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USGS2025

Limited directional change in mountaintop plant communities over 19 years in western North America

Plant communities on mountain summits are commonly long-lived, cold-adapted perennials with low dispersal ability. These characteristics in tandem with limited area to track suitable conditions make these mountain communities potentially highly vulnerable to climate change, and indicators of climate change impacts. We investigated temporal changes in plant communities on 29 arid mountain summits across eight study regions in California and Nevada, USA, over 19 years. We analyzed community dynamics in terms of species richness, turnover, gain and loss of functional groups, and relative abundance of functional groups. First, across all summits and regions, we found no change in species richness over time. Second, there was relatively high species turnover (21.7%) between the five-year survey intervals, but turnover was not significantly different from random expectation. Within functional groups, forbs had the greatest proportion of gains and cushions had the greatest proportion of losses. Third, qualitative abundance categories presented a small but consistent signal of decrease in the relative abundance of cushions, graminoids, and shrubs/trees over the study period. Across a broad geographic scale and nearly two decades, community patterns were widely similar, suggesting that climate change has not impacted local colonization or extirpation of mountaintop species in this arid region. These findings support observed differences in response to climate change between temperature-limited and water-limited regions globally, and highlight the lagged and variable nature of high-elevation systems. Our findings fill a major data gap on alpine plant community responses to climate change in the western United States and bolster the importance of long-term ecological monitoring with rapid climate change.

California, Nevada↗

USGS2014

Freshwater availability and coastal wetland foundation species: ecological transitions along a rainfall gradient

Climate gradient-focused ecological research can provide a foundation for better understanding critical ecological transition points and nonlinear climate-ecological relationships, which is information that can be used to better understand, predict, and manage ecological responses to climate change. In this study, we examined the influence of freshwater availability upon the coverage of foundation plant species in coastal wetlands along a northwestern Gulf of Mexico rainfall gradient. Our research addresses the following three questions: (1) what are the region-scale relationships between measures of freshwater availability (e.g., rainfall, aridity, freshwater inflow, salinity) and the relative abundance of foundation plant species in tidal wetlands; (2) How vulnerable are foundation plant species in tidal wetlands to future changes in freshwater availability; and (3) What is the potential future relative abundance of tidal wetland foundation plant species under alternative climate change scenarios? We developed simple freshwater availability-based models to predict the relative abundance (i.e., coverage) of tidal wetland foundation plant species using climate data (1970-2000), estuarine freshwater inflow-focused data, and coastal wetland habitat data. Our results identify regional ecological thresholds and nonlinear relationships between measures of freshwater availability and the relative abundance of foundation plant species in tidal wetlands. In drier coastal zones, relatively small changes in rainfall could produce comparatively large landscape-scale changes in foundation plant species abundance which would affect some ecosystem good and services. Whereas a drier future would result in a decrease in the coverage of foundation plant species, a wetter future would result in an increase in foundation plant species coverage. In many ways, the freshwater-dependent coastal wetland ecological transitions we observed are analogous to those present in dryland terrestrial ecosystems.

Gulf Of Mexico↗

USGS2016

The relative contribution of climate to changes in lesser prairie-chicken abundance

Managing for species using current weather patterns fails to incorporate the uncertainty associated with future climatic conditions; without incorporating potential changes in climate into conservation strategies, management and conservation efforts may fall short or waste valuable resources. Understanding the effects of climate change on species in the Great Plains of North America is especially important, as this region is projected to experience an increased magnitude of climate change. Of particular ecological and conservation interest is the lesser prairie-chicken ( Tympanuchus pallidicinctus ), which was listed as “threatened” under the U.S. Endangered Species Act in May 2014. We used Bayesian hierarchical models to quantify the effects of extreme climatic events (extreme values of the Palmer Drought Severity Index [PDSI]) relative to intermediate (changes in El Niño Southern Oscillation) and long-term climate variability (changes in the Pacific Decadal Oscillation) on trends in lesser prairie-chicken abundance from 1981 to 2014. Our results indicate that lesser prairie-chicken abundance on leks responded to environmental conditions of the year previous by positively responding to wet springs (high PDSI) and negatively to years with hot, dry summers (low PDSI), but had little response to variation in the El Niño Southern Oscillation and the Pacific Decadal Oscillation. Additionally, greater variation in abundance on leks was explained by variation in site relative to broad-scale climatic indices. Consequently, lesser prairie-chicken abundance on leks in Kansas is more strongly influenced by extreme drought events during summer than other climatic conditions, which may have negative consequences for the population as drought conditions intensify throughout the Great Plains.

Ecosphere↗

USGS2018

Submerged aquatic vegetation mapping in coastal Louisiana through development of a spatial likelihood occurrence (SLOO) model

Determining the spatial distribution of coastal foundation species is essential to accurately determine restoration goals, predict the ecological effects of climate change, and develop habitat management strategies. Mapping the distribution of submerged aquatic vegetation (SAV) species assemblages, which provide important habitat resource and ecological services in Louisiana, has been difficult due to the dynamic nature of SAV occurrence and the limited water clarity across much of the coast. Species distribution models (SDMs) link ecological conditions species occurrence across landscapes, and can predict the distribution of species across un-sampled or hard to sample areas and support the development of habitat maps. To predict SAV distribution in coastal Louisiana, a SDM was developed and projected across the landscape to create a spatial likelihood of occurrence (SLOO) model describing the probability of SAV presence in aquatic habitats. SAV presence and absence data were examined from over 500 field observations in relation to physical and hydrologic variables, including exposure, turbidity, water level, and salinity. A binary logistic regression model (p < 0.0001) identified three significant predictors of SAV presence: mean winter salinity, exposure, and turbidity. As each of these variables increased, the probability of SAV presence in the summer growing season decreased. The spatial application of this SDM helps to predict the likelihood of occurrence across the coastal landscape, creating a valuable tool to describe un-sampled SAV habitat and estimate future changes in habitat availability.

Louisiana↗

USGS2025

Mountain sentinels in a changing world: Review and conservation implications of weather and climate effects on mountain goats (Oreamnos americanus)

Climate change is occurring at an accelerated rate in high-elevation alpine and mountain ecosystems. Cold-adapted, mountain species are at risk due to forecasted change and knowledge is needed to respond to current and future conservation challenges. Mountain goats ( Oreamnos americanus ) are an iconic species of North American mountain cultures and landscapes, and due to specialized adaptations for life in cold, mountainous environments they are particularly sensitive to changes in weather and climate. As sentinels of change in alpine ecosystems, the study of mountain goats offers insight into the ecological effects and conservation challenges associated with climate change in these sensitive and biodiverse environments. Here, we synthesize existing knowledge about how climate change is expected to influence environmental conditions experienced by mountain goats and associated mechanistic changes to behavior, nutritional ecology, demography, health, and interspecific interactions. In many instances, climate change effects are likely to be negative and additive to existing threats (such as human disturbance, hunting, disease, predation) though benefits are expected in some cases. Changes in climate and mountain environments will necessitate re-examination and modification of population monitoring, management, and conservation strategies. Specifically, spatiotemporal (and other) aspects of monitoring and management may need to be adjusted to accommodate emerging and novel conservation challenges. Yet, key data and knowledge gaps remain and should be addressed to advance conservation and decision-making capabilities. For mountain goats and similarly climate-sensitive alpine herbivores, effective conservation will ultimately benefit from collaborations among diverse networks guided by well-planned, strategic visions focused on common ground – namely the resiliency and persistence of culturally and ecologically significant mountain species and the alpine environment they inhabit.

Alaska, Alberta, British Columbia, Idaho, Montana,↗

USGS2012

Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis

Introduction Evaluating the environmental impacts of climate change on water resources and biological components of the landscape is an integral part of hydrologic and ecological investigations, and the resultant land and resource management in the twenty-first century. Impacts of both climate and simulated hydrologic parameters on ecological processes are relevant at scales that reflect the heterogeneity and complexity of landscapes. At present, simulations of climate change available from global climate models [GCMs] require downscaling for hydrologic or ecological applications. Methods Using statistically downscaled future climate projections developed using constructed analogues, a methodology was developed to further downscale the projections spatially using a gradient-inverse-distance-squared approach for application to hydrologic modeling at 270-m spatial resolution. Results This paper illustrates a methodology to downscale and bias-correct national GCMs to subkilometer scales that are applicable to fine-scale environmental processes. Four scenarios were chosen to bracket the range of future emissions put forth by the Intergovernmental Panel on Climate Change. Fine-scale applications of downscaled datasets of ecological and hydrologic correlations to variation in climate are illustrated. Conclusions The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.

Ecological Processes↗

USGS2018

Climate change and future wildfire in the western USA: An ecological approach to nonstationarity

We developed ecologically based climate‐fire projections for the western United States. Using a finer ecological classification and fire‐relevant climate predictors, we created statistical models linking climate and wildfire area burned for ecosections, which are geographic delineations based on biophysical variables. The results indicate a gradient from purely fuel‐limited (antecedent positive water balance anomalies or negative energy balance anomalies) to purely flammability‐limited (negative water balance anomalies or positive energy balance anomalies) fire regimes across ecosections. Although there are other influences (such as human ignitions and management) on fire occurrence and area burned, seasonal climate significantly explains interannual fire area burned. Differences in the role of climate across ecosections are not random, and the relative dominance of climate predictors allows objective classification of ecosection climate‐fire relationships. Expected future trends in area burned range from massive increases, primarily in flammability limited systems near the middle of the water balance deficit distribution, to substantial decreases, in fuel‐limited nonforested systems. We predict increasing area burned in most flammability‐limited systems but predict decreasing area burned in primarily fuel‐limited systems with a flammability‐limited (“hybrid”) component. Compared to 2030–2059 (2040s), projected area burned for 2070–2099 (2080s) increases much more in the flammability and flammability‐dominated hybrid systems than those with equal control and continues to decrease in fuel‐limited hybrid systems. Exceedance probabilities for historical 95th percentile fire years are larger in exclusively flammability‐limited ecosections than in those with fuel controls. Filtering the projected results using a fire‐rotation constraint minimizes overprojection due to static vegetation assumptions, making projections more conservative.

Earth's Future↗

USGS2017

Skagit River coho salmon life history model—Users’ guide

Natural resource management is conducted in the context of multiple anthropogenic stressors and is further challenged owing to changing climate. Experiments to determine the effects of climate change on complex ecological systems are nearly impossible. However, using a simulation model to synthesize current understanding of key ecological processes through the life cycle of a fish population can provide a platform for exploring potential effects of and management responses to changing conditions. Potential climate-change scenarios can be imposed, responses can be observed, and the effectiveness of potential actions can be evaluated. This approach is limited owing to future conditions likely deviating in range and timing from conditions used to create the model so that the model is expected to become obsolete. In the meantime, however, the modeling process explicitly states assumptions, clarifies information gaps, and provides a means to better understand which relationships are robust and which are vulnerable to changing climate by observing whether and why model output diverges from actual observations through time. The purpose of the model described herein is to provide such a decision-support tool regarding coho ( Oncorhynchus kisutch ) salmon for the Sauk-Suiattle Indian Tribe of Washington State. The Skagit coho salmon model is implemented in a system dynamics format and has three primary stocks—(1) predicted smolts, (2) realized smolts, and (3) escapement. “Predicted smolts” are the number of smolts expected based on the number of spawners in any year and the Ricker production curve. Pink salmon ( Oncorhynchus gorbuscha ) return to the Skagit River in odd years, and when they overlap with juvenile rearing coho salmon, coho smolt production is substantially higher than in non-pink years. Therefore, the model uses alternative Ricker equations to predict smolts depending on whether their juvenile year was a pink or non-pink year. The stock “realized smolts” is calculated based on the expected effect of streamflow conditions to alter the productivity predicted by the Ricker curve. Adverse conditions include scouring flow events that occur when redds are present; high-flow events during winter on juveniles, which can cause fish displacement and adverse water turbidity; and extremely low flows in summer. The stock “escapement” represents the fish remaining after accounting for ocean mortality and harvest. Ocean mortality has been linked with indices of ocean conditions, which are related to ocean biological productivity. Ocean survival also may have a density-dependent component such that lower survival is associated with higher numbers of smolts. The model allows the user to change certain model parameters and inputs, and choose among alternative predictors for certain modeled relations.

Washington↗

USGS2019

Natural resource management decision-making under climate uncertainty: Building social-ecological resilience in southwestern Colorado

The goal of this project was to facilitate climate change adaptation that contributes to social-ecological resilience, ecosystem and species conservation, and sustainable human communities in southwestern Colorado. The team developed and piloted integrated adaptation planning tools and principles that merge the strengths of the iterative scenario process, the Adaptation for Conservation Targets (ACT) planning framework, institutional analysis, and climate modeling. These tools and principles generated practical strategies and scientific knowledge to advance climate change adaptation in both the Gunnison River Basin and San Juan River Basin and, potentially, other landscapes. A key objective of this project was to work with decision-makers to develop social-ecological adaptation strategies and coordinate actions to reduce the impacts of a changing climate on nature and people. To accomplish this, the project blended science (biophysical and social) and participatory approaches to integrate expert knowledge, land management decision making, and local needs. These adaptation strategies and their creation process were documented by the project team to assist communities and scientists elsewhere who are grappling with the challenges posed by climate change.

Colorado↗

USGS2016

The story of rising voices: Facilitating collaboration between indigenous and western ways of knowing

Indigenous community self-determination, cultures, and ways of life are at high risk from climate change impacts and ecological dispossession. Partnerships between experts with backgrounds in Indigenous and western knowledge may be productive and effective ways to reduce vulnerability and foster resilience. This chapter examines collaborations among scientific and Native American, Alaska Native, and Pacific Island communities to support climate solutions. We draw examples from the "Rising Voices: Collaborative Science with Indigenous Knowledge for Climate Solutions" program (Rising Voices) to examine how boundary organizations function cross-culturally to increase communities' adaptive capacity through knowledge exchange, as well as building the decision-making capacity needed to exercise sovereignty and make adaptive decisions in a changing climate.

Book chapter↗

USGS2025

Microbial ecology of permafrost soils: Populations, processes, and perspectives

Permafrost microbial research has flourished in the past decades, due in part to improvements in sampling and molecular techniques, but also the increased focus on the permafrost greenhouse gas feedback to climate change and other ecological processes in high latitude and alpine permafrost soils. Permafrost microorganisms are adapted to these extreme environments and remain active at low temperatures and when resources are limited. They are also an important component of global elemental cycles as they regulate organic matter turnover and greenhouse gas production, particularly as permafrost thaws. Here we review the permafrost microbiology literature coupled with an exploration of its historical aspects, with a particular focus on a new understanding advanced by molecular biology techniques. We further identify knowledge gaps and ways forward to improve our understanding of microbial contributions to ecosystem biogeochemistry of permafrost-affected systems.

Permafrost and Periglacial Processes↗

USGS2019

Selecting a landscape model for natural resource management applications

Purpose of Review: Climate change and associated ecological impacts have challenged many conventional, observation-based approaches for predicting ecosystem and landscape responses to natural resource management. Complex spatial ecological models provide powerful, flexible tools which managers and others can use to make inferences about management impacts on future, no-analog landscape conditions. However, land managers who wish to use ecosystem and landscape models for natural resource applications are faced with the difficult task of deciding among many models that differ in important ways. Here, we summarize a process to aid managers in the selection of an appropriate model for natural resource management. Recent Findings: To guide management planning, scientifically credible information on how landscapes will respond to management actions under changing climate is required. Landscape models are increasingly used in a management context to evaluate of impacts of changing climate and interacting stressors on ecosystems and to test effects of alternative management options on desired conditions. However, the wide range of available models makes selection of appropriate and viable models a complex process. Summary: We present a series of preliminary steps to define critical scales of time, space, and ecological organization to guide an experimental design for a modeling project and then list a set of criteria for selecting a landscape or ecological model. Material presented includes the preliminary steps (crafting modeling objective, designing modeling project), organizational concerns (resources available, expertise on hand, timelines), and modeling details (complexity, design, documentation) of model selection.

Current Landscape Ecology Reports↗

USGS2017

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Sonoran Desert↗

USGS2011

Predicting phenology by integrating ecology, evolution and climate science

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology – the timing of life‐history events. Phenology has well‐demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species’ reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Global Change Biology↗

USGS2011

Seeing the forest and the trees: USGS scientist links local changes to global scale

The recent recipient of two major awards, Craig D. Allen, a research ecologist with the U.S. Geological Survey Fort Collins Science Center, has loved trees since childhood. He is now considered an expert of world renown on the twin phenomena of forest changes and tree mortality resulting from climate warming and drought, and in 2010 was twice recognized for his scientific contributions. In December 2010, Dr. Allen was named a 2010 Fellow of the American Association for the Advancement of Science “for outstanding leadership in the synthesis of global forest responses to climate change, built from worldwide collaboration and a deep understanding of the environmental history of the southwestern United States.” In March 2010, he was honored with the Meritorious Service Award from the U.S. Department of the Interior (DOI) in recognition of his outstanding vision, initiative, and scientific contributions to the USGS, DOI, and U.S. Department of Agriculture in establishing a model science program to support adaptive land management at the new Valles Caldera National Preserve in north-central New Mexico. Dr. Allen has authored more than 85 publications on landscape ecology and landscape change, from fire history and ecology to ecosystem responses to climate change. He has appeared on NOVA discussing fire ecology and on The Discovery Channel and Discovery Canada explaining the links between drought-induced tree mortality and climate warming, in addition to being interviewed and quoted in innumerable newspaper articles on both topics. But how did this unassuming scientist grow from nurturing maple saplings on 40 acres in Wisconsin to understanding forest system stress worldwide?

Report↗

USGS2020

Climate change can drive marine diseases

As an ultimate driver of marine ecosystem processes, climate change is expected to influence proximate disease drivers in marine systems. The observable effects of climate change, including changes in temperature, hypoxia, CO 2 accumulation, precipitation, and storm and cyclone frequencies and intensities, may directly act as proximate drivers of marine disease, especially in poikilotherms. These climate-driven changes are expected to result in the active and passive movement of pathogens and hosts into previously naïve geographical areas, thereby disrupting the long-evolved, stable host–pathogen relationships. Additionally, large-scale ecological changes stemming from climate change are expected to impact pathogen virulence and host susceptibilities. These real and anticipated changes present evolving challenges for resource managers who are charged with managing stochastic marine diseases in a constantly changing environment.

Book chapter↗

USGS2012

A national geographic framework for guiding conservation on a landscape scale

The U.S. Fish and Wildlife Service, along with the global conservation community, has recognized that the conservation challenges of the 21st century far exceed the responsibilities and footprint of any individual agency or program. The ecological effects of climate change and other anthropogenic stressors do not recognize geopolitical boundaries and, as such, demand a national geographic framework to provide structure for cross-jurisdictional and landscape-scale conservation strategies. In 2009, a new map of ecologically based conservation regions in which to organize capacity and implement strategic habitat conservation was developed using rapid prototyping and expert elicitation by an interagency team of U.S. Fish and Wildlife Service and U.S. Geological Survey scientists and conservation professionals. Incorporating Bird Conservation Regions, Freshwater Ecoregions, and U.S. Geological Survey hydrologic unit codes, the new geographic framework provides a spatial template for building conservation capacity and focusing biological planning and conservation design efforts. The Department of Interior's Landscape Conservation Cooperatives are being organized in these new conservation regions as multi-stakeholder collaborations for improved conservation science and management.

Journal of Fish and Wildlife Management↗

USGS2024

Incorporating projected climate conditions to map future riparian refugia

Identifying areas expected to remain buffered from climate change and maintain biodiversity and ecological function (i.e., climate refugia) is important for climate adaptation planning. As structurally diverse transitional zones between terrestrial and aquatic environments, riparian areas are often biological hotspots and provide critical corridors for species movement, particularly in arid and semi-arid regions. In our study region in the western and central USA, identifying riparian areas that could serve as climate refugia is a priority for wildlife managers. We mapped areas with connected riparian habitats that, based on landscape diversity and projected changes in summer temperatures and landscape runoff, are expected to serve as climate refugia. To incorporate uncertainty and balance the need for near- and long-term planning, we mapped potential refugia for 2 future time periods (2040–2069, 2070–2099) based on 2 climate models that represented divergent but plausible climate outcomes. The approach we developed is not constrained by physiology or behavior of target species and can be used to identify areas expected to fare comparatively well under a wide range of future climate scenarios. Our approach can also be used to identify areas where restoration could increase riparian connectedness and climate resilience.

Colorado, Indiana, Kansas, Montana, North Dakota, ↗