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At least 73 records · Page 4Linked to original sources
USGS2003

Foraminifera as bioindicators in coral reef assessment and monitoring: The foram index

Coral reef communities are threatened worldwide. Resource managers urgently need indicators of the biological condition of reef environments that can relate data acquired through remote-sensing, water-quality and benthic-community monitoring to stress responses in reef organisms. The "FORAM" (Foraminifera in Reef Assessment and Monitoring) Index (FI) is based on 30 years of research on reef sediments and reef-dwelling larger foraminifers. These shelled protists are ideal indicator organisms because: ??? Foraminifers are widely used as environmental and paleoenvironmental indicators in many contexts; ??? Reef-building, zooxanthellate corals and foraminifers with algal symbionts have similar water-quality requirements; ??? The relatively short life spans of foraminifers as compared with long-lived colonial corals facilitate differentiation between long-term water-quality decline and episodic stress events; ??? Foraminifers are relatively small and abundant, permitting statistically significant sample sizes to be collected quickly and relatively inexpensively, ideally as a component of comprehensive monitoring programs; and ??? Collection of foraminifers has minimal impact on reef resources. USEPA guidelines for ecological indicators are used to evaluate the FI. Data required are foraminiferal assemblages from surface sediments of reef-associated environments. The FI provides resource managers with a simple procedure for determining the suitability of benthic environments for communities dominated by algal symbiotic organisms. The FI can be applied independently, or incorporated into existing or planned monitoring efforts. The simple calculations require limited computer capabilities and therefore can be applied readily to reef-associated environments worldwide. In addition, the foraminiferal shells collected can be subjected to morphometric and geochemical analyses in areas of suspected heavy-metal pollution, and the data sets for the index can be used with other monitoring data in detailed multidimensional assessments.

Environmental Monitoring and Assessment↗
USGS2010

Linking microbial and ecosystem ecology using ecological stoichiometry: a synthesis of conceptual and empirical approaches

Currently, one of the biggest challenges in microbial and ecosystem ecology is to develop conceptual models that organize the growing body of information on environmental microbiology into a clear mechanistic framework with a direct link to ecosystem processes. Doing so will enable development of testable hypotheses to better direct future research and increase understanding of key constraints on biogeochemical networks. Although the understanding of phenotypic and genotypic diversity of microorganisms in the environment is rapidly accumulating, how controls on microbial physiology ultimately affect biogeochemical fluxes remains poorly understood. We propose that insight into constraints on biogeochemical cycles can be achieved by a more rigorous evaluation of microbial community biomass composition within the context of ecological stoichiometry. Multiple recent studies have pointed to microbial biomass stoichiometry as an important determinant of when microorganisms retain or recycle mineral nutrients. We identify the relevant cellular components that most likely drive changes in microbial biomass stoichiometry by defining a conceptual model rooted in ecological stoichiometry. More importantly, we show how X-ray microanalysis (XRMA), nanoscale secondary ion mass spectroscopy (NanoSIMS), Raman microspectroscopy, and in situ hybridization techniques (for example, FISH) can be applied in concert to allow for direct empirical evaluation of the proposed conceptual framework. This approach links an important piece of the ecological literature, ecological stoichiometry, with the molecular front of the microbial revolution, in an attempt to provide new insight into how microbial physiology could constrain ecosystem processes.

Ecosystems↗
USGS2009

Selected achievements, science directions, and new opportunities for the WEBB small watershed research program

Over nearly two decades, the Water, Energy, and Biogeochemical Budgets (WEBB) small watershed research program of the U.S. Geological Survey (USGS) has documented how water and solute fluxes, nutrient, carbon, and mercury dynamics, and weathering and sediment transport respond to natural and humancaused drivers, including climate, climate change, and atmospheric deposition. Together with a continued and increasing focus on the effects of climate change, more investigations are needed that examine ecological effects (e.g., evapotranspiration, nutrient uptake) and responses (e.g., species abundances, biodiversity) that are coupled with the physical and chemical processes historically observed in the WEBB program. Greater use of remote sensing, geographic modeling, and habitat/watershed modeling tools is needed, as is closer integration with the USGS-led National Phenology Network. Better understanding of process and system response times is needed. The analysis and observation of land-use and climate change effects over time should be improved by pooling data obtained by the WEBB program during the last two decades with data obtained earlier and (or) concurrently from other research and monitoring studies conducted at or near the five WEBB watershed sites. These data can be supplemented with historical and paleo-environmental information, such as could be obtained from tree rings and lake cores. Because of the relatively pristine nature and small size of its watersheds, the WEBB program could provide process understanding and basic data to better characterize and quantify ecosystem services and to develop and apply indicators of ecosystem health. In collaboration with other Federal and State watershed research programs, the WEBB program has an opportunity to contribute to tracking the short-term dynamics and long-term evolution of ecosystem services and health indicators at a multiplicity of scales across the landscape.

Conference Paper↗
USGS2023

Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations

Scientific experts from different disciplines often struggle to mesh their specialized perspectives into the shared mindset that is needed to address difficult and persistent environmental, ecological, and societal problems. Many traditional graduate programs provide excellent research and technical skill training. However, these programs often do not teach a systematic way to learn team skills, nor do they offer a protocol for identifying and tackling increasingly integrated interdisciplinary (among disciplines) and transdisciplinary (among researchers and stakeholders) questions. As a result, professionals trained in traditional graduate programs (e.g., current graduate students and employed practitioners) may not have all of the collaborative skills needed to advance solutions to difficult scientific problems. In the present article, we illustrate a tractable, widely implementable structured process called RISE that accelerates the development of these missing skills. The RISE process (Route to Identifying, learning, and practicing interdisciplinary and transdisciplinary team Skills to address difficult Environmental problems) can be used by diverse teams as a tool for research, professional interactions, or training. RISE helps professionals with different expertise learn from each other by repeatedly asking team-developed questions that are tested using an interactive quantitative tool (e.g., agent-based models, machine learning, case studies) applied to a shared problem framework and data set. Outputs from the quantitative tool are then discussed and interpreted as a team, considering all team members’ perspectives, disciplines, and expertise. After this synthesis, RISE is repeated with new questions that the team jointly identified in earlier data interpretation discussions. As a result, individual perspectives, originally informed by disciplinary training, are complemented by a shared understanding of team function and elevated interdisciplinary knowledge.

BioScience↗
USGS2014

Strategic conservation planning for the Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team

The Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team (ENCSEVA) is a partnership among local federal agencies and programs with a mission to apply Strategic Habitat Conservation to accomplish priority landscape-level conservation within its geographic region. ENCSEVA seeks to further landscape-scale conservation through collaboration with local partners. To accomplish this mission, ENCSEVA is developing a comprehensive Strategic Habitat Conservation Plan (Plan) to provide guidance for its members, partners, and collaborators by establishing mutual conservation goals, objectives, strategies, and metrics to gauge the success of conservation efforts. Identifying common goals allows the ENCSEVA team to develop strategies that leverage joint resources and are more likely to achieve desired impacts across the landscape. The Plan will also provide an approach for ENCSEVA to meet applied research needs (identify knowledge gaps), foster adaptive management principles, identify conservation priorities, prioritize threats (including potential impacts of climate change), and identify the required capacity to implement strategies to create more resilient landscapes. ENCSEVA seeks to support the overarching goals of the South Atlantic Landscape Conservation Cooperative (SALCC) and to provide scientific and technical support for conservation at landscape scales as well as inform the management of natural resources in response to shifts in climate, habitat fragmentation and loss, and other landscape-level challenges (South Atlantic LCC 2012). The ENCSEVA ecoregion encompasses the northern third of the SALCC geography and offers a unique opportunity to apply landscape conservation at multiple scales through the guidance of local conservation and natural resource management efforts and by reporting metrics that reflect the effectiveness of those efforts (Figure 1). The Environmental Decision Analysis Team, housed within the North Carolina Cooperative Fish and Wildlife Research Unit at North Carolina State University, is assisting the ENCSEVA team in developing a scientifically sound basis for the Plan though the elicitation of expert knowledge and the organization of that knowledge using the Open Standards for the Practice of Conservation. The Open Standards for the Practice of Conservation is a framework that is well suited to incorporating decision-making tools such as Structured Decision Making and provides a multi-step process to conceptually organize conservation projects in a manner that enhances the rigor and transparency of expert and knowledge-based plans. It helps define explicit pathways from 2 planned conservation activities and ultimate impact, as well as indicators to measure success (Stem et al. 2005). Specifically, the framework identifies conservation targets, key ecological attributes, threats, and associated indicators to monitor responses given the implementation of a conservation action (Conservation Measures Partnership 2007). This report serves to provide a scientific foundation for the Plan by summarizing the expert opinion of wildlife biologists, ecologists, hydrologists, researchers, natural resource managers, and conservation practitioners regarding five environments (wetlands, riverine systems, estuaries, uplands, and barrier islands) within the ENCSEVA geography. Specifically, this report describes (1) the approach to elicit expert knowledge meant to support the strategic plan, (2) how this knowledge can inform collaborative conservation planning, and (3) a summary of opportunities available for the ENCSEVA team to address threats and impacts associated with climate change within the ecoregion.

Technical Bulletin↗
USGS2020

Determinants and consequences of dispersal in vertebrates with complex life cycles: a review of pond-breeding amphibians

Dispersal is a central process in ecology and evolution. It strongly influences the dynamics of spatially structured populations, by affecting population growth rate and local colonization-extinction processes. Dispersal can also influence evolutionary processes because it determines rates and patterns of gene flow in spatially structured populations and is closely linked to local adaptation. For these reasons, dispersal has received considerable attention from ecologists and evolutionary biologists. However, although it has been studied extensively in taxa such as birds and mammals, much less is known about dispersal in vertebrates with complex life cycles such as pond-breeding amphibians. Over the past two decades, researchers have taken an interest in amphibian dispersal and initiated both fundamental and applied studies, using a broad range of experimental and observational approaches. This body of research reveals complex dispersal patterns, causations and syndromes, with dramatic consequences for the demography and genetics of amphibian populations. In this review, our goals are to (1) redefine and clarify the concept of amphibian dispersal, (2) review current knowledge about the effects of individual (i.e., condition-dependent dispersal) and environmental (i.e., context-dependent dispersal) factors during the three stages of dispersal (i.e., emigration, immigration, transience), (3) identify the demographic and genetic consequences of dispersal in spatially structured amphibian populations, and (4) propose new research avenues to extend our understanding of amphibian dispersal. In particular, we emphasize the need to (1) quantify dispersal rate and distance rigorously using suitable model systems, (2) investigate the genetic basis and dispersal evolution patterns, and (3) examine dispersal-related eco-evolutionary dynamics. These proposed research avenues tap from the recent advances in quantitative and molecular methods and have the potential to improve our understanding of dispersal in organisms with complex life cycles.

The Quarterly Review of Biology↗
USGS2017

Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail ( Bellamya chinensis ) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B . chinensis , 2) how B . chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Journal of Environmental Management↗
USGS1985

Environmental systems and management activities on the Kennedy Space Center, Merritt Island, Florida: results of a modeling workshop

In the early 1960's, the National Aeronautics and Space Administration (NASA) began purchasing 140,000 acres on Merritt Island, Florida, in order to develop a center for space exploration. Most of this land was acquired to provide a safety and security buffer around NASA facilities. NASA, as the managing agency for the Kennedy Space Center (KSC), is responsible for preventing or controlling environmental pollution from the Federal facilities and activities at the Space Center and is committed to use all practicable means to protect and enhance the quality of the surrounding environment. The Merritt Island National Wildlife Refuge was established in 1963 when management authority for undeveloped lands at KSC was transferred to the U.S. Fish and Wildlife Service. In addition to manage for 11 Federally-listed threatened and endangered species and other resident and migratory fish and wildlife populations, the Refuge has comanagement responsibility for 19,000 acres of mosquito control impoundments and 2,500 acres of citrus groves. The Canaveral National Seashore was developed in 1975 when management of a portion of the coastal lands was transferred from NASA to the National Park Service. This multiagency jurisdiction on Merritt Island has resulted in a complex management environment. The modeling workshop described in this report was conducted May 21-25, 1984, at the Kennedy Space Center to: (1) enhance communication among the agencies with management responsibilities on Merritt Island; (2) integrate available information concerning the development, management, and ecology of Merritt Island; and (3) identify key research and monitoring needs associated with the management and use of the island's resources. The workshop was structured around the formulation of a model that would simulate primary management and use activities on Merritt Island and their effects on upland, impoundment, and estuarine vegetation and associated wildlife. The simulation model is composed of four connected submodels. The Uplands submodel calculates changes in acres and structural components of vegetation communities resulting from succession, fire, facilities development, and shuttle launch depositions, as well as the quantity and quality of surface runoff and aquifer input to an impoundment and an estuary. The Impoundment submodel next determines water quality and quantity and changes in vegetation resulting from water level manipulation and prescribed burning. The Estuary submodel than determines water quality parameters and acres of seagrass beds. Finally, the Wildlife submodel calculates habitat suitability indices for key species of interest, based on vegetation conditions in the uplands and impoundments and on several hydrologic parameters. The model represents a hypothetical management unit with 2,500 acres of uplands, a 600-acre impoundment, and a 1,500-acre section of estuary. Two management scenarios were run to analyze model behavior. The scenarios differ in the frequency of shuttle launches and prescribed burning, the extent of facilities development, the amount of land disposed waste material applied, and the nature and timing of impoundment water level control. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. Open communication occurs among the Federal, State, and local agencies involved with activities on Merritt Island and the agencies have a cooperative working relationship. The workshop provided an opportunity for all of these agencies to meet at one time and have focused discussions on the key environmental and multiagency resource management issues. The workshop framework helped to integrate information and assumptions from a number of disciplines and agencies. This integration occurred in the computer simulation model and among workshop participants as submodel linkages were developed and scenario results discussed. A number of research needs were identified at the workshop during the model building and testing exercises and associated discussions. These needs were based on the informed judgement of researchers and managers familiar with Merritt Island or similar areas, rather than on a comprehensive literature review of sensitivity analysis of the preliminary model developed at the workshop. Some of the needs can be addressed by interpreting the results of completed studies from similar geographic areas as they relate to Merritt Island, while other will require additional research studies on Merritt Island. Major research needs associated with the Upland submodel include behavior of the near-surface aquifer, factors limiting slash pine regeneration, frequency and effects of natural fire on various cover types, cumulative effects of shuttle launches, and fate in upland soils of nitrogen and phosphorous from land applied waste material. Key Impoundment submodel needs include documentation of vegetation changes in response to altered water depth, salinity, and nutrient concentrations and better specification of the functional characteristics of impoundments as chemical filters. Important information gaps identified in the Estuary submodel include a more complete analysis of factors contributing to phytoplankton abundance, evaluation of sources of turbidity other than phytoplankton, and identification and quantification of factors limiting seagrass distribution. Primary research needs associated with the Wildlife submodel include a survey of breeding habitat, production data, and harvest data for mottled ducks; data on the emigration and immigration of juvenile mullet (and other transient fish) in the impoundment; the contribution of various seagrasses to habitat requirements of sea trout; and the effects of dissolved oxygen on survival of juvenile sea trout. Ideally, the modeling workshop process is iterative in nature. Periods between workshops are used for research, data collection, and model refinement. Each workshop integrates information collected since the last workshop and produces a more credible model that is more useful in evaluating management alternatives. Participants felt that continued application of this process would help provide ongoing integration and communication among agencies and would allow each agency's planning and management activities to be viewed within the context of an overall assessment.

Report↗
USGS2019

Assessing rangeland health under climate variability and change

RANGELAND HEALTH IN A CHANGING WORLD Rangeland health is an integrated metric that describes a complex suite of ecosystem properties and processes as applied to resource management. While the concept of “healthy” landscapes has a long history, the term “rangeland health” was codified in the US in 1994 as part of an effort to move towards a national, data driven, rangeland condition assessment (National Research Council 1994). Rangeland health encompasses the status of both soils and ecological processes as well as the condition of those ecosystems relative to ecological thresholds (e.g. “healthy”, “at-risk”, or “unhealthy"; National Research Council 1994). This latter application ensures that rangeland health assessments not only evaluate the conditions of plants and soils, but also gauge those conditions with respect to known or hypothesized ecological dynamics (Bestelmeyer et al. 2013) for a given set of abiotic constraints (climate, soil, and topographic setting). Thus, an assessment of rangeland health should identify the “degree to which the integrity of the soil and the ecological processes are sustained” (National Research Council 1994, Us Department of Agriculture 1997). Rangeland health attributes and assessment procedures have become widely utilized tools for measuring and monitoring dryland ecosystems, and they may provide valuable perspectives on rangeland response to climate change, although long-term directional change in environmental conditions represents a challenge for traditional rangeland health assessment frameworks.

Book chapter↗
USGS2017

Occurrence of dichloroacetamide herbicide safeners and co-applied herbicides in midwestern U.S. streams

Dichloroacetamide safeners (e.g., AD-67, benoxacor, dichlormid, and furilazole) are co-applied with chloroacetanilide herbicides to protect crops from herbicide toxicity. While such safeners have been used since the early 1970s, there are minimal data about safener usage, occurrence in streams, or potential ecological effects. This study focused on one of these research gaps, occurrence in streams. Seven Midwestern U.S. streams (five in Iowa and two in Illinois), with extensive row-crop agriculture, were sampled at varying frequencies from spring 2016 through summer 2017. All four safeners were detected at least once; furilazole was the most frequently detected (31%), followed by benoxacor (29%), dichlormid (15%), and AD-67 (2%). The maximum concentrations ranged from 42 to 190 ng/L. Stream detections and concentrations of safeners appear to be driven by a combination of timing of application (spring following herbicide application) and precipitation events. Detected concentrations were below known toxicity levels for aquatic organisms.

Illinois, Iowa↗
USGS2022

A review of supervised learning methods for classifying animal behavioural states from environmental features

Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations. We review SL methods (weighted k -nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles. Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package ( xgboost ) facilitate investigation of variable relationships and importance. For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.

Methods in Ecology and Evolution↗
USGS2015

FORUM: Effective management of ecological resilience – are we there yet?

Ecological resilience is developing into a credible paradigm for policy development and environmental management for preserving natural capital in a rapidly changing world. However, resilience emerges from complex interactions, limiting the translation of theory into practice. Main limitations include the following: (i) difficulty in quantification and detection of changes in ecological resilience, (ii) a lack of empirical evidence to support preventative or proactive management and (iii) difficulties in managing processes operating across socio-ecological systems that vary in space and time. We highlight recent research with the potential to address these limitations including new and/or improved indicators of resilience and tools to assess scale as a driver of resilience. Synthesis and applications . Effective resilience-based management must be adaptive in nature. To support this, we propose an operational model using resilience-based iterative management actions operating across scales.

Journal of Applied Ecology↗
USGS2009

Changing perceptions of change: The role of scientists in tamarix and river management

Initially introduced to western United States to provide ecosystem services such as erosion control, Tamarix by the mid-1900s had became vilified as a profligate waster of water. This large shrub continues, today, to be indicted for various presumed environmental and economic costs, and millions of dollars are expended on its eradication. In this review, we examine the role of scientists in driving changes in perceptions of Tamarix from valuable import to vilified invader and (in some instances) back to a productive member of riparian plant communities. Scientists over the years have sustained a negative perception of Tamarix by, among other things, (1) citing outmoded sources; (2) inferring causation from correlative studies; (3) applying conclusions beyond the scope (domain) of the studies; and (4) emphasizing findings that present the species as an extreme or unnatural agent of change. Recent research is challenging the prevailing dogma regarding Tamarix ’s role in ecosystem function and habitat degradation and many scientists now recommend management shifts from “pest plant” eradication to systemic, process-based restoration. However, prejudice against this and other non-native species persists. To further close the gap between science and management, it is important for scientists to strive to (1) cite sources appropriately; (2) avoid reflexive antiexotic bias; (3) avoid war-based and pestilence-based terminology; (4) heed the levels of certainty and the environmental domain of studies; (5) maintain up-to-date information on educational Web sites; and (6) prior to undertaking restoration or management actions, conduct a thorough and critical review of the literature.

Restoration Ecology↗
USGS2009

Adaptive management: The U.S. Department of the Interior technical guide

The purpose of this technical guide is to present an operational definition of adaptive management, identify the conditions in which adaptive management should be considered, and describe the process of using adaptive management for managing natural resources. The guide is not an exhaustive discussion of adaptive management, nor does it include detailed specifications for individual projects. However, it should aid U.S. Department of the Interior (DOI) managers and practitioners in determining when and how to apply adaptive management. Adaptive management is framed within the context of structured decision making, with an emphasis on uncertainty about resource responses to management actions and the value of reducing that uncertainty to improve management. Though learning plays a key role in adaptive management, it is seen here as a means to an end, namely good management, and not an end in itself. The operational definition used in the guide is adopted from the National Research Council, which characterizes adaptive management as an iterative learning process producing improved understanding and improved management over time: Adaptive management [is a decision process that] promotes flexible decision making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood. Careful monitoring of these outcomes both advances scientific understanding and helps adjust policies or operations as part of an iterative learning process. Adaptive management also recognizes the importance of natural variability in contributing to ecological resilience and productivity. It is not a ‘trial and error’ process, but rather emphasizes learning while doing. Adaptive management does not represent an end in itself, but rather a means to more effective decisions and enhanced benefits. Its true measure is in how well it helps meet environmental, social, and economic goals, increases scientific knowledge, and reduces tensions among stakeholders. Adaptive management as defined here involves ongoing, real-time learning and knowledge creation, both in a substantive sense and in terms of the adaptive process itself. It is described in what follows in a series of 9 steps, as summarized in section 4.1, involving stakeholder involvement, management objectives, management alternatives, predictive models, monitoring plans, decision making, monitoring responses to management, assessment, and adjustment to management actions. An adaptive approach actively engages stakeholders in all phases of a project over its timeframe, facilitating mutual learning and reinforcing the commitment to learning-based management. Adaptive management in DOI is implemented within a legal context that includes statutory authorities such as the National Environmental Policy Act (NEPA), the Endangered Species Act, and the Federal Advisory Committee Act. For many important problems now facing the resource management community, adaptive management holds great promise in reducing the uncertainties that limit the effective management of natural resource systems. For many conservation and management problems, utilizing management itself in an experimental context may be the only feasible way to gain the system understanding needed to improve management. Though it is commonly thought that an adaptive approach can produce results quickly at low cost, the opposite is more likely to be true. An initial investment of time and effort will increase the likelihood of better decision making and resource stewardship in the future, but patience, flexibility, and support are needed over the life of an adaptive management project. For these reasons it is important to carefully consider the potential use of an adaptive approach, and to engage in careful planning and evaluation when adaptive management is used.

Report↗
USGS2025

Ice Age biogeography corresponds with current climate vulnerability of freshwater fishes

1. Both local environmental factors and historical biogeography shape ecological communities, but determining which historical biogeographical patterns correspond with contemporary climate vulnerability is an underused conservation method. The historical colonization patterns of freshwater fishes following the Pleistocene (“Ice Age”) glaciations offers an ideal model for comparing historical biogeography and climate-change vulnerability. 2. We used current thermal niches and future stream-temperature projections to estimate the climate vulnerability of 29 Great Plains and Rocky Mountain fishes that we classified as either early or late colonists of the region in the wake of glacial retreat (~19,000 years ago). 3. Ninety-three percent of the most vulnerable species were amongst the earliest colonists of the region and we consider them “postglacial-pioneer species”. Median predicted site loss (number of historically occupied sites predicted to become too warm by end-of-century) was 0% for late colonizing species and 33% for early colonizing species. 4. We provide empirical evidence that postglacial-pioneer fishes are uniquely vulnerable to climate change, and we suggest this may apply to many taxa from formerly glaciated regions. More broadly, we demonstrate that evaluating the relationship between current species-environment patterns and historical biogeography may be a fruitful avenue for future climate change and conservation research.

North America↗
USGS2025

Restoring the Florida Everglades: Insights on integrating sea level rise into decision-support tools

Although coastal ecosystems are impacted by climate change and sea-level rise, many ecological and hydrological models do not yet incorporate sea-level rise projections in their modeling outputs. Therefore, this research examined the various challenges that may prevent sea-level rise from being effectively incorporated in modeling and decision-support tools. We conducted semi-structured interviews with twenty-six professionals involved in Florida’s Everglades restoration. We applied the Diffusions of Innovations Theory to better understand factors that can impact practitioners’ adoption of newly designed decision-support tools that examine sea-level rise in the freshwater Everglades. The Diffusions of Innovations Theory provided insights into practitioners’ perceptions of these tools. We found that these practitioners have a strong interest in using dynamic decision-support tools to plan for sea-level rise impacts on Everglades restoration, particularly when they receive information at appropriate geographic and temporal scales and are given hands-on tools and training. However, challenges that prevent developing these tools include outdated data, limited organizational capacity and funding, limited use of long-term indicators, uncertainty about climate change impacts on local ecosystems, and lack of integration between hydrological and ecological models. Our research also highlights that greater availability of different types of tools can help to meet the needs of the scientific and non-scientific audiences involved in Everglades restoration.

Florida↗
USGS2025

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↗
USGS2021

Grand challenges of hydrologic modeling for food-energy-water nexus security in high mountain Asia

Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution ( in-situ ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.

Frontiers in Water↗