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USGS2017

States and rates: Complementary approaches to developing flow‐ecology relationships

In recognition of the influence of flow on riverine habitats and organisms, stream ecologists have devoted considerable effort to the development of quantitative predictive relationships describing ecological responses to flow variability, i.e. flow‐ecology relationships. Methods used to generate flow‐ecology relationships can be thought of as a continuum bookended by pure states approaches on one end and by rates approaches on the other. In pure states approaches, the ecological response is a snapshot of a condition or property (i.e. a state) derived from a single measurement in time. In contrast, ecological responses in rates approaches reflect temporal change (i.e. a rate) and are thus reliant on repeated measurements made over time. Here, we elaborate on the fundamental characteristics of different approaches (pure states, rates and an intermediate approach we call repeated states) for generating flow‐ecology relationships, examine how commonly the different approaches are used in the flow‐ecology literature, conduct an independent analysis to illustrate the different outcomes achieved by applying repeated‐states and rates approaches using a dataset for stream fish diversity in relation to flow magnitude, and identify some of the different ways ecologists are applying rates approaches in flow ecology. Our literature review revealed that repeated‐states approaches (53% of reviewed studies) were used far more commonly than either pure states (19%) or rates (12%) approaches to generate flow‐ecology relationships. The remaining hybrid studies (17%) used both state and rate responses, and thus also relied on repeated measurements over time. Despite frequent collection of data suitable for rates approaches, flow‐ecology relationships have generally been developed using states approaches that relate changes in ecological states to different long‐term average flow conditions, rather than to specific flow sequences over much shorter time intervals. Such flow‐ecology relationships cannot generate temporally specific predictions of ecological responses to changing flow conditions (i.e. the expected change in state following a specific flow sequence), nor can they describe demographic processes underlying observed changes. While there are different scenarios in which a pure or repeated‐states approach would be useful, more frequent use of rates approaches would increase our ability to test flow‐ecology hypotheses and our mechanistic understanding of flow‐ecology relationships.

Freshwater Biology↗

USGS2025

Ecological thresholds and transformations due to climate change: The role of abiotic stress

An ecological threshold is the point at which a comparatively small environmental change triggers an abrupt and disproportionately large ecological response. In the face of accelerating climate change, there is concern that abrupt ecosystem transformations will become more widespread as critical ecological thresholds are crossed. There has been ongoing debate, however, regarding the prevalence of ecological thresholds across the natural world. While ecological thresholds are ubiquitous in some ecosystems, thresholds have been difficult to detect in others. Some studies have even concluded that threshold responses are uncommon in the natural world and overly emphasized in the ecological literature. As ecologists who work in ecosystems chronically exposed to high abiotic stress, we consider ecological thresholds and ecosystem transformations to be critical concepts that can greatly advance understanding of ecological responses to climate change and inform ecosystem management. But quantifying ecological thresholds can be challenging, if not impossible, without data that are strategically collected for that purpose. Here, we present a conceptual framework built upon linkages between abiotic stress, climate-driven ecological threshold responses, and the risk of ecosystem transformation. We also present a simple approach for quantifying ecological thresholds across abiotic stress gradients. We hypothesize that climate-driven threshold responses are especially influential in ecosystems chronically exposed to high abiotic stress, where autotroph diversity is low and foundation species play a prominent ecological role. Abiotic conditions in these environments are often near physiological tolerance limits of foundation species, which means that small abiotic changes can trigger landscape-level ecological transformations. Conversely, the alleviation of stress near thresholds can allow foundation species to thrive and spread into previously inhospitable locations. We provide examples of this climate-driven threshold behavior from four high-stress environments: coastal wetlands, coral reefs, drylands, and alpine ecosystems. Our overarching aim in this review is to clarify the strong relationships between abiotic stress, climate-driven ecological thresholds, and the risk of ecosystem transformation under climate change.

Ecosphere↗

USGS2019

Introduction: Defining and interpreting ecological disturbances

Within the field of ecology, disturbance can be defined as a physical force, agent, or process, either abiotic or biotic, causing a perturbation or stress, to an ecological component or system, relative to a specified reference state and/or system. Disturbance drive ecosystems, and our understanding of how disturbances interact with biological diversity and scales of space, time, and ecological complexity, have matured over a century of advancement in ecology since early ideas of perturbations and community organization were first formalized. Throughout this book, we approach a set of unifying framing questions for disturbance ecology, including: How can disturbances be categorized in meaningful ways? How do we address scale in disturbance ecology? How does geographic context influence ecological consequences of disturbance, in the near and longer terms? In this introductory chapter, we provide an overview of disturbance ecology and the related topics of diversity and scale that are fundamental to understanding the dynamics of perturbed ecosystems. Subsequently, we outline recent advances in disturbance ecology, which have facilitated greater understanding about dynamic systems and context dependencies. These, in turn, have provided richer insights into the complex manner in which ecosystems change under stress. We survey analytical and methodological advances that are expanding the data flows available to inform disturbance ecology as well as the statistical tools available to investigate disturbance dynamics and ecosystem structure and function. Finally, we lay out four core themes threaded through the remainder of the book: (1) fundamental mechanisms related to ecological theory drive complex system behaviors, including the existence of thresholds; (2) dynamics of ecological disturbance are context-dependent and can be unpredictable; (3) antecedent conditions and the legacies of past disturbances influence contemporary ecosystem dynamics; and (4) natural and anthropogenic disturbances interact in complex ways. Summaries are provided for each of the book’s remaining chapters, highlighting how that material relates to these four core themes. In sum, in this introductory chapter we seek to set a foundation for concepts to ground the remainder of the book. By highlighting constraints in past research and identifying research frontiers, we hope to provide a path forward for advancements in disturbance ecology.

Book chapter↗

USGS2022

The power of forecasts to advance ecological theory

Ecological forecasting provides a powerful set of methods for predicting short- and long-term change in living systems. Forecasts are now widely produced, enabling proactive management for many applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealized. Here, we provide a conceptual framework describing how ecological forecasts can energize and advance ecological theory. We emphasize the many opportunities for future progress in this area through increased forecast development, comparison and synthesis. Our framework describes how a forecasting approach can shed new light on existing ecological theories while also allowing researchers to address novel questions. Through rigorous and repeated testing of hypotheses, forecasting can help to refine theories and understand their generality across systems. Meanwhile, synthesizing across forecasts allows for the development of novel theory about the relative predictability of ecological variables across forecast horizons and scales. We envision a future where forecasting is integrated as part of the toolset used in fundamental ecology. By outlining the relevance of forecasting methods to ecological theory, we aim to decrease barriers to entry and broaden the community of researchers using forecasting for fundamental ecological insight.

Methods in Ecology and Evolution↗

USGS2009

The ecological limits of hydrologic alteration (ELOHA): A new framework for developing regional environmental flow standards

The flow regime is a primary determinant of the structure and function of aquatic and riparian ecosystems for streams and rivers. Hydrologic alteration has impaired riverine ecosystems on a global scale, and the pace and intensity of human development greatly exceeds the ability of scientists to assess the effects on a river-by-river basis. Current scientific understanding of hydrologic controls on riverine ecosystems and experience gained from individual river studies support development of environmental flow standards at the regional scale. 2. This paper presents a consensus view from a group of international scientists on a new framework for assessing environmental flow needs for many streams and rivers simultaneously to foster development and implementation of environmental flow standards at the regional scale. This framework, the ecological limits of hydrologic alteration (ELOHA), is a synthesis of a number of existing hydrologic techniques and environmental flow methods that are currently being used to various degrees and that can support comprehensive regional flow management. The flexible approach allows scientists, water-resource managers and stakeholders to analyse and synthesise available scientific information into ecologically based and socially acceptable goals and standards for management of environmental flows. 3. The ELOHA framework includes the synthesis of existing hydrologic and ecological databases from many rivers within a user-defined region to develop scientifically defensible and empirically testable relationships between flow alteration and ecological responses. These relationships serve as the basis for the societally driven process of developing regional flow standards. This is to be achieved by first using hydrologic modelling to build a 'hydrologic foundation' of baseline and current hydrographs for stream and river segments throughout the region. Second, using a set of ecologically relevant flow variables, river segments within the region are classified into a few distinctive flow regime types that are expected to have different ecological characteristics. These river types can be further subclassified according to important geomorphic features that define hydraulic habitat features. Third, the deviation of current-condition flows from baseline-condition flow is determined. Fourth, flow alteration-ecological response relationships are developed for each river type, based on a combination of existing hydroecological literature, expert knowledge and field studies across gradients of hydrologic alteration. 4. Scientific uncertainty will exist in the flow alteration-ecological response relationships, in part because of the confounding of hydrologic alteration with other important environmental determinants of river ecosystem condition (e.g. temperature). Application of the ELOHA framework should therefore occur in a consensus context where stakeholders and decision-makers explicitly evaluate acceptable risk as a balance between the perceived value of the ecological goals, the economic costs involved and the scientific uncertainties in functional relationships between ecological responses and flow alteration. 5. The ELOHA framework also should proceed in an adaptive management context, where collection of monitoring data or targeted field sampling data allows for testing of the proposed flow alteration-ecological response relationships. This empirical validation process allows for a fine-tuning of environmental flow management targets. The ELOHA framework can be used both to guide basic research in hydroecology and to further implementation of more comprehensive environmental flow management of freshwater sustainability on a global scale. ?? 2009 Blackwell Publishing Ltd.

Freshwater Biology↗

USGS2026

Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology

Landscape ecologists have long depended on satellite and aerial remote sensing to address questions about landscape pattern and process, structure, and change (Foody 2023 ). Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) technology is becoming an increasingly popular research tool in environmental sciences allowing scientists to generate low-cost, high-quality, and high-resolution imagery on demand that can be tailored to specific research questions. While satellite data are of a fixed resolution and temporal interval, UAS offer researchers control and flexibility to design studies and collect data at resolutions and scales that provide ecologically relevant information at finer spatial resolutions (e.g., < 30 cm) than what is currently available from satellite platforms (typically > 3m), thus helping capture objects such as individual plant canopies, micro-topography, and individual animals. Unlike satellites with fixed orbits, UAS can be deployed at more optimal temporal frequencies for ecological monitoring. We organized the special collection “Advances and Applications of Unoccupied Aerial Systems (UAS) Research in Landscape Ecology” to showcase the many ways that UAS tools and technologies are currently applied to advance landscape ecological research. When we announced the collection in 2023, only 11 papers published in the journal Landscape Ecology used UAS data, which was a notably small number compared to many other general ecology, environmental science and remote sensing journals. In an attempt to understand why UAS were not more widely used in landscape ecology and provide possible solutions, we published a review article (Villarreal et al. 2025) that identified the challenges, knowledge gaps, and obstacles for the adoption of UAS technologies in landscape ecology research. The main issues we identified include: (1) an abundance of UAS methods papers in the existing literature, with comparatively few studies demonstrating how UAS can be applied to address ecological questions; (2) a perceived scale mismatch between the geographic extent of UAS data collection (local) compared to larger study areas (landscapes) and a need to design robust scaling approaches to connect fine-scale UAS data with broader ecological patterns; and (3) a need for improved integration of UAS data with other commonly used remote sensing datasets including historical high resolution aerial imagery. Additionally, researchers new to UAS remote sensing may be discouraged or overwhelmed by the general lack of scientific consensus and standardized protocols for typical tasks such as data collection, vegetation classification, and change detection, as well as restrictive and/or confusing policy, regulatory, and legal issues surrounding UAS operations (Villarreal et al. 2025).

Landscape Ecology↗

USGS2014

Getting the message across: using ecological integrity to communicate with resource managers

This chapter describes and illustrates how concepts of ecological integrity, thresholds, and reference conditions can be integrated into a research and monitoring framework for natural resource management. Ecological integrity has been defined as a measure of the composition, structure, and function of an ecosystem in relation to the system’s natural or historical range of variation, as well as perturbations caused by natural or anthropogenic agents of change. Using ecological integrity to communicate with managers requires five steps, often implemented iteratively: (1) document the scale of the project and the current conceptual understanding and reference conditions of the ecosystem, (2) select appropriate metrics representing integrity, (3) define externally verified assessment points (metric values that signify an ecological change or need for management action) for the metrics, (4) collect data and calculate metric scores, and (5) summarize the status of the ecosystem using a variety of reporting methods. While we present the steps linearly for conceptual clarity, actual implementation of this approach may require addressing the steps in a different order or revisiting steps (such as metric selection) multiple times as data are collected. Knowledge of relevant ecological thresholds is important when metrics are selected, because thresholds identify where small changes in an environmental driver produce large responses in the ecosystem. Metrics with thresholds at or just beyond the limits of a system’s range of natural variability can be excellent, since moving beyond the normal range produces a marked change in their values. Alternatively, metrics with thresholds within but near the edge of the range of natural variability can serve as harbingers of potential change. Identifying thresholds also contributes to decisions about selection of assessment points. In particular, if there is a significant resistance to perturbation in an ecosystem, with threshold behavior not occurring until well beyond the historical range of variation, this may provide a scientific basis for shifting an ecological assessment point beyond the historical range. We present two case studies using ongoing monitoring by the US National Park Service Vital Signs program that illustrate the use of an ecological integrity approach to communicate ecosystem status to resource managers. The Wetland Ecological Integrity in Rocky Mountain National Park case study uses an analytical approach that specifically incorporates threshold detection into the process of establishing assessment points. The Forest Ecological Integrity of Northeastern National Parks case study describes a method for reporting ecological integrity to resource managers and other decision makers. We believe our approach has the potential for wide applicability for natural resource management.

Book chapter↗

USGS2009

The South Florida Ecosystem Portfolio Model - A Map-Based Multicriteria Ecological, Economic, and Community Land-Use Planning Tool

The South Florida Ecosystem Portfolio Model (EPM) prototype is a regional land-use planning Web tool that integrates ecological, economic, and social information and values of relevance to decision-makers and stakeholders. The EPM uses a multicriteria evaluation framework that builds on geographic information system-based (GIS) analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to regional land-use/land-cover (LULC) change. The EPM uses both economics (monetized) and multiattribute utility (nonmonetized) approaches to valuing these endpoints and consequences. This hybrid approach represents a methodological middle ground between rigorous economic and ecological/ environmental scientific approaches. The EPM sacrifices some degree of economic- and ecological-forecasting precision to gain methodological transparency, spatial explicitness, and transferability, while maintaining credibility. After all, even small steps in the direction of including ecosystem services evaluation are an improvement over current land-use planning practice (Boyd and Wainger, 2003). There are many participants involved in land-use decision-making in South Florida, including local, regional, State, and Federal agencies, developers, environmental groups, agricultural groups, and other stakeholders (South Florida Regional Planning Council, 2003, 2004). The EPM's multicriteria evaluation framework is designed to cut across the objectives and knowledge bases of all of these participants. This approach places fundamental importance on social equity and stakeholder participation in land-use decision-making, but makes no attempt to determine normative socially 'optimal' land-use plans. The EPM is thus a map-based set of evaluation tools for planners and stakeholders to use in their deliberations of what is 'best', considering a balancing of disparate interests within a regional perspective. Although issues of regional ecological sustainability can be explored with the EPM (for example, changes in biodiversity potential and regional habitat fragmentation), it does not attempt to define or evaluate long-term ecological sustainability as such. Instead, the EPM is intended to provide transparent first-order indications of the direction of ecological, economic, and community change, not to make detailed predictions of ecological, economic, and social outcomes. In short, the EPM is an attempt to widen the perspectives of its users by integrating natural and social scientific information in a framework that recognizes the diversity of values at stake in South Florida land-use planning. For terrestrial ecosystems, land-cover change is one of the most important direct drivers of changes in ecosystem services (Hassan and others, 2005). More specifically, the fragmentation of habitat from expanding low-density development across landscapes appears to be a major driver of terrestrial species decline and the impairment of terrestrial ecosystem integrity, in some cases causing irreversible impairment from a land-use planning perspective (Brody, 2008; Peck, 1998). Many resource managers and land-use planners have come to realize that evaluating land-use conversions on a parcel-by-parcel basis leads to a fragmented and narrow view of the regional effects of natural land-cover loss to development (Marsh and Lallas, 1995). The EPM is an attempt to integrate important aspects of the coupled natural-system/human-system view from a regional planning perspective. The EPM evaluates proposed land-use changes, both conversion and intensification, in terms of relevant ecological, economic, and social criteria that combine information about probable land-use outcomes, based on ecological and environmental models, as well as value judgments, as expressed in user-modifiable preference models. Based on on-going meetings and interviews with stakeholders and potential tool users we foc

Scientific Investigations Report↗

USGS2014

An ecological response model for the Cache la Poudre River through Fort Collins

The Poudre River Ecological Response Model (ERM) is a collaborative effort initiated by the City of Fort Collins and a team of nine river scientists to provide the City with a tool to improve its understanding of the past, present, and likely future conditions of the Cache la Poudre River ecosystem. The overall ecosystem condition is described through the measurement of key ecological indicators such as shape and character of the stream channel and banks, streamside plant communities and floodplain wetlands, aquatic vegetation and insects, and fishes, both coolwater trout and warmwater native species. The 13- mile-long study area of the Poudre River flows through Fort Collins, Colorado, and is located in an ecological transition zone between the upstream, cold-water, steep-gradient system in the Front Range of the Southern Rocky Mountains and the downstream, warm-water, low-gradient reach in the Colorado high plains. The City wanted to better understand the ecological response of the Poudre River ecosystem to potential changes in stream flow and other physical parameters through the conceptual framework of a multivariable integrated model. This goal was met through the use of a probabilistic model based on Bayesian concepts. This construct allowed the integration of a wide range of data and expert opinion (as informed by local data) to predict potential changes to ecosystem conditions under various flow scenarios. Nine flow scenarios representing past, present, and possible future hydrology were developed as the primary model input. Both reach-scale drivers such as stream channel conditions and pollutant loads, as well as ecological conditions, including species composition, interactions, and habitat requirements influenced model-predicted ecosystem outcomes. Model output consisted of probability distributions for eight ecological indicators collectively representing the physical setting, aquatic life, and riparian habitats of the river ecosystem. We are confident in model predictions related to probable trends, relative magnitude of changes and potential ecosystem responses to changing flow conditions, though data availability and the process of converting diverse data types into a common unit (probabilities) limit precision of individual results. Key findings suggest that: The present ecological function of the Poudre River is altered as a result of more than 150 years of human influences that include highly managed flows, urbanization, gravel mining, channelization and urban and industrial encroachment in the floodplain, underscoring the vulnerable and complex character of the Poudre River; A continuation of today’s flow management will lead to ongoing changes in ecosystem condition, and additional water depletions will compromise ecological conditions; High flows play an essential role in maintaining and improving the aquatic and riparian condition of the river; Adequate flows in base-flow periods are critical to desirable water quality, and thriving fish and insect populations; Improvement of native aquatic life is possible if issues related to channel modifications, siltation, invasive species, and base and high flow conditions are managed properly; The present confined river channel and modified flows has reduced the potential for a keystone and iconic species, plains cottonwood, to be self-sustaining in the study area; The streamside corridor retains the potential to support a functioning riparian forest that provides important ecological services if periodic floodplain inundation occurs. Environmental flows that combine stable and adequate flows in base-flow periods with occasional rejuvenating high flows that meet target levels defined in this study are likely improve all biological indicators across the system. ERM test scenarios that include both stable base flows and rejuvenating high flows indicate that substantial improvements in the river ecosystem can be achieved with improved management of flow volumes similar to those observed in the river during the last half century of intensive water development. These results underscore the possibility of improving the river ecosystem through active management while still maintaining the Poudre’s diverse economic benefits and role as a working river. The ERM was designed to represent the multi-dimensional ecological character of the contemporary urban Poudre River. It provides a scientific foundation that can serve as a decision support tool and foster a more informed community discussion about the future of the river as it provides a better understanding of the likely response of the Poudre River ecosystem to environmental flow management and other stewardship activities. In particular, model results can assist managers in developing specific management actions to achieve desirable goals for key indicators of river health.

Colorado↗

USGS2012

Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools

Ecological indicators are science-based tools used to assess how human activities have impacted environmental resources. For monitoring and environmental assessment, existing species assemblage data can be used to make these comparisons through time or across sites. An impediment to using assemblage data, however, is that these data are complex and need to be simplified in an ecologically meaningful way. Because multivariate statistics are mathematical relationships, statistical groupings may not make ecological sense and will not have utility as indicators. Our goal was to define a process to select defensible and ecologically interpretable statistical simplifications of assemblage data in which researchers and managers can have confidence. For this, we chose a suite of statistical methods, compared the groupings that resulted from these analyses, identified convergence among groupings, then we interpreted the groupings using species and ecological guilds. When we tested this approach using a statewide stream fish dataset, not all statistical methods worked equally well. For our dataset, logistic regression (Log), detrended correspondence analysis (DCA), cluster analysis (CL), and non-metric multidimensional scaling (NMDS) provided consistent, simplified output. Specifically, the Log, DCA, CL-1, and NMDS-1 groupings were ≥60% similar to each other, overlapped with the fluvial-specialist ecological guild, and contained a common subset of species. Groupings based on number of species (e.g., Log, DCA, CL and NMDS) outperformed groupings based on abundance [e.g., principal components analysis (PCA) and Poisson regression]. Although the specific methods that worked on our test dataset have generality, here we are advocating a process (e.g., identifying convergent groupings with redundant species composition that are ecologically interpretable) rather than the automatic use of any single statistical tool. We summarize this process in step-by-step guidance for the future use of these commonly available ecological and statistical methods in preparing assemblage data for use in ecological indicators.

Ecological Indicators↗

USGS2022

A quantitative soil-geomorphic framework for developing and mapping ecological site groups

Land management decisions need context about how landscapes will respond to different circumstances or actions. As ecologists’ understanding of nonlinear ecological dynamics has evolved into state-and-transition models (STMs), they have put more emphasis on defining and mapping the soil, geomorphological, and climate parameters that mediate these dynamics. The US Department of Agriculture Natural Resources Conservation Service ecological site descriptions (ESDs) have become the foremost system in classifying lands into ecological units based on STMs. However, an exhaustive inventory of ESDs has proved challenging to complete in the United States, and there have been questions about the consistency of detail in areas completed and the ability to objectively support some assertions made in existing ESDs. To address these issues, this study examines ESDs in the diverse Upper Colorado River region, where ESDs are only partially complete, to look at quantitative approaches to generalizing ecological site concepts based on unifying underlying soil, geomorphology, and climate patterns. Using existing ESDs and vegetation monitoring plot data, results show that a simple hierarchical soil geomorphic unit (SGU) framework based on topographic mediation of moisture, soil salinity, soil depth, slope, rock content, and soil texture can represent much of the ecological dynamics cataloged in ESDs. Analyses of reference plant production data, ecological state attribution, and regional monitoring data show that the new SGUs represent more variation than common climate parameters. This study also included predictively mapping SGUs at 30-m resolution (Kappa of 0.53, 74% agreement with top two predictions in validation). An optimized combination of SGUs with climate zones derived from an aridity index and maximum temperature of the hottest month resulted in an ecological site group framework that condensed over 826 unique ecological site records at various stages of completeness in the regional soil survey down to 35 intuitive and mappable ecological site groups.

Rangeland Ecology and Management↗

USGS2024

Climate change amplifies ongoing declines in sagebrush ecological integrity

Understanding how climate change will contribute to ongoing declines in sagebrush ecological integrity is critical for informing natural resource management, yet complicated by interactions with wildfire and biological invasions. Here, we assessed potential future changes in sagebrush ecological integrity under a range of scenarios using an individual plant-based simulation model, integrated with remotely sensed estimates of current sagebrush ecological integrity. The simulation model allowed us to estimate how climate change, wildfire, and invasive annuals interact to alter the potential abundance of key plant functional types that influence sagebrush ecological integrity: sagebrush, perennial grasses, and annual grasses. Our results suggest that climate driven reductions in sagebrush ecological integrity may occur over broader areas than increases in sagebrush ecological integrity. Declines in sagebrush ecological integrity were most likely in hot and dry regions while increases were more likely in cool and wet regions. Increases in wildfire probability, largely driven by increasing invasive annual grass abundance, resulted in projected declines in sagebrush abundance and sagebrush ecological integrity in some regions, particularly the Great Basin. The most common projected transitions in sagebrush habitat classification were declines from Core Sagebrush Area to Growth Opportunity Area and from Growth Opportunity Area to Other Rangeland Area. Responses varied considerably across projections from different global climate models, highlighting the importance of climate uncertainty. However, our projections tended to be robust in areas that currently have the highest sagebrush ecological integrity. Our results provide a long-term perspective on the vulnerability of sagebrush ecosystems to climate change and may inform geographic prioritization of conservation and restoration investments. These results suggest that ongoing threats, such as the continued invasion by annual grasses and increased wildfire frequency, are likely to be amplified by climate change, and imply that the current imbalance between capacity for conservation to address threats to sagebrush will grow as the climate warms.

Rangeland Ecology and Management↗

USGS2015

Understanding protected area resilience: a multi-scale, social-ecological approach

Protected areas (PAs) remain central to the conservation of biodiversity. Classical PAs were conceived as areas that would be set aside to maintain a natural state with minimal human influence. However, global environmental change and growing cross-scale anthropogenic influences mean that PAs can no longer be thought of as ecological islands that function independently of the broader social-ecological system in which they are located. For PAs to be resilient (and to contribute to broader social-ecological resilience), they must be able to adapt to changing social and ecological conditions over time in a way that supports the long-term persistence of populations, communities, and ecosystems of conservation concern. We extend Ostrom's social-ecological systems framework to consider the long-term persistence of PAs, as a form of land use embedded in social-ecological systems, with important cross-scale feedbacks. Most notably, we highlight the cross-scale influences and feedbacks on PAs that exist from the local to the global scale, contextualizing PAs within multi-scale social-ecological functional landscapes. Such functional landscapes are integral to understand and manage individual PAs for long-term sustainability. We illustrate our conceptual contribution with three case studies that highlight cross-scale feedbacks and social-ecological interactions in the functioning of PAs and in relation to regional resilience. Our analysis suggests that while ecological, economic, and social processes are often directly relevant to PAs at finer scales, at broader scales, the dominant processes that shape and alter PA resilience are primarily social and economic.

Ecological Applications↗

USGS2025

Mapping predicted ecological states at landscape scales using remote sensing data and machine learning

Dryland ecosystems, covering 45% of the Earth's land and supporting over one-third of the global population, face significant threats from land degradation and ecological state change. Managing these ecosystems is complex, and science-based frameworks like Ecological Site Descriptions and state-and-transition models are essential tools for guiding decisions to support ecological health while maintaining stakeholder values such as grazing, wildlife, and recreation. However, alignment of these frameworks with smaller scale soil survey maps limits their applicability to broader ecological processes. Here, we extend these frameworks to larger landscapes with a machine learning approach that integrates large-scale, high-resolution vegetation data with identified ecological states from a data-driven state-and-transition model developed for a landscape-scale Ecological Site Group. A “global” model, which used combined inputs from multiple remotely sensed datasets, outperformed individual dataset models based on evaluation with independent data. Ecological state maps generated through this approach broaden the utility of state-and-transition models across Ecological Site Groups, providing a more spatially robust tool for land management at watershed and larger landscape scales. These methods, and the associated ecological state maps, can help meet critical needs for improved land condition assessments that support development of resource management plans and help identify priority areas for restoration and conservation.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2019

Ecological health indicators

Contemporary policymakers rarely stress ecological knowledge, and yet this knowledge remains crucial—just as it was in prehistory—to protecting overall human well-being. Measuring carefully selected ecological health indicators—that is, signs or symptoms, especially those focused on biotic assemblages—can provide insights into the ecological condition of a place and the variety of ecological consequences of proposed or present human actions there. In turn, measured ecological conditions may be judged as acceptable (healthy) or unacceptable (unhealthy), depending on prevailing value systems and societal goals. Ecological health indicators characterize the ecological conditions of where we live; improve scientific understanding of ecosystems and the benefits they provide; diagnose causes of ecological degradation; communicate scientific knowledge to nontechnical audiences; guide environmental policy; and measure progress toward societal goals. By helping to identify who benefits and who suffers from societal choices, ecological health indicators inform our choices about how to use or protect ecosystems and their living components, including human society itself.

Book chapter↗

USGS2024

Global assessment of aquatic Isoëtes species ecology

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

Freshwater Biology↗

USGS2017

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Global Change Biology↗

USGS2010

Sampling in ecology and evolution - bridging the gap between theory and practice

Sampling is a key issue for answering most ecological and evolutionary questions. The importance of developing a rigorous sampling design tailored to specific questions has already been discussed in the ecological and sampling literature and has provided useful tools and recommendations to sample and analyse ecological data. However, sampling issues are often difficult to overcome in ecological studies due to apparent inconsistencies between theory and practice, often leading to the implementation of simplified sampling designs that suffer from unknown biases. Moreover, we believe that classical sampling principles which are based on estimation of means and variances are insufficient to fully address many ecological questions that rely on estimating relationships between a response and a set of predictor variables over time and space. Our objective is thus to highlight the importance of selecting an appropriate sampling space and an appropriate sampling design. We also emphasize the importance of using prior knowledge of the study system to estimate models or complex parameters and thus better understand ecological patterns and processes generating these patterns. Using a semi-virtual simulation study as an illustration we reveal how the selection of the space (e.g. geographic, climatic), in which the sampling is designed, influences the patterns that can be ultimately detected. We also demonstrate the inefficiency of common sampling designs to reveal response curves between ecological variables and climatic gradients. Further, we show that response-surface methodology, which has rarely been used in ecology, is much more efficient than more traditional methods. Finally, we discuss the use of prior knowledge, simulation studies and model-based designs in defining appropriate sampling designs. We conclude by a call for development of methods to unbiasedly estimate nonlinear ecologically relevant parameters, in order to make inferences while fulfilling requirements of both sampling theory and field work logistics. ?? 2010 The Authors.

Ecography↗