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USGS2024

Threshold changes in winter temperature and precipitation drive threshold responses across nine global climate zones and associated biomes

Globally, winter temperatures are rising, and snowpack is shrinking or disappearing entirely. Despite previous research and published literature reviews, it remains unknown whether biomes across the globe will cross important thresholds in winter temperature and precipitation that will lead to significant ecological changes. Here, we combine the widely used Köppen–Geiger climate classification system with worst-case-scenario projected changes in global monthly temperature and precipitation to illustrate how multiple climatic zones across Earth may experience shifting winter conditions by the end of this century. We then examine how these shifts may affect ecosystems within corresponding biomes. Our analysis demonstrates potential widespread losses of extreme cold (<−20°C) in Arctic, boreal, and cool temperate regions. We also show the possible disappearance of freezing temperatures (<0°C) and large decreases in snowfall in warm temperate and dryland areas. We identify important and potentially irreversible ecological changes associated with crossing these winter climate thresholds.

Annual Review of Ecology, Evolution, and Systemati↗

USGS2011

Statistical Comparisons of watershed scale response to climate change in selected basins across the United States

In an earlier global climate-change study, air temperature and precipitation data for the entire twenty-first century simulated from five general circulation models were used as input to precalibrated watershed models for 14 selected basins across the United States. Simulated daily streamflow and energy output from the watershed models were used to compute a range of statistics. With a side-by-side comparison of the statistical analyses for the 14 basins, regional climatic and hydrologic trends over the twenty-first century could be qualitatively identified. Low-flow statistics (95% exceedance, 7-day mean annual minimum, and summer mean monthly streamflow) decreased for almost all basins. Annual maximum daily streamflow also decreased in all the basins, except for all four basins in California and the Pacific Northwest. An analysis of the supply of available energy and water for the basins indicated that ratios of evaporation to precipitation and potential evapotranspiration to precipitation for most of the basins will increase. Probability density functions (PDFs) were developed to assess the uncertainty and multimodality in the impact of climate change on mean annual streamflow variability. Kolmogorov?Smirnov tests showed significant differences between the beginning and ending twenty-first-century PDFs for most of the basins, with the exception of four basins that are located in the western United States. Almost none of the basin PDFs were normally distributed, and two basins in the upper Midwest had PDFs that were extremely dispersed and skewed.

Earth Interactions↗

USGS2011

Hydrologic effects of urbanization and climate change on the Flint River Basin, Georgia

The potential effects of long-term urbanization and climate change on the freshwater resources of the Flint River basin were examined by using the Precipitation-Runoff Modeling System (PRMS). PRMS is a deterministic, distributed-parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land cover on streamflow and multiple intermediate hydrologic states. Precipitation and temperature output from five general circulation models (GCMs) using one current and three future climate-change scenarios were statistically downscaled for input into PRMS. Projections of urbanization through 2050 derived for the Flint River basin by the Forecasting Scenarios of Future Land-Cover (FORE-SCE) land-cover change model were also used as input to PRMS. Comparison of the central tendency of streamflow simulated based on the three climate-change scenarios showed a slight decrease in overall streamflow relative to simulations under current conditions, mostly caused by decreases in the surface- runoff and groundwater components. The addition of information about forecasted urbanization of land surfaces to the hydrologic simulation mitigated the decreases in streamflow, mainly by increasing surface runoff.

Georgia↗

USGS2011

Effects of baseline conditions on the simulated hydrologic response to projected climate change

Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study. Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.

California↗

USGS2018

Do downscaled general circulation models reliably simulate historical climatic conditions?

The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

Earth Interactions↗

USGS2016

Climate change implications for tropical islands: Interpolating and interpreting statistically downscaled GCM projections for management and planning

The potential ecological and economic effects of climate change for tropical islands were studied using output from 12 statistically downscaled general circulation models (GCMs) taking Puerto Rico as a test case. Two model selection/model averaging strategies were used: the average of all available GCMs and the average of the models that are able to reproduce the observed large-scale dynamics that control precipitation over the Caribbean. Five island-wide and multidecadal averages of daily precipitation and temperature were estimated by way of a climatology-informed interpolation of the site-specific downscaled climate model output. Annual cooling degree-days (CDD) were calculated as a proxy index for air-conditioning energy demand, and two measures of annual no-rainfall days were used as drought indices. Holdridge life zone classification was used to map the possible ecological effects of climate change. Precipitation is predicted to decline in both model ensembles, but the decrease was more severe in the “regionally consistent” models. The precipitation declines cause gradual and linear increases in drought intensity and extremes. The warming from the 1960–90 period to the 2071–99 period was 4.6°–9°C depending on the global emission scenarios and location. This warming may cause increases in CDD, and consequently increasing energy demands. Life zones may shift from wetter to drier zones with the possibility of losing most, if not all, of the subtropical rain forests and extinction risks to rain forest specialists or obligates.

Puerto Rico↗

USGS2015

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

Journal of Hydrometeorology↗

USGS2017

A multimodal wave spectrum-based approach for statistical downscaling of local wave climate

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g. the Pacific). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, we address these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into “wave families,” defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications.

Journal of Physical Oceanography↗

USGS2020

What are the effects of climate variability and change on ungulate life-histories, population dynamics, and migration in western North America? A systematic map protocol

Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors, and can affect the growth, development, fecundity, dispersal, and demographic trends of populations. Changes in temperature and precipitation, and resulting shifts in plant phenology, winter severity, drought and wildfire conditions, invasive species distribution and abundance, predation, and disease have the potential to directly or indirectly affect ungulates. However, ungulate responses to climate variability and change are not uniform and vary by species and geography. Here, we present a systematic map protocol aiming to describe the abundance and distribution of evidence on the effects of climate variability and change on ungulate life-histories, population dynamics, and migration in North America. This map will help to identify knowledge gaps and clusters of evidence, and can be used to inform future research directions and adaptive management strategies.

Environmental Evidence↗

USGS2022

Modeled interactions of mountain pine beetle and wildland fire under future climate and management scenarios for three western US landscapes

Mountain pine beetle (MPB) is a native disturbance agent across most pine forests in the western US. Climate changes will directly and indirectly impact frequencies and severities of MPB outbreaks, which can then alter fuel characteristics and wildland fire dynamics via changes in stand structure and composition. To investigate the importance of MPB to past and future landscape dynamics, we used the mechanistic, spatially explicit ecosystem process model FireBGCv2 to quantify interactions among climate, MPB, wildfire, fire suppression, and fuel management under historical and projected future climates for three western US landscapes. We compared simulated FireBGCv2 output from three MPB modules (none, simple empirical, and complex mechanistic) using three focus variables and six exploratory variables to evaluate the importance of MPB to landscape dynamics.

Fire Ecology↗

USGS2003

Late-Holocene climate andecosystem history from Chesapeake Bay sediment cores, USA

Palaeoclimate records from late-Holocene sediments in Chesapeake Bay, the largest estuary in the USA, provide evidence that both decadal to centennial climate variability and European colonization had severe impacts on the watershed and estuary. Using pollen and dinoflagellate cysts as proxies for mid-Atlantic regional precipitation, estuarine salinity and dissolved oxygen (DO) during the last 2300 years, we identified four dry intervals, centred on AD 50 (P1/D1), AD 1000 (P2/D2), AD 1400 (P3) and AD 1600 (P4). Two centennial-scale events, P1/D1 and P2/D2, altered forest composition and led to increased salinity and DO levels in the estuary. Intervals P3 and P4 lasted several decades, leading to decreased production of pine pollen. Periods of dry mid-Atlantic climate correspond to 'megadroughts' identified from tree-ring records in the southeastern and central USA. The observed mid-Atlantic climate variability may be explained by changes in atmospheric circulation resulting in longer-term, perhaps amplified, intervals of meridional flow. After European colonization in the early seventeenth century, forest clearance for agriculture, timber and urbanization altered estuarine water quality, with dinoflagellate assemblages indicating reduced DO and increased turbidity.

Holocene↗

USGS2023

Climatic drivers of estuarine sediment dynamics

Estuarine sediment dynamics are controlled by myriad physical processes that operate across broad spatiotemporal scales. On the smallest scales, interactions between turbulence and individual particles control mobilization and settling, while interactions across larger scales between freshwater and marine inflow can control decadal timescale geomorphic change. Climate change, through the combined effects of sea-level rise, precipitation intensity, atmospheric variability, and anthropogenic intervention will affect sediment dynamics, geomorphology, and ultimately estuarine function. Therefore, it is imperative to understand the influence of these effects on sediment dynamics to assess the future evolution of estuaries. In this chapter we address the basic tidal, non-tidal, and geologic timescale concepts of estuarine sediment transport, then we illustrate how these concepts may be affected by future climate change. While sea-level rise alone will tend to favor sediment trapping and landward movement of estuaries, human influences within the watershed and estuary, including shoreline stabilization and dredging, may be of similar magnitude. The overarching goal of this chapter is to provide the reader with a basic framework of estuarine sediment transport so they can apply these general concepts to a specific system, under a predicted future state of climate, and develop testable hypotheses on future estuarine geomorphology and function.

Book chapter↗

USGS2017

Assessing the impacts of future climate conditions on the effectiveness of winter cover crops in reducing nitrate loads into the Chesapeake Bay Watershed using SWAT model

Winter cover crops (WCCs) have been widely implemented in the Coastal Plain of the Chesapeake Bay watershed (CBW) due to their high effectiveness at reducing nitrate loads. However, future climate conditions (FCCs) are expected to exacerbate water quality degradation in the CBW by increasing nitrate loads from agriculture. Accordingly, the question remains whether WCCs are sufficient to mitigate increased nutrient loads caused by FCCs. In this study, we assessed the impacts of FCCs on WCC nitrate reduction efficiency on the Coastal Plain of the CBW using Soil and Water Assessment Tool (SWAT) model. Three FCC scenarios (2085 – 2098) were prepared using General Circulation Models (GCMs), considering three Intergovernmnental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) greenhouse gas emission scenarios. We also developed six representative WCC implementation scenarios based on the most commonly used planting dates and species of WCCs in this region. Simulation results showed that WCC biomass increased by ~ 58 % under FCC scenarios, due to climate conditions conducive to the WCC growth. Prior to implementing WCCs, annual nitrate loads increased by ~ 43 % under FCC scenarios compared to the baseline scenario (2001 – 2014). When WCCs were planted, annual nitrate loads were substantially reduced by ~ 48 % and WCC nitrate reduction efficiency water ~ 5 % higher under FCC scenarios relative to the baseline. The increase rate of WCC nitrate reduction efficiency varied by FCC scenarios and WCC planting methods. As CO2 concentration was higher and winters were warmer under FCC scenarios, WCCs had greater biomass and therefore showed higher nitrate reduction efficiency. In response to FCC scenarios, the performance of less effective WCC practices (e.g., barley, wheat, and late planting) under the baseline indicated ~ 14 % higher increase rate of nitrate reduction efficiency compared to ones with better effectiveness under the baseline (e.g., rye and early planting), due to warmer temperatures. According to simulation results, WCCs were effective to mitigate nitrate loads accelerated by FCCs and therefore the role of WCCs in mitigating nitrate loads is even more important in the given FCCs.

Chesapeake Bay↗

USGS2013

Climatic correlates of tree mortality in water- and energy-limited forests

Recent increases in tree mortality rates across the western USA are correlated with increasing temperatures, but mechanisms remain unresolved. Specifically, increasing mortality could predominantly be a consequence of temperature-induced increases in either (1) drought stress, or (2) the effectiveness of tree-killing insects and pathogens. Using long-term data from California’s Sierra Nevada mountain range, we found that in water-limited (low-elevation) forests mortality was unambiguously best modeled by climatic water deficit, consistent with the first mechanism. In energy-limited (high-elevation) forests deficit models were only equivocally better than temperature models, suggesting that the second mechanism is increasingly important in these forests. We could not distinguish between models predicting mortality using absolute versus relative changes in water deficit, and these two model types led to different forecasts of mortality vulnerability under future climate scenarios. Our results provide evidence for differing climatic controls of tree mortality in water- and energy-limited forests, while highlighting the need for an improved understanding of tree mortality processes.

California↗

USGS2017

Thermal regimes of Rocky Mountain lakes warm with climate change

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade -1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade -1 , and summer mean lake surface temperature is predicted to increase by 0.47°C·decade -1 . Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.

PLoS ONE↗

USGS2019

Facilitating adaptation to climate change while restoring a montane plant community

Montane plant communities throughout the world have responded to changes in temperature regimes by shifting ranges upward in elevation, and made downslope movements to track shifts in climatic water balance. Organisms that cannot disperse or adapt biologically to projected climate scenarios in situ may decrease in distributional range and abundance over time. Restoration strategies will need to incorporate the habitat suitability of future predicted conditions to ensure long-term persistence. We propagated seedlings of three native Hawaiian montane plant species from high- (~2,500 m asl) and low-elevation (~1,900 m asl) sources, planted them in 8 common plots along a 500 m elevation gradient, and monitored microclimate at each plot for 20 weeks. We explored how temperature and precipitation influenced survival and growth differently among high- and low-elevation origin seedlings. Significantly more seedlings of only one species, Dodonaea viscosa , from high-elevation origin (75.2%) survived than seedlings from low-elevation origin (58.7%) across the entire elevation gradient. Origin also influenced survival in generalized linear mixed models that controlled for temperature, precipitation, and elevation in D . viscosa and Chenopodium oahuense . Survival increased with elevation and soil moisture for Sophora chrysophylla , while it decreased for the other two species. Responses to microclimate varied between the three montane plant species; there were no common patterns of growth or survival. Although limited in temporal scope, our experiment represents one of the few attempts to examine local adaptation to prospective climate scenarios and addresses challenges to restoration efforts within species’ current ranges.

Hawaii↗

USGS2022

Assessing climate change impacts on Pacific salmon using bioenergetics and spatiotemporal explicit river temperature predictions under varying riparian conditions

Pacific salmon and trout populations are affected by timber harvest, the removal and alteration of riparian vegetation, and the resulting physical changes to water quality, temperature, and associated delivery of high-quality terrestrial prey. Juvenile salmon and trout growth, a key predictor of survival, is poorly understood in the context of current and future (climate-change mediated) conditions, with resource managers needing information on how land use will impact future river conditions for these commercially and culturally important species. We used the Heat Source water temperature modeling framework to develop a spatiotemporal model to assess how riparian canopy and vegetation preservation and addition could influence river temperatures under future climate predictions in a coastal river fed by a moraine-dammed lake: the Quinault River in Washington State. The model predicted higher water temperatures under future carbon emission projections, representative concentration pathway (RCP) 4.5 and 8.5, with varying magnitude based on different riparian vegetation scenarios. We used the daily average temperature output from these scenarios to predict potential juvenile fish growth using the Wisconsin bioenergetics model. A combination of riparian vegetation removal and continued high carbon emissions resulted in a predicted seven-day average daily maximum temperature (7DADM) increase of 1.7°C in the lower river by 2080; increases in riparian shading mitigate this 7DADM increase to only 0.9°C. Under the current thermal regime, bioenergetics modeling predicts juvenile fish lose weight in the lower river; this loss of potential growth worsens by an average of 20–83% in the lower river by 2080, increasing with the loss of riparian shading. This study assess the impact of riparian vegetation management on future thermal habitat for Pacific salmon and trout under warming climates and provide a useful spatially explicit modeling framework that managers can use to make decisions regarding riparian vegetation management and its mechanistic impact to water temperature and rearing juvenile fish.

Washington↗

USGS2009

Change in abundance of Pacific brant wintering in Alaska: Evidence of a climate warming effect?

Winter distribution of Pacific Flyway brant ( Branta bernicla nigricans ) has shifted northward from low-temperate areas to sub-Arctic areas over the last 42 years. We assessed the winter abundance and distribution of brant in Alaska to evaluate whether climate warming may be contributing to positive trends in the most northern of the wintering populations. Mean surface air temperatures during winter at the end of the Alaska Peninsula increased about 1°C between 1963 and 2004, resulting in a 23% reduction in freezing degree days and a 34% decline in the number of days when ice cover prevents birds from accessing food resources. Trends in the wintering population fluctuated with states of the Pacific Decadal Oscillation, increasing during positive (warm) phases and decreasing during negative (cold) phases, and this correlation provides support for the hypothesis that growth in the wintering population of brant in Alaska is linked to climate warming. The size of the wintering population was negatively correlated with the number of days of strong northwesterly winds in November, which suggests that the occurrence of tailwinds favorable for migration before the onset of winter was a key factor in whether brant migrated from Alaska or remained there during winter. Winter distribution of brant on the Alaska Peninsula was highly variable and influenced by ice cover, particularly at the heavily used Izembek Lagoon. Observations of previously marked brant indicated that the Alaska wintering population was composed primarily of birds originating from Arctic breeding colonies that appear to be growing. Numbers of brant in Alaska during winter will likely increase as temperatures rise and ice cover decreases at high latitudes in response to climate warming.

Alaska↗