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USGS2023

Improving ecological data science with workflow management software

Pressing environmental research questions demand the integration of increasingly diverse and large-scale ecological datasets as well as complex analytical methods, which require specialized tools and resources. Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor- and time-intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies. Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with the targets r package to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers. Although WMS requires familiarity with function-oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales.

Methods in Ecology and Evolution↗

USGS2020

Hillslope groundwater discharges provide localized ecosystem buffers from regional PFAS contamination in a gaining coastal stream

Emerging groundwater contaminants such as per- and polyfluoroalkyl substances (PFAS) may impact surface-water quality and groundwater-dependent ecosystems of gaining streams. Although complex near-surface hydrogeology of stream corridors challenges sampling efforts, recent advances in heat tracing of discharge zones enable efficient and informed data collection. For this study we used a combination of streambed temperature push-probe and thermal infrared methods to guide a discharge-zone-oriented sample collection along approximately 6 km of a coastal trout stream on Cape Cod, MA where groundwater discharge constitutes approximately 95% of total streamflow. Eight surface-water locations and discharging groundwater from 24 streambed and bank seepages were analyzed for dissolved oxygen, specific conductance, stable water isotopes, and a range of PFAS compounds which are contaminants of emerging concern in aquatic environments. The results indicate a complex system of groundwater discharge source flowpaths, where the sum of concentrations of six PFAS compounds (Environmental Protection Agency third Unregulated Contaminant Monitoring Rule UCMR 3) showed a median concentration of 52 331 (SD) ng/L with two higher outliers and three discharges with non-detection of PFAS. Higher UCMR 3 PFAS concentration was related -0.66 (Spearman Rank, p<0.001) to discharging groundwater that showed an evaporative signature (deuterium excess), indicating flow through at least one upgradient kettle lake. Therefore, more regional groundwater flowpaths originating from outside the local river corridor tended to show higher PFAS concentrations as evaluated at their respective discharge zones. Conversely, UCMR 3 PFAS concentrations were typically low at discharges that did not indicate evaporation and were adjacent to steep hillslopes and, therefore, were classified as locally recharged groundwater. Previous research at this stream found that the native brook trout favor discharge points of groundwater recharged on local hillslopes for spawning, likely in response to generally higher levels of dissolved oxygen compared to discharge zones located further away from hillslopes. Our study shows that the trout may thereby be avoiding emerging contaminants such as PFAS in groundwater recharged farther from the stream.

Massachusetts↗

USGS2019

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗

USGS2023

Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20

Loss and degradation of sagebrush ( Artemisia spp.) rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western U.S. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (hereinafter, “Needs”) for informing the actions proposed under the five topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse ( Centrocercus urophasianus ), Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed four Needs identified under the Climate and Weather topic in the Plan. The topic outlined research Needs broadly focused on understanding the potential effects of climate change on vegetative resilience to inform restoration of sagebrush rangelands. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (hereinafter, “Next Steps”) were either addressed well, partially addressed or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 92 science products that at least partially addressed a Need identified in the Climate and Weather topic. The Needs that were well and partially addressed included: studies of the complex set of climatic relationships that influence sagebrush rangeland restoration and seeding success; the identification of seed collection areas across the range of environmental variability inhabited by target restoration species; and develop predictive models to assess targeted restoration species’ responses to mid-century climatic conditions. The Need addressed poorly was the identification of native plant species, genotypes and ecotypes, and seed mixes that may be resilient to a changing climate. The information provided in this assessment will assist updating the Plan, and can inform updates of other relevant science planning documents as needed.

Open-File Report↗

USGS2009

Broadening our approaches to studying dispersal in raptors

Dispersal is a behavioral process having consequences for individual fitness and population dynamics. Recent advances in technology have spawned new theoretical examinations and empirical studies of the dispersal process in birds, providing opportunities for examining how this information may be applied to studies of the dispersal process in raptors. Many raptors are the focus of conservation efforts; thus, reliable data on all aspects of a species' population dynamics, including dispersal distances, movement rates, and mortality rates of dispersers, are required for population viability analyses that are increasingly used to inform management. Here, we address emerging issues and novel approaches used in the study of avian dispersal, and provide suggestions to consider when developing and implementing studies of dispersal in raptors. Clarifying study objectives is essential for selection of an appropriate methodology and sample size needed to obtain accurate estimates of movement distances and rates. Identifying an appropriate study-area size will allow investigators to avoid underestimating population connectivity and important population parameters. Because nomadic individuals of some species use temporary settling areas or home ranges before breeding, identification of these areas is critical for conservation efforts focusing on habitats other than breeding sites. Study designs for investigating raptor dispersal also should include analysis of environmental and social factors influencing dispersal, to improve our understanding of condition-dependent dispersal strategies. Finally, we propose a terminology for use in describing the variety of movements associated with dispersal behavior in raptors, and we suggest this terminology could be used consistently to facilitate comparisons among studies. ?? 2009 The Raptor Research Foundation, Inc.

Journal of Raptor Research↗

USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗

USGS2018

Climate Assessments and Scenario Planning (CLASP)

The NE CASC boasts an interdisciplinary array of scientists, from ecologists to biologists, hydrologists to climatologists, each contributing new, original academic research to advance our understanding of the impacts of climate change on wildlife and other natural resources in the Northeast. Needed was an outreach specialist who would interface directly with the management agencies who benefited from this research to aid the integration of this research into their management planning as part of adapting to climate change. A climatologist was preferred to address queries about climate modeling, climate change uncertainties, and other areas of climate science outside the expertise of NE CASC ecologists, biologists, and hydrologists. This person’s activities would include responding to inquiries, presenting climate science concepts at management workshops, gathering managers’ climate science needs, contributing to the climate portion of synthesis reports and other resources for managers, and collaborating with ecologists on interdisciplinary studies of climate change by providing climate data and guidance on interpretation. The objective was to relay and interpret the scientific findings most relevant to managers’ resources of concern and management activities around those resources to guide adjustments to their activities toward better protecting their resources of concern. As an outcome, managers often relied on synthesized climate science to be able to consider how climate trends affect their work, especially those thinking about climate change for the first time in the context of their work. This lays the groundwork for more detailed management-driven science delivery that can aid eventual implementation. Management groups reached by this project include land managers with the National Park Service, state fish and game departments and DNRs, and tribal environmental coordinators.

Report↗

USGS2014

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Ecography↗

USGS2013

Bactericidal efficacy of elevated pH on fish pathogenic and environmental bacteria

Ship ballast water is a recognized medium for transfer and introductions of nonindigenous species. There is a need for new ballast water treatment methods that effectively and safely eliminate or greatly minimize movements of these species. The present study employed laboratory methods to evaluate the bactericidal efficacy of increased pH (pH 10.0–12.0) for exposure durations of up to 72 h to kill a variety of Gram-negative and Gram-positive bacteria including fish pathogens (Aeromonas spp., Yersinia ruckeri, Edwardsiella ictaluri, Serratia liquefaciens, Carnobacterium sp.), other common aquatic-inhabitant bacteria (Serratia marcescens, Pseudomonas fluorescens, Staphylococcus sp., Bacillus sp.) and indicators listed in International Maritime Organization D2 Standards; namely, Vibrio cholera (an environmental isolate from fish), Escherichia coli and Enterococcus faecalis. Volumes of 5 N NaOH were added to tryptic soy broth to obtain desired pH adjustments. Viable cells were determined after 0, 4, 12, 24, 48, and 72 h. Initial (0 h) cell numbers ranged from 3.40 × 10 4 cfu/mL for Bacillus sp. to 2.44 × 10 7 cfu/mL for E. faecalis. The effective endpoints of pH and treatment duration necessary to realize 100% bactericidal effect varied; however, all bacteria tested were killed within 72 h at pH 12.0 or lower. The lowest parameters examined, 4 h at pH 10.0, were bactericidal to V. cholera, E. ictaluri, three of four isolates of E. coli, and (three of four) Aeromonas salmonicida subsp. salmonicida. Bactericidal effect was attained at pH 10.0 within 12 h for the other A. salmonicida subsp. salmonicida, and within 24 h for P. fluorescens, and the remaining E. coli.

Journal of Advanced Research↗

USGS2022

Resisting-accepting-directing: Ecosystem management guided by an ecological resilience assessment

As anthropogenic influences push ecosystems past tipping points and into new regimes, complex management decisions are complicated by rapid ecosystem changes that may be difficult to reverse. For managers who grapple with how to manage ecosystems under novel conditions and heightened uncertainty, advancing our understanding of regime shifts is paramount. As part of an ecological resilience assessment, researchers and managers have collaborated to identify alternate regimes and build an understanding of the thresholds and factors that govern regime shifts in the Upper Mississippi River System. To describe the management implications of our assessment, we integrate our findings with a recently developed framework that explicitly acknowledges ecosystem regime change and outlines management approaches of resisting change, accepting change, or directing change. More specifically, we developed guidance for using knowledge of desirability of current conditions, distance to thresholds, and general resilience (that is, an ecosystem’s capacity to cope with uncertain disturbances) to navigate the resist-accept-direct (RAD) framework. We applied this guidance to outline strategies that resist, accept, or direct change in the context of management of aquatic vegetation, floodplain vegetation, and fish communities across nearly 2000 river kilometers. We provide a case study for how knowledge of ecological dynamics can aid in assessing which management approach(es) are likely to be most ecologically feasible in a changing world. Continued learning from management decisions will be critical to advance our understanding of how ecosystems respond and inform the management of ecosystems for desirable and resilient outcomes.

Illinois, Iowa, Kentucky, Minnesota, Missouri, Wis↗

USGS2012

Guidelines for a graph-theoretic implementation of structural equation modeling

Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for an updated definition of the SEM process that subsumes the historical matrix approach under a graph-theory implementation. The implementation is also designed to permit complex specifications and to be compatible with various estimation methods. Finally, they are meant to foster the use of probabilistic reasoning in both retrospective and prospective considerations of the quantitative implications of the results.

Ecosphere↗

USGS2016

Assessing the socioeconomic impact and value of open geospatial information

The production and accessibility of geospatial information including Earth observation is changing greatly both technically and in terms of human participation. Advances in technology have changed the way that geospatial data are produced and accessed, resulting in more efficient processes and greater accessibility than ever before. Improved technology has also created opportunities for increased participation in the gathering and interpretation of data through crowdsourcing and citizen science efforts. Increased accessibility has resulted in greater participation in the use of data as prices for Government-produced data have fallen and barriers to access have been reduced. The increase in participation in the production and in the use of data, defined as data democracy for this workshop, are having great impacts on economics and more generally on society. There is also a strong drive by governments around the world, as shown by the G8 Declaration in June 2013, to make public sector information and scientific data more widely accessible. These are respectively termed “open data” and “open research data.” This report summarizes discussion at the Workshop on Assessing the Impact and Value of Open Geospatial Information held at George Washington University in Washington, D.C. in October 2014. Workshop participants examined the consequences of expanding data democracy with a focus on its socioeconomic impacts. Evaluations were presented of state-of-the-art methods to assess these socioeconomic impacts, which included position papers and remarks by discussants. The workshop included discussions about the following topics: (1) increased and expanded information sources; (2) societal impacts, including approaches to economics assessments; (3) constraints to open access, including the demands for return on investment, specifications of intellectual property rights, and privacy issues; and (4) learning from the experiences of other data-rich domains, such as environmental management, internet businesses, health, and transportation. The workshop was a working meeting with strong participant engagement, leading to recommendations for action. The meeting included five topic-driven sessions and keynote presentations. Precirculated position papers for each panel session facilitated preparation and remarks by discussants. After the position papers are updated following the discussants’ remarks, it is planned to submit them for publication. The workshop included 68 participants coming from international organizations, the U.S. public and private sectors, nongovernmental organizations, and academia. Participants included policy makers and analysts, financial analysts, economists, information scientists, geospatial practitioners, and other discipline experts.

Open-File Report↗

USGS2019

Incorporating uncertainty and risk into decision making to reduce nitrogen inputs to impaired waters

This article aims to understand decision making under uncertainty and risk, with a case study on Cape Cod, Massachusetts. Decision makers need to consider imperfect information on the cost and effectiveness of advanced nitrogen-removing on-site wastewater treatment systems as options to mitigate water quality degradation. Research included modeling nitrogen load reduction to impaired coastal waters from seven treatment system technologies and eliciting expert knowledge on their costs. Predictions of nitrogen load removal and cost for each technology incorporated variation in effectiveness and uncertainty in household water use, costs, and expert confidence in costs. The predictions were evaluated using the Pareto efficiency concept to reveal tradeoffs between cost and effectiveness. The stochastic dominance index was used to identify preferred technologies for risk-averse decision making, assuming no further learning is possible. Lastly, the predictions were combined into a cost-effectiveness metric to estimate the expected payoff of implementing the best treatment system in the face of uncertainty and the expected payoff of learning which treatment systems are most cost-effective over time. The expected value of perfect information was calculated as the difference between the expected payoffs. Three technologies revealed Pareto efficient tradeoffs between cost and effectiveness, whereas one technology was the preferred risk-averse option in the absence of future learning. There was a high expected value of perfect information, which could motivate adaptive management on Cape Cod. This research demonstrated decision analysis methods to guide future research and decision making toward meeting water quality objectives and reducing uncertainty.

Massachusetts↗

USGS2017

The blind men meet the elephant at the dam: Alternative spatial and taxonomic components reveal different insights about how low-head dams impact fish biodiversity

Dams are ubiquitous environmental impacts that threaten aquatic ecosystems. The ability to compare across research studies is essential to conserve the native biodiversity that is impacted by the millions of low‐head dams that currently fragment streams and rivers. Here, we identify a previously unaddressed obstacle that impedes this generalization. Specifically, divergent spatial and taxonomic approaches that result from different conceptualizations of the dam‐biodiversity problem can produce conflicting science‐based conclusions about the same dam impact. In this research, using the same dammed and undammed sites, we evaluated the scientific generality of different conceptualizations of the dam‐biodiversity problem. We compared two different but commonly used spatial approaches—(1) above dam–below dam vs. (2) undammed–dammed comparisons—and 11 different, commonly used taxonomic approaches (three assemblage summaries, eight guilds). Sites above the dam structure had less diverse fish assemblages than sites below dams, whereas sites below the dam structure were similar to undammed sites. Thus, spatial approach 1 detected a large dam effect and spatial approach 2 detected a small dam effect. Similarly, some taxonomic responses (species richness, diversity, abundance, and number of guilds) detected large dam effects; other responses detected small (riffle specialist guild) or no dam effects (pool generalists). In summary, our results showed that how the problem was framed altered scientific conclusions and created different dam realities. The metaphor of how individual blind men disagree about the structure of an elephant, based on examinations of different body parts, reinforces the need for a coordinated, holistic perspective on dam research. Although no single approach is adequate for all problems, identifying the form, consequences of, and relationships among different research conceptualizations will set the stage for future syntheses of dam‐biodiversity research to advance science‐based conservation.

Ecosphere↗

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↗

USGS2015

Predicting the resilience and recovery of aquatic systems: a framework for model evolution within environmental observatories

Maintaining the health of aquatic systems is an essential component of sustainable catchmentmanagement, however, degradation of water quality and aquatic habitat continues to challenge scientistsand policy-makers. To support management and restoration efforts aquatic system models are requiredthat are able to capture the often complex trajectories that these systems display in response to multiplestressors. This paper explores the abilities and limitations of current model approaches in meeting this chal-lenge, and outlines a strategy based on integration of ﬂexible model libraries and data from observationnetworks, within a learning framework, as a means to improve the accuracy and scope of model predictions.The framework is comprised of a data assimilation component that utilizes diverse data streams from sensornetworks, and a second component whereby model structural evolution can occur once the model isassessed against theoretically relevant metrics of system function. Given the scale and transdisciplinarynature of the prediction challenge, network science initiatives are identiﬁed as a means to develop and inte-grate diverse model libraries and workﬂows, and to obtain consensus on diagnostic approaches to modelassessment that can guide model adaptation. We outline how such a framework can help us explore thetheory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry,and, in doing so, also advance the role of prediction in aquatic ecosystem management.

Water Resources Research↗

USGS2020

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.

Open-File Report↗

USGS2006

Integration of coral reef ecosystem process studies and remote sensing

Worldwide, local-scale anthropogenic stress combined with global climate change is driving shifts in the state of reef benthic communities from coral-rich to micro- or macroalgal-dominated (Knowlton, 1992; Done, 1999). Such phase shifts in reef benthic communities may be either abrupt or gradual, and case studies from diverse ocean basins demonstrate that recovery, while uncertain (Hughes, 1994), typically involves progression through successional stages (Done, 1992). These transitions in benthic community structure involve changes in community metabolism, and accordingly, the holistic evaluation of associated biogeochemical variables is of great intrinsic value (Done, 1992). Effective reef management requires advance prediction of coral reef alteration in the face of anthropogenic stress and change in the global environment (Hatcher, 1997a). In practice, this goal requires techniques that can rapidly discern, at an early stage, sublethal effects that may cause long-term increases in mortality (brown, 1988; Grigg and Dollar, 1990). Such methods would improve our understanding of the differences in the population, community, and ecosystem structure, as well as function, between pristine and degraded reefs. This knowledge base could then support scientifically based management strategies (Done, 1992). Brown (1988) noted the general lack of rigor in the assessment of stress on coral reefs and suggested that more quantitative approaches than currently exist are needed to allow objective understanding of coral reef dynamics. Sensitive techniques for the timely appraisal of pollution effects or generalized endemic stress in coral reefs are sorely lacking (Grigg and Dollar, 1990; Wilkinsin, 1992). Moreover, monitoring methods based on population inventories, sclerochronology, or reproductive biology tend to myopic and may give inconsistent results. Ideally, an improved means of evaluating reef stress would discriminate mortality due to natural causes from morality to anthropogenic causes (Brown, 1988). Models of coral reef ecosystems, parameterized by process measurements and scaled in time-space using remote sensing, have the potential to address pressing research questions that are central to devising valid management strategies (Grigg el al., 1984; Hatcher, 1997b). To attain this goal, ecosystem-level models that integrate studies of physical and chemical forcing with observed biological and geological responses are required. This interdisciplinary approach to understanding reef biogeochemical dynamics can allow investigations that integrate the scales of time and space (Hatcher, 1997a), thereby enabling prediction of coral reef change (Andréfouët and Payri, 2001). In turn, prediction of holistic ecosystem function within various environmental focusing scenarios has substantial promise in mitigating future disturbance. Indeed, management of coral reefs at the ecosystem level has been suggested as the only meaningful approach to preserving coral reefs (Bohnsack and Ault, 1996; Christensen et al., 1996).

Florida↗