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Abstract Farmers are showing a growing interest in soil health. Therefore, it is necessary to understand how and when indicators respond to changes in land management. Measurements of soil carbon (C) and nitrogen can take up to a decade to shift. However, it is unknown how other biotic markers of soil health (i.e., nematode communities) react. Here we use the long‐term agroecosystem research trial at the W. K. Kellogg Biological Station to determine which biotic indicators respond first to the implementation of sustainable agricultural management. High‐diversity perennial forage and native prairie had higher nematode abundances compared to monoculture crops with perennial forage also being compositionally distinct. Additionally, nematode abundance was higher in the aspirational corn (Zea mays) treatment than conventionally managed corn (p < 0.05). Mineralizable carbon (minC) was marginally greater in high plant diversity treatments (p < 0.1). Overall, nematode abundance, in combination with incremental changes in labile C, are indicators of rapid shifts in soil health. 

Abstract As farmers adapt to changing climate, they modify practices to manage evolving production risk. Understanding farmers' risk attitudes is critical to predicting their decisions about climate change adaptation. This research empirically estimates utility functions to measure the risk preferences of Michigan corn‐soybean farmers. We elicit choices between paired lotteries in both a general and an agricultural domain. We find that farmers are risk‐averse across domains. However, farmer risk preferences are more heterogeneous in the agricultural domain than in the general one. These results are robust across specifications of utility functions, individual versus aggregate estimates, and types of risky outcomes. 

Abstract Insect declines in agricultural landscapes have been reported as part of the larger biodiversity crisis, but long-term trends are difficult to assess due to natural population fluctuations, interactions with exotic species, and lack of consistent data. Here, we report on population trajectories of a community of predaceous lady beetles (Coleoptera: Coccinellidae) monitored annually over 31 years in a long-term agroecosystem experiment in southwestern Michigan, United States. The total lady beetle community has declined in abundance by 39% during this time, with native species exhibiting larger declines (77%) than exotics (23%). However, these gross trends mask apparent periods of stability, recovery, and, in some cases, very sharp declines lasting many years across individual species and groups. Native and exotic communities exhibit significant nonlinear abundance trends that are often asynchronous in time. Habitat perenniality moderates these patterns, with communities in annual crops exhibiting large changes and those in perennial crops following similar but less pronounced trajectories, while communities in forested habitats remain stable or exhibit gradual, nearly linear declines. Several once-common natives have fallen below detection limits, with six of 10 species not detected on an annual basis in the last 5 years. Over the full length of the study, the pest suppression potential of the entire community has declined 42%, threatening this valuable ecosystem service, which may be further undermined by the effective loss of functionally redundant species. The evidence for varying drivers of these patterns provides unique insights into the broader phenomenon of insect decline. 

ABSTRACT Ecosystem resistance and resilience to extreme climate events is impacted by community properties, including biodiversity. However, the relative importance of species richness, evenness and dominance is debated and is further modulated by global change factors such as nutrient addition. Using nearly 40 years of data from naturally‐assembled plant communities at three Long‐Term Ecological Research sites, we found that while species richness is important for resistance to extreme dry events, dominance is important for resistance to extreme wet events and evenness is important for resilience under ambient (unfertilized) conditions. Furthermore, nutrient addition alters resistance and resilience indirectly by reducing species richness and increasing dominance. Species richness and dominance are also directly reduced by extreme climate events, which may erode resistance and resilience to future events. Our results show that species richness, dominance and evenness shape ecosystem stability under climate extremes and that fertilization fundamentally modifies biodiversity–stability relationships in mesic grasslands. 

ABSTRACT Perennial grasses like switchgrass (Panicum virgatum) and miscanthus (Miscanthus × giganteus) are expected to supply a substantial amount of the United States bioeconomy's feedstock demand. However, uncertainties around their long‐term yields challenge the viability of their potential and limit their wider adoption. To resolve their long‐term yield patterns, we analyzed over 200 plantings of switchgrass and miscanthus across Michigan and Wisconsin, USA, measured over 5–15 years. We found a consistent two‐phase long‐term yield dynamic; during ayield‐building phase, peak yields occurred within 4–5 years after planting, followed by ayield‐decline phasein which switchgrass and miscanthus lost 30%–47% and 14%–40% of peak yields, respectively. Among the potential drivers of this dynamic and the yield decline, we found that weather conditions had little impact, as the variation across years was not large enough to drive the observed yield differences. Added nitrogen increased peak yields by 10%–20% and attenuated the yield decline by 20%–50%. However, since fertilized stands still showed a yield decline, other factors became limiting as stands aged. This conserved long‐term yield dynamic has direct implications on management. A farm‐to‐gate economic analysis suggests replanting switchgrass and miscanthus 5 and 9 years following their peak yields maximizes profit over a 30‐year time horizon. Results call for further management and breeding strategies to mitigate the yield‐decline phase, and for reparameterization of global bioenergy models with carbon capture and storage, which may overestimate yields and the economic and environmental benefits of crops grown for bioenergy feedstocks. 

Summary In coevolving species, parasites locally adapt to host populations as hosts locally adapt to resist parasites. Parasites often outpace host local adaptation since they have rapid life cycles, but host diversity, the strength of selection, and external environmental influence can result in complex outcomes.To better understand local adaptation in host–parasite systems, we examined locally adapted switchgrass (Panicum virgatum), and its leaf rust pathogen (Puccinia novopanici) across a latitudinal range in North America. We grew switchgrass genotypes in 10 replicated multiyear common gardens, measuring rust severity from natural infection in a ‘host reciprocal transplant’ framework for testing local adaptation. We conducted genome‐wide association mapping to identify genetic loci associated with rust severity.Genetically differentiated rust populations were locally adapted to northern and southern switchgrass, despite host local adaptation to environmental conditions in the same regions. Rust resistance was polygenic, and distinct loci were associated with rust severity in the north and south. We narrowed a previously identified large‐effect quantitative trait locus for rust severity to a candidate YELLOW STRIPE‐LIKE gene and linked numerous other loci to defense‐related genes.Overall, our results suggest that both hosts and parasites can be simultaneously locally adapted, especially when parasites impose less selection than other environmental factors. 

Abstract Agricultural researchers are increasingly encouraged to engage with stakeholders to improve the usefulness of their projects, but iterative research on the design and assessment of stakeholder engagement is scarce. The USDA Long‐Term Agroecosystem Research (LTAR) Network recognizes the importance of effective engagement in increasing the utility of information and technologies for future agriculture. Diverse stakeholders and researchers at the Kellogg Biological Station (KBS) LTAR site co‐designed the KBS LTAR Aspirational Cropping System Experiment, a process that provides a testing ground and interdisciplinary collaborations to develop theory‐driven assessment protocols for continuous stakeholder engagement. Informed by prior work, we designed an assessment protocol that aims to measure participant preferences, experiences, and perceived benefits at various stages of this long‐term project. Two online surveys were conducted in 2021 and 2022 among participants of LTAR engagement events at KBS, using a pre‐post design, resulting in 125 total responses. Survey respondents had positive perceptions of the collaboratively designed research experiment. They had a strong expectation that the research would generate conservation and environmental advances while also informing policy and programs. Respondents also indicated a desire to network with other stakeholders. The research team noted the significant role of a long‐term stakeholder engagement specialist in inviting participants from diverse backgrounds and creating an open and engaging experience. Overall, results highlight an interdisciplinary path of intentional and iterative engagement and evaluation to build a program that is adaptive and responsive to stakeholder needs. 

Abstract Mitigating the effects of climate stress on crops is important for global food security. The microbiome associated with plant roots, the rhizobiome, can harbor beneficial microbes that alleviate stress, but the factors influencing their recruitment are unclear. We conducted a greenhouse experiment using field soil with a legacy of growing switchgrass and common bean to investigate the impact of short-term drought severity on the recruitment of active bacterial rhizobiome members. We applied 16S rRNA and 16S rRNA gene sequencing for both crops and metabolite profiling for switchgrass. We included planted and unplanted conditions to distinguish environment- versus plant-mediated rhizobiome drivers. Differences in community structure were observed between crops and between drought and watered and planted and unplanted treatments within crops. Despite crop-specific communities, drought rhizobiome dynamics were similar across the two crops. The presence of a plant more strongly explained the rhizobiome variation in bean (17%) than in switchgrass (3%), with a small effect of plant mediation during drought observed only for the bean rhizobiome. The switchgrass rhizobiome was stable despite changes in rhizosphere metabolite profiles between planted and unplanted treatments. We conclude that rhizobiome responses to short-term drought are crop-specific, with possible decoupling of plant exudation from rhizobiome responses. 

Abstract Long-term climate history can influence rates of soil carbon cycling but the microbial traits underlying these legacy effects are not well understood. Legacies may result if historical climate differences alter the traits of soil microbial communities, particularly those associated with carbon cycling and stress tolerance. However, it is also possible that contemporary conditions can overcome the influence of historical climate, particularly under extreme conditions. Using shotgun metagenomics, we assessed the composition of soil microbial functional genes across a mean annual precipitation gradient that previously showed evidence of strong climate legacies in soil carbon flux and extracellular enzyme activity. Sampling coincided with recovery from a regional, multi-year severe drought, allowing us to document how the strength of climate legacies varied with contemporary conditions. We found increased investment in genes associated with resource cycling with historically higher precipitation across the gradient, particularly in traits related to resource transport and complex carbon degradation. This legacy effect was strongest in seasons with the lowest soil moisture, suggesting that contemporary conditions—particularly, resource stress under water limitation—influences the strength of legacy effects. In contrast, investment in stress tolerance did not vary with historical precipitation, likely due to frequent periodic drought throughout the gradient. Differences in the relative abundance of functional genes explained over half of variation in microbial functional capacity—potential enzyme activity—more so than historical precipitation or current moisture conditions. Together, these results suggest that long-term climate can alter the functional potential of soil microbial communities, leading to legacies in carbon cycling. 

Abstract As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) within a fine-scale geographic area (30 m). We scaled National Agricultural Statistic Survey land management data to National Land Cover Data cropland extents to assess GWP of cropland management over time and among management units (i.e. counties and production systems). We found that cropland extent alone was not indicative of GWP emissions; rather, rates of management intensity, such as energy and fertilizer use, are greater indicators of anthropogenic GWP. We found production processes for fuel and fertilizers contributed 51.93% of GWP, where 33.58% GWP was estimated from N₂O emissions after fertilization, and only 13.31% GWP was due to energy consumption by field equipment. This demonstrates that upstream processes in LCA should be considered in NbS with the relative contribution of fertilization to GWP. Additionally, while land cover change had minimal GWP effect, urbanization will replace croplands and forests where NbS are implemented. Fine-scale landscape variations are essential for NbS to identify, as they accumulate within regional and global estimates. As such, this study demonstrates the capability to harness both LCA and fine-resolution imagery for applications in spatiotemporal and socioecological research towards identifying and monitoring NbS.