Geology ReportsSearch

SEARCH · Geology Reports

Results for “Space Weather”

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

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

At least 91 records · Page 5Linked to original sources

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security, and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using boosted regression tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

California, Delaware, Maryland, New Jersey, North

Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

Authorea

Relation between earthquakes, weather, and soil tilt

Two years of local earthquake, temperature, and rainfall data taken near a tiltmeter site were used in a study of the numerical relation between these phenomena and the recorded tilt response. A least-squares shaping and predictive error filter approach was used. The relations were ranked in part according to the root mean square (r.m.s.) error of fit across the entire sample space. The tilt data with an annual range of tilt of approximately 10 microradians were fitted to the combined weather data of temperature and rainfall with a 0.75-microradian r.m.s. error. The best fit of earthquakes to these same tilt data is the subclass of events with magnitude (M) > 2.5 within 30 kilometers of the tilt site. The filter that mapped earthquakes to tilt yielded a 1.03-microradian r.m.s. error. The most unusual tilt anomaly over the entire 2-year period has the best fit of rainfall to the data for any single month of the entire data set. This unusual anomaly was the basis of an erroneously predicted earthquake (M ∼ 5). These data indicate that if there are premonitory earthquake signals, they are buried in local meteorlogical noise. Separating an earthquake anomaly from the response to surface phenomena becomes more difficult as the earthquake anomaly lead time approaches the rise time of the soil to weather and seasonal variations.

Science

Can we advance individual-level heat-health research through the application of stochastic weather generators?

Individuals living in every region of the world are increasingly vulnerable to negative health outcomes due to extreme heat exposure. Children, in particular, may face long-term consequences associated with heat stress that affect their educational attainment and later life health and well-being. Retrospective individual-level analyses are useful for determining the effects of extreme heat exposure on health outcomes. Typically, future risk is inferred by extrapolating these effects using future warming scenarios that are applied uniformly over space and time without consideration of topographical or climatological gradients. We propose an alternative approach using a stochastic weather generator. This approach employs a 1 °C warming scenario to produce an ensemble of plausible future weather scenarios, and subsequently a distribution of future health risks. We focus on the effect of global warming on fetal development as measured by birth weight in Ethiopia. We demonstrate that predicted changes in birth weight are sensitive to the evolution of temperatures not quantified in a uniform warming scenario. Distributions of predicted changes in birth weight vary in magnitude and variability depending on geographic and socioeconomic region. We present these distributions alongside results from the uniform warming scenario and discuss the spatiotemporal variability of these predicted changes.

Climatic Change

Grand challenges in understanding the interplay of climate and land changes

Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

Earth Interactions

Rapid and gradual permafrost thaw: A tale of two sites

Warming temperatures and increasing disturbance by wildfire and extreme weather events is driving permafrost change across northern latitudes. The state of permafrost varies widely in space and time, depending on landscape, climate, hydrologic, and ecological factors. Despite its importance, few approaches commonly measure and monitor the changes in deep (>1 m) permafrost conditions with high spatial resolution. Here, we use electrical resistivity tomography surveys along two transects in interior Alaska previously disturbed by wildfire and more recently by warming temperatures and extreme precipitation. Long-term point observations of permafrost depth, temperature, and water content inform geophysical measurements which, in turn, are used to extrapolate interpretations over larger areas and with high spatial fidelity. We contrast gradual loss of recently formed permafrost driven by warmer temperatures and increased snowfall, with rapid permafrost loss driven by changes in air temperature, snow depth, and extreme summer precipitation in 2014.

Alaska

Habitat use as indicator of adaptive capacity to climate change

Aim Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose ( Alces alces ), a charismatic species of conservation and public interest. Location The northeastern United States, along the trailing edge of the moose geographic range in North America. Methods We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use. Results We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times. Main conclusionsOur results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation.

New York, Vermont, New Hampshire, Massachusetts

Development of projected depth-duration-frequency curves for precipitation in Florida, 2020–59 and 2050–89

The planning, permitting, and design of stormwater-management projects require estimates of the depths of extreme precipitation for current and future events with specified durations and return periods. In this project, precipitation data from six downscaled climate datasets were used to determine changes in precipitation depth-duration-frequency curves from the period 1966–2005 to the periods 2020–59 and 2050–89. The downscaled climate datasets are from the Coupled Model Intercomparison Project Phases 5 and 6 and include (1) Coordinated Regional Downscaling Experiment (CORDEX), (2) Localized Constructed Analogs (LOCA), (3) Multivariate Adaptive Constructed Analogs (MACA), (4) Jupiter Intelligence Weather Research and Forecasting model (JupiterWRF), (5) LOCA version 2 (LOCA2), and (6) National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). Change factors—multiplicative changes in expected extreme precipitation magnitude from a historical to future period—were computed for grid cells containing National Oceanic and Atmospheric Administration Atlas 14 stations in Florida. Change factors for specific durations and return periods were developed to scale the National Oceanic and Atmospheric Administration Atlas 14 historical depth-duration-frequency values to the periods 2020–59 and 2050–89 on the basis of changes in extreme precipitation derived from six downscaled climate datasets. Overall, a large variation in change factors across downscaled climate datasets was found, with change factors generally being greater than 1 and increasing with return period. In general, median change factors were found to range within 1.01–1.58 for 2020–59 and 1.01–1.63 for 2050–89, depending on the downscaled climate dataset, region, duration, and return period, indicating a projected overall increase in future extreme-precipitation events. When data from all datasets are considered together, median change factors range within 1.04–1.18 for the period 2020–59 and within 1.04–1.23 for the period 2050–89, depending on the region, duration, and return period. Spatial patterns in median change factors were found to vary by dataset.

Florida

Toward a US framework for continuity of satellite observations of Earth's climate and for supporting societal resilience

There is growing urgency for improved public and commercial services to support a resilient, secure, and thriving United States (US) in the face of mounting decision-support needs for environmental stewardship and hazard response, as well as for climate change adaptation and mitigation. Sustained space-based Earth observations are critical infrastructure to support the delivery of science and decision-support information with local, national, and global utility. This is reflected in part through the United States' sustained support of a suite of weather and land-imaging satellites. However, outside of these two areas, the US lacks an overarching, systematic plan or framework to identify, prioritize, fund, and implement sustained space-based Earth observations to meet the Nation's full range of needs for science, government policy, and societal support. To aid and accelerate the discussion on our nation's needs, challenges and opportunities associated with sustained critical space-based Earth observations, the Keck Institute for Space Studies (KISS) sponsored a multi-week think-tank study to offer ways forward. Based on this study, the KISS study team suggests the establishment of a robust coordination framework to help address US needs for sustained Earth observations. This coordination framework could account for: (a) approaches to identify and prioritize satellite observations needed to meet US needs for science and services, (b) the rapidly evolving landscape of space-based Earth viewing architecture options and technology improvements with increasing opportunities and lower cost access to space, and (c) the technical and programmatic underpinnings required for proper and comprehensive data stewardship to support a wide range of research and public services.

Earth's Future

The CEOS-Land Surface Imaging Constellation Portal for GEOSS: A resource for land surface imaging system information and data access

The Committee on Earth Observation Satellites is an international group that coordinates civil space-borne observations of the Earth, and provides the space component of the Global Earth Observing System of Systems (GEOSS). The CEOS Virtual Constellations concept was implemented in an effort to engage and coordinate disparate Earth observing programs of CEOS member agencies and ultimately facilitate their contribution in supplying the space-based observations required to satisfy the requirements of the GEOSS. The CEOS initially established Study Teams for four prototype constellations that included precipitation, land surface imaging, ocean surface topography, and atmospheric composition. The basic mission of the Land Surface Imaging (LSI) Constellation [1] is to promote the efficient, effective, and comprehensive collection, distribution, and application of space-acquired image data of the global land surface, especially to meet societal needs of the global population, such as those addressed by the nine Group on Earth Observations (GEO) Societal Benefit Areas (SBAs) of agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and weather. The LSI Constellation Portal is the result of an effort to address important goals within the LSI Constellation mission and provide resources to assist in planning for future space missions that might further contribute to meeting those goals.

earthzine, an IEEE online publication

Characterizing changes in postfire debris-flow hazard as burned areas recover

Emergency assessments of postfire debris-flow hazards that are performed by the U.S. Geological Survey (USGS) provide estimates of debris-flow likelihood and rainfall triggering conditions that are used for evaluating and managing runoff-generated debris-flow hazards in recently burned areas throughout the western United States. Although the immediate postfire period, within roughly one year after fire, is typically the most susceptible to runoff-generated debris flows, the hazard evolves in time and space as the burned area recovers. The recovery trajectory a given burned area will take depends on local climate and weather and can be difficult to predict. Some burned areas recover quickly, whereas others experience debris flows for multiple years after fire. As a result, extending our ability to update debris-flow likelihood estimates and rainfall thresholds based on observed recovery of the burned area would be beneficial. We present a method for multi-year runoff-generated debris-flow hazard assessment that leverages the USGS “M1” debris-flow likelihood model and integrates updated, satellite-derived, normalized burn ratio data to estimate vegetation recovery. We predict recovery-aware rainfall thresholds and validate them against a multi-year debris-flow hazard prediction and could be adapted for use with other debris-flow models that incorporate burn severity data.

Arizona, California, Colorado, New Mexico, Washing

Flood tracking chart for the Illinois River basin

This Flood Tracking Chart for the Illinois River Basin in Illinois can be used to record and compare the predicted or current flood-crest stage to past flood-crest information. This information can then be used by residents and emergency-response personnel to make informed decisions concerning the threat of flooding to life and property. The chart shows a map of the Illinois River Basin (see below), the location of real-time streamflow-gaging stations in the basin, graphs of selected historical recorded flood-crest stages at each of the stations, and sea-level conversion (SLC) factors that allow conversion of the current or predicted flood-crest stage to elevation above sea level. Each graph represents a streamflow-gaging station and has a space to record the most current river stage reported for that station by the U.S. Geological Survey (USGS). The National Weather Service (NWS) predicts flood crests for many of the stations shown on this chart.

Illinois

Estimating site occupancy and detection probability parameters for meso- and large mammals in a coastal eosystem

Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant detectability when documenting species occurrence. This assumption is rarely met in practice because animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these influences, we estimated site occupancy rates using species-specific detection probabilities for meso- and large terrestrial mammal species on Cape Cod, Massachusetts, USA. We used model selection to assess the influence of different sampling methods and major environmental factors on our ability to detect individual species. Remote cameras detected the most species (9), followed by cubby boxes (7) and hair traps (4) over a 13-month period. Estimated site occupancy rates were similar among sampling methods for most species when detection probabilities exceeded 0.15, but we question estimates obtained from methods with detection probabilities between 0.05 and 0.15, and we consider methods with lower probabilities unacceptable for occupancy estimation and inference. Estimated detection probabilities can be used to accommodate variation in sampling methods, which allows for comparison of monitoring programs using different protocols. Vegetation and seasonality produced species-specific differences in detectability and occupancy, but differences were not consistent within or among species, which suggests that our results should be considered in the context of local habitat features and life history traits for the target species. We believe that site occupancy is a useful state variable and suggest that monitoring programs for mammals using occupancy data consider detectability prior to making inferences about species distributions or population change.

Journal of Wildlife Management

Space-based imaging radar studies of U.S. volcanoes

The arrival of space-based imaging radar as a revolutionary land-surface mapping and monitoring tool little more than a quarter century ago enabled a spate of innovative volcano research worldwide. Soon after launch of European Space Agency’s ERS-1 spacecraft in 1991, the U.S. Geological Survey began SAR and InSAR studies of volcanoes in the Aleutian and Cascades arcs, in Hawai’i, and elsewhere in the western U.S. including the Yellowstone and Long Valley calderas. This paper summarizes results of that effort and presents new findings concerning: (1) prevalence of volcano deformation in the Aleutian and Cascade arcs; (2) surface-change detection and hazard assessment during eruptions at Aleutian and Hawaiian volcanoes; (3) geodetic imaging of magma storage and transport systems in Hawai’i; and (4) deformation sources and processes at the Yellowstone and Long Valley calderas. Surface deformation caused by a variety of processes is common in arc settings and could easily escape detection without systematic InSAR surveillance. Space-based SAR imaging of active lava flows and domes in remote or heavily vegetated settings, including during periods of bad weather and darkness, extends land-based monitoring capabilities and improves hazards assessments. At Kīlauea Volcano, comprehensive SAR and InSAR observations identify multiple magma storage zones beneath the summit area and along the East Rift Zone, and illuminate magma transport pathways. The same approach at Yellowstone tracks the ascent of magmatic volatiles from a mid-crustal intrusion to shallow depth and relates that process to increased hydrothermal activity at the surface. Together with recent and planned launches of highly capable imaging-radar satellites, these findings support an optimistic outlook for near-real time surveillance of volcanoes at global scale in the coming decade.

Frontiers in Earth Science

Influence of climate, post‐treatment weather extremes, and soil factors on vegetation recovery after restoration treatments in the southwestern US

Aims Understanding the conditions associated with dryland vegetation recovery after restoration treatments is challenging due to a lack of monitoring data and high environmental variability over time and space. Tracking recovery trajectories with satellite‐based vegetation indices can strengthen predictions of restoration outcomes across broad areas with varying environmental conditions. Location Southwestern United States. Methods We quantified the recovery trajectories of spring and summer soil‐adjusted total vegetation index (SATVI) for 5 to 10 year periods following post‐wildfire seeding or prescribed burns for 241 treatment sites, and related SATVI to ground‐based vegetation cover. We modeled SATVI based on time since treatment, yearly temperature and precipitation, weather extremes following treatment, soil available water capacity, invasive species presence, and treatment type. We also tested for the effects of environmental variables on trajectories, by examining interactions with years post‐treatment. Results Ground‐based vegetation cover and SATVI were highly correlated. Most treatment sites had positive recovery rates for spring (82%) and summer (85%) SATVI. Several environmental variables affected vegetation recovery trajectories as indicated by interactions with time since treatment. Yearly warm season precipitation had a positive effect on SATVI recovery that increased over time, whereas the positive effect of extreme high warm season precipitation following treatment decreased over time for both seasons of vegetation measurements. For spring SATVI, the positive effect of cool season yearly precipitation increased over time while the negative effect of extreme high temperatures following treatment became more negative over time. Invasive species presence led to higher spring, but not summer, SATVI. Conclusions Satellite‐based remote sensing is a promising tool to assess vegetation recovery following restoration treatments, particularly when it is combined with ground‐based monitoring. Our results suggest that weather extremes following restoration treatments can affect vegetation recovery trajectories and should be considered in decisions such as the timing of restoration treatments.

Applied Vegetation Science

On the nature and rate of resurfacing of Venus

Crater production and obliteration are modeled for the plains of Venus, using: (1 ) the observed distribution of Venus-crossing asteroids and comets, (2) viscous relaxation of crater topography, and (3) erosion and burial by atmospheric, volcanic, and tectonic processes. Crater lifetimes are assumed to be proportional to crater depths for both classes of obliterative processes although the individual criteria vary. An average crater retention age between 0.4 to 2.0 Ga is estimated for plains under the assumption that craters are produced and not removed. The range is driven by uncertainty in identifying degraded impact as opposed to volcanic craters. On the other hand, crater retention ages greater than about 1.6 Ga are unlikely if viscous relaxation operates without loading of crater floors by burial. Our preferred model has plains subject to crater production and obliteration processes that vary over both space and time. In some areas, radar-bright crater ejecta haloes are preserved for long periods of time because volcanism, tectonism, and weathering occurs at rates « 1 km/Ga. Viscous relaxation has probably generated numerous shallow craters in these relatively quiescent regions. In other areas, volcanism and tectonism have resurfaced the terrain at rates greater than several km/Ga. The global coverage and high resolution SAR and altimetry data expected from Magellan will allow testing of this model, based on detailed crater observations (diameter, depth distributions; morphologic criteria; surface scattering properties) and their association with volcanic and tectonic features.

Geophysical Research Letters

Temporal variability of local abundance, sex ratio and activity in the Sardinian chalk hill blue butterfly

When capturing and marking of individuals is possible, the application of newly developed capture-recapture models can remove several sources of bias in the estimation of population parameters such as local abundance and sex ratio. For example, observation of distorted sex ratios in counts or captures can reflect either different abundances of the sexes or different sex-specific capture probabilities, and capture-recapture models can help distinguish between these two possibilities. Robust design models and a model selection procedure based on information-theoretic methods were applied to study the local population structure of the endemic Sardinian chalk hill blue butterfly, Polyommatus coridon gennargenti. Seasonal variations of abundance, plus daily and weather-related variations of active populations of males and females were investigated. Evidence was found of protandry and male pioneering of the breeding space. Temporary emigration probability, which describes the proportion of the population not exposed to capture (e.g. absent from the study area) during the sampling process, was estimated, differed between sexes, and was related to temperature, a factor known to influence animal activity. The correlation between temporary emigration and average daily temperature suggested interpreting temporary emigration as inactivity of animals. Robust design models were used successfully to provide a detailed description of the population structure and activity in this butterfly and are recommended for studies of local abundance and animal activity in the field.

Oecologia

Native forage mediates influence of irrigated agriculture on migratory behaviour of elk

Ungulates migrate to maximize nutritional intake when forage varies seasonally. Populations of ungulates often include both migratory and non-migratory individuals, but the mechanisms driving individual differences in migratory behaviour are not well-understood. We quantified associations between hypothesized drivers of partial migration and the likelihood of migration for individual ungulates that experienced a range of environmental conditions and anthropogenic influences. We evaluated the effects of forage variation, conspecific density, and human land uses on migratory behaviour of 308 adult female elk in 16 herds across western Montana. We found irrigated agriculture on an individual's winter range reduced migratory behaviour, but individuals were more likely to migrate away from irrigated agricultural areas if better forage was available elsewhere or if they experienced high conspecific density on their winter range. When the forage available during the summer growing season varied predictably between years, elk were more likely to migrate regardless of whether they had access to irrigated agriculture. Our study shows that predictable availability of beneficial native forage can encourage migration even for ungulates with irrigated agriculture on their winter range. Perturbations that can affect the forage available to ungulates include wildfires, timber harvest, livestock grazing and changing weather patterns. If these or other disturbances negatively affect forage on summer ranges of migrants, or if they cause forage to vary unpredictably across space and time, our results suggest migratory behaviour may decline as a result.

Montana