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At least 145 records · Page 8Linked to original sources
USGS2007

Investigating the Environmental Effects of Agriculture Practices on Natural Resources: Scientific Contributions of the U.S. Geological Survey to Enhance the Management of Agricultural Landscapes

The U.S. Geological Survey (USGS) enhances and protects the quality of life in the United States by advancing scientific knowledge to facilitate effective management of hydrologic, biologic, and geologic resources. Results of selected USGS research and monitoring projects in agricultural landscapes are presented in this Fact Sheet. Significant environmental and social issues associated with agricultural production include changes in the hydrologic cycle; introduction of toxic chemicals, nutrients, and pathogens; reduction and alteration of wildlife habitats; and invasive species. Understanding environmental consequences of agricultural production is critical to minimize unintended environmental consequences. The preservation and enhancement of our natural resources can be achieved by measuring the success of improved management practices and by adjusting conservation policies as needed to ensure long-term protection.

Fact Sheet↗
USGS2011

Rethinking hyporheic flow and transient storage to advance understanding of stream-catchment connections

Although surface water and groundwater are increasingly referred to as one resource, there remain environmental and ecosystem needs to study the 10 m to 1 km reach scale as one hydrologic system. Streams gain and lose water over a range of spatial and temporal scales. Large spatial scales (kilometers) have traditionally been recognized and studied as river-aquifer connections. Over the last 25 years hyporheic exchange flows (1-10 m) have been studied extensively. Often a transient storage model has been used to quantify the physical solute transport setting in which biogeochemical processes occur. At the longer 10 m to 1 km scale of stream reaches it is now clear that streams which gain water overall can coincidentally lose water to the subsurface. At this scale, the amounts of water transferred are not necessarily significant but the exchanges can, however, influence solute transport. The interpretation of seemingly straightforward questions about water, contaminant, and nutrient fluxes into and along a stream can be confounded by flow losses which are too small to be apparent in stream gauging and along flow paths too long to be detected in tracer experiments. We suggest basic hydrologic approaches, e.g., measurement of flow along the channel, surface and subsurface solute sampling, and routine measurements of the water table that, in our opinion, can be used to extend simple exchange concepts from the hyporheic exchange scale to a scale of stream-catchment connection.

Water Resources Research↗
USGS2025

Factors regulating the potential for freshwater mineral soil wetlands to function as natural climate solutions

There are increasing global efforts and initiatives aiming to tackle climate change and mitigate its impacts via natural climate solutions (NCS). Wetlands have been considered effective NCS given their capacity to sequester and retain atmospheric carbon dioxide (CO 2 ) while also providing a myriad of other ecosystem functions that can assist in mitigating the impacts of climate change. However, wetlands have a dual impact on climate, influencing the atmospheric concentrations of both CO 2 and methane (CH 4 ). The cooling effect associated with wetland CO 2 sequestration can be counterbalanced by the warming effect caused by CH 4 emissions from wetlands. The relative ability of wetlands to sequester CO 2 versus emit CH 4 is dependent on a suite of interacting physical, chemical, and biological factors, making it difficult to determine if/which wetlands are considered important NCS. The fact that wetlands are embedded in landscapes with surface and subsurface hydrological connections to other wetlands (i.e., wetlandscapes) that flow over and through geochemically active soils and sediments adds a new layer of complexity and poses further challenges to understanding wetland carbon sequestration and greenhouse gas fluxes at large spatial scales. Our review demonstrates how additional scientific advances are required to understand the driving mechanisms associated with wetland carbon cycling under different environmental conditions. It is vital to understand wetland functionality at both wetland and wetlandscape scales to effectively implement wetlands as NCS to maximize ecological, social, and economic benefits.

Wetlands↗
USGS2022

Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis

Background Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone. Methods We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries. Findings We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities. Interpretation The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. Funding Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.

The Lancet Planetary Health↗
USGS2026

Stacked machine learning for timber identification with laser-induced breakdown spectroscopy (LIBS)

This study presents a new approach to wood species identification using laser-induced breakdown spectroscopy (LIBS) combined with stacked machine learning techniques. The research analyzed 700 samples comprising nine Dalbergia species and nine additional tropical timber species, utilizing a handheld LIBS analyzer. A stacking methodology was developed by integrating three support vector machine (SVM) models with different kernel functions (linear, polynomial, and radial) in a one-versus-all (OVA) configuration. These SVM outputs were then combined using a partial least squares discriminant analysis (PLS-DA) meta-learner. Through PCA-based variable selection, the dimensionality was reduced from 23 401 to wavelengths while maintaining classification accuracy. The stacking approach achieved a Cohen's kappa value of 0.8671 in the validation set, significantly outperforming traditional flat classifiers. Variable importance analysis revealed calcium, magnesium, and barium as crucial elements for species differentiation, with their concentrations reflecting environmental conditions and geographical origins. This research demonstrates the potential of combining LIBS spectroscopy with advanced machine learning techniques for rapid, non-invasive timber identification, which can support efforts against illegal logging and enforcement of international trade regulations.

Applied Spectroscopy↗
USGS2018

Continuing progress toward a national assessment of water availability and use

Executive Summary The Omnibus Public Land Management Act of 2009 (Public Law 111—11) was passed into law on March 30, 2009. Subtitle F, also known as the SECURE Water Act, calls for the establishment of a “national water availability and use assessment program” within the U.S. Geological Survey (USGS). The USGS issued the first report on the program in 2013. Program progress over the period 2013–17 is reported herein to fulfill the requirement to inform Congress on implementation of the national water availability and use assessment program, also referred to as the USGS National Water Census (the Water Census). Much work has been accomplished during 2013–17 on producing water budgets for the nation, a goal USGS outlined in its first report on program progress to Congress. The USGS has completed three geographic focus area studies and has begun three others. Work has advanced on nationwide efforts in streamflow analysis, groundwater assessment and research, evapotranspiration studies, water use, environmental water science, and drought science. The USGS works with Federal and non-Federal agencies, universities, and other organizations to ensure that the information can be aggregated with other types of water-availability and socioeconomic information, such as data on food and energy production. The USGS has also made great strides in measures for delivering data and information on the Water Census to stakeholders and the public. Much work remains to be accomplished for the Nation to have a comprehensive, ongoing Water Census. In this report, the USGS lays out activities to be accomplished in the next 5 years (2017–22), based upon current funding levels. These include selecting new focus area studies, conducting hydrologic modeling to complete water budgets for the conterminous United States, expanding groundwater modeling efforts, mapping a national classification system for environmental water science, and developing an inventory of interbasin water transfers. All of these steps are necessary in order for the Water Census to achieve the goals outlined by Congress in the SECURE Water Act.

Circular↗
USGS2012

The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration

Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policy-makers are faced with countless decisions each year at local, state, tribal, territorial, and national levels on issues as diverse as renewable and non-renewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decision-making is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and well-being of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decision-makers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that USGS scientists and partners can play in building scientific understanding and providing timely information to decision-makers. The strategy underscores the connection between scientific discoveries and the application of new knowledge. The strategy integrates ecosystem science and decision-making, producing new scientific outcomes to assist resource managers and providing public benefits. The USGS is uniquely positioned to play an important role in ecosystem science. With its wide range of expertise, the agency can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the DOI and other partners in the natural sciences, in both conducting science and its application. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework and vision for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected and reinforcing components: • Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. • Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. • Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. • Develop tools, technologies, and capacities to inform decision-making about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. • Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: • Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. • Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. • Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. • Support decision-making. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the strategic approaches are a set of proposed actions that represent a sampling of specific activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct both discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role over the next decade in advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Open-File Report↗
USGS2023

A metasystem approach to designing environmental flows

Accelerating the design and implementation of environmental flows (e-flows) is essential to curb the rapid, ongoing loss of freshwater biodiversity and the benefits it provides to people. However, the effectiveness of e-flow programs may be limited by a singular focus on ensuring adequate flow conditions at local sites, which overlooks the role of other ecological processes. Recent advances in metasystem ecology have shown that biodiversity patterns and ecosystem functions across river networks result from the interplay of local (environmental filtering and biotic interactions) and regional (dispersal) ecological processes. No guidelines currently exist to account for these processes in designing e-flows. We address this gap by providing a step-by-step operational framework that outlines how e-flows can be designed to conserve or restore metasystem dynamics. Our recommendations are relevant to diverse regulatory contexts and can improve e-flow outcomes even in basins with limited in situ data.

BioScience↗
USGS2015

Towards a global terrestrial species monitoring program

Introduction: The Convention for Biological Diversity’s (CBD) Strategic Plan for Biodiversity 2011-2020 envisions that “By 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people.” Although 193 parties have adopted these goals, there is little infrastructure in place to monitor global biodiversity trends. Recent international conservation policy requires such data to be up-to-date, reliable, comparable among sites, relevant, and understandable; as is becoming obvious from the work plan adopted by the Intergovernmental Panel for Biodiversity and Ecosystem Services (IPBES: www.ipbes.net/; http://tinyurl.com/ohdnknq). In order to meet the five strategic goals of the Strategic Plan for Biodiversity 2011-2020 and its 20 accompanying Aichi Targets for 2020 (www.cbd.int/sp/targets/), advances need to be made in coordinating large-scale biodiversity monitoring and linking these with environmental data to develop a comprehensive Global Observation Network, as is the main idea behind GEOSS the Global Earth Observation System of Systems (Christian 2005)...Here we identify ten requirements important for the successful implementation of a global biodiversity monitoring network under the flag of GEO BON and especially a global terrestrial species monitoring program.

Journal for Nature Conservation↗
USGS2018

Spring temperature, migration chronology, and nutrient allocation to eggs in three species of arctic‐nesting geese: Implications for resilience to climate warming

The macronutrients that Arctic herbivores invest in their offspring are derived from endogenous reserves of fat and protein (capital) that females build prior to the period of investment or from foods they consume concurrently with investment (income). The relative contribution from each source can be influenced by temporal and environmental constraints on a female's ability to forage on Arctic breeding areas. Warming temperatures and advancing Arctic phenology may alter those constraints. From 2011–2014, we examined relationships among spring temperature, timing of migration and reproduction, and the sources of nutrients females deposited in eggs for three sympatric species of geese that nested in northern Alaska. Compared to lesser snow geese ( Anser caerulescens caerulescens ) and greater white‐fronted geese ( Anser albifrons frontalis ), black brant ( Branta bernicla nigricans ) were more likely to initiate follicle development during migration, resulting in fewer days between their arrival in the Arctic and the onset of incubation, and requiring a relatively greater capital investment in eggs. Delaying follicle development until after their arrival in the Arctic provided snow geese and white‐fronted geese an opportunity to forage near their nesting area and to deposit exogenous nutrients in eggs. With warmer spring temperatures brant invested more capital in eggs but snow geese invested less capital. Brant likely used capital to meet costs associated with earlier onset of follicle development when phenology was advanced, whereas snow geese used capital to compensate for poor foraging conditions during colder Arctic springs. Global warming is likely to reduce the quality of lower‐latitude marine habitats where brant acquire endogenous reserves, and advancing Arctic phenology may increase their reliance on those reserves during reproduction. Near‐term warming in northern Alaska may improve foraging conditions and favor the reproductive strategies of some herbivores such as snow geese and white‐fronted geese that mainly invest Arctic nutrients in their offspring.

Global Change Biology↗
USGS2013

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗
USGS2017

Conservation endocrinology

Endocrinologists can make significant contributions to conservation biology by helping to understand the mechanisms by which organisms cope with changing environments. Field endocrine techniques have advanced rapidly in recent years and can provide substantial information on the growth, stress, and reproductive status of individual animals, thereby providing insight into current and future responses of populations to changes in the environment. Environmental stressors and reproductive status can be detected nonlethally by measuring a number of endocrine-related endpoints, including steroids in plasma, living and nonliving tissue, urine, and feces. Information on the environmental or endocrine requirements of individual species for normal growth, development, and reproduction will provide critical information for species and ecosystem conservation. For many taxa, basic information on endocrinology is lacking, and advances in conservation endocrinology will require approaches that are both “basic” and “applied” and include integration of laboratory and field approaches.

BioScience↗
USGS2025

A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters

Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.

BioRxiv↗
USGS2021

Is the grass always greener? Land surface phenology reveals differences in peak and season-long vegetation productivity responses to climate and management

Vegetation phenology—the seasonal timing and duration of vegetative phases—is controlled by spatiotemporally variable contributions of climatic and environmental factors plus additional potential influence from human management. We used land surface phenology derived from the Advanced Very High Resolution Radiometer and climate data to examine variability in vegetation productivity and phenological dates from 1989 to 2014 in the U.S. Northwestern Plains, a region with notable spatial heterogeneity in climate, vegetation, and land use. We first analyzed interannual trends in six phenological measures as a baseline. We then demonstrated how including annual-resolution predictors can provide more nuanced insights into measures of phenology between plant communities and across the ecoregion. Across the study area, higher annual precipitation increased both peak and season-long productivity. In contrast, higher mean annual temperatures tended to increase peak productivity but for the majority of the study area decreased season-long productivity. Annual precipitation and temperature had strong explanatory power for productivity-related phenology measures but predicted date-based measures poorly. We found that relationships between climate and phenology varied across the region and among plant communities and that factors such as recovery from disturbance and anthropogenic management also contributed in certain regions. In sum, phenological measures did not respond ubiquitously nor covary in their responses. Nonclimatic dynamics can decouple phenology from climate; therefore, analyses including only interannual trends should not assume climate alone drives patterns. For example, models of areas exhibiting greening or browning should account for climate, anthropogenic influence, and natural disturbances. Investigating multiple aspects of phenology to describe growing-season dynamics provides a richer understanding of spatiotemporal patterns that can be used for predicting ecosystem responses to future climates and land-use change. Such understanding allows for clearer interpretation of results for conservation, wildlife, and land management.

Ecology and Evolution↗
USGS2017

USA National Phenology Network gridded products documentation

The goals of the USA National Phenology Network ( USA-NPN, www.usanpn.org ) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to facilitate informed ecosystem stewardship and management by providing phenological information freely and openly. One way the USA-NPN is endeavoring to accomplish these goals is by providing data and data products in a wide range of formats, including gridded real-time, short-term forecasted, and historical maps of phenological events, patterns and trends. This document describes the suite of gridded phenologically relevant data products produced and provided by the USA National Phenology Network, which can be accessed at www.usanpn.org/data/phenology_maps and also through web services at geoserver.usanpn.org/geoserver/wms?request=GetCapabilities .

Open-File Report↗
USGS2020

A socio-environmental geodatabase for integrative research in the transboundary Rio Grande/Río Bravo basin

Management of water resources in the transboundary Rio Grande/Río Bravo Basin (the Basin) presents challenges for state and Federal entities in the United States and Mexico making management decisions on shared water resources. Damming, channelization, water availability, and allocation are governed by water rights and water-sharing agreements. Data and information sharing are important aspects of transboundary cooperation, but differences in format, content, spatial and temporal resolution, and language hinder collaboration. In addition, data on the kinds and geographic distribution of water governance and management institutions across the Basin have not been consistently documented. Existing data disparities parallel the hydrological and social fragmentation of the Basin. Seeking to underscore the interdependence between social and environmental processes in the Basin, anthropologists and modelers collaborated to develop a socio-environmental geodatabase. This geodatabase is a first step in modeling the social components of decision making and their connectivity to environmental processes across the Basin. The geodatabase is available in an open-access domain and contains geospatial data related to water and land governance, hydrology, water use and hydraulic infrastructure, socioeconomics, and the biophysical environment necessary to advance the understanding of basin dynamics. Having these data documented and compiled in a central location serves as a resource to help decision makers better understand upstream and downstream social-environmental characteristics. This knowledge is useful for developing sustainable water management policies in a region where water resources are increasingly under pressure from climatic, environmental, and human-related changes.

Chihuahua, New Mexico, Texas↗
USGS2025

Real-time oil spill concentration assessment through fluorescence imaging and deep learning

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

Journal of Hazardous Materials↗