Dataset Information

Applying cover crop residues as diverse mixtures increases initial microbial assimilation of crop residue‐derived carbon

ABSTRACT: Abstract Increasing the diversity of crops grown in arable soils delivers multiple ecological functions. Whether mixtures of residues from different crops grown in polyculture contribute to microbial assimilation of carbon (C) to a greater extent than would be expected from applying individual residues is currently unknown. In this study, we used 13C isotope labelled cover crop residues (buckwheat, clover, radish, and sunflower) to track microbial assimilation of plant residue‐derived C using phospholipid fatty acid (PLFA) analysis. We also quantified microbial assimilation of C derived from the soil organic matter (SOM) because fresh residue inputs also prime the decomposition of SOM. To consider the initial stages of residue decomposition, and preclude microbial turnover, we compared a quaternary mixture of residues with the average effect of their four components 1 day after incorporation. Our results show that the microbial biomass carbon (MBC) in the treatment receiving the mixed residue was significantly greater, by 132% (3.61 μg C g−1), than the mean plant residue‐derived MBC in treatments receiving the four individual components of the mixture. However, there was no evidence that the mixture resulted in any additional assimilation of C derived from native SOM than the average observed in individual residue treatments. We surmise that, during the initial stages of crop residue decomposition, a greater biodiversity of residues increases microbial assimilation to a greater extent than would be expected from applying individual residues either due to faster decomposition or greater carbon use efficiency (CUE). This might be facilitated by functional complementarity in the soil microbiota, permitted by a greater diversity of substrates, reducing competition for any single substrate. Therefore, growing and incorporating crop polycultures (e.g., cover crop mixtures) could be an effective method to increase microbial C assimilation in the early stages of cover crop decomposition.

Highlights

The effect of mixing crop residues on assimilation of C by soil microbial biomass was investigated. The study is important due to recent interest in diverse cover crop mixtures for arable systems. Mixing crop residues enhanced the assimilation of plant residue‐derived C into microbial biomass. Growing and incorporating cover crop polycultures may enhance C storage in arable soils.

SUBMITTER: Shu X

PROVIDER: S-EPMC9311145 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Cover crop mixtures have the potential to provide more ecosystem services than cover crop monocultures. However, seeding rates that are typically recommended (i.e. seeding rate of monoculture divided by the number of species in the mixture) are non-optimized and often result in the competitive species dominating the mixture, and therefore limiting the amount of ecosystem services that are provided. We created an analytical framework for selecting seeding rates for cover crop mixtures that maximize multifunctionality while minimizing seed costs. The framework was developed using data from a field experiment, which included six response surface designs of two-species mixtures, as well as a factorial replacement design of three-species and four-species mixtures. We quantified intraspecific and interspecific competition among two grasses and two legume cover crop species with grass and legume representing two functional groups: pearl millet [Pennisetum glaucum (L.) R.Br.], sorghum sudangrass [Sorghum bicolor (L.) Moench × Sorghum sudanense (Piper) Stapf], sunn hemp (Crotalaria juncea L.), and cowpea [Vigna unguiculata (L.) Walp]. Yield-density models were fit to estimate intraspecific and interspecific competition coefficients for each species in biculture. The hierarchy from most to least competitive was sorghum sudangrass > sunn hemp > pearl millet > cowpea. Intraspecific competition of a less competitive species was the greatest when the biculture was composed of two species in the same functional group. Competition coefficients were used to build models that estimated the biomass of each cover crop species in three-species and four-species mixtures. The competition coefficients and models were validated with an additional nine site-years testing the same cover crop mixtures. The biomass of a species in a site-year was accurately predicted 69% of the time (low root mean square error, correlation > 0.5, not biased, r2 > 0.5). Applying the framework, we designed three-species and four-species mixtures by identifying relative seeding rates that produced high biomass with high species evenness (i.e. high multifunctionality) at low seed costs based on a Pareto front analysis of 10,418 mixtures. Accounting for competition when constructing cover crop mixtures can improve the ecosystem services provided, and such an advancement is likely to lead to greater farmer adoption.

Project description:The dataset presented here supports the research paper entitled "A calculator to quantify cover crop effects on soil health and productivity". Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters - erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity - to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

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Applying cover crop residues as diverse mixtures increases initial microbial assimilation of crop residue‐derived carbon

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