Soil Community Structure, Function, and Spatial Variation in an Organic Agroecosystem

Soil Community Structure, Function, and Spatial Variation in an Organic Agroecosystem

Summary

This project examines the spatial variation of soil organisms and other edaphic properties across a large organic vegetable farm with diverse soil physical properties. Our study site, Full Circle Farm (FCF), is located near Carnation, WA (Figure 1). In 2006 we sampled across a 62-acre area to examine spatial variation of edaphic properties at a farm scale. In 2007 we intensively sampled two separate fields with near identical management to examine spatial variation at a field scale. In 2007 we presented research results at a farm walk at FCF (with over 80 participants) and at the WA Tilth Producers Conference.

Objectives/Performance Targets

There are five primary objectives for our project: 1) use geostatistics to develop maps for soil organisms and edaphic properties, 2) develop biological indicators that correlate to N-mineralization potential and aggregate stability, 3) recommend general biological sampling methods, 4) make recommendations to optimize farm productivity and profitability, and 5) share results with other growers and agricultural professionals.

Important performance targets:
Spring 2006 Establish sample locations & map management zones at FCF

Fall 2006 1st sampling at FCF

Spring 2007 2nd sampling at FCF

Summer 2007 Presentation at Puyallup Field Day, 50 people expected. Farm walk at FCF.

Fall 2007 1.) Presentation at WA Tilth Producers Conference. 2.) Post report on Puyallup Soils Group Webpage. 3.) Submit to WSU Small Farms Newsletter

Accomplishments/Milestones

Farm-scale Mapping. Our first sampling in 2006 was designed to describe edaphic properties across a 62-acre area on the eastern, more intensively farmed, side of FCF. We created a sampling plan that would evenly cover our sampling area and also serve the needs of a geostatistical analysis. To do this, 84 sites were placed across the sample area. The smallest spacing between sample sites (also called minimum lag distance) was 5 meters. This clustered type of spacing allowed us to accurately describe variation at a relatively small scale (5m), medium scale (90m) and larger scales (>100m). Farm management at the time of fall sampling was classified into five categories that primarily reflect the degree of recent disturbance: 1) harvested but not tilled, 2) not harvested, 3) recently tilled, 4) recently tilled and planted, and 5) perennial meadow (Figure 2). Plant type at each sample site was also recorded.

Field-scale Mapping. Analysis of results from the 2006 sampling indicated that plant type and management were both important in influencing biological properties. To better isolate the influence of edaphic properties and to focus on spatial variation of edaphic properties at scales between 5 and 90 m, we decided to sample at a field scale in 2007. Based on results of the 2006 sampling we chose two fields from areas of the farm with contrasting soil texture and placed 42 sample sites within each field (Figure 3). Both fields were planted to spinach in early June within 4 days of each other.

Soil Sampling. The first year’s sampling took place over 4 days between 12 and 20 October 2006. Though 84 sites were identified, 3 sites in the large meadow area had to be skipped due to time constraints. The second year’s sampling took place over 2 days on 9 and 10 July 2007.

Parameters Tested. Twelve parameters were tested for each sample site in 2006: soil moisture content, bulk density, aggregate stability, organic matter, total nitrogen, nitrate-N, texture, N-mineralization potential, collembolan diversity, nematode diversity, and total microbial biomass. In 2007 we tested the same parameters except for nitrate-N and N-mineralization potential.

Data analysis. We used kriging to generate maps of the physical, chemical, and biological properties tested within the sampled area, and this was done with GSLIB software (Deutsch and Journel, 1997). Kriging interpolates unknown values with knowledge about the underlying spatial relationships of known values. This knowledge is derived by fitting a model to a semivariogram, an analysis of the continuity of data values for a specific separation distance in a specific direction. Semivariograms were produced for 6 directions at 30-degree intervals. We displayed the kriged maps with ArcMap 9.2 (ESRI Inc.)

We are also using classification and regression tree analysis with RPART software (R development Core Team, 2007). This analysis, which is still underway, will help describe the relative importance of different edaphic properties in determining biological community structure and function. Classification and regression trees are a useful technique for partitioning value ranges of a response variable using both category responses (e.g. management type) and continuous variables (e.g. clay content) (De’ath and Fabricius, 2000).

Results
Soils within the area of the farm sampled varied greatly in texture. There was a strong gradient of increasing sand and decreasing clay from west to east (Figure 4a-c). Sand ranged from 5-54% while clay ranged from 9-27% and silt ranged from 35-76%. Four texture classes were identified: sandy loam, loam, silt loam, and silty clay loam. Silt loam was the predominant texture class (Figure 5).

The proportion of soil composed of aggregates was higher in the western, more clay rich, area of the farm (Figure 6).

Collembola (Figure 7) and nematode (Figure 8) populations were highly aggregated at the farm scale but areas of highest populations did not overlap.

Total C (Figure 9), N-mineralization potential (Figure 10), and microbial biomass (Figure 11) were all highest in an area of the farm managed as a meadow. The ratio of bacteria to fungi ranged from 1.3-3.7 (Figure 12) and pH ranged from 4.86 to 6.84 (Figure 13).

Farm Walk / Field Day
The soils research group at WSU Puyallup presented a field day / farm walk at Full Circle Farm on July 30, 2007 and over 80 participants were in attendance. We featured results from our on-farm research FCF and also discussed related soils research projects. We included hands-on demonstrations of soil quality assessment, discussion of relay cover cropping techniques, and explanation of the importance of spatial variation of edaphic properties at the farm scale. Each participant received a booklet with results summary and related information.

Presentation: Tilth Producers of Washington Conference
On November 11, 2007, Collins gave a presentation titled, “Soil fertility and soil biology: The role of soil organisms in maintaining productive soils” to the Tilth Producers of Washington Annual meeting. More than 50 meeting participants attended the presentation. Results from the FCF study were used to demonstrate the variability of edaphic properties across a farm and also the important relationship between total C and N mineralization potential.

Expectations for 2008.
Data analysis and interpretation will continue for both the 2006 and 2007 samplings. The project will be a chapter in Collins’ Ph.D. thesis and summaries will be posted to the Puyallup Soil’s group web page and submitted to the WSU Small Farms Newsletter.

Impacts and Contributions/Outcomes

This research examines the relationship between edaphic properties and soil biological communities across an organic vegetable farm. Growers are interested in the potential of using soil organisms to evaluate soil health. We use a spatial approach to evaluate the utility of collembola, nematodes, and microbial biomass as soil health indicators across soils with diverse physical characteristics. Growers will benefit from a greater understanding of the variation of soil organisms across a farm and how soil properties or management techniques influence soil communities. Those wishing to include biological parameters in soil health monitoring will be assisted by this research in designing sampling programs.

The research at Full Circle Farm has already created interest among the cooperating farmer in using precision agriculture techniques to address the challenges of farming across diverse soil types. While larger farms have adopted precision agriculture to optimize fertilizer and pesticide applications across a monoculture, this technology is underutilized to address problems encountered in diverse row crop operations. While technological solutions cannot replace farmer experience, a spatially explicit farm plan built on knowledge of edaphic properties could be instrumental in planning multi-year cropping strategies, amendment application, and tillage regimes.

References:

De’ath, G. and K. E. Fabricius. 2000. Classification and regression trees: A powerful yet simple technique for ecological data analysis. Ecology. 81: 3178-3192.

Deutsch, C. and A. Journel, 1997. GSLIB: Geostatistical Software Library and User’s Guide, 2nd edition. Oxford University Press. 340 pp.

R Development Core Team (2007). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.

Collaborators: