Predictions of changes in properties of forest soils

Pavel Samec

Content

• The problems• Material

- Data

- Forest ecosystem classification

• Methods - Basic time-series analysis

- Optimalization of the time-series parameters

- Statistical testing

• Results and Discussion• Summary• References

The Problems

The aim of the work

Description of the short-term development trend of soil physico-chemical conditions within leading forest ecosystem units

Observed trends of recent

forest soil development

-Post-war reconstruction 1953-1978-Heavy air pollution 1979-1994-Momentary revitalization 1995-2000-Residual acidification since 2001

Material

Data

• State pilot surveys of the Ministry of Agriculture of the Czech Republic on forest soils (17,380 pits used).

• Period 1953-2008.• Known innovations in sampling technology:

- 1971

- 1983

- 1996

- 2001

• Substrate characteristics: soil clay, total CaO and MgO.

• Trophically indicative characteristics: pH, BS, Corg and Ntot.

Material

Based on state biogeographical classification of management populations of forest types (Pitko and Plíva 1967).

Aggregated management populations of forest types in the Czech Republic

According to Samec et al. (2012)

Methods

• Soil properties are naturally subject to a lot of fluctuation periods that indicate

the development of ecological soil conditions.

• Several soil chemical properties run at cyclic (seasonal) oscillations (Heuvelink

and Webster 2001).

• Some soil (bio)chemical and physico-chemical properties moderately increase

or decrease (Cosby et al. 2001).

• Aproximated predictive periods:

- short-term prediction ≤ 2 years

- potentially medium-term prediction >2 years

• Optimalization of the function parameters by the Gauss-Newton transformation.

• Statistical testing by ANOVA and t-tests.

Experimental cyclometric functions for predictions of changes in selected soil properties:

• The cyclic aspect: cyclometric operator

• The trend aspect: Euler’s number

Results and discussion

• 5-year running means of substrate soil characteristics.

• 5-year running means of physico-chemical soil characteristics.

• 5-year running means of organic soil components.

• The overview of soil prediction functions.

• The overview of statistical testing of the results.

The fluctuations of 5-year running means of the clay fraction (CF) and base elements at acidic sites (AS), nutrient-rich highland sites (NHS) and waterlogged highland sites (WHS).

The fluctuations of 5-year running means of the soil base saturation (BS) and soil acidity (pH) at acidic sites (AS), nutrient-rich highland sites (NHS) and waterlogged highland sites (WHS).

The fluctuations of 5-year running means of the soil organic carbon (Corg) and total nitrogen

(Ntot) at acidic sites (AS), nutrient-rich highland sites (NHS) and waterlogged highland sites

(WHS).

Parameters and attributes of the soil prediction functions and calculated normal and predicted values of soil properties at the leading forest ecosystem units (FEU) in the Czech Republic; AS- acidic sites; HNS - nutrient-rich highland sites; WHS - waterlogged highland sites.

Statistical tests of quality in regression prediction of the selected soil properties (bold statistical signification differences at P<0.05).

Summary

• Development of selected soil properties is predicable within a period of 5

years.

• Soil acidity (pH) has potentially medium-term periodical oscillation. After mark

decrease during the period of heavy air pollution it is currently increase.

• BS and Corg in forest soils indicated parallel trends of development.

• During the period of 1953–2008 soil pH, BS, CaO have decreased but the

content of Corg and Ntot have increased.

• During the period of 2009-2014 the soil BS and pH may temporarily increase

and Corg and Ntot may decrease.

• Continuous increase in the soil BS with consequence effect in forest prospects

is only sustainable if concurrent with the increase in Corg.

References

• Cosby B.J., Ferrier R.C., Jenkins A., Wright R.F. 2001. Modelling the effects of acid deposition: refinements, adjustments and inclussion of nitrogne dynamics in the MAGIC model. Hydrology and Earth System Science 5: 499–517.

• Heuvelink G.B.M., Webster R. 2001. Modelling soil variation: past, present, and future. Geoderma 100: 269–301.

Pitko J., Plíva K. 1967. Hospodárské súbory lesných typov a ich využitie. Lesnický časopis 13: 905–924 (In Slovak).

Samec P., Tuček P., Bojko J., Janoška Z., Rychtecká P., Hájek F., Zapletal M., Sirota I., Miloš L., Mlčoušková P., Zeman M., Smejkal J., Mach S., Podrácká O. 2012. Modelování růstových podmínek lesů v České republice. Univerzita Palackého v Olomouci (In Czech).