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At least 811 records · Page 45Linked to original sources

USGS2016

Using climate, energy, and spatial-based hypotheses to interpret macroecological patterns of North America chelonians

Our study investigates how factors, such as latitude, productivity, and several environmental variables, influence contemporary patterns of the species richness in North American turtles. In particular, we test several hypotheses explaining broad-scale species richness patterns on several species richness data sets: ( i ) total turtles, ( ii ) freshwater turtles only, ( iii ) aquatic turtles, ( iv ) terrestrial turtles only, ( v ) Emydidae, and ( vi ) Kinosternidae. In addition to spatial data, we used a combination of 25 abiotic variables in spatial regression models to predict species richness patterns. Our results provide support for multiple hypotheses related to broad-scale patterns of species richness, and in particular, hypotheses related to climate, productivity, water availability, topography, and latitude. In general, species richness patterns were positively associated with temperature, precipitation, diversity of streams, coefficient of variation of elevation, and net primary productivity. We also found that North America turtles follow the general latitudinal diversity gradient pattern (i.e., increasing species richness towards equator) by exhibiting a negative association with latitude. Because of the incongruent results among our six data sets, our study highlights the importance of considering phylogenetic constraints and guilds when interpreting species richness patterns, especially for taxonomic groups that occupy a myriad of habitats.

Canadian Journal of Zoology↗

USGS2011

The influence of irrigation water on the hydrology and lake water budgets of two small arid-climate lakes in Khorezm, Uzbekistan

Little is known regarding the origins and hydrology of hundreds of small lakes located in the western Uzbekistan province of Khorezm, Central Asia. Situated in the Aral Sea Basin, Khorezm is a productive agricultural region, growing mainly cotton, wheat, and rice. Irrigation is provided by an extensive canal network that conveys water from the Amu Darya River (AD) throughout the province. The region receives on average 10 cm/year of precipitation, yet potential evapotranspiration exceeds this amount by about 15 times. It was hypothesized that the perennial existence of the lakes of interest depends on periodic input of excess irrigation water. This hypothesis was investigated by studying two small lakes in the region, Tuyrek and Khodjababa. In June and July 2008, surface water and shallow groundwater samples were collected at these lake systems and surrounding communities and analyzed for δ 2 H, δ 18 O, and major ion hydrochemistry to determine water sources. Water table and lake surface elevations were monitored, and the local aquifer characteristics were determined through aquifer tests. These data and climate data from a Class A evaporation pan and meteorological stations were used to estimate water budgets for both lakes. Lake evaporation was found to be about 0.7 cm/day during the study period. Results confirm that the waters sampled at both lake systems and throughout central Khorezm were evaporated from AD water to varying degrees. Together, the water budgets and stable isotope and major ion hydrochemistry data suggest that without surface water input from some source (i.e. excess irrigation water), these and other Khorezm lakes with similar hydrology may decrease in volume dramatically, potentially to the point of complete desiccation.

Khorezm↗

USGS2020

The GFDL Earth System Model Version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation characteristics

We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon-chemistry-climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous-generation coupled ESM2-carbon and CM3-chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land-atmosphere-ocean cycling of CO 2 , dust and iron, and interactive ocean-atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO 2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.

Journal of Advances in Modeling Earth Systems (JAM↗

USGS2013

Generalized additive regression models of discharge and mean velocity associated with direct-runoff conditions in Texas: Utility of the U.S. Geological Survey discharge measurement database

A database containing more than 17,700 discharge values and ancillary hydraulic properties was assembled from summaries of discharge measurement records for 424 U.S. Geological Survey streamflow-gauging stations (stream gauges) in Texas. Each discharge exceeds the 90th-percentile daily mean streamflow as determined by period-of-record, stream-gauge-specific, flow-duration curves. Each discharge therefore is assumed to represent discharge measurement made during direct-runoff conditions. The hydraulic properties of each discharge measurement included concomitant cross-sectional flow area, water-surface top width, and reported mean velocity. Systematic and statewide investigation of these data in pursuit of regional models for the estimation of discharge and mean velocity has not been previously attempted. Generalized additive regression modeling is used to develop readily implemented procedures by end-users for estimation of discharge and mean velocity from select predictor variables at ungauged stream locations. The discharge model uses predictor variables of cross-sectional flow area, top width, stream location, mean annual precipitation, and a generalized terrain and climate index (OmegaEM) derived for a previous flood-frequency regionalization study. The mean velocity model uses predictor variables of discharge, top width, stream location, mean annual precipitation, and OmegaEM. The discharge model has an adjusted R-squared value of about 0.95 and a residual standard error (RSE) of about 0.22 base-10 logarithm (cubic meters per second); the mean velocity model has an adjusted R-squared value of about 0.67 and an RSE of about 0.063 fifth root (meters per second). Example applications and computations using both regression models are provided. - See more at: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000635#sthash.jhGyPxgZ.dpuf

Journal of Hydrologic Engineering↗

USGS2011

Response of spectral vegetation indices to soil moisture in grasslands and shrublands

The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture.

International Journal of Remote Sensing↗

USGS2025

Post-fire recovery of sagebrush-steppe communities is better explained by elevation than climate-derived indicators of resistance and resilience

More landscapes require restoration than can feasibly be treated, and so decision-support tools to prioritize areas for treatment are needed. Moreover, restoration is complicated by the threat of biological invasion in disturbed areas, and so indicators of ecosystem resistance to invasion and resilience to disturbance (hereafter R&R) are important candidate criteria for prioritizing sites for restoration. We asked how climate-based R&R indicators that differed in being either categorical or continuous compared in their ability to explain plant-community recovery after six wildfires that collectively encompassed >750,000 ha and 7803 plot-year observations in sagebrush steppe of the western USA. Unique associations of species that most frequently co-occurred were identified using structural topic modelling. Mixed effect random forests were used to identify the relative importance of various R&R indicators in explaining post-fire plant associations compared with weather, landscape characteristics and treatment history. Simple metrics (elevation, latitude, longitude and year of monitoring) were more informative predictors of post-fire recovery than climate-based R&R indicators. However, small differences in the abundances of perennial grass and especially annual grass associations were predicted by the spring modified Thornthwaite Moisture Index (difference between precipitation and potential evapotranspiration). Synthesis and applications : The convenience of categorical resistance and resilience indicators has led to their widespread adoption for large-scale planning of restoration. Our results reveal that none of the resistance and resilience indicators assessed effectively explained post-fire restoration better than elevation, although a simple continuous resistance and resilience indicator describing water balance performed better than categorical indicators for explaining small but critical differences in cheatgrass association abundances.

California, Idaho, Nevada, Oregon↗

USGS2018

100-year lower Mississippi floods in a global climate model: Characteristics and future changes

Floods in the Mississippi basin can have large negative societal, natural, and economic impacts. Understanding the drivers of floods, now and in the future, is relevant for risk management and infrastructure-planning purposes. We investigate the drivers of 100-yr-return lower Mississippi River floods using a global coupled climate model with an integrated surface water module. The model provides 3400 years of physically consistent data from a static climate, in contrast to available observational data (relatively short records, incomplete land surface data, transient climate). In the months preceding the model’s 100-yr floods, as indicated by extreme monthly discharge, above-average rain and snowfall lead to moist subsurface conditions and the buildup of snowpack, making the river system prone to these major flooding events. The meltwater from snowpack in the northern Missouri and upper Mississippi catchments primes the river system, sensitizing it to subsequent above-average precipitation in the Ohio and Tennessee catchments. An ensemble of transient forcing experiments is used to investigate the impacts of past and projected anthropogenic climate change on extreme floods. There is no statistically significant projected trend in the occurrence of 100-yr floods in the model ensemble, despite significant increases in extreme precipitation, significant decreases in extreme snowmelt, and significant decreases in less extreme floods. The results emphasize the importance of considering the fully coupled land–atmosphere system for extreme floods. This initial analysis provides avenues for further investigation, including comparison to characteristics of less extreme floods, the sensitivity to model configuration, the role of human water management, and implications for future flood-risk management.

Journal of Hydrometeorology↗

USGS2008

A 1500-year holocene caribbean climate archive from the Blue Hole, lighthouse reef, belize

Sediment cores (up to 6 m in length) from the bottom of the Blue Hole, a 125 m deep Pleistocene sinkhole located in the lagoon of Lighthouse Reef Atoll, Belize, consist of undisturbed, annually layered biogenic carbonate muds and silts with intercalated coarser grained storm beds. The sedimentation rate of the layered sections is 2.5 mm/y on average, and the long cores span the past 1500 years. Oxygen isotopes of laminated sediment provide a late Holocene climate proxy: A high-resolution ??18O time series traces the final Migration Period Pessimum, the Medieval Warm Period, the Little Ice Age, and the subsequent temperature rise. Carbon isotopes (??13C) decrease up core and show the impacts of the decline of the Mayan culture and the Suess effect. Time series analyses of ??18O and ??13C content reveal 88-, 60-, 52-, and 32-year cyclicities, and suggest solar forcing. Storm event beds are most common during AD 650-850, around AD 1000, during AD 1200-1300, and AD 1450-1550. Major storm beds are rare during the past 500 years BP.

Journal of Coastal Research↗

USGS2025

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California↗

USGS2011

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

Journal of Flood Risk Management↗

USGS2015

Influence of ecological factors on prevalence of meningeal worm ( Parelaphostrongylus tenuis infection in South Dakota, USA

The meningeal worm ( Parelaphostrongylus tenuis ) is a nematode parasite that commonly infects white-tailed deer ( Odocoileus virginianus ; WTD) throughout the deciduous forest biome and deciduous-coniferous ecotone of eastern and central North America; the species is not known to occur west of the grassland biome of central North America. We used county-specific prevalence data to evaluate potential effects of landscape and climatologic factors on the spatial distribution of meningeal worm infection in South Dakota, US. Probability of infection increased 4-fold between eastern and western South Dakota and 1.3-fold for each 1-cm increase in summer precipitation. Sixty-three percent of WTD had only a single worm in the cranium. Expansion of meningeal worm infection across western South Dakota may be inherently low due to the combined effects of arid climate and potential attributes of the Missouri River that limit regional movements by infected WTD. Use of landscape genetic analyses to identify potential relationships between landscape features and population genetic structure of infected deer and parasites may contribute to a greater understanding of regional heterogeneity in meningeal worm infection rates across South Dakota, particularly in counties adjacent to the Missouri River. Future research evaluating heterogeneity in prevalence and intensity of infection between fawn and yearling deer, and the potential role of yearling male deer as dispersal agents of meningeal worms across the Missouri River, also is warranted.

South Dakota↗

USGS2019

Freezing resistance, safety margins, and survival vary among big sagebrush populations across the western United States

Premise Physiological responses to temperature extremes are considered strong drivers of species’ demographic responses to climate variability. Plants are typically classified as either avoiders or tolerators in their freezing‐resistance mechanism, but a gradient of physiological‐threshold freezing responses may exist among individuals of a species. Moreover, adaptive significance of physiological freezing responses is poorly characterized, particularly under warming conditions that relax selection on cold hardiness. Methods Freezing responses were measured in winter and again for new foliage in spring for 14 populations of Artemisia tridentata collected throughout its range and planted in a warm common garden. The relationships of the freezing responses to survival were evaluated in the warm garden and in two colder gardens. Results Winter and spring freezing resistance were not correlated and appeared to be under differing selection regimes, as evident in correlations with different population climate of origin variables. All populations resisted considerably lower temperatures in winter than in spring, with populations from more continental climates showing narrower freezing safety margins (difference in temperatures at which ice‐nucleation occurs and 50% reduction in chlorophyll fluorescence occurs) in spring. Populations with greater winter freezing resistance had lower survivorship in the warmest garden, while populations with greater spring freezing resistance had lower survivorship in a colder garden. Conclusions These survivorship patterns relative to physiological thresholds suggest excess freezing resistance may incur a survival cost that likely relates to a trade‐off between carbon gain and freezing resistance during critical periods of moisture availability. This cost has implications for seed moved from cooler to warmer environments and for plants growing in warming environments.

American Journal of Botany↗

USGS2007

A simple daily soil-water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas

Quantifying the spatial and temporal distribution of natural groundwater recharge is usually a prerequisite for effective groundwater modeling and management. As flow models become increasingly utilized for management decisions, there is an increased need for simple, practical methods to delineate recharge zones and quantify recharge rates. Existing models for estimating recharge distributions are data intensive, require extensive parameterization, and take a significant investment of time in order to establish. The Wisconsin Geological and Natural History Survey (WGNHS) has developed a simple daily soil-water balance (SWB) model that uses readily available soil, land cover, topographic, and climatic data in conjunction with a geographic information system (GIS) to estimate the temporal and spatial distribution of groundwater recharge at the watershed scale for temperate humid areas. To demonstrate the methodology and the applicability and performance of the model, two case studies are presented: one for the forested Trout Lake watershed of north central Wisconsin, USA and the other for the urban-agricultural Pheasant Branch Creek watershed of south central Wisconsin, USA. Overall, the SWB model performs well and presents modelers and planners with a practical tool for providing recharge estimates for modeling and water resource planning purposes in humid areas. ?? Springer-Verlag 2007.

Hydrogeology Journal↗

USGS1993

The role of permafrost and seasonal frost in the hydrology of northern wetlands in North America

Wetlands are a common landscape feature in the Arctic, Subarctic, and north Temperate zones of North America. In all three-zones, the occurrnce of seasonal frost results in similar surface-water processes in the early spring. For example, surface ice and snow generally melt before the soil frost thaws, causing melt water to flow into depressions, over the land surface and at times, across low topographic divides. However, evapotranspiration and ground-water movement differ among the three climatic zones because they are more affected by permafrost than seasonal frost. The water source for plants in the Arctic is restricted to the small volume of subsurface water lying above the permafrost. Although this is also true in the Subarctic where permafrost exists, where it does not, plants may receive and possibly reflect, more regional ground-water sources. Where permafrost exists, the interaction of wetlands with subsurface water is largely restricted to shallow local flow systems. But where permafrost is absent in parts of the Subarctic and all of the Temperature zone, wetlands may have a complex interaction with ground-water-flow systems of all magnitudes.

Journal of Hydrology↗

USGS2012

Bats and wind energy: a literature synthesis and annotated bibliography

Turbines have been used to harness energy from wind for hundreds of years. However, with growing concerns about climate change, wind energy has only recently entered the mainstream of global electricity production. Since early on in the development of wind-energy production, concerns have arisen about the potential impacts of turbines to wildlife; these concerns have especially focused on the mortality of birds. Despite recent improvements to turbines that have resulted in reduced mortality of birds, there is clear evidence that bat mortality at wind turbines is of far greater conservation concern. Bats of certain species are dying by the thousands at turbines across North America, and the species consistently affected tend to be those that rely on trees as roosts and most migrate long distances. Turbine-related bat mortalities are now affecting nearly a quarter of all bat species occurring in the United States and Canada. Most documented bat mortality at wind-energy facilities has occurred in late summer and early fall and has involved tree bats, with hoary bats ( Lasiurus cinereus ) being the most prevalent among fatalities. This literature synthesis and annotated bibliography focuses on refereed journal publications and theses about bats and wind-energy development in North America (United States and Canada). Thirty-six publications and eight theses were found, and their key findings were summarized. These publications date from 1996 through 2011, with the bulk of publications appearing from 2007 to present, reflecting the relatively recent conservation concerns about bats and wind energy. The idea for this Open-File Report formed while organizing a joint U.S. Fish and Wildlife Service/U.S. Geological Survey "Bats and Wind Energy Workshop," on January 25-26, 2012. The purposes of the workshop were to develop a list of research priorities to support decision making concerning bats with respect to siting and operations of wind-energy facilities across the United States. This document was intended to provide background information for the workshop participants on what has been published on bats and wind-energy issues in North America (United States and Canada).

Open-File Report↗

USGS2013

Short-term variability of 7 Be atmospheric deposition and watershed response in a Pacific coastal stream, Monterey Bay, California, USA

Beryllium-7 is a powerful and commonly used tracer for environmental processes such as watershed sediment provenance, soil erosion, fluvial and nearshore sediment cycling, and atmospheric fallout. However, few studies have quantified temporal or spatial variability of 7 Be accumulation from atmospheric fallout, and parameters that would better define the uses and limitations of this geochemical tracer. We investigated the abundance and variability of 7 Be in atmospheric deposition in both rain events and dry periods, and in stream surface-water samples collected over a ten-month interval at sites near northern Monterey Bay (37°N, 122°W) on the central California coast, a region characterized by a rainy winters, dry summers, and small mountainous streams with flashy hydrology. The range of 7 Be activity in rainwater samples from the main sampling site was 1.3–4.4 Bq L −1 , with a mean (±standard deviation) of 2.2 ± 0.9 Bq L −1 , and a volume-weighted average of 2.0 Bq L −1 . The range of wet atmospheric deposition was 18–188 Bq m −2 per rain event, with a mean of 72 ± 53 Bq m −2 . Dry deposition fluxes of 7 Be ranged from less than 0.01 up to 0.45 Bq m −2 d −1 , with an estimated dry season deposition of 7 Bq m −2 month −1 . Annualized 7 Be atmospheric deposition was approximately 1900 Bq m −2 yr −1 , with most deposition via rainwater (>95%) and little via dry deposition. Overall, these activities and deposition fluxes are similar to values found in other coastal locations with comparable latitude and Mediterranean-type climate. Particulate 7 Be values in the surface water of the San Lorenzo River in Santa Cruz, California, ranged from <0.01 Bq g −1 to 0.6 Bq g −1 , with a median activity of 0.26 Bq g −1 . A large storm event in January 2010 characterized by prolonged flooding resulted in the entrainment of 7 Be-depleted sediment, presumably from substantial erosion in the watershed. There were too few particulate 7 Be data over the storm to accurately model a 7 Be load, but the results suggest enhanced watershed export of 7 Be from small, mountainous river systems compared to other watershed types.

California↗

USGS2014

Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors

Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change. Precipitation during and after the monsoon is likely to increase in both basins under the A1B and A2 emission scenarios; whereas, the pre-monsoon precipitation is likely to decrease. Peak monsoon precipitation is likely to shift from July to August, and may impact the livelihoods of large rural populations linked to subsistence agriculture in the basins. Uncertainty analysis of the downscaled precipitation indicated that the uncertainty in the downscaled precipitation was less than the uncertainty in the original CGCM3.1 precipitation; hence, the CGCM3.1 downscaled precipitation was a better input for the regional hydrological impact studies. However, downscaled precipitation from multiple GCMs is suggested for comprehensive impact studies.

Brahmaputra;Ganges↗

USGS2015

Multi-decadal trends in spring arrival of avian migrants to the central Arctic coast of Alaska: Effects of environmental and ecological factors

Warming in the Arctic has caused the transition from winter to summer to occur weeks earlier over the last half century, yet little is known about whether avian migrants have altered their timing of arrival on breeding areas to match this earlier seasonal transition. Over a 50-yr period, we examined trends in the timing of the first arrival for 16 avian migrant species at the terminus of their northward migration along the central Arctic coast of Alaska and compared these trends to factors potentially influencing migration phenology. Date of first arrival occurred an average of 0.12 d yr −1 or 6 d (range = 3–10 d) earlier across all species and did not differ significantly among species between 1964 and 2013. Local climatic variables, particularly temperature, had a greater effect on a species first arrival date than did large-scale climatic predictors. First arrival date was 1.03 d earlier for every 1°C annual change in temperature, but there was nearly a 2-fold difference in the range of responses across species (0.69–1.33 d °C −1 ), implying that some species did better than others at timing their arrival with changing temperature. There was weak support for an influence of foraging strategy, migration distance, and flight path on timing of first arrival. Our findings, like others from temperate latitudes, indicate that avian migrants are responsive to changing environmental conditions, though some species appear to be more adaptive than others.

Alaska↗