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At least 37 records · Page 2Linked to original sources
USGS2016

Biocrusts in the context of global change

A wide range of studies show global environmental change will profoundly affect the structure, function, and dynamics of terrestrial ecosystems. The research synthesized here underscores that biocrust communities are also likely to respond significantly to global change drivers, with a large potential for modification to their abundance, composition, and function. We examine how elevated atmospheric CO 2 concentrations, climate change (increased temperature and altered precipitation), and nitrogen deposition affect biocrusts and the ecosystems they inhabit. We integrate experimental and observational data, as well as physiological, community ecology, and biogeochemical perspectives. Taken together, these data highlight the potential for biocrust organisms to respond dramatically to environmental change and show how changes to biocrust community composition translate into effects on ecosystem function (e.g., carbon and nutrient cycling, soil stability, energy balance). Due to the importance of biocrusts in regulating dryland ecosystem processes and the potential for large modifications to biocrust communities, an improved understanding and predictive capacity regarding biocrust responses to environmental change are of scientific and societal relevance.

Book chapter↗
USGS2005

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.

Remote Sensing of Environment↗
USGS2026

The Zooplankton International Geospatial (ZIG) dataset: A global repository of spatiotemporal freshwater zooplankton community composition data from lakes and reservoirs to support ecological research

Zooplankton transfer substantial energy in aquatic food webs and are used as indicators of environmental change. Syntheses of zooplankton community dynamics globally require datasets that span a wide range of environmental gradients; however, these datasets are limited due to methodological differences across programs, taxonomic inconsistencies, and a lack of standardized metadata. To reconcile these challenges, we created the Zooplankton International Geospatial (ZIG) dataset, which includes original zooplankton, water physical and chemical variables, and lake morphometric data from 311 inland lakes and reservoirs. ZIG includes waterbodies ranging in size from 0.005 to 82,100 km 2 and spanning broad latitudinal (−47.26 to 64.90) and longitudinal ranges (−165.04 to 176.53). Temporal coverage for individual waterbodies ranges between 1 and 60 yr with sampling frequency ranging from annually to weekly. With its extensive coverage and content, we consider ZIG to be a cornerstone for future investigations of global scale lake biodiversity change.

Limnology & Oceanography - Letters↗
USGS2012

Science implementation of Forecast Mekong for food and environmental security

Forecast Mekong is a significant international thrust under the Delta Research and Global Observation Network (DRAGON) of the U.S. Geological Survey (USGS) and was launched in 2009 by the U.S. Department of State and the Foreign Ministers of Cambodia, Laos, Thailand, and Vietnam under U.S. Department of State Secretary Hillary R. Clinton's Lower Mekong Initiative to enhance U.S. engagement with countries of the Lower Mekong River Basin in the areas of environment, health, education, and infrastructure. Since 2009, the USGS has worked closely with the U.S. Department of State; personnel from Cambodia, Laos, Thailand, and Vietnam; nongovernmental organizations; and academia to collect and use research and data from the Lower Mekong River Basin to provide hands-on results that will help decisionmakers in future planning and design for restoration, conservation, and management efforts in the Lower Mekong River Basin. In 2012 Forecast Mekong is highlighting the increasing cooperation between the United States and Lower Mekong River Basin countries in the areas of food and environmental security. Under the DRAGON, Forecast Mekong continues work in interactive data integration, modeling, and visualization system by initiating three-dimensional bathymetry and river flow data along with a pilot study of fish distribution, population, and migratory patterns in the Lower Mekong River Basin. When fully developed by the USGS, in partnership with local governments and universities throughout the Mekong River region, Forecast Mekong will provide valuable planning tools to visualize the consequences of climate change and river management.

Phnom Penh↗
USGS2025

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia↗
USGS2022

Ungulate migrations of the western United States, volume 2

Migration is widespread across taxonomic groups and increasingly recognized as fundamental to maintaining abundant wildlife populations and communities. Many ungulate herds migrate across the western United States to access food and avoid harsh environmental conditions. With the advent of global positioning system (GPS) collars, researchers can describe and map the year-round movements of ungulates at both large and small spatial scales. The migrations can traverse landscapes that are a mix of different jurisdictional ownership and management. Today, the landscapes migrating herds traverse are increasingly threatened by fencing, high-traffic roads, oil and gas development, and other types of permanent development. Through the use of GPS collars, a model of science-based conservation emerged in which migration corridors, stopovers, and winter ranges can be mapped in detail, thereby allowing threats and conservation opportunities to be identified and remedied. In 2018, the U.S. Geological Survey (USGS) assembled a Corridor Mapping Team (CMT) to work collaboratively with western states to map migrations of Odocoileus hemionus (mule deer), Cervus canadensis (elk), and Antilocapra americana (pronghorn). Led by the USGS Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of Federal scientists, university researchers, and biologists and analysts from participating State and Tribal agencies. The first set of maps described a total of 42 migrations across 5 western states and was published in 2020 as the first volume of this report series. This second volume describes an additional 65 migrations mapped within 9 western states and select Tribal lands. As the western United States continues to grow, this report series and the associated map files released by the USGS will allow for migration maps to be used for conservation planning by a wide array of State and Federal stakeholders to reduce barriers to migration caused by fences, roads, and other development.

western United States↗
USGS2012

Investigating global change, environmental response, and adaptation: Jill Baron's 30 years as an ecosystem ecologist

Three decades of research, 145 publications (including two books), 15 graduate students, leadership in scientific organizations, invited talks around the world, and two collaborative entities that facilitate scientific synthesis—it’s a lot to pack into one career. But USGS research ecologist and Colorado State University senior scientist Jill Baron isn’t finished yet.

Report↗
USGS2006

Understanding Amphibian Declines Through Geographic Approaches

Growing concern over worldwide amphibian declines warrants serious examination. Amphibians are important to the proper functioning of ecosystems and provide many direct benefits to humans in the form of pest and disease control, pharmaceutical compounds, and even food. Amphibians have permeable skin and rely on both aquatic and terrestrial ecosystems during different seasons and stages of their lives. Their association with these ecosystems renders them likely to serve as sensitive indicators of environmental change. While much research on amphibian declines has centered on mysterious causes, or on causes that directly affect humans (global warming, chemical pollution, ultraviolet-B radiation), most declines are the result of habitat loss and habitat alteration. Improving our ability to characterize, model, and monitor the interactions between environmental variables and amphibian habitats is key to addressing amphibian conservation. In 2000, the U.S. Geological Survey (USGS) initiated the Amphibian Research and Monitoring Initiative (ARMI) to address issues surrounding amphibian declines.

Fact Sheet↗
USGS2025

Environmental controls of suppressed fall crop productivity in an agrivoltaic solar array

Globally, agrivoltaics (AV) research has revealed how microclimates created by photovoltaic (PV) panels can be leveraged to promote reciprocal benefits for agricultural land use and PV energy generation. Yet, in regions of the United States where emissions reduction laws are likely to lead to greater PV development on croplands, empirical evaluation of such co-location remain under explored. Furthermore, the most common approach to AV in the United States is one that maximizes energy generation and secondarily accommodates for agricultural management, and the controls of crop production in facilities that employ such an approach are underrepresented in the AV literature. Here, we assessed the agronomic and physiological response of two vegetable crops (radish and radicchio) with different carbon allocation patterns (belowground and aboveground, respectively) in an energy focused AV facility during a fall growing season, in New York, United States. We found that a reduction in total irradiance (−24%) within the AV array decreased total biomass in both crop types (46% and 49%), with significant alterations to root-shoot ratios in radish. Reductions in total biomass were not a result of physiological acclimation, indicating that AV crops had similar photosynthetic capacity as control crops; however, the environmental constraints imposed by energy focused AV design (i.e. reduced irradiance) limited C uptake overall. Our findings highlight the need for novel management approaches (e.g. earlier planting of AV fall crops) to help overcome yield penalties incurred by energy focused AV designs.

New York↗
USGS2018

Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling

A wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.

Environmental Research Letters↗
USGS2013

Global change and mercury

More than 140 nations recently agreed to a legally binding treaty on reductions in human uses and releases of mercury that will be signed in October of this year. This follows the 2011 rule in the United States that for the first time regulates mercury emissions from electricity-generating utilities. Several decades of scientific research preceded these important regulations. However, the impacts of global change on environmental mercury concentrations and human exposures remain a major uncertainty affecting the potential effectiveness of regulatory activities.

Science↗
USGS2026

Co-producing coastal bird research on the Gulf Coast through structured decision making (SDM) and constructed value of information (CVoI)

Conservation practitioners face the complex challenge of addressing global biodiversity threats within social-ecological systems with multiple jurisdictions, numerous interest groups, and changing environmental conditions. Bridging the research-to-implementation gap between scientists and managers, which integrates diverse perspectives that represent the variety of considerations impacting management outcomes can help to inform efficient and effective conservation. Avian conservation programs along the U.S. Gulf Coast exemplify these challenges, as management decisions must address diverse threats to declining coastal bird populations across large breeding, wintering, and migratory ranges while facing uncertainty surrounding the efficacy of large-scale strategies. This provides opportunities for improving management through co-produced research with structured decision making (SDM). We present a case study that demonstrates the application of co-production principles and SDM to collaboratively develop high-priority research questions informing effective avian conservation and management. Additionally, we applied a constructed value of information (CVoI) framework to identify and prioritize which uncertainties to reduce and better understand how research questions impact management actions. The integration of SDM’s five-step decision making framework ensured key principles of co-production were met, while co-production enhanced SDM outcomes by incorporating diverse perspectives and knowledge bases. CVoI further allowed participants to collectively determine final high-priority research questions in the face of complexity and uncertainty. Together, these approaches supported co-produced knowledge-generation, strategic hypothesis prioritization, and identification of research questions most likely to improve conservation decisions. This case study from the U.S. Gulf Coast demonstrates how co-produced research through SDM offers a broadly applicable approach for navigating ecological complexity and bridging the research-to-implementation gap in avian conservation.

Gulf Coast↗
USGS2012

A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring

Aim: To develop a novel global spatial framework for the integration and analysis of ecological and environmental data. Location: The global land surface excluding Antarctica. Methods: A broad set of climate-related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis (PCA). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature. Results: The global environmental stratification (GEnS) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the Kappa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS. Main conclusions: The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (http://www.geoportal.org).

Global Ecology and Biogeography↗
USGS2015

Understanding ocean acidification impacts on organismal to ecological scales

Ocean acidification (OA) research seeks to understand how marine ecosystems and global elemental cycles will respond to changes in seawater carbonate chemistry in combination with other environmental perturbations such as warming, eutrophication, and deoxygenation. Here, we discuss the effectiveness and limitations of current research approaches used to address this goal. A diverse combination of approaches is essential to decipher the consequences of OA to marine organisms, communities, and ecosystems. Consequently, the benefits and limitations of each approach must be considered carefully. Major research challenges involve experimentally addressing the effects of OA in the context of large natural variability in seawater carbonate system parameters and other interactive variables, integrating the results from different research approaches, and scaling results across different temporal and spatial scales.

Oceanography↗
USGS2026

Seasons and seasonality in lakes: Synthesis amid global change

Seasonality in environmental conditions plays a fundamental role in shaping lake ecosystems. However, patterns of seasonality vary worldwide, and these patterns are shifting over time amid global change. Thus, it is increasingly important to evaluate how seasons and seasonality are represented in lake ecosystem research. Here, we used a literature review and global data analysis to synthesize approaches for conceptualizing seasons and seasonality in lakes. We found that a wide range of criteria are used to delineate discrete seasons in published literature, including fixed dates (e.g., months, solstice/equinox), environmental thresholds (e.g., temperature and precipitation cutoffs), and lake-specific indicators (e.g., ice cover, plankton phenology). Analyzing data from lakes worldwide, we found that using different criteria to define the same season resulted in divergent interpretations of ecosystem states. Based on our synthesis, we offer recommendations for how to incorporate seasonality into lake research and communications amid global change.

Limnology and Oceanography Letters↗
USGS2023

Isothermal recombinant polymerase amplification and CRIPSR (CAS12A) assay detection of Renibacterium salmoninarum as an example for wildlife pathogen detection in environmental DNA samples

Improving rapid detection methods for pathogens is important for research as we collectively aim to improve the health of ecosystems globally. In the northern hemisphere, the success of salmon ( Oncorhynchus spp.) populations is vitally important to the larger marine, aquatic, and terrestrial ecosystems they inhabit. This has led to managers cultivating salmon in hatcheries and aquaculture to bolster their populations, but young salmon face many challenges, including diseases such as bacterial kidney disease (BKD). Early detection of the BKD causative agent, Renibacterium salmoninarum , is useful for managers to avoid outbreaks in hatcheries and aquaculture stocks to enable rapid treatment with targeted antibiotics. Isothermal amplification and CRIPSR-Cas12a systems may enable sensitive, relatively rapid, detection of target DNA molecules from environmental samples compared to quantitative PCR (qPCR) and culture methods. We used these technologies to develop a sensitive and specific rapid assay to detect R. salmoninarum from water samples using isothermal recombinase polymerase amplification (RPA) and an AsCas12a RNA-guided nuclease detection. The assay was specific to R. salmoninarum (0/10 co-occurring or closely related bacteria detected) and sensitive to 0.0128 pg/µL of DNA (approximately 20–40 copies/µL) within 10 min of Cas activity. This assay successfully detected R. salmoninarum environmental DNA in 14/20 water samples from hatcheries with known quantification for the pathogen via previous qPCR (70% of qPCR-positive samples). The RPA-CRISPR/AsCas12a assay had a limit of detection (LOD) of >10 copies/µL in the hatchery water samples and stochastic detection below 10 copies/µL, similar to but slightly higher than the qPCR assay. This LOD enables 37 C isothermal detection, potentially in the field, of biologically relevant levels of R. salmoninarum in water. Further research is needed to develop easy-to-use, cost-effective, sensitive RPA/CRISPR-AsCas12a assays for rapidly detecting low concentrations of wildlife pathogens in environmental samples.

Journal of Wildlife Diseases↗
USGS2024

Global assessment of aquatic Isoëtes species ecology

Isoëtes are iconic but understudied wetland plants, despite having suffered severe losses globally mainly because of alterations in their habitats. We therefore provide the first global ecological assessment of aquatic Isoëtes to identify their environmental requirements and to evaluate if taxonomically related species differ in their ecology. The assessment resulted in an extensive new database on aquatic Isoëtes , ecological niche analyses, and descriptive species accounts. We compiled a global database that includes all known environmental data collected from 1935 to 2023 regarding aquatic Isoëtes. We then evaluated the environmental drivers of 16 species using 2,179 global records. Additionally, we used hypervolume analysis to quantify the ecological niches of the two species with the greatest number of records, finding significant differences and evidence that Isoëtes echinospora occupies a wider ecological niche than Isoëtes lacustris . Fifty-nine species (30% of the c. 200 Isoëtes species known today) were categorised as aquatic and were mainly reported in the Americas and northern Europe. About 38% of the aquatic species are threatened with extinction or are endemic to a small region, according to the International Union for Conservation of Nature's Red List in 2023. Many species were determined to be sensitive to certain water physical and chemical factors, generally preferring oligotrophic conditions such as low total phosphorus, moderate total nitrogen, moderate to low pH, and low conductivity. This analysis includes ecological data in the assessment of rare/threatened aquatic plants globally. This new database and the ecological analyses completed defined the ecological requirements of several species and identified knowledge gaps, which can aid management actions and future research. This paper highlights ecological significance and environmental sensitivities of aquatic Isoëtes . The current level of knowledge is inadequate for a large proportion of known taxa. We affirm the extreme need to support global, collaborative initiatives on which to build future conservation strategies.

Freshwater Biology↗
USGS2022

Global genetic diversity status and trends: Towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: ( i ) Genetic Diversity; ( ii ) Genetic Differentiation; ( iii ) Inbreeding; and ( iv ) Effective Population Size ( N e ). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.

Biological Reviews↗