Soil Health and Mesofauna following the Cornell Organic Grain Cropping Systems ExperimentAshley Jernigan1, Chris Pelzer1, Kyle Wickings2, and Matt Ryan1

Section of Soil and Crop Sciences1, Department of Entomology2, Cornell University, Ithaca NY

Cropping Systems Cover Crops Fertility Inputs Tillage

HF High Fertility

Ryegrass before soybean

Red Clover before corn

N-P-K on corn and spelt based on soil tests

Poultry compost on barley and spelt

Moldboard plow

Tine weed 1-3x

Cultivate 1-4x

LF Low FertilityRed Clover before corn

N-P-K corn starter

Moldboard plow

Tine weed 1-3x

Cultivate 1-4x

EWMEnhanced Weed Management

Red Clover before corn

N-P-K corn starter

Poultry compost on spelt

Moldboard plow

Tine weed 1-3x

Cultivate 2-5x

RTReduced Tillage

Oat/Winter Pea before corn

N-P-K corn starter

Poultry compost on barley (also applied on corn if legume N insufficient)

Deep zone till

Chisel plow

Cultivate 1-3x

Table 1. Summary of cropping system management practices for OGCS from 2011-2017.

▪ Long-term cropping systems experiment established in 2005

▪ Located in Aurora, New York (USDA zone 6a, Lima silt loam)

▪ Split-plot randomized complete block design (4 replications, 4 cropping systems, 2 crop rotation entry points)

▪ 3-yr crop rotation: soybean→spelt/red clover→corn crop rotation, with two exceptions: ▪ (1) the RT system intercropped

winter pea into the spelt instead of red clover

▪ (2) the HF and RT systems replaced corn with buckwheat and barley in a 6-yr rotation from 2011-2017

▪ A sorghum sudangrass (SSG) uniformity trial was conducted in 2017

▪ Long-term sustainability of ecosystems is commonly assessed by the fluctuations of soil quality (1).

▪ Soil fauna are considered useful indicators of soil quality due to their sensitivity to changes in land management practices and involvement in multiple soil functions (2).

▪ It is important that long-term experiments be used for the evaluation of soil quality in cropping systems since soil quality requires several years to reach a new equilibrium (3).

▪ The Cornell Organic Grains Cropping Systems Experiment (OGCS) was established to compare four crop management systems characterized by different practices. In 2017 a uniformity trial was conducted to evaluate the legacy effects of these management systems on the agroecosystem.

Hypotheses:▪ Soil aggregate stability and soil surface moisture would be greatest in the reduced

tillage system due to less intensive disturbance of the soil.▪ Chemical soil health indicators would have the strongest relationship with

aboveground biomass production in the uniformity trial.

Introduction

Experiment Design

Soil Health Sampling:▪ Soil samples collected on May 19th and 24th, 2017▪ Dairy One Soil Nutrient Analysis

▪ 5 cores collected in each plot using soil fertility probe to a depth of 8 cm

▪ Cornell Soil Health Test▪ 4 cores collected in each plot using a golf corer to a depth of 15-

20 cm, large rocks were removed

Methods

Results

Figure 3. Correlation analysis with data collected during the uniformity trial. R2

values ≥0.33 are statistically significant.

Figure 1. Nonmetric Multidimensional Scaling (NDMS) with environmental response variables measured during the uniformity trial (above). Cropping system colors: HF = blue, LF = red, EWM = black, RT = purple, Alleyway = green. Entry point line type: EP A (ryegrass) = dashed line, EP B (legume) = solid line.

Conclusions

References

• The EWM and LF systems had the poorest overall soil health (Figure 1).

• The EWM and RT systems had significantly more soil mesofauna at sampling date 2 than the HF and LF systems (Figure 2).

• Aggregate stability had the strongest correlation with SSG biomass (Figure 3).

• Soil mesofauna abundance had a stronger correlation with SSG biomass than most of the other soil health indicators tested (Figure 3).• Mesofauna may be a better

predictor of crop performance potential than other common soil health indicators.

• Cropping system management practices in conjunction with site factors, such as soil type and weather, have significant impacts on soil health indicators and soil mesofauna.

Figure 2. Mesofauna abundance by cropping system and crop rotation entry point at sampling date 1 and sampling date 2 (above).

Soil Mesofauna Sampling:▪ Soil sample collection

▪ Soil was sampled on August 1, 2017 (34 days after tillage) & September 6, 2017 (70 days after tillage)▪ Ten soil cores were collected with soil fertility probe to a depth of 10 cm

▪ Berlese funnel extraction for soil mesofauna▪ Temperature was gradually increased from 30C to 50C over the 3 day extraction▪ Extracted mesofauna were stored in 95% ethanol and identified to functional groups and morpho-

species; dry soil weights were recorded

Aboveground Biomass Sampling:▪ Two 0.5m2 quadrats per plot, plants clipped at ground level on August 31, 2017▪ Samples were dried in oven at 60C▪ Sorghum sudangrass and weed biomass were recorded

1. Schoenholtz, S., Miegroet, H.V., Burger, J., 2000. A review of chemical and physical properties as indicators of forest soil quality: challenges and opportunities. For. Ecol. Manage. 138, 335–356.

2. Stork, N.E., Eggleton, P., 1992. Invertebrates as determinants and indicators of soil quality. Am. J. Altern. Agric. 7, 38.

3. Raupp, J., Pekrun, C., Oltmanns, M., Köpke, U., 2006. Long Term Field Experiments in Organic Farming. Verlag Dr. Köster, Berlin, Darmstadt, Germany.

Aerial image (above) of the OGCS experiment taken on August 30th, 2017, illustrating the inter- and intra- plot variation observed during the uniformity trial.

Onychuridae

MesostigmataMite

Entomobryidae

OribatidaMite

Berlese Funnels