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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↗

USGS2016

The Aleutian-Bering Climate Vulnerability Assessment

Recent efforts to develop downscaled climate projections for the Bering Sea and Aleutians created an opportunity to better assess regional vulnerability to climate change. The Aleutian Bering Climate Vulnerability Assessment (ABCVA) was launched in 2014 to bring together regional science expertise and stakeholder interests in a rapid evaluation of the implications of future climate projections. This effort followed an internationally accepted but flexible pathway to develop practical, priority research topics that address ecosystem and community vulnerabilities. The ABCVA was completed as a partnership between the Aleutian and Bering Sea Islands Landscape Conservation Cooperative (ABSI LCC), the Alaska Climate Science Center and the Alaska Ocean Observing System (AOOS), and ultimately brought together three linked objectives: 1. identify and assess selected climate vulnerabilities of key resources and ecosystem services in the Aleutian Islands and Bering Sea region 2. broadly engage managers and stakeholders about the implications of climate vulnerabilities in the region 3. help ABSI LCC and the Alaska Climate Science Center and AOOS prioritize future research investments and focus The ABCVA convened a group of 30 researchers with expertise ranging from anthropology to zooplankton to review climate projections and their implications for the Aleutians and Bering Sea. These experts worked in five topic-based teams to assess vulnerabilities of species and ecosystem services relative. Each team identified initial vulnerabilities and made recommendations for further research that would help managers and communities better understand the implications of the changing climate in this region.

Aleutian and Bering Sea Islands↗

USGS2013

Identifying stakeholder-relevant climate change impacts: a case study in the Yakima River Basin, Washington, USA

Designing climate-related research so that study results will be useful to natural resource managers is a unique challenge. While decision makers increasingly recognize the need to consider climate change in their resource management plans, and climate scientists recognize the importance of providing locally-relevant climate data and projections, there often remains a gap between management needs and the information that is available or is being collected. We used decision analysis concepts to bring decision-maker and stakeholder perspectives into the applied research planning process. In 2009 we initiated a series of studies on the impacts of climate change in the Yakima River Basin (YRB) with a four-day stakeholder workshop, bringing together managers, stakeholders, and scientists to develop an integrated conceptual model of climate change and climate change impacts in the YRB. The conceptual model development highlighted areas of uncertainty that limit the understanding of the potential impacts of climate change and decision alternatives by those who will be most directly affected by those changes, and pointed to areas where additional study and engagement of stakeholders would be beneficial. The workshop and resulting conceptual model highlighted the importance of numerous different outcomes to stakeholders in the basin, including social and economic outcomes that go beyond the physical and biological outcomes typically reported in climate impacts studies. Subsequent studies addressed several of those areas of uncertainty, including changes in water temperatures, habitat quality, and bioenergetics of salmonid populations.

Washington↗

USGS2018

Sensitivity of streamflow to climate change in California

Climate change is rapidly altering the global water cycle, exposing vulnerabilities in both social and environmental systems. However, uncertainty in future climate predictions makes it difficult to design and evaluate strategies for building climate resilience. In regions such as California, characterized by stressed water-supply systems, high natural climate variability, and substantial uncertainty in future precipitation projections, alternative approaches to assessing climate risks may be useful. Here, we develop a hydrologic sensitivity approach to estimate regional streamflow responses to climate change in California. We use statistical models to predict monthly streamflow from physical catchment features and evaluate how flow changes with incremental changes in precipitation and temperature. The results indicate unique regional and monthly flow responses to climate change, with early summer flows (May - July) in interior mountain region having the greatest sensitivity to temperature and winter flow (December - March) in the xeric region having the greatest sensitivity to precipitation. When evaluated over the range of global climate model projections for mid-century (2040-2069), models generally suggest shifts in streamflow regimes towards higher wet season flows and lower dry season flows relative to historical conditions. The sensitivity analysis provides insight into catchment- and regional-scale hydrologic responses in California and complements other approaches for understanding the consequences of climatic change for water and risk management.

California↗

USGS2012

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

Journal of Climate↗

USGS2017

Climate change refugia and habitat connectivity promote species persistence

Background Climate change refugia, areas buffered from climate change relative to their surroundings, are of increasing interest as natural resource managers seek to prioritize climate adaptation actions. However, evidence that refugia buffer the effects of anthropogenic climate change is largely missing. Methods Focusing on the climate-sensitive Belding’s ground squirrel ( Urocitellus beldingi ), we predicted that highly connected Sierra Nevada meadows that had warmed less or shown less precipitation change over the last century would have greater population persistence, as measured by short-term occupancy, fewer extirpations over the twentieth century, and long-term persistence measured through genetic diversity. Results Across California, U. beldingi were more likely to persist over the last century in meadows with high connectivity that were defined as refugial based on a suite of temperature and precipitation factors. In Yosemite National Park, highly connected refugial meadows were more likely to be occupied by U. beldingi . More broadly, populations inhabiting Sierra Nevada meadows with colder mean winter temperatures had higher values of allelic richness at microsatellite loci, consistent with higher population persistence in temperature-buffered sites. Furthermore, both allelic richness and gene flow were higher in meadows that had higher landscape connectivity, indicating the importance of metapopulation processes. Conversely, anthropogenic refugia, sites where populations appeared to persist due to food or water supplementation, had lower connectivity, genetic diversity, and gene flow, and thus might act as ecological traps. This study provides evidence that validates the climate change refugia concept in a contemporary context and illustrates how to integrate field observations and genetic analyses to test the effectiveness of climate change refugia and connectivity. Conclusions Climate change refugia will be important for conserving populations as well as genetic diversity and evolutionary potential. Our study shows that in-depth modeling paired with rigorous fieldwork can identify functioning climate change refugia for conservation.

California↗

USGS2024

North Central Climate Adaptation Science Center regional science plan—2023–28

The U.S. Geological Survey North Central Climate Adaptation Science Center (NC CASC), established in 2012, is part of a national network supporting climate-informed decisions that benefit wildlife and habitats. The NC CASC provides climate science for the U.S. Department of the Interior, State agencies, and Tribal nations to support effective resource management. Collaborating with the National and Regional Climate Adaptation Science Center network, the NC CASC addresses multiregion challenges through a partnership involving the U.S. Geological Survey and additional regional partners. Input is collected from an Advisory Committee of State, Federal, and Tribal Government representatives. The center hosts Tribal Climate Resilience Liaisons, which are funded by the Bureau of Indian Affairs Branch of Tribal Climate Resilience and aligned with a Tribal Engagement Strategy. Positioned at the meeting point of scientists and managers and guided by core values, the NC CASC studies diverse ecosystems affected by climate change and empowers resource managers with actionable data and innovative science. This report outlines the 5-year Science Plan (hereafter “the Plan”) for the NC CASC. The center uses stakeholder engagement and coproduction of knowledge for effective collaboration, including engagement of Advisory Committee members and other management partners in the development of the Plan. The Plan provides a high-level overview of the NC CASC, covering the center’s geographical scope, key collaborators, stakeholders, and the strategic framework guiding the application of climate science to make informed management decisions. The Plan also summarizes management challenges and scientific objectives related to the impact of climate change on habitat, ecological drought, wildlife disease, invasives and encroachment, fire, and phenology.

Colorado, Kansas, Montana, North Dakota, Nebraska,↗

USGS2004

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895—1993 on a 0.5° latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers.

Climate Research↗

USGS2017

Climatic controls on the global distribution, abundance, and species richness of mangrove forests

Mangrove forests are highly productive tidal saline wetland ecosystems found along sheltered tropical and subtropical coasts. Ecologists have long assumed that climatic drivers (i.e., temperature and rainfall regimes) govern the global distribution, structure, and function of mangrove forests. However, data constraints have hindered the quantification of direct climate-mangrove linkages in many parts of the world. Recently, the quality and availability of global-scale climate and mangrove data have been improving. Here, we used these data to better understand the influence of air temperature and rainfall regimes upon the distribution, abundance, and species richness of mangrove forests. Although our analyses identify global-scale relationships and thresholds, we show that the influence of climatic drivers is best characterized via regional range limit-specific analyses. We quantified climatic controls across targeted gradients in temperature and/or rainfall within 14 mangrove distributional range limits. Climatic thresholds for mangrove presence, abundance, and species richness differed among the 14 studied range limits. We identified minimum temperature-based thresholds for range limits in eastern North America, eastern Australia, New Zealand, eastern Asia, eastern South America, and southeast Africa. We identified rainfall-based thresholds for range limits in western North America, western Gulf of Mexico, western South America, western Australia, Middle East, northwest Africa, east central Africa, and west central Africa. Our results show that in certain range limits (e.g., eastern North America, western Gulf of Mexico, eastern Asia), winter air temperature extremes play an especially important role. We conclude that rainfall and temperature regimes are both important in western North America, western Gulf of Mexico, and western Australia. With climate change, alterations in temperature and rainfall regimes will affect the global distribution, abundance, and diversity of mangrove forests. In general, warmer winter temperatures are expected to allow mangroves to expand poleward at the expense of salt marshes. However, dispersal and habitat availability constraints may hinder expansion near certain range limits. Along arid and semi-arid coasts, decreases or increases in rainfall are expected to lead to mangrove contraction or expansion, respectively. Collectively, our analyses quantify climate-mangrove linkages and improve our understanding of the expected global- and regional-scale effects of climate change upon mangrove forests.

Ecological Monographs↗

USGS2016

Influence of climate drivers on colonization and extinction dynamics of wetland-dependent species

Freshwater wetlands are particularly vulnerable to climate change. Specifically, changes in temperature, precipitation, and evapotranspiration (i.e., climate drivers) are likely to alter flooding regimes of wetlands and affect the vital rates, abundance, and distributions of wetland-dependent species. Amphibians may be among the most climate-sensitive wetland-dependent groups, as many species rely on shallow or intermittently flooded wetland habitats for breeding. Here, we integrated multiple years of high-resolution gridded climate and amphibian monitoring data from Grand Teton and Yellowstone National Parks to explicitly model how variations in climate drivers and habitat conditions affect the occurrence and breeding dynamics (i.e., annual extinction and colonization rates) of amphibians. Our results showed that models incorporating climate drivers outperformed models of amphibian breeding dynamics that were exclusively habitat based. Moreover, climate-driven variation in extinction rates, but not colonization rates, disproportionately influenced amphibian occupancy in monitored wetlands. Long-term monitoring from national parks coupled with high-resolution climate data sets will be crucial to describing population dynamics and characterizing the sensitivity of amphibians and other wetland-dependent species to climate change. Further, long-term monitoring of wetlands in national parks will help reduce uncertainty surrounding wetland resources and strengthen opportunities to make informed, science-based decisions that have far-reaching benefits.

Grand Teton National Park, Yellowstone National Pa↗

USGS2024

A habitat-centered framework for wildlife climate change vulnerability assessments: Application to Gunnison sage-grouse

The persistence of threatened wildlife species depends on successful conservation and restoration of habitats, but climate change and other stressors make these tasks increasingly challenging. Applying climate change vulnerability analyses to contemporary wildlife management can be difficult because most analyses predict direct effects of future climate on wildlife species at broad geographic scales, rather than assessing their habitats at local scales (<1 km) that correspond to site-specific habitat management actions. We present a framework that synthesizes vegetation-focused vulnerability assessments to assess multiple effects on wildlife species' diverse habitat needs, providing a scenario-driven climate vulnerability assessment that maps differences in vulnerability of populations within a species' range. Our flexible habitat-centered synthesis approach leverages available spatial datasets describing projected exposure to vegetation changes due to climate change and other potentially synergistic stressors, reclassifies and weights them based on available estimates of species' sensitivity to these changes, and recombines them to create <1-km resolution maps of overall species vulnerability and threat-specific habitat vulnerability . To demonstrate its potential to guide decision-making, we applied this approach to the Gunnison sage-grouse ( Centrocercus minimus ), a federally threatened habitat specialist that depends on sagebrush and mesic habitats that are imperiled by climate change. We mapped six threats forecasted out to the year 2070: direct effects of climate on (1) sagebrush cover loss and (2) mesic habitat drying, indirect changes in invasion risk from (3) pinyon–juniper conifers and (4) annual grasses, and potentially synergistic risk of (5) development and (6) wildfire. We then assessed species vulnerability for each of the eight extant populations under three climate scenarios: Optimistic, Continuation, and Pessimistic. We found that the extent of cumulative species vulnerability due to multiple habitat changes was far greater than the extent of any single habitat vulnerability. Over 75% of critical habitats were at risk under the Pessimistic scenario, and nearly two thirds of habitats were at high risk for three or more threats. Invasive species were the most widespread threat, highlighting the importance of indirect effects of climate change. We illustrate how our approach can be applied to the existing management planning strategies to better prioritize conservation of habitats for the persistence of threatened species.

Colorado, Utah↗

USGS2000

Streamflow changes in the Sierra Nevada, California, simulated using a statistically downscaled general circulation model scenario of climate change

Simulations of future climate using general circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. Of less certainty is the extent to which regional scale (i.e., sub-GCM grid) environmental processes will be affected. In this chapter, a range of downscaling techniques are critiqued. Then a relatively simple (yet robust) statistical downscaling technique and its use in the modelling of future runoff scenarios for three river basins in the Sierra Nevada, California, is described. This region was selected because GCM experiments driven by combined greenhouse-gas and sulphate-aerosol forcings consistently show major changes in the hydro-climate of the southwest United States by the end of the 21st century. The regression-based downscaling method was used to simulate daily rainfall and temperature series for streamflow modelling in three Californian river basins under current-and future-climate conditions. The downscaling involved just three predictor variables (specific humidity, zonal velocity component of airflow, and 500 hPa geopotential heights) supplied by the U.K. Meteorological Office couple ocean-atmosphere model (HadCM2) for the grid point nearest the target basins. When evaluated using independent data, the model showed reasonable skill at reproducing observed area-average precipitation, temperature, and concomitant streamflow variations. Overall, the downscaled data resulted in slight underestimates of mean annual streamflow due to underestimates of precipitation in spring and positive temperature biases in winter. Differences in the skill of simulated streamflows amongst the three basins were attributed to the smoothing effects of snowpack on streamflow responses to climate forcing. The Merced and American River basins drain the western, windward slope of the Sierra Nevada and are snowmelt dominated, whereas the Carson River drains the eastern, leeward slope and is a mix of rainfall runoff and snowmelt runoff. Simulated streamflow in the American River responds rapidly and sensitively to daily-scale temperature and precipitation fluctuations and errors; in the Merced and Carson Rivers, the response to the same short-term influences is much less. Consequently, the skill of simulated flows was significantly lower in the American River model than in the Carson and Merced. The physiography of the three basins also accounts for differences in their sensitivities to future climate change. Increases in winter precipitation exceeding +100% coupled with mean temperature rises greater than +2°C result in increased winter streamflows in all three basins. In the Merced and Carson basins, these streamflow increases reflect large changes in winter snowpack, whereas the streamflow changes in the lower elevation American basin are driven primarily by rainfall runoff. Furthermore, reductions in winter snowpack in the American River basin, owing to less precipitation falling as snow and earlier melting of snow at middle elevations, lead to less spring and summer streamflow. Taken collectively, the downscaling results suggest significant changes to both the timing and magnitude of streamflows in the Sierra Nevada by the end of the 21st Century. In the higher elevation basins, the HadCM2 scenario implies more annual streamflow and more streamflow during the spring and summer months that are critical for water-resources management in California. Depending on the relative significance of rainfall runoff and snowmelt, each basin responds in its own way to regional climate forcing. Generally, then, climate scenarios need to be specified — by whatever means — with sufficient temporal and spatial resolution to capture subtle orographic influences if projections of climate-change responses are to be useful and reproducible.

California↗

USGS2001

Potential changes in the distributions of western North America tree and shrub taxa under future climate scenarios

Increases in atmospheric greenhouse gases are driving significant changes in global climate. To project potential vegetation response to future climate change, this study uses response surfaces to describe the relationship between bioclimatic variables and the distribution of tree and shrub taxa in western North America. The response surfaces illustrate the probability of the occurrence of a taxon at particular points in climate space. Climate space was defined using three bioclimatic variables: mean temperature of the coldest month, growing degree days, and a moisture index. Species distributions were simulated under present climate using observed data (1951–80, 30-year mean) and under future climate (2090–99, 10-year mean) using scenarios generated by three general circulation models—HADCM2, CGCM1, and CSIRO. The scenarios assume a 1% per year compound increase in greenhouse gases and changes in sulfate (SO 4 ) aerosols based on the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. The results indicate that under future climate conditions, potential range changes could be large for many tree and shrub taxa. Shifts in the potential ranges of species are simulated to occur not only northward but in all directions, including southward of the existing ranges of certain species. The simulated potential distributions of some species become increasingly fragmented under the future climate scenarios, while the simulated potential distributions of other species expand. The magnitudes of the simulated range changes imply significant impacts to ecosystems and shifts in patterns of species diversity in western North America.

Ecosystems↗

USGS2016

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Upper Colorado River basin↗

USGS2017

Climate change as a long-term stressor for the fisheries of the Laurentian Great Lakes of North America

The Laurentian Great Lakes of North America provide valuable ecosystem services, including fisheries, to the surrounding population. Given the prevalence of other anthropogenic stressors that have historically affected the fisheries of the Great Lakes (e.g., eutrophication, invasive species, overfishing), climate change is often viewed as a long-term stressor and, subsequently, may not always be prioritized by managers and researchers. However, climate change has the potential to negatively affect fish and fisheries in the Great Lakes through its influence on habitat. In this paper, we (1) summarize projected changes in climate and fish habitat in the Great Lakes; (2) summarize fish responses to climate change in the Great Lakes; (3) describe key interactions between climate change and other stressors relevant to Great Lakes fish, and (4) summarize how climate change can be incorporated into fisheries management. In general, fish habitat is projected to be characterized by warmer temperatures throughout the water column, less ice cover, longer periods of stratification, and more frequent and widespread periods of bottom hypoxia in productive areas of the Great Lakes. Based solely on thermal habitat, fish populations theoretically could experience prolonged optimal growth environment within a changing climate, however, models that assess physical habitat influences at specific life stages convey a more complex picture. Looking at specific interactions with other stressors, climate change may exacerbate the negative impacts of both eutrophication and invasive species for fish habitat in the Great Lakes. Although expanding monitoring and research to consider climate change interactions with currently studied stressors, may offer managers the best opportunity to keep the valuable Great Lakes fisheries sustainable, this expansion is globally applicable for large lake ecosystem dealing with multiple stressors in the face of continued human-driven changes.

Great Lakes↗

USGS1995

Effects of a 2 x CO2 climate on two large lake systems: Pyramid Lake, Nevada, and Yellowstone Lake, Wyoming

The possible effects of trace-gas induced climatic changes on Pyramid and Yellowstone Lakes are assessed using a model of lake temperature. The model is driven by 3 1 2 "> 312 years of hourly meteorological data obtained directly from the output of double-CO 2 experiments (2 × CO 2 ) conducted with a regional climate model nested in a general circulation model. The regional atmospheric model is the climate version of the National Center for Atmospheric Research/Pennsylvania State University mesoscale model, MM4. Average annual surface temperature of Pyramid Lake for the 2 × CO 2 climate is 15.5 ± 5.4°C (±1 σ), 2.8°C higher than the control. Annual overturn of the lake ceases as a result of these higher temperatures for the 2 × CO 2 climate. Evaporation increases from 1400 mm yr −1 in the control to 1595 mm yr −1 in the 2 × CO 2 simulation, but net water supplied to the Pyramid Lake basin increases from −6 mm yr −1 in the control to +27 mm yr −1 in the 2 × CO 2 simulation due to increased precipitation. For the open water periods, the average annual surface temperature of Yellowstone Lake is 13.2 ± 5.1°C for the 2 × CO 2 climate, a temperature 1.6°C higher than the control. The annual duration of ice cover on the lake is 152 days in the 2 × CO 2 simulation, a reduction of 44 days relative to the control. Warming of the lake for the 2 × CO 2 climate is mostly confined to the near-surface. Simulated spring overturn for the 2 × CO 2 climate occurs earlier in the year and fall overturn later than in the control. Evaporation increases from 544 mm yr −1 to 600 mm yr −1 in the 2 × CO 2 simulation, but net water supplied to the Yellowstone Lake basin increases from +373 mm yr −1 in the control to +619 mm yr −1 due to increased precipitation. The effects of these climatic changes suggest possible deterioration of water quality and productivity in Pyramid Lake and possible enhancement of productivity in Yellowstone Lake.

Nevada, Wyoming↗

USGS2019

Functional and geographic components of risk for climate sensitive vertebrates in the Pacific Northwest, USA

Rarity and life history traits inform multiple dimensions of intrinsic risk to climate and environmental change and can help systematically identify at-risk species. We quantified relative geographic rarity (area of occupancy), climate niche breadth, and life history traits for 114 freshwater fishes, amphibians, and reptiles in the U.S. Pacific Northwest. Our approach leveraged presence-only, publicly available data and traits-based inference to evaluate area of occupancy, climate sensitivity (i.e., climate niche breadth), and a Rarity and Climate Sensitivity (RCS) index of all species across multiple geographic extents, grain sizes, and data types. The RCS index was relatively stable across extents, grains, and data types, with climate sensitivity differentiating species with otherwise similar areas of occupancy. We also found that species with sensitivity-associated traits (e.g., long generation time, low fecundity) were not necessarily the same species identified as at-risk with geographical approaches (small range size, small climate niche breadth). Many multispecies assessments using coarse-scale data (e.g., entire range maps or convex-hull approaches) often focus on a single dimension of intrinsic risk; others rely on data-intensive models only applicable to a few well-studied species. What remains is a need for an approach that enables multispecies, multidimensional assessment efforts. This is particularly true at regional scales, where management needs require assessments that are intermediate to coarse- and fine-scale approaches. We demonstrate that by considering multiple dimensions of intrinsic risk to climate change (range size, climate sensitivity, and traits), site-specific locality data may offer a pathway for ensuring vulnerable, understudied species do not go overlooked in conservation.

Pacific Northwest↗

USGS2020

Ecosystem-specific growth responses to climate pattern by a temperate freshwater fish

Somatic growth patterns among animal populations are maintained through complex processes that vary among ecosystems. Changes in growth patterns may be concomitant with changes in climate; however, understanding how growth will manifest among ecosystems is limited. Information embedded within fish hard-parts (i.e., otoliths, spines, vertebrae) can account for variation in growth patterns resulting from changing climate conditions. Channel catfish Ictalurus punctatus is a freshwater fish species widely distributed across North America with limited information regarding climate influences on growth and differences in climate-growth relations among ecological systems. We assessed growth (total length) response to changing climate conditions for channel catfish among three waterbody types—pit lakes, irrigation and power-generation reservoirs, and flood-control reservoirs in Nebraska, USA. We used linear mixed-effect models and an information theoretic approach to assess the relative strengths among competing hypotheses. The most supported linear mixed-effect model of channel catfish growth was a function of fish age and an interaction between waterbody type and growing-degree-day (GDD). A positive trend existed in GDD from 1990 through 2008 whereby the predicted increase in GDD among waterbody types ranged from 182 GDD to 189 GDD. The predicted change in channel catfish growth resulting from increased GDD ranged from 1% to 39% among waterbody types. Channel catfish population rate functions, thus, may not respond similarly to climate conditions across ecosystem types. Changes in climate variables may contribute to system-specific responses in population dynamics for channel catfish as well as other similar freshwater species. The establishment of relations between climate and growth variables for a freshwater generalist with a plastic diet and broad temperature tolerance serves as an indication of the breadth of responses possible for freshwater fishes under global changes in climate conditions.

Nebraska↗