Geology topics

Daniel R. Uden

Publications and source records attributed to Daniel R. Uden.

At least 19 recordsLinked to original sources

USGS2026

Biome-scale spatial patterns of avian abundance reveal proactive conservation opportunities in North American grasslands

North American grassland birds have experienced steeper population declines than any other avian guild, yet conservation efforts remain largely reactive and fragmented. We used nearly four decades of North American Breeding Bird Survey data to identify biome-scale spatial patterns (clustering) of grassland bird abundance for the Great Plains. Our results reveal an ecological core in the north-central Plains where community-level abundance is either increasing by >100% or remains high and stable, providing a strategic roadmap for a “Defend the Core” conservation approach. This approach flips the script from reactive triage centered on isolated population fragments to a proactive strategy of maintaining large-scale ecosystem integrity. Conversely, we found that population losses are more spatially clustered than wins, reflecting the relentless, one-way movement of woody encroachment and agricultural conversion. This asymmetry supports prioritizing intact landscapes, as current restoration rates are often outpaced by the scale of habitat loss. Notably, we found that community-level spatial clustering is a more robust indicator of biome condition than trends of individual flagship species, suggesting that managing for ecosystem integrity provides a more effective multi-species umbrella. Given our results, there is an opportunity for operationalizing a Great Plains Conservation Design that is ecosystem-centric and rooted in the sustainability of the private-land cattle production that maintains these open spaces. By leveraging avian abundance as a biological sensor, managers and producers can deploy a shared vision that matches the spatial scale of the threats, moving from reactive triage to proactive defense of core working grasslands in North America.

Great Plains biome↗

USGS2026

Finding the (small) cores: Spatial covariance tracks grassland bird community occupancy in fragmented grasslands

Grasslands are an imperiled ecosystem, and grassland bird abundance is declining across North America. One of the strongest drivers for these declines is woody plant encroachment of grasslands. In the Great Plains and Sagebrush biomes of North America, spatial covariance—a remote-sensing metric for tracking boundaries between vegetation types—is emerging as a new method to identify and strategize conservation of grassland cores in the face of woody plant encroachment. However, the relationship between spatial covariance and grassland bird community occupancy is unknown. Here, we used Bayesian multispecies occupancy models to understand how occupancy probability of six declining grassland species responded to spatial covariance at three scales (0.81, 7.29, and 65.61 ha) and tree cover in fragmented grasslands of Arkansas, USA. Model selection revealed that the smallest spatial scale (0.81 ha) best explained grassland bird occupancy. Tree cover alone was a poor predictor of grassland bird occupancy compared to models that included spatial covariance at the 0.81- and 7.29-ha scales. Grassland bird occupancy declined at tree-grass boundaries (negative spatial covariance at the 0.81-ha scale) and increased in grassland cores (near-zero or slightly positive spatial covariance at the 0.81-ha scale). At low tree cover, Dickcissel ( Spiza americana ), Eastern Kingbird ( Tyrannus tyrannus ), Loggerhead Shrike ( Lanius ludovicianus ), Northern Bobwhite ( Colinus virginianus ), and Scissor-tailed Flycatcher ( Tyrannus forficatus ) occupancy probability more than doubled in grassland cores (where spatial covariance approached zero). Eastern Meadowlark ( Sturnella magna ) had the weakest relationship with spatial covariance. Our results suggest that spatial covariance can identify grassland cores and serve as a powerful predictor of grassland bird community occupancy, even in highly fragmented grasslands. Identifying grassland cores empowers defending core grasslands from woody plant encroachment and then growing cores via active restoration.

Arkansas↗

USGS2026

Comparing spatial covariance to common field vegetation metrics

Spatial covariance is a metric used to delineate grassland cores and track state transitions driven by woody encroachment in rangelands, and it does so by calculating the degree of spatial coexistence between functional groups like grasses and trees at different scales. Spatial covariance is being used in biome-scale frameworks aimed at combatting woody plant encroachment and grassland conservation, but little is known about how spatial covariance relates to on-the-ground vegetation metrics. Here, we begin to address this knowledge gap by comparing tree-grass spatial covariance (0.81 ha scale) to a variety of established, field vegetation structure metrics. Generalized additive models revealed that relationships between spatial covariance and field-based vegetation metrics were weak to moderate (deviance explained ranging from 10% – 47%). Tree density had the strongest relationship with spatial covariance (deviance explained = 47%): tree density nonlinearly decreased to near-zero when spatial covariance became positive. Average visual obstruction and visual percent grass cover had the weakest relationships with spatial covariance (deviance explained = 13% and 10%, respectively). The stronger tie between tree density and spatial covariance and the very weak link between dominant vegetation cover aligns with the intended usage of spatial covariance in rangeland management, which is to locate treeless grassland cores (i.e., spatial covariance values near zero) and prioritize them for defending “core” rangeland habitats. This also aligns with current applications of spatial covariance in grassland conservation as a metric of early warning, variation, intactness, and boundary strength, not of central tendencies or dominance. Additional testing at different scales and in different ecosystem contexts will help to further understand how spatial covariance relates to other field vegetation metrics.

Arkansas↗

USGS2025

What is a specialist? Quantifying host breadth enables impact prediction for invasive herbivores

Herbivores are commonly classified as host specialists or generalists for various purposes, yet the definitions of these terms, and their intermediates, are often imprecise and ambiguous. We quantified host breadth for 240 non-native, tree-feeding insects in North America using phylogenetic diversity. We demonstrated that a partitioning of host breadth: (1) causes 67% of non-native insects to shift from a generalist to specialist category, (2) displays a reduction in host breadth from the native to introduced range, (3) identifies an inflection point in a model predicting the likelihood of non-native insect ecological impact, with a corresponding change in behaviour associated with specialists versus generalists, and (4) enables three models for strong prediction of whether a non-native forest insect will cause high impacts. Together, these results highlight the primacy of how herbivore host recognition and plant defences mediate whether novel host interactions will result in high impact after invasion.

Ecology Letters↗

USGS2025

Spatial regimes provide ample early warning of tipping points

Accelerating global change is a hallmark of the Anthropocene, and the interaction of rapid change in climate, land use and land cover makes understanding the response of social-ecological systems to global change difficult to predict. Global change directly and indirectly affects both social-ecological systems and the landscapes in which they are embedded. Spatial heterogeneity in the location, manifestation of, and responses to global change makes spatially explicit approaches to management and conservation necessary. Spatial regimes, a concept derived from resilience theory, are at the forefront of attempts to operationalize and quantify resilience of dynamic landscapes. Spatial regimes are defined as dynamic landscape units that are shaped by a self-organizing set of processes and structures. They have identifiable spatial extents with discrete boundaries at a given scale that exhibit relative homogeneity in process, structure and composition maintained by feedback mechanisms. Here, we describe the concept of, evidence for, and applications of spatial regimes and how spatial regimes relate to scale and telecoupling of change across social-ecological systems. We emphasize the utility of the concept as an early warning of regime change, one that can provide ample early warning. We discuss methods that can be used to detect spatial regimes and uses of the concept for understanding and managing the spatio-temporal response of social-ecological systems to global change.

Advances in Ecological Research↗

USGS2025

Reconciling scale using the Resist-Accept-Direct (RAD) Framework to improve management of woody encroachment in grasslands

Implementing strategies to navigate large-scale ecological transitions in grasslands is one of this century's greatest conservation challenges. In the US Great Plains, managing areas impacted by woody transitions have been reactive, short-lived, costly, and ineffective. Along with current technological innovation in rangeland monitoring, the promise of early warning science is to provide managers with sufficient time to be better prepared for novel signals of ecological change. Combining the science of early warning signals and frameworks such as the Resist – Accept – Direct (RAD) can provide land managers with guidelines to identify proactive strategies when facing ecological change. Using this approach, we found that opportunities to resist woody transitions decreased from 84 % to 60 % between 1990 and 2020 over the entire biome but remained highest in the northern and western Great Plains, which contributes to large scale conservation targets. These are key areas to prioritize resist opportunities. In contrast, 11 % of the biome exhibited early warning transition signals across all hierarchical scales by 2020, a fourfold increase since 1990. Lastly by 2020, 30 % of the biome exhibited early warning signals across multiple but not all scales. Here, efforts may be more effective when management is directed to conserve fragmented grassland legacies within a woody-dominated matrix and avoid large-scale monocultures of problematic encroaching woody species. Our multi-scale study indicates that 1) anchoring to the last remaining grassland core areas with no early warning of transitions and 2) strategically investing in these intact grasslands may provide the best results for grassland conservation.

Great Plains↗

USGS2024

Population increases of the threatened American burying beetle (Nicrophorus americanus) linked to large-scale collaborations in a working lands ecoregion

Woody plant encroachment and row-crop agricultural land conversion are existential threats to species that rely on grassland ecosystems. The American Burying Beetle ( Nicrophorus americanus ) is a threatened species whose largest remnant populations are predominantly located in grassland ecoregions comprised of privately-owned ranching lands. Here, we seek to determine functional scaling patterns and population trends of the American Burying Beetle in the face of conservation threats and grassland restoration. We used 13 years (2007–2019) of American Burying Beetle abundance data collected from permanent sampling locations across the Loess Canyons ecoregion (Nebraska, USA), where a network of ranchers have been restoring large-scale grasslands. To estimate beetle abundance relative to land cover variables, we developed a Bayesian N-mixture model, incorporating the Bayesian latent indicator scale selection (BLISS) method to probabilistically determine at which scales land cover variables best explained beetle abundance. American Burying Beetle abundance exhibited high interannual variation but overall significantly increased across the ecoregion. Increases in beetle abundance were associated with large-scale (1149 ha extent) grassland cover. Decreases in abundance were associated with large-scale crop conversion (590 ha extent) and large-scale increases in woody cover (1149 ha extent). This study provides the first evidence of ecoregion-scale population increases of the American Burying Beetle. These increases are tied to landscape variables that are managed in a large-scale, coordinated private lands grassland restoration effort. Our results suggest that successful grassland restoration will depend on coordinating across property boundaries to implement conservation at scales necessary to conserve species that require large-scale, unfragmented grasslands.

Nebraska↗

USGS2022

Phylogenetic risk assessment is robust for forecasting the impact of European insects on North American conifers

Some introduced species cause severe damage, although the majority have little impact. Robust predictions of which species are most likely to cause substantial impacts could focus efforts to mitigate those impacts or prevent certain invasions entirely. Introduced herbivorous insects can reduce crop yield, fundamentally alter natural and managed forest ecosystems, and are unique among invasive species in that they require certain host plants to succeed. Recent studies have demonstrated that understanding the evolutionary history of introduced herbivores and their host plants can provide robust predictions of impact. Specifically, divergence times between hosts in the native and introduced ranges of a nonnative insect can be used to predict the potential impact of the insect should it establish in a novel ecosystem. However, divergence time estimates vary among published phylogenetic datasets, making it crucial to understand if and how the choice of phylogeny affects prediction of impact. Here, we tested the robustness of impact prediction to variation in host phylogeny by using insects that feed on conifers and predicting the likelihood of high impact using four different published phylogenies. Our analyses ranked 62 insects that are not established in North America and 47 North American conifer species according to overall risk and vulnerability, respectively. We found that results were robust to the choice of phylogeny. Although published vascular plant phylogenies continue to be refined, our analysis indicates that those differences are not substantial enough to alter the predictions of invader impact. Our results can assist in focusing biosecurity programs for conifer pests and can be more generally applied to nonnative insects and their potential hosts by prioritizing surveillance for those insects most likely to be damaging invaders.

Ecological Applications↗

USGS2022

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R 2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes.

Kansas↗

USGS2022

Guiding principles for using satellite-derived maps in rangeland management

On the Ground Rangeland management has entered a new era with the accessibility and advancement of satellite-derived maps. Maps provide a comprehensive view of rangelands in space and time, and challenge us to think critically about natural variability. Here, we advance the practice of using satellite-derived maps with four guiding principles designed to increase end user confidence and thereby accessibility of these data for decision-making.

Idaho↗

USGS2021

Predicting non-native insect impact: Focusing on the trees to see the forest

Non-native organisms have invaded novel ecosystems for centuries, yet we have only a limited understanding of why their impacts vary widely from minor to severe. Predicting the impact of non-established or newly detected species could help focus biosecurity measures on species with the highest potential to cause widespread damage. However, predictive models require an understanding of potential drivers of impact and the appropriate level at which these drivers should be evaluated. Here, we used non-native, specialist herbivorous insects of forest ecosystems to test which factors drive impact and if there were differences based on whether they used woody angiosperms or conifers as hosts. We identified convergent and divergent patterns between the two host types indicating fundamental similarities and differences in their interactions with non-native insects. Evolutionary divergence time between native and novel hosts was a significant driver of insect impact for both host types but was modulated by different factors in the two systems. Beetles in the subfamily Scolytinae posed the highest risk to woody angiosperms, and different host traits influenced impact of specialists on conifers and woody angiosperms. Tree wood density was a significant predictor of host impact for woody angiosperms with intermediate densities (0.5–0.6 mg/mm 3 ) associated with highest risk, whereas risk of impact was highest for conifers that coupled shade tolerance with drought intolerance. These results underscore the importance of identifying the relevant levels of biological organization and ecological interactions needed to develop accurate risk models for species that may arrive in novel ecosystems.

Biological Invasions↗

USGS2021

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗

USGS2019

Evolutionary history predicts high-impact invasions by herbivorous insects

A long‐standing goal of invasion biology is to identify factors driving highly variable impacts of non‐native species. Although hypotheses exist that emphasize the role of evolutionary history (e.g., enemy release hypothesis & defense‐free space hypothesis), predicting the impact of non‐native herbivorous insects has eluded scientists for over a century. Using a census of all 58 non‐native conifer‐specialist insects in North America, we quantified the contribution of over 25 factors that could affect the impact they have on their novel hosts, including insect traits (fecundity, voltinism, native range, etc.), host traits (shade tolerance, growth rate, wood density, etc.), and evolutionary relationships (between native and novel hosts and insects). We discovered that divergence times between native and novel hosts, the shade and drought tolerance of the novel host, and the presence of a coevolved congener on a shared host, were more predictive of impact than the traits of the invading insect. These factors built upon each other to strengthen our ability to predict the risk of a non‐native insect becoming invasive. This research is the first to empirically support historically assumed hypotheses about the importance of evolutionary history as a major driver of impact of non‐native herbivorous insects. Our novel, integrated model predicts whether a non‐native insect not yet present in North America will have a one in 6.5 to a one in 2,858 chance of causing widespread mortality of a conifer species if established (R2 = 0.91) Synthesis and applications. With this advancement, the risk to other conifer host species and regions can be assessed, and regulatory and pest management efforts can be more efficiently prioritized.

Ecology and Evolution↗

USGS2018

Doublethink and scale mismatch polarize policies for an invasive tree

Mismatches between invasive species management policies and ecological knowledge can lead to profound societal consequences. For this reason, natural resource agencies have adopted the scientifically-based density-impact invasive species curve to guide invasive species management. We use the density-impact model to evaluate how well management policies for a native invader ( Juniperus virginiana ) match scientific guidelines. Juniperus virginiana invasion is causing a sub-continental regime shift from grasslands to woodlands in central North America, and its impacts span collapses in endemic diversity, heightened wildfire risk, and crashes in grazing land profitability. We (1) use land cover data to identify the stage of Juniperus virginiana invasion for three ecoregions within Nebraska, USA, (2) determine the range of invasion stages at individual land parcel extents within each ecoregion based on the density-impact model, and (3) determine policy alignment and mismatches relative to the density-impact model in order to assess their potential to meet sustainability targets and avoid societal impacts as Juniperus virginiana abundance increases. We found that nearly all policies evidenced doublethink and policy-ecology mismatches, for instance, promoting spread of Juniperus virginiana regardless of invasion stage while simultaneously managing it as a native invader in the same ecoregion. Like other invasive species, theory and literature for this native invader indicate that the consequences of invasion are unlikely to be prevented if policies fail to prioritize management at incipient invasion stages. Theory suggests a more realistic approach would be to align policy with the stage of invasion at local and ecoregion management scales. There is a need for scientists, policy makers, and ecosystem managers to move past ideologies governing native versus non-native invader classification and toward a framework that accounts for the uniqueness of native species invasions, their anthropogenic drivers, and their impacts on ecosystem services.

Nebraska↗

USGS2018

Thermal tolerance limits of the Chinese mystery snail (Bellamya chinensis): Implications for management

The Chinese mystery snail, Bellamya chinensis (Gray, 1834) is a gastropod native to East Asia and is considered an invasive species in North America where its impacts on native species and ecosystems are not well understood. Scientific literature describing its biology and life history are sparse. Thermal tolerance limits, or the maximum and minimum temperature under which a species can survive, are key to identifying the potential geographical range of a species. The ability of managers to control invasive species is directly impacted by the thermal tolerance limits of a species. We attempted to identify the thermal tolerance limits of B. chinensis in a laboratory setting. Using a random sampling design, we exposed groups of wild-caught B. chinensis to either extreme high or low temperature treatments. We identified the upper temperature tolerance limit as between 40 and 45 °C. This result indicates some hot water management techniques may successfully prevent spread of B. chinensis among waterways. Despite exposing B. chinensis to freezing temperatures for extended periods of time we did not identify a lower temperature limit. Identifying the thermal tolerance limits of this and other invasive species informs predictions of range expansion and identification of potential prevention efforts.

American Malacological Bulletin↗

USGS2017

Culturally induced range infilling of eastern redcedar: a problem in ecology, an ecological problem, or both?

The philosopher John Passmore distinguished between (1) “problems in ecology,” or what we might call problems in scientific understanding of ecological change, and (2) “ecological problems,” or what we might call problems faced by societies due to ecological change. The spread of eastern redcedar ( Juniperus virginiana ) and conversion of the central and southern Great Plains of North America to juniper woodland might be categorized as a problem in ecology, an ecological problem, or both. Here, we integrate and apply two interdisciplinary approaches to problem-solving—social-ecological systems thinking and ecocriticism—to understand the role of human culture in recognizing, driving, and responding to cedar’s changing geographic distribution. We interpret the spread of cedar as a process of culturally induced range infilling due to the ongoing social-ecological impacts of colonization, analyze poetic literary texts to clarify the concepts that have so far informed different cultural values related to cedar, and explore the usefulness of diverse interdisciplinary collaborations and knowledge for addressing social-ecological challenges like cedar spread in the midst of rapidly unfolding global change. Our examination suggests that it is not only possible, but preferable, to address cedar spread as both a scientific and a social problem. Great Plains landscapes are teetering between grassland and woodland, and contemporary human societies both influence and choose how to cope with transitions between these ecological states. We echo previous studies in suggesting that human cultural values about stability and disturbance, especially cultural concepts of fire, will be primary driving factors in determining future trajectories of change on the Great Plains. Although invasion-based descriptors of cedar spread may be useful in ecological research and management, language based on the value of restraint could provide a common vocabulary for effective cross-disciplinary and interdisciplinary communication about the relationship between culture and cedar, as well as an ethical framework for cross-cultural communication, decision-making, and management.

Ecology and Society↗

USGS2016

Avoiding decline: Fostering resilience and sustainability in midsize cities

Eighty-five percent of United States citizens live in urban areas. However, research surrounding the resilience and sustainability of complex urban systems focuses largely on coastal megacities (>1 million people). Midsize cities differ from their larger counterparts due to tight urban-rural feedbacks with their immediate natural environments that result from heavy reliance and close management of local ecosystem services. They also may be less path-dependent than larger cities due to shorter average connection length among system components, contributing to higher responsiveness among social, infrastructural, and ecological feedbacks. These distinct midsize city features call for a framework that organizes information and concepts concerning the sustainability of midsize cities specifically. We argue that an integrative approach is necessary to capture properties emergent from the complex interactions of the social, infrastructural, and ecological subsystems that comprise a city system. We suggest approaches to estimate the relative resilience of midsize cities, and include an example assessment to illustrate one such estimation approach. Resilience assessments of a midsize city can be used to examine why some cities end up on sustainable paths while others diverge to unsustainable paths, and which feedbacks may be partially responsible. They also provide insight into how city planners and decision makers can use information about the resilience of midsize cities undergoing growth or shrinkage relative to their larger and smaller counterparts, to transform them into long-term, sustainable social-ecological systems.

Sustainability↗

USGS2015

Predictions of future ephemeral springtime waterbird stopover habitat availability under global change

In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.

Nebraska↗