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  1. ; ; ; ; ; ; ; ( , American Journal of Botany)
    Premise

    Nutrients, light, water, and temperature are key factors limiting the growth of individual plants in nature. Mutualistic interactions between plants and microbes often mediate resource limitation for both partners. In the mutualism between legumes and rhizobia, plants provide rhizobia with carbon in exchange for fixed nitrogen. Because partner quality in mutualisms is genotype‐dependent, within‐species genetic variation is expected to alter the responses of mutualists to changes in the resource environment. Here we ask whether partner quality variation in rhizobia mediates the response of host plants to changing light availability, and conversely, whether light alters the expression of partner quality variation.

     Methods

    We inoculated clover hosts with 11 strains ofRhizobium leguminosarumthat differed in partner quality, grew plants under either ambient or low light conditions in the greenhouse, and measured plant growth, nodule traits, and foliar nutrient composition.

     Results

    Light availability and rhizobium inoculum interactively determined plant growth, and variation in rhizobium partner quality was more apparent in ambient light.

     Conclusions

    Our results suggest that variation in the costs and benefits of rhizobium symbionts mediate host responses to light availability and that rhizobium strain variation might more important in higher‐light environments. Our work adds to a growing appreciation for the role of microbial intraspecific and interspecific diversity in mediating extended phenotypes in their hosts and suggests an important role for light availability in the ecology and evolution of legume–rhizobium symbiosis.

     
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  2. ; ; ; ; ( , European Journal of Soil Science)
    Highlights

    We developed a new approach to calibration for 2‐D soil zymography.

    The approach accounted for spatial nonuniformity of soil zymograms.

    Standard calibration resulted in systematic underestimation of enzyme activity.

    Soil zymography requires pixel‐based calibration with nonuniformly saturated membranes.

     
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  3. ; ; ; ( , Global Change Biology)
    Abstract

    Groundwater irrigation of cropland is expanding worldwide with poorly known implications for climate change. This study compares experimental measurements of the net global warming impact of a rainfed versus a groundwater‐irrigated corn (maize)–soybean–wheat, no‐till cropping system in the Midwest US, the region that produces the majority of U.S. corn and soybean. Irrigation significantly increased soil organic carbon (C) storage in the upper 25 cm, but not by enough to make up for the CO2‐equivalent (CO2e) costs of fossil fuel power, soil emissions of nitrous oxide (N2O), and degassing of supersaturated CO2and N2O from the groundwater. A rainfed reference system had a net mitigating effect of −13.9 (±31) g CO2e m−2 year−1, but with irrigation at an average rate for the region, the irrigated system contributed to global warming with net greenhouse gas (GHG) emissions of 27.1 (±32) g CO2e m−2 year−1. Compared to the rainfed system, the irrigated system had 45% more GHG emissions and 7% more C sequestration. The irrigation‐associated increase in soil N2O and fossil fuel emissions contributed 18% and 9%, respectively, to the system's total emissions in an average irrigation year. Groundwater degassing of CO2and N2O are missing components of previous assessments of the GHG cost of groundwater irrigation; together they were 4% of the irrigated system's total emissions. The irrigated system's net impact normalized by crop yield (GHG intensity) was +0.04 (±0.006) kg CO2e kg−1yield, close to that of the rainfed system, which was −0.03 (±0.002) kg CO2e kg−1yield. Thus, the increased crop yield resulting from irrigation can ameliorate overall GHG emissions if intensification by irrigation prevents land conversion emissions elsewhere, although the expansion of irrigation risks depletion of local water resources.

     
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  4. ; ; ; ( , Scientific Reports)
    null (Ed.)
    Abstract Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar ( Populus nigra X P. maximowiczii ), switchgrass ( Panicum virgatum ), miscanthus ( Miscanthus giganteus ), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha −1  year −1 ) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L −1 ) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha −1  year −1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. 
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  5. ; ; ; ; ( , Soil Biology and Biochemistry)
    null (Ed.)
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  6. ( , Agriculture and Human Values)
    null (Ed.)
    Technical best management practices are the dominant approach promoted to mitigate agriculture’s significant contributions to environmental degradation. Yet very few social science studies have examined how farmers actually use these practices. This study focuses on the outcomes of farmers’ technical best management practice adoption related to synthetic nitrogen fertilizer management in the context of Midwestern corn agriculture in the United States. Moving beyond predicting the adoption of nitrogen best management practices, I use structural equation modeling and data from a sample of over 2500 farmers to analyze how the number of growing season applications a farmer uses influences the rate at which synthetic nitrogen is applied at the field-level. I find that each additional application of N during the growing season is associated with an average increase of 2.4 kg/ha in farmers’ average N application rate. This result counters expectation for the outcome of this practice and may suggest that structural pressures are leading farmers to use additional growing season applications to ensure sufficiently high N rates, rather than allowing them to reduce rates. I conclude by discussing the implication of this study for future research and policy. 
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  7. ; ; ; ; ; ( , Soil Biology and Biochemistry)
    null (Ed.)
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  8. ; ( , Frontiers in Ecology and Evolution)
    null (Ed.)
    Long-term monitoring programs are a fundamental part of both understanding ecological systems and informing management decisions. However, there are many constraints which might prevent monitoring programs from being designed to consider statistical power, site selection, or the full costs and benefits of monitoring. Key considerations can be incorporated into the optimal design of a management program with simulations and experiments. Here, we advocate for the expanded use of a third approach: non-random resampling of previously-collected data. This approach conducts experiments with available data to understand the consequences of different monitoring approaches. We first illustrate non-random resampling in determining the optimal length and frequency of monitoring programs to assess species trends. We then apply the approach to a pair of additional case studies, from fisheries and agriculture. Non-random resampling of previously-collected data is underutilized, but has the potential to improve monitoring programs. 
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  9. ; ; ; ; ( , Rhizosphere)
    null (Ed.)
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  10. ; ; ; ; ( , Environmental Science & Technology)
    null (Ed.)
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