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  1. Abstract

    Monitoring livestock feeding behavior may help assess animal welfare and nutritional status, and to optimize pasture management. The need for continuous and sustained monitoring requires the use of automatic techniques based on the acquisition and analysis of sensor data. This work describes an open dataset of acoustic recordings of the foraging behavior of dairy cows. The dataset includes 708 h of daily records obtained using unobtrusive and non-invasive instrumentation mounted on five lactating multiparous Holstein cows continuously monitored for six non-consecutive days in pasture and barn. Labeled recordings precisely delimiting grazing and rumination bouts are provided for a total of 392 h and for over 6,200 ingestive and rumination jaw movements. Companion information on the audio recording quality and expert-generated labels is also provided to facilitate data interpretation and analysis. This comprehensive dataset is a useful resource for studies aimed at exploring new tools and solutions for precision livestock farming.

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    Free, publicly-accessible full text available December 1, 2024
  2. Abstract

    ‘Marginal lands’ are low productivity sites abandoned from agriculture for reasons such as low or high soil water content, challenging topography, or nutrient deficiency. To avoid competition with crop production, cellulosic bioenergy crops have been proposed for cultivation on marginal lands, however on these sites they may be more strongly affected by environmental stresses such as low soil water content. In this study we used rainout shelters to induce low soil moisture on marginal lands and determine the effect of soil water stress on switchgrass growth and the subsequent production of bioethanol. Five marginal land sites that span a latitudinal gradient in Michigan and Wisconsin were planted to switchgrass in 2013 and during the 2018–2021 growing seasons were exposed to reduced precipitation under rainout shelters in comparison to ambient precipitation. The effect of reduced precipitation was related to the environmental conditions at each site and biofuel production metrics (switchgrass biomass yields and composition and ethanol production). During the first year (2018), the rainout shelters were designed with 60% rain exclusion, which did not affect biomass yields compared to ambient conditions at any of the field sites, but decreased switchgrass fermentability at the Wisconsin Central–Hancock site. In subsequent years, the shelters were redesigned to fully exclude rainfall, which led to reduced biomass yields and inhibited fermentation for three sites. When switchgrass was grown in soils with large reductions in moisture and increases in temperature, the potential for biofuel production was significantly reduced, exposing some of the challenges associated with producing biofuels from lignocellulosic biomass grown under drought conditions.

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  3. Abstract Background

    Root and soil microbial communities constitute the below-ground plant microbiome, are drivers of nutrient cycling, and affect plant productivity. However, our understanding of their spatiotemporal patterns is confounded by exogenous factors that covary spatially, such as changes in host plant species, climate, and edaphic factors. These spatiotemporal patterns likely differ across microbiome domains (bacteria and fungi) and niches (root vs. soil).


    To capture spatial patterns at a regional scale, we sampled the below-ground microbiome of switchgrass monocultures of five sites spanning > 3 degrees of latitude within the Great Lakes region. To capture temporal patterns, we sampled the below-ground microbiome across the growing season within a single site. We compared the strength of spatiotemporal factors to nitrogen addition determining the major drivers in our perennial cropping system. All microbial communities were most strongly structured by sampling site, though collection date also had strong effects; in contrast, nitrogen addition had little to no effect on communities. Though all microbial communities were found to have significant spatiotemporal patterns, sampling site and collection date better explained bacterial than fungal community structure, which appeared more defined by stochastic processes. Root communities, especially bacterial, were more temporally structured than soil communities which were more spatially structured, both across and within sampling sites. Finally, we characterized a core set of taxa in the switchgrass microbiome that persists across space and time. These core taxa represented < 6% of total species richness but > 27% of relative abundance, with potential nitrogen fixing bacteria and fungal mutualists dominating the root community and saprotrophs dominating the soil community.


    Our results highlight the dynamic variability of plant microbiome composition and assembly across space and time, even within a single variety of a plant species. Root and soil fungal community compositions appeared spatiotemporally paired, while root and soil bacterial communities showed a temporal lag in compositional similarity suggesting active recruitment of soil bacteria into the root niche throughout the growing season. A better understanding of the drivers of these differential responses to space and time may improve our ability to predict microbial community structure and function under novel conditions.

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  4. Abstract

    Monitoring soil nitrogen (N) dynamics in agroecosystems is foundational to soil health management and is critical for maximizing crop productivity in contrasting management systems. The newly established soil health indicator, autoclaved‐citrate extractable (ACE) protein, measures an organically bound pool of N. However, the relationship between ACE protein and other N‐related soil health indicators is poorly understood. In this study, ACE protein is investigated in relation to other soil N measures at four timepoints across a single growing season along a 33‐year‐old replicated eight‐system management intensity gradient located in southwest Michigan, USA. On average, polyculture perennial systems that promote soil health had two to four times higher (2–12 g kg−1higher) ACE protein concentrations compared to annual cropping and monoculture perennial systems. In addition, ACE protein fluctuated less than total soil N, NH4+‐N, and NO3‐N across the growing season, which shows the potential for ACE protein to serve as a reliable indicator of soil health and soil organic N status. Furthermore, ACE protein was positively correlated with total soil N and NH4+‐N and negatively correlated with NO3‐N at individual sampling timepoints across the management intensity gradient. In addition, ACE protein, measured toward the end of the growing season, showed a consistent and positive trend with yield across different systems. This study highlights the potential for ACE protein as an indicator of sustainable management practices, SOM cycling, and soil health and calls for more studies investigating its relationship with crop productivity.

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    Free, publicly-accessible full text available January 1, 2025
  5. Abstract

    Ecological restoration often targets plant community recovery, but restoration success may depend on the recovery of a complex web of biotic interactions to maintain biodiversity and promote ecosystem services. Specifically, management that drives resource availability, such as seeding richness and provenance, may alter species interactions across multiple trophic levels. Using experimentally seeded prairies, we examine three key groups—plants, pollinators and goldenrod crab spiders (Misumena vatia, predators of pollinators)—to understand the effects of species richness and admixture seed sourcing of restoration seed mixtures on multitrophic interactions.

    Working with prairie plants, we experimentally manipulated seed mix richness and the number of seed source regions (single‐source region or admixture seed sourcing). In each experimental prairie, we surveyed floral abundance and richness, pollinator visitation and plant–M. vatiainteractions.

    A high richness seed mix increased floral abundance when seeds were sourced from a single geographic region, and floral abundance strongly increased pollinator visitation,M. vatiaabundance and prey capture. Seeding richness and admixture seed sourcing of the seed mixture did not affect floral species richness, but floral species richness increased pollinator visitation.

    Pollinators interacted with different floral communities across seeding treatments, indicating a shift in visited floral species with restoration practices.

    Synthesis and applications. Long‐term success in prairie restoration requires the restoration of plant–arthropod interactions. We provide evidence that seed mix richness and admixture seed sourcing affect arthropod floral associations, but effective restoration of plant–arthropod interactions should consider total floral resource availability. Incorporating a food web perspective in restoration will strengthen approaches to whole ecosystem restoration.

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  6. Abstract

    Our knowledge of microbial processes—who is responsible for what, the rates at which they occur, and the substrates consumed and products produced—is imperfect for many if not most taxa, but even less is known about how microsite processes scale to the ecosystem and thence the globe. In both natural and managed environments, scaling links fundamental knowledge to application and also allows for global assessments of the importance of microbial processes. But rarely is scaling straightforward: More often than not, process rates in situ are distributed in a highly skewed fashion, under the influence of multiple interacting controls, and thus often difficult to sample, quantify, and predict. To date, quantitative models of many important processes fail to capture daily, seasonal, and annual fluxes with the precision needed to effect meaningful management outcomes. Nitrogen cycle processes are a case in point, and denitrification is a prime example. Statistical models based on machine learning can improve predictability and identify the best environmental predictors but are—by themselves—insufficient for revealing process‐level knowledge gaps or predicting outcomes under novel environmental conditions. Hybrid models that incorporate well‐calibrated process models as predictors for machine learning algorithms can provide both improved understanding and more reliable forecasts under environmental conditions not yet experienced. Incorporating trait‐based models into such efforts promises to improve predictions and understanding still further, but much more development is needed.

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  7. Abstract

    Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum (Sorghum bicolor), switchgrass (Panicum virgatumL.), and giant miscanthus (Miscanthus×giganteus), and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo (αs) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆α) and albedo‐induced radiative forcing (RFα). We used a nearby forest as a historical native cover type to estimate reference albedo and RFαchange upon original land use conversion, and a continuous no‐till maize (Zea mays L.) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually,αsdiffered significantly (p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annualαs(0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing seasonαsin perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS)αs(0.370 ± 0.020) was much higher than growing seasonαs(0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RFαMAIZE: −3.83 ± 1.00 W m−2; RFαFOREST: −16.75 ± 3.01 W m−2). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest.

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    Free, publicly-accessible full text available November 1, 2024
  8. Abstract

    Butterfly abundances are declining globally, with meta‐analysis showing a rate of −2% per year. Agriculture contributes to butterfly decline through habitat loss and degradation. Prairie strips—strips of farmland actively restored to native perennial vegetation—are a conservation practice with the potential to mitigate biodiversity loss, but their impact on butterfly biodiversity is not known.

    Working within a 30‐year‐old experiment that varied land use intensity, from natural areas to croplands (maize–soy–wheat rotation), we introduced prairie strips to less intensely managed crop treatments. Treatments included conservation land, biologically based (organic) row crops with prairie strips, reduced input row crops with prairie strips, no‐till row crops and conventional row crops. We measured butterfly abundance and richness: (1) within prairie strips and (2) across the gradient of land use intensity at the plot level.

    Butterfly abundance was higher within prairie strips than in all other treatments. Across the land use intensity gradient at the plot level, the conservation land treatment had the highest abundance, treatments with prairie strips had intermediate levels and no‐till and conventional treatments had the lowest abundances. Also across entire plots, butterfly richness increased as land use intensity decreased. Treatments with prairie strips, which also had reduced land use intensity, had distinct butterfly communities as they harboured several butterfly species that were not found in other row crop treatments.

    In addition to the known effects of prairie strips on ecosystem services including erosion control and increased water quality, prairie strips can increase biodiversity in multifunctional landscapes.

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  9. Abstract

    Cellulosic bioenergy is a primary land‐based climate mitigation strategy, with soil carbon (C) storage and nitrogen (N) conservation as important mitigation elements. Here, we present 13 years of soil C and N change under three cellulosic cropping systems: monoculture switchgrass (Panicum virgatumL.), a five native grasses polyculture, and no‐till corn (Zea maysL.). Soil C and N fractions were measured four times over 12 years. Bulk soil C in the 0–25 cm depth at the end of the study period ranged from 28.4 (± 1.4 se) Mg C ha−1in no‐till corn, to 30.8 (± 1.4) Mg C ha−1in switchgrass, and to 34.8 (± 1.4) Mg C ha−1in native grasses. Mineral‐associated organic matter (MAOM) ranged from 60% to 90% and particulate organic matter (POM) from 10% to 40% of total soil C. Over 12 years, total C as well as both C fractions persisted under no‐till corn and switchgrass and increased under native grasses. In contrast, POM N stocks decreased 33% to 45% across systems, whereas MAOM N decreased only in no‐till corn and by less than 13%. Declining POM N stocks likely reflect pre‐establishment land use, which included alfalfa and manure in earlier rotations. Root production and large soil aggregate formation explained 69% (p < 0.001) and 36% (p = 0.024) of total soil C change, respectively, and 60% (p = 0.020) and 41% (p = 0.023) of soil N change, demonstrating the importance of belowground productivity and soil aggregates for producing and protecting soil C and conserving soil N. Differences between switchgrass and native grasses also indicate a dependence on plant diversity. Soil C and N benefits of bioenergy crops depend strongly on root productivity and pre‐establishment land use.

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  10. Abstract

    Various soil health indicators that measure a chemically defined fraction of nitrogen (N) or a process related to N cycling have been proposed to quantify the potential to supply N to crops, a key soil function. We evaluated five N indicators (total soil N, autoclavable citrate extractable N, water‐extractable organic N, potentially mineralizable N, andN‐acetyl‐β‐D‐glucosaminidase activity) at 124 sites with long‐term experiments across North America evaluating a variety of managements. We found that 59%–81% of the variation in N indicators was among sites, with indicator values decreasing with temperature and increasing with precipitation and clay content. The N indicators increased from 6%–39% in response to decreasing tillage, cover cropping, retaining residue, and applying organic sources of nutrients. Overall, increasing the quantity of organic inputs, whether from increased residue retention, cover cropping, or rotations with higher biomass, resulted in higher values of the N indicators. Although N indicators responded to management in similar ways, the analysis cost and availability of testing laboratories is highly variable. Further, given the strong relationships of the N indicators with carbon (C) indicators, measuring soil organic C along with 24‐h potential C mineralization could be used as a proxy for N supply instead of measuring potentially mineralizable N or any other N indicator directly.

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    Free, publicly-accessible full text available July 1, 2024