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At least 1,279 records · Page 71Linked to original sources
USGS2013

Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability

Subalpine meadows are some of the most ecologically important components of mountain landscapes, and primary productivity is important to the maintenance of meadow functions. Understanding how changes in primary productivity are associated with variability in moisture and temperature will become increasingly important with current and anticipated changes in climate. Our objective was to describe patterns and variability in aboveground live vascular plant biomass in relation to climatic factors. We harvested aboveground biomass at peak growth from four 64-m 2 plots each in xeric, mesic, and hydric meadows annually from 1994 to 2000. Data from nearby weather stations provided independent variables of spring snow water content, snow-free date, and thawing degree days for a cumulative index of available energy. We assembled these climatic variables into a set of mixed effects analysis of covariance models to evaluate their relationships with annual aboveground net primary productivity (ANPP), and we used an information theoretic approach to compare the quality of fit among candidate models. ANPP in the xeric meadow was negatively related to snow water content and thawing degree days and in the mesic meadow was negatively related to snow water content. Relationships between ANPP and these 2 covariates in the hydric meadow were not significant. Increasing snow water content may limit ANPP in these meadows if anaerobic conditions delay microbial activity and nutrient availability. Increased thawing degree days may limit ANPP in xeric meadows by prematurely depleting soil moisture. Large within-year variation of ANPP in the hydric meadow limited sensitivity to the climatic variables. These relationships suggest that, under projected warmer and drier conditions, ANPP will increase in mesic meadows but remain unchanged in xeric meadows because declines associated with increased temperatures would offset the increases from decreased snow water content.

Western North American Naturalist↗
USGS1998

Seasonal and interannual variations of atmospheric CO2 and climate

Interannual variations of atmospheric CO 2 concentrations at Mauna Loa are almost masked by the seasonal cycle and a strong trend; at the South Pole, the seasonal cycle is small and is almost lost in the trend and interannual variations. Singular-spectrum analysis (SSA) is used here to isolate and reconstruct interannual signals at both sites and to visualize recent decadal changes in the amplitude and phase of the seasonal cycle. Analysis of the Mauna Loa CO 2 series illustrates a hastening of the CO 2 seasonal cycle, a close temporal relation between Northern Hemisphere (NH) mean temperature trends and the amplitude of the seasonal CO 2 cycle, and tentative ties between the latter and seasonality changes in temperature over the NH continents. Variations of the seasonal CO 2 cycle at the South Pole differ from those at Mauna Loa: it is phase changes of the seasonal cycle at the South Pole, rather than amplitude changes, that parallel hemispheric and global temperature trends. The seasonal CO 2 cycles exhibit earlier occurrences of the seasons by 7 days at Mauna Loa and 18 days at the South Pole. Interannual CO 2 variations are shared at the two locations, appear to respond to tropical processes, and can be decomposed mostly into two periodicities, around (3 years) -1 and (4 years) -1 , respectively. Joint SSA analyses of CO 2 concentrations and tropical climate indices isolate a shared mode with a quasi-triennial (QT) period in which the CO 2 and sea-surface temperature (SST) participation are in phase opposition. The other shared mode has a quasi-quadrennial (QQ) period and CO 2 variations are in phase with the corresponding tropical SST variations throughout the tropics. Together these interannual modes exhibit a mean lag between tropical SSTs and CO 2 variations of about 6–8 months, with SST leading. Analysis of the QT and QQ signals in global gridded SSTs, joint SSA of CO 2 and δ13C isotopic ratios, and SSA of CO 2 and NH-land temperatures indicate that the QT variations in CO 2 mostly reflect upwelling variations in the eastern tropical Pacific. QQ variations are dominated by the CO 2 signature of terrestrial-ecosystem response to global QQ climate variations. Climate variations associated with these two interannual components of tropical variability have very different effects on global climate and, especially, on terrestrial ecosystems and the carbon cycle.

Tellus, Series B: Chemical and Physical Meteorolog↗
USGS1999

The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO2 in the United States

We use the Terrestrial Ecosystem Model (TEM, Version 4.1) and the land cover data set of the international geosphere-biosphere program to investigate how increasing atmospheric CO2 concentration and climate variability during 1900-1994 affect the carbon storage of terrestrial ecosystems in the conterminous USA, and how carbon storage has been affected by land-use change. The estimates of TEM indicate that over the past 95 years a combination of increasing atmospheric CO2 with historical temperature and precipitation variability causes a 4.2% (4.3 Pg C) decrease in total carbon storage of potential vegetation in the conterminous US, with vegetation carbon decreasing by 7.2% (3.2 Pg C) and soil organic carbon decreasing by 1.9% (1.1 Pg C). Several dry periods including the 1930s and 1950s are responsible for the loss of carbon storage. Our factorial experiments indicate that precipitation variability alone decreases total carbon storage by 9.5%. Temperature variability alone does not significantly affect carbon storage. The effect of CO2 fertilization alone increases total carbon storage by 4.4%. The effects of increasing atmospheric CO2 and climate variability are not additive. Interactions among CO2, temperature and precipitation increase total carbon storage by 1.1%. Our study also shows substantial year-to-year variations in net carbon exchange between the atmosphere and terrestrial ecosystems due to climate variability. Since the 1960s, we estimate these terrestrial ecosystems have acted primarily as a sink of atmospheric CO2 as a result of wetter weather and higher atmospheric CO2 concentrations. For the 1980s, we estimate the natural terrestrial ecosystems, excluding cropland and urban areas, of the conterminous US have accumulated 78.2 Tg C yr-1 because of the combined effect of increasing atmospheric CO2 and climate variability. For the conterminous US, we estimate that the conversion of natural ecosystems to cropland and urban areas has caused a 18.2% (17.7 Pg C) reduction in total carbon storage from that estimated for potential vegetation. The carbon sink capacity of natural terrestrial ecosystems in the conterminous US is about 69% of that estimated for potential vegetation.

Tellus, Series B: Chemical and Physical Meteorolog↗
USGS2015

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science↗
USGS2010

Effects of simultaneous climate change and geomorphic evolution on thermal characteristics of a shallow Alaskan lake

We used a hydrodynamics model to assess the consequences of climate warming and contemporary geomorphic evolution for thermal conditions in a large, shallow Alaskan lake. We evaluated the effects of both known climate and landscape change, including rapid outlet erosion and migration of the principal inlet stream, over the past 50 yr as well as future scenarios of geomorphic restoration. Compared to effects of air temperature during the past 50 yr, lake thermal properties showed little sensitivity to substantial (~60%) loss of lake volume, as the lake maximum depth declined from 6 m to 4 m driven by outlet erosion. The direction and magnitude of future lake thermal responses will be driven largely by the extent of inlet stream migration when it occurs simultaneously with outlet erosion. Maintaining connectivity with inlet streams had substantial effects on buffering lake thermal responses to warming climate. Failing to account for changing rates and types of geomorphic processes under continuing climate change may misidentify the primary drivers of lake thermal responses and reduce our ability to understand the consequences for aquatic organisms.

Alaska↗
USGS2019

Climatic variation drives growth potential of juvenile Chinook Salmon (Oncorhynchus tshawytscha) along a sub-Arctic boreal riverscape

Climatic variation is a key driver of freshwater physical processes that in turn control stream fish growth and population dynamics at fine spatial scales and species distributions across broad landscapes. A recent downturn in Chinook Salmon returns across the Yukon River basin, Alaska, USA, and Yukon Territories, Canada, has led to hardship among user groups and increased interest in understanding how freshwater processes affect population persistence within this important commercial, recreational, and subsistence fishery. Here we present results for the Chena River basin, interior Alaska, where we used field observations and riverscape-scale spatially-explicit models to assess the influence of stream temperature on juvenile Chinook Salmon growth potential among years (2003 2015) and across 438 stream-km. We ran bioenergetic simulations for warm and cool year scenarios and contrasted temperature model precision and growth among different habitat types (small and large tributaries, main stem, side channels) based on field estimates of growth, size, and diet, and measured stream temperatures. Stream temperature regimes predicted from remotely-sensed land surface temperature were precise during the open water season (R2 > 0.87; RMSE < 1.1 C) although the relationship was weakest in groundwater-mediated tributary habitats. Field observations revealed salmon were 67% larger by mass (g) in September during a warm year versus a cool year from main stem sites. Bioenergetic simulations predicted that, on average, growth potential was 42% higher in warm years, although growth potential varied across the riverscape as much as 60% between cool upstream and warm downstream habitats. Climate variability is clearly an important driver of freshwater habitat conditions and has a large role in controlling freshwater growth of juvenile salmon. A better understanding of how climate influences growth conditions in different habitat types and across broad landscapes will be critical for conservation and management of Alaskan Chinook Salmon stocks under an expected warmer and more variable climate.

Alaska, Yukon↗
USGS2011

Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem

In the boreal region, soil organic carbon (OC) dynamics are strongly governed by the interaction between wildfire and permafrost. Using a combination of field measurements, numerical modeling of soil thermal dynamics, and mass-balance modeling of OC dynamics, we tested the sensitivity of soil OC storage to a suite of individual climate factors (air temperature, soil moisture, and snow depth) and fire severity. We also conducted sensitivity analyses to explore the combined effects of fire-soil moisture interactions and snow seasonality on OC storage. OC losses were calculated as the difference in OC stocks after three fire cycles (~500 yr) following a prescribed step-change in climate and/or fire. Across single-factor scenarios, our findings indicate that warmer air temperatures resulted in the largest relative soil OC losses (~5.3 kg C m −2 ), whereas dry soil conditions alone (in the absence of wildfire) resulted in the smallest carbon losses (~0.1 kg C m −2 ). Increased fire severity resulted in carbon loss of ~3.3 kg C m −2 , whereas changes in snow depth resulted in smaller OC losses (2.1–2.2 kg C m −2 ). Across multiple climate factors, we observed larger OC losses than for single-factor scenarios. For instance, high fire severity regime associated with warmer and drier conditions resulted in OC losses of ~6.1 kg C m −2 , whereas a low fire severity regime associated with warmer and wetter conditions resulted in OC losses of ~5.6 kg C m −2 . A longer snow-free season associated with future warming resulted in OC losses of ~5.4 kg C m −2 . Soil climate was the dominant control on soil OC loss, governing the sensitivity of microbial decomposers to fluctuations in temperature and soil moisture; this control, in turn, is governed by interannual changes in active layer depth. Transitional responses of the active layer depth to fire regimes also contributed to OC losses, primarily by determining the proportion of OC into frozen and unfrozen soil layers.

Biogeosciences↗
USGS2017

The ACER pollen and charcoal database: A global resource to document vegetation and fire response to abrupt climate changes during the last glacial period

Quaternary records provide an opportunity to examine the nature of the vegetation and fire responses to rapid past climate changes comparable in velocity and magnitude to those expected in the 21st century. The best documented examples of rapid climate change in the past are the warming events associated with the Dansgaard-Oeschger (D-O) cycles during the last glacial period, which were sufficiently large to have had a potential feedback through changes in albedo and greenhouse gas emissions on climate. Previous reconstructions of vegetation and fire changes during the D-O cycles used independently constructed age models, making it difficult to compare the changes between different sites and regions. Here we present the ACER (Abrupt Climate Changes and Environmental Responses) global database which includes 93 pollen records from the last glacial period (73–15 ka) with a temporal resolution better than 1,000 years, 32 of which also provide charcoal records. A harmonized and consistent chronology based on radiometric dating (¹⁴C, ²³⁴U/²³⁰Th, OSL, ⁴⁰Ar/³⁹Ar dated tephra layers) has been constructed for 86 of these records, although in some cases additional information was derived using common control points based on event stratigraphy. The ACER database compiles metadata including geospatial and dating information, pollen and charcoal counts and pollen percentages of the characteristic biomes, and is archived in Microsoft AccessTM at doi:10.1594/PANGAEA.870867.

Earth System Science Data↗
USGS2019

Influence of multi-decadal land use, irrigation practices and climate on riparian corridors across the Upper Missouri River Headwaters Basin, Montana

The Upper Missouri River Headwaters Basin (36,400 km2) depends on its river corridors to support irrigated agriculture and world-class trout fisheries. We evaluated trends (1984-2016) in riparian wetness, an indicator of riparian condition, in peak irrigation months (June, July, August) for 158 km2 of riparian area across the basin using the Landsat Normalized Difference Wetness Index (NDWI). We found that 8 of the 19 riparian reaches across the basin showed a significant drying trend over this period, including all three basin outlet reaches along the Jefferson, Madison and Gallatin Rivers. The influence of upstream climate was quantified using per reach random forest regressions. Much of the interannual variability in the NDWI was explained by climate, especially by drought indices and annual precipitation, but the significant temporal drying trends persisted in the NDWI-climate model residuals, indicating that trends were not entirely attributable to climate. Over the same period we documented a basin-wide shift from 9% of agriculture irrigated with center pivot irrigation to 50% irrigated with center pivot irrigation. Riparian reaches with a drying trend had a greater increase in the total area with center pivot irrigation (within-reach and upstream from the reach) relative to riparian reaches without such a trend (p<0.05). The drying trend, however, did not extend to river discharge. Over the same period, stream gages (n=7) showed a positive correlation with riparian wetness (p<0.05), but no trend in summer river discharge, suggesting that riparian areas may be more sensitive to changes in irrigation return flows, relative to river discharge. Identifying trends in riparian vegetation is a critical precursor to enhancing the resiliency of river systems and associated riparian corridors.

Montana↗
USGS2023

Trade-offs in adapting to changes in climate, land use, and water availability in California

Changes in land use and land cover, water systems, and climate are inextricably linked, and their combined stresses have had severe impacts in many regions worldwide. Integrated adaptation planning can support adaptive capacity by helping institutions manage land and water resources at regional to local scales. Linkages between these stressors mean that planners are often faced with potential trade-offs, and how to couple social and environmental sustainability remains a key question. We explore these questions in California’s Central Coast, a region that is already experiencing serious water shortages, housing shortages, rapid expansion of perennial agriculture, and severe droughts that are projected to become worse with climate change. Linked models of land use change (the Land Use and Carbon + Water Simulator [LUCAS-W]), water resources (LUCAS-W), and climate (the Basin Characterization Model [BCM]) produced forecasts of exposure to regional changes at 270-m resolution. We worked with regional stakeholders to develop a matrix of nine vulnerability measures that assessed key sensitivities to these changes. Each vulnerability measure combined one of the three exposure projections with spatial datasets representing one of three sensitivity communities (agricultural, domestic, or ecological). We assessed how five scenarios of land-use and water management strategies under consideration by regional planners could provide institutional, top-down adaptive capacity, and whether there were trade-offs in sustainable development goals for these communities. We found that specific land and water management strategies could greatly reduce regional vulnerability, particularly programs to cap water extractions to sustainable levels. The most dramatic trade-off was between the strategy of water demand caps that increased risk of habitat loss and ecosystem preservation that increased water vulnerability. However, trade-offs were usually limited and spatially localized, suggesting local tailoring of the strategies we assessed could reduce them. Trade-offs were more frequent across exposure classes (land use vs. water vs. climate changes) rather than sensitivity classes (agricultural vs. domestic vs. ecological communities), suggesting win-win opportunities for natural resource management. Our vulnerability maps can inform prioritization efforts for local adaptation planning.

California↗
USGS2000

Seasonal-range forecasting of the ozark climate by a principal component regression scheme with antecedent sea surface temperatures and upper air conditions

On the basis of principal component analysis of long-term climatological records, regression models are formulated and forecast experiments are conducted for monthly temperature and precipitation of the Ozark Highlands area, a large area of low mountains and plateau in the south central midwestern United States. Predictors include global sea surface temperatures, hemispheric upper air fields and the local climate observations. The experiments for all months of the year are performed with the data from continuous 15-year segments of 1961-75 to 1980-94 for those years beyond the respective data segments. Relationships between regional-scale and large-scale climate variables are investigated by cross-correlation analysis to identify useful teleconnections for seasonal-range forecasting. The predictability of the Ozark Highlands climate is examined with the multiple linear regression scheme and the principal component regression scheme. It is shown that the forecast performance by the latter is superior to that of the former. The results of the extensive forecast experiments reveal the useful and stable predictability of the Ozark Highlands climate elements. The validity of the forecasting models is verified for up to 10 years after the data period of regression formulation.

Arkansas, Missouri↗
USGS2005

Climate patterns as predictors of amphibians species richness and indicators of potential stress

Amphibians occupy a range of habitats throughout the world, but species richness is greatest in regions with moist, warm climates. We modeled the statistical relations of anuran and urodele species richness with mean annual climate for the conterminous United States, and compared the strength of these relations at national and regional levels. Model variables were calculated for county and subcounty mapping units, and included 40-year (1960-1999) annual mean and mean annual climate statistics, mapping unit average elevation, mapping unit land area, and estimates of anuran and urodele species richness. Climate data were derived from more than 7,500 first-order and cooperative meteorological stations and were interpolated to the mapping units using multiple linear regression models. Anuran and urodele species richness were calculated from the United States Geological Survey's Amphibian Research and Monitoring Initiative (ARMI) National Atlas for Amphibian Distributions. The national multivariate linear regression (MLR) model of anuran species richness had an adjusted coefficient of determination (R2) value of 0.64 and the national MLR model for urodele species richness had an R2 value of 0.45. Stratifying the United States by coarse-resolution ecological regions provided models for anUrans that ranged in R2 values from 0.15 to 0.78. Regional models for urodeles had R2 values. ranging from 0.27 to 0.74. In general, regional models for anurans were more strongly influenced by temperature variables, whereas precipitation variables had a larger influence on urodele models.

Alytes↗
USGS2009

Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Proceedings of the National Academy of Sciences↗
USGS2011

Analysis of trends in climate, streamflow, and stream temperature in north coastal California

As part of a broader project analyzing trends in climate, streamflow, vegetation, salmon, and ocean conditions in northern California national park units, we compiled average monthly air temperature and precipitation data from 73 climate stations, streamflow data from 21 river gaging stations, and limited stream temperature data from salmon-bearing rivers in north coastal California. Many climate stations show a statistically significant increase in both average maximum and average minimum air temperature in early fall and midwinter during the last century. Concurrently, average September precipitation has decreased. In many coastal rivers, summer low flow has decreased and summer stream temperatures have increased, which affects summer rearing habitat for salmonids. Nevertheless, because vegetative cover has also changed during this time period, we cannot ascribe streamflow changes to climate change without first assessing water budgets. Although shifts in the timing of the centroid of runoff have been documented in snowmelt-dominated watersheds in the western United States, this was not the case in lower elevation coastal rivers analyzed in this study.

California↗
USGS1980

Mid- Tertiary climate of southeastern United States, the sporomorph evidence

Climatic affinities of modern genera represented by late Eocene sporomorphs suggest that the climate of that time in southeastern United States was winter-dry tropical close to the Gulf of Mexico and marginal humid subtropical on the upper Coastal Plain. Lack of change of the sporomorph assemblages suggests that the climate of southeastern United States did not change appreciably from late in the middle Eocene until nearly the end of the Eocene. Then the climate rapidly became cooler and perhaps drier, a regime that persisted into the early Oligocene.

Journal of Paleontology↗
USGS1993

Effects of climate change on drought risks in the Apalachicola, Chattahoochee, and Flint River basin

Possible effects of climate change on the Apalachicola-Chattahoochee-Flint (ACF) River basin is simulated with a computer model. Model inputs are monthly temperature and precipitation that simulate several possible climate change scenarios. Preliminary results for climate scenarios based on output for three popular general circulation models indicate that lower flows will occur more frequently if the regional climate warms and monthly precipitation decreases during critical summer months.

Conference Paper↗
USGS1994

Nested-model approach to investigate climate change

Determination of the spatial and temporal distribution of precipitation in mountainous regions is critical for assessing the effects of climate variability on water resources in these regions. Potential effects of climate change on water resources in the Gunnison River basin of southwestern Colorado currently are being studied using a nested-model approach to disaggregate large-scale general circulation model output to account for smaller-scale processes. This paper presents a disaggregation technique in which scenarios of possible climate change will be developed by nesting a global general circulation model, a mesoscale climate model, a local orographic precipitation model, and a watershed model.

Conference Paper↗
USGS1999

Socioeconomic impacts of climate change on U.S. water supplies

A greenhouse warming would have major effects on water supplies and demands. A framework for examining the socioeconomic impacts associated with changes in the long-term availability of water is developed and applied to the hydrologic implications of the Canadian and British Hadley2 general circulation models (GCMs) for the 18 water resource regions in the conterminous United States. The climate projections of these two GCMs have very different implications for future water supplies and costs. The Canadian model suggests most of the nation would be much drier in the year 2030. Under the least-cost management scenario the drier climate could add nearly $105 billion to the estimated costs of balancing supplies and demands relative to the costs without climate change. Measures to protect instream flows and irrigation could result in significantly higher costs. In contrast, projections based on the Hadley model suggest water supplies would increase throughout much of the nation, reducing the costs of balancing water supplies with demands relative to the no-climate-change case.

Conference Paper↗