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Abstract In situ soil respiration is driven by annual patterns of temperature and soil moisture, but what about extracellular enzyme activities responsible for depolymerizing soil organic matter? We conducted biweekly measurements of potential soil β‐glucosidase activities during a 4‐month period from March soil thawing through July in annually cropped field plots in eastern South Dakota. Our objective was to determine the best sampling time to resolve the effects of crop rotational diversity on soil microbial activities. Potential β‐glucosidase activities were elevated immediately following soil thaw, peaked in May, and declined to their lowest value in mid‐summer. Temperature and precipitation had no value in predicting enzyme activities; however, enzyme activities were affected by crop rotational diversity and responded to current crop and previous crop. These findings are pertinent to the use of soil extracellular enzymes in soil health assessments and as indicators of microbial substrate preference with implications for soil carbon stabilization.

Abstract The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

Abstract Background Soil microbial communities are difficult to measure and critical to soil processes. The bulk soil microbiome is highly diverse and spatially heterogeneous, which can make it difficult to detect and monitor the responses of microbial communities to differences or changes in management, such as different crop rotations in agricultural research. Sampling a subset of actively growing microbes should promote monitoring how soil microbial communities respond to management by reducing the variation contributed by high microbial spatial and temporal heterogeneity and less active microbes. We tested an in-growth bag method using sterilized soil in root-excluding mesh, “sterile sentinels,” for the capacity to differentiate between crop rotations. We assessed the utility of different incubation times and compared colonized sentinels to concurrently sampled bulk soils for the statistical power to differentiate microbial community composition in low and high diversity crop rotations. We paired this method with Oxford Nanopore MinION sequencing to assess sterile sentinels as a standardized, fast turn-around monitoring method. Results Compared to bulk soil, sentinels provided greater statistical power to distinguish between crop rotations for bacterial communities and equivalent power for fungal communities. The incubation time did not affect the statistical power to detect treatment differences in community composition, although longer incubation time increased total biomass. Bulk and sentinel soil samples contained shared and unique microbial taxa that were differentially abundant between crop rotations. Conclusions Overall, compared to bulk soils, the sentinels captured taxa with copiotrophic or ruderal traits, and plant-associated taxa. The sentinels show promise as a sensitive, scalable method to monitor soil microbial communities and provide information complementary to traditional soil sampling.

There is increasing global demand for food, bioenergy feedstocks and a wide variety of bio-based products. In response, agriculture has advanced production, but is increasingly depleting soil regulating and supporting ecosystem services. New production systems have emerged, such as no-tillage, that can enhance soil services but may limit yields. Moving forward, agricultural systems must reduce trade-offs between production and soil services. Soil functional zone management (SFZM) is a novel strategy for developing sustainable production systems that attempts to integrate the benefits of conventional, intensive agriculture and no-tillage. SFZM creates distinct functional zones within crop row and inter-row spaces. By incorporating decimetre-scale spatial and temporal heterogeneity, SFZM attempts to foster greater soil biodiversity and integrate complementary soil processes at the sub-field level. Such integration maximizes soil services by creating zones of ‘active turnover’, optimized for crop growth and yield (provisioning services); and adjacent zones of ‘soil building’, that promote soil structure development, carbon storage and moisture regulation (regulating and supporting services). These zones allow SFZM to secure existing agricultural productivity while avoiding or minimizing trade-offs with soil ecosystem services. Moreover, the specific properties of SFZM may enable sustainable increases in provisioning services via temporal intensification (expanding the portion of the year during which harvestable crops are grown). We present a conceptual model of ‘virtuous cycles’, illustrating how increases in crop yields within SFZM systems could create self-reinforcing feedback processes with desirable effects, including mitigation of trade-offs between yield maximization and soil ecosystem services. Through the creation of functionally distinct but interacting zones, SFZM may provide a vehicle for optimizing the delivery of multiple goods and services in agricultural systems, allowing sustainable temporal intensification while protecting and enhancing soil functioning.

The importance of corn production to the midwestern United States cannot be overestimated. However, high production requires high nitrogen fertilization, which carries costs to environmental services such as water quality. Therefore, a trade-off exists between the production of corn yield and water quality. We used the Groundwater Vulnerability Assessment for Shallow depths and Crop Environment Resource Synthesis-Maize models to investigate the nature of this trade-off while testing the Simple Analytic Framework trade-offs featured in this Special Feature. First, we estimated the current levels of yield and water quality production in northeastern Iowa and southern Minnesota at the 1-square-kilometer, county, and regional scales. We then constructed an efficiency frontier from optimized nitrogen application patterns to maximize the production of both yield and water quality. Results highlight the context dependency of this trade-off, but show room for increasing the production of both services to the benefit of all stakeholders. We discuss these results in the context of spatial scale, biophysical limitations to the production of services, and stakeholder outcomes given disparate power balances and biophysical contexts.

Since the mid-20th century, crop breeding has driven unprecedented yield gains. Breeders generally select for broadly- and reliably-performing varieties that display little genotype-by-environment interaction (GxE). In contrast, ecological theory predicts that across environments that vary spatially or temporally, the most productive population will be a mixture of narrowly adapted specialists. We quantified patterns of broad and narrow adaptation in modern, commercial maize (Zea mays L.) hybrids planted across 216 site-years, from 1999-2018, for the University of Illinois yield trials. We found that location was the dominant source of yield variation (44.5%), and yearly weather was the smallest (1.7%), which suggested a benefit for reliable performance in narrow biophysical environments. Varieties displayed a large "home field advantage" when growing in the location of best performance relative to other varieties. Home field advantage accounted for 19% of GxE and provided a yield increase of 1.01 ± 0.04 Mg ∙ ha-1 (7.6% relative to mean yield), yet was both smaller than predicted by a null model and unchanged across time. This counterfactual suggests that commercial breeding programs have missed an opportunity to further increase yields by leveraging local adaptation. Public breeding programs may pursue this opportunity by releasing specialist varieties that perform reliably in narrow environments. As seed sources are increasingly privatized and consolidated, this alternate strategy may compliment private breeding to support global food security.