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USGS2017

Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush ( Artemisia tridentata ), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata , we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

Global Change Biology↗

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↗

USGS2020

Genetic and environmental indicators of climate change vulnerability for desert bighorn sheep

Assessments of organisms’ vulnerability to potential climatic shifts are increasingly common. Such assessments are often conducted at the species level and focused primarily on the magnitude of anticipated climate change (i.e., climate exposure). However, wildlife management would benefit from population-level assessments that also incorporate measures of local or regional potential for organismal adaptation to change. Estimates of genetic diversity, gene flow, and landscape connectivity can address this need and complement climate exposure estimates to establish management priorities at broad to local scales. We provide an example of this holistic approach for desert bighorn sheep ( Ovis canadensis nelsoni ) within and surrounding lands administered by the U.S. National Park Service. We used genetic and environmental data from 62 populations across the southwestern U.S. to delineate genetic structure, evaluate relationships between genetic diversity and isolation, and estimate relative climate vulnerability for populations as a function of five variables associated with species’ responses to climate change: genetic diversity, genetic isolation, geographic isolation, forward climate velocity within a population’s habitat patch (a measure of geographic movement rate required for an organism to maintain constant climate conditions), and maximum elevation within the habitat patch (a measure of current climate stress, as lower maximum elevation is associated with higher temperature, lower precipitation, and lower population persistence). Genetic structure analyses revealed a high-level division between populations in southeastern Utah and populations in the remainder of the study area, which were further differentiated into four lower-level genetic clusters. Genetic diversity decreased with population isolation, whereas genetic differentiation increased, but these patterns were stronger for native populations than for translocated populations. Populations exhibited large variation in predicted vulnerability across the study area with respect to all variables, but native populations occupying relatively intact landscapes, such as Death Valley and Grand Canyon national parks, had the lowest overall vulnerability. These results provide local and regional context for conservation and management decisions regarding bighorn populations in a changing climate. Our study further demonstrates how assessments combining multiple factors could allow a more integrated response, such as increasing efforts to maintain connectivity and thus potential for adaptation in areas experiencing rapid climate change.

Arizona, California, Nevada, Utah↗

USGS1996

Effects of glacial meltwater inflows and moat freezing on mixing in an ice-covered antarctic lake as interpreted from stable isotope and tritium distributions

Perennially ice-covered lakes in the McMurdo Dry Valleys have risen several meters over the past two decades due to climatic warming and increased glacial meltwater inflow. To elucidate the hydrologic responses to changing climate and the effects on lake mixing processes we measured the stable isotope (??18O and ??D) and tritium concentrations of water and ice samples collected in the Lake Fryxell watershed from 1987 through 1990. Stable isotope enrichment resulted from evaporation in stream and moat samples and from sublimation in surface lake-ice samples. Tritium enrichment resulted from exchange with the postnuclear atmosphere in stream and moat samples. Rapid injection of tritiated water into the upper water column of the make and incorporation of this water into the ice cover resulted in uniformly elevated tritium contents (> 3.0 TU) in these reservoirs. Tritium was also present in deep water, suggesting that a component of bottom water was recently at the surface. During summer, melted lake ice and stream water forms the moat. Water excluded from ice formation during fall moat freezing (enriched in solutes and tritium, and depleted in 18O and 2H relative to water below 15-m depth) may sink as density currents to the bottom of the lake. Seasonal lake circulation, in response to climate-driven surface inflow, is therefore responsible for the distribution of both water isotopes and dissolved solutes in Lake Fryxell.

Limnology and Oceanography↗

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↗

USGS2015

Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data

Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal extents. Second, we adapt a statistical procedure combining a non-metric multidimensional scaling technique and higher density region plots to detect potentially anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability and patterns in variability through time, as well as spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal their differential vulnerability to climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.

Hydrology and Earth System Sciences↗

USGS2021

A greener future for the Galapagos: Forecasting ecosystem productivity by finding climate analogs in time

Forecasting ecosystem response to climate change is critical for guiding policymaking but challenging due to: complicated relationships between microclimates and regional climates; species’ responses that are driven by extremes rather than averages; the multifaceted nature of species’ interactions; and the lack of historical analogs to future climates. Given these challenges, even model systems such as the Galapagos Islands, a world-famous biodiversity hotspot and World Heritage Site, lack clear forecasts for future environmental change. Here, we developed a novel nonparametric method for simulating the ecosystem futures based on observed vegetation productivity (NDVI) during analogous weather observed historically. Using satellite images taken from the past to piece together a simulated future, we projected that productivity of terrestrial vegetation of the Galapagos will increase over the next century by approximately one standard deviation archipelago-wide, with largest increases during the wet season (January to June) and in the arid zones. Such greening would impact a variety of ecological and evolutionary processes, species of conservation concern, and agricultural practices. Our straightforward approach can be applied to many other regions, particularly those with rapid ecosystem responses to stochastic inter-annual climatic fluctuations that provide appropriate climate analogs for forecasting.

Galápagos Islands↗

USGS2023

Restoration research actions to address rapid change in drylands: Insights from the Colorado Plateau

The rapid intensification of ecological extremes in response to climate change and human land use is perhaps nowhere more apparent than in drylands, including the semiarid region of the Colorado Plateau in the southwestern United States. Here, we describe research directions to aid in the restoration of Colorado Plateau ecosystems during the UN Decade on Ecosystem Restoration (2021–2030) that 1) address high levels of heterogeneity 2) explore simultaneous global change drivers 3) are co-produced with a broad range of partners and 4) center Indigenous ways of knowing. We highlight restoration research efforts led by early career scientists grappling with informing management actions in a region where a rapidly changing climate intersects with historic grazing and continued land use pressures to create novel ecological extremes. We highlight restoration research efforts led by early career researchers grappling with informing management actions in a region where novel ecological extremes are the result of historic grazing, continued land-use pressures, and a rapidly changing climate.

Arizona, Colorado, New Mexico, Utah↗

USGS2017

Seasonality of change: Summer warming rates do not fully represent effects of climate change on lake temperatures

Responses in lake temperatures to climate warming have primarily been characterized using seasonal metrics of surface-water temperatures such as summertime or stratified period average temperatures. However, climate warming may not affect water temperatures equally across seasons or depths. We analyzed a long-term dataset (1981–2015) of biweekly water temperature data in six temperate lakes in Wisconsin, U.S.A. to understand (1) variability in monthly rates of surface- and deep-water warming, (2) how those rates compared to summertime average trends, and (3) if monthly heterogeneity in water temperature trends can be predicted by heterogeneity in air temperature trends. Monthly surface-water temperature warming rates varied across the open-water season, ranging from 0.013 in August to 0.073°C yr −1 in September (standard deviation [SD]: 0.025°C yr −1 ). Deep-water trends during summer varied less among months (SD: 0.006°C yr −1 ), but varied broadly among lakes (–0.056°C yr −1 to 0.035°C yr −1 , SD: 0.034°C yr −1 ). Trends in monthly surface-water temperatures were well correlated with air temperature trends, suggesting monthly air temperature trends, for which data exist at broad scales, may be a proxy for seasonal patterns in surface-water temperature trends during the open water season in lakes similar to those studied here. Seasonally variable warming has broad implications for how ecological processes respond to climate change, because phenological events such as fish spawning and phytoplankton succession respond to specific, seasonal temperature cues.

Wisconsin↗

USGS2014

Organizing phenological data resources to inform natural resource conservation

Changes in the timing of plant and animal life cycle events, in response to climate change, are already happening across the globe. The impacts of these changes may affect biodiversity via disruption to mutualisms, trophic mismatches, invasions and population declines. To understand the nature, causes and consequences of changed, varied or static phenologies, new data resources and tools are being developed across the globe. The USA National Phenology Network is developing a long-term, multi-taxa phenological database, together with a customizable infrastructure, to support conservation and management needs. We present current and potential applications of the infrastructure, across scales and user groups. The approaches described here are congruent with recent trends towards multi-agency, large-scale research and action.

Biological Conservation↗

USGS2008

Complex seasonal patterns of primary producers at the land-sea interface

Seasonal fluctuations of plant biomass and photosynthesis are key features of the Earth system because they drive variability of atmospheric CO 2 , water and nutrient cycling, and food supply to consumers. There is no inventory of phytoplankton seasonal cycles in nearshore coastal ecosystems where forcings from ocean, land and atmosphere intersect. We compiled time series of phytoplankton biomass (chlorophyll a ) from 114 estuaries, lagoons, inland seas, bays and shallow coastal waters around the world, and searched for seasonal patterns as common timing and amplitude of monthly variability. The data revealed a broad continuum of seasonal patterns, with large variability across and within ecosystems. This contrasts with annual cycles of terrestrial and oceanic primary producers for which seasonal fluctuations are recurrent and synchronous over large geographic regions. This finding bears on two fundamental ecological questions: (1) how do estuarine and coastal consumers adapt to an irregular and unpredictable food supply, and (2) how can we extract signals of climate change from phytoplankton observations in coastal ecosystems where local‐scale processes can mask responses to changing climate?

Ecology Letters↗

USGS2016

Populations of concern

Climate change is already causing, and is expected to continue to cause, a range of health impacts that vary across different population groups in the United States. The vulnerability of any given group is a function of its sensitivity to climate change related health risks, its exposure to those risks, and its capacity for responding to or coping with climate variability and change. Vulnerable groups of people, described here as populations of concern, include those with low income, some communities of color, immigrant groups (including those with limited English proficiency), Indigenous peoples, children and pregnant women, older adults, vulnerable occupational groups, persons with disabilities, and persons with preexisting or chronic medical conditions. Planners and public health officials, politicians and physicians, scientists and social service providers are tasked with understanding and responding to the health impacts of climate change. Collectively, their characterization of vulnerability should consider how populations of concern experience disproportionate, multiple, and complex risks to their health and well-being in response to climate change. Some groups face a number of stressors related to both climate and non-climate factors. For example, people living in impoverished urban or isolated rural areas, floodplains, coastlines, and other at-risk locations are more vulnerable not only to extreme weather and persistent climate change but also to social and economic stressors. Many of these stressors can occur simultaneously or consecutively. Over time, this “accumulation” of multiple, complex stressors is expected to become more evident1 as climate impacts interact with stressors associated with existing mental and physical health conditions and with other socioeconomic and demographic factors.

Report↗

USGS2020

FiCli, the Fish and Climate Change Database, informs climate adaptation and management for freshwater fishes

Inland fishes provide important ecosystem services to communities worldwide and are especially vulnerable to the impacts of climate change. Fish respond to climate change in diverse and nuanced ways, which creates challenges for practitioners of fish conservation, climate change adaptation, and management. Although climate change is known to affect fish globally, a comprehensive online, public database of how climate change has impacted inland fishes worldwide and adaptation or management practices that may address these impacts does not exist. We conducted an extensive, systematic primary literature review to identify peer-reviewed journal publications describing projected and documented examples of climate change impacts on inland fishes. From this standardized Fi sh and Cli mate Change database, FiCli (pronounced fick-lee), researchers and managers can query fish families, species, response types, or geographic locations to obtain summary information on inland fish responses to climate change and recommended management actions. The FiCli database is updatable and provides access to comprehensive published information to inform inland fish conservation and adaptation planning in a changing climate.

Scientific Data↗

USGS2011

Responses of ecosystem carbon cycling to climate change treatments along an elevation gradient

Global temperature increases and precipitation changes are both expected to alter ecosystem carbon (C) cycling. We tested responses of ecosystem C cycling to simulated climate change using field manipulations of temperature and precipitation across a range of grass-dominated ecosystems along an elevation gradient in northern Arizona. In 2002, we transplanted intact plant–soil mesocosms to simulate warming and used passive interceptors and collectors to manipulate precipitation. We measured daytime ecosystem respiration (ER) and net ecosystem C exchange throughout the growing season in 2008 and 2009. Warming generally stimulated ER and photosynthesis, but had variable effects on daytime net C exchange. Increased precipitation stimulated ecosystem C cycling only in the driest ecosystem at the lowest elevation, whereas decreased precipitation showed no effects on ecosystem C cycling across all ecosystems. No significant interaction between temperature and precipitation treatments was observed. Structural equation modeling revealed that in the wetter-than-average year of 2008, changes in ecosystem C cycling were more strongly affected by warming-induced reduction in soil moisture than by altered precipitation. In contrast, during the drier year of 2009, warming induced increase in soil temperature rather than changes in soil moisture determined ecosystem C cycling. Our findings suggest that warming exerted the strongest influence on ecosystem C cycling in both years, by modulating soil moisture in the wet year and soil temperature in the dry year.

Arizona↗

USGS1985

Cyclic variations in calcium carbonate and organic carbon in Miocene to Holocene sediments, Walvis Ridge, South Atlantic Ocean

The entire upper Miocene to Holocene sedimentary sequence recovered in a hydraulic piston core at DSDP Site 532 on Walvis Ridge shows distinct cycles in amount of CaCO sub(3) that correlate with dark and light cycles of sediment color. The average periodicities of the carbonate cycles for the Quaternary, upper Pliocene, and lower Pliocene are about 35, 46, and 28 ky, respectively, with an overall average of about 36 ky for the last 5 my. Most minima in carbonate abundance correspond to dark parts of the color cycles, and most maxmia in carbonate abundance correspond to dark parts of color cycles, The darker parts of the color cycle usually contain higher concentrations of organic carbon, but organic carbon does not follow the color cycles in detail. Organic carbon cycles were analyzed only for the last 2.5 my, and for this interval they have an average periodicity of about 34 ky. The carbonate and color cycles persist through more than 5my during which major changes in relative proportions of siliceous-biogenic, calcareous- biogenic and terrigenous- clastic components occurent in response to climate change and to the waxing and waning of the Benguela Current upwelling systems off southwest Africa. The cyclic nature of these sediments probably is the result of dilution by terrigrnous clastic material and not dissolution of carbonate. We believe that the forcing mechanisms that produced the cycliclity was external to the area of site 532. Because of the similarity among the periodicities of the Walvis Ridge cycles and those of carbonate cycles in the northeastern Atlantic, Caribbean and eastern equatorial Pacific, these cycles probably are responses to global events. We conclude that fluctuations om global sea level with an average period of about 36 ky during the last 5 my caused variations in influx of terrigenous clastic materials from the Africans continental margin

Book chapter↗

USGS2013

Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin

Although groundwater and surface water are considered a single resource, historically hydrologic simulations have not accounted for feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system. Simulations that iteratively couple the surface-water and groundwater systems, however, are characterized by long run times and calibration challenges. In this study, calibrated, uncoupled transient surface-water and steady-state groundwater models were used to construct one coupled transient groundwater/surface-water model for the Trout Lake Watershed in north-central Wisconsin, USA. The computer code GSFLOW (Ground-water/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil-zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, stream, and lake budgets. The coupled GSFLOW model was calibrated by using heads, streamflows, lake levels, actual evapotranspiration rates, solar radiation, and snowpack measurements collected during water years 1998–2007; calibration was performed by using advanced features present in the PEST parameter estimation software suite. Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model to simulate daily stream temperature in selected tributaries in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2002. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the period extending to the year 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the period 2010–2100 showed increases in maximum and minimum temperature over the scenario period. Scenarios of future precipitation did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased over time for both temperature and precipitation. Separate calibration of the uncoupled groundwater and surface-water models did not provide a representative initial parameter set for coupled model calibration. A sequentially linked calibration, in which the uncoupled models were linked by means of utility software, provided a starting parameter set suitable for coupled model calibration. Even with sequentially linked calibration, however, transmissivity of the lower part of the aquifer required further adjustment during coupled model calibration to attain reasonable parameter values for evaporation rates off a small seepage lake (a lake with no appreciable surface-water outlets) with a long history of study. The resulting coupled model was well calibrated to most types of observed time-series data used for calibration. Daily stream temperatures measured during 2002 were successfully simulated with SNTEMP; the model fit was acceptable for a range of groundwater inflow rates into the streams. Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snow-melt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions in rainfed wetlands and uplands, in contrast to less drying in groundwater-fed systems. Seepage lakes showed larger forecast stage declines related to climate change than did drainage lakes (lakes with outlet streams). Seepage lakes higher in the watershed (nearer to groundwater divides) had less groundwater inflow and thus had larger forecast declines in lake stage; however, ground-water inflow to seepage lakes in general tended to increase as a fraction of the lake budgets with lake-stage decline because inward hydraulic gradients increased. Drainage lakes were characterized by less simulated stage decline as reductions in outlet streamflow of set losses to other water flows. Net groundwater inflow tended to decrease in drainage lakes over the scenario period. Simulated stream temperatures increased appreciably with climate change. The estimated increase in annual average temperature ranged from approximately 1 to 2 degrees Celsius by 2100 in the stream characterized by a high groundwater inflow rate and 2 to 3 degrees Celsius in the stream with a lower rate. The climate drivers used for the climate-change scenarios had appreciable variation between the General Circulation Model and emission scenario selected; this uncertainty was reflected in hydrologic flow and temperature model results. Thus, as with all forecasts of this type, the results are best considered to approximate potential outcomes of climate change.

Wisconsin↗

USGS2016

Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin

A groundwater/surface-water model was constructed and calibrated for the Black Earth Creek watershed in south-central Wisconsin. The model was then run to simulate scenarios representing common societal concerns in the basin, focusing on maintaining a cold-water resource in an urbanizing fringe near its upper stream reaches and minimizing downstream flooding. Although groundwater and surface water are considered a single resource, many hydrologic models simplistically simulate feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system; however, computer models can now routinely and iteratively couple the surface-water and groundwater systems—albeit with longer model run times. In this study, preliminary calibrations of uncoupled transient surface-water and steady-state groundwater models were used to form the starting point for final calibration of one transient computer simulation that iteratively couples groundwater and surface water. The computer code GSFLOW (Groundwater/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, and streams. The coupled GSFLOW model was run on a daily time step during water years 1985–2007. Early simulation times (1985–2000) were used for spin-up to make the simulation results less sensitive to initial conditions specified; the spin-up period was not included in the model calibration. Model calibration used observed heads, streamflows, solar radiation, and snowpack measurements from 2000 to 2007 for history matching. Calibration was performed by using the PEST parameter estimation software suite. Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model. SNTEMP was used to simulate daily stream temperature in selected stream reaches in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2005. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the years 2010 through 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the simulation period showed increases in maximum and minimum air temperature. Scenarios of future precipitation, however, did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased with time for both temperature and precipitation. Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snowmelt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions, with relatively less drying expected in groundwater-fed systems. Groundwater discharge in the current upper cold-water reaches of Black Earth Creek is expected to decrease; flooding in downstream reaches may appreciably increase. The magnitude of changes in forecasted flow and associated groundwater/surface-water interaction is dependent on the General Circulation Model and emission scenario chosen. Potential future changes in air temperature drivers were consistently upward regardless of General Circulation Model and emission scenario selected; thus, simulated stream temperatures are forecast to increase appreciably with future climate. However, the amount of temperature increase was variable. Such uncertainty is reflected in temperature model results, along with uncertainty in the groundwater/surface-water interaction itself. The estimated increase in annual average temperature ranged from approximately 3 to 6 degrees Celsius by 2100 in the upper reaches of Black Earth Creek and 2 to 4 degrees Celsius in reaches farther downstream. As with all forecasts that rely on projections of an unknowable future, the results are best considered to approximate potential outcomes of climate change given the underlying uncertainty.

Wisconsin↗

USGS2007

Net emissions of CH4 and CO2 in Alaska: Implications for the region's greenhouse gas budget

We used a biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to study the net methane (CH4) fluxes between Alaskan ecosystems and the atmosphere. We estimated that the current net emissions of CH4 (emissions minus consumption) from Alaskan soils are ???3 Tg CH 4/yr. Wet tundra ecosystems are responsible for 75% of the region's net emissions, while dry tundra and upland boreal forests are responsible for 50% and 45% of total consumption over the region, respectively. In response to climate change over the 21st century, our simulations indicated that CH 4 emissions from wet soils would be enhanced more than consumption by dry soils of tundra and boreal forests. As a consequence, we projected that net CH4 emissions will almost double by the end of the century in response to high-latitude warming and associated climate changes. When we placed these CH4 emissions in the context of the projected carbon budget (carbon dioxide [CO2] and CH4) for Alaska at the end of the 21st century, we estimated that Alaska will be a net source of greenhouse gases to the atmosphere of 69 Tg CO2 equivalents/yr, that is, a balance between net methane emissions of 131 Tg CO2 equivalents/yr and carbon sequestration of 17 Tg C/yr (62 Tg CO2 equivalents/yr). ?? 2007 by the Ecological Society of America.

Ecological Applications↗