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At least 397 records · Page 22Linked to original sources
USGS2016

Seasonal electrical resistivity surveys of a coastal bluff, Barter Island, North Slope Alaska

Select coastal regions of the North Slope of Alaska are experiencing high erosion rates that can be attributed in part to recent warming trends and associated increased storm intensity and frequency. The upper sediment column of the coastal North Slope of Alaska can be described as continuous permafrost underlying a thin (typically less than 1–2 m) active layer that responds variably to seasonal thaw cycles. Assessing the temporal and spatial variability of the active layer and underlying permafrost is essential to better constrain how heightened erosion may impact material fluxes to the atmosphere and the coastal ocean, and how enhanced thaw cycles may impact the stability of the coastal bluffs. In this study, multi-channel electrical resistivity tomography (ERT) was used to image shallow subsurface features of a coastal bluff west of Kaktovik, on Barter Island, northeast Alaska. A comparison of a suite of paired resistivity surveys conducted in early and late summer 2014 provided detailed information on how the active layer and permafrost are impacted during the short Arctic summer. Such results are useful in the development of coastal resilience models that tie together fluvial, terrestrial, climatic, geologic, and oceanographic forcings on shoreline stability.

Alaska↗
USGS2015

Long-term shifts in the phenology of rare and endemic Rocky Mountain plants

PREMISE OF THE STUDY: Mountainous regions support high plant productivity, diversity, and endemism, yet are highly vulnerable to climate change. Historical records and model predictions show increasing temperatures across high elevation regions including the Southern Rocky Mountains, which can have a strong influence on the performance and distribution of montane plant species. Rare plant species can be particularly vulnerable to climate change because of their limited abundance and distribution. METHODS: We tracked the phenology of rare and endemic species, which are identified as imperiled, across three different habitat types with herbarium records to determine if flowering time has changed over the last century, and if phenological change was related to shifts in climate. KEY RESULTS: We found that the flowering date of rare species has accelerated 3.1 d every decade (42 d total) since the late 1800s, with plants in sagebrush interbasins showing the strongest accelerations in phenology. High winter temperatures were associated with the acceleration of phenology in low elevation sagebrush and barren river habitats, whereas high spring temperatures explained accelerated phenology in the high elevation alpine habitat. In contrast, high spring temperatures delayed the phenology of plant species in the two low-elevation habitats and precipitation had mixed effects depending on the season. CONCLUSIONS: These results provide evidence for large shifts in the phenology of rare Rocky Mountain plants related to climate, which can have strong effects on plant fitness, the abundance of associated wildlife, and the future of plant conservation in mountainous regions.

American Journal of Botany↗
USGS2007

Relations between winter precipitation and atmospheric circulation simulated by the Geophysical Fluid Dynamics Laboratory general circulation model

General circulation model (GCM) simulations of atmospheric circulation are more reliable than GCM simulations of temperature and precipitation. In this study, temporal correlations between 700 hPa height anomalies simulated winter precipitation at eight locations in the conterminous United States are compared with corresponding correlations in observations. The objectives are to 1) characterize the relations between atmospheric circulation and winter precipitation simulated by the GFDL, GCM for selected locations in the conterminous USA, ii) determine whether these relations are similar to those found in observations of the actual climate system, and iii) determine if GFDL-simulated precipitation is forced by the same circulation patterns as in the real atmosphere. -from Authors

International Journal of Climatology↗
USGS2020

Effects of a temperature rise on melatonin and thyroid hormones during smoltification of Atlantic salmon, Salmo salar

Smoltification prepares juvenile Atlantic salmon ( Salmo salar ) for downstream migration. Dramatic changes characterize this crucial event in the salmon’s life cycle, including increased gill Na + /K + -ATPase activity (NKA) and plasma hormone levels. The triggering of smoltification relies on photoperiod and is modulated by temperature. Both provide reliable information, to which fish have adapted for thousands of years, that allows deciphering daily and calendar time. Here we studied the impact of different photoperiod (natural, sustained winter solstice) and temperature (natural, ~ + 4° C) combinations, on gill NKA, plasma free triiodothyronine (T3) and thyroxine (T4), and melatonin (MEL; the time-keeping hormone), throughout smoltification. We also studied the impact of temperature history on pineal gland MEL production in vitro. The spring increase in gill NKA was less pronounced in smolts kept under sustained winter photoperiod and/or elevated temperature. Plasma thyroid hormone levels displayed day–night variations, which were affected by elevated temperature, either independently from photoperiod (decrease in T3 levels) or under natural photoperiod exclusively (increase in T4 nocturnal levels). Nocturnal MEL secretion was potentiated by the elevated temperature, which also altered the MEL profile under sustained winter photoperiod. Temperature also affected pineal MEL production in vitro, a response that depended on previous environmental acclimation of the organ. The results support the view that the salmon pineal is a photoperiod and temperature sensor, highlight the complexity of the interaction of these environmental factors on the endocrine system of S. salar , and indicate that climate change might compromise salmon’s time “deciphering” during smoltification, downstream migration and seawater residence.

Journal of Comparative Physiology B: Biochemical, ↗
USGS2000

Suspended-sediment and fresh-water discharges in the Ob and Yenisey rivers, 1960-1988

Of the world's great rivers, the Ob and Yenisey rank among the largest suppliers of fresh water and among the smallest suppliers of suspended sediment to the coastal ocean. Sediment in the middle reaches of the rivers is mobilized from bordering terraces and exchanged between channels and flood plains. Sediment in the lower reaches of these great rivers is deposited and stored (permanently, on a millennial time scale) in flood plains. Sediment discharges, already small under natural conditions, are diminished further by large manmade reservoirs that trap significant proportions of the moving solids. The long winter freeze and sudden spring breakup impose a peakedness in seasonal water runoff and sediment discharge that contrasts markedly with that in rivers of the tropics and more temperate climates. Very little sediment from the Ob and Yenisey rivers is being transported to the open waters of the Arctic Ocean under present conditions.

Arctic Ocean, Gulf of Ob, Irtysh River, Ob River, ↗
USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗
USGS2026

Deep learning error post-processing improves stochastic watershed modeling

Hydrologic extremes, including floods and droughts, pose substantial societal risks that are expected to intensify with climate change. Deterministic watershed models (DWMs) remain a mainstay for modeling these extremes, but lack explicit representation of uncertainty, limiting their utility for risk-informed planning. Stochastic watershed models (SWMs) address this limitation by generating ensembles of streamflow via models of observed DWM residuals. However, most SWMs struggle with the complex dependence between DWM residuals and the underlying hydrologic state, which can complicate stochastic simulations under nonstationary climates. Deep learning (DL) models, whether used as standalone models or post-processors for process-based DWMs, offer a pathway to address this challenge by reducing conditional dependence. In this study, we evaluate SWMs applied to seven models: three process-based models (PRMS, Hymod, and HBV), their hybrid process-DL counterparts, and a pure DL DWM, focusing on daily simulations and extremes under both historical conditions and synthetic climate change scenarios. Results for a case study watershed in Massachusetts show that SWMs applied to hybrid or pure DL DWMs consistently outperform those applied to process-based DWMs. However, an SWM applied to the pure DL model exhibits weaknesses at low flows for this study basin, underscoring the value of hybrid approaches. Extending the analysis across 73 additional basins demonstrates that these improvements are robust and generalizable statewide. This work highlights the potential of a DL-enhanced stochastic watershed modeling framework to advance hydrologic risk prediction under changing climate conditions, offering a scalable methodology for integrating uncertainty into watershed modeling for long-term planning.

Journal of Hydrology↗
USGS1997

Sedimentary history and mass flow structures of Chryse and Acidalia Planitiae, Mars

Geologic mapping and crater counting in Chryse and Acidalia Planitiae (GAP) reveal five major sedimentary deposits of Hesperian to Early Amazonian age, including (1) a mass flow deposited during the Early Hesperian near Deuteronilus Mensae (northeast of the map region) that may have resulted from the carving of Kasei Valles, >3000 km southwest of the exposed part of the deposit; (2) knobby plains material consisting of channel (likely; from Simud and Tiu Valles and possibly Ares and Shalbatana Valles) and mass-wasting deposits in central and eastern CAP; (3) material largely from Maja and Ares Valles emplaced in at least western and southern CAP (outcrops in southern Chryse Planitia developed thermokarst); (4) a thin mass flow covering much of southern Chryse Planitia that emanated from Simud and Tiu Valles; and (5) a thick, extensive (perhaps >3500 km across) mass flow deposit in central and northern CAP derived from accumulation and backflow of the preceding thin mass flow or perhaps melting of polar deposits. Other possible deposits may not be recognizable owing to burial by younger materials or a lack of morphologic signature. Various associated landforms appear to be consistent with the mass flow interpretations, including lobate and linear scarps along deposit edges, fractures related to desiccation of thick sediments, troughs, and ridges near the edges of the deposit indicative of secondary mass movement and deformation, pitted domes and fissure-fed flows possibly formed by sedimentary (mud) eruptions, and longitudinal channel grooves perhaps formed by roller vortices. No convincing evidence for paleoshorelines or stagnant ice sheets is found in CAP. These findings suggest that mass flow and hyperconcentrated flooding may have been the predominant processes of outflow-channel dissection in CAP. Elsewhere in the northern plains, similar landforms are prevalent. The mass flow interpretation does not require either multiple episodes of extraordinarily high water-discharge rates achieved by freeing huge volumes of water from the crust, repetitive recycling of immense volumes of water into highland aquifers at the heads of Chryse channels, or profound climate change. Mars Pathfinder will most likely land on and inspect the surface of the thin mass flow that originated from the canyons of Simud and Tiu Valles.

Journal of Geophysical Research E: Planets↗
USGS2009

Snow and ice in a changing hydrological world

On the occasion of the 60th anniversary of the International Association of Hydrological Sciences, the 100th and 50th anniversaries of the First and Second International Polar Years, and the 25th anniversary of the International Geophysical Year, it seems appropriate to re-examine the world's water balance and the role of snow and ice in the global hydrological climatic system. Snow cover on land (especially in the Northern Hemisphere) and sea ice (especially in the Southern Hemisphere) vary seasonally, and this seasonal change has an important effect on the world climate because snow and sea ice reflect solar radiation efficiently and affect other heat flow processes between atmosphere and land or ocean. Glaciers, including ice sheets, store most of the fresh water on Earth, but change dimensions relatively slowly. There is no clear evidence that the glacier ice volume currently is declining, but more needs to be known about mountain glacier and ice sheet mass balances. The current rise in sea level poses an enigma: thermal expansion of the oceans may account for half of the present rise, but the other half is unexplained. Although major changes in the large ice sheets take place over time scales of 10 4 to 10 5 years, marine ice sheets may be subject to rapid disintegration due to grounding line instability, perhaps accompanied by surging. Ice cores may produce remarkably complete histories of air temperature, precipitation, fallout, and atmospheric composition. A recent core through the Greenland Ice Sheet shows an abrupt transition from glacial to modern climate just over 10000 years ago, suggesting that climate is an “almost intransitive” system. Because of the possibility of abrupt climate transitions and the uncertain stability of the West Antarctic Ice Sheet, future climatic variations are difficult to predict. The calculated heating of the atmosphere in the polar regions due to CO 2 increase is, therefore, of special interest.

Hydrological Sciences Journal↗
USGS2020

Possible effects of climate change on ixodid ticks and the pathogens they transmit: Predictions and observations

The global climate has been changing over the last century due to greenhouse gas emissions and will continue to change over this century, accelerating without effective global efforts to reduce emissions. Ticks and tick-borne diseases (TTBDs) are inherently climate-sensitive due to the sensitivity of tick lifecycles to climate. Key direct climate and weather sensitivities include survival of individual ticks, and the duration of development and host-seeking activity of ticks. These sensitivities mean that in some regions a warming climate may increase tick survival, shorten life-cycles and lengthen the duration of tick activity seasons. Indirect effects of climate change on host communities may, with changes in tick abundance, facilitate enhanced transmission of tick-borne pathogens. High temperatures, and extreme weather events (heat, cold, and flooding) are anticipated with climate change, and these may reduce tick survival and pathogen transmission in some locations. Studies of the possible effects of climate change on TTBDs to date generally project poleward range expansion of geographical ranges (with possible contraction of ranges away from the increasingly hot tropics), upslope elevational range spread in mountainous regions, and increased abundance of ticks in many current endemic regions. However, relatively few studies, using long-term (multi-decade) observations, provide evidence of recent range changes of tick populations that could be attributed to recent climate change. Further integrated ‘One Health’ observational and modeling studies are needed to detect changes in TTBD occurrence, attribute them to climate change, and to develop predictive models of public- and animal-health needs to plan for TTBD emergence.

Journal of Medical Entomology↗
USGS2017

Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission. Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [ Cervus Canadensis ] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem. Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts. Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands. Synthesis and applications . Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.

Journal of Applied Ecology↗
USGS2019

Hydroclimatology of the Mississippi River Basin

Model estimated monthly water balance (WB) components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff [ R ]) for 848 United States (U.S.) Geological Survey 8-digit hydrologic units located in the Mississippi River Basin (MRB) are used to examine the temporal and spatial variability of the MRB WB for water years 1901 through 2014. Results indicate the MRB can be divided into nine subregions with similar temporal variability in R . The WB analyses indicated ~79% of total water-year MRB runoff is generated by four of the nine subregions and most of the R in the basin is derived from surplus ( S ) water during the months of December through May. Furthermore, the analyses showed temporal variability in S is largely controlled by the occurrence of negative atmospheric pressure anomalies over the western U.S. and positive atmospheric pressure anomalies over the eastern U.S. coast. This combination of atmospheric pressure anomalies results in an anomalous flow of moist air from the Gulf of Mexico into the MRB. In the context of paleo-climate reconstructions of the Palmer Drought Severity Index, since about 1900 the MRB has experienced wetter conditions than were experienced during the previous 500 years.

Mississippi River Basin↗
USGS2013

Air - water temperature relationships in the trout streams of southeastern Minnesota’s carbonate - sandstone landscape

Carbonate-sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface-water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater-fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air-water temperature relationships for 40 GWFS in southeastern Minnesota. A 40-stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R 2 of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface-water dominated streams. Regression models for streams with high R 2 values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater-fed systems, but will do so at a slower rate than surface-water dominated systems. A regression model of intercept vs . slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs . management strategies to protect trout streams.

Minnesota↗
USGS2018

Effects of land use on summer thermal regimes in critical salmonid habitats of the Pacific Northwest

The effect of climate change on stream temperature regimes is of significant concern to natural resource managers focused on protecting cold-water-dependent species. Nevertheless, understanding of how human land-use activities may act to exacerbate the effects of climate change on stream temperature regimes is limited. Using extensive stream temperature data with high-resolution climate and habitat data, we quantified how land management activities are related to summer stream temperatures across the Pacific Northwest, USA. We then described the distribution of land management practices influencing summer thermal regimes relative to the distribution of salmonid fish species of conservation concern. After accounting for climatic and geophysical variation, we detected a strong relationship between livestock grazing and summer thermal regimes. Maximum, average, and diel variation in water temperature was greater where livestock grazing was present. Livestock grazing was widespread, occurring in 43%–100% of sites supporting salmonid species of conservation concern. Thus, current land management practices may be intensifying the effects of ongoing climate change in freshwater habitats, acting to further threaten cold-water fishes of conservation concern.

Washington, Oregon, Idaho, Montana↗
USGS2017

Characterizing sources of uncertainty from global climate models and downscaling techniques

In recent years climate model experiments have been increasingly oriented towards providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here we present a method, based on a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. We apply the method to the Southeast U.S. using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios are typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast U.S. for precipitation and ~30% for extreme heat days (> 35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a sub-sample of all models are available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. We conclude with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.

Journal of Applied Meteorology and Climatology↗
USGS2015

Deep-sea ostracods from the South Atlantic sector of the Southern ocean during the Last 370,000 years

We report changes of deep-sea ostracod fauna during the last 370,000 yr from the Ocean Drilling Program (ODP) Hole 704A in the South Atlantic sector of the Southern Ocean. The results show that faunal changes are coincident with glacial/interglacial-scale deep-water circulation changes, even though our dataset is relatively small and the waters are barren of ostracods until mid-MIS (Marine Isotope Stage) 5. Krithe and Poseidonamicus were dominant during the Holocene interglacial period and the latter part of MIS 5, when this site was under the influence of North Atlantic Deep Water (NADW). Conversely, Henryhowella and Legitimocythere were dominant during glacial periods, when this site was in the path of Circumpolar Deep Water (CPDW). Three new species (Aversovalva brandaoae, Poseidonamicus hisayoae, and Krithe mazziniae) are described herein. This is the first report of Quaternary glacial/interglacial scale deep-sea ostracod faunal changes in the Southern and South Atlantic Oceans, a key region for understanding Quaternary climate and deep-water circulation, although the paucity of Quaternary ostracods in this region necessitates further research. ?? 2009 The Paleontological Society.

Journal of Paleontology↗
USGS2010

Temperature mediated moose survival in Northeastern Minnesota

The earth is in the midst of a pronounced warming trend and temperatures in Minnesota, USA, as elsewhere, are projected to increase. Northern Minnesota represents the southern edge to the circumpolar distribution of moose (Alces alces), a species intolerant of heat. Moose increase their metabolic rate to regulate their core body temperature as temperatures rise. We hypothesized that moose survival rates would be a function of the frequency and magnitude that ambient temperatures exceeded the upper critical temperature of moose. We compared annual and seasonal moose survival in northeastern Minnesota between 2002 and 2008 with a temperature metric. We found that models based on January temperatures above the critical threshold were inversely correlated with subsequent survival and explained >78 of variability in spring, fall, and annual survival. Models based on late-spring temperatures also explained a high proportion of survival during the subsequent fall. A model based on warm-season temperatures was important in explaining survival during the subsequent winter. Our analyses suggest that temperatures may have a cumulative influence on survival. We expect that continuation or acceleration of current climate trends will result in decreased survival, a decrease in moose density, and ultimately, a retreat of moose northward from their current distribution.

Journal of Wildlife Management↗
USGS1977

Tertiary and Quaternary deposits at The Palisades, central Alaska

The Palisades of the Yukon River, located near the geographic center of Alaska, has long been an attraction to people traveling along the river. Numerous scientific field parties have viewed or visited the locality and published short accounts of their observations. The river bluffs are as much as 90 meters high and are composed of Tertiary lignite-rich sedimentary rocks and frozen Quaternary sand, silt, and gravel. Resampling and analysis of pollen show that the Tertiary rocks are Miocene rather than Miocene and Pliocene as previously thought. The Miocene flora, possessing a number of conifer and hardwood-tree types, was more varied than the present vegetation and indicates a warmer and wetter climate than at present. The area is frequently referred to as the boneyard because of the common occurrence of large bones of Pleistocene mammals within the frozen silts.

Alaska↗