff is

dependent on rainfall, and hence in the subtropical environment may be influenced by

seasonal fluctuations in rainfall.

In this study, pre-incubation concentrations of NH4+-N and NO3

--N in the

plantation soils were comparable to those measured during long-term in situ incubation

studies in other hoop pine plantations of south-east Queensland (Bubb et al., 1998a;

Blumfield and Xu, 2003; Blumfield et al., 2005). The NH4+ -N concentration in all

forest types tended to be highest from autumn to spring 2003 (sampling cycle 9 to 15

see Fig. 6.5). The hoop pine growing season is between late spring and late autumn

(Bubb et al., 1998b) therefore the NH4+-N pattern appears to be a classic plant uptake

pattern, where the NH4+-N is low or negligible during the growing season as it being

used by the trees.

Similar to results discussed in the previous Chapters, the soil mineral N pool in

all forest types tended to be dominated by NO3-- N (Table 6.1). Whilst Blumfield et al.

(2005) had similar results, the mineral N pool in other hoop pine plantation soils have

been dominated by NH4+-N (Bubb et al., 1998a; Blumfield and Xu, 2003). As

discussed in Chapter 3, one possible explanation for the dominance of NO3-- N in these

soils is that plant microbe interactions favour nitrification. Furthermore, the relatively

dry conditions at the site in comparison to others may result in minimal losses of NO3--

N through leaching.

Seasonal trends in NO3--N concentrations were generally opposite to those found

for NH4+-N concentrations, with concentrations tending to be higher in summer. The

Chapter 6 118

higher concentrations coincide with the growing season, but also with the dominant

rainfall period. Hence, there is the potential that NO3--N may be lost from the system

through leaching and runoff, with ensuing impacts on groundwater and adjacent

waterways.

6.4.3 Seasonal trends of soil N transformations

Similar to soil N availability, seasonal trends in soil N transformation rates play

an important role in determining the fate of N in ecosystems, and have implications for

plant nutrition and the environment (Carlyle, 1986; Stevenson and Cole, 1999;

Raubauch and Joergensen, 2002; Zhu and Carreiro, 2004). Of particular importance is

the timing of nitrification, as the end product, NO3--N, may be lost from the system

(Zhu and Carreiro, 2004).

Seasonal variations in net N mineralisation and nitrification have been reported

in a number of forest ecosystems (e.g. Bubb et al., 1998a; Zhu and Carreiro, 2004; Chen

et al., 2006). However, seasonal trends are not always consistent. Bubb et al. (1998a)

found that the majority of net N mineralisation in hoop pine plantation soils occurred

during the growing season (October – May). In contrast, Blumfield et al. (2005) found

that seasonal trends of N mineralisation and nitrification, also in hoop pine plantation

soils, were variable between years. In this study, soil N mineralisation and nitrification

responded to increases in soil moisture that occurred at the end of summer in 2002 but

slightly earlier (mid spring to summer) in 2003/4. Strong N immobilisation in the NF

soil in mid summer 2003 (sampling cycle 6), corresponded to a decrease in NO3--N

concentration in the pre-incubation cores from mid to late summer 2003 (sampling cycle

6 and 7), but may also be partly due to spatial variation (Figs. 6.5, 6.7 and 6.8).

In general, rates of net N mineralisation and nitrification measured in this study

were comparable with those measured in seasonal in-situ incubation studies in hoop

pine plantations of south-east Queensland (Bubb et al., 1998a; Blumfield et al., 2005).

Chapter 6 119

Similar to results discussed in Chapter 3, nitrification was the dominant process in all

forest soils, and is responsible for the dominance of NO3--N in the mineral N pool.

6.4.3 Seasonal trends of soil microbial biomass C and N

The soil microbial biomass acts as both a source and a sink for N. Fluctuations

in the soil microbial biomass influence N turnover and availability, with increases

potentially resulting in immobilisation of N, while decreases may lead to N

mineralisation (Singh et al., 1989; Chen et al., 2003a,b). Seasonal dynamics of soil

microbial biomass may reflect the impact of a combination of factors including soil

moisture, temperature, root activity and organic matter input (Chen et al., 2003a,b).

Seasonal changes in microbial biomass have been reported in a number of

ecosystems. Whilst there is some variation, in general, MBC and MBN tend to be

higher during seasons dominated by rainfall compared to those when little rainfall

occurs (Maithani et al., 1996; Barbhuiya et al., 2004; Anaya et al., 2007).

In this study, both MBC and MBN were highest in the winter sampling cycle

and lowest in the summer sampling cycle. A similar seasonal trend of MBC and MBN

in soils of hoop pine plantations in south-east Queensland was reported by Chen et al.

(2003b). Lower MBC and MBN values in the summer compared to the winter may be

related to higher temperatures and soil moistures, creating more favourable conditions

for microbial activity (Maithani et al., 1996). Another factor that may contribute to this

result is competition for nutrients between plants and microbes during the growing

season (Sarathchandra et al., 1984). Higher MBC and MBN in the winter may indicate

an increase in N immobilisation as a result of unfavourable climatic conditions for

microbial activity (Maithani et al., 1996; Chen et al., 2003b).

Chapter 6 120

6.4.4 Potential N loss

Loss of N from soil is of importance not only due to loss of plant available

nutrients from the system but also due to the potential for pollution of ground water and

adjacent water bodies when loss of N occurs via leaching. The potential for leaching to

occur is of particular interest in these soils due to the dominance of nitrification and

NO3--N.

The results indicate that the potential for loss of N is higher in periods of high

rainfall, indicating that leaching is a potential loss mechanism of N at this site. This is

consistent with earlier research in hoop pine plantations (Pu et al., 2001, 2002, 2005).

Future studies quantifying the amount of N lost from these soils via leaching and runoff

would give a better indication of the extent to which N lost from this system impacts on

water quality.

6.5 Conclusion

The findings of this study clearly indicate that the land-use change from NF to

1R hoop pine plantation reduced the rate of N transformations as well as the availability

of soil N and had an impact on soil microbial biomass. Although differences were not

always significant, the amount of N mineralised and nitrified tended to be highest in the

2R-W soil followed by the 2R-T soil, and lowest in the 1R soil. Overall, the results

suggest that the land-use change from NF to plantation has had a significant impact on

the chemical, biochemical and biological processes involved in the dynamics of soil N

transformations. There were some indications that harvesting and residue management

may also influence N transformations and availability, however results were not

conclusive. This was likely due to spatial variation in the data. Temperature and soil

moisture were significant factors influencing seasonal trends in soil N transformations

and availability. A longer-term field trial (e.g. two or 3 full years) would be required

Chapter 6 121

for further understanding of the seasonal dynamics of soil N cycling and availability in

response to land-use change.

Chapter 7 122

Chapter 7

Summary, Conclusions and Recommendations for Future Work

7.1 Summary

Increasing demands for forest products coupled with a reduced forest land-base

mean that the long-term sustainability of the Queensland forestry industry is reliant on

the continuing productivity of the current soil resource. Hoop pine plantations account

for a significant proportion of the Queensland forest estate and make a substantial

contribution to the Queensland economy. Being a nitrogen (N) demanding species, the

future of these plantations is particularly reliant on the maintenance of soil N

availability, especially if the economic and environmental costs of N fertilization are to

be limited. A number of studies on soil N dynamics have been carried out in hoop pine

plantation soils over the past two decades. However, the impacts of the initial land-use

change from native forest (NF) to first rotation (1R) hoop pine plantation, and

subsequent conversion to second rotation (2R) plantation on soil N dynamics have not

been studied. Knowledge of how ecosystems function in their native state, and how

their function is affected by land-use change and management will contribute to the

ability of forest managers to devise management strategies that promote the

maintenance of soil health and fertility. This body of work focused on the impact of

land-use change from native forest to 1R hoop pine plantation and subsequent 2R

planation on soil N transformations and availability. The effect of residue management

in the 2R plantation on soil N dynamics was also investigated. The experiments were

based on the hypotheses that:

1) Land-use change from NF to hoop pine plantation can cause a

significant shift in the diversity of tree species and disturbance to soil

system. The shift in tree species diversity can influence interactions

between plant roots and microbes, alter the quality and quantity of

Chapter 7 123

organic matter input, and change soil microclimate conditions. These

changes together with the disturbance caused by harvesting of NF and

1R plantation establishment affect the chemical, biochemical, and

biological processes involved in soil N dynamics.

2) The disturbance, removal of organic matter and nutrients, changes in

microclimate and shift in the stage of plant development associated

with the conversion of 1R hoop pine plantation to 2R hoop pine

plantation impact the chemical, biochemical, and biological processes

involved in soil N dynamics

3) Residue management results in differences in organic matter quantity

and microclimate between the second rotation tree row (2R-T) and

second rotation windrow (2R-W). These differences affect the

chemical, biochemical, and biological processes involved in soil N

dynamics

Laboratory experiments and a field based seasonal study were designed to test

these hypotheses. In addition, forest floor and roots were collected from the NF and 1R

sites, with analysis of total carbon (C) and total N providing an indication of organic

matter quality and quantity. The results of each of the four data chapters are

summarized below.

The impact of land-use and residue management on soil N transformations was

examined in a laboratory incubation study using the 15N dilution method (Chapter 3).

The rate of nitrification and the availability of mineral N (NH4+-N and NO3

--N) were

found to be significantly lower in the 1R soil compared with the NF soil. Results of a

single sampling of litter, roots and soil from the adjacent NF and 1R sites demonstrated

that the land-use change from the NF to the 1R hoop pine plantation had resulted in a

Chapter 7 124

significant reduction in litter, root and soil total carbon (C) and total N, and an increase

in the C:N ratio. These results confirmed that the land-use change from the NF to the

1R hoop pine plantation was associated with a significant reduction in the quality and

quantity of organic matter, which subsequently reduced the rate of nitrification and the

amount of available N. The conversion of 1R hoop pine plantation to 2R hoop pine

plantation resulted in significantly higher rates of ammonification but had no impact on

the rate of nitrification or the availability of mineral N. It was hypothesized that the

increase in ammonification was likely due to increased mineralisation of native organic

N as a result of the disturbance and increase in soil temperature caused by harvesting of

the 1R plantation. This study also demonstrated that in the fifth year of the 2R hoop

pine plantation, residue management did not have a significant influence on soil N

transformations or the availability of mineral N. Finally, nitrification appeared to be the

dominant N transformation process in all forest types, and there was some indication

that heterotrophic nitrification may be important in these soils.

Soil N transformations can be affected by the size and lability of the organic N

pool, which may in turn be influenced by land-use change. Moreover, research suggests

that soil soluble organic N (SON) may be available for plant uptake. Therefore the

impact of land-use change on this pool has consequences for the long term productivity

of the soil resource. The effect of land use and residue management on soil SON pools

through the soil profile was measured (Chapter 4). Soil SON was extracted using water,

hot water, 2 M KCl, 0.5 M K2SO4, and hot 2 M KCl. The potential production of SON

was measured in a 7-d anaerobic incubation. The results demonstrated that the

conversion of NF to 1R hoop pine plantation reduced the amount of soil SON and

soluble organic carbon (SOC), as well as the potential of the soil to produce SON. The

reduction in soil SON was likely to be associated with the decline in organic matter

quality and quantity associated with the change in land use. Soil SON pools were

Chapter 7 125

generally smaller in the 2R soils compared to the 1R soil. While residue management

also had some influence on SON pools, with pool size and the potential to produce SON

tending to be lower in the 2R-T soil compared to the 2R-W soil. The effect of land use

on SON pools tended to be most prominent in the 0-10 cm layer. There was evidence to

suggest that, of the SON pools measured, the hot water and hot KCl extractable pools,

and to a lesser extent the water extractable pool represent the most labile components of

SON.

The lability and amount of organic N influences the size, activity and diversity

of the soil microbial community, which in turn affects soil N dynamics. The effect of

land-use and management on the soil microbial community was examined and

relationships between the soil microbial community and organic matter quality and

quantity were explored (Chapter 5). Community composition was measured using both

whole soil (MicroRespTM) and soil extract (BiologTM) community level physiological

profiling (CLPP) techniques. A number of different statistical methods were used to

interpret the impact of land use and residue management on soil microbial community

composition. The NF soil was found to have higher microbial biomass and activity, and

a different community composition when compared to the 1R soils. The significant

relationship of microbial biomass and activity with soil total C and N, as well as labile

pools of SON, indicated that the significant differences in the quantity and quality of

organic matter between the two forest types were likely responsible for differences in

the microbial community. The conversion of 1R hoop pine plantation to 2R plantation

appeared to have no significant influence on the size and activity of the microbial

community, however there was a difference in community composition. In this study,

residue management did not appear to have an impact on the size and activity of the

microbial community, however there were some indications of a difference in

community composition. The whole soil CLPP technique (MicroRespTM) tended to be

Chapter 7 126

most sensitive to land use and residue management. Differences among the forest types

were detected using statistical methods based on measurements of distance (non-metric

multidimensional scaling and cluster analysis).

Previous experiments measured the impact of land use and residue management

on soil N dynamics and microbial properties based on a single sampling. Therefore, the

impact of land use and residue management on seasonal soil N dynamics was measured

in an 18-month field trial using the in situ incubation method (Chapter 6). The results

from this study generally confirmed the conclusions from the laboratory experiments,

that the conversion of NF to 1R hoop pine plantation reduced the rate of N

transformations and availability and had an impact on the soil microbial biomass. These

reductions coincided with decreases in total C, total N and an increase in C:N ratios,

indicating once more that differences between the two forest types may be a result of

differences in the quantity and quality of organic matter. Statistical analysis suggested

that the conversion of 1R hoop pine plantation to 2R plantation and residue

management did not significantly influence on soil N dynamics. The lack of statistical

significance may have been a result of large variation. Trends in the data indicated that

the conversion from 1R hoop pine plantation to 2R plantation may have caused a flush

of N mineralization and availability in the early sampling cycles which led to a greater

amount of N being mineralised and nitrified in the 2R soils over the sampling period.

Trends also indicated that the total amount of N mineralised and nitrified over the

sampling period was sensitive to residue management, with the 2R-W soil generally

having a greater amount of N mineralized and nitrified compared to the 2R-T soil. The

length of the field trial made it difficult to interpret seasonal trends, however

temperature and soil moisture appeared to influence soil N transformations and

availability.

Chapter 7 127

7.2 Conclusions

The major conclusions of this study are as follows:

1) The land-use change from the NF to the 1R hoop pine plantation

significantly reduced the rates of N mineralisation and nitrification,

which, in turn, resulted in a decrease in the amount of available N (NH4+-

N and NO3--N) (Chapters 3 and 6). This may have occurred due to the

shift in the diversity of tree species, which was associated with a

significant decline in organic matter quality and quantity (Chapters 3, 4

and 6). This, in turn, was associated with a significant reduction in

microbial biomass (Chapter 5 and 6) and activity as well as a change in

microbial community composition (Chapter 5). The results emphasize

the importance of the quantity and quality of organic matter, and the soil

microbial community in soil N cycling.

2) There is some evidence that the conversion of 1R hoop pine plantation to

2R hoop pine plantation may have caused a temporary flush of N

mineralization (Chapters 3 and 6), however this did not result in overall

higher N availability. It is likely that this flush is a result of the

disturbance. The conversion also resulted in a general decline in SON

pool size, the potential of the 2R soils to produce SON, and microbial

biomass, as well as a shift in the microbial community composition

(Chapters 4 and 5). This suggests that the conversion had an impact on

both native organic N stocks and the microbial community, which may

in the long term cause a decline in soil N mineralisation and availability

at the 2R site.

Chapter 7 128

3) While the effect of residue management on N transformations and

availability was not significant, over an 18-month period, more N had

been mineralized in the 2R-W soil than in the 2R-T soil. Soil under

windrows was also found to have greater SON content and a higher

potential to produce SON than the soil under tree rows. Furthermore,

there was some indication that residue management had shifted the

microbial community composition. As such, there may be long-term

effects of residue management on the chemical, biochemical, and

biological processes involved in soil N dynamics. A better silvicultural

technique may be to leave residues in place for 1-2 years and plant

through them after windrowing the remaining large residues

4) The quality and quantity of organic matter; the size, activity and

composition of the microbial community; as well as the size of soil

mineral and organic N pools and transformations, were in general

sensitive to land-use change and residue management. This indicates

that in these soils land-use change and residue management had a

significant influence on the chemical, biochemical, and biological

processes involved in soil N dynamics, which may have long-term

implications for plantation productivity.

7.3 Future work

This body of work has improved our understanding of the impacts of land-use

change and residue management on soil N dynamics. However, further studies are

required to understand the mechanisms driving changes in soil N cycling, and the long

term implications of land-use change. This information would enable forest managers

to devise management strategies that promote the sustainability of the Queensland forest

Chapter 7 129

industry. There is a particular need for further investigation in the following important

areas:

• Long-term field trials in several locations within the hoop pine

plantations of south-east Queensland are required to fully investigate the

chemical, biochemical and biological processes involved in soil N

dynamics at different stages of stand development and time since land-

use change. As seasonal trends can change from year to year, such

studies should be conducted over the longest possible time and should

include monitoring of fluctuations in soil moisture and temperature. This

information would improve the understanding of the mechanisms driving

seasonal trends of soil N dynamics in the adjacent NF, 1R, 2R-T and 2R-

W sites.

• Differences in microclimate as a result of land-use change and

management were discussed as one of the factors that could influence

soil N cycling. Due to the failure of technical equipment during the

seasonal experiment, there is currently no information on the impact of

land-use change and residue management on soil microclimate. Such

information would further enhance our understanding of how land use

and residue management impact soil N dynamics and future field trials

should incorporate measurement of microclimate.

• This study used basic measurements of total C and N, and C:N ratios as

an indicator of organic matter quality and quantity. Characterisation of

the organic matter input from the NF and hoop pine plantations using

techniques such as nuclear magnetic resonance or chemical fractionation,

combined with decomposition studies, would enhance our understanding

Chapter 7 130

of the effect of land-use change on the chemical, biochemical, and

biological processes involved in soil N dynamics.

• Soil SON accounts for a significant proportion of the total soluble N, and

the actual size of the pool varies with extract type. Further knowledge of

the chemical and biological nature of soil SON pools in a wide range of

soil and the microbial processes involved in SON dynamics are required.

Such information would allow further interpretation of how and why

SON pools are influenced by land use. This information would also

contribute to the determination of a set of standard methods to measure

SON pools and the potential production of SON. While soil SON is a

significant source of N in these soils, it is not yet known whether hoop

pine trees are able to directly access and use this resource. Future studies

need to determine whether or not hoop pines are able to use SON.

• This study and previous studies at this site (e.g. He et al., 2004; He et al.

2005), have established that there are differences in the composition and

diversity of the soil microbial community as a result of land-use change

and potentially even residue management. Future studies should focus

on the determination of functional differences in the microbial

communities using techniques such as phospholipid fatty acid analysis,

and enzyme studies.

• Plants play an important role in soil N dynamics through factors such as

competition with microbes for nutrients, nutrient uptake, root exudation,

and organic matter input through fine root turnover. Experiments that

incorporate plants into the system being studied would provide a more

sophisticated understanding of soil N cycling in these soils.

Chapter 7 131

• The high rates of nitrification in these soils, despite relatively low rates

of ammonification and NH4+-N availability, warrant further investigation

of the nitrification pathways in these soils and determination of the

relative importance of heterotrophic nitrification.

• Ultimately, data gathered in this study as well as that from the suggested

studies would enhance current models of soil nutrient cycling in forest

ecosystems. This would in turn provide forest managers with a useful

decision making tool.

References 132

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