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USGS2026

Climate-driven waterline variability along the North American West Coast

Sandy coasts are highly dynamic environments shaped by a myriad of hydro-sedimentary processes operating across various spatio-temporal scales. From seasonal to centennial timescales, sandy beach dynamics are strongly influenced by climate variability expressed in various forms, including seasonal cycles, climate modes (e.g., El Niño Southern Oscillation (ENSO)), and global warming. Satellite-based methods enable the observation of coastlines with unprecedented spatial and temporal coverage. However, over the past decade, as these methods have matured, coastal change studies have predominantly focused on long-term trends rather than on climate-driven cycles of shoreline change. In this study, we utilize a large dataset of monthly-sampled time series of waterline positions along the Pacific Coast of the United States and Baja California, Mexico. From these time series, we derived information on long-term trends and seasonal cycles of waterline change. Our analysis reveals clear contrasts in seasonal patterns of waterline variability across the study area, with greater amplitudes observed at higher latitudes. A shift in the dominant dynamics is evident in Southern Baja California, where shoreline variability is more influenced by intertropical dynamics and sea-level anomalies than by wave energy modulation, which dominates further north. ENSO is found to induce contrasting responses of the waterline along the study area. During El Niño events, shoreline retreat is observed in subtropical regions, while La Niña winters drive waterline retreat in higher latitudes, with southern regions either remaining stable or advancing.

Baja California, California, Oregon, Washington↗

USGS2015

A model for evaluating stream temperature response to climate change in Wisconsin

Expected climatic changes in air temperature and precipitation patterns across the State of Wisconsin may alter future stream temperature and flow regimes. As a consequence of flow and temperature changes, the composition and distribution of fish species assemblages are expected to change. In an effort to gain a better understanding of how climatic changes may affect stream temperature, an approach was developed to predict and project daily summertime stream temperature under current and future climate conditions for 94,341 stream kilometers across Wisconsin. The approach uses a combination of static landscape characteristics and dynamic time-series climatic variables as input for an Artificial Neural Network (ANN) Model integrated with a Soil-Water-Balance (SWB) Model. Future climate scenarios are based on output from downscaled General Circulation Models (GCMs). The SWB model provided a means to estimate the temporal variability in groundwater recharge and provided a mechanism to evaluate the effect of changing air temperature and precipitation on groundwater recharge and soil moisture. The Integrated Soil-Water-Balance and Artificial Neural Network version 1 (SWB-ANNv1) Model was used to simulate daily summertime stream temperature under current (1990–2008) climate and explained 76 percent of the variation in the daily mean based on validation at 67 independent sites. Results were summarized as July mean water temperature, and individual stream segments were classified by thermal class (cold, cold transition, warm transition, and warm) for comparison of current (1990–2008) with future climate conditions. Integrating the SWB Model with the ANN Model provided a mechanism by which downscaled global or regional climate model results could be used to estimate the potential effects of climate change on future stream temperature on a daily time step. To address future climate scenarios, statistically downscaled air temperature and precipitation projections from 10 GCMs and 2 time periods were used with the SWB-ANNv1 Model to project future stream temperature. Projections of future stream temperatures at mid- (2046–65) and late- (2081–2100) 21st century showed the July mean water temperature increasing for all stream segments with about 80 percent of stream kilometers increasing by 1 to 2 degrees Celsius (°C) by mid-century and about 99 percent increasing by 1 to 3 °C by late-century. Projected changes in stream temperatures also affected changes in thermal classes with a loss in the total amount of cold-water, cold-transition, and warm-transition thermal habitat and a gain in warm-water and very warm thermal habitat for both mid- and late-21st century time periods. The greatest losses occurred for cold-water streams and the greatest gains for warm-water streams, with a contraction of cold-water streams in the Driftless Area of western and southern Wisconsin and an expansion of warm-water streams across northern Wisconsin. Results of this study suggest that such changes will affect the composition of fish assemblages, with a loss of suitable habitat for cold-water fishes and gain in suitable habitat for warm-water fishes. In the end, these projected changes in thermal habitat attributable to climate may result in a net loss of fisheries, because many warm-water species may be unable to colonize habitats formerly occupied by cold-water species because of other habitat limitations (e.g., stream size, gradient). Although projected stream temperatures may vary greatly, depending on the emissions scenario and models used, the results presented in this report represent one possibility. The relative change in stream temperature can provide useful information for planning for potential climate impacts to aquatic ecosystems. Model results can be used to help identify vulnerabilities of streams to climate change, guide stream surveys and thermal classifications, prioritize the allocation of scarce financial resources, identify approaches to climate adaptation to best protect and enhance resiliency in stream thermal habitat, and provide information to make quantitative assessments of statewide stream resources.

Wisconsin↗

USGS2023

Connecting research and practice to enhance the evolutionary potential of species under climate change

Resource managers have rarely accounted for evolutionary dynamics in the design or implementation of climate change adaptation strategies. We brought the research and management communities together to identify challenges and opportunities for applying evidence from evolutionary science to support on-the-ground actions intended to enhance species' evolutionary potential. We amalgamated input from natural-resource practitioners and interdisciplinary scientists to identify information needs, current knowledge that can fill those needs, and future avenues for research. Three focal areas that can guide engagement include: (1) recognizing when to act, (2) understanding the feasibility of assessing evolutionary potential, and (3) identifying best management practices. Although researchers commonly propose using molecular methods to estimate genetic diversity and gene flow as key indicators of evolutionary potential, we offer guidance on several additional attributes (and their proxies) that may also guide decision-making, particularly in the absence of genetic data. Finally, we outline existing decision-making frameworks that can help managers compare alternative strategies for supporting evolutionary potential, with the goal of increasing the effective use of evolutionary information, particularly for species of conservation concern. We caution, however, that arguing over nuance can generate confusion; instead, dedicating increased focus on a decision-relevant evidence base may better lend itself to climate adaptation actions.

Conservation Science and Practice↗

USGS2020

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R 2 , RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year ( p < 0.01), and harvesting dates were delayed by 0.78 days/year ( p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2013

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO 2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

South Dakota↗

USGS2017

Recent stability of resident and migratory landbird populations in National Parks of the Pacific Northwest

Monitoring species in National Parks facilitates inference regarding effects of climate change on population dynamics because parks are relatively unaffected by other forms of anthropogenic disturbance. Even at early points in a monitoring program, identifying climate covariates of population density can suggest vulnerabilities to future change. Monitoring landbird populations in parks during the breeding season brings the added benefit of allowing a comparative approach to inference across a large suite of species with diverse requirements. For example, comparing resident and migratory species that vary in exposure to non-park habitats can reveal the relative importance of park effects, such as those related to local climate. We monitored landbirds using breeding-season point-count data collected during 2005–2014 in three wilderness areas of the Pacific Northwest (Mount Rainier, North Cascades, and Olympic National Parks). For 39 species, we estimated recent trends in population density while accounting for individual detection probability using Bayesian hierarchical N -mixture models. Our analyses integrated several recent developments in N -mixture modeling, incorporating interval and distance sampling to estimate distinct components of detection probability while also accommodating count intervals of varying duration, annual variation in the length and number of point-count transects, spatial autocorrelation, random effects, and covariates of detection and density. As covariates of density, we considered metrics of precipitation and temperature hypothesized to affect breeding success. We also considered effects of park and elevational stratum on trend. Regardless of model structure, we estimated stable or increasing densities during 2005–2014 for most populations. Mean trends across species were positive for migrants in every park and for residents in one park. A recent snowfall deficit in this region might have contributed to the positive trend, because population density varied inversely with precipitation-as-snow for both migrants and residents. Densities varied directly but much more weakly with mean spring temperature. Our approach exemplifies an analytical framework for estimating trends from point-count data, and for assessing the role of climatic and other spatiotemporal variables in driving those trends. Understanding population trends and the factors that drive them is critical for adaptive management and resource stewardship in the context of climate change.

Ecosphere↗

USGS2021

Current activity on the Martian surface: A key subject for future exploration

One of the fundamental discoveries in Mars science in the last decade has been the extent and importance of current surface activity. Recent results have shifted our view of Mars from a world where the most interesting geologic events were in the distant past (similar to the Moon) to a world that undergoes active evolution and one where understanding the present is key to deciphering the planet’s history. When input was requested for the last Planetary Science Decadal Survey, some observations of surface changes had been published, but the number of detections was small and their significance not fully appreciated. Since that time, detections have proliferated, driven primarily by the long-term operation of the Mars Reconnaissance Orbiter (MRO) and the High Resolution Imaging Science Experiment (HiRISE) as well as landed observations of aeolian activity. In addition to observed changes, theory suggests that additional important surface processes are likely active but not yet observed because orbital data are limited in space and time and landed studies are rare. Understanding current Martian surface processes is a fundamental science question in itself, as it provides a test for physical and terrestrial analog-based models of specific geological processes acting under non-Earth planetary and environmental conditions. It is also an essential step for reading Mars’ geologic history and providing input to climate models: without understanding current dynamic processes, we cannot understand how they have varied during recent climate cycles, nor how they are reflected in ancient rock or modern ice records. Understanding the rates and types of current surface activity is also highly relevant to selecting geological samples, setting Planetary Protection rules, and understanding the hazards and environment that would be experienced by future human explorers.

Bulletin of the AAS↗

USGS2026

Assessing future hydrologic extremes using an integrated hydrology and river operations model in the Russian River watershed

Study region The Russian River watershed, situated in coastal, northern California, experiences hydrologic extremes, including periodic droughts and flooding. Water managers are working to maintain sustainable water supplies and environmental flows, while mitigating flood risks. Study focus This paper introduces an integrated hydrology and river operations model for the Russian River watershed. This model is distinct from models in previous studies because it represents surface-groundwater interactions and uses climate forcings to estimate dynamic water use demands that are superimposed onto both reservoir operations and water supply constraints. The model was used to examine three historical (1990–2015) and eight future (2016–2099) water use and climate change scenarios. New hydrological insights for the region The direct connection between streams and aquifers facilitated both annual aquifer replenishment by high winter streamflows and streamflow depletion by groundwater wells (19 % of pumped groundwater in alluvial aquifers from stream leakage) during critical low flow periods. Simulated streamflow changes included 59 % longer and 54 % more severe streamflow droughts, 26 % lower seasonal low streamflows, and up to 125 % higher peak streamflows, averaged over future climate and water use scenarios, suggesting increased future flood and water availability risks. Results showed the importance of reservoir operations for mitigating the impacts of increased hydroclimatic volatility, despite a decrease in reservoir reliability at Lake Mendocino, suggesting that reservoir management may be used to decrease future risks.

California↗

USGS2017

Woody vegetation die off and regeneration in response to rainfall variability in the west African Sahel

The greening in the Senegalese Sahel has been linked to an increase in net primary productivity, with significant long-term trends being closely related to the woody strata. This study investigates woody plant growth and mortality within greening areas in the pastoral areas of Senegal, and how these dynamics are linked to species diversity, climate, soil and human management. We analyse woody cover dynamics by means of multi-temporal and multi-scale Earth Observation, satellite based rainfall and in situ data sets covering the period 1994 to 2015. We find that favourable conditions (forest reserves, low human population density, sufficient rainfall) led to a rapid growth of Combretaceae and Balanites aegyptiaca between 2000 and 2013 with an average increase of 4% woody cover. However, the increasing dominance and low drought resistance of drought prone species bears the risk of substantial woody cover losses following drought years. This was observed in 2014–2015, with a die off of Guiera senegalensis in most places of the study area. We show that woody cover and woody cover trends are closely related to mean annual rainfall, but no clear relationship with rainfall trends was found over the entire study period. The observed spatial and temporal variation contrasts with the simplified labels of “greening” or “degradation”. While in principal a low woody plant diversity negatively impacts regional resilience, the Sahelian system is showing signs of resilience at decadal time scales through widespread increases in woody cover and high regeneration rates after periodic droughts. We have reaffirmed that the woody cover in Sahel responds to its inherent climatic variability and does not follow a linear trend.

Senegalese Sahel↗

USGS2015

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change ( γ sensitivity) of −14 to −19 Pg C °C −1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.

Philosophical Transactions of the Royal Society A:↗

USGS2021

Factors influencing distributional shifts and abundance at the range core of a climate-sensitive mammal

Species are frequently responding to contemporary climate change by shifting to higher elevations and poleward to track suitable climate space. However, depending on local conditions and species’ sensitivity, the nature of these shifts can be highly variable and difficult to predict. Here, we examine how the American pika ( Ochotona princeps ), a philopatric, montane lagomorph, responds to climatic gradients at three spatial scales. Using mixed-effects modeling in an information-theoretic approach, we evaluated a priori model suites regarding predictors of site occupancy, relative abundance, and elevational-range retraction across 760 talus patches, nested within 64 watersheds across the Northern Rocky Mountains of North America, during 2017–2020. The top environmental predictors differed across these response metrics. Warmer temperatures in summer and winter were associated with lower occupancy, lower relative abundances, and greater elevational retraction across watersheds. Occupancy was also strongly influenced by habitat patch size, but only when combined with climate metrics such as actual evapotranspiration. Using a second analytical approach, acute heat stress and summer precipitation best explained retraction residuals (i.e., the relative extent of retraction given the original elevational range of occupancy). Despite the study domain occurring near the species’ geographic-range center, where populations might have higher abundances and be at lower risk of climate-related stress, 33.9% of patches showed evidence of recent extirpations. Pika-extirpated sites averaged 1.44℃ warmer in summer than did occupied sites. Additionally, the minimum elevation of pika occupancy has retracted upslope in 69% of watersheds (mean: 281 m). Our results emphasize the nuance associated with evaluating species’ range dynamics in response to climate gradients, variability, and temperature exceedances, especially in regions where species occupy gradients of conditions that may constitute multiple range edges. Furthermore, this study highlights the importance of evaluating diverse drivers across response metrics to improve the predictive accuracy of widely used, correlative models.

Idaho, Montana↗

USGS2023

Divergent community trajectories with climate change across a fine-scale gradient in snow depth

Fine-scale microclimate variation due to complex topography can shape both current vegetation distributional patterns and how vegetation responds to changing climate. Topographic heterogeneity in mountains is hypothesized to mediate responses to regional climate change at the scale of metres. For alpine vegetation especially, the interplay between changing temperatures and topographically mediated variation in snow accumulation will determine the overall impact of climate change on vegetation dynamics. We combined 30 years of co-located measurements of temperature, snow and alpine plant community composition in Colorado, USA, to investigate vegetation community trajectories across a snow depth gradient. Our analysis of long-term trends in plant community composition revealed notable directional change in the alpine vegetation with warming temperatures. Furthermore, community trajectories are divergent across the snow depth gradient, with exposed parts of the landscape that experience little snow accumulation shifting towards stress-tolerant, cold- and drought-adapted communities, while snowier areas shifted towards more warm-adapted communities. Synthesis : Our findings demonstrate that fine-scale topography can mediate both the magnitude and direction of vegetation responses to climate change. We documented notable shifts in plant community composition over a 30-year period even though alpine vegetation is known for slow dynamics that often lag behind environmental change. These results suggest that the processes driving alpine plant population and community dynamics at this site are strong and highly heterogeneous across the complex topography that is characteristic of high-elevation mountain systems.

Journal of Ecology↗

USGS2016

Observations and modeling of fjord sedimentation during the 30 year retreat of Columbia Glacier, AK

To explore links between glacier dynamics, sediment yields and the accumulation of glacial sediments in a temperate setting, we use extensive glaciological observations for Columbia Glacier, Alaska, and new oceanographic data from the fjord exposed during its retreat. High-resolution seismic data indicate that 3.2 × 10 8 m 3 of sediment has accumulated in Columbia Fjord over the past three decades, which corresponds to ~5 mm a −1 of erosion averaged over the glaciated area. We develop a general model to infer the sediment-flux history from the glacier that is compatible with the observed retreat history, and the thickness and architecture of the fjord sediment deposits. Results reveal a fivefold increase in sediment flux from 1997 to 2000, which is not correlated with concurrent changes in ice flux or retreat rate. We suggest the flux increase resulted from an increase in the sediment transport capacity of the subglacial hydraulic system due to the retreat-related steepening of the glacier surface over a known subglacial deep basin. Because variations in subglacial sediment storage can impact glacial sediment flux, in addition to changes in climate, erosion rate and glacier dynamics, the interpretation of climatic changes based on the sediment record is more complex than generally assumed.

Alaska↗

USGS2022

Warming conditions boost reproductive output for a northern gopher tortoise population

The effects of climate change on at-risk species will depend on how life history processes respond to climate and whether the seasonal timing of local climate changes overlaps with species-specific windows of climate sensitivity. For long-lived, iteroparous species like gopher tortoises Gopherus polyphemus , climate likely has a greater influence on reproduction than on adult survival. Our objective was to estimate the timing, magnitude, and direction of climate-driven effects on gopher tortoise reproductive output using a 25 yr dataset collected in southeastern Georgia, USA, near the northern edge of the species’ range. We assessed the timing of climate effects on reproductive output (both probability of reproduction and clutch size) by fitting models with climate covariates (maximum temperature, precipitation, and temperature range) summarized at all possible time intervals (in 1 mo increments) within the 24 mo period prior to the summer census date. We then fit a final model of reproductive output as a function of the identified climate variables and time windows using a Bayesian mixture model. Probability of reproduction was positively correlated with the prior year’s April-May maximum temperature, and clutch size was positively correlated with the prior year’s June maximum temperature. April-May and June maximum temperatures have increased over the past 3 decades at the study site, which likely led to an increase in clutch size of approximately 1 egg (15% increase over a mean of 6.5 eggs). However, the net effect of climate change on gopher tortoise population dynamics will depend on whether there are opposing or reinforcing climate responses for other demographic rates.

Georgia↗

USGS2014

Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest

A warming climate influences boreal forest productivity, dynamics, and disturbance regimes. We used ecosystem models and 250 m satellite Normalized Difference Vegetation Index (NDVI) data averaged over the growing season (GSN) to model current, and estimate future, ecosystem performance. We modeled Expected Ecosystem Performance (EEP), or anticipated productivity, in undisturbed stands over the 2000–2008 period from a variety of abiotic data sources, using a rule-based piecewise regression tree. The EEP model was applied to a future climate ensemble A1B projection to quantify expected changes to mature boreal forest performance. Ecosystem Performance Anomalies (EPA), were identified as the residuals of the EEP and GSN relationship and represent performance departures from expected performance conditions. These performance data were used to monitor successional events following fire. Results suggested that maximum EPA occurs 30–40 years following fire, and deciduous stands generally have higher EPA than coniferous stands. Mean undisturbed EEP is projected to increase 5.6% by 2040 and 8.7% by 2070, suggesting an increased deciduous component in boreal forests. Our results contribute to the understanding of boreal forest successional dynamics and its response to climate change. This information enables informed decisions to prepare for, and adapt to, climate change in the Yukon River Basin forest.

Alaska↗

USGS2018

Effect of climate change on disease spread in wildlife

A growing body of evidence indicates that climate change alone, or acting synergistically with current anthropogenic threats, is affecting the health of wild populations of aquatic and terrestrial wildlife. Measurable by-products of climate change include elevated atmospheric concentrations of greenhouse gases, higher average global temperatures; variations in global precipitation patterns, rising and warming oceans, altered hydrographs of rivers, and increased mid-continental drying during summer. These consequences affect the terrestrial environment through shifts in phenology, vegetation cover, and fire regimes. Warmer ocean temperatures, increased acidification, rise in sea levels, and reduction in sea ice cover are also leading to widespread ecological changes in marine systems. Wildlife populations face a variety of climate-related pressures, such as changes in animal distribution or density, limitation of food resources, and alteration to critical habitats. The increased potential for emergence and resurgence of diseases that are responsive to environmental conditions also has implications for wildlife populations. Shifts in temperature or other climatic factors may directly affect the incidence of disease in wildlife by altering host-pathogen interactions, promoting vector populations or allowing new ranges for vectors, or reducing development times for parasites. A number of examples from both field and laboratory studies have demonstrated a clear link between warming environments and disease spread. Many climate-related environmental changes also influence wildlife health indirectly. For example, increasing temperatures, in combination with shifts in rainfall and humidity, may aggravate current trends for water resource limitation and habitat degradation or destruction and lead to increased crowding of animal populations, thereby promoting transmission opportunities of pathogens within populations or across species. Although it may be difficult to disentangle the influences of other anthropogenic changes from the direct effects of warming, some ecosystems provide especially useful models for studying climate-related disease spread in wildlife. For example, the effects of climate change on parasite dynamics may be easily observed in the Arctic, where environmental changes are occurring rapidly, anthropogenic influences are relatively limited, and biodiversity is generally low. Marine ecosystems are also undergoing rapid rates of change and may be vulnerable to a variety of natural and anthropogenic perturbations. Although many factors affect the health of organisms in ocean environments, temperature has been clearly linked to an increase in disease prevalence among sessile organisms such as corals. In this chapter, we discuss observed and predicted changes to wildlife health resulting from climate change. Our review will not include all aspects of wildlife health, but will instead focus on established or suspected links between climate drivers and disease spread and discuss examples from the current literature. Here, we define disease spread to include: 1) change in geographical or altitudinal distribution of pathogens, parasites, and vectors and the diseases they cause; 2) change in prevalence or severity of disease; and 3) emergence of novel diseases. Additionally, because wildlife species serve as reservoirs for zoonotic diseases that affect both animals and humans, we include select examples of the effect of climate change on the capacity of wildlife to harbor and spread these disease agents.

Book chapter↗

USGS2015

Optimal population prediction of sandhill crane recruitment based on climate-mediated habitat limitations

Prediction is fundamental to scientific enquiry and application; however, ecologists tend to favour explanatory modelling. We discuss a predictive modelling framework to evaluate ecological hypotheses and to explore novel/unobserved environmental scenarios to assist conservation and management decision-makers. We apply this framework to develop an optimal predictive model for juvenile (<1 year old) sandhill crane Grus canadensis recruitment of the Rocky Mountain Population (RMP). We consider spatial climate predictors motivated by hypotheses of how drought across multiple time-scales and spring/summer weather affects recruitment. Our predictive modelling framework focuses on developing a single model that includes all relevant predictor variables, regardless of collinearity. This model is then optimized for prediction by controlling model complexity using a data-driven approach that marginalizes or removes irrelevant predictors from the model. Specifically, we highlight two approaches of statistical regularization, Bayesian least absolute shrinkage and selection operator (LASSO) and ridge regression. Our optimal predictive Bayesian LASSO and ridge regression models were similar and on average 37% superior in predictive accuracy to an explanatory modelling approach. Our predictive models confirmed a priori hypotheses that drought and cold summers negatively affect juvenile recruitment in the RMP. The effects of long-term drought can be alleviated by short-term wet spring–summer months; however, the alleviation of long-term drought has a much greater positive effect on juvenile recruitment. The number of freezing days and snowpack during the summer months can also negatively affect recruitment, while spring snowpack has a positive effect. Breeding habitat, mediated through climate, is a limiting factor on population growth of sandhill cranes in the RMP, which could become more limiting with a changing climate (i.e. increased drought). These effects are likely not unique to cranes. The alteration of hydrological patterns and water levels by drought may impact many migratory, wetland nesting birds in the Rocky Mountains and beyond. Generalizable predictive models (trained by out-of-sample fit and based on ecological hypotheses) are needed by conservation and management decision-makers. Statistical regularization improves predictions and provides a general framework for fitting models with a large number of predictors, even those with collinearity, to simultaneously identify an optimal predictive model while conducting rigorous Bayesian model selection. Our framework is important for understanding population dynamics under a changing climate and has direct applications for making harvest and habitat management decisions.

Journal of Animal Ecology↗

USGS2025

Proactive assisted gene flow for Caribbean corals in an era of rapid coral reef decline

Coral reefs are one of the most well-documented marine ecosystems under increasing threat from climate change. Catastrophic episodes of coral bleaching and subsequent mortality caused by prolonged heat stress ( 1 ) highlight the need to test and implement new approaches to prevent species loss and retain ecosystem function ( 2 ). One of these approaches is assisted gene flow (AGF)—the managed movement of individuals or gametes between populations within species ranges to mitigate local maladaptation ( 3 ). AGF has recently been approved to help save elkhorn corals in Florida from local extirpation but faces challenges for its broader application owing to static regulatory frameworks whose precautionary nature does not readily account for the high cost of inaction in response to the dynamic ecological realities of climate change ( 4 , 5 ). Here, we highlight how regulatory action could help safely facilitate coral AGF across international boundaries, at least in the tropical western Atlantic (Caribbean).

Science↗