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Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗

Designing count-based studies in a world of hierarchical models

Advances in hierarchical modeling have improved estimation of ecological parameters from count data, especially those quantifying population abundance, distribution, and dynamics by explicitly accounting for observation processes, particularly incomplete detection. Even hierarchical models that account for incomplete detection, however, cannot compensate for data limitations stemming from poorly planned sampling. Ecologists therefore need guidance for planning count-based studies that follow established sampling theory, collect appropriate data, and apply current modeling approaches to answer their research questions. We synthesize available literature relevant to guiding count-based studies. Considering the central historical and ongoing contributions of avian studies to ecological knowledge, we focus on birds as a case study for this review, but the basic principles apply to all populations whose members are sufficiently observable to be counted. The sequence of our review represents the thought process in which we encourage ecologists to engage 1) the research question(s) and population parameters to measure, 2) sampling design, 3) analytical framework, 4) temporal design, and 5) survey protocol. We also provide 2 hypothetical demonstrations of these study plan components representing different research questions and study systems. Mirroring the structure of hierarchical models, we suggest researchers primarily focus on the ecological processes of interest when designing their approach to sampling, and wait to consider logistical constraints of data collection and observation processes when developing the survey protocol. We offer a broad framework for researchers planning count-based studies, while pointing to relevant literature elaborating on particular tools and concepts.

Journal of Wildlife Management↗

Combined multibeam and bathymetry data from Rhode Island Sound and Block Island Sound: a regional perspective

Detailed bathymetric maps of the sea floor in Rhode Island and Block Island Sounds are of great interest to the New York, Rhode Island, and Massachusetts research and management communities because of this area's ecological, recreational, and commercial importance. Geologically interpreted digital terrain models from individual surveys provide important benthic environmental information, yet many applications of this information require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 14 contiguous multibeam bathymetric datasets that were produced by the National Oceanic and Atmospheric Administration during charting operations into one digital terrain model that covers much of Block Island Sound and extends eastward across Rhode Island Sound. The new dataset, which covers over 1244 square kilometers, is adjusted to mean lower low water, gridded to 4-meter resolution, and provided in Universal Transverse Mercator Zone 19, North American Datum of 1983 and geographic World Geodetic Survey of 1984 projections. This resolution is adequate for sea-floor feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the data include boulder lag deposits of winnowed Pleistocene strata, sand-wave fields, and scour depressions that reflect the strength of oscillating tidal currents and scour by storm-induced waves. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic features visible in the data include shipwrecks and dredged channels. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities offshore of Rhode Island.

Rhode Island↗

Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective

Detailed bathymetric maps of the sea floor in Long Island Sound are of great interest to the Connecticut and New York research and management communities because of this estuary's ecological, recreational, and commercial importance. The completed, geologically interpreted digital terrain models (DTMs), ranging in area from 12 to 293 square kilometers, provide important benthic environmental information, yet many applications require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 12 multibeam and 2 LIDAR (Light Detection and Ranging) contiguous bathymetric DTMs, produced by the National Oceanic and Atmospheric Administration during charting operations, into one dataset that covers much of eastern Long Island Sound and extends into westernmost Block Island Sound. The new dataset is adjusted to mean lower low water, is gridded to 4-meter resolution, and is provided in UTM Zone 18 NAD83 and geographic WGS84 projections. This resolution is adequate for sea floor-feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the grid include exposed bedrock outcrops, boulder lag deposits of submerged moraines, sand-wave fields, and scour depressions that reflect the strength of the oscillating and asymmetric tidal currents. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic artifacts visible in the bathymetric data include a dredged channel, shipwrecks, dredge spoils, mooring anchors, prop-scour depressions, buried cables, and bridge footings. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities in this major east-coast estuary.

Open-File Report↗

Fort Collins Science Center Ecosystem Dynamics branch--interdisciplinary research for addressing complex natural resource issues across landscapes and time

The Ecosystem Dynamics Branch of the Fort Collins Science Center offers an interdisciplinary team of talented and creative scientists with expertise in biology, botany, ecology, geology, biogeochemistry, physical sciences, geographic information systems, and remote-sensing, for tackling complex questions about natural resources. As demand for natural resources increases, the issues facing natural resource managers, planners, policy makers, industry, and private landowners are increasing in spatial and temporal scope, often involving entire regions, multiple jurisdictions, and long timeframes. Needs for addressing these issues include (1) a better understanding of biotic and abiotic ecosystem components and their complex interactions; (2) the ability to easily monitor, assess, and visualize the spatially complex movements of animals, plants, water, and elements across highly variable landscapes; and (3) the techniques for accurately predicting both immediate and long-term responses of system components to natural and human-caused change. The overall objectives of our research are to provide the knowledge, tools, and techniques needed by the U.S. Department of the Interior, state agencies, and other stakeholders in their endeavors to meet the demand for natural resources while conserving biodiversity and ecosystem services. Ecosystem Dynamics scientists use field and laboratory research, data assimilation, and ecological modeling to understand ecosystem patterns, trends, and mechanistic processes. This information is used to predict the outcomes of changes imposed on species, habitats, landscapes, and climate across spatiotemporal scales. The products we develop include conceptual models to illustrate system structure and processes; regional baseline and integrated assessments; predictive spatial and mathematical models; literature syntheses; and frameworks or protocols for improved ecosystem monitoring, adaptive management, and program evaluation. The descriptions in this fact sheet provide snapshots of our three research emphases, followed by descriptions of select current projects.

Fact Sheet↗

Baseline studies in the Elwha River ecosystem prior to dam removal: Introduction to the special issue

The planned removal of two dams that have been in place for over 95 years on the Elwha River provides a unique opportunity to study dam removal effects. Among the largest dams ever considered for removal, this project is compelling because 83% of the watershed lies undisturbed in Olympic National Park. Eighteen million cubic meters of sediment have accumulated in and will be released from the reservoirs, and there is potential for rehabilitating depressed Pacific salmon runs. Researchers from academia, non-profit organizations, federal and state governments, and the Lower Elwha Klallam Tribe are currently assessing baseline ecological conditions of the Elwha River as part of dam removal studies. We introduce dam removal topics, provide a brief history of the dams, and summarize the ecology of the Elwha River basin as an introduction to a special issue devoted to research in the watershed.

Washington↗

USGS global change research

The Earth's global environment--its interrelated climate, land, oceans, fresh water, atmospheric and ecological systems-has changed continually throughout Earth history. Human activities are having ever-increasing effects on these systems. Sustaining our environment as population and demands for resources increase requires a sound understanding of the causes and cycles of natural change and the effects of human activities on the Earth's environmental systems. The U.S. Global Change Research Program was authorized by Congress in 1989 to provide the scientific understanding necessary to develop national and international policies concerning global environmental issues, particularly global climate change. The program addresses questions such as: what factors determine global climate; have humans already begun to change the global climate; will the climate of the future be very different; what will be the effects of climate change; and how much confidence do we have in our predictions? Through understanding, we can improve our capability to predict change, reduce the adverse effects of human activities, and plan strategies for adapting to natural and human-induced environmental change.

Fact Sheet↗

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N ‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N ‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N ‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N ‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

Ecology and Evolution↗

A guide to Bayesian model checking for ecologists

Checking that models adequately represent data is an essential component of applied statistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in their research. The appeal of this modeling paradigm is undeniable, as researchers can build and fit models that embody complex ecological processes while simultaneously accounting for observation error. However, ecologists tend to be less focused on checking model assumptions and assessing potential lack of fit when applying Bayesian methods than when applying more traditional modes of inference such as maximum likelihood. There are also multiple ways of assessing the fit of Bayesian models, each of which has strengths and weaknesses. For instance, Bayesian P values are relatively easy to compute, but are well known to be conservative, producing P values biased toward 0.5. Alternatively, lesser known approaches to model checking, such as prior predictive checks, cross‐validation probability integral transforms, and pivot discrepancy measures may produce more accurate characterizations of goodness‐of‐fit but are not as well known to ecologists. In addition, a suite of visual and targeted diagnostics can be used to examine violations of different model assumptions and lack of fit at different levels of the modeling hierarchy, and to check for residual temporal or spatial autocorrelation. In this review, we synthesize existing literature to guide ecologists through the many available options for Bayesian model checking. We illustrate methods and procedures with several ecological case studies including (1) analysis of simulated spatiotemporal count data, (2) N‐mixture models for estimating abundance of sea otters from an aircraft, and (3) hidden Markov modeling to describe attendance patterns of California sea lion mothers on a rookery. We find that commonly used procedures based on posterior predictive P values detect extreme model inadequacy, but often do not detect more subtle cases of lack of fit. Tests based on cross‐validation and pivot discrepancy measures (including the “sampled predictive P value”) appear to be better suited to model checking and to have better overall statistical performance. We conclude that model checking is necessary to ensure that scientific inference is well founded. As an essential component of scientific discovery, it should accompany most Bayesian analyses presented in the literature.

Ecological Monographs↗

Elk personality and anthropogenic food subsidy: Managing conflict and migration loss

The continued decline of long-distance ungulate migrations threatens to decouple important ecological processes that increase biodiversity and wildlife abundance. Past research has focused on preserving migration paths where habitat fragmentation and loss disrupt movement corridors. However, shifting residency-migration trade-offs are the stronger driver of migration loss in some populations. Suburban residential developments may provide ungulates with anthropogenic food sources and refuge from predators, which can increase population growth among short-distance migrants relative to long-distance migrants. This trend can increase wildlife vehicle collisions and other human–wildlife conflicts while simultaneously reducing hunting opportunities. Yet, individual animals vary in their tolerance of human disturbance. We investigated how interindividual variation relative to conflict and human habituation influences elk migration and space use on shared winter range. We used a clustering algorithm applied to GPS collar data to identify elk use of anthropogenic food resources in suburban habitat. Cluster locations identified all known anthropogenic subsidy locations during the study period. Elk that used suburban anthropogenic food sources also migrated 60% shorter distances between summer and winter ranges than elk with no known use of these food subsidies. Elk use of protected wintering grounds was spatially structured such that conflict-prone, short-distance migrants disproportionately used areas with more human activity. Clustering algorithms applied to GPS collar data may allow managers to identify foci of concentrated use that generates human–wildlife conflict, and where prion deposition and environmental contamination facilitate the spread of chronic wasting disease, particularly in suburban areas with anthropogenic food subsidies. The apparent spatial structuring of shared winter range according to the conflict potential and migration strategy of individual elk may also permit managers to assess relative recruitment among cryptic population segments using different migration strategies and facilitate targeted, adaptive management actions. These associations between conflict, human habituation, and migration shed light on the urbanization of wildlife species, inform efforts to manage human–wildlife conflict and disease spread, and emphasize that a multipronged approach beyond maintaining habitat corridors may be necessary to conserve long-distance migrations for species that can become human-habituated.

Wyoming↗

Factors driving nutrient trends in streams of the Chesapeake Bay watershed

Despite decades of effort toward reducing nitrogen and phosphorus flux to Chesapeake Bay, water-quality and ecological responses in surface waters have been mixed. Recent research, however, provides useful insight into multiple factors complicating the understanding of nutrient trends in bay tributaries, which we review in this paper, as we approach a 2025 total maximum daily load (TMDL) management deadline. Improvements in water quality in many streams are attributable to management actions that reduced point sources and atmospheric nitrogen deposition and to changes in climate. Nutrient reductions expected from management actions, however, have not been fully realized in watershed streams. Nitrogen from urban nonpoint sources has declined, although water-quality responses to urbanization in individual streams vary depending on predevelopment land use. Evolving agriculture, the largest watershed source of nutrients, has likely contributed to local nutrient trends but has not affected substantial changes in flux to the bay. Changing average nitrogen yields from farmland underlain by carbonate rocks, however, may suggest future trends in other areas under similar management, climatic, or other influences, although drivers of these changes remain unclear. Regardless of upstream trends, phosphorus flux to the bay from its largest tributary has increased due to sediment infill in the Conowingo Reservoir. In general, recent research emphasizes the utility of input reductions over attempts to manage nutrient fate and transport at limiting nutrients in surface waters. Ongoing research opportunities include evaluating effects of climate change and conservation practices over time and space and developing tools to disentangle and evaluate multiple influences on regional water quality.

Chesapeake Bay watershed↗

Global Change and the Function and Distribution of Wetlands

The Global Change Ecology and Wetlands book series will highlight the latest research from the world leaders in the field of climate change in wetlands. Global Change and the Function and Distribution of Wetlands highlights information of importance to wetland ecologists. The chapters include syntheses of international studies on the effects of drought on function and regeneration in wetlands, sea level rise and the distribution of mangrove swamps, former distributions of swamp species and future lessons from paleoecology, and shifts in atmospheric emissions across geographical regions in wetlands. Overall, the book will contribute to a better understanding of the potential effects of climate change on world wetland distribution and function.

Book↗

Prioritizing US Geological Survey science on salinization and salinity in candidate and selected priority river basins

The US Geological Survey (USGS) is selecting and prioritizing basins, known as Integrated Water Science basins, for monitoring and intensive study. Previous efforts to aid in this selection process include a scientifically defensible and quantitative assessment of basins facing human-caused water resource challenges (Van Metre et al. in Environmental Monitoring and Assessment , 192(7), 458 2020). In the present work, we explore this ranking process based on water quality considerations, specifically salinity and salinization. We selected top candidate basins to study salinity and salinization issues in 18 hydrologic regions that include 163 candidate basins. Our prioritization is based on quantitative assessment of sources of salinity, drivers of change, and receptors that must respond to those sources and drivers. Source terms represented in the prioritization include geology, depth to brackish groundwater, stream conductivity, chloride in precipitation, urban and agricultural land use, application of road salt as a deicer, and irrigation. Drivers represented in prioritization include changes in chemical weathering as a result of changes in rainwater chemistry. Receptors include measures of water stress, measurements of stream ecological health, and socioeconomic factors. In addition, we present research activities for the USGS on salinity and salinization that can be pursued in these basins including assessment of sources, pathways, and loadings; predicting and understanding changes in sources, peaks, and trends; understanding the components of salinity and mobilization of contaminants; understanding the relationship between salinization and changing ecosystems; and developing knowledge on the causes and distribution of groundwater salinity, brackish water resources, and challenges related to desalination.

Enviornmental Monitoring and Assessment↗

Rivers of the Lower Mississippi Basin

Discussed in this chapter are seven significant tributaries of the Lower Mississippi River and its major distributary. As a group, these eight rivers and their basins encompass substantial variation in physical form, hydrology, biota, ecology, and human impacts. The Current River, Ouachita River, and Saline River, flow to the Mississippi out of the U.S. Interior Highlands. The Cache River basin, centered in Arkansas, contains a vast expanse of bottomland hardwood forest and is famous for wintering waterfowl. The Hatchie River, flowing west out of Tennessee, is the longest free-flowing tributary of the Lower Mississippi River and famous for its rich diversity of mussels and fishes. The Wolf River of Tennessee supports a magnificent bald cypress-tupelo swamp and is notable as a protected urban river that flows through Memphis. The Big Sunflower River begins and ends in the alluvial floodplain of the Mississippi River and flows through a basin of intense agriculture and historical human conflict. The Atchafalaya River, the primary distributary of the Mississippi River, supports the nation's largest expanse of bottomland hardwood forest and swamp wetlands. In this chapter, we review the physiography, geomorphology, hydrology, water chemistry, land use, biological diversity, ecological processes, human impacts, and areas of need for research and management of each of these eight rivers and their basins.

Lower Mississippi River basin↗

Moving from decision to action in conservation science

Biodiversity loss is a major threat to the integrity of ecosystems and is projected to worsen, yet the path to successful conservation remains elusive. Decision support frameworks (DSFs) are increasingly applied by resource managers to navigate the complexity, uncertainty, and differing socio-ecological objectives inherent to conservation problems. Most published conservation research that uses DSFs focuses on analytical stages (e.g., identifying an optimal decision), making it difficult to assess and learn from previous examples in a conservation practice context. Here, we (1) evaluate the relationship between the application of decision science and the resulting conservation outcomes, and (2) identify and address existing barriers to the application of DSFs to conservation practice. To do this, we develop a framework for evaluating conservation initiatives using decision science that emphasizes setting attainable goals, building momentum, and obtaining partner buy-in. We apply this framework to a systematic review of amphibian conservation decision support projects, including a follow-up survey of the pertinent conservation practitioners, stakeholders, and scientists. We found that all projects identified optimal solutions to reach stated objectives, but positive conservation outcomes were limited when implementation challenges arose. Further, we identified multiple barriers (e.g., dynamic and hierarchical leadership, scale complexity, limited resource availability) that can inhibit the progression from decision identification to action implementation (i.e., ‘decision-implementation gap’), and to successful conservation outcomes. Based on these results, we provide potential actionable steps and avenues for future development of DSFs to facilitate the transition from decision to action and the realization of conservation successes.

Biological Conservation↗

Modeling water quality in the Anthropocene: Directions for the next-generation aquatic ecosystem models

“Everything changes and nothing stands still” (Heraclitus). Here we review three major improvements to freshwater aquatic ecosystem models — and ecological models in general — as water quality scenario analysis tools towards a sustainable future. To tackle the rapid and deeply connected dynamics characteristic of the Anthropocene, we argue for the inclusion of eco-evolutionary, novel ecosystem and social-ecological dynamics. These dynamics arise from adaptive responses in organisms and ecosystems to global environmental change and act at different integration levels and different time scales. We provide reasons and means to incorporate each improvement into aquatic ecosystem models. Throughout this study we refer to Lake Victoria as a microcosm of the evolving novel social-ecological systems of the Anthropocene. The Lake Victoria case clearly shows how interlinked eco-evolutionary, novel ecosystem and social-ecological dynamics are, and demonstrates the need for transdisciplinary research approaches towards global sustainability.

Current Opinion in Environmental Sustainability↗

A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices

Wildlife conservation planning increasingly requires collaboration and integration of research from discrete studies spanning large geographic areas. Tracking datasets are essential for analyzing animal movements and species distributions in relation to environmental conditions and combining them can enable powerful analyses to further aid planning efforts. However, combining datasets necessitates addressing variation in study designs, tracking methodologies, location uncertainty, and data attributes. We outline a compilation pipeline to integrate ground-based and satellite-based telemetry tracking datasets, motivated from our work with greater sage-grouse ( Centrocercus urophasianus ), a highly imperiled species of western North America. Our objective was to create a database with a standardized set of attributes to facilitate filtering locations for spatial analyses. Our pipeline phases are: (1) dataset pre-processing, (2) formatting individual datasets to a common template, (3) dataset binding, (4) error checking, and (5) filtering. Our pipeline includes additional functionality to identify coordinates from recurrently visited locations (e.g., nest sites), which may be of special interest. The final compiled sage-grouse database included nearly 5 million locations collected from 53 datasets and over 19,000 birds tracked from 1980 to 2022, including over 11,000 nest locations. Our error checks flagged 3.9 % of locations as likely errors, predominantly collected from satellite-based telemetry transmissions. We demonstrate the ability of our pipeline to identify nest locations and flag erroneous locations by applying it to simulated tracking datasets. Overall, our workflow offers a transferable approach for researchers aiming to standardize wildlife telemetry datasets and conduct ecological analyses for both individual studies and large-scale collaborations.

California, Colorado, Idaho, Montana, Nevada, Nort↗

Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China

Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.

Dongjiang↗