USGS Science⌕ Search

SEARCH · USGS Science

Results for “Climate Change”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41Linked to original sources
USGS2018

How will East African maize yields respond to climate change and can agricultural development mitigate this response?

We analyze the response of Kenyan maize yields to near-term climate change and explore potential mitigation options. We model county level yields as a function of rainfall and temperature during a period of increased regional warming and drying (1989–2008). We then do a counter factual analysis by comparing existing maize yields from 2000 to 2008 to what yields might have been if observed warming and drying trends had not occurred. We also examine maize yields based on projected 2026–2040 climate trends. Without the observed warming and drying trends, Eastern Kenya would have had an 8% increase in maize yields, which in turn would have led to a net production increase of 500,000 metric tons. In Western Kenya, the magnitude of change is higher but the relative changes in predicted values are smaller. If warming and drying trends continue, we expect future maize yields to decline by 11% in Eastern Kenya (vs. 7% in Western Kenya). We also examine whether these future losses might be offset through agricultural development. For that analysis, we use a household panel dataset (2000, 2005) with measurements of individual farm plot yields, inputs, and outputs. We find that under a scenario of aggressive adoption of hybrid seeds and fertilizer usage coupled with warming and drying trends, yields in Western Kenya might increase by 6% while those in Eastern Kenya could increase by 14%. This increase in yields might be larger if there is a corresponding increase in usage of drought-tolerant hybrids. However, wide prediction intervals across models highlight the uncertainty in these outcomes and scenarios.

Climatic Change↗
USGS2010

Initial Results from a Study of Climatic Changes and the Effect on Wild Sheep Habitat in Selected Study Areas of Alaska

Climate change theorists have projected striking changes in local weather on earth due to increases in temperature. These predicted changes may cause melting glaciers and ice caps, rising sea levels, increasing desertification and other environmental changes which seem likely to affect presumed indicator species as harbingers of more significant changes. Wild sheep, even though they are one of the more successful mammalian taxa since Pleistocene times, exhibit a suite of adaptations to glacier driven environments which may be presumed to render them sensitive to environmental changes. The authors began investigation with these assumptions by comparing changes, as determined by satellite imagery, in glacier extent in our study areas in Denali National Park, Alaska, during the last 30 years. Our findings showed the extent of glacial retreat in Alaska during this time period was approximately 40-50 percent as measured by ablation zone and retreat of terminal moraines. During the first half of this 30-year period, Dall sheep (Ovis dalli dalli) populations were stable at historically recorded highs. In the early to mid-1990s, Dall sheep populations in Alaska declined from an historical estimated high of 75,000 sheep to the presently estimated 40-50,000. The declines seemed to be weather related, on the basis of the presumption that lamb survival rates are primarily weather-mediated in Alaska. Changes in local weather appear, at this point, to be correlated with oscillation in the Pacific Current in the Northern Pacific ocean. Of course, changes in local weather affect forage abundance and quality seasonally. In investigating a possible linkage of weather to seasonal forage abundance and quality, we also investigated changes in snow and ice extent and distribution, as well as increased water runoff associated with permafrost and depleted glaciers. Databases were assembled from a wide variety of remotely sensed satellite data, ground-based observations, and historical data bases relating to Dall sheep habitats in selected study areas. Alaska's sheep habitats are typified by long, narrow bands of mountainous uplifts generally arrayed west-to-east, and perpendicular to prevailing south-to-north weather-front movements. Classic Dall sheep habitat occurs on snow-shadowed slopes within these narrow mountainous habitats. On the basis of these data, we offer an explanatory hypothesis relating Dall sheep welfare to weather and climate-influenced nutrition and a monitoring scheme, which should produce data sufficient to test the robustness of this hypothesis. If correlated with population changes, the methods used in our comparative observations may provide long-term monitoring tools for wildlife managers and be applicable in other widely-dispersed wild sheep habitats. If no significant correlations emerge from our modeling exercises, the notion that wild sheep are a sufficiently sensitive species to be seen as an indicator species will have to be reexamined.

Open-File Report↗
USGS2018

Future southcentral US wildfire probability due to climate change

Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

Climate Change↗
USGS2006

Baldcypress swamp management and climate change

In the future, climates may become warmer and drier in the southeastern United States; as a result, the range of baldcypress (Taxodium distichum) swamps may shrink. Managers of baldcypress swamps at the southern edge of the range may face special challenges in attempting to preserve these swamp habitats in the future if climates become warmer and drier.

Open-File Report↗
USGS2012

Evidence from 12-year study links ecosystem changes in the Gulf of Maine with climate change

Investigators at the Bigelow Laboratory for Ocean Sciences (East Boothbay, Maine) and the U.S. Geological Survey collaborated to study ecosystem changes in the Gulf of Maine. As part of the Gulf of Maine North Atlantic Time Series (GNATS), a comprehensive long-term study of hydrographic, biological, optical and chemical properties, multiple cruises have been conducted each year since 2001 by using a portable laboratory aboard different vessels (figure 1) and occasionally a remotely controlled glider (figure 2). Data collected during these cruises, when analyzed within the context of a century of climatological and streamflow data, document changes in temperature, salinity, and coastal ocean productivity that appear to be related to recent increases in precipitation and streamflow. These results are evidence of a link between changing hydrologic conditions on land and changes in coastal ocean productivity.

EcoSystem Indicator Partnership Journal↗
USGS2021

Optimal strategies for managing wildlife harvest under climate change

Wildlife populations are experiencing shifting dynamics due to climate and landscape change. Management policies that fail to account for non‐stationary dynamics may fail to achieve management objectives. We establish a framework for understanding optimal strategies for managing a theoretical harvested population under non‐stationarity. Building from harvest theory, we develop scenarios representing changes in population growth rate ( ) or carrying capacity ( ) and derive time‐dependent optimal harvest policies using stochastic dynamic programming. We then evaluate the cost of falsely assuming stationarity by comparing the outcomes of forward projections in which either the optimal policy or a stationary policy is applied. When declines over time, the stationary policy leads to an underharvest of the population, resulting in less harvest over the short term but leaving the population in a higher‐value state. When declines over time, the stationary policy leads to overharvest, resulting in greater harvest returns in the short term but leaving the population in a lower and potentially more vulnerable state. This work demonstrates the basic properties of time‐dependent harvest management and provides a framework for evaluating the many outstanding questions about optimal management strategies under climate change. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Journal of Wildlife Management↗
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

Effects of climate change and anthropogenic modification on a disturbance-dependent species in a large riverine system

Humans have altered nearly every natural disturbance regime on the planet through climate and land-use change, and in many instances, these processes may have interacting effects. For example, projected shifts in temperature and precipitation will likely influence disturbance regimes already affected by anthropogenic fire suppression or river impoundments. Understanding how disturbance-dependent species respond to complex and interacting environmental changes is important for conservation efforts. Using field-based demographic and movement rates, we conducted a metapopulation viability analysis for piping plovers ( Charadrius melodus ), a threatened disturbance-dependent species, along the Missouri and Platte rivers in the Great Plains of North America. Our aim was to better understand current and projected future metapopulation dynamics given that natural disturbances (flooding or high-flow events) have been greatly reduced by river impoundments and that climate change could further alter the disturbance regime. Although metapopulation abundance has been substantially reduced under the current suppressed disturbance regime (high-flow return interval ~ 20 yr), it could grow if the frequency of high-flow events increases as predicted under likely climate change scenarios. We found that a four-year return interval would maximize metapopulation abundance, and all subpopulations in the metapopulation would act as sources at a return interval of 15 yr or less. Regardless of disturbance frequency, the presence of even a small, stable source subpopulation buffered the metapopulation and sustained a low metapopulation extinction risk. Therefore, climate change could have positive effects in ecosystems where disturbances have been anthropogenically suppressed when climatic shifts move disturbance regimes toward more historical patterns. Furthermore, stable source populations, even if unintentionally maintained through anthropogenic activities, may be critical for the persistence of metapopulations of early-successional species under both suppressed disturbance regimes and disturbance regimes where climate change has further altered disturbance frequency or scope.

Iowa, Nebraska, South Dakota↗
USGS2022

Projecting flood frequency curves under near-term climate change

Flood-frequency curves, critical for water infrastructure design, are typically developed based on a stationary climate assumption. However, climate changes are expected to violate this assumption. Here, we propose a new, climate-informed methodology for estimating flood-frequency curves under non-stationary future climate conditions. The methodology develops an asynchronous, semiparametric local-likelihood regression (ASLLR) model that relates moments of annual maximum flood to climate variables using the generalized linear model. We estimate the first two marginal moments (MM) – the mean and variance – of the underlying log-Pearson Type-3 distribution from the ASLLR with the monthly rainfall and temperature as predictors. The proposed methodology, ASLLR-MM, is applied to 40 U.S. Geological Survey streamgages covering 18 water resources regions across the conterminous United States. A correction based on the aridity index was applied on the estimated variance, after which the ASLLR-MM approach was evaluated with both historical (1951–2005) and projected (2006–2035, under RCP4.5 and RCP8.5) monthly precipitation and temperature from eight Global Circulation Models (GCMs) consisting of 39 ensemble members. The estimated flood-frequency quantiles resulting from the ASLLR-MM and GCM members compare well with the flood-frequency quantiles estimated using the historical period of observed climate and flood information for humid basins, whereas the uncertainty in model estimates is higher in arid basins. Considering additional atmospheric and land-surface conditions and a multi-level model structure that includes other basins in a region could further improve the model performance in arid basins.

Water Resources Research↗
USGS2025

From models to management: Implementing the climate-change refugia conservation cycle in national parks of the northeastern United States

Managing climate-change refugia is a commonly recommended strategy for conserving biodiversity. However, few efforts have moved beyond the modeling phase of refugia science to management. Here, we present two case studies that move beyond modeling to testing models and management. In the first case study, we model refugia for two plant species (three-toothed cinquefoil [ Sibbaldia tridentata ] and black crowberry [ Empetrum nigrum ]) in Acadia National Park, Maine, United States, and use greenhouse experiments, common-garden experiments, and participatory science to evaluate the output of those models. Our results suggest that three-toothed cinquefoil growth and survival are reduced under increased temperatures as models predict. However, other variables (e.g., soil moisture and salinity) might also be important to modeling and managing refugia for both species. National Park Service staff and partners have been directing restoration for both species to refugia, but are also exploring other adaptation strategies. In the second case study, we demonstrate that existing prioritization processes for habitat restoration in national parks of the northeastern United States rarely incorporate refugia for two indicator species: Jefferson salamander ( Ambystoma jeffersonianum ) and grasshopper sparrow ( Ammodramus savannarum ). Our work demonstrates that moving beyond modeling can improve models and lead to new management insights.

Northeast United States↗
USGS2012

Adaptation to climate change: changes in farmland use and stocking rate in the U.S.

This paper examines possible adaptations to climate change in terms of pasture and crop land use and stocking rate in the United States (U.S.). Using Agricultural Census and climate data in a statistical model, we find that as temperature and precipitation increases agricultural commodity producers respond by reducing crop land and increasing pasture land. In addition, cattle stocking rate decreases as the summer Temperature-humidity Index (THI) increases and summer precipitation decreases. Using the statistical model with climate data from four General Circulation Models (GCMs), we project that land use shifts from cropping to grazing and the stocking rate declines, and these adaptations are more pronounced in the central and the southeast regions of the U.S. Controlling for other farm production variables, crop land decreases by 6 % and pasture land increases by 33 % from the baseline. Correspondingly, the associated economic impact due to adaptation is around -14 and 29 million dollars to crop producers and pasture producers by the end of this century, respectively. The national and regional results have implications for farm programs and subsidy policies.

Mitigation and Adaptation Strategies for Global Ch↗
USGS2015

Climate change and physical disturbance cause similar community shifts in biological soil crusts

Biological soil crusts (biocrusts)—communities of mosses, lichens, cyanobacteria, and heterotrophs living at the soil surface—are fundamental components of drylands worldwide, and destruction of biocrusts dramatically alters biogeochemical processes, hydrology, surface energy balance, and vegetation cover. While there has been long-standing concern over impacts of 5 physical disturbances on biocrusts (e.g., trampling by livestock, damage from vehicles), there is also increasing concern over the potential for climate change to alter biocrust community structure. Using long-term data from the Colorado Plateau, USA, we examined the effects of 10 years of experimental warming and altered precipitation (in full-factorial design) on biocrust communities, and compared the effects of altered climate with those of long-term physical 10 disturbance (>10 years of replicated human trampling). Surprisingly, altered climate and physical disturbance treatments had similar effects on biocrust community structure. Warming, altered precipitation frequency [an increase of small (1.2 mm) summer rainfall events], and physical disturbance from trampling all promoted early successional community states marked by dramatic declines in moss cover and increased cyanobacteria cover, with more variable effects 15 on lichens. While the pace of community change varied significantly among treatments, our results suggest that multiple aspects of climate change will affect biocrusts to the same degree as physical disturbance. This is particularly disconcerting in the context of warming, as temperatures for drylands are projected to increase beyond those imposed by the climate treatments used in our study.

PNAS↗
USGS2023

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

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

Conservation Science and Practice↗
USGS2018

Responses of unimpaired flows, storage, and managed flows to scenarios of climate change in the San Francisco Bay-Delta watershed

Projections of meteorology downscaled from global climate model runs were used to drive a model of unimpaired hydrology of the Sacramento/San Joaquin watershed, which in turn drove models of operational responses and managed flows. Twenty daily climate change scenarios for water years 1980–2099 were evaluated with the goal of producing inflow boundary conditions for a watershed sediment model and for a hydrodynamical model of the San Francisco Bay-Delta estuary. The resulting time series of meteorology, snowpack, unimpaired flow, reservoir storage, and managed flow were analyzed for century-scale trends. In the Sacramento basin, which dominates Bay-Delta inflows, all 20 scenarios portrayed warming trends (with a mean of 4.1 °C) and most had precipitation increases (with a mean increase of 9%). Sacramento basin snowpack water equivalent declined sharply (by 89%), which was associated with a major shift toward earlier unimpaired runoff timing (33% more flow arriving prior to 1 April). Sacramento basin reservoirs showed large declines in end-of-September storage. Water-year averaged outflows increased for most scenarios for both unimpaired and impaired flows, and frequency of extremely high daily unimpaired and impaired flows increased (increases of 175% and 170%, respectively). Managed Delta inflows were projected to experience large increases in the wet season and declines in the dry season. Changes in management strategy and infrastructure can mitigate some of these changes, though to what degree is uncertain.

California↗
USGS2016

Midcontinent Prairie-Pothole wetlands and climate change: An Introduction to the Supplemental Issue

The multitude of wetlands in the Prairie Pothole Region of North America forms one of Earth’s largest wetland complexes. The midcontinent location exposes this ecologically and economically important wetland system to a highly variable climate, markedly influencing ponded-water levels, hydroperiods, chemical characteristics, and biota of individual basins. Given their dominance on the landscape and recognized value, great interest in how projected future changes in climate will affect prairie-pothole wetlands has developed and spawned much scientific research. On June 2, 2015, a special symposium, “Midcontinent Prairie-Pothole Wetlands: Influence of a Changed Climate,” was held at the annual meeting of the Society of Wetland Scientists in Providence, Rhode Island, USA. The symposium’s twelve presenters covered a wide range of relevant topics delivered to a standing-room-only audience. Following the symposium, the presenters recognized the need to publish their presented papers as a combined product to facilitate widespread distribution. The need for additional papers to more fully cover the topic of prairie-pothole wetlands and climate change was also identified. This supplemental issue of Wetlands is the realization of that vision.

Prairie Pothole Region↗
USGS2020

Baseline conditions and projected future hydro-climatic change in National Parks in the conterminous United States

The National Park Service (NPS) manages hundreds of parks in the United States, and many contain important aquatic ecosystems and/or threatened and endangered aquatic species vulnerable to hydro-climatic change. Effective management of park resources under future hydro-climatic uncertainty requires information on both baseline conditions and the range of projected future conditions. A monthly water balance model was used to assess baseline (1981-1999) conditions and a range of projected future hydro-climatic conditions in 374 NPS parks. General circulation model outputs representing 214 future climate simulations were used to drive the model. Projected future changes in temperature (T), precipitation (P), and runoff (R) are expressed as departures from historical baselines. Climate simulations indicate increasing T in 2030 for all parks with 50th percentile simulations projecting increases of 1.67 oC or more in 50% of parks. Departures in 2030 P indicate a mix of mostly increases and some decreases, with 50th percentile simulations projecting increases in P in more than 70% of parks. Departures in R for 2030 are mostly decreases , with the 50th percentile simulations projecting decreases in R in more than 50% of parks in all seasons except winter. Hence in many parks, R is projected to decrease even when P is projected to increase because of increasing T in all NPS parks. Projected changes in future hydro-climatic conditions can also be assessed for individual parks, and Rocky Mountain National Park and Congaree National Park are used as examples.

Water↗
USGS2021

Impacts of climate change on groundwater availability and spring flows: Observations from the highly productive Medicine Lake Highlands/Fall River Springs Aquifer System

Medicine Lake Highlands/Fall River Springs Aquifer System, located in northeastern California, is home to some of the largest first-order springs in the United States. This work assesses the likely effects of projected climate change on spring flow. Four anticipated climate futures (GFDL A2, GFDL B1, CCSM4 rcp 8.5, CNRM rcp 8.5) for California, which predict a range of conditions (generally warming and transitioning from snow to rain with variable amounts of total precipitation), are postulated to affect groundwater recharge primarily by changing evapotranspiration. The linkages between climate variables and spring flow are evaluated using a water balance model that represents the physics of evapotranspiration and recharge, the Basin Characterization Model. Three of the four climate scenarios (GFDL A2, GFDL B1, CCSM4 rcp 8.5) project that by the year 2100, groundwater recharge (and consequently decreased spring flow) will decrease by 27%, 21%, and 9%, respectively. The fourth scenario (CNRM rcp 8.5) showed an increase in recharge of 32% due to a significant increase in precipitation (27%). Evapotranspiration increases due to a shift in the type of precipitation and a longer growing season. While the likelihood of each scenario is outside the scope of this work, unless total precipitation increases dramatically in the future, increased temperatures and decreasing precipitation will likely result in reduced spring flows, along with warmer water temperatures in downstream habitats.

California↗