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DOE OSTI2022

Evolution of zygomycete secretomes and the origins of terrestrial fungal ecologies

Fungi survive in diverse ecological niches by secreting proteins and other molecules into the environment to acquire food and interact with various biotic and abiotic stressors. Fungal secretome content is, therefore, believed to be tightly linked to fungal ecologies. We sampled 132 genomes from the early-diverging terrestrial fungal lineage zygomycetes (Mucoromycota and Zoopagomycota) and characterized their secretome composition. Our analyses revealed that phylogeny played an important role in shaping the secretome composition of zygomycete fungi with trophic mode contributing a smaller amount. Reconstruction of the evolution of secreted digestive enzymes revealed lineage-specific expansions, indicating that Mucoromycota and Zoopagomycota followed different trajectories early in their evolutionary history. We identified the presence of multiple pathogenicity-related proteins in the lineages known as saprotrophs, suggesting that either the ecologies of these fungi are incompletely known, and/or that these pathogenicity-related proteins have important functions associated with saprotrophic ecologies, both of which invite further investigation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed ‘meta-metabolome ecology.’ Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering and variations in putative biochemical transformations. We refer to this phenomenon as ‘thermodynamic redundancy,’ which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable principles, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Danczak, Robert E.↗

DOE OSTI2020

Comparing traditional and Bayesian approaches to ecological meta‐analysis

Abstract Despite the wide application of meta‐analysis in ecology, some of the traditional methods used for meta‐analysis may not perform well given the type of data characteristic of ecological meta‐analyses. We reviewed published meta‐analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies ( n i ) and the number of studies or records ( k ) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta‐analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that n i and k were highly variable, distributions were right‐skewed and were generally small (median n i = 5, median k = 44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval (CI) based on the t distribution that uses an adjusted standard error (the Hartung–Knapp–Sidik–Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z distribution CIs had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta‐analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random‐effects meta‐analysis, the performance of the best frequentist and Bayesian methods was similar for the same combinations of factors ( k and mean replication), though the Bayesian approach had higher than nominal (>95%) coverage for the mean effect when k was very low ( k < 15). Our literature review suggests that many meta‐analyses that used z distribution or bootstrapping CIs may have overestimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta‐analyses.

Pappalardo, Paula↗

DOE OSTI2024

The mycorrhizal symbiosis: research frontiers in genomics, ecology, and agricultural application

Summary Mycorrhizal symbioses between plants and fungi are vital for the soil structure, nutrient cycling, plant diversity, and ecosystem sustainability. More than 250 000 plant species are associated with mycorrhizal fungi. Recent advances in genomics and related approaches have revolutionized our understanding of the biology and ecology of mycorrhizal associations. The genomes of 250+ mycorrhizal fungi have been released and hundreds of genes that play pivotal roles in regulating symbiosis development and metabolism have been characterized. rDNA metabarcoding and metatranscriptomics provide novel insights into the ecological cues driving mycorrhizal communities and functions expressed by these associations, linking genes to ecological traits such as nutrient acquisition and soil organic matter decomposition. Here, we review genomic studies that have revealed genes involved in nutrient uptake and symbiosis development, and discuss adaptations that are fundamental to the evolution of mycorrhizal lifestyles. We also evaluated the ecosystem services provided by mycorrhizal networks and discuss how mycorrhizal symbioses hold promise for sustainable agriculture and forestry by enhancing nutrient acquisition and stress tolerance. Overall, unraveling the intricate dynamics of mycorrhizal symbioses is paramount for promoting ecological sustainability and addressing current pressing environmental concerns. This review ends with major frontiers for further research.

Plant Sciences↗

DOE OSTI2024

The role of emerging scientists in restoration ecology: insights from a SER2023 conference workshop

Emerging professionals are crucial in advancing ecological restoration by connecting newcomers with established leaders and blending new ideas with traditional practices. This paper highlights the vital role emerging scientists play in restoration ecology and the Society for Ecological Restoration (SER). A survey conducted during the SER2023 conference workshop, organized by the Students and Emerging Professionals committee, showed that emerging professionals contribute significantly to every stage of scientific work, from planning to publication. However, participants emphasized the scarcity of funding opportunities for non‐senior scientists, which limits academic growth. The workshop underscored the importance of nurturing emerging professionals to develop future leaders for SER and ensure continuity. Fostering non‐hierarchical and inclusive networking is key to engaging and empowering these professionals, ultimately contributing to the long‐term success of ecological restoration efforts.

Weidlich, Emanuela W. A.↗

DOE OSTI2023

Screening Level Ecological Exposure Assessment Work Plan

This work plan is part of an effort to complete an updated evaluation of the potential for adverse effects from miscellaneous treatment unit emissions to potential ecological receptors within and surrounding Site 200. It will address potential pathways between air emissions from the Lawrence Livermore National Laboratory’s (LLNL) Decontamination and Waste Treatment Facility (DWTF), single emission stack, and ecological receptors (i.e., plants and wildlife) present onsite and within a one-mile radius from the DWTF stack. This work plan outlines the procedures by which data collected as part of the previous investigations will be evaluated to assess risks to ecological receptors. It presents the problem formulation, initial conceptual site models, methods for characterizing exposure, toxicity, and risks that will be used if a more detailed “baseline” ecological risk assessment (BERA) is required.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

2023 Central Hanford Ecological Integrity Assessments Monitoring Report

The Hanford Site is comprised of an expanse of shrub-steppe habitats that provides exceptional ecological value to plants and animals located on the site and in the surrounding greater Columbia Basin. The U.S. Department of Energy (DOE)-managed portion of the Hanford Site, referred to from here on as Central Hanford, has been the focus of various ecological monitoring efforts, including vegetation monitoring. The scope and goals of vegetation surveys have varied greatly since the Hanford Site was established, but previous studies have documented a rapidly changing landscape, making it clear that continued vegetation monitoring is integral to preserving the ecological value of Central Hanford. A new vegetation monitoring effort was initiated in 2023 using methods based on ecological integrity assessments (EIA) (Natural Heritage Report [NHR] 2020-05) developed by the Washington Natural Heritage Program (WNHP), a division of the Washington State Department of Natural Resources (DNR) and NatureServe®. The methods were modified and supplemented to meet monitoring goals at the Hanford Site. The 2023 EIA monitoring effort consisted of field surveys to evaluate vegetation and soil condition across Central Hanford. Surveys were focused on upland habitats, and areas under consideration for upcoming projects were prioritized. Vegetation cover estimates were used to score a variety of metrics for vegetation conditions in each area. In 2023, approximately half of the site was surveyed. Monitoring methods and results for the 2023 field season are summarized in this report, and management recommendations are also provided.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Data from: Comparing traditional and Bayesian approaches to ecological meta-analysis

Despite the wide application of meta-analysis in ecology, some of the traditional methods used for meta-analysis may not perform well given the type of data characteristic of ecological meta-analyses. We reviewed published meta-analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies (ni) and the number of studies or records (k) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta-analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that ni and k were highly variable, distributions were right-skewed, and were generally small (median ni =5, median k=44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval based on the t-distribution that uses an adjusted standard error (the Hartung-Knapp-Sidik-Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z-distribution confidence intervals had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta-analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random-effects meta-analysis, the performance of the best frequentist and Bayesian methods were similar for the same combinations of factors (k and mean replication), though the Bayesian approaches had higher than nominal (>95%) coverage for the mean effect when k was very low (k<15). Our literature review suggests that many meta-analyses that used z-distribution or bootstrapping confidence intervals may have over-estimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta-analyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Custom surface reflectance, shade mask, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study (2025)

This dataset contains land surface reflectance estimates and additional derived products generated from NEON Imaging Spectrometer (NIS) data collected in the Upper Gunnison river basin during June and July of 2025. Data was collected over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). These products were derived from radiance and LiDAR data collected by the NEON Airborne Observation Platform (AOP) campaign funded by the Colorado Headwaters Ecological Spectroscopy Study (CHESS) (doi:10.15485/3017965). Products include per-pixel surface reflectance (rfl) and reflectance uncertainty (rfl_unc), observational data (obs), canopy equivalent water thickness (ewt), and shade masks. Atmospheric correction was performed per flightline using the ISOFIT (Imaging Spectrometer Optimal FITting) optimal estimation framework to estimate surface reflectance and the associated per-band reflectance uncertainty. Reflectance retrievals achieved a mean absolute error of 1.5% across diverse validation surfaces (see validation report.pdf). Equivalent water thickness was calculated from surface reflectance using the Beer–Lambert absorption of liquid water. Shade masks were generated based on the geometry between the sun angle, ground surface, and sensor at the time of flight. Data products are provided per-flightline and as mosaics for each domain. Flightline data products are provided as ENVI-formatted binary files (rfl, rfl_unc, ewt) and GeoTIFFs (shade). Reflectance and uncertainty mosaics are provided as tiled NetCDFs, while all other mosaicked products are provided as cloud-optimized GeoTIFFs. These formats are supported by common geospatial software (e.g., QGIS, ArcGIS, ENVI) and programmatic libraries in Python (e.g., rasterio, xarray, spectral, netCDF4) and R (e.g., terra, ncdf4). Processing workflows were designed to be equivalent to those used to generate the 2018 CHESS campaign airborne imaging spectroscopy data products (doi:10.15485/3013527). All outputs were co-registered to a common spatial grid to support time series analyses. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). Computational research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗

DOE OSTI2025

Beneath the surface: Unsolved questions in soil virus ecology

Soil virus ecology is an exciting but still nascent field of research in soil microbiology. While there has been a recent surge in soil virus research studies, many fundamental questions remain unanswered, and a range of technical and bioinformatic challenges need to be overcome. In this perspective article, we present a series of key questions that highlight fruitful research areas for ongoing and future efforts. These include describing the challenges involved in understanding soil viral abundance and activity, spatiotemporal dynamics, life strategy prevalence, virus-mediated biogeochemical impacts, viral protein function, host prediction, and soil RNA virus discovery. In the near term, combining approaches (e.g., cultivation-based, meta-omics, biogeochemical, experimental, and bioinformatic) will be key to assessing the ecological and biogeochemical impacts of soil viruses from the microscopic to the field and global scales. Still, we stress that results must be tempered by current methodological limitations and highlight knowledge gaps that are most pressing to fill via new methods or measurements, such as the prevalence of different viral replication strategies across soils, the fate of microbial necromass carbon after viral lysis, the frequency of virus-host encounters that do not lead to successful infections yet could be bioinformatically mistaken as infections, and the diversity and ecological impacts of RNA viruses in soil.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Soil viral diversity, ecology and climate change

Soil viruses are highly abundant and have important roles in the regulation of host dynamics and soil ecology. Climate change is resulting in unprecedented changes to soil ecosystems and the life forms that reside there, including viruses. In this Review, we explore our current understanding of soil viral diversity and ecology, and we discuss how climate change (such as extended and extreme drought events or more flooding and altered precipitation patterns) is influencing soil viruses. Finally, here, we provide our perspective on future research needs to better understand how climate change will impact soil viral ecology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

AmeriFlux FLUXNET-1F US-xJE NEON Jones Ecological Research Center (JERC)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xJE NEON Jones Ecological Research Center (JERC). This is the FLUXNET version of the carbon flux data for the site US-xJE NEON Jones Ecological Research Center (JERC) produced by applying the standard ONEFlux (1F) software. Site Description - This terrestrial relocatable field site is located in the Joseph Jones Ecological Research Center is an 11,000-hectare reserve located within the Lower Coastal Plains and Flatwoods areas in southern Georgia. The Jones site has been managed with low intensity, dormant-season prescribed fires for the past 75 years at a frequency of every 3-4 years.

Network), NEON (National Ecological Observatory↗

DOE OSTI2024

Exploring Ecological, Morphological, and Environmental Controls on Coastal Foredune Evolution at Annual Scales Using a Process-Based Model

Coastal communities commonly rely upon foredunes as the first line of defense against sea-level rise and storms, thus requiring management guidance to optimize their protective services. Here, we use the AeoLiS model to simulate wind-driven accretion and wave-driven erosion patterns on foredunes with different morphologies and ecological properties under modern-day conditions. Additional sets of model runs mimic potential future climate changes to inform how both morphological and ecological properties may have differing contributions to net dune changes under evolving environmental forcing. This exploratory study, applied to represent the morphological, environmental, and ecological conditions of the northern Outer Banks, North Carolina, USA, finds that dunes experiencing minimal wave collision have similar net volumetric growth rates regardless of beach morphology, though the location and density of vegetation influence sediment deposition patterns across the dune profile. The model indicates that high-density, uniform planting strategies trap sediment close to the dune toe, whereas low-density plantings may allow for accretion across a broader extent of the dune face. The initial beach and dune shape generally plays a larger role in annual-scale dune evolution than vegetation cover. For steeper beach slopes and/or low dune toe elevations, the model generally predicts wave-driven dune erosion at the annual scale.

Environmental Sciences & Ecology↗

DOE OSTI2020

A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming

Abstract Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

Abstract The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field‐based measures of abundance, demographic performance, and forecasted stochastic population growth (λ s ). Predicted climatic suitability showed a J‐shaped relationship with A. utahensis abundance, where low‐abundance populations were associated with low‐to‐intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λ s from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM‐predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.

Baer, Kathryn C.↗

DOE OSTI2022

Delayed fire mortality has long‐term ecological effects across the Southern Appalachian landscape

Abstract Fire is a critical ecological process to the forests of the Southern Appalachians. Where fire was excluded from forest types that historically burned frequently, unanticipated changes can occur when fire is reintroduced. For example, the development of new fuel characteristics can change the patterns of fire mortality and associated ecological responses. To test the fire effects of delayed fire mortality (mortality initiated by fire that occurs subsequent to the fire year) in the Southern Appalachians, USA, we developed a fire‐effects model using both field studies and remote sensing. We then simulated these effects at a landscape scale to estimate broader ecological effects. Fire‐effects models that accounted for delayed mortality increased landscape biomass removed annually (~23%) and increased the number of sites with high light conditions (leaf area index < 4) when compared to simulations that only account for immediate mortality. While delayed mortality occurred across species and age classes, it was especially prevalent among older trees (>100 years old) and fire‐resistant species ( Quercus spp.). Overall, regeneration (trees <20 years old) changed very little, even with the inclusion of delayed mortality. This evidence suggests that, even when accounting for delayed mortality, individual fires are unlikely to shift the landscape composition toward the conditions of forests prior to fire exclusion and may even increase mesophication long term due to the loss of overstory dominant xeric trees.

Robbins, Zachary J.↗

DOE OSTI2025

An ecological framework for microbial metabolites in the ocean ecosystem

The ocean microbe‐metabolite network involves thousands of individual metabolites that encompass a breadth of chemical diversity and biological functions. These microbial metabolites mediate biogeochemical cycles, facilitate ecological relationships, and impact ecosystem health. While analytical advancements have begun to illuminate such roles, a challenge in navigating the deluge of marine metabolomics information is to identify a subset of metabolites that have the greatest ecosystem impact. Here, we present an ecological framework to distill knowledge of fundamental metabolites that underpin marine ecosystems. We borrow terms from macroecology that describe important species, namely “dominant,” “keystone,” and “indicator” species, and apply these designations to metabolites within the ocean microbial metabolome. These selected metabolites may shape marine community structure, function, and health and provide focal points for enhanced study of microbe‐metabolite networks. Applying ecological concepts to marine metabolites provides a path to leverage metabolomics data to better describe and predict marine microbial ecosystems.

microbial metabolites↗

DOE OSTI2023

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks

Abstract Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions “centered” on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These “specialist” sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

54 ENVIRONMENTAL SCIENCES↗