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USGS2016

A network model framework for prioritizing wetland conservation in the Great Plains

Context Playa wetlands are the primary habitat for numerous wetland-dependent species in the Southern Great Plains of North America. Plant and wildlife populations that inhabit these wetlands are reciprocally linked through the dispersal of individuals, propagules and ultimately genes among local populations. Objective To develop and implement a framework using network models for conceptualizing, representing and analyzing potential biological flows among 48,981 spatially discrete playa wetlands in the Southern Great Plains. Methods We examined changes in connectivity patterns and assessed the relative importance of wetlands to maintaining these patterns by targeting wetlands for removal based on network centrality metrics weighted by estimates of habitat quality and probability of inundation. Results We identified several distinct, broad-scale sub networks and phase transitions among playa wetlands in the Southern Plains. In particular, for organisms that can disperse > 2 km a dense and expansive wetland sub network emerges in the Southern High Plains. This network was characterized by localized, densely connected wetland clusters at link distances ( h ) >2 km but <5 km and was most sensitive to changes in wetland availability ( p ) and configuration when h = 4 km, and p = 0.2–0.4. It transitioned to a single, large connected wetland system at broader spatial scales even when the proportion of inundated wetland was relatively low ( p = 0.2). Conclusions Our findings suggest that redundancy in the potential for broad and fine-scale movements insulates this system from damage and facilitates system-wide connectivity among populations with different dispersal capacities.

New Mexico, Texas↗

USGS2023

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate

Scientists, resource managers, and decision-makers increasingly use knowledge co-production to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley, USA to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We co-produced scenario narratives, spatially-explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We document our co-production process, and using the co-produced models, we ask: “when and where do management actions make a difference?” and “when does climate override these actions?” The outcomes of this process provide lessons learned on how to co-create usable information and how to increase climate adaptive capacity in a highly managed landscape. We found that: 1) actions to restore wetlands and prioritize their water supply create habitat outcomes resilient to climate change impacts particularly in March, when habitat is most limited, 2) land protection combined with management can increase the ecosystem's resilience to climate change, and 3) the uptake and use of this information was influenced by the roles of different stakeholders, plus rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. While a broad stakeholder group contributed knowledge to scenario narratives and model development, to co-produce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped to build legitimacy, yet broad-scale use of climate adaptation knowledge will depend on state and local policies, engagement with decision-makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.

California↗

USGS2009

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.

Landscape Ecology↗

USGS2022

Using paleoecological data to inform decision making: A deep-time perspective

Latest climate models project conditions for the end of this century that are generally outside of the human experience. These future conditions affect the resilience and sustainability of ecosystems, alter biogeographic zones, and impact biodiversity. Deep-time records of paleoclimate provide insight into the climate system over millions of years and provide examples of conditions very different from the present day, and in some cases similar to model projections for the future. In addition, the deep-time paleoecologic and sedimentologic archives provide insight into how species and habitats responded to past climate conditions. Thus, paleoclimatology provides essential context for the scientific understanding of climate change needed to inform resource management policy decisions. The Pliocene Epoch (5.3–2.6 Ma) is the most recent deep-time interval with relevance to future global warming. Analysis of marine sediments using a combination of paleoecology, biomarkers, and geochemistry indicates a global mean annual temperature for the Late Pliocene (3.6–2.6 Ma) ∼3°C warmer than the preindustrial. However, the inability of state-of-the-art climate models to capture some key regional features of Pliocene warming implies future projections using these same models may not span the full range of plausible future climate conditions. We use the Late Pliocene as one example of a deep-time interval relevant to management of biodiversity and ecosystems in a changing world. Pliocene reconstructed sea surface temperatures are used to drive a marine ecosystem model for the North Atlantic Ocean. Given that boundary conditions for the Late Pliocene are roughly analogous to present day, driving the marine ecosystem model with Late Pliocene paleoenvironmental conditions allows policymakers to consider a future ocean state and associated fisheries impacts independent of climate models, informed directly by paleoclimate information.

Frontiers in Ecology and Evolution↗

USGS2017

Dam removal: Listening in

Dam removal is widely used as an approach for river restoration in the United States. The increase in dam removals—particularly large dams—and associated dam-removal studies over the last few decades motivated a working group at the USGS John Wesley Powell Center for Analysis and Synthesis to review and synthesize available studies of dam removals and their findings. Based on dam removals thus far, some general conclusions have emerged: (1) physical responses are typically fast, with the rate of sediment erosion largely dependent on sediment characteristics and dam-removal strategy; (2) ecological responses to dam removal differ among the affected upstream, downstream, and reservoir reaches; (3) dam removal tends to quickly reestablish connectivity, restoring the movement of material and organisms between upstream and downstream river reaches; (4) geographic context, river history, and land use significantly influence river restoration trajectories and recovery potential because they control broader physical and ecological processes and conditions; and (5) quantitative modeling capability is improving, particularly for physical and broad-scale ecological effects, and gives managers information needed to understand and predict long-term effects of dam removal on riverine ecosystems. Although these studies collectively enhance our understanding of how riverine ecosystems respond to dam removal, knowledge gaps remain because most studies have been short (< 5 years) and do not adequately represent the diversity of dam types, watershed conditions, and dam-removal methods in the U.S.

Water Resources Research↗

USGS2025

Catchment prioritization for freshwater mussel conservation in the Northeastern United States based on distribution modelling

Freshwater mussels are critical to the health of freshwater systems, but their populations are declining dramatically throughout the world. The limited resources available for freshwater mussel conservation necessitates the geographic prioritization of conservation-related actions. However, lack of knowledge about freshwater mussel spatial distributions hinders decision making in this context. In this study, we assessed the distribution of twelve native freshwater mussel species across six Northeastern states (Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine) in the United States using data collected from lentic and lotic environments by eight state agencies. We first modeled individual distributions using a maximum entropy (MaxEnt) model and then compiled distribution models to assess the distribution of freshwater mussel species richness. We also determined geographic prioritization for three conservation-related actions: species surveys, land protection, and population restoration of species of high conservation concern. We found that the percent of catchments predicted to have species occurrence (based on a probability threshold) varied across species, with Elliptio complanata (Eastern elliptio) predicted to occur in the greatest percent of available catchments (33.92%) and Alasmidonta heterodon (Dwarf wedgemussel) expected in the smallest percent (5.30%). The predicted overall species richness within our modeled catchments ranged from zero to all twelve species, with an average of two species per catchment. Although conservation priorities vary depending on the conservation action of interest, we found some areas of consistent importance including much of Maine and the southern reaches of the Connecticut River. An improved understanding of freshwater mussel distribution in a landscape framework will enable managers to implement more precise and efficient conservation interventions for these essential aquatic species.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2011

Integrating estimates of ecosystem services from conservation programs and practices into models for decision makers

Most government agencies involved in land management are seeking consistent approaches to evaluate the effects of specific management actions on ecological processes and concurrent changes on ecosystem services. This is especially true within the context of anthropogenic influences, such as land use and climate change. The Conservation Effects Assessment Project—Wetlands National Component (CEAP–Wetlands) was developed by the U.S. Department of Agriculture (USDA) to evaluate effects of conservation practices on ecosystem services including carbon sequestration for climate stability, groundwater recharge, runoff and flood attenuation, water storage, nutrient and contaminant retention, and wildlife habitat. A primary purpose of CEAP–Wetlands is to provide science‐based information in an adaptive monitoring framework for use by the USDA to facilitate policy and management decisions, and to document effects of conservation programs and practices to the federal Office of Management and Budget. Herein, we propose a modeling framework to allow estimation of conservation practice and program effects on various ecosystem services at different temporal and spatial scales. This modeling approach provides the broad view needed by decision‐makers to avoid unintended negative environmental outcomes, and to communicate to society the positive effects of conservation actions on a broad suite of ecosystem services.

Ecological Applications↗

USGS2001

Habitat evaluation using GIS a case study applied to the San Joaquin Kit Fox

Concern over the fate of plant and animal species throughout the world has accelerated over recent decades. Habitat loss is considered the main culprit in reducing many species' abundance and range, leading to numerous efforts to plan and manage habitat preservation. Our work uses Geographic Information Systems (GIS) data and modeling to define a spatially explicit analysis of habitat value, using the San Joaquin Kit Fox (Vulpes macrotis mutica) of California (USA) as an example. Over the last 30 years, many field studies and surveys have enhanced our knowledge of the life history, behavior, and needs of the kit fox, which has been proposed as an umbrella or indicator species for grassland habitat in the San Joaquin Valley of California. There has yet been no attempt to convert much of this field knowledge into a model of spatial habitat value useful for planning purposes. This is a significant omission given the importance and visibility of the imperiled kit fox and increasing trends toward spatially explicit modeling and planning. In this paper we apply data from northern California to derive a small-cell GIS raster of habitat value for the kit fox that incorporates both intrinsic habitat quality and neighborhood context, as well the effects of barriers such as roads. Such a product is a useful basis for assessing the presence and amounts of good (and poor) quality habitat and for eventually constructing GIS representations of viable animal territories that could be included in future reserves. ?? 2001 Elsevier Science B.V.

Landscape and Urban Planning↗

USGS2015

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua , an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

California, Nevada↗

USGS2019

A statistical forecasting approach to metapopulation viability analysis

Conservation of at‐risk species is aided by reliable forecasts of the consequences of environmental change and management actions on population viability. Forecasts from conventional population viability analysis (PVA) are made using a two‐step procedure in which parameters are estimated, or elicited from expert opinion, and then plugged into a stochastic population model without accounting for parameter uncertainty. Recently developed statistical PVAs differ because forecasts are made conditional on models fitted to empirical data. The statistical forecasting approach allows for uncertainty about parameters, but it has rarely been applied in metapopulation contexts where spatially explicit inference is needed about colonization and extinction dynamics and other forms of stochasticity that influence metapopulation viability. We conducted a statistical metapopulation viability analysis (MPVA) using 11 yr of data on the federally threatened Chiricahua leopard frog ( Lithobates chiricahuensis ) to forecast responses to landscape heterogeneity, drought, environmental stochasticity, and management. We evaluated several future environmental scenarios and pond restoration options designed to reduce extinction risk. Forecasts over a 50‐yr time horizon indicated that metapopulation extinction risk was <4% for all scenarios, but uncertainty was high. Without pond restoration, extinction risk is forecasted to be 3.9% (95% CI 0–37%) by year 2066. Restoring six ponds by increasing their hydroperiod reduced extinction risk to <1% and greatly reduced uncertainty (95% CI 0–2%). Our results suggest that managers can mitigate the impacts of drought and environmental stochasticity on metapopulation viability by maintaining ponds that hold water throughout the year and keeping them free of invasive predators. Our study illustrates the utility of the spatially explicit statistical forecasting approach to MPVA in conservation planning efforts.

Ecological Applications↗

USGS2016

Controls on the geochemical evolution of Prairie Pothole Region lakes and wetlands over decadal time scales

One hundred sixty-seven Prairie Pothole lakes, ponds and wetlands (largely lakes) previously analyzed chemically during the late 1960’s and early to mid-1970’s were resampled and reanalyzed in 2011–2012. The two sampling periods differed climatically. The earlier sampling took place during normal to slightly dry conditions, whereas the latter occurred during and immediately following exceptionally wet conditions. As reported previously in Mushet et al. ( 2015 ), the dominant effect was expansion of the area of these lakes and dilution of their major ions. However, within that context, there were significant differences in the evolutionary pathways of major ions. To establish these pathways, we employed the inverse modeling computer code NetpathXL. This code takes the initial and final lake composition and, using mass balance constrained by the composition of diluting waters, and input and output of phases, calculates plausible geochemical evolution pathways. Despite the fact that in most cases major ions decreased, a subset of the lakes had an increase in SO 4 2− . This distinction is significant because SO 4 2− is the dominant anion in a majority of Prairie Pothole Region wetlands and lakes. For lakes with decreasing SO 4 2− , the proportion of original lake water required for mass balance was subordinate to rainwater and/or overland flow. In contrast, lakes with increasing SO 4 2− between the two sampling episodes tended to be dominated by original lake water. This suite of lakes tended to be smaller and have lower initial SO 4 2− concentrations such that inputs of sulfur from dissolution of the minerals gypsum or pyrite had a significant impact on the final sulfur concentration given the lower dilution factors. Thus, our study provides context for how Prairie Pothole Region water bodies evolve geochemically as climate changes. Because wetland geochemistry in turn controls the ecology of these water bodies, this research contributes to the prediction of the impact of climate change on this important complex of ecosystems.

North Dakota↗

USGS2014

Waterfowl populations of conservation concern: learning from diverse challenges, models, and conservation strategies

There are 30 threatened or endangered species of waterfowl worldwide, and several sub-populations are also threatened. Some of these species occur in North America, and others there are also of conservation concern due to declining population trends and their importance to hunters. Here we review conservation initiatives being undertaken for several of these latter species, along with conservation measures in place in Europe, to seek common themes and approaches that could be useful in developing broad conservation guidelines. While focal species may vary in their life histories, population threats and geopolitical context, most conservation efforts have used a systematic approach to understand factors limiting populations and o identify possible management or policy actions. This approach generally includes a priori identification of plausible hypotheses about population declines or status, incorporation of hypotheses into conceptual or quantitative planning models, and the use of some form of structured decision making and adaptive management to develop and implement conservation actions in the face of many uncertainties. A climate of collaboration among jurisdictions sharing these birds is important to the success of a conservation or management programme. The structured conservation approach exemplified herein provides an opportunity to involve stakeholders at all planning stages, allows for all views to be examined and incorporated into model structures, and yields a format for improved communication, cooperation and learning, which may ultimately be one of the greatest benefits of this strategy.

Wildfowl↗

USGS2024

Unravelling spatial heterogeneity of inundation pattern domains for 2D analysis of fluvial landscapes and drainage networks

Fluvial landscape analysis is an essential part of geomorphology, hydrology, ecology, and cartography. It is traditionally focused on the transition between hillslopes and channel domain, in which the network drainage is represented by static flow lines. However, the natural fluctuations of the processes occurring in the watershed induce lateral and longitudinal expansions and contractions in the drainage patterns and variations of stream surface area. These dynamics can be better understood by introducing a two-dimensional (2D) view of catchment hydrography, in which river width and floodplain are included in the analysis. The novelty introduced in this work is the development of a hydrodynamic hierarchical framework (HHF) to analyse the transitions among geomorphic and hydrographic features of the fluvial landscape, distinguishing hillslope, unchanneled valleys, floodplains, and single/multithreads channels. HHF is based on the estimation of nested inundation pattern domains (IPDs) from digital elevation models and 2D hydrodynamic modeling. IPDs are defined by scaling laws that characterize log–log relations between watershed drainage density and unit discharge thresholds extracted from a 2D direct rainfall method (DRM) under steady state solutions. The physical significance of the IPDs is analysed within the context of both the physiographic features of the fluvial landscape and the rainfall rates employed as input for the modeling approach. Initially, the spatial heterogeneity of the IPDs is used to derive stream width metrics as a function of the rainfall rate. Then, a spatial index, representative of the IPDs' heterogeneity, is introduced as a measure of the susceptibility of the drainage network surface area to expansion and contraction. Finally, the consistency of the results is assessed in comparison to another hydrodynamic-based method for fluvial landscape analysis recently proposed in the literature. The proposed approach is analysed using challenging mountain and low-relief environments, characterized by multithread channels, meander cut-offs, oxbow lakes, and extreme landscapes that feature glacial outwash, permafrost, and peatlands.

Alaska↗

USGS2012

Evaluating observations in the context of predictions for the death valley regional groundwater system

When a model is calibrated by nonlinear regression, calculated diagnostic and inferential statistics provide a wealth of information about many aspects of the system. This work uses linear inferential statistics that are measures of prediction uncertainty to investigate the likely importance of continued monitoring of hydraulic head to the accuracy of model predictions. The measurements evaluated are hydraulic heads; the predictions of interest are subsurface transport from 15 locations. The advective component of transport is considered because it is the component most affected by the system dynamics represented by the regional-scale model being used. The problem is addressed using the capabilities of the U.S. Geological Survey computer program MODFLOW-2000, with its Advective Travel Observation (ADV) Package. Copyright ASCE 2004.

Conference Paper↗

USGS2016

Deriving habitat models for northern long-eared bats from historical detection data: A case study using the Fernow Experimental Forest

The listing of the northern long-eared bat ( Myotis septentrionalis ) as federally threatened under the Endangered Species Act following severe population declines from white-nose syndrome presents considerable challenges to natural resource managers. Because the northern long-eared bat is a forest habitat generalist, development of effective conservation measures will depend on appropriate understanding of its habitat relationships at individual locations. However, severely reduced population sizes make gathering data for such models difficult. As a result, historical data may be essential in development of habitat models. To date, there has been little evaluation of how effective historical bat presence data, such as data derived from mist-net captures, acoustic detection, and day-roost locations, may be in developing habitat models, nor is it clear how models created using different data sources may differ. We explored this issue by creating presence probability models for the northern long-eared bat on the Fernow Experimental Forest in the central Appalachian Mountains of West Virginia using a historical, presence-only data set. Each presence data type produced outputs that were dissimilar but that still corresponded with known traits of the northern long-eared bat or are easily explained in the context of the particular data collection protocol. However, our results also highlight potential limitations of individual data types. For example, models from mist-net capture data only showed high probability of presence along the dendritic network of riparian areas, an obvious artifact of sampling methodology. Development of ecological niche and presence models for northern long-eared bat populations could be highly valuable for resource managers going forward with this species. We caution, however, that efforts to create such models should consider the substantial limitations of models derived from historical data, and address model assumptions.

West Virginia↗

USGS2019

Modeling ash dispersal from future eruptions of Taupo supervolcano

Hazard analysis at caldera volcanoes is challenging due to the wide range of eruptive and environmental conditions that can plausibly occur during renewed activity. Taupo volcano, New Zealand, is a frequently active and productive rhyolitic caldera volcano that has hosted the world's youngest known supereruption and numerous smaller explosive events. To assess ashfall hazard from future eruptions, we have simulated atmospheric ash dispersal using the Ash3d model. We consider five eruption scenarios spanning magma volumes of 0.1–500 km 3 and investigate the main factors governing ash dispersal in modern atmospheric conditions. Our results are examined in the context of regional synoptic weather patterns (Kidson types) that provide a framework for assessing the variability of ashfall distribution in different wind fields. For the smallest eruptions (~0.1‐km 3 magma), ashfall thicknesses >1 cm are largely confined to the central North Island, with dispersal controlled by day‐to‐day weather and the dominance of westerly winds. With increasing eruptive volume (1–5‐km 3 magma), ashfall thicknesses >1 cm would likely reach major population centers throughout the North Island. Dispersal is less dependent on weather patterns as the formation of a radially expanding umbrella cloud forces ash upwind or crosswind, although strong stratospheric winds significantly restrict umbrella spreading. For large eruptions (50–500‐km 3 magma), powerful expansion of the umbrella cloud results in widespread ashfall at damaging thicknesses (>10 cm) across most of the North Island and top of the South Island. Synoptic climatology may prove a useful additional technique for long‐term hazard planning at caldera volcanoes.

Taupo volcano↗

USGS2024

Correcting for measurement errors in a long-term aerial survey with auxiliary photographic data

Long-term, large-scale monitoring of wildlife populations is an integral part of conservation research and management. However, some traditional monitoring protocols lack the information needed to account for sources of measurement error in data analyses. Ignoring measurement error, such as partial availability, imperfect detection, and species misidentification, can lead to mischaracterizations of population states and processes. Accounting for measurement error is key to robust monitoring of populations, which can inform a wide variety of decisions, including harvest, habitat restoration, and determination of the legal status of species. We undertook an effort to retroactively minimize bias in a large-scale, long-term monitoring program for marine birds in the Salish Sea, Washington, USA, by conducting an auxiliary study to jointly estimate components of measurement error. We built a novel model in a Bayesian framework that simultaneously harnessed human observer and photographic data types to produce estimates necessary to correct for the effects of partial availability, imperfect detection, and species misidentification. Across all 31 species identified in photographs, both observers had instances of undercounting and overcounting birds but tended to undercount (observers undercounted totals across all species on 69.3%–78.9% of transects). We estimated species-specific correction factors that can be used to correct both historical and future counts from the Salish Sea survey, which has been running since 1992. Our novel modeling framework can be applied in other multispecies monitoring contexts where minimal photographic data can be collected for the purposes of correcting for measurement error in large-scale, long-term datasets.

Washington↗

USGS2015

Climate-induced lake drying causes heterogeneous reductions in waterfowl species richness

Context Lake size has declined on breeding grounds for international populations of waterfowl. Objectives Our objectives were to (1) model the relationship between waterfowl species richness and lake size; (2) use the model and trends in lake size to project historical, contemporary, and future richness at 2500+ lakes; (3) evaluate mechanisms for the species–area relationship (SAR); and (4) identify species most vulnerable to shrinking lakes. Methods Monte Carlo simulations of the richness model were used to generate projections. Correlations between richness and both lake size and habitat diversity were compared to identify mechanisms for the SAR. Patterns of nestedness were used to identify vulnerable species. Results Species richness was greatest at lakes that were larger, closer to rivers, had more wetlands along their perimeters and were within 5 km of a large lake. Average richness per lake was projected to decline by 11 % from 1986 to 2050 but was heterogeneous across sub-regions and lakes. Richness in sub-regions with species-rich lakes was projected to remain stable, while richness in the sub-region with species-poor lakes was projected to decline. Lake size had a greater effect on richness than did habitat diversity, suggesting that large lakes have more species because they provide more habitat but not more habitat types. The vulnerability of species to shrinking lakes was related to species rarity rather than foraging guild. Conclusions Our maps of projected changes in species richness and rank-ordered list of species most vulnerable to shrinking lakes can be used to identify targets for conservation or monitoring.

Landscape Ecology↗