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Changes in Nutrient Cycling and Availability due to Different Forest Management Methods

Changes in Nutrient Cycling and Availability due to Different Forest Management Methods. K.W. Goyne 1 , M.A. Albers 1 , J. Kabrick 2 , P. Motavalli 1 , D. Gwaze 3 , and M. Wallendorf 3 1 Univ. Missouri, Dept. Soil, Environ., Atmospheric Science

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Changes in Nutrient Cycling and Availability due to Different Forest Management Methods

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  1. Changes in Nutrient Cycling and Availability due to Different Forest Management Methods K.W. Goyne 1, M.A. Albers 1, J. Kabrick 2, P. Motavalli 1, D. Gwaze 3, and M. Wallendorf 3 1 Univ. Missouri, Dept. Soil, Environ., Atmospheric Science 2 U.S.D.A. Forest Service, Northern Research Station 3 Missouri Department of Conservation, Resource Science Division

  2. Overall Project Goals • Elucidate landscape factors influencing nutrient status in MOFEP soils.

  3. Overall Project Goals • Quantify the effects of current MOFEP management practices on nutrient cycling and availability in soils with differing nutrient supply capacities.

  4. Long-Term Team Goal • Being able to model and predict changes in nutrient cycling and pools within MOFEP and other Ozark Highlands forests to ensure that forest management practices are sustainable.

  5. Expected Benefits • Results will either confirm that existing management practices minimally or negligibly impact soil nutrient status. • Demonstrate that current management practices may not be suitable for all soil types. • Improve MDC’s ability to make sound, scientifically-based management decisions.

  6. Objective 1 • To quantify the landscape determinants (biotic and abiotic factors) of base cation supply and to rank them in order of importance across non-harvested forested landscapes within MOFEP. • Hypothesis: Base cation supply is closely associated with (1) depth to bedrock, (2) soil parent material, and (3) forest plant community type.

  7. Objective 1 - Approach • Used soil characterization data collected from 117 pedons during the 1995-1996 soil-landscape analysis. • Soil texture, cation exchange capacity, base cation concentration, etc. • Data set was appended with biotic and abiotic site factors that may affect base cation supply. • Community type, slope position, aspect, parent material, geologic strata, depth to bedrock, etc. • Classification and Regression Tree (CART) Analysis was used to identify and rank important explanatory site factors related to base cation supply.

  8. CART model — Ca and Mg in lower portion of the diagnostic subsurface horizon

  9. CART model — Ca and Mg in lower portion of the diagnostic subsurface horizon Tasks for this objective are ~ 85% complete.

  10. Objective 2 • To conduct laboratory experiments and analyses investigating changes in total soil N (TN), potentially mineralizable N, the distribution of N in labile and stable pools, and exchangeable base cations that occur after even-aged and uneven-aged harvest in soils with differing nutrient status. • Hypothesis: TN, potentially mineralizable N, and soil exchangeable base cations will decrease and the proportion of N in stable pools will increase with harvest intensity, effects will be greater in low nutrient soils.

  11. Objective 2- Approach • In August 2007, low, medium and high nutrient status soils were sampled in 10 cm increments from 0-30 cm within 9 MOFEP sites (486 samples). • Within each site and soil type, 3 subsamples were randomly collected in areas harvested in 1996 and nearby no-harvest areas (paired sampling). • Chosen to minimize variability of soil properties, vegetation, and climatic conditions that could mask treatment effects. • Control sites sampled using paired technique as well.

  12. Medium nutrient status map unit 82F Low nutrient status map unit 80F High nutrient status map unit 74F B = location of field replicates; myriad solid colors = soil map units; cross hatching, red = intermediate cuts, black = clear cuts.

  13. Objective 2- Approach

  14. Objective 2- Approach • Potentially Mineralizable N (PMN) • 84 day incubations of soil • samples • 30oC – optimum for N • mineralizing bacteria • Leaching conducted on days • 0, 1, 3, 7, 14, 21, 28, 42, 56, • 70, and 84 • Leachates analyzed for • inorganic N (NO3- and NH4+)

  15. Objective 2- Data

  16. Objective 2- Data

  17. Objective 2 – Characterization of N pools • PMN incubations to continue into spring 2009. • Total N combustion analysis in progress, anticipated completion January 2009. • Labile and stable N (potassium permanganate extraction ) anticipated completion spring 2009. • Water soluble N extractions completed by summer 2009.

  18. Objective 2 – Base Cation and Soil Characterization Analyses • Cation exchange capacity and exchangeable cations • pH and exchangeable acidity • Organic carbon content and particle size analysis • 60% completed by Soil Characterization Lab, anticipated completion December 2008.

  19. Objectives 3 and 4 - Future Work • To conduct laboratory column experiments investigating initial effects and longer-term effects of forest harvest management on leaching of N species and base cations from soils with differing nutrient status. • To determine changes in soil solution chemistry and nutrient flux with emphasis on the loss and gains of N, base cations and acidity before and after even-aged and uneven-aged harvest conducted on soils with differing soil nutrient status.

  20. Objectives 3 and 4 - Future Work • Construction of cation and anion resin samplers has been initiated. Soil solution samplers will be created in Spring 2009.

  21. Objectives 3 and 4 - Future Work • Construction of cation and anion resin samplers has been initiated. Soil solution samplers will be created in Spring 2009. • Using existing data, we will begin identifying sites in Summer 2009 to be sampled and instrumented.

  22. Objectives 3 and 4 - Future Work • Ground investigations and installation of samplers in late Summer and early Fall 2009.

  23. Integration and Collaboration • Collaboration with Dr. Chen and colleagues, sharing of data and integration of results, perhaps investigation of deep carbon quantity and distribution. • Studies investigating changes in microbial or decomposer communities. • We have initiated development of a molecular technique to assess nitrifying bacterial populations, specifically ammonia oxidizing bacteria. • Studies investigating the effects of wildfires on soil carbon, nutrients and biotic communities.

  24. PHYSICAL ENVIRONMENT SUB-MODEL Other Sub-models Human Impacts (Management) Geology/ Parent material Nutrients Biotic Community Topography Flora (ground flora, fungi, lichen) Slope Aspect Elevation Forest structure& composition Soil Landform Decomposers Climate Time Temperature Water Wind Fauna (Birds, Mammals, Herps, Invertebrates) Air Light Rain Wild Fire

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