A Quantitative Investigation and Inventory of the ... · A Quantitative Investigation and Inventory...

A Quantitative Investigation and Inventory of the

Vegetation and Soils of Coastal Lowland Wetlands in

Hawai‘i

A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAI‘I IN PARTIAL FULFILLMENT OF THE

REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

IN

NATURAL RESOURCES AND ENVIRONMENTAL MANAGEMENT

MAY 2008

By Meris Bantilan-Smith

Thesis Committee:

Greg Bruland, Chairperson

Michael Robotham Wendy Wiltse

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We certify that we have read this thesis and that, in our opinion, it is satisfactory in scope

and quality as a thesis for the degree of Master of Science in Natural Resources and

Environmental Management.

THESIS COMMITTEE

_____________________________________

Chairperson

_____________________________________

_____________________________________

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Acknowledgements I would like to express my sincere appreciation to my advisor, Dr. Greg Bruland,

for inspiring me to pursue a career in wetland ecology and for his direction and guidance

throughout this project. I also thank Dr. Michael Robotham and Dr. Wendy Wiltse for

their service as committee members, and their valuable input on the content of this thesis.

A special thanks to Dr. Richard MacKenzie, Adonia Henry, and Christina Ryder

for their friendship and role in implementing this project. Thanks to Kim Peyton,

Arleone Dibben-Young, Dr. Scott Fischer, Dr. Diane Drigot, Mike Silbernagle, Sylvia

Pelizza, Glynnis Nakai, David Smith, Dave Burney, Mike Mitchell, Fern Duvall, David

Ivy, Jamie Redunzle, Thomas Kaiakapu, Sally Beavers, Greg Koob, Steve Berkson, Gary

Blaich, Hugo and Cindy deVries, and Propane Pete for help with site selection and

access.

I am grateful to Napua Harbottle and the Bishop Museum Herbarium staff for

plant identification assistance.

I would like to recognize the U.S. Environmental Protection Agency (EPA)

Region IX Wetland Program Development Grant program for funding this project.

Although the research described in this thesis has been funded by the U.S. Environmental

Protection Agency, it has not been subjected to any EPA review and therefore does not

necessarily reflect the views of the Agency, and no official endorsement should be

inferred.

Finally, I would like to thank my family especially my mom and my dad for their

support and unconditional love.

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Abstract

Due to the loss and degradation of coastal lowland wetlands throughout the

Hawaiian Islands, created (CW) and restored (RW) wetland projects are becoming more

common. A comprehensive, quantitative assessment of the conditions of these wetlands

has yet to occur, and it has not been resolved whether CWs and RWs provide the same

ecological functions as natural wetlands (NWs). This study was conducted to generate

baseline data and to examine differences in the vegetation characteristics and soil

properties among CWs, RWs, and NWs in Hawai‘i. Forty coastal wetlands sites across

the five major Hawaiian Islands (Kauai, Oahu, Moloka‘i, Maui, and Hawai‘i) were

intensively sampled for vegetation and soils.

Wetland status (i.e. CW versus RW versus NW) accounted for a significant

proportion of the variation in vegetative characteristics and soil properties among sites,

while position along the hydrologic gradient accounted for a significant proportion of the

variation in vegetative characteristics and soil properties within sites. Specifically, NWs

had the greatest number of species observed with 67, of which 20 were unique to NWs.

By comparison, forty-two species were observed in RWs and 30 in CWs. Furthermore,

only 17 (17%) of the 101 plant species identified across the 40 wetland sites were native,

indicating that coastal lowland wetlands in Hawai‘i are highly impacted by exotic species

regardless of their status. Differences in soil properties between wetland status were

quantified with a general linear model (GLM) and Principle Components Analysis

(PCA). Soils in NWs had higher soil organic matter (SOM), total nitrogen (TN), and clay

content, and lower bulk density (BD) and pH. Soils in RWs were characterized by high

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BD and silt and clay content, and low SOM, TN, and total carbon (TC); and soils of CWs

were characterized by high BD and sand content, and low SOM and TN. These

differences in vegetative and edaphic characteristics suggested that coastal lowland RWs

and CWs in Hawai‘i currently do not exhibit the same functions as NWs. Management

strategies including seeding newly restored and created sites with native plant species and

applying organic soil amendments should be incorporated into wetland restoration and

creation practices in Hawaii in order to facilitate the colonization and proliferation of

native vegetation and development of soil properties of future RWs and CWs.

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Table of Contents Acknowledgements ............................................................................................................. ii Abstract .............................................................................................................................. iii List of Tables ..................................................................................................................... vi List of Figures .................................................................................................................. viii List of Abbreviations .......................................................................................................... x Chapter 1. Introduction ....................................................................................................... 1

Introduction ..................................................................................................................... 1 Wetland Functions and Values ....................................................................................... 4 Wetland Policy and Mitigation ....................................................................................... 6 Reference Wetlands and Mitigation Success .................................................................. 7 Objectives and Hypotheses ........................................................................................... 12

Chapter 2. Wetland Vegetation ......................................................................................... 16 Introduction ................................................................................................................... 16 Objectives and Hypotheses ........................................................................................... 18 Methods......................................................................................................................... 19

Study Sites ................................................................................................................ 19 Vegetation Sampling ................................................................................................. 20 Data Analysis ............................................................................................................ 22

Results ........................................................................................................................... 24 Discussion ..................................................................................................................... 35

Chapter 3. Wetland Soils .................................................................................................. 40 Introduction ................................................................................................................... 40 Objectives and Hypotheses ........................................................................................... 42 Methods and Materials .................................................................................................. 43

Soil Survey ................................................................................................................ 43 Laboratory Analysis .................................................................................................. 43 Data Analysis ............................................................................................................ 44

Results ........................................................................................................................... 51 Discussion ..................................................................................................................... 62

Chapter 4. Conclusions ..................................................................................................... 68 Integrated Rankings of Semi-Natural, Restored, and Created Wetland Sites in Hawai‘i....................................................................................................................................... 74 Summary ....................................................................................................................... 79

Appendix A ....................................................................................................................... 81 Appendix B. ...................................................................................................................... 84 Appendix C. .................................................................................................................... 122 Literature Cited ............................................................................................................... 132

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List of Tables Table Page 1.1. List of 17 semi-natural, 11 restored, and 7 created wetland study sites in Hawaii,

including site name, island, status, and latitude and longitude. ............................... 14 2.1. Results of the GLM ANOVAs testing for significance of wetland status, hydrologic

zone, and wetland status by hydrologic zone effects for mean species richness (SR), mean total wetland vegetation (OBL, FACW, and FAC species), mean cover of exotic species, and mean total cover ........................................................................ 25

2.2. Means and standard errors for mean species richness, mean total wetland vegetation

(OBL, FACW, and FAC species), mean exotic cover, and mean total cover ......... 30 2.3. Indicator species for wetland status. Monte Carlo test of significance of observed

maximum indicator value (IV)................................................................................. 31 2.4. List of indicator species for each salinity class. Monte Carlo test of significance of

observed maximum indicator value (IV) for species, based on 4999 randomizations.................................................................................................................................. 31

3.1. Descriptive statistics for bulk density (BD), soil organic matter (SOM), pH,

electrical conductivity (EC), total nitrogen (TN), total carbon (TC), moisture, extractable phosphorus (ExP), clay, silt, and sand. .................................................. 46

3.2. Results of the GLM ANOVAs testing for significance of wetland status, hydrologic

zone, and wetland status by hydrologic zone effects for mean moisture, bulk density (BD),soil organic matter (SOM), pH, total nitrogen (TN), total carbon (TC), conductivity (EC), and extractable phosphorus (ExP) ................................. 47

3.3. Means and standard errors for mean soil moisture bulk density, SOM, TN, TC, EC,

ExP, and particle size distribution ........................................................................... 56 3.4. Spearman rank correlations among the soil properties measured at the 40 coastal

lowland wetland sites in Hawaii .............................................................................. 58 3.5. Spearman rank correlations among the soil properties and the dominant vegetative

species measured at the 40 coastal lowland wetland sites in Hawaii ...................... 62

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4.1. Fishpond site descriptive statistics for bulk density (BD), soil organic matter (SOM), pH, electrical conductivity (EC), total nitrogen (TN), total carbon (TC), moisture, extractable phosphorus (ExP), clay, silt, sand, and vegetative characteristics. .......................................................................................................... 73

4.2. Actual means of soil organic matter (SOM %) and native vegetative cover (%), as

well as site assessment rank for natural, restored, and created coastal lowland wetlands in Hawai‘i. ................................................................................................ 75

4.3. Natural, restored, and created wetland site ranks. Rank 1 weighs the native cover

and SOM equally; Rank 2 gives a 50% weight to native cover, 40% weight to SOM, and 10% weight to site assessment; and Rank 3 equally weights native cover, SOM, and site assessment .................................................................................................. 76

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List of Figures Figure Page 1.1. Study site locations for the 17 semi-natural, 11 restored, and 7 created wetlands in

Hawaii. ..................................................................................................................... 11 2.1. Sampling Design for riparian and isolated wetland sites. ........................................ 21 2.2. Effect of position along the hydrologic gradient and wetland status on species

richness .................................................................................................................... 26 2.3. Effect of position along the hydrologic gradient and wetland status on total cover . 26 2.4. Effect of position along the hydrologic gradient and wetland status on exotic

species cover (%). .................................................................................................... 28 2.5. Effect of position along the hydrologic gradient and wetland status on total wetland

vegetation cover (OBL, FACW, FAC species) ....................................................... 28 2.6. Principle components analysis (PCA) of the species composition of coastal lowland

Hawaiian wetlands. Vectors represent the magnitude of correlation with axis 1 and 2 (i), and 1 and 3 (ii).. .............................................................................................. 33

3.1. Effect of position along the hydrologic gradient and wetland status on bulk density.

.................................................................................................................................. 49 3.2. Effect of position along the hydrologic gradient and wetland status on soil organic

matter (SOM) ........................................................................................................... 49 3.3. Effect of position along the hydrologic gradient and wetland status on total nitrogen

(TN).......................................................................................................................... 52 3.4. Effect of position along the hydrologic gradient and wetland status on total carbon

(TC) .......................................................................................................................... 52 3.5. Effect of position along the hydrologic gradient and wetland status on soil pH ..... 53 3.6. Effect of position along the hydrologic gradient and wetland status on clay content.

.................................................................................................................................. 53 3.7. Effect of position along the hydrologic gradient and wetland status on silt content.

.................................................................................................................................. 54

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3.8. Effect of position along the hydrologic gradient and wetland status on sand content. .................................................................................................................................. 54

3.9. Effect of position along the hydrologic gradient and wetland status on soil moisture.

.................................................................................................................................. 55 3.10. Effect of position along the hydrologic gradient and wetland status on soil

conductivity (EC) ................................................................................................... 55 3.11. Principle Components Analysis (PCA) of the soil properties of coastal lowland

Hawaiian wetlands. Includes all soil cores, and excludes the particle size distribution variables.. ............................................................................................ 60

3.12. Principle components analysis (PCA) of the soil properties of coastal lowland

Hawaiian wetlands. Includes sites with mineral soils only (SOM < 30%) .......... 61

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List of Abbreviations

ACOE Army Corps of Engineers ADSC Agricultural Diagnostic Service Center ANOVA Analysis of Variance BD Bulk Density CWs Created Wetlands EC Electrical Conductivity EPA Environmental Protection Agency ExP Extractable Phosphorus GLM General Linear Model NRCS National Resources Conservation Service NWs Natural Wetlands PCA Principle Components Analysis PSD Particle Size Distribution RWs Restored Wetlands SOM Soil Organic Matter TC Total Carbon TN Total Nitrogen UHM University of Hawai‘i, Mānoa

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Chapter 1. Introduction

Introduction Wetlands are characterized by saturated and/or inundated soil conditions, which

are physically, chemically, and biologically distinct from adjacent upland soils, and

support hydrophytic (water tolerant) vegetation (NRC 1995, Mitsch and Gosselink 2000).

They are important features in the landscape that provide numerous functions and values

for both people and wildlife, including water quality improvement, flood attenuation,

endangered species habitat, and provide a means of economic livelihood for millions of

people (Richardson 1994). For these reasons, the United States has a “no-net-loss”

policy for wetlands (Mitsch and Gosselink 2000). Compensatory wetland mitigation

plays a central role in this policy and has increased the interest in and practice of wetland

creation and restoration by state and federal agencies (Brown and Batzer 2001)

consulting firms, and private landowners.

Wetland mitigation is defined as the "restoration, creation, or enhancement of

wetlands to compensate for permitted wetland losses" (EPA 2007). Wetland mitigation

may compensate for losses caused by urban and industrial development, agriculture,

forestry, road construction, and military activities. When damage or destruction of a

wetland is unavoidable, mitigation is required in the form of wetland creation protection

or restoration (Race and Fonseca 1996, Zedler 1996). Wetland creation is defined as the

conversion or construction of a site that originally was not a wetland to a site that meets

the three parameter test (contains hydric soils, hydrophytic vegetation, and wetland

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hydrology), whereas wetland restoration is the return of a site that has been degraded by

human activities (i.e. drainage, fill, agriculture) to its pre-existing wetland condition

(Brinson and Rheinhardt 1996).

Currently, numerous wetland restoration and creation projects are being

undertaken across the state of Hawai‘i by an array of governmental and non-

governmental organizations such as the U.S. Fish and Wildlife Service (USFWS),

Natural Resources Conservation Service (NRCS), Department of Transportation (DOT),

Hawai‘i Department of Land and Natural Resources (DLNR), Ducks Unlimited (DU),

and private land owners. The ability of created (CWs) and restored (RWs) wetlands to

functionally replace natural wetlands (NWs) has become a topic of considerable debate

(Zedler 1996, Zedler and Callaway 1999, Kentula 2000).

Studies comparing CWs and RWs to NWs have examined differences in

vegetation communities (Heaven et al. 2003, Spieles 2005), physical and chemical soil

properties (Bishel-Machung et al. 1996, Craft 2001, Campbell et al. 2002, Bruland et al.

2003, Bruland and Richardson 2005a, Bruland and Richardson 2006), hydrology

(Zampella and Laidig 2003), and biological communities (Hannaford 1998, King et al.

2000).

The soil physical and chemical properties of CWs and RWs have almost always

been shown to differ from NWs (Bruland and Richardson 2006). There are several

primary reasons that contribute to these differences. First, the creation or restoration of a

wetland generally results in disturbance of soils during the construction project,

especially the excavation and removal of the topsoil (Shaffer and Ernst 1999). The

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removal of topsoil is an important factor accounting for low concentrations of soil

organic matter (SOM) in CWs and RWs. Differences in SOM have been shown to

significantly affect many other soil properties, such as total-percent nitrogen, bulk

density, and pH (Bishel-Machung et al. 1996). Second, the use of heavy machinery in

project construction results in the compaction of soils, further increasing the bulk

densities in CWs and RWs. Finally, differences in hydrology between CWs RWs, and

NWs, have also been shown to affect soil properties. For example, during flooding ,

anaerobic conditions slow decomposition rates and allow for organic matter to

accumulate in the soil, decreasing the bulk density and pH as well as increasing porosity

and N (Craft et al. 2002).

In contrast to NWs, the vegetation of RWs and CWs often differs in species

richness, total cover, and species composition. Differences in vegetative characteristics

are typically attributed to the young age or the lack of maturity of the mitigation sites,

differences in landscape position, or differences in hydrology (Heaven et al. 2003). The

creation or restoration of wetlands usually involves the use of heavy machinery to scrape

the surface and remove the topsoil (Bruland and Richardson 2005b). In doing so, not

only is the topsoil removed but so is the vegetation and seed bank. A Newly created or

restored sites are also rather unstable, and as such they tend to support a suite of species

that are adapted to disturbed environments (Balcombe et al. 2005). Differences in total

cover as well as in species composition have also been attributed to differences in

maturity, such that with time total cover and composition of CWs and RWs approaches

that of NWs (Reinartz and Warne 1993, Balcombe et al. 2005).

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The landscape position of a mitigation site has also been found to have profound

effects on the vegetative characteristics of mitigation wetlands (Jarman et al. 1991).

Many mitigation wetlands are established in uplands, with few nearby wetland seed

sources (Campbell et al. 2002). Reinartz and Warne (1993) observed correlations with

distance to seed sources, and found that as distance to the nearest wetland seed source

increased, species richness of mitigation sites decreased.

No comprehensive investigation of both the vegetation and soil characteristics of

wetlands in the state of Hawai‘i has previously been conducted. In order to provide base-

line data about coastal lowland wetlands, soil properties and vegetative community

composition will be discussed in relation to semi-natural “reference” wetlands and

created and restored wetlands in Hawai‘i. The results of this study will further our

knowledge of Hawaiian wetland ecosystems by providing data, results, and

recommendations that are applicable to wetland sites across the state of Hawai‘i.

Ultimately, the data collected from semi-natural wetlands will also help us to establish

criteria that can be used to assess restored and created wetlands and make

recommendations on how to improve wetland mitigation activities in Hawai‘i.

Wetland Functions and Values Wetlands are a diverse natural resource, which provide many useful functions and

values for society. The Natural Resource Council (1995) defines wetland functions as

“processes and manifestations of processes that occur within wetlands.” Most functions

fall into three broad categories: hydrologic, biogeochemical, and habitat and food web

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maintenance (NRC 1995, Brinson and Rheinhardt 1996). Costanza et al. (1997)

estimated that wetlands provide a total of $14,785 (1994 US$) per hectare in annual

ecosystem services. These ecosystem services include the maintenance of water quality

such as promoting denitrification, trapping sediment, and phosphorus sorption;

minimizing flood surges by storing storm water, among others (Environmental Protection

Agency 2001). Wetlands also hold aesthetic value to millions of people, and provide a

variety of recreational opportunities such as fishing and bird watching.

Wetlands are also extremely important to wildlife, serving as critical habitat for

many endemic waterfowl, macroinvertebrates, and algae. More than one third of the

threatened and endangered species in the United States’ live exclusively in wetlands, and

approximately half use wetlands at some point in their lives (EPA 1995). Throughout the

Hawaiian Islands, wetlands provide important habitat for seven native resident

waterbirds, six of which are listed as endangered species. Migratory waterfowl and

shorebirds also use Hawaiian wetlands as critical stopover and wintering habitat.

Approximately 30 species of migratory ducks and geese as well as 30 species of

migratory shorebirds have been recorded in Hawaiian wetlands (Erickson and Puttock

2006, DU 2007).

The U.S. Fish and Wildlife Service, National Wetlands Inventory estimates that

over 50% of U.S. wetlands have been lost since the 1780’s. The state of Hawai‘i has lost

approximately 7,000 acres which amounts to a 12-percent loss of wetlands statewide

(Dahl 1990). Kosaka (1990) analyzed wetlands below 305 m (1000 ft) elevation and

estimated a 3 % loss of coastal wetlands between the 1780s and the 1980s. According to

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Dahl (1990), Hawai‘i currently has 9,095 hectares of lowland wetlands and 14,701

hectares of upper/mid-elevation wetlands remaining.

Wetland Policy and Mitigation Through most of the twentieth century wetlands have been viewed as either

wastelands or as areas providing little benefits beyond support of waterfowl populations

(Kusler and Kentula 1990). This negative perception of wetlands was encouraged by

policies and incentives of the United States federal government which encouraged or

subsidized the draining or filling of wetlands. Due to these policies, the total wetland

area in the United States was reduced to half of the original total by the mid-1980s

(Kusler and Kentula 1990, NRC 1995, Dahl 2006). In recent years the negative trend of

wetland loss has shifted, and as of 2004, the contiguous United States has experienced an

annual net gain of wetland area (Dahl 2006).

The shift in trends of wetland area in the U.S. are due to changes in nation-wide

wetland policy as well as increased scientific knowledge of wetland values over the past

35 years. The origin of this shift can be traced to the Federal Water Pollution and Control

Act of 1972 (later retitled the Clean Water Act), which identified a goal to restore and

maintain the biological, physical, and chemical integrity of the nation’s waters. This act

was followed by the Coastal Barrier Resource Act of 1972, the 1985 Food Security Act,

and the 1986 Tax Reform Act (Mitsch and Gosselink 2000). Wetlands are currently

regulated through Section 404 of the Clean Water Act, with regulatory duties being

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assumed by the US Army Corps of Engineers (USACE) and the US Environmental

Protection Agency (EPA) (Cole and Shafer 2002).

Another significant initiative in developing U.S. wetland policy was undertaken in

1987, when the National Wetland Policy Forum convened and set a significant goal for

the nations remaining wetlands, “no net loss.” The “no net loss” policy seeks to replace

lost wetland habitat with new habitat by restoring and/ or constructing wetlands. This

policy introduced wetland mitigation as the leading tool in combating wetland loss, and is

now the cornerstone of wetland conservation in the U.S. (Zedler 1996, Mitsch and

Gosselink 2000).

Reference Wetlands and Mitigation Success Although the increased pace of wetland restoration and construction is

encouraging, a key question still remains, “do the created and restored wetland sites

provide the same ecological and environmental functions as the natural wetlands they

were created to replace?” The ability of CWs and RWs to functionally replace natural

wetlands has become a topic of considerable debate (Mitsch and Wilson 1996, Zedler and

Callaway 1999, Kentula 2000).

Within compensatory mitigation there are three recognized levels of success:

compliance, landscape, and functional success. Compliance success is determined by

evaluating permit compliance, such as whether the mitigation site meets the acreage and

the percent vegetation cover specified in the permit. Landscape success is a measurement

of how restoration has contributed to the ecological integrity of the region or watershed,

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whereas functional success is determined by evaluating whether the ecological attributes

of a system have been restored (Quammen 1986, Kentula 2000). In a memorandum of

agreement in 1990 the US EPA and USACE agreed that mitigation was to focus on

functional replacement in addition to the replacement of area or structure (Hoeltje and

Cole 2007).

Several approaches have been used by researchers to assess mitigation success.

The Wetland Evaluation Technique (WET) assigns values to specific functions of

individual wetlands such as groundwater recharge and discharge, flood-flow alteration,

sediment stabilization and retention, nutrient removal/ transformation, wildlife and

aquatic diversity, production export, recreation, and uniqueness/ heritage (Adamus 1983).

The Environmental Monitoring and Assessment Program-Wetlands (EMAP) was

developed by the Environmental Protection Agency. This technique identifies indicators

of wetland condition which are used to determine the ecological functions of a group of

wetlands by comparing the function of a statistical sample of wetlands to reference

wetlands in a region (Novitzki et al. 1997). The hydrogeomorphic (HGM) method

developed by Brinson (1993) represents a combination of the WET and EMAP

approaches. The HGM method classifies and separates wetlands based on their

hydrodynamics and geomorphology, and then analyzes the functional characteristics of

wetlands within a single hydrogeomorphic class at both reference sites and sites across a

disturbance gradient (Brinson 1993, EPA 1997).

Today many researchers use reference wetlands to assess mitigation success

(Confer and Niering 1992, Bishel-Machung et al. 1996, Moore et al. 1999, Stolt et al.

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2000, Campbell et al. 2002, Bruland et al. 2003, Balcombe et al. 2005). Reference

wetlands are naturally-occurring, relatively-undisturbed systems that contain hydric soils,

support some if not all native, hydrophytic vegetation for some part of the year, and have

water tables near the surface for a considerable duration of the growing season (Brinson

and Rheinhardt 1996, Kentula 2000). Semi-natural wetlands (NWs) were used as

reference wetlands because there are few, if any, true “pristine, undisturbed” coastal

lowland wetlands left in Hawai‘i. Semi-natural wetlands serve as a standard for

comparison when evaluating the success of mitigation projects. Generally the ecological

attributes of a similar or nearby wetland are most commonly used. Single site studies and

comparisons of pairs of sites have been used to effectively evaluate the status of

individual projects; however the results cannot be extrapolated beyond the specific study

sites. Kentula (2000) recommends comparing samples of populations of NWs, RWs, and

CWs within an area in order to capture an entire range of conditions and factors

important to the function of wetlands.

Many of the functions discussed in previous sections, such as traps for sediments,

sinks for non-point source pollution, and denitrification of ground water are difficult and

costly to measure directly. Thus the use of reference wetlands is based on the underlying

assumptions that NWs represent high levels of functioning and that wetlands sharing

similar soil properties, hydrology characteristics, vegetation community, or

environmental conditions, function in a similar or equivalent manner (Brinson and

Rheinhardt 1996, Stolt et al. 2000, Zampella and Laidig 2003). Numerous variables have

been used when evaluating the success of CWs and RWs, with measurements of

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vegetation being most common (Galatowitsch and van der Valk 1996, Mitsch and Wilson

1996, Kentula 2000), followed by soils (Stolt et al. 2000, Craft 2001, Bruland and

Richardson 2004), hydrology (Ashworth 1997), and macrofauna (Brown and Batzer

2001). In this study, a quantitative investigation and inventory of coastal lowland

Hawaiian wetlands, I will assess vegetation community composition and soil chemical

and physical properties of NWs, RWs, and CWs in Hawaii.

Vegetative community composition and soil characteristics of 40 coastal lowland

wetland sites located across the 5 major Hawaiian Islands were sampled between March

and April 2007 (Figure 1.1). The sites consisted of 17 NWs, 11 RWs, 7 CWs, 4 former

fishponds, and 1 site under a flooded agriculture (taro) regime. The sites sampled met

three criteria: 1) they occurred across the 5 major Hawaiian Islands (Hawai‘i, Kauai,

Maui, Moloka‘i, and Oahu); 2) they were located between 0 – 300 meters in elevation;

and 3) they were representative of CWs, RWs, and NWs found within the state and were

available for sampling during the study period. A summary of the site characteristics is

provided in Table 1.1.

Although there are a wide variety of wetlands present throughout the state of

Hawai‘i, the focus of this project was on coastal lowland wetlands. The decision to focus

on one specific type of wetland stems from several factors. First, the objectives of the

project called for the comparison of wetland status (CWs vs. RWs vs. NWs). It was

assumed that wetlands that are of the same type, coastal lowland, will have similar

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Figure 1.1. Study site locations for the 17 semi-natural, 11 restored, and 7 created wetlands in Hawai‘i.

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physical and chemical properties or characteristics. Thus, the unexplained variability/

variance between wetlands will be minimized and the observed differences attributed to

their differences in status. Second, coastal wetlands play an important role in

maintaining water-quality in near-shore habitats. Theses wetlands are particularly

important to coral reefs because they protect reefs from turbidity, sediment, and pulses of

fresh water during heavy rains. The protection of coral reefs is important to numerous

commercial and recreational fisheries as well as tourism in Hawai‘i. Both recreational

and commercial fishing is important to Hawai‘i’s economy, which contribute $48 and

$63 million respectively (Stedman and Hanson 2007). Lastly, the accelerating

urbanization in coastal environments has resulted in greater pressure on these ecosystems

and the increased use of wetland restoration and construction as a tool for replacing NWs

(Craft et al. 1999).

Objectives and Hypotheses The overall objective of this study was to document the vegetative and edaphic

attributes of created, restored, and semi-natural coastal lowland Hawaiian wetlands. Site

characteristics were used to calculate statistical differences among wetlands of different

status (created vs. restored vs. semi-natural) and across hydrologic gradients within sites.

Both chapters of original research, the first which deals with wetland vegetation and the

second which deals with wetland soils, have their own specific objectives. Details

regarding the scientific background behind these objectives and hypotheses will be

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presented in the introduction to the individual chapters. The following is an outline of the

thesis chapters, objectives, and hypotheses:

Chapter 2: Wetland Vegetation

Objective 2-1: Compare vegetative community composition of CW, RW, and NWs.

Objective 2-2: To examine differences in vegetation across a hydrologic (wetness)

gradient within sites.

Hypothesis 2-1a: Vegetative community composition is different in CW/RW and NWs.

Hypothesis 2-2a: There are differences in vegetative community composition across the

hydrologic gradients present within the sites.

Chapter 3: Wetland Soils

Objective 3-1: To document soil properties such as bulk density, soil moisture content,

organic matter content, pH, extractable P, and total N and C in CW, RW, and NWs.

Objective 3-2: To compare soil properties of CW/NW to those of NWs.

Objective 3-3: To examine differences in soil properties across hydrologic (wetness)

gradient in CW/ RW and NWs.

Hypothesis 3-1a: Soil properties are different in CW/ RWs than in NWs.

Hypothesis 3-2a: There are differences in soil properties across the hydrologic gradient.

The concluding chapter will synthesize the individual objectives and hypotheses

to provide an overall assessment of the status of CWs, RWs, and NWs across the

Hawaiian Islands. It will also provide a ranking of CW, RW, and RW sites based on

vegetative characteristics, soil properties, and sites visits. Finally, recommendations on

how to improve wetland creation and restoration projects in Hawai‘i will be presented

14

Table 1.1. List of 17 semi-natural, 11 restored, and 7 created wetland study sites in Hawai‘i, including site name, island, status, and latitude and longitude.

Site Name Island Status Latitude Longitude Fed/State/ Private Water Source Bellows Oahu Semi-Natural 21.36368 -157.712 Federal Surface water Coconut Grove Oahu Semi-Natural 21.69591 -157.9682 Federal Groundwater Honoapu Hawaii Semi-Natural 19.08697 -155.5483 Private Surface water Kamilo Point 6 Hawaii Semi-Natural 18.9743 -155.6004 State Groundwater Kamilo Point 7 Hawaii Semi-Natural 18.97347 -155.60130 State Groundwater Kanaha Maui Semi-Natural 20.8889 -156.4569 State Surface water Kauaihau Riparian Kauai Semi-Natural 22.06493 -159.3308 Private Surface water Kawai Nui Oahu Semi-Natural 21.38363 -157.7616 State Surface water Kealia Maui Semi-Natural 20.79549 -156.476 Federal Groundwater Kilauea Kauai Semi-Natural 22.21847 -159.3878 Private Groundwater Lawai Kai Kauai Semi-Natural 21.89213 -159.5026 Private Surface water Nu‘u Maui Semi-Natural 20.62737 -156.1766 Private Groundwater Paiko Lagoon Oahu Semi-Natural 21.28202 -157.7234 State Surface water Paukukalo Maui Semi-Natural 20.91362 -156.4912 Private Groundwater Punamano Oahu Semi-Natural 21.69889 -157.9708 Federal Groundwater Waimea Oahu Semi-Natural 21.63894 -158.0604 Private Surface water Waipio Hawaii Semi-Natural 20.12094 -155.5988 Private Groundwater Hanalei Kauai Restored 22.20192 -159.471 Federal Groundwater Hamakua Oahu Restored 21.39082 -157.744 State Surface water Huleia Kauai Restored 21.94506 -159.3873 Federal Surface water Kauaihau Coastal Kauai Restored 22.06291 -159.323 Private Surface water

15

Table 1.1. Continued Site Name Island Status Latitude Longitude Fed/State/Private Water Source Ka‘elepulu Oahu Restored 21.37497 -157.7388 Private Surface water Kii Oahu Restored 21.68703 -157.9497 Federal Groundwater Koheo Molokai Restored 21.0844 -157.014 Private Surface water Ohiapilo Molokai Restored 21.10332 -157.05376 State Groundwater Pouhala Oahu Restored 21.3797 -158.006 State Surface water Waiawa Oahu Restored 21.38722 -157.982 Federal Surface water Waihe‘e Maui Restored 20.94133 -156.5102 Private Surface water Kakahaeia Molokai Created 21.06341 -156.9406 Federal Groundwater Kawaiele Kauai Created 22.01058 -159.769 State Groundwater Klipper Pond Oahu Created 21.45151 -157.7484 Federal Groundwater Moloka‘i Sea Farms Molokai Created 21.10474 -157.0862 Private Groundwater Nukolii Kauai Created 22.0138 -159.3387 Private Groundwater Percolation Ditch Oahu Created 21.4369 -157.7495 Federal Surface water Salvage Yard Oahu Created 21.43753 -157.7597 Federal Groundwater Keanai Maui Other 20.85939 -156.1473 Private Surface water Aimakapa Hawaii Fishpond 19.67635 -156.025 Federal Surface water Koloko Hawaii Fishpond 19.68707 -156.0313 Federal Surface water Mohouli Hawaii Fishpond 19.71549 -155.0765 State Surface water Ualapue Molokai Fishpond 21.05984 -156.8329 Private Surface water

16

Chapter 2. Wetland Vegetation

Introduction The saturated conditions found in wetlands during the growing season result in an

environment that favors the establishment and maintenance of hydrophytic vegetation

(Mitsch and Gosselink 1993). Hydrophytic vegetation is defined as:

“the sum total of macrophytic plant life that occurs in areas where the

frequency and duration of inundation or soil saturation produce

permanently saturated soils of sufficient duration to exert a controlling

influence on the plant species present” (Environmental Laboratory, 1987).

Due to characteristics of wetland ecosystems such as anoxia, wide ranges of salinity, and

water fluctuations, plants lacking certain physiological and structural adaptations are not

able to persist in wetland environments. This limiting effect has led to the use of

vegetation in the identification and delineation of wetland systems (Tiner 1999), such

that certain plant species and communities are characteristic of wetlands. The NRCS

(2007) has estimated that 7,000 species of plants are growing in U.S. wetlands, and the

affinity of these plants to grow in wetlands varies among plant species and regions.

Based on differences in expected frequency of occurrence in wetlands, these species

were designated to one of five “wetland indicator categories.” These include obligate

wetland species (OBL) that occur in wetlands greater than 99% of the time, facultative

wetland species (FACW) that occur in wetlands 67-99% of the time, facultative species

(FAC) that occur in wetlands 34-66% of the time, facultative upland species (FACU)

17

that occur in wetlands 1-33% of the time, and upland plant species (UPL) that occur in

wetlands less than 1% of the time (Tiner 1991, Erickson and Puttock 2006). This

classification system is used to categorize vegetation in sampling units. For example, if

50 percent of the dominant species are comprised of OBL, FACW, and FAC plants, then

the sampling unit meets the criterion for wetland vegetation as identified by the U.S.

ACOE (Environmental Laboratory, 1987). Besides their use in wetland identification

and delineation, vegetation has also been used to evaluate the success of mitigation

projects.

Vegetation plays a role in numerous wetland functions including nutrient uptake

and cycling, water quality regulation, flood retention and storm surge delay, and wildlife

habitat (Castelli et al. 2000). Numerous studies have shown that vegetative structure

and composition influence the quantity and quality of plant foods (Brown 1999), the

quantity and type of substrate available for invertebrates (Balcombe et al. 2005), and the

water chemistry (Goslee et al. 1997, Castelli et al. 2000). Due to the role that vegetation

plays in the aforementioned functions, wetland vegetation has also been used as an

indicator of environmental conditions. Herbaceous plants respond rapidly to both

degradation and improvement of wetland health and integrate disturbances at the

hydrologic, biogeochemical, and ecological scales (Ervin et al. 2006). Previous studies

have found significant relationships between water chemistry and soil physical and

chemical properties (pH, conductivity, temperature, or alkalinity) with plant community

composition (Ashworth 1997, Goslee et al. 1997, Hunt et al. 1999, Houlahan et al.

2006).

18

As vegetation is responsive to changes in environmental conditions, this

sensitivity to change can be used to identify or diagnose alterations in functions which are

difficult to directly measure. Because vegetation is relatively easy to sample and is

intricately involved in complex interactions that contribute to function, the composition

of wetland vegetation has become the most consistently measured ecological parameter

when it comes to monitoring the development of mitigation projects (Craft et al. 2002).

In this chapter, I compared vegetative community characteristics, including species

richness, percent cover, percent exotic species cover, and wetland indicator status, among

different types of wetlands (i.e. NWs vs. RWs vs. CWs) and along hydrologic gradients

within wetlands.

It should be noted that CWs and RWs in Hawai‘i are designed and managed for

open space and water which is desirable for waterbird habitat. Thus having a high

percentage of vegetative cover is not appropriate to maximize this function. Conversely,

waterbird habitat does not always favor ecological functions such as water quality

improvement. It is recognized that that there are multiple functions and uses of wetlands

and that these functions may be contradictory to one another. Therefore, for the purpose

of this study vegetation properties are evaluated based on environmental and ecological

functions, rather than for waterbird habitat.

Objectives and Hypotheses The two major objectives of this chapter were as follows: (3-1) To compare

vegetative community composition of CWs, RWs, and NWs; and (3-2) To examine

19

differences in vegetation across hydrologic (wetness) gradients within sites. As

previously noted, vegetation has often been the easiest and most common method used to

monitor the progress of mitigation projects (Wilson and Mitsch 1996). Many studies

have compared species richness, composition, and cover between natural and mitigation

wetlands throughout the conterminous U.S. Some studies have found that species

richness or cover is greater in RWs than NWs (Galatowitsch and van der Valk 1996,

Heaven et al. 2003), whereas other studies have found that NWs have greater species

richness or cover (Brown 1999, Brown and Veneman 2001, Campbell et al. 2002,

Seabloom and van der Valk 2003), or that there is no difference (Confer and Niering

1992, Parikh and Gale 1998). The findings in these studies were not in accordance with

each other, therefore non-directional hypotheses were used in this study. The two main

hypotheses tested were: (3-1a) Vegetative community composition is different in

CW/RW and NWs; and (3-2a) There are differences in vegetative community

composition across the hydrologic gradient.

Methods

Study Sites Forty coastal lowland wetlands across the state of Hawai‘i were sampled (Table

1.1, page 20-21; Figure 1.1, page 16). These sites were located below 300 m in elevation

on the islands of Oahu, Maui, Kauai, Moloka‘i, and Hawai‘i. Of the 40 wetlands studied,

17 sites were NWs, 11 sites were RWs, 7 sites were CWs, 4 sites were former fishponds,

and one site was under a flooded agricultural regime.

20

Vegetation Sampling

Vegetation sampling occurred between March and April of 2007. At each of the

40 wetland sites, four representative transects were identified and then two were

randomly selected for sampling. Transects spanned the major hydrologic gradient

present within each site, beginning at the wetter edge and continuing up to the drier edge

of the site. For riparian and tidal wetlands, transects ran perpendicular to the stream or

tidal creek, while for isolated wetlands transects radiated outward from deepwater zones

in random directions (Figure 2.1). The selected transects were then stratified into three

zones (wet, intermediate, and dry) based on wetness, elevation, and visual changes in

plant community composition. In each zone a single 1-m2 quadrat was randomly placed

along the two transects. The specific location of each quadrat corresponded to the

locations used for the soil core sampling (Chapter 3). This sampling design generated to

a stratified random sample and followed a protocol recommended by the Hawaii Wetland

Field Guide (Erickson and Puttock 2006).

Vegetation sampling consisted of recording species composition and percent

cover. Within each 1-m2 quadrat each unique species was identified in the field by genus

and species using Whistler (1994) and Erickson and Puttock (2006). A species was

recorded if any of their above-ground parts extended into the quadrat, even though they

were be rooted outside the plot. In addition to percent cover of each unique species,

exposed substrate, standing water, and percent cover of litter were recorded by visual

21

Figure 2.1. Sampling design for riparian and isolated wetland sites.

Transect 1

Transect 2

Stre

am /

Tida

l Cre

ek

Hydrologic Gradient

Wet

Inte

rmed

iate

Drie

r

S1 S2 S3

S4 S5 S6

Hydrologic Gradient

Wet

Inte

rmed

iate

Drie

r

a. Riparian or tidal sites

b. Isolated wetland sites

Transect 1

Transect 2

Pond

S1S2

S3

S4S5

S6

22

estimation. At least two investigators generated coverage values independently and then

compared values with one another. If the independently-generated values differed, the

average of the two values was recorded. Voucher specimens were collected when

additional identification was necessary. Upon returning to the University of Hawai‘i,

Mānoa, the voucher specimens were dried and pressed at 60oC for a minimum of 5 days

then delivered to Bishop Museum Herbarium located in Honolulu, Hawai‘i for further

identification.

Data Analysis All sites were included when summarizing the overall vegetative results such as

total number of species observed. Statistical analyses, however, were only conducted on

the sites designated as NWs, RWs, and CWs. Semi-natural wetlands, RWs, and CWs

were compared by calculating mean species richness, percent cover of exotic species,

percent cover of wetland plant species, and total cover for each zone. Native species

status was assigned based on Erickson and Puttock (2006) and Starr and Starr (2007).

Wetland indicator status was assigned based on the National Resource Conservation

Service Plant Database (2007). Species richness was defined as the total number of plant

species present in a quadrat (Kent and Coker 1992), and percent cover of wetland plant

species was defined as the sum of cover from species in a plot with a wetland indicator

status of facultative (FAC), facultative wet (FACW), or obligate (OBL) (Environmental

Laboratory, 1987).

Due to the unbalanced study design (17 NWs, 11 RWs, and 7 CWs) the data were

analyzed using a fixed, two-factor generalized linear model (GLM) procedure in Minitab

23

Statistical Software for Windows Version 15 (Minitab Inc., State College, PA) and SAS

for Windows Version 9.1 (SAS Institute, Cary, NC). The independent factors tested were

wetland status (NW vs. RW vs. CW), hydrologic zone (wet vs. intermediate vs. dry), and

the status by zone interaction. The response variables included mean species richness,

mean exotic cover, mean cover of wetland plant species, and mean total cover.

Additionally, a one-way analysis of variance (ANOVA) was used to evaluate the effect of

island on the same dependent variables in the GLM. Assumptions of normality were

evaluated and Levene’s Test was used for homogeneity of variances. A post-hoc Tukey

test was used in cases of a significant main effect (status, zone, or status x zone). A

significance level of p < 0.05 was used for both the GLM and ANOVA and the post-hoc

Tukey tests.

To examine and identify the similarities and/or differences in vegetative

composition as well as to summarize the vegetative data, a Principle Components

Analysis (PCA) was conducted using the PC-ORD program (McCune and Mefford

1999). PCA is an eigenanalysis ordination technique that produces orthogonal axes,

which captures the highest amount of variation that is present in the data set (Hair et al.

1995, McCune and Grace 2002). The species cover data was placed into a

species*quadrat matrix, then arcsine-square root transformed. In order to rescale the data

to range between 0 and 1, it was then multiplied by 2/π. As recommended by McCune

and Grace (2002), all rare species (species that occurred in fewer than 5% of the sample

units) were removed from the analysis. Additionally, the sites designated as fishponds

and the site under the flooded agriculture regime were removed from the PCA.

24

To assess affinities of species to wetland status and salinity classes an indicator

species analysis (Peterson and McCune 2001) was conducted on the vegetation cover

data using PC-ORD (McCune and Mefford 1999). Indicator species analysis is a

nonparametric technique used to identify species with a high fidelity for a particular

group (King et al. 2004). All positively-identified species were placed in a

species*quadrat matrix and 4,999 permutations were used in the Monte Carlo test of

significance. A significance level of p < 0.05 was used for the Monte Carlo test.

Results A total of 101 plant species were positively identified within 240 quadrats

(Appendix A and B). The number of species observed within the different zones

increased along the hydrological gradient, such that the wet zone had the least amount of

species (35 species) followed by the intermediate zone (57 species), and the dry zone (71

species). Furthermore, NWs had the greatest number of species observed with 67, of

which 20 were unique to NWs. Forty-two species were observed in RWs and 30 in CWs.

Finally, 40 species were found in the 4 fishponds and flooded agriculture site. For all

species sampled, mean species richness was significantly different among wetlands of

different status as well as across the hydrologic gradient (Table 2.1). Species richness

was significantly greater in CWs than in RWs as well as significantly increased along the

hydrologic gradient. The wet zone had the lowest species richness, followed by the

intermediate, and the dry zone (Figure 2.2). Like species richness, mean total vegetative

cover was significantly different for both wetland status and position along the

25

Table 2.1. Results of the GLM ANOVAs testing for significance of wetland status, hydrologic zone, and wetland status by hydrologic zone effects for mean species richness (SR), mean total wetland vegetation (OBL, FACW, and FAC species), mean cover of exotic species, and mean total cover. All significant effects (p < 0.05) are indicated by underlining.

Vegetation Property Source of Variation df† F P Species Richness status 2 5.20 0.007 zone 2 11.29 0.000 status x zone 4 0.38 0.822 Total Wetland Veg (%) status 2 2.37 0.099 zone 2 2.34 0.101 status x zone 4 1.68 0.161 Exotic Cover (%) status 2 0.95 0.392 zone 2 4.61 0.012 status x zone 4 0.91 0.461 Total Cover (%) status 2 3.70 0.028 zone 2 6.48 0.002 status x zone 4 1.20 0.314 † Error degrees of freedom = 100

26

Figure 2.2. Effect of position along the hydrologic gradient and wetland status on species richness. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 2.3. Effect of position along the hydrologic gradient and wetland status on total cover. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

BE

AC

A

B

DCE CDEBE

BEAD

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Wet Intermediate Dry

Species Richne

ss

Hydrologic Zone

CWs

RWs

NWs

BC

AC

AC

B

AB

AC

AC

A

AC

20

30

40

50

60

70

80

90

100


(%) T

otal Cover

Hydrologic Zone

CWs

RWs

NWs

27

hydrologic gradient (Table 1). For example, NWs had significantly greater cover than

RWs (Figure 2.3), and total cover tracked the hydrologic gradient for all wetland types

according to the Tukey test. There was a major convergence of total cover in the dry

zones for all wetland types, such that each wetland type had approximately 80% total

cover in the dry zone.

The majority of the species observed were introduced with only 17 (17 %) native

species present across all sites. Overall, there was higher cover of exotic species cover in

NWs than CWs and RWs in the wet and intermediate zones. Statistical analysis of exotic

species cover indicated that position along the hydrologic gradient was significant, while

wetland status and their interaction were not (Table 2.1). The post-hoc Tukey test

indicated that mean percent cover of exotic species was greater in the dry zone than in the

wet zone (Figure 2.4). Overall, the most common species observed within the 210

sample quadrats were Urochloa mutica (California grass), Batis maritima (pickelweed),

Paspalum vaginatum (seashore paspalum), and Bacopa monneri (water hyssop). U.

mutica, B. maritima, and P. vaginatum are exotic and considered highly-invasive

(Erickson and Puttock 2006), whereas B. monneri is a native.

For all species sampled, 15 of 101 were obligate (OBL), 13 were facultative wet

(FACW), 29 were facultative (FAC), 21 were facultative upland (FACU), 3 were upland,

and the remaining 20 species were undesignated (Erickson and Puttock 2006, USDA and

NRCS 2007). Percent of species by wetland indicator status was calculated for all

species sampled within the quadrats. According to the two-factor GLM, neither wetland

status nor position along the hydrologic gradient were significant factors in accounting

28

Figure 2.4. Effect of position along the hydrologic gradient and wetland status on exotic species cover (%). Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 2.5. Effect of position along the hydrologic gradient and wetland status on total wetland vegetation cover (OBL, FACW, FAC species). Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

AC

AB

AB

A

AC

B

AC

BC BC

0

10

20

30

40

50

60

70

80

90

100


Exotic Cover

Hydrologic Zone

CWs

RWs

NWs

AB

BC

AB

AE

ADE

BCD

BCD

BCD

BCD

25

35

45

55

65

75

85

95


Total W

etland

Vegetation Co

ver (%

)

Hydrologic Zone

CWs

RWs

NWs

29

for the variability in mean percent cover of wetland vegetation (OBL, FACW, and FAC

species) (Table 1). Although not statistically significant, mean cover of wetland

vegetation was slightly greater at CWs (69.3%) than in NWs (68.4%) and RWs (53.6%)

(Figure 2.5).

The number of species observed at a given site (excluding Keanai) ranged from 1

to 13. The Percolation Ditch site located on Oahu was the most diverse with 13 species,

whereas the Moloka‘i Sea Farms and Ohiapilo sites, both located on the island of

Molaka‘i, were dominated by a single exotic species, B. maritima. Lastly, the Klipper

Pond site, a CW located at Marine Corps Base Hawai‘i on the island of Oahu, had the

greatest number of native species present with a total of 6.

In addition to the 101 identified species, another 10 species were observed but

could not be identified beyond the family level and were thus designated as unknowns.

Seven of the unknown plants were sterile grasses (Poaceae family), two were in the

Convolvulaceae family, and the final unknown was in the Chenopodiaceae family. The

number of unknowns was equally common in the intermediate and dry zones, and least

common in the wet zone. Furthermore, the unknowns occurred across a number of sites,

and were present on all islands, except Moloka‘i.

The effect of island on the vegetation properties was also evaluated. All means

and standard errors are presented in Table 2.2. The one-way ANOVA indicated that both

mean total cover (F4, 35 = 3.43, P = 0.018) and mean percent cover of wetland vegetation

(F4, 35 = 4.29, P = 0.006) were significantly different among islands. According to the

30

Table 2.2. Means and standard errors for mean species richness, mean total wetland vegetation (OBL, FACW, and FAC species), mean exotic cover, and mean total cover. Means with different letters are significantly different at the p < 0.05 level according to the Tukey test.

___Moloka‘i__ ___Kauai___ ___Maui____ ____Oahu_____ ____Hawai‘i___

Vegetation Property Mean SE Mean SE Mean SE Mean SE Mean SE

Species Richness 1.30 a 0.19 2.60 a 0.24 2.23 a 0.41 2.30 a 0.31 2.21 a 0.52

Total Wetland Veg. (%) 82.5 a 15.2 68.04 ab 7.03 66.57 ab 9.48 50.52 b 5.24 80.54 a 6.30

Exotic Cover (%) 82.5 a 15.2 54.06 a 8.37 55.8 a 15.8 47.37 a 5.35 58.3 a 17.9

Total Cover (%) 82.5 a 15.2 71.67 ab 5.98 72.27 ab 9.70 59.32 b 5.53 92.21 ab 2.46

31

Table 2.3. Indicator species for wetland status. Monte Carlo test of significance of observed maximum indicator value (IV) for species, based on 4999 randomizations. A significance level of p < 0.05 was used for the Monte Carlo test.

Species

Status

Observed Indicator Value

p-value

Batis maritima CW 47.8 0.0154 Urochloa mutica NW 50.8 0.0120

Table 2.4. List of indicator species for each salinity class. Monte Carlo test of significance of observed maximum indicator value (IV) for species, based on 4999 randomizations. A significance level of p < 0.05 was used for the Monte Carlo test.

Species

Salinity

Observed Indicator Value

p-value

Thespesia populnea Hyperhaline 39.8 0.0486 Bare ground Hyperhaline 40.7 0.0096 Chloris barbata Hyperhaline 42.4 0.0258 Batis maritima Euhaline 59.4 0.0002 Paspalum vginatum Brackish 64.3 0.0002 Bacopa monnieri Fresh 41.5 0.0440 Ipomoea triloba Fresh 29.5 0.0412 Ludwigia octovalis Fresh 39.6 0.0200 Sphagneticola trilobata Fresh 48.9 0.0138 Schoenoplectus spp. Fresh 50.8 0.0050 Cyperus polystachos Fresh 47.6 0.0032 Urochola mutica Fresh 48.0 0.0024 Commelina diffusa Fresh 52.4 0.0008

32

Tukey test, Hawai‘i had significantly greater total cover than Oahu, and Moloka‘i and

Hawai‘i had significantly greater wetland vegetation cover than Oahu. Neither species

richness (F4, 35 = 1.10, P = 0.373) nor exotic cover (F4, 35 = 1.92, P = 0.129) were

significantly different among islands (Table 2.2).

The results of the indicator species analysis are provided in Table 2.3 and Table

2.4. According to the Monte Carlo test, B. maritima was a significant indicator of CWs

and U. mutica was a significant indicator of NWs. The test failed to identify any

significant indicators species for RWs. When the fishpond sites were included in the

species indicator analysis, the Monte Carlo test identified numerous indicator species for

this wetland type. However due to the small sample size of fishponds and their

restriction to two islands, the fishpond sites were removed from the final indicator species

analysis. Eight species were significant indicators of freshwater sites, one species each

for brackish and euhaline sites. Commelina diffusa and U. mutica were the best

indicators for the freshwater sites, while the bare ground cover category was a significant

indicator for the hyperhaline sites, and B. maritima and P. vaginatum were significant

indicators for the euhaline and brackish sites, respectively. Each of these top-ranking

indicator species are considered highly invasive in Hawaiian wetlands. Two native

species were found to be significant indicators for freshwater sites, Cyperus polystachos

and B. monnieri.

Results of the PCA are shown in Figure 2.6. Each point on the graph represents

an individual quadrat. Points that are close together in ordination space represent

33

Axi

s 2

(13.

7%)

Figure 2.6. Principle components analysis (PCA) of the species composition of coastal lowland Hawaiian wetlands. Vectors represent the magnitude of correlation with axis 1 and 2 (i), and 1 and 3 (ii). Axes 1, 2, and 3 accounted for 14%, 14%, and 12% of the total variance respectively.

Batis maritima

Urochola mutica

Bolboschoenus maritimus

Bacopa monnieri Paspalum vaginatum

Axis 1 (14.4%)

x

Site Salinity Freshwater Brackish Euhaline Hyperhaline

i

34

Figure 2.6. Continued

Pluchea indica

Urochola mutica

Bolboschoenus maritimus

Sesuvium portulacastra

Paspalum vaginatum

Axis 1 (14.4%)

Site Salinity

Axis

3 (1

1.9%

)

ii.

X Euhaline

Fresh Brackish

Hyperhaline

35

quadrats that have similar species composition, whereas points that are farther apart

represent quadrats that share few if any common species. Axis 1, 2, and 3 accounted for

14%, 13%, and 12% of the total variance in the data (Figure 5). Species with relatively

strong positive loadings on axis 1 were U. mutica, P. vaginatum, and B. maritimus. Batis

maritima had a strong positive loading on axis 2, and Sesuvium portulacastrum (sea

purslane) and Pluchea indica (Indian fleabane) had strong positive loadings on axis 3.

The sites grouped together based on their site salinity class, regardless of their wetland

status, zone, and island (site salinities were measured using a handheld YSI Model 556

Multi probe system). Freshwater sites grouped together at the high end of axis 1 and axis

2, indicating greater cover of U. mutica. Additionally, brackish sites tended to group

together at the low end of axis 1 indicating high percent cover of B. maritimus, P.

vaginatum, and B. monnieri. Finally, both euhaline and hyperhaline sites appear to be

dominated by the highly invasive species, B. maritima.

Discussion This data set provides an overall picture of the vegetation of coastal lowland

wetlands in Hawai‘i. Based on this sample, a disproportionate amount of the species

sampled were exotic. Specifically, non-native plant species accounted for 83% of all

species observed. In this survey, species richness also varied widely from 1 to 13 across

the sites sampled. The sites with the fewest species (Moloka‘i Sea Farms and Ohiapilo)

were both located on Moloka‘i. Furthermore, the site with the greatest number species,

Percolation Ditch, and the site with the greatest number of natives, Klipper Pond, were

36

both CWs located at Marine Corps Base Hawai‘i on the island of Oahu. The largest

number of native species observed at Klipper Pond is the result of the planting of native

species during site creation and periodic removal of exotics.

A detailed comparison of CWs, RWs and NWs in Hawai‘i revealed that the effect

of position along the hydrologic gradient was more pronounced than the effect of wetland

status. Hydrologic zone accounted for a significant portion of variance in mean species

richness, mean exotic cover, and mean total cover. While wetland status accounted for a

significant portion of variance in mean species richness and mean total vegetative cover,

the effect accounted for a slightly smaller portion of the variability when compared to the

effect of position along the hydrologic gradient.

The effect of hydrologic zone differed with respect to most of the variables

measured. The only exception was the mean total cover of wetland vegetation (OBL,

FACW, and FAC species). The other variables, mean species richness, mean cover of

exotic species, and mean total cover, all followed the same trend, such that they were

greatest in the dry zone, followed by the intermediate, and then the wet zone. In all, the

dry zone was significantly greater than the wet zone and was only slightly greater than

the intermediate zone. The differences observed in the vegetative characteristics (species

richness, exotic cover, and total cover) among the wet, intermediate, and dry zones were

likely due to the major stresses that persist in wetland ecosystems: anoxia, wide ranges in

surface and porewater salinity, and fluctuations in water levels. Most organisms are

unable to survive in these conditions, thus limiting the number and species found within

wetlands (Mitsch and Gosselink 1993).

37

The vegetation of CWs and RWs were similar to that of NWs in a number of

ways. Mean species richness, mean cover of wetland vegetation, mean cover exotic

species, and mean vegetative cover of CWs compared favorably to NWs. Furthermore,

the performance of RWs is only in question with relation to the mean total vegetative

cover such that it was found that NWs (76%) have a significantly greater cover of mean

vegetation than RWs (59%). Some studies have shown NWs have a greater total

vegetative cover than mitigation wetlands, which can be attributed to differences in age

(Confer and Niering 1992, Heaven et al. 2003). Additionally, RWs in Hawai‘i are

typically managed for waterbird habitat which requires greater amounts of open water.

High values of vegetative cover are not necessarily desirable for bird habitat, thus greater

total cover in NWs than in RWs may be a result in differences in management goals.

Although I observed a significant difference between NWs and RWs, CWs and NWs had

similar mean total cover. The lack of a significant difference between mean total cover in

NWs and CWs could be due to an increase in soil nutrient availability caused by the

flooding of upland mineral soils (Confer and Niering 1992). As available nutrients are

used up over time a decrease in plant cover is likely to occur.

It was interesting that the mean cover of wetland vegetation and mean cover of

exotic species were similar among CWs, RWs, and NWs. Typically, the total cover of

exotic species increased from the wet to the dry zone. Again, this trend in increasing

cover from the wet to dry zone can be attributed to the environmental stresses associated

with living in the wet zone of a wetland. The exotic species observed in this study may

lack the physiological adaptations required to be successful in the wetland environment.

38

If this study were to have sampled more sites with Rhizophora mangle (mangrove), it

would be expected that this trend would be more subtle or reversed as it was at the

Bellows site on Oahu where R. mangle was present.

Although wetland status had a significant effect on mean species richness, the

difference occurred between CWs and RWs, with both having mean species richness

similar to NWs. It was expected that there would be more pronounced differences

between CWs, RWs, and NWs in the above mentioned explanatory variables. Although

the statistical results of this study indicated that mean species richness, mean cover of

wetland vegetation, and mean cover of exotic species were similar among wetland types,

not all studies have yielded similar results. Campbell et al. (2002) attributed differences

between vegetation features such as species richness and total vegetative cover in CWs,

RWs, and NWs to the age of the mitigation project. Seabloom and van der Valk (2003)

also found species diversity in RWs to be limited by age as well as by landscape

isolation. Heaven et al. (2003) further recommend evaluating mitigation projects not

only relative to their age, but also to their size, context, and disturbance, to better explain

differences and similarities between CWs, RWs, and NWs. Unfortunately metadata such

as the age of RWs and CWs is difficult to obtain as a number of the sites have changed

ownership multiple times and little if any information on site histories are available. It

would be useful to collect this information and perform additional analyses to determine

the root of the similarities and dissimilarities.

Using PCA, additional differences in vegetative composition were revealed that

were not obtained using univariate procedures. The ordination of vegetation quadrats

39

revealed that the association of quadrats in ordination space appeared to be driven more

by site salinity than wetland status, the hydrologic gradient, or island (Figure 2.6). In the

PCA, the majority of the freshwater sites were positioned in an area of ordination space

correlated with a high total cover of U. mutica. Brackish water sites were positioned in a

space correlated with a high percent cover of B. maritimus, P. vaginatum, and B.

monnieri and low cover of U. mutica. Although there appeared to be a correlation

between salinity and species composition, none of the principle component axes were

significant according to the broken-stick eigenvalue test. Axis 1, 2, and 3 only recovered

a total variance 40% in the vegetation data (Figure 2.6), thus suggesting that there may be

additional environmental variables driving the vegetation composition found in coastal

lowland Hawaiian wetlands.

The indicator species analysis identified two highly invasive species, B. maritimus

as an indicator for CWs and U. mutica as an indicator species for NWs. The analysis,

however, failed to identify any significant indicator species for RWs. This suggested that

RWs share common species with both NWs and CWs. The fact that both indicator

species listed above are invasive was not surprising given the overwhelming number of

exotic species (78) that were observed in this study. These findings raise some concerns

regarding the dominant presence of invasive species in coastal lowland Hawaiian

wetlands, such as a lack of management or removal of invasive species. This also

suggests that it may be difficult to locate “reference” sites for coastal lowland wetlands

due to the pervasive nature of invasive species encroachment in the Hawaiian Islands.

40

Chapter 3. Wetland Soils

Introduction While current monitoring of created and restored wetlands nearly always includes

some measure of vegetation as a performance standard (Mitsch and Wilson 1996, Cole

2002, Spieles 2005), it typically does not require monitoring of soil properties or

processes (Shaffer and Ernst 1999) since soil transformations are thought to be slow and

vegetation is relatively easy to sample (Atkinson et al. 2005). This is problematic

because soils are the physical foundation for every wetland ecosystem. Both plants and

animals are dependent upon wetland soils for growth and survival (Stolt et al. 2000). For

example, soils serve as a storage reservoir of available chemicals and nutrients for most

wetland plants and are also the medium in which many nutrient and chemical

transformations take place (Mitsch and Gosselink 2000).

The physical and chemical properties of soil reflect the condition of the wetland

environment, such that proper hydrological function will result in wetland soils with

characteristic pH values (Bishel-Machung et al. 1996, Galatowitsch and van der Valk

1996) and soil organic matter content (Campbell et al. 2002). As soils play an essential

role in many wetland functions and are a critical factor in project development, they are

also useful parameters for comparison. Given the important role that soils play in the

biogeochemical processes that occur in wetlands, the measurement of soil properties has

become more common when evaluating wetland mitigation projects. Soil properties,

such as soil organic matter (SOM), nutrient content, and particle-size distribution have

been shown to reflect the wetland environment and have thus been used to evaluate and

41

compare mitigation and reference wetlands (Craft et al. 1988, Bishel-Machung et al.

1996, Shaffer and Ernst 1999, Stolt et al. 2000, Craft 2001, Campbell et al. 2002, Bruland

and Richardson 2004, Bruland and Richardson 2005a, Bruland and Richardson 2006).

Soil organic matter is a frequent parameter used to assess soil development

(Campbell et al. 2002) because it is an important indicator of soil quality (Bruland and

Richardson 2004). Organic matter accumulates in wetlands as a result of the anaerobic

conditions caused by inundation or saturation of soils which slows down decomposition

and allows organic matter to accumulate (Hogan et al. 2004). The accumulation and

decomposition of SOM in wetland soils has an important effect on nutrient storage and

recycling, which in turn has numerous effects on the wetland structure and function.

Previous research has shown that SOM supports and regulates a number of wetland

functions, such as secondary production by contributing detritus to benthic organisms

(Craft et al. 1999). Soil organic matter also fuels microbial processes such as

denitrification and nitrogen fixation (Craft 2001). Low SOM has been associated with

poor plant community establishment and growth as well as altered nutrient cycling

(Shaffer and Ernst 1999). Additionally, SOM influences several other soil properties and

processes such as bulk density, pH, total nitrogen, moisture, and phosphorus sorption

(Bishel-Machung et al. 1996, Bruland and Richardson 2004).

Nutrient content, such as carbon and nitrogen levels have also been used to

evaluate the development of wetland mitigation projects. The measurement of nutrient

pools (C, N, and P) is important because they are critical for the development of

ecosystem processes (Craft 2001). Soils store the nutrients necessary for vegetative

42

growth and development. The availability of nutrients can greatly affect plant

distribution, abundance, productivity, reproductive potential, and standing biomass.

Extreme nutrient levels in a wetland soil can even prevent the colonization of some

vegetative species (Neckles et al. 2002). These features in turn influence vertebrate and

invertebrate biota by altering ecosystem processes such as primary productivity and food

chain support (Langis et al. 1991).

Soil properties such as water-holding capacity, cation exchange capacity,

permeability, and porosity are largely controlled by particle-size distribution (% clay, %

silt, % sand) (Stolt et al. 2000). Poach and Faulkner (1998) found that wetland soils

dominated by sands are much less effective in retaining nutrients as well as are unable to

hold sufficient water for plant survival as compared to soils dominated by silts and clays.

Additionally, exchange capacities have been shown to be directly correlated with clay

and organic matter content (Stolt et al. 2000). Cation exchange sites in soils are critical

for holding essential plant elements such as Ca, Mg, and K. Wetland sites with greater

amounts of sand have lower water-holding and exchange capacities, and greater porosity

and permeability compared to sites with lower amounts of sand.

Objectives and Hypotheses Due to the dynamic relationships between wetland soil properties, vegetation, and

hydrology, the comparison of physical and chemical soil properties across wetlands can

provide insights into the cumulative effects of hydrology and vegetation of a site. The

objectives of this chapter were as follows: (3.1) To document differences in soil

43

properties such as soil moisture, bulk density (BD), soil organic matter content (SOM),

pH, electrical conductivity (EC), extractable P (ExP), total N (TN), total carbon (TC), and

particle size distribution in CW, RW, and NWs; (3.2) To examine differences in soil

properties across hydrologic (wetness) gradients in CW/ RW and NWs; and (3.3) To

examine the correlation structure among the measured soil properties. The corresponding

hypotheses tested in this chapter were as follows: (3-1a) Soil properties are different in

CW/ RWs than in NWs; and (3-2a) There are differences in soil properties across the

hydrologic gradient.

Methods and Materials

Soil Survey Soil samples were taken in the center of each 1-m2 quadrat identified during the

vegetation survey (Chapter 2). Soil cores were collected from the upper 0 – 20 cm of the

soil profile using a stainless steel piston corer with a circular plastic sleeve insert of 4.8

cm diameter. Once collected, samples were capped and stored on ice until being

transported back to UHM Soil and Water Conservation Laboratory.

Laboratory Analysis Upon returning to UMH, the soil cores were removed from the plastic sleeves and

sliced in half vertically with a sharp knife. Half of the core was oven dried at 105ºC for

24 hours to determine moisture and BD. The ratio of the mass of water to the volume of

the core half (core radius = 2.4 cm) was used as soil moisture (g·cm-3) (Bruland and

Richardson 2004), and the ratio of oven dried soil to the volume of soil resulted in the

44

bulk density (g•cm-3) (Wilke 2005). The dry half of the core was passed through a 2mm

mesh sieve to remove rock fragments and other large organic debris. The dried and

sieved soil was used to determine the percent soil organic matter (SOM) content by loss

on ignition at 450oC for 4 hours (Bruland and Richardson, 2006), and soil texture (%

sand, % silt, % clay) by the pipette method (Tan 1996). Particle size was only

determined for soils with a SOM content less than 30%, as soils with SOM above this

threshold were considered to be organic.

Representative 30 gram sub-samples were placed in small plastic vials and

delivered to the College of Tropical Agriculture and Human Resources Agricultural

Diagnostic Service Center (ADSC) for analysis of pH, EC, TC, TN, and ExP. pH was

measured with a Beckman pH meter (Hue et al. 2000). Extractable phosphorus was

measured using the Olsen extraction (Olsen 1982). Total carbon and TN were measured

using a LECO CN2000 combustion gas analyzer (AOAC International 1997). Lastly, EC

was quantified with a conductivity bridge (Hue et al. 2000).

Data Analysis The fishpond sites and the site under the flooded agriculture regime (Table 1.1)

were excluded from all statistical analyses. Natural wetlands, RWs, and CWs were

compared by calculating mean moisture, BD (g•cm-3), SOM (%), clay, silt, sand, TN (%),

TC (%), pH, EC (mmho•cm-1), and ExP (µg•g-1).

Due to the unbalanced study design (17 NW sites, 11 RW sites, and 7 CW sites)

the data were analyzed using a fixed, two-factor generalized linear model (GLM)

procedure in Minitab Statistical Software for Windows Version 15 (Minitab Inc., State

45

College, PA) and SAS for Windows Version 9.1 (SAS Institute, Cary, NC). The

independent factors tested were wetland status (NW vs. RW vs. CW), hydrologic zone

(wet vs. intermediate vs. dry), and the status by zone interaction with response variables

being moisture, bulk density, SOM, clay, silt, sand, TN, TC, pH, EC, and ExP. As SOM,

EC, TN, and TC were non-normally distributed, SOM, EC, and TN were square-root

transformed and the last was log-transformed before conducting the GLM analysis. The

remaining soil properties met the assumption of normality. Levene’s Test was used to

test for homogeneity of variances. A post-hoc Tukey test was used in cases of a

significant main effect (status, zone, or status x zone). A significance level of p < 0.05

was used for both the GLM and the post-hoc Tukey tests.

A one-way analysis of variance (ANOVA) was used to evaluate the effect of

island on the same dependent variables in the GLM. As SOM, EC, TN, TC, and ExP did

not meet the assumption of normality of homogenous variances the data were log-

transformed before conducting the ANOVA. Both soil pH and BD did not meet the

assumption of homogenous variances even after transformation, and thus the effect of

island was not evaluated in respect to these properties. A post-hoc Tukey test was used

in cases of a significant island effect. A significance level of p < 0.05 was used for both

the ANOVA and the post-hoc Tukey tests.

A correlation analysis was also conducted to identify the relationships among the

eleven soil properties. Due to the non-normally distributed data, the soil properties were

46

Table 3.1. Descriptive statistics for bulk density (BD), soil organic matter (SOM), pH, electrical conductivity (EC), total nitrogen (TN), total carbon (TC), moisture, extractable phosphorus (ExP), clay, silt, and sand.

BD (g cm-3) SOM (%) pH EC

(µS cm-1) TN (%) TC (%)

Mean 0.55 22.1 6.87 28.7 0.53 10.01 Median 0.55 17.5 7.30 9.8 0.29 6.38 Standard Error 0.02 1.2 0.08 3.2 0.04 0.66 Range 1.73 87.4 5.30 399.6 2.96 55.73 Minimum 0.02 1.5 3.50 0.4 0.00 0.74 Maximum 1.76 88.9 8.80 400.0 2.96 56.47 Count 236 236 236 236 236 236 Moisture (g cm-3) ExP (μg g-1) Clay (%) Silt (%) Sand (%) Mean 0.41 60.39 33.70 29.14 37.16 Median 0.42 42.50 33.53 30.94 31.52 Standard Error 0.012 3.90 1.35 1.37 2.34 Range 0.92 438.70 78.20 65.30 97.09 Minimum 0.025 2.30 2.82 0.00 0.09 Maximum 0.95 441.00 81.03 65.30 97.18 Count 236 236 175† 175 175 † The count is 175 for clay, silt, and sand as particle size was not determined on samples with > 30 % SOM

47

Table 3.2. Results of the GLM ANOVAs testing for significance of wetland status, hydrologic zone, and wetland status by hydrologic zone effects for mean moisture, bulk density (BD),soil organic matter (SOM), pH, total nitrogen (TN), total carbon (TC), conductivity (EC), and extractable phosphorus (ExP). All significant effects (p < 0.05) are indicated by underlining.

48

Soil Property Source of Variation df† F P Moisture (g cm-3) Status 2 0.69 0.504 Zone 2 10.51 0.000 status x zone 4 0.94 0.444 BD (g cm-3) Status 2 12.74 0.000 Zone 2 6.24 0.003 status x zone 4 0.45 0.771 SOM (%)§ Status 2 8.43 0.000 Zone 2 2.73 0.070 status x zone 4 1.08 0.373 pH Status 2 6.80 0.002 Zone 2 0.99 0.376 status x zone 4 0.32 0.865 TN (%)§ Status 2 14.30 0.000 Zone 2 1.40 0.250 status x zone 4 0.98 0.424 TC (%)‡ Status 2 12.01 0.000 Zone 2 0.79 0.485 status x zone 4 0.65 0.626 EC (μS cm-1) § Status 2 0.09 0.914 Zone 2 4.75 0.011 status x zone 4 0.66 0.622 ExP (µg g-1) Status 2 0.18 0.835 Zone 2 1.26 0.288 status x zone 4 0.41 0.799 Clay (%)†† Status 2 4.34 0.016 Zone 2 0.46 0.631 status x zone 4 0.21 0.934 Silt (%) Status 2 4.73 0.011 Zone 2 1.24 0.293 status x zone 4 0.33 0.856 Sand (%) Status 2 5.49 0.006 Zone 2 1.09 0.342 status x zone 4 0.15 0.964 † Error degrees of freedom = 96 ‡ These soil properties underwent log transformations before the analysis § The soil properties underwent square-root transformations before the analysis †† Error degrees of freedom = 87 for clay, silt, and sand as particle size was not determined on samples with > 30 % SOM

49

Figure 3.1. Effect of position along the hydrologic gradient and wetland status on bulk density. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 3.2. Effect of position along the hydrologic gradient and wetland status on SOM. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

BC

AC

A

BC

AC A

BB

BC

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


Bulk Den

sity (g/ccm

)

Hydrologic Zone

CWs

RWs

NWs

AC

AA

AC A

A

BC

B

AC

2

2.5

3

3.5

4

4.5

5

5.5

6


Squa

re‐roo

t[ SOM ] (%

)

Hydrologic Zone

CWs

RWs

NWs

50

rank transformed and a Spearman correlation analysis conducted using SAS for Windows

Version 9.1 (SAS Institute, Cary, NC). A significance level of p < 0.05 was used to

assess the significance of the Spearman correlations.

To examine and identify the similarities and/or differences in soil data between

CWs, RWs, and NWs a Principle Components Analysis (PCA) was conducted using the

PC-ORD (McCune and Mefford 1999). PCA is an eigenanalysis ordination technique

that produces orthogonal axes, which capture the highest amount of variation that is

present in the data set (Hair et al. 1995, McCune and Grace 2002). The soil data was

placed into a properties*soil core matrix. The first PCA was run with all soils excluding

the particle size distribution (PSD) variables. The second ordination included both clay

and sand for only the mineral soils (SOM < 30%). Additionally, the sites designated as

former fishponds and flooded agriculture were removed from the PCA.

Finally, a correlation analysis was conducted to identify the relationships among

the eleven soil properties and the 4 most commonly sampled vegetative species: B.

maritima, U. mutica, P. vaginatum, and B. monneri. Due to the non-normally distributed

data, the soil properties and the vegetation cover data were rank transformed and a

Spearman correlation analysis conducted using SAS for Windows Version 9.1 (SAS

Institute, Cary, NC). A significance level of p < 0.05 was used to assess the significance

of the Spearman correlations.

51

Results Descriptive statistics for BD, SOM, pH, EC, TN, TC, ExP, and particle size

distribution are provided in Table 3.1. These data illustrated the wide range of soil

properties that occur in Hawaiian coastal lowland wetlands. A more detailed comparison

of these soil metrics among wetlands of different status and across hydrologic gradients

follows.

In contrast to the vegetation properties (Chapter 2), the effect of status appeared to

be more pronounced than the effect of position along hydrologic gradient. According to

the two-way GLM, most of the soil characteristics differed between NWs, RWs, and

CWs, whereas only three experienced a significant zone effect (EC, BD, and moisture)

(Table 3.2).

Statistical analysis of BD indicated that both wetland status and position along the

hydrologic gradient were significant explanatory factors (Table 3.2). Bulk density

tracked the hydrologic gradient at all three wetland types, and according to the Tukey test

the wet and intermediate zones of NWs had significantly lower BDs than the dry zones of

CWs and RWs, and the intermediate zones of RWs (Figure 3.1).

The analysis of SOM, TC, TN, pH, and particle size distribution (percent-sand,

silt, clay) indicated that wetland status was significant while position on the hydrologic

gradient and their interaction were not (Table 3.2). According to the Tukey test, both

SOM and TN were significantly greater in NWs than CWs and RWs for each zone

(Figures 3.2 and 3.3). Likewise TC was significantly greater in NWs than in RWs,

however is not significantly greater than CWs (Figure 3.4). Soil pH followed an opposite

trend from SOM and TC. Soil pH was significantly lower in NWs and RWs than in

52

Figure 3.3. Effect of position along the hydrologic gradient and wetland status on TN. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 3.4. Effect of position along the hydrologic gradient and wetland status on TC. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

ACA

A

AC ADAD

BC

B

BCD

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1


Squa

re‐roo

t[TN

] (%)

Hydrologic Zone

CWs

RWs

NWs

B

AB

AB

AA A

B

BB

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2


Logrithm

[TC] (%

)

Hydrologic Zone

CWs

RWs

NWs

53

Figure 3.5. Effect of position along the hydrologic gradient and wetland status on soil pH. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 3.6. Effect of position along the hydrologic gradient and wetland status on clay content. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

AC

AA

AB

ABAB

BC BAB

5

5.5

6

6.5

7

7.5

8

8.5


pH

Hydrologic Zone

CWs

RWs

NWs

AB

B

BC

A AC

ABABAC AB

0

5

10

15

20

25

30

35

40

45

50


Clay (%

)

Hydrologic Zone

CWs

RWs

NWs

54

Figure 3.7. Effect of position along the hydrologic gradient and wetland status on silt content. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 3.8. Effect of position along the hydrologic gradient and wetland status on sand content. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

AB

AB

B

AA A

ABAB

B

0

5

10

15

20

25

30

35

40


Silt (%

)

Hydrologic Zone

CWs

RWs

NWs

AB

A

AC

BBC

ABAB

ABAC

0

10

20

30

40

50

60

70


Sand

(%)

Hydrologic Zone

CWs

RWs

NWs

55

Figure 3.9. Effect of position along the hydrologic gradient and wetland status on soil moisture. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

Figure 3.10. Effect of position along the hydrologic gradient and wetland status on soil conductivity. Data presented are means and error bars represent ±1 standard error. Data points with different letters are significantly different at the p < 0.05 level.

ABAB

BCD

A

CA

BC

ACAD

B

0

0.1

0.2

0.3

0.4

0.5

0.6


Moisture (g/ccm

)

Hydrologic Zone

CWs

RWs

NWs

A

ABAB

ABAB

B

AB

AB

B

0

1

2

3

4

5

6

7

8


Squa

re‐roo

t [EC] (mmho

/cm)

Hydrologic Zone

CWs

RWs

NWs

56

Table 3.3. Means and standard errors for mean soil moisture, BD, SOM, TN, TC, EC, ExP, and particle size distribution. Means with different letters were significantly different at the p < 0.05 level according to the Tukey test.

Moloka‘i___ _ Kauai____ Maui____ ___Oahu_____ ___Hawai‘i___

Soil Property Mean SE Mean SE Mean SE Mean SE Mean SE

Moisture (g cm-3) 0.494a 0.05 0.392ab 0.03 0.298b 0.05 0.485a 0.04 0.387ab 0.02

BD† 0.675 0.12 0.597 0.09 0.567 0.20 0.270 0.03 0.620 0.04

SOM (%) 14.85 2.05 16.27 3.45 20.78 7.12 40.56 7.71 16.65 1.30

TN (%) 0.233ab 0.06 0.287b 0.80 0.561ab 0.22 1.204a 0.26 0.293b 0.04

TC (%) 4.441a 0.30 7.55a 1.04 9.88ab 3.57 20.05b 4.81 7.04a 1.09

EC (µS cm-1) 53.44 5.00 7.20 2.33 22.88 9.47 48.8 14.6 28.4 10.3

ExP (μg g-1) 97.0a 27.7 23.94b 4.63 71.1ab 28.0 86.9a 32.5 51.27ab 6.12

pH† 7.55 0.40 6.36 0.59 7.65 0.12 6.11 0.39 7.28 0.17

Clay (%) 43.30 5.03 35.85 6.34 23.46 6.63 26.58 1.50 40.91 4.48

Silt (%) 48.97 3.82 26.27 6.70 23.2 10.0 22.81 7.09 30.60 3.66

Sand (%) 23.4 12.0 37.9 12.2 53.3 14.3 50.61 7.24 28.47 6.88

† ANOVA analysis was not conducted due to heterogeneous variances.

57

CWs, and increased from the wet to dry zones (Figure 3.5). Percent clay, silt, and sand

all showed significant status effects. Soils of RWs had the highest clay and silt contents,

whereas CWs contained the highest sand contents. Natural wetlands and RWs contained

significantly more clay than CWs; RWs contained significantly more silt than CWs and

NWs; and CWs contained significantly more sand than RWs (Figures 3.6-3.8).

Position on the hydrologic gradient explained a significant portion of the variance

in both the moisture and EC data (Table 3.2). The Tukey test indicated that moisture was

significantly greater in the wet and intermediate zones (Figure 3.9). Furthermore, EC

was significantly greater in the wet than in the dry zones (Figure 3.10). Neither wetland

status nor position along hydrologic gradient were significant factors in accounting for

the variability in ExP (Table 3.2). Although not significant, ExP appeared to increase

slightly from wet to dry zones.

In addition to wetland status and hydrologic zone, the effect of island was

assessed. Of the eleven soil properties, the effect of island accounted for a significant

portion of variance in moisture, TN, TC, and ExP (Table 3.3). According to the one-way

ANOVA and Tukey test, soil moisture was significantly lower on Maui than on Moloka‘i

and Oahu. Furthermore, Oahu had a significantly greater TN concentration than both

Hawai‘i and Kauai. TC was also significantly different among islands, such that

Moloka‘i and Kauai were lower than Oahu, and Oahu was greater than Hawai‘i. Lastly,

both Moloka‘i and Oahu had a significantly greater ExP than Kauai according to the

Tukey test.

58

Table 3.4. Spearman rank correlations among the soil properties measured at the 40 coastal lowland wetland sites in Hawai‘i. Only those correlations significant at the p < 0.05 level were reported in the table. (ns = not significant).

BD SOM pH EC TN TC ExP Clay Silt SandMoist -0.23 0.42 -0.31 0.50 0.32 ns ns 0.39 0.41 -0.46BD - -0.75 0.52 -0.40 -0.76 -0.47 -0.21 -0.46 -0.29 0.44SOM - -0.60 0.50 0.91 0.45 0.36 0.60 0.51 -0.64pH - ns -0.57 ns ns -0.32 -0.42 0.43EC - 0.38 0.27 ns ns 0.30 -0.24TN - 0.56 0.47 0.27 ns -0.20TC - 0.19 -0.23 -0.56 0.46ExP - ns ns nsClay - 0.47 -0.86Silt - -0.86Sand -

The Spearman correlation analyses of the eleven soil properties revealed that

moisture had significant negative correlations with BD, pH, and sand content, as well as

significant positive correlations with SOM, EC, TN, and clay and silt content. Bulk

density had significant negative correlations with SOM, EC, TN, TC, ExP, and clay and

silt content, and a significant positive correlation with pH and sand content. Soil organic

matter showed a significant positive correlation to every soil property except pH and sand

content. Soil pH had a significant negative correlation with TN, clay and sand content,

and a positive correlation with sand content. Total nitrogen had significant positive

correlations with EC, TC, Exp, and clay content, and a significant negative correlation

with sand content. Total carbon was negatively correlated with BD, clay and silt content,

and was positively correlated with EC, ExP and sand content. Total carbon had

59

significant positive correlations with TN, EC, and ExP, and significant negative

correlations with clay and silt content (Table 3.4).

Results of the Principle Components Analysis are shown in Figures 3.11 and 3.12.

Each point on the graph represents an individual soil core. Points that are close together

in ordination space represent cores that have similar soil properties, whereas points that

are farther apart represent cores that share few similar soil properties. When PSD was

excluded from the PCA (Figure 3.12), the majority of the cores grouped together at the

high end of axis 1 and axis 2 regardless of wetland status. Additionally, there were more

outliers present when PSD was excluded. However, the inclusion of clay and sand into

the PCA (Figure 3.12) resulted in a greater grouping effect of wetland status. Axis 1, 2,

and 3 accounted for 42.5%, 16%, and 12% of the total variance in the data. Soil

properties with relatively strong loadings on axis 1 were percent sand and clay, pH,

moisture, and SOM. Total carbon had a strong positive loading on axis 2, and ExP had

strong positive loading on axis 3. NWs tended to group together at the low end of axis 1,

indicating greater SOM and clay content. Additionally, CWs tended to group together at

the high end of axis 1 indicating high sand content, pH, and BD. Finally, RWs appeared

to be loading at the high ends of axis 2 (Figure 3.12).

The Spearman correlation analyses of the soil properties and the four most

commonly-observed vegetative species revealed that B. maritima had significant positive

correlations with soil moisture, soil pH, EC, ExP, and silt, as well as significant negative

correlations with TC and sand content. U. mutica experienced a significant positive

60

Moisture

BDSOM

pH

EC

TN TC

ExP

Axis 1 (43.4 %)

Axis

2 (1

6.1

%)

STATUS Natural Restored

X Created

High BD High SOM, TC

Figure 3.11. Principle Components Analysis (PCA) of the soil properties of coastal lowland Hawaiian wetlands. Includes all soil cores, and excludes the particle size distribution variables. Vectors represent the magnitude of correlation with axis 1 and 2. Axes 1 and 2 accounted for 43.4 % and 16.1 % of the total variance respectively.

High ExP

High Moisture

61

Moisture BD

SOMpH

TN

TC

Clay

Sand

Axis 1 (42.5 %)

Status

Axis

2 (1

5.7

%)

Natural Restored

x Created

High BD, Sand, pH

High SOM, Clay

Figure 3.12. Principle components analysis (PCA) of the soil properties of coastal lowland Hawaiian wetlands. Includes sites with mineral soils only (SOM < 30%). Vectors represent the magnitude of correlation with axis 1 and 2. Axes 1 and 2 accounted for 42.5% and 15.7% of the total variance respectively.

Low TC

High TC

62

Table 3.5. Spearman rank correlations among the soil properties and the dominant vegetative species measured at the 40 coastal lowland wetland sites in Hawai‘i. Only those correlations significant at the p < 0.05 level were reported in the table. (ns = not significant).

B. maritima U. mutica P. vaginatum B. monneri Moisture 0.221 ns ns ns BD ns ns -0.242 ns SOM ns ns ns ns pH 0.194 -0.302 ns ns EC 0.379 -0.409 0.274 ns TN ns ns ns ns TC -0.142 -0.171 0.248 0.235 ExP 0.144 ns -0.157 ns Clay ns ns ns ns Silt 0.176 0.171 -0.223 -0.287 Sand -0.182 ns 0.172 0.239

correlation with silt content and significant negative correlations with pH, EC, and TC.

P. vaginatum had significant positive correlations with EC and sand content as well as

significant negative correlations with BD and silt content. Lastly, B. monneri had

significant positive correlations with TC and sand content and a negative correlation with

silt content (Table 3.5).

Discussion A detailed comparison of the soil properties of CWs, RWs and NWs in Hawai‘i

revealed that the effect of wetland status was more pronounced than the effect of position

along the hydrologic gradient. Differences among wetland status were significant for

63

BD, SOM, particle size (% clay, % silt, % sand), pH, TC, and TN, and differences across

the gradient were significant for moisture, BD, and EC. NWs had significantly lower BD

and higher SOM and TN than CWs and RWs. Additionally, NWs had significantly

greater TC concentrations than RWs, significantly lower pH, and higher silt content than

CWs. These results are consistent with previous studies that reported lower BD and pH,

and higher SOM, silt, TN, and TC in NWs than in CWs and RWs (Bishel-Machung et al.

1996, Shaffer and Ernst 1999, Stolt et al. 2000, Craft et al. 2002, Bruland et al. 2003,

Bruland and Richardson 2004, Bruland and Richardson 2005a, Bruland and Richardson

2006).

The lower SOM and higher BDs observed in CWs and RWs compared to NWs

can be explained by several factors. Organic matter accumulation is a function of time,

established vegetation, and hydrology. Organic matter accumulation is favored in NWs

due to the inhibition of decomposition caused by the anaerobic conditions typical of NWs

(Craft et al. 2002, Hogan et al. 2004). In contrast, soils of CWs have not been under the

same environmental conditions as NWs, thus soils of newly created wetlands may retain

soil characteristics typical of terrestrial soils, including lower SOM (Hogan et al. 2004).

Additionally, lower SOM in CWs and RWs is also due to excavation and removal of

topsoil during the development of CWs and RWs (Shaffer and Ernst 1999, Bruland and

Richardson 2005b). Furthermore, the use of heavy machinery in project construction

results in the compaction of soils, resulting in the higher BDs present in CWs and RWs

(Campbell et al. 2002).

64

In studies that measured soil textural characteristics, NWs had higher silt content

than RWs and CWs (Bishel-Machung et al. 1996), while CWs were higher in sand

content (Bruland and Richardson 2005b). Most wetland creation projects involve the

removal of fine-textured surface soils during excavation, resulting in the textural

differences that are typical of mitigation projects. In this study, RWs had significantly

greater clay and silt contents than CWs. NWs however, only differed from CWs with

respect to clay content, and had significantly lower silt content than RWs. The higher

amounts of clay and silt content in RWs and the lack of differences in sand content

between NWs and CWs, may be a function of location or parent material. The location

of a site relative to a river may result in differing soil textures. In this study RWs may

receive a higher deposition of silts and clays from neighboring stream systems, or the

NWs sampled in this study may be located closer to the coast, resulting in higher sand

contents observed in NWs than in RWs.

In a pooled study of 20 reference and 44 constructed wetlands in Pennsylvania,

Bishel-Machung et al. (1996) found that soil pH in reference wetlands tended to be lower

than that of restored or created wetlands. This study found similar results, such that the

pH of NWs and RWs were significantly lower than the soils of CWs. The differences

between NWs, RWs, and CWs found through the literature and in this study are likely the

consequence of differences in hydrology, further resulting in differences in SOM levels

in NWs, RWs, and CWs. Anoxic conditions caused by flooding result in the buildup of

carbonic acid when the decomposition of organic matter is inhibited. These changes lead

65

to the domination of hydrogen ions and thus lower pH values (Mitsch and Gosselink

1993).

Both TC and TN are known to co-vary with SOM content in wetland soils

(Bishel-Machung et al. 1996, Stolt et al. 2000). In this study, TC levels were

significantly higher in NWs than in RWs, and TN levels were significantly higher in

NWs than in CWs and RWs. Similar results were found for TC and TN by Stolt et al.

(2000) in a study of constructed and reference wetlands in Virginia. They argued that the

hydroperiod of a wetland had a significant effect on nutrient transformations and the

availability of the nutrients to vegetation. The nearly continuous saturation of the soil

surface of reference wetlands show limited decomposition of organic matter, and thus

have elevated carbon and nitrogen levels. Low soil TC in mitigation areas would indicate

that the degree of saturation is not sufficient enough to retard the rate of organic matter

accumulation. The low levels of TC and TN imply that organic matter accumulation is

not occurring in restored and created wetlands (Langis et al. 1991). The differences in

TC and TN can also be attributed to the observed textural differences in NWs, RWs and

CWs. Soils comprised primarily of sand particles such as those found in the CWs,

generally have lower nutrient retention capacities than soils comprised of finer silts and

clays (Bruland and Richardson 2005b).

Given the significant differences in clay content and SOM between NWs, RWs,

and CWs, it would be expected that ExP would also differ (Hogan and Walbridge 2007).

The similarity in ExP in NWs, RWs, and CWs may indicate that organic matter is not an

important source of phosphorus in these Hawaiian wetlands. The lack of a significant

66

difference may also indicate that phosphorus is the limiting nutrient in all wetlands

regardless of status and is taken up fairly uniformly by plants across all sites.

According to the Spearman rank correlations, the majority of the soil properties

were significantly correlated. Soil organic matter had significant associations with all

soil properties samples in this study excluding BD and pH. This highlighted the

importance of this parameter as an indicator of soil development in coastal wetlands. A

more detailed discussion of the relationships between measured soil properties is

provided in the discussion of the univariate findings above. The results of this study are

similar to those found in a study of 40 wetlands in Pennsylvania (Bishel-Machung et al.

1996) and 11 wetlands in Virginia (Bruland and Richardson 2004).

Using PCA, differences in soil properties were revealed that supported the results

obtained using univariate procedures. In the PCA, the majority of NWs were positioned

in an area of ordination space correlated with a high TN, SOM, and clay content, and low

bulk density. RWs were positioned in a space correlated with low TC and TN, and CWs

were correlated with high sand content, bulk density, pH, and low SOM (Figure 3.12).

The separation of NWs and CWs on axis 1 is indicative of larger differences in soil

properties between NWs and CWs. The cluster of RWs located in the center of axis 1

and slightly skewed towards RWs, suggests that RWs share soil properties that are more

similar to NWs, however they may still be in a transitional phase to fully functioning

NWs. Axis 1 has a positive loading by sand and clay, suggesting that the structure of

axis 1 of the PCA reflects a distribution of sites along a texture gradient. The positive

loading of TC and TN on axis 2 suggests that axis 2 represents a nutrient gradient.

67

The soil versus vegetation Spearman rank correlations revealed that the 4 most

commonly sampled vegetative species have preferences for sites with certain soil

characteristics. Specifically, B. maritima does well in sites that have higher soil salinity

and mineral silty soil. U. mutica prefers sites with low soil salinity, pH, and TC. P.

vaginatum prefers sites with higher soil salinities and TC. Lastly, the native, B. monneri,

appears to do well in sites with soils high in TC. Due to the species-specific responses to

the soil properties the management of vegetation, especially those that are invasive, will

be difficult as individual species respond differently to the soil properties. The results for

B. monneri also suggest that this species might respond positively to restoration practices

such as organic amendments.

68

Chapter 4. Conclusions

The intent of this research was to gather baseline data and evaluate the effects of

wetland status and position along the hydrologic gradient on coastal lowland wetlands in

Hawai‘i. The research hypotheses were as follows: (2-1a) vegetative community

composition is different in CW/RWs than in NWs; (2-2a) there are differences in

vegetative community composition across the hydrologic gradient; (3-1a) soil properties

are different in CW/RWs than in NWs; and (3-2a) there are differences in soil properties

across the hydrologic gradient. Based on the results of this study, these research

hypotheses were accepted as a number of the vegetative characteristics and soil properties

were different among CWs, RWs and NWs and a number of the vegetative and soil

properties differed across hydrologic gradients.

Specifically, vegetation was affected by both wetland status and position along

the hydrologic gradient (Table 2.1). The effect of hydrology was more pronounced than

the effect of wetland status, as position along the hydrologic gradient accounted for a

greater portion of variance in all variables with the exception of total wetland vegetation.

Species richness, cover of exotic species, and total vegetative cover all followed the same

trend, such that they were greatest in the dry zone, followed by the intermediate, and then

the wet zone. These findings were explained by the major stresses that persist in the

wetland environment, i.e. anoxia and porewater salinity. Species richness and total cover

were also greatest in CWs, followed by NWs, and RWs. Although CWs had the greatest

species richness, it is interesting to note that collectively, NWs had the greatest number of

69

species observed with 67, of which 20 were unique to NWs. Forty-two species were

observed in RWs and 30 in CWs.

Another observation gathered from the site visits in March 2007 was the presence

of an overwhelming number of exotic plant species. In fact, 84% of all species observed

were exotic. Additionally, the lack of significant differences in exotic cover among

wetland status further indicated that the coastal lowland wetlands in Hawai‘i are heavily

impacted by exotic species. Possible ways to address the invasion of coastal lowland

wetlands with exotic species include seeding newly restored or created wetland sites with

native plant species, attempting to control invasive vegetation with mechanical means or

herbicides, and transplanting native vegetation from wetland sites slated for impacts to

restored or created sites.

Manual seeding can jump-start the growth and production of native vegetation in

a disturbed environment that normally favors exotic species (Reinartz and Warne 1993).

It is important that manual seeding be cost effective as budgetary constraints are often

placed on wetland restoration and creation projects. Reinartz and Warne (1993)

employed a low-cost method which consisted of scattering seeds of native species. In

their study in Southeastern Wisconsin, this technique increased species diversity,

richness, and cover of native wetland species within two years compared to unseeded

sites. Additionally, a post-restoration or creation exotic and invasive species control

program may result in greater cover of desirable native species as it has been observed at

the Marine Corps Base Hawai‘i wetland site, Klipper Pond, where managers and

volunteers are regularly involved in invasive species removal activities.

70

The evaluation of the soil properties of NWs RWs and CWs, in Hawai‘i revealed

that the effect of wetland status was more pronounced than the effect of position along

the hydrologic gradient (Table 3.2). Most notable were the differences in BD, SOM, pH,

sand content, and TN. Natural wetlands were characterized by high SOM, TN, clay

content, and low bulk density and pH. The RWs sites were characterized by high bulk

density, silt and clay content, and low SOM, TN, TC. Created wetlands were

characterized by high bulk density, and sand content, and low SOM and TN. The

differences in the soil properties indicated that the CWs and RWs may not achieve the

same ecological functions as NWs. Low SOM in CWs and RWs will limit denitrification

nitrogen fixation, and secondary production (Craft et al. 1999, Craft 2001) Some plants

may be growth limited in the CWs and RWs because of the low levels of TN and TC

(Stolt et al. 2000). The CWs may also be less effective in retaining nutrients and holding

essential plant elements such as Ca, Mg, and K due the limited cation exchange capacity

as a result of the higher sand contents (Poach and Faulkner 1998). The differences

observed in these soil properties were mainly attributed to construction practices and lack

of organic matter accumulation in CWs and RWs since site construction.

Based on these findings there are several steps that can be taken for mitigation to

be more effective in replacing wetland structure and function as related to soils. A first

step is to consider soils in the project construction and design. Typically mitigation plans

tend to ignore soils all together and focus on vegetation development. This is of great

concern because soils are the physical foundation for every wetland ecosystem (Stolt et

al. 2000). Secondly, when restoration and creation sites are designed and constructed,

71

attempts should be made to reduce soil compaction by ripping both the topsoil and

subsoil layers prior to planting. Additionally, soil conditions of RWs and CWs can be

improved through amelioration of the dredged material or soil amendments.

Amendments such as compost, mulch, or other organic material increase the total amount

of moisture, carbon and nitrogen, and decreases bulk density, thus improving the overall

condition of the soil. Bruland and Richardson (2004) found that topsoil and organic

amendments were an effective strategy to increase moisture, water holding capacity, and

phosphorus sorption in Virginia created wetlands. The application of organic

amendments may also help to prevent B. maritima from dominating a wetland site as

there was a negative correlation between B. maritima cover and TC (Table 3.5). A third

step is to reestablish microtopography in RWs and CWs. Recreation of microtopography

may increase restoration success by creating both anaerobic and aerobic zones that are

needed for nitrogen retention and transformation. Some authors have suggested that

recreating surface microtopography during wetland restoration or creation may be an

effective way to accelerate the development of wetland functions (Contelmo and

Ehrenfeld 1999, Bruland and Richardson 2005a), as microtopography creates a mosaic of

soil patches with substrates that differ structurally, hydrologically, and chemically.

The univariate analysis of SOM, bulk density, TN, pH, and sand content showed a

significant separation between NWs and the mitigation wetland sites of this study (Table

3.2, Figures 3.2-3, 3.5, and 3.8), as they have in other wetland soil comparisons (Bishel-

Machung et al. 1996, Shaffer and Ernst 1999, Campbell et al. 2002, Bruland and

Richardson 2006). Each of these variables showed greater similarities between NWs and

72

RWs than NWs and CWs. Given the greater similarities between NWs and RWs soil

properties it can be inferred that the time for RWs to develop wetland functions

characteristic of NWs will be less than that of CWs. Thus, given the option between

restoration and creation, restoration should be the preferred mitigation option in Hawai’i.

To further minimize the time of lost wetland functions, project construction should occur

before the permitted impact of the natural wetland site. Construction of mitigation

projects typically begins after the impact on the natural system has occurred. Soil

properties such as SOM accumulation and nutrient take decades to reach the levels of

NWs (Craft et al. 2002). The time-lag until lost functions are realized should be

considered and compensated for during the permit process. Monitoring of the

development of soil properties of CWs and RWs should be conducted to provide

desperately need quantitative data about the time requirements to develop soils

characteristic of their natural counterparts.

The fishpond sites are a unique class of created wetlands found in Hawai‘i.

Although these sites were removed from the statistical analyses due to their differences,

the fishponds are important to Hawai‘i due to their cultural significance. Table 4.1

presents the descriptive statistics of the soil and vegetation properties for the fishpond

sites. Like the soil properties of the CWs, RWs, and NWs, the fishpond soil properties

were highly variable. In comparison to CWs, RWs, and NWs, the fishponds had greater

moisture, SOM, EC, TN, TC, ExP, sand content, exotic cover, total wetland vegetation,

and total vegetation, as well as lower BD, pH, and clay and silt content. Differences in

the fishpond site soil properties may be a result of the age of the sites, as they were

73

Table 4.1. Fishpond site descriptive statistics for species richness, total cover, wetland vegetation cover, exotic cover, bulk density (BD), soil organic matter (SOM), pH, electrical conductivity (EC), total nitrogen (TN), total carbon (TC), moisture, extractable phosphorus (ExP), clay, silt, and sand.

SOM (%) pH

EC (µS•cm-1)

TN (%)

TC (%)

ExP (µg•g-1)

Clay (%)

Silt (%)

Sand (%)

Mean 45.55 5.91 61.55 1.57 23.47 86.61 20.35 19.76 59.90Median 39.23 5.80 24.98 1.62 21.57 76.00 21.06 18.46 60.89Standard Error 4.91 0.24 14.55 0.16 2.69 10.44 3.87 6.06 8.87Range 67.86 4.20 199.00 2.64 39.91 177.00 28.73 50.40 79.13Minimum 12.20 3.70 1.00 0.32 4.18 28.00 2.24 0.00 18.63Maximum 80.07 7.90 200.00 2.96 44.09 205.00 30.97 50.40 97.76Count 23 23 23 23 23 23 7† 7 7

Species

Richness Total

Cover (%) Wetland Veg.

Cover (%) Exotic

Cover (%) Moisture (g•cm-3) BD (g•cm-3)

Mean 2.71 85.25 82.63 74.17 0.47 0.23Median 2.0 90.0 90.0 84.5 0.52 0.14Standard Error 0.41 3.75 4.96 5.83 0.04 0.04Range 6.0 69.0 100.0 100.0 0.84 0.64Minimum 1.0 31.0 0.0 0.0 0.03 0.03Maximum 7.0 100.0 100.0 100.0 0.86 0.67Count 24 24 24 24 23 23

† The count is 7 for clay, silt, and sand as particle size was not determined on samples with > 30 % SOM.

74

created hundreds of years ago. Additionally, the soil properties may also reflect the

preferential location of the fishponds on the shore line and near river mouths. Further

research into the physical, chemical, and ecological processes of Hawaiian fishpond

wetlands may reveal that these wetlands hold values beyond cultural significance as well

as may provide insight into wetland creation in Hawai‘i.

Integrated Rankings of Semi-Natural, Restored, and Created Wetland Sites in Hawai‘i

To identify the quality of CW, RW, and NW sites in Hawai‘i, each site was

ranked based on percent native cover, SOM content, and an assessment based on multiple

site visits. Soil organic matter was measured at all sample sites and is correlated with a

number of other soil properties, suggesting that SOM is a key component that relates to

the functions of other soil characteristics. Created wetlands, RWs, and NWs were also

ranked based on my site assessment, which took into consideration disturbance, wetland

size, and heterogeneity. Percent native cover, site mean SOM, and site assessment ranks

for CWs, RWs, and NWs are presented in Table 4.1. Each parameter was ranked and

assigned to a percentile using Microsoft Excel 2007. Wetland sites were ranked together

regardless of status. A rank of 1 (0%) was given to wetlands that scored the worst or

lowest value for a particular metric, whereas 40 (100%) was given to wetlands that

scored the best or highest value relative to the other evaluated wetlands. Wetlands with

similar means were averaged and ranked the same number. Three separate ranking

schemes were conducted: (1) native cover and SOM were equally weighted; (2) native

cover, SOM, and the site assessment were weighted at 50%, 40%, and 10% respectively;

75

Table 4.2. Actual means of soil organic matter (SOM %) and native vegetative cover (%), as well as site assessment rank for natural, restored, and created coastal lowland wetlands in Hawai‘i. Island location shown in parenthesis (Ma = Maui, Mo = Moloka‘i, Ka = Kauai, Hi = Hawai‘i, Oa = Oahu).

Natural Wetlands

Site SOM (%)

Native (%) Assessment

Kanaha Pond (Ma) 44.51 18.17 12 Waipio (Ha) 60.27 19.00 26 Kilauea (Ka) 20.13 2.50 19 Lawai Kai (Ka) 17.28 15.33 30 Kauaihau Riparian (Ka) 27.29 14.50 1 Honoapu (Hi) 30.12 1.83 27 Kamilo Pt. 6 (Hi) 29.94 29.50 28 Kamilo Pt. 7 (Hi) 49.77 85.33 29 Punamano (Oa) 14.46 12.50 24 Coconut Grove (Oa) 19.43 27.00 21 Kealia (Ma) 21.84 10.00 8 Paukukalo (Mo) 4.31 2.17 9 Nu‘u (Ma) 25.11 47.83 31 Kawai Nui (Oa) 19.14 0.00 23 Waimea (Oa) 15.91 0.00 25 Paiko Lagoon (Oa) 9.90 0.00 17 Bellows (Oa) 21.49 0.00 4 Restored Wetlands

Site SOM (%)


Koheo (Mo) 10.59 0.00 5 Ohiapilo (Mo) 12.10 0.00 11 Hanalei (Ka) 14.63 0.00 19 Huleia (Ka) 28.99 21.67 20 Kauaihau Coastal (Ka) 16.65 0.50 16 Ki‘i (Oa) 18.20 9.83 18 Waihe‘e (Ma) 8.11 4.00 22 Hamakua (Oa) 17.80 11.83 18 Waiawa (Oa) 17.93 0.00 3 Pouhala (Oa) 12.12 0.00 3 Ka‘elepulu (Oa) 15.83 5.00 14

76

Table 4.2. Continued. Created Wetlands

Site SOM (%)


Kakahaeia (Mo) 18.19 0.00 7 Mo. Sea Farms (Mo) 18.52 0.00 5 Kawaiele (Ka) 2.52 38.00 15 Nukolii (Ka) 2.97 48.33 13 Klipper Pond (Oa) 9.29 32.83 10 Perc. Ditch (Oa) 13.50 66.33 6 Salvage Yard (Oa) 28.06 2.00 2

Table 4.3. Natural, restored, and created wetland site ranks. Rank 1 weighs the native cover and SOM equally; Rank 2 gives a 50% weight to native cover, 40% weight to SOM, and 10% weight to site assessment; and Rank 3 equally weights native cover, SOM, and site assessment. Data are sorted by Rank 2. Island names are in parentheses.

Natural Wetlands Site Rank 1 Rank 2 Rank 3 Kamilo Pt. 7 (Hi) 98.50 98.21 97.03 Nu‘u (Ma) 83.75 86.11 89.17 Kamilo Pt. 6 (Hi) 85.25 85.54 87.20 Waipio (Hi) 86.75 85.27 86.23 Kanaha (Ma) 82.30 76.71 67.60 Coconut Grove (Oa) 72.05 72.63 71.53 Kauaihau Riparian (Ka) 72.05 64.11 48.03 Honoapu (Hi) 63.15 62.86 71.50 Lawai Kai (Ka) 55.85 61.14 69.57 Kealia (Ma) 64.65 59.94 51.90 Kilauea (Ka) 55.85 55.26 57.80 Punamano (Oa) 45.55 50.55 56.83 Kawai Nui (Oa) 30.85 32.32 46.03 Bellows (Oa) 35.25 29.37 27.40 Paukukalo (Ma) 23.45 25.81 25.43 Waimea (Oa) 19.10 23.51 40.17 Paiko Lagoon (Oa) 7.35 11.17 22.53

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Table 4.3. Continued. Restored Wetlands Site Rank 1 Rank 2 Rank 3 Huleia (Ka) 80.80 79.04 76.40 Kii (Oa) 54.35 54.35 54.83 Hamakua (Oa) 52.90 53.78 53.87 Ka‘elepulu (Oa) 42.60 43.49 43.10 Kauaihau Coastal (Ka) 36.70 37.59 41.13 Waihe‘e (Ma) 27.90 34.37 43.10 Waiawa (Oa) 25.00 20.58 18.60 Hanalei (Ka) 16.15 19.09 31.33 Ohiapilo (Mo) 10.25 11.72 18.57 Pouhala (Oa) 11.75 9.98 9.77 Koheo (Mo) 8.80 8.51 10.77 Created Wetlands Site Rank 1 Rank 2 Rank 3 Perc. Ditch (Oa) 61.70 61.11 47.97 Nukolii (Ka) 48.50 52.32 46.03 Salvage Yard (Oa) 60.25 52.31 41.13 Klipper Pond (Oa) 48.45 50.51 43.07 Kawaiele (Ka) 44.10 48.80 45.07 Mo. Sea Farms (Mo) 29.40 24.99 24.50 Kakahaeia (Mo) 26.45 23.51 25.47

78

and (3) native cover, SOM, and site assessment were equally weighted. The final

wetland site ranks are provided in Table 4.2.

The wetland rakings in Rank 1 provide an assessment of the quality of individual

coastal lowland wetland sites in performing ecological functions relative to one another.

Ranks 2 and 3 incorporate the wetland values I assigned based on my best professional

judgment. Wetland sites located at the top of the lists (based on Rank 2) represent sites

that have high native vegetative cover and SOM, and thus represent high quality sites.

Wetland sites at the bottom of the tables contained little to no native cover and low SOM

(Table 4.3). Both NWs and RWs have a wide range of values for all three ranking

schemes, whereas CWs had a smaller range in values. Based on Rank 2, only 4 NWs and

1 RWs sites have a greater wetland scoring rank than CWs. While NWs and RWs have

the highest site values, they also have the lowest. It was interesting to note that the

lowest site rankings in CWs were more “successful” than the six least successful NWs

and RWs.

Additionally, the highest quality NWs are located on the islands of Hawai‘i and

Maui. Although Oahu had the lowest quality NWs, Oahu and Kauai had the highest

quality RW and CW sites. The evaluation of management/ownership in relation to the

wetland ranks identified that the highest ranking NWs sites were under State of Hawai‘i

and private management, whereas the highest ranking RWs and CWs were federally

managed. The results of this ranking scheme have identified the highest quality semi-

natural wetlands, as well as the highest and lowest quality restored, and created coastal

lowland wetlands based on native cover and SOM. These top listed sites from each

79

category could become long-term reference sites for future mitigation of coastal lowland

wetlands in Hawai‘i. This ranking system could also be used to prioritize sites in terms

of future management needs and invasive species removal efforts. Finally, based on the

data and research I have identified performance standards with regards to SOM and total

vegetative cover for CWs and RWs. A reasonable level of SOM is 20% as this is the

mean value of the NW sites sampled in this study. Based on the need for open space for

waterbird habitat I recommend that CWs and RWs have 60% vegetative cover with the

attempts to maximize the cover of native vegetation.

Although vegetation and soil properties are the most commonly sampled metrics

and have been linked to ecosystem functions, the inclusion of additional metrics, such as

water quality, macroinvetebrate community composition, and wildlife populations, into

the wetland rankings would provide a more complete picture of the overall condition of

coastal lowland wetlands in Hawai‘i. The inclusion of these metrics will allow for

greater understanding of these wetlands as well as may help to establish links between the

vegetation, soil, and hydrology in the functioning of these wetland ecosystems.

Summary Four key conclusions of this work are as follows: (1) species richness, total exotic

cover, and total vegetative cover were driven by position along hydrologic gradient, to a

greater degree than wetland status. (2) A broad spectrum of wetland plant species were

established across the 40 wetlands sampled. Eighty-four percent of the species observed

were exotic, indicating that coastal lowland wetlands in Hawai‘i are heavily impacted by

80

exotic species regardless of wetland status. (3) Vegetation composition of coastal

lowland wetlands in Hawai‘i appear to be driven by salinity to a greater degree than

wetland status, position along hydrologic gradient, and island. (4) Semi-natural wetlands

are characterized by high cover of U. mutica, SOM, TN, clay content, and low bulk

density and pH. The RWs sites are characterized by high BD and silt and clay content,

low SOM, TN, TC; and CWs are characterized by high cover of B. maritima, bulk

density, and sand content, and low SOM and TN.

These results suggest that there are considerable differences in the vegetative and

soil properties in this study of 40 semi-natural, restored, and created coastal lowland

wetlands in Hawai‘i as well as along hydrologic gradients within these sites. This

statement is not meant to imply that RWs and CWs lack value entirely, as they likely

provide beneficial environmental services. For example they may store and purify storm

water, process nutrients and toxins, or provide habitat for wildlife, however not to the

same degree as NWs.

More research is needed to examine the interactions between soils, hydrology,

vegetation, and wildlife to provide a comprehensive picture of the status of coastal

lowland wetlands in Hawai‘i. The participation and cooperation between academia and

federal and state organizations are encouraged, as it will result in the acquisition of more

baseline and detailed data. A better understanding of these systems will result in

improved design techniques, construction methods, adaptive management activities, and

long-term sustainability of these vital resources.

81

Appendix A. Species List, indicator status, and origin. (Indicator Status: OBL = Obligate, FACW = Facultative Wet, FAC = Facultative, FACU = Facultative Upland, UPL = Upland; Origin: I = Introduced, N = Native). Species Indicator Status OriginAgeratum conyziodes FAC I Alternanthera sessilis FAC I Amaranthus spinus FACU I Amaranthus virdis FACU I Asystasia gangentica FACU I Atriplex semibaccata FAC I Bacopa monnieri OBL N Batis maritima OBL I Bidens alba FAC I Bolboschoenus maritimus OBL N Canavalia cathartica FACU I Casurina equisetifolia FACU I Cenchrus ciliaris NI I Ceratiohyllum demersum OBL I Chamaesyce hirta FACU I Chamaesyce hypericifolia FACU I Chloris barbata FAC I Chloris radiata FAC I Coccinia grandis NI I Coix lachryma-jobi FACW I Commelina diffusa FACW I Coronopus didymus NI I Cuphea carthangensis FAC I Cyclosorus interruptus FACW N Cylosorus interruptus FACW N Cynadon dactylon FAC I Cyperus compressus FACW I Cyperus halpan FACW I Cyperus involucratus FACW I Cyperus javanicus FACW N Cyperus lavigatus OBL N Cyperus polystachyos FACW N Cyprus gracilis FAC I Desmanthus virgatus FACU I Dicliptera chinensis NI I Digitaria insularis FACU I Distichlis spicata FACW I Echinochola crus-galli FACW I Eclipta prostrata FACW I

82

Species Indicator Status OriginEgeria densa OBL I Eleocharis spp OBL I Eleusine indica FACU I Emilia fosbergii NI I Heteromeles arbutifolia NI I Hibiscus tiliaceus FAC I Hyptis pectinata UPL I Ipomoea alba FAC I Ipomoea indica FAC N Ipomoea pes-caprae FAC N Ipomoea triloba NI I Killinga brevifolia FAC I Lemmna aequinocital OBL I Lipochaeta succlenta FAC N Lucaena leucocephals NI I Ludwigi octovalis OBL I Macroptilium atropurpureum FACU I Melilotus indica UPL I Mimosa pudica FAC I Myoporum sandwicense NI N Nephrolepis spp. FAC N Nymphaea capensis OBL I Paederia foetida UPL I Panicum maximum FAC I Paspalum conjugatum FACW I Paspalum vaginatum FACW I Passiflora foetida FACU I Pennisetum setaceum NI I Persicaria indica OBL I Philadelphus spp. NI I Pluchea carolensis FAC I Pluchea indica FAC I Polygala paniculata FACU I Polypogon spp. FACW I Prosopis pallida FACU I Rhizophora mangle OBL I Ricinus communis FACU I Rivina humilis NI I Sacciolepis indica FAC I Sagittaria latifolia OBL I Scaevola sericea FACU N Schinus terebinthifolius FACU I Schoenoplectus spp. OBL I

83

Species Indicator Status OriginSesuvim portulacastrum FAC N Setaria parviflora FAC I Sida fallax NI N Solanum americanum FACU I Solanum seaforthianum NI I Solanum torvum NIN I Sonchus oleraceus FACU I Sphagneticola trilobata FACW I Thespesia populnea FAC I Thunbergia fragrans NI I Tillandsia spp. NI I Trifolium spp. NI I Typha spp. OBL I Urochola mutica FACW I Verbena litoralis FACU I Vigna marina FAC N Vitex rotundifolia NI N Waltheria indica NI N Xanthium strumariuim FACU I Youngia joponica FACU I Unknown Chenopodiaceae 1 Unknown Convolvulaceae 1 Unknown Convolvulaceae 2 Unknown Grass 1 Unknown Grass 10 Unknown Grass 2 Unknown Grass 3 Unknown Grass 4 Unknown Grass 5 Unknown Grass 6 Unknown Grass 7 Unknown Grass 8 Unknown Grass 9

84

Appendix B.

Site Zone

B. m

ariti

ma

P. in

dica

P.ca

role

nsis

U. m

utic

a

P. m

axim

um

Scho

enop

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us sp

p.

B. m

ariti

mus

C. d

iffus

a

Eleo

char

is sp

p.

D. s

pica

ta

L. o

ctov

alis

T.po

puln

ea

R. m

angl

e

L. le

ucoc

epha

ls

S. p

ortu

laca

stru

m

P. p

allid

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B. m

onni

eri

C. j

avan

icus

C. p

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tach

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C.

lavi

gatu

s

C.

invo

lucr

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C. h

alpa

n

C. c

ompr

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s

E. c

rus-

galli

Koheo W 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koheo I 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koheo D 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koheo W 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koheo I 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koheo D 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kakahaiea W 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kakahaiea I 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kakahaiea D 75 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kakahaiea W 90 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kakahaiea I 70 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kakahaiea D 47 5 0 0 0 48 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mo. SF W 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mo. SF I 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mo. SF D 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mo. SF W2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mo. SF I2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mo. SF D2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Species composition and percent cover per sample quadrat.

85

Ualapue W1 0 0 0 0 0 15 0 0 20 5 0 1 11 0 0 0 0 0 0 0 0 0 0 0 Ualapue I1 0 75 0 9 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ualapue D1 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ualapue W2 0 70 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Ualapue I2 0 0 0 60 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ualapue D2 0 0 0 95 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 Ohiapilo W1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ohiapilo I1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ohiapilo D1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ohiapilo W2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ohiapilo I2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ohiapilo D2 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kilauea W1 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kilauea I1 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kilauea D1 0 0 0 98 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kilauea W2 0 0 0 75 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kilauea I2 0 0 0 97 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kilauea D2 0 0 0 0 99 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hanalei W1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 Hanalei I1 0 0 0 55 0 0 0 1 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 Hanalei D1 0 0 0 95 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hanalei W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hanalei I2 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hanalei D2 0 0 0 4 0 0 0 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 Lawai Kai W1 0 0 0 0 0 70 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Lawai Kai I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 91 0 0 0 0 0 0 Lawai Kai D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Lawai Kai W2 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Lawai Kai I2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Lawai Kai D2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Huleia W1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 Huleia I1 0 0 0 5 0 0 0 10 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 Huleia D1 0 0 0 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Huleia W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

86

Huleia I2 0 0 0 0 0 0 0 35 0 0 4 0 0 0 0 0 35 0 0 0 0 0 0 0 Huleia D2 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawaiele W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 Kawaiele I1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 40 0 0 0 0 0 0 0 0 0 Kawaiele D1 0 10 0 0 0 0 0 0 0 0 0 0 0 10 5 0 0 0 0 0 0 0 0 0 Kawaiele W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 48 0 35 0 0 0 0 0 0 0 Kawaiele I2 0 20 0 0 0 0 0 0 0 0 0 0 0 0 35 0 40 0 0 0 0 0 0 0 Kawaiele D2 0 1 1 0 0 0 0 0 0 0 0 0 0 10 6 0 0 0 0 0 0 0 0 0 Kawai.Coastal W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai. Coastal I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 Kawai. Coastal D1 0 25 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai. Coastal W2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Kawai. Coastal I2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai. Coastal D2 0 35 0 60 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 Kawai. Riparian W1 0 0 0 0 0 85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai. Riparian I1 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 Kawai. Riparian D1 0 0 0 33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 Kawai. Riparian W2 0 0 0 28 0 5 0 0 0 0 28 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai. Riparian I2 0 0 0 23 0 0 0 0 0 0 10 0 0 0 0 0 0 0 35 0 0 0 0 0 Kawai. Riparian D2 0 0 0 42 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 Nukolii W1 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nukolii I1 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 84 0 0 0 0 0 0 0 Nukolii D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 38 0 0 0 0 0 0 0 Nukolii W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 40 0 0 0 0 0 0 0 Nukolii I2 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 Nukolii D2 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 70 0 0 0 0 0 0 0 Kealia W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kealia I1 97 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kealia D1 65 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kealia W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kealia I2 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kealia D2 74 20 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Keanai W1 0 0 0 0 0 0 0 12 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 35 Keanai I1 0 0 0 27 0 0 0 10 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 1

87

Keanai D1 0 0 0 92 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Keanai W2 0 0 0 10 0 0 0 9 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 25 Keanai I2 0 0 0 20 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 Keanai D2 0 0 0 60 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waihe‘e W1 0 0 50 0 0 0 23 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 Waihe‘e I1 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waihe‘e D1 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waihe‘e W2 0 0 0 87 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waihe‘e I2 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waihe‘e D2 0 0 0 0 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paukukalo W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paukukalo I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paukukalo D1 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paukukalo W2 0 0 0 88 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paukukalo I2 0 0 0 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paukukalo D2 0 0 0 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nu‘u W1 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nu‘u I1 0 0 0 0 0 0 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nu‘u D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0 Nu‘u W2 0 0 0 0 0 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nu‘u I2 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nu‘u D2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 67 0 0 0 0 0 0 0 0 0 Kanaha W1 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 Kanaha I1 0 3 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 Kanaha D1 0 69 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kanaha W2 0 0 0 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 16 0 0 0 0 Kanaha I2 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 Kanaha D2 0 84 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 Waipio W1 0 0 0 7 0 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waipio I1 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 80 0 0 0 Waipio D1 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waipio W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waipio I2 0 0 0 44 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waipio D2 0 0 0 0 0 0 0 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

88

Mohouli W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 Mohouli I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 Mohouli D1 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 Mohouli W2 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 Mohouli I2 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 3 0 23 0 0 7 0 0 Mohouli D2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Aimakapa W1 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Aimakapa I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Aimakapa D1 80 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 Aimakapa W2 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Aimakapa I2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Aimakapa D2 0 0 0 0 0 0 0 0 0 0 0 9 0 0 2 0 0 0 0 0 0 0 0 0 Koloko W1 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koloko I1 85 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 Koloko D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koloko W2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koloko I2 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Koloko D2 75 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 Honuapo W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Honuapo I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Honuapo D1 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Honuapo W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Honuapo I2 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Honuapo D2 0 0 0 97 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kamilo Pt 6 W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kamilo Pt 6 I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 37 0 0 0 0 0 0 0 Kamilo Pt 6 D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 Kamilo Pt 6 W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kamilo Pt 6 I2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kamilo Pt 6 D2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kamilo Pt 7 W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 80 0 0 15 0 0 0 0 Kamilo Pt 7 I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 Kamilo Pt 7 D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 Kamilo Pt 7 W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 25 0 0 0 0

89

Kamilo Pt 7 I2 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 40 0 0 40 0 0 0 0 Kamilo Pt 7 D2 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 12 0 0 0 0 0 0 0 Kii W1 15 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 Kii I1 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kii D1 60 17 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 Kii W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kii I2 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kii D2 93 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano W1 0 0 0 0 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano I1 0 0 0 0 0 40 0 0 10 0 0 0 0 0 0 0 10 0 20 0 0 0 0 0 Punamano D1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 Punamano W2 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano I2 0 25 0 0 0 5 0 0 0 0 0 0 0 0 0 0 25 5 0 0 0 0 1 0 Punamano D2 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Coconut Grove W1 3 0 0 0 0 17 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 Coconut Grove I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 70 0 0 0 0 0 0 Coconut Grove D1 0 3 0 0 0 0 0 0 0 0 0 0 0 66 0 0 0 0 0 0 0 0 0 0 Coconut Grove W2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 Coconut Grove I2 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 Coconut Grove D2 0 5 0 0 0 0 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 0 0 0 Kawai Nui W1 0 0 0 62 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai Nui I1 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai Nui D1 0 0 0 15 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai Nui W2 0 0 0 85 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai Nui I2 0 0 0 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kawai Nui D2 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua W1 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua I1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 Hamakua D1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 Hamakua W2 68 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua I2 0 0 0 0 0 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua D2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa W1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa I1 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

90

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119

Kii 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kii 0 0 0 0 0 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Kii 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano 0 0 0 0 0 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 Punamano 0 0 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano 0 0 10 0 0 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Punamano 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Coconut Grove 0 0 0 0 0 42 3 0 0 0 0 0 0 0 0 0 0 0 0 0 Coconut Grove 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Coconut Grove 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Coconut Grove 0 0 0 0 0 55 10 0 0 0 0 0 0 0 0 0 0 0 0 0 Coconut Grove 0 0 0 0 0 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Coconut Grove 0 0 15 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KawaiNui 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KawaiNui 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KawaiNui 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KawaiNui 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KawaiNui 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 KawaiNui 0 0 8 62 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua 0 0 22 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua 0 0 0 22 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Hamakua 0 0 0 24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa 0 0 25 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa 0 0 0 65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waiawa 0 0 10 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Pouhala 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0

120

Pouhala 0 0 94 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Pouhala 0 15 20 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Pouhala 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Pouhala 0 0 98 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Pouhala 0 0 0 50 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waimea 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waimea 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waimea 0 0 6 45 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waimea 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waimea 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Waimea 0 0 4 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paiko Lagoon 0 0 0 0 0 70 30 0 0 0 0 0 0 0 0 0 0 0 0 0 Paiko Lagoon 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paiko Lagoon 0 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paiko Lagoon 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 Paiko Lagoon 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Paiko Lagoon 0 0 0 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Klipper Pond 0 0 0 0 0 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Klipper Pond 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Klipper Pond 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Klipper Pond 0 0 0 0 0 60 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Klipper Pond 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Klipper Pond 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Perc Ditch 3 0 0 0 0 59 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Perc Ditch 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Perc Ditch 0 0 1 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Perc Ditch 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 Perc Ditch 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Perc Ditch 2 0 3 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Salvage Yard 0 0 30 50 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Salvage Yard 0 0 82 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Salvage Yard 0 0 27 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Salvage Yard 0 0 15 50 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Salvage Yard 0 0 75 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

121

Salvage Yard 0 0 23 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ka‘elepulu 0 0 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ka‘elepulu 0 0 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ka‘elepulu 0 0 10 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ka‘elepulu 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ka‘elepulu 0 0 80 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Ka‘elepulu 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bellows 0 0 0 0 0 88 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bellows 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bellows 0 0 0 16 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bellows 0 0 0 0 0 43 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bellows 0 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Bellows 0 0 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

122

Appendix C.

Location Zone

Moisture (g/cm3)

Bulk Density (g/ccm)

LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Koheo W 0.49 1.44 11.21 8.00 46.00 0.05 4.14 34 22.16 23.16 54.69 Koheo I 0.29 1.18 9.06 8.10 48.00 0.02 4.40 30 16.08 14.68 69.25 Koheo D 0.29 0.93 7.89 8.40 7.30 0.07 5.24 23 9.30 13.65 77.05 Koheo W 0.25 0.74 7.71 8.10 23.00 0.01 5.44 23 13.14 15.35 71.51 Koheo I 0.31 0.66 15.60 8.00 48.00 0.10 2.63 38 21.80 45.52 32.68 Koheo D 0.51 1.09 12.05 8.20 16.00 0.15 2.33 156 25.81 53.94 20.24 Kakahaeia W 0.59 0.40 22.70 7.90 96.00 0.40 5.39 147 51.31 47.72 0.96 Kakahaeia I 0.77 0.65 20.12 8.10 70.00 0.30 3.83 156 NA NA NA Kakahaeia D 0.49 0.40 21.29 8.00 62.00 0.37 5.25 156 NA NA NA Kakahaeia W 0.51 0.48 16.18 8.20 22.00 0.23 3.24 160 42.11 55.88 2.01 Kakahaeia I 0.24 0.22 14.39 8.20 6.20 0.23 3.03 318 NA NA NA Kakahaeia D 0.58 0.68 14.44 7.50 6.00 0.24 3.03 128 50.24 46.75 3.01 Mo. Sea Farms W 0.60 0.46 18.66 6.20 53.00 0.31 3.89 60 46.36 49.34 4.29 Mo. Sea Farms I 0.50 0.59 13.88 7.00 28.00 0.24 2.63 150 19.18 57.03 23.79 Mo. Sea Farms D 0.61 0.61 16.82 6.30 36.00 0.31 3.87 79 53.17 42.91 3.92 Mo. Sea Farms W 0.68 0.31 25.71 5.70 70.00 0.71 9.99 62 34.13 58.47 7.40 Mo. Sea Farms I 0.65 0.57 18.92 6.60 40.00 0.31 3.80 53 NA NA NA Mo. Sea Farms D 0.54 0.61 17.14 6.50 34.00 0.26 2.87 75 40.58 58.43 0.99 Ualapue W 0.58 0.09 68.09 3.80 32.00 1.59 36.63 28 NA NA NA Ualapue I 0.52 0.12 49.77 5.80 9.20 1.65 24.21 43 NA NA NA Ualapue D 0.22 0.59 17.81 7.20 2.30 0.53 6.17 205 14.88 24.23 60.89 Ualapue W 0.53 0.62 16.53 7.00 6.10 0.34 4.69 38 30.97 50.40 18.63 Ualapue I 0.29 0.03 79.98 6.1 14 2.94 44.09 205 NA NA NA Ualapue D 0.18 0.67 12.20 7.10 1.00 0.32 4.18 94 16.27 24.25 59.48

Soil properties for each sample quadrat.

123

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Ohiapilo W 0.66 0.39 19.15 6.90 40.00 0.33 4.08 51 65.95 32.21 1.84 Ohiapilo I 0.49 0.62 11.00 8.00 17.00 0.15 2.84 68 32.90 62.98 4.12 Ohiapilo D 0.43 0.87 11.10 8.00 24.00 0.21 2.79 216 24.31 59.62 16.07 Ohiapilo W 0.63 0.52 17.99 7.20 40.00 0.29 4.99 37 37.37 48.66 13.97 Ohiapilo I 0.46 0.73 8.28 8.00 12.00 0.17 8.96 96 20.92 15.81 63.26 Ohiapilo D 0.27 1.02 5.07 8.00 6.00 0.11 7.95 13 7.60 9.14 83.26 Kanaha W 0.58 0.08 47.66 7.9 54 1.83 25.52 24 NA NA NA Kanaha I 0.40 0.25 19.25 8.30 20.00 0.33 12.80 32 36.11 17.38 46.52 Kanaha D 0.54 0.23 24.51 8.40 20.99 0.61 11.55 24 56.06 26.99 16.95 Kanaha W 0.39 0.04 63.72 7.2 73 1.92 34.64 49 NA NA NA Kanaha I 0.42 0.06 66.78 6.9 65 1.66 35.35 52 NA NA NA Kanaha D 0.54 0.09 45.12 6.5 45 1.27 22.48 17 NA NA NA Waipio W 0.55 0.05 88.87 5.9 15 2.10 56.47 257 NA NA NA Waipio I 0.43 0.05 78.04 5.4 6.8 2.69 42.72 166 NA NA NA Waipio D 0.44 0.68 17.88 7.40 5.20 0.43 4.32 33 34.22 33.74 32.04 Waipio W 0.29 0.02 86.03 5.4 12 2.03 48.28 441 NA NA NA Waipio I 0.33 0.04 71.87 5.6 7.5 2.93 40.11 149 NA NA NA Waipio D 0.38 0.58 18.90 6.60 1.20 0.36 4.32 37 22.72 27.57 49.71 Mohouli W 0.33 0.08 30.46 4.70 19.98 0.98 11.68 81 NA NA NA Mohouli I 0.34 0.22 38.87 5.1 5.8 1.62 21.92 76 NA NA NA Mohouli D 0.29 0.16 43.95 3.70 2.40 1.42 20.04 92 NA NA NA Mohouli W 0.59 0.11 39.23 5.20 24.98 1.34 16.45 60 NA NA NA Mohouli I 0.67 0.39 26.03 5.6 12 1.42 20.74 57 2.24 0.00 97.76 Mohouli D 0.35 0.14 69.31 4.1 4.4 1.80 27.39 69 NA NA NA


124

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Aimakapa W 0.57 0.07 39.81 7.6 130 1.62 16.63 48 NA NA NA Aimakapa I 0.52 0.05 77.15 5.50 194.81 2.14 41.58 92 NA NA NA Aimakapa D 0.67 0.07 36.01 5.5 162 2.67 42.43 47 NA NA NA Aimakapa W 0.49 0.04 80.07 6.2 200 2.96 41.17 92 NA NA NA Aimakapa I 0.79 0.09 77.57 5.70 154.85 2.20 35.93 51 NA NA NA Aimakapa D 0.86 0.19 79.49 5.5 90 2.36 35.62 97 NA NA NA Hanalei W 0.45 0.57 13.98 5.00 0.95 0.21 2.43 19 30.19 48.45 21.35 Hanalei I 0.65 0.88 14.21 5.40 1.00 0.20 2.27 17 33.53 51.95 14.52 Hanalei D 0.57 0.83 15.05 6.10 1.40 0.25 3.33 23 31.67 50.75 17.58 Hanalei W 0.48 0.69 14.99 5.40 1.35 0.20 2.20 18 36.05 57.81 6.15 Hanalei I 0.53 0.70 14.61 5.30 1.20 0.19 2.07 16 35.05 54.79 10.16 Hanalei D 0.38 0.81 14.95 6.00 1.22 0.23 2.82 17 26.98 39.16 33.86 Kilauea W 0.47 0.27 21.70 4.80 9.60 0.36 6.22 19 NA NA NA Kilauea I 0.53 0.62 22.65 6.10 2.80 0.41 5.60 13 63.90 34.06 2.04 Kilauea D 0.16 0.43 15.27 7.40 1.20 0.16 2.24 34 36.50 25.30 38.19 Kilauea W 0.73 0.42 20.78 5.30 8.40 0.28 4.48 11 53.24 41.18 5.59 Kilauea I 0.39 0.62 19.51 6.80 1.48 0.28 3.62 21 54.23 30.94 14.82 Kilauea D 0.21 0.40 20.84 6.60 1.75 0.36 4.59 15 58.11 32.22 9.66 Lawai Kai W 0.51 0.38 16.98 6.70 15.50 0.22 6.28 27 33.31 22.03 44.67 Lawai Kai I 0.48 0.47 18.42 7.40 9.50 0.25 4.57 17 27.23 31.67 41.10 Lawai Kai W 0.18 0.18 17.52 7.10 9.50 0.32 7.01 28 36.42 23.61 39.97 Lawai Kai I 0.55 0.52 13.84 7.50 8.70 0.20 5.83 19 39.98 25.58 34.44 Lawai Kai D 0.21 0.51 19.66 6.80 2.55 0.34 4.10 28 58.08 34.47 7.45 Huleia W 0.43 0.16 40.29 4.70 10.50 1.19 16.35 13 NA NA NA


125

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Huleia I 0.63 0.47 28.00 4.40 7.50 0.65 9.04 28 49.20 47.48 3.31 Huleia D 0.38 0.57 21.84 5.20 2.30 0.40 4.69 42 58.00 39.09 2.91 Huleia W 0.69 0.38 27.81 4.50 9.00 0.66 8.64 42 45.12 52.91 1.97 Huleia I 0.49 0.32 26.74 4.50 7.10 0.57 8.36 51 NA NA NA Huleia D 0.32 0.49 29.30 4.40 1.90 0.33 4.71 47 NA NA NA Kawaiele W 0.21 0.50 3.60 7.90 7.00 0.04 10.53 2 NA NA NA Kawaiele I 0.12 0.94 3.13 8.50 2.55 0.02 9.85 12 8.11 0.38 91.51 Kawaiele D 0.05 1.31 3.02 8.40 0.40 0.04 9.65 13 10.04 1.04 88.92 Kawaiele W 0.30 1.16 1.75 8.60 2.75 0.00 10.99 10 10.06 0.47 89.47 Kawaiele I 0.31 1.11 1.95 8.50 4.90 0.00 10.79 11 6.38 1.60 92.03 Kawaiele D 0.28 1.33 1.68 8.80 1.00 0.00 10.92 8 9.99 0.97 89.05 Kauai. Coastal W 0.41 0.29 16.34 7.00 39.00 0.26 10.81 14 37.01 12.89 50.10 Kauai. Coastal I 0.53 0.77 17.98 4.50 22.00 0.28 8.95 15 47.20 16.55 36.24 Kauai. Coastal D 0.33 0.68 15.57 7.80 16.00 0.25 6.97 48 45.98 19.44 34.58 Kauai. Coastal W 0.48 0.53 13.21 7.40 29.00 0.21 10.64 40 31.91 13.04 55.05 Kauai. Coastal I 0.34 0.71 13.96 7.70 18.00 0.19 9.66 44 36.53 11.19 52.29 Kauai. Coastal D 0.43 0.91 22.86 7.80 7.75 0.27 8.18 51 43.03 17.05 39.92 Kauai. Riparian W 0.28 0.15 22.69 4.0 5.2 0.60 7.77 27 56.83 38.18 5.00 Kauai. Riparian I 0.50 0.29 25.98 3.70 2.70 0.69 9.13 33 30.83 27.51 41.66 Kauai. Riparian D 0.43 0.77 20.08 3.50 2.75 0.28 4.07 36 48.27 32.52 19.21 Kauai. Riparian W 0.23 0.07 38.14 4.0 2.8 0.59 7.97 33 NA NA NA Kauai. Riparian I 0.27 0.20 24.66 3.80 2.00 0.52 7.48 42 60.66 30.95 8.40 Kauai. Riparian D 0.53 0.51 32.18 3.50 5.40 0.82 10.98 79 NA NA NA Nukolii W 0.33 0.81 2.89 8.10 7.60 0.03 11.15 7 6.70 0.85 92.45


126

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Nukolii I 0.39 0.85 3.03 8.00 9.00 0.02 10.94 5 8.86 0.06 91.08 Nukolii D 0.30 0.71 3.77 8.30 10.60 0.05 10.89 8 12.09 3.17 84.74 Nukolii W 0.30 0.53 2.67 8.10 4.80 0.02 10.88 7 10.50 0.58 88.92 Nukolii I 0.43 0.83 2.79 8.20 4.50 0.03 10.94 6 7.35 1.79 90.86 Nukolii D 0.39 1.14 2.67 8.40 5.20 0.02 11.00 5 7.02 1.20 91.79 Kaloko W 0.64 0.36 20.34 6.9 72 0.74 9.39 133 21.06 10.10 68.84 Kaloko D 0.03 0.40 28.16 7.0 5.8 1.78 21.57 166 26.30 10.88 62.82 Kaloko W 0.67 0.09 63.26 6.2 165 2.07 30.74 118 NA NA NA Kaloko I 0.36 0.31 31.29 6.6 66 0.86 13.16 31 NA NA NA Kaloko D 0.41 0.51 22.36 7.9 42 0.74 13.44 69 30.70 18.46 50.84 Honoapu W 0.48 0.39 19.90 5.90 30.00 0.15 2.03 15 22.41 56.05 21.54 Honoapu I 0.37 0.26 16.59 5.10 34.00 0.13 1.91 16 23.23 21.33 55.44 Honoapu D 0.53 0.59 20.08 6.60 24.00 0.44 5.36 47 30.22 39.14 30.63 Honoapu W 0.45 0.16 22.94 5.80 70.00 0.55 7.43 24 NA NA NA Honoapu I 0.45 0.07 64.32 4.6 120 1.76 33.27 82 NA NA NA Honoapu D 0.46 0.22 36.89 5.70 36.00 0.87 12.60 70 NA NA NA Kamilo Pt. 6 W 0.23 0.57 3.40 8.70 9.20 0.05 5.92 14 10.43 4.33 85.24 Kamilo Pt. 6 I 0.49 0.09 43.51 7.4 82 1.67 21.19 95 NA NA NA Kamilo Pt. 6 D 0.42 0.52 10.05 7.60 19.50 0.35 9.60 24 NA NA NA Kamilo Pt. 6 W 0.58 0.24 21.85 6.70 96.00 0.63 8.38 28 35.58 17.96 46.46 Kamilo Pt. 6 I 0.68 0.10 70.90 5.3 120 2.43 37.51 78 NA NA NA Kamilo Pt. 7 W 0.41 0.09 55.82 5.4 100 1.93 28.19 147 NA NA NA Kamilo Pt. 7 I 0.70 0.39 21.67 5.80 46.00 0.63 8.27 46 33.43 13.21 53.36 Kamilo Pt. 7 D 0.48 0.29 22.45 5.9 46 0.72 9.09 52 25.72 7.97 66.31


127

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Kamilo Pt. 7 W 0.95 0.15 73.79 5.00 100.00 2.63 38.22 58 NA NA NA Kamilo Pt. 7 I 0.65 0.11 75.14 5.3 125 2.34 37.22 130 NA NA NA Kii W 0.62 0.61 19.81 6.50 15.80 0.31 4.27 42 74.98 21.87 3.16 Kii I 0.58 0.62 18.98 7.80 11.50 0.23 4.25 40 NA NA NA Kii D 0.60 0.84 18.17 7.60 25.00 0.20 3.14 46 59.16 37.82 3.03 Kii W 0.49 0.59 17.85 7.40 9.40 0.22 3.61 79 59.93 39.41 0.66 Kii I 0.68 0.89 17.45 7.40 21.00 0.18 3.35 54 58.66 38.34 3.00 Kii D 0.66 0.82 16.98 7.60 27.00 0.19 3.57 34 52.50 41.41 6.09 Punamano W 0.49 0.53 7.36 8.20 1.40 0.14 10.50 26 42.98 31.09 25.94 Punamano I 0.55 0.31 24.81 7.90 7.40 0.69 12.51 91 60.96 26.54 12.50 Punamano D 0.40 0.58 14.50 8.10 5.90 0.44 11.56 42 43.59 13.55 42.86 Punamano W 0.26 0.14 15.76 8.00 2.55 0.21 4.64 33 76.37 22.04 1.58 Punamano I 0.56 0.51 9.92 8.10 2.70 0.21 9.55 28 49.94 29.15 20.91 Punamano D 0.36 0.47 14.40 7.60 10.60 0.29 7.82 30 57.63 6.65 35.72 Coconut Grove W 0.45 0.29 23.13 7.40 3.40 0.66 8.33 42 NA NA NA Coconut Grove I 0.69 0.65 20.71 7.60 3.65 0.39 5.61 51 79.14 17.00 3.86 Coconut Grove D 0.11 0.22 28.40 7.30 3.55 1.07 15.30 29 64.42 28.07 7.51 Coconut Grove W 0.55 0.55 11.90 7.60 3.90 0.33 4.51 58 78.89 20.15 0.96 Coconut Grove I 0.51 0.46 19.61 7.20 2.80 0.35 4.02 140 81.03 18.19 0.78 Coconut Grove D 0.25 0.52 12.81 7.80 3.30 0.34 10.02 72 49.67 26.83 23.50 Kealia W 0.48 0.65 16.12 7.90 54.00 0.12 2.19 40 25.44 63.54 11.02 Kealia I 0.29 0.39 21.50 7.70 49.00 0.43 6.32 65 37.19 62.72 0.09 Kealia D 0.18 0.29 27.89 6.90 57.00 0.56 6.47 30 NA NA NA Kealia W 0.46 0.70 25.46 7.90 50.00 0.11 1.74 47 28.26 65.30 6.45


128

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Kealia I 0.44 0.56 15.82 7.80 15.00 0.27 4.46 51 30.53 56.79 12.68 Kealia D 0.18 0.25 24.27 7.30 31.00 0.54 5.98 47 NA NA NA Keanai W 0.39 0.43 13.23 5.20 0.72 0.24 2.87 110 17.45 37.50 45.04 Keanai I 0.28 0.59 15.00 6.00 0.55 0.24 2.74 21 19.36 39.56 41.08 Keanai D 0.39 0.92 11.48 5.40 0.42 0.08 1.07 47 22.24 47.60 30.15 Keanai W 0.54 0.75 10.99 5.40 0.70 0.12 1.29 70 12.27 31.74 55.99 Keanai I 0.31 0.64 14.96 5.40 1.25 0.32 3.50 70 24.73 38.00 37.27 Keanai D 0.31 0.67 10.87 5.50 0.75 0.09 1.18 44 24.92 48.70 26.39 Waihe‘e W 0.42 0.45 8.29 7.70 4.90 0.26 7.69 70 21.59 10.20 68.20 Waihe‘e I 0.20 1.20 7.74 7.60 3.20 0.26 6.94 353 13.92 6.61 79.47 Waihe‘e D 0.12 1.14 6.21 7.80 1.50 0.19 6.21 161 12.87 4.63 82.50 Waihe‘e W 0.48 0.42 12.20 7.60 7.60 0.33 8.16 61 31.85 14.94 53.22 Waihe‘e I 0.22 0.97 7.39 7.70 1.05 0.22 7.27 234 13.82 3.80 82.38 Waihe‘e D 0.09 1.00 6.84 7.70 3.90 0.17 6.45 182 13.60 4.32 82.09 Paukukalo W 0.17 1.70 2.07 8.60 0.55 0.02 3.08 9 3.40 1.27 95.34 Paukukalo I 0.06 0.94 5.15 7.80 0.75 0.22 7.53 25 NA NA NA Paukukalo D 0.06 1.76 1.96 8.50 0.50 0.02 3.87 10 4.54 0.98 94.48 Paukukalo W 0.48 0.76 7.54 7.90 1.45 0.14 4.37 28 16.48 16.76 66.76 Paukukalo I 0.23 0.95 7.63 7.80 1.70 0.17 4.33 28 16.78 17.87 65.35 Paukukalo D 0.08 1.17 1.50 7.90 0.72 0.11 4.89 33 7.01 3.38 89.60 Nu‘u W 0.34 0.21 23.22 7.00 17.00 0.77 8.00 51 25.48 36.00 38.52 Nuu I 0.24 0.14 25.73 6.00 18.60 0.86 9.45 51 2.82 0.00 97.18 Nu‘u D 0.33 0.69 10.72 8.40 4.40 0.27 3.19 121 13.05 16.01 70.93 Nu‘u W 0.24 0.06 37.01 7.4 45 1.46 16.07 69 NA NA NA


129

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Nu‘u I 0.19 0.05 36.34 6.8 35 1.26 13.91 31 NA NA NA Nu‘u D 0.09 0.11 17.63 8.5 5.2 0.49 5.60 137 2.88 0.00 97.12 Kawai Nui I 0.37 0.72 18.28 5.90 1.60 0.36 4.09 23 42.68 46.13 11.20 Kawai Nui D 0.23 0.49 17.03 5.90 1.75 0.41 4.42 102 47.74 39.68 12.58 Kawai Nui W 0.44 0.39 20.99 5.40 1.72 0.39 5.43 24 44.11 51.90 3.99 Kawai Nui I 0.32 0.54 20.03 5.90 2.00 0.42 4.95 44 49.02 50.73 0.25 Kawai Nui D 0.32 0.82 17.02 6.60 1.90 0.38 4.37 91 51.83 37.42 10.76 Kawai Nui W 0.26 0.20 21.47 6.10 1.95 0.44 6.51 22 42.02 47.99 9.99 Hamakua W 0.61 0.59 18.78 7.30 45.00 0.38 4.61 27 NA NA NA Hamakua I 0.33 0.70 16.11 7.20 10.00 0.35 4.12 70 45.81 39.81 14.39 Hamakua D 0.21 0.69 15.32 7.40 1.53 0.26 3.50 51 46.49 32.46 21.05 Hamakua W 0.64 0.41 26.64 7.20 52.00 0.67 8.17 25 66.26 33.37 0.37 Hamakua I 0.42 0.55 18.92 7.40 10.20 0.49 5.38 54 50.18 47.97 1.85 Hamakua D 0.29 1.13 11.02 6.20 1.05 0.17 1.86 37 36.23 38.70 25.07 Waiawa W 0.54 1.02 17.46 7.80 60.00 0.06 2.43 63 34.73 47.09 18.19 Waiawa I 0.35 0.51 22.12 7.70 80.00 0.22 4.51 21 39.55 54.97 5.48 Waiawa D 0.12 0.44 22.63 7.40 14.00 0.62 10.29 133 34.78 50.54 14.68 Waiawa W 0.40 0.95 11.92 7.40 48.00 0.03 0.74 8 48.71 47.19 4.10 Waiawa I 0.49 0.68 19.87 7.70 74.00 0.14 3.48 19 39.15 56.36 4.49 Waiawa D 0.16 0.75 13.57 7.90 2.20 0.16 4.54 135 35.55 55.73 8.72 Pouhala W 0.67 0.61 20.43 7.40 91.00 0.26 5.23 28 37.18 53.68 9.14 Pouhala I 0.46 0.59 4.30 7.20 94.00 0.10 1.74 21 31.46 37.02 31.52 Pouhala D 0.12 0.58 9.18 5.80 17.00 0.04 0.77 2 49.08 37.92 13.01 Pouhala W 0.49 0.93 15.81 7.50 66.00 0.11 2.50 26 40.59 55.57 3.84


130

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Pouhala I 0.24 0.64 4.35 6.30 70.00 0.10 1.86 21 49.77 47.73 2.50 Pouhala D 0.30 0.82 18.68 6.20 30.00 0.19 3.32 26 34.69 45.84 19.48 Waimea W 0.43 0.53 14.59 6.30 16.00 0.19 2.89 7 30.94 34.67 34.39 Waimea I 0.73 0.66 16.36 6.00 14.00 0.26 3.80 5 33.07 42.70 24.23 Waimea D 0.18 0.42 13.13 6.50 2.60 0.15 2.26 7 51.40 36.14 12.46 Waimea W 0.47 0.32 22.96 6.10 23.00 0.36 6.14 12 36.11 41.22 22.67 Waimea I 0.65 0.55 20.72 5.70 19.00 0.31 4.79 8 35.62 51.59 12.80 Waimea D 0.18 0.68 7.72 7.90 2.00 0.14 9.09 31 14.63 13.00 72.36 Paiko Lagoon W 0.27 0.92 3.22 8.30 15.50 0.01 10.66 16 7.65 4.72 87.63 Paiko Lagoon I 0.55 1.01 6.33 8.20 43.00 0.07 11.04 9 13.93 4.98 81.09 Paiko Lagoon D 0.03 1.03 3.56 8.10 1.75 0.09 11.74 14 6.75 1.31 91.94 Paiko Lagoon W 0.39 1.08 3.90 8.20 18.00 0.04 10.25 16 9.24 6.60 84.16 Paiko Lagoon I 0.64 0.22 38.94 7.00 143.00 0.94 17.03 50 NA NA NA Paiko Lagoon D 0.05 1.09 3.46 8.0 2.2 0.06 11.30 16 4.51 1.86 93.63 Klipper Pond W 0.40 0.82 11.50 8.5 2.1 0.01 2.95 24 47.40 22.13 30.47 Klipper Pond I 0.47 0.81 7.17 8.4 2.1 0.08 5.11 40 21.10 10.88 68.03 Klipper Pond D 0.57 0.99 9.92 8.1 3.4 0.11 5.73 83 24.77 18.09 57.14 Klipper Pond W 0.21 0.48 6.94 8.0 3.1 0.03 5.50 47 21.82 12.77 65.41 Klipper Pond I 0.19 0.32 12.28 8.1 2.0 0.09 5.23 59 31.07 21.21 47.72 Klipper Pond D 0.31 0.86 7.93 8.2 2.3 0.06 6.63 47 19.14 11.04 69.82 Perc. Ditch W 0.36 0.68 12.07 7.6 3.0 0.18 7.62 28 27.13 39.59 33.27 Perc. Ditch I 0.32 0.90 13.73 7.9 4.7 0.19 3.94 78 24.80 28.69 46.51 Perc. Ditch D 0.15 0.55 19.24 7.6 5.0 0.33 6.08 137 28.45 29.88 41.68 Perc. Ditch W 0.27 0.46 13.80 7.6 2.7 0.21 8.77 69 31.28 23.31 45.41


131

Appendix C.

Location Zone

Moisture (g/cm3)


LOI (%) pH

EC (µS /cm)

N (%)

C (%)

ExP. (μg/g)

Clay (%)

Silt (%)

Sand (%)

Perc. Ditch I 0.25 0.65 8.11 8.2 1.6 0.07 7.36 88 34.97 26.36 38.67 Perc. Ditch D 0.12 0.67 14.04 7.7 2.2 0.29 10.72 166 29.82 28.45 41.73 Salvage Yard W 0.54 0.08 57.45 7.5 400 0.99 32.61 83 NA NA NA Salvage Yard I 0.17 0.79 10.21 7.9 27 0.13 10.82 28 14.93 15.06 70.00 Salvage Yard D 0.12 1.23 3.06 8.3 6.2 0.06 8.53 33 4.16 0.73 95.11 Salvage Yard W 0.45 0.07 59.96 5.9 390 1.21 33.28 103 NA NA NA Salvage Yard I 0.28 0.60 22.04 7.4 39 0.36 7.32 52 36.96 27.06 35.98 Salvage Yard D 0.31 0.81 15.65 7.6 23 0.17 4.87 78 24.70 17.92 57.39 Ka‘elepulu W 0.40 0.27 16.58 6.9 30 0.24 3.74 21 48.51 48.03 3.45 Ka‘elepulu I 0.52 0.69 19.37 7.1 33 0.22 2.87 20 NA NA NA Ka‘elepulu D 0.19 0.72 15.97 7.3 1.8 0.30 3.38 178 49.63 40.72 9.66 Ka‘elepulu W 0.27 0.31 13.22 6.8 18 0.16 2.02 21 56.78 41.72 1.50 Ka‘elepulu I 0.48 0.67 15.11 7.4 19 0.20 2.70 21 56.24 39.48 4.28 Ka‘elepulu D 0.23 0.95 14.74 7.5 1.7 0.30 3.27 166 40.78 34.29 24.93 Bellows W 0.73 0.48 20.01 7.1 12 0.32 8.22 59 39.01 37.23 23.77 Bellows I 0.57 0.22 27.33 5.8 29 0.91 16.98 71 47.57 31.51 20.92 Bellows D 0.09 0.76 8.25 7.6 1.4 0.18 12.06 95 12.97 9.36 77.67 Bellows W 0.76 0.41 25.20 6.0 14 0.44 8.32 69 49.64 42.87 7.49 Bellows I 0.51 0.24 40.27 5.7 66 0.81 15.34 66 NA NA NA Bellows D 0.13 0.83 7.87 7.8 1.3 0.19 12.71 76 14.63 9.52 75.85


132

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