USGS Science⌕ Search

SEARCH · USGS Science

Results for “Climate Change”

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

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

At least 1,657 records · Page 92Linked to original sources
USGS2019

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

Aim Phenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal. Location North America. Time period 2010–2017. Major taxa studied Snowshoe hare ( Lepus americanus ). Methods We used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring. Results Spatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack. Main conclusions Long‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.

Global Ecology and Biogeography↗
USGS2018

Increasing soil organic carbon to mitigate greenhouse gases and increase climate resiliency for California

Rising air temperatures are projected to continue to drive up urban, agricultural, and rangeland water use, straining both surface and groundwater resources. Scientific studies have shown that managing farms, ranches, and public lands to increase soil carbon can increase soil waterholding capacity and increase hydrologic benefits such as increased baseflows and aquifer recharge, reduced flooding and erosion, and reduced climate-related water deficits. Coincident improvements in forage and crop yields are also indicated, while simultaneously sequestering carbon, reducing atmospheric greenhouse gases and mitigating climate change. This study was developed to consider the multiple benefits of increasing the organic matter content of soils across California’s working lands. Study results indicate that a one-time ¼” application of compost to rangelands can lead to carbon sequestration rates in soils that are maximized after approximately 15 years, and more than offset greenhouse gas emissions stimulated by the compost addition for at least five decades longer. Modeled increases in total soil organic matter of 3% enhanced hydrologic benefits across 97% of working lands, and reduced climate change impacts. Economic valuation indicated all benefits increasing over time, demonstrating a large potential for the California carbon market to support incentives in regionalizing the impacts in the coming decades. Socioeconomic and related land use pressures pose barriers to implementing management practices to increase soil organic matter by driving conversion of rangeland to urban or to more greenhouse-gas emission intensive agriculture. Results can be effectively used with land use change scenarios to identify where on California’s working lands hydrologic benefits of soil organic matter enhancement coincide with development risk, highlighting counties in California in which there may be resilience to climate change when strategic soil management and land conservation are combined.

California↗
USGS2011

Are secular correlations between sunspots, geomagnetic activity, and global temperature significant?

Recent studies have led to speculation that solar‐terrestrial interaction, measured by sunspot number and geomagnetic activity, has played an important role in global temperature change over the past century or so. We treat this possibility as an hypothesis for testing. We examine the statistical significance of cross‐correlations between sunspot number, geomagnetic activity, and global surface temperature for the years 1868–2008, solar cycles 11–23. The data contain substantial autocorrelation and nonstationarity, properties that are incompatible with standard measures of cross‐correlational significance, but which can be largely removed by averaging over solar cycles and first‐difference detrending. Treated data show an expected statistically‐significant correlation between sunspot number and geomagnetic activity, Pearson p < 10 −4 , but correlations between global temperature and sunspot number (geomagnetic activity) are not significant, p = 0.9954, ( p = 0.8171). In other words, straightforward analysis does not support widely‐cited suggestions that these data record a prominent role for solar‐terrestrial interaction in global climate change. With respect to the sunspot‐number, geomagnetic‐activity, and global‐temperature data, three alternative hypotheses remain difficult to reject: (1) the role of solar‐terrestrial interaction in recent climate change is contained wholly in long‐term trends and not in any shorter‐term secular variation, or, (2) an anthropogenic signal is hiding correlation between solar‐terrestrial variables and global temperature, or, (3) the null hypothesis, recent climate change has not been influenced by solar‐terrestrial interaction.

Geophysical Research Letters↗
USGS2024

Peak streamflow trends in Wisconsin and their relation to changes in climate, water years 1921–2020

This study characterizes hydroclimatic variability and change in peak streamflow and daily streamflow in Wisconsin from water years 1921 through 2020. Nonstationarity in peak streamflow in Wisconsin can include monotonic trends, change points, and autocorrelation. Spatial patterns of nonstationarity in peak streamflow, daily streamflow, and monthly precipitation, temperature, and snowfall were examined using four temporal periods. Upward trends in peak streamflow and daily streamflow were detected across the State, from around 1990 to 2020 and were likely predominantly driven by concurrent increases in precipitation and temperatures during this time. Earlier decreases in peak streamflow between the 1920s to the 1980s in the southern parts of the State were likely affected by nonclimate-related factors such as urbanization, water use, and land-use changes associated with agriculture.

Wisconsin↗
USGS2024

Climate-smart agriculture for Ukraine: Winter wheat breeding for food security and climate adaptation

Since the onset of the COVID-19 pandemic in early 2020, people have experienced food insecurity challenges because of increased prices of staple food commodities and loss of income or livelihood. Globally, countries with limited capacity to adapt have struggled to recover from pandemic-related disruptions and are further challenged to address adverse effects of climate change on agricultural production (United Nations [UN], 2022). Ukraine, a key agricultural exporter of staple food commodities, has a vital role in contributing to global food security, in particular through its wheat exports to countries in the Middle East, North Africa, and Europe (Martyshev and others, 2023). However, Ukraine’s role as a stable source of global wheat has been disrupted by the ongoing Russia-Ukraine war—a conflict which began in February of 2022. Given the fragile state of global and local markets and food systems, and the increasing risk climate change poses to agricultural production globally, Ukraine has prioritized adopting efficient agricultural practices to contribute to stabilizing crop yields and to increase its capacity to export wheat and other staple crops. According to Ukraine’s Ministry of Agrarian Policy and Food (MINAGRO), along with addressing climate change, a contributing driver for this prioritization is the desire to join the European Union (EU) and the need to meet the requirements for the EU’s Common Agricultural Policy (CAP) for acceptance as a union member state (Markiyan Dmytrasevych, a former deputy minister of MINAGRO, oral commun., 2023). As a result, MINAGRO is considering climate-smart agricultural practices to secure future crop yields and build resilience within its agricultural sector, especially as the war has impeded millions of tons of crops from reaching domestic and global markets. This report employs the climate-smart agriculture framework to provide Ukrainian agricultural policy- and decision makers and others in technical and development assistance roles with an overview of relevant climate, environmental, and agricultural policy and market factors, and projections on climate and environmental resources that could influence the implementation of climate-smart agricultural practices in Ukraine, and aid Ukraine in successfully joining the EU.

Report↗
USGS2020

Simulated estuary-wide response of seagrass (Zostera marina) to future scenarios of temperature and sea level

Seagrass communities are a vital component of estuarine ecosystems, but are threatened by projected sea level rise (SLR) and temperature increases with climate change. To understand these potential effects, we developed a spatially explicit model that represents seagrass ( Zostera marina ) habitat and estuary-wide productivity for Barnegat Bay-Little Egg Harbor (BB-LEH) in New Jersey, United States. Our modeling approach included an offline coupling of a numerical seagrass biomass model with the spatially variable environmental conditions from a hydrodynamic model to calculate above and belowground biomass at each grid cell of the hydrodynamic model domain. Once calibrated to represent present day seagrass habitat and estuary-wide annual productivity, we applied combinations of increasing air temperature and sea level following regionally specific climate change projections, enabling analysis of the individual and combined impacts of these variables on seagrass biomass and spatial coverage. Under the SLR scenarios, the current model domain boundaries were maintained, as the land surrounding BB-LEH is unlikely to shift significantly in the future. SLR caused habitat extent to decrease dramatically, pushing seagrass beds toward the coastline with increasing depth, with a 100% loss of habitat by the maximum SLR scenario. The dramatic loss of seagrass habitat under SLR was in part due to the assumption that surrounding land would not be inundated, as the model did not allow for habitat expansion outside the current boundaries of the bay. Temperature increases slightly elevated the rate of summer die-off and decreased habitat area only under the highest temperature increase scenarios. In combined scenarios, the effects of SLR far outweighed the effects of temperature increase. Sensitivity analysis of the model revealed the greatest sensitivity to changes in parameters affecting light limitation and seagrass mortality, but no sensitivity to changes in nutrient limitation constants. The high vulnerability of seagrass in the bay to SLR exceeded that demonstrated for other systems, highlighting the importance of site- and region-specific assessments of estuaries under climate change.

New Jersey↗
USGS2025

UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape

Context Shifts in precipitation regimes due to climate change are significantly impacting dryland ecosystems, including vegetation composition and structure. Unoccupied aerial vehicles (UAVs) are widely used to monitor vegetation, but whether models built to predict changes in these characteristics are robust under extreme precipitation regimes is unclear. Objectives We aimed to predict key vegetation characteristics under three precipitation regimes (ambient, drought, and water addition) and assess model performance across these moisture conditions. We also evaluated how models built under ambient conditions predicted vegetation characteristics under extreme precipitation regimes. Methods UAV surveys were conducted at five sites subject to long-term precipitation manipulation along an elevation gradient in northern Arizona, United States (U.S.). Twenty-one vegetation indices and point cloud data from the UAV imagery were used to develop models to predict vegetation structure and composition characteristics. Model performance and transferability were assessed via error and directional bias within each treatment (i.e., in situ) and from ambient to precipitation treatments (i.e., model transfer). Results UAV-based models accurately measured vegetation characteristics across all regimes, but maximum height showed significantly higher error under drought conditions. Models developed under ambient precipitation and applied to extreme precipitation treatments exhibited significant differences in the error and directional bias, indicating they may not be suitable under climate change. Conclusions UAV-based models are effective for monitoring vegetation characteristics but may lose accuracy under extreme precipitation regimes expected under climate change. This study emphasizes the need to improve model transferability and suggests refining landscape monitoring approaches to consider extreme changes in precipitation and associated vegetation responses.

Arizona↗
USGS2014

The future of nearshore processes research

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment. Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes: Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability. Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities. The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies. The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.

Report↗
USGS1999

Potential effects of gas hydrate on human welfare

For almost 30 years, serious interest has been directed toward natural gas hydrate, a crystalline solid composed of water and methane, as a potential (i) energy resource, (ii) factor in global climate change, and (iii) sub-marine geohazard. Although each of these issues can affect human welfare, only (iii) is considered to be of immediate importance. Assessments of gas hydrate as an energy resource have often been overly optimistic, based in part on its very high methane content and on its worldwide occurrence in continental margins. Although these attributes are attractive, geologic settings, reservoir properties, and phase-equilibria considerations diminish the energy resource potential of natural gas hydrate. The possible role of gas hydrate in global climate change has been often overstated. Although methane is a 'greenhouse' gas in the atmosphere, much methane from dissociated gas hydrate may never reach the atmosphere, but rather may be converted to carbon dioxide and sequestered by the hydrosphere/biosphere before reaching the atmosphere. Thus, methane from gas hydrate may have little opportunity to affect global climate change. However, submarine geohazards (such as sediment instabilities and slope failures on local and regional scales, leading to debris flows, slumps, slides, and possible tsunamis) caused by gas-hydrate dissociation are of immediate and increasing importance as humankind moves to exploit seabed resources in ever-deepening waters of coastal oceans. The vulnerability of gas hydrate to temperature and sea level changes enhances the instability of deep-water oceanic sediments, and thus human activities and installations in this setting can be affected.

Conference Paper↗
USGS2024

Concordant signal of genetic variation across marker densities in the desert annual Chylismia brevipes is linked with timing of winter precipitation

Climate change coupled with large-scale surface disturbances necessitate active restoration strategies to promote resilient and genetically diverse native plant communities. However, scarcity of native plant materials hinders restoration efforts, leading practitioners to choose from potentially viable but nonlocal seed sources. Genome scans for genetic variation linked with selective environmental gradients have become a useful tool in such efforts, allowing rapid delineation of seed transfer zones along with predictions of genomic vulnerability to climate change. When properly applied, genome scans can reduce the risk of maladaptation due to mismatches between seed source and planting site. However, results are rarely replicated among complimentary data sources. Here, we compared RAD-seq datasets with 819 and 2699 SNPs (in 625 and 356 individuals, respectively) from the Mojave Desert winter annual Chylismia brevipes . Overall, we found that the datasets consistently characterized both neutral population structure and genetic–environmental associations. Ancestry analyses indicated consistent spatial genetic structuring into four regional populations. We also detected a marked signal of isolation by resistance (IBR), wherein spatial genetic structure was better explained by habitat resistance than by geographic distance. Potentially adaptive loci identified from genome scans were associated with the same environmental gradients—fall precipitation, winter minimum temperature, and precipitation timing—regardless of dataset. Paired with our finding that habitat resistance best explained genetic divergence, our results suggest that isolation of populations within environmentally similar habitats—and subsequent local adaption along gradients parallel to these habitats—drive genome-wide divergence in this species. Moreover, strong genetic associations with winter precipitation timing, along with forecasted shifts in precipitation regime due to midcentury climate change, could impact future population dynamics, habitat distribution, and genetic connectivity for C. brevipes populations within the Mojave Desert.

Arizona, California, Nevada↗
USGS1991

Detectability of the effects of a hypothetical temperature increase on the Thornthwaite moisture index

Climatic changes that result from increasing concentrations of atmospheric carbon dioxide may affect the availability of water for vegetation, groundwater recharge, runoff, and human consumption. Most studies of the effects of climatic change on water resources focus on changes in mean characteristics of hydrologic variables and do not consider the effects of these changes amid natural climatic variability. In this study, the Thornthwaite moisture index, an index of the supply of water in an area (precipitation) relative to the climatic demand for water (potential evapotranspiration), was used to examine the effects of a hypothetical increase in air temperature on moisture conditions in the United States. The effects of a gradual increase in air temperature at the rate of 4°C per 100 years, with no accompanying change in precipitation, was used to induce a change in Thornthwaite moisture index values for the United States in order to: (i) determine the relation between natural variability in climate and the time needed for significant trends in the moisture index to occur in response to hypothetical warming; (ii) identify the characteristics of areas (e.g. wet/cool, hot/dry etc.) that are most likely to be the first to experience significant changes in the moisture index given the hypothetical temperature increase. The increased temperature resulted in increased potential evapotranspiration and a decrease in the moisture index across the United States. Decreases in the moisture index were greatest in cool/wet regions and least in hot/dry regions. The time required to detect significant trends in the moisture index was a function of both the magnitude of change in the moisture index and the natural year-to-year variability of the moisture index. In general, when the ratio of the magnitude of change in the moisture index to the magnitude of variability was large, the time required to detect significant trends was short. This ratio was largest in cool/wet regions resulting in the shortest detection times.

Journal of Hydrology↗
USGS2022

Deconstructing the microbial necromass continuum to inform soil carbon sequestration

Microbial necromass is a large, dynamic and persistent component of soil organic carbon, the dominant terrestrial carbon pool. Quantification of necromass carbon stocks and its susceptibility to global change is becoming standard practice in soil carbon research. However, the typical proxies used for necromass carbon do not reveal the dynamic nature of necromass carbon flows and transformations within soil that ultimately determine necromass persistence. In this review, we define and deconstruct four stages of the necromass continuum: production, recycling, stabilization and destabilization. Current understanding of necromass dynamics is described for each continuum stage. We highlight recent advances, methodological limitations and knowledge gaps which need to be addressed to determine necromass pool sizes and transformations. We discuss the dominant controls on necromass process rates and aspects of soil microscale structure including biofilms and food web interactions. The relative importance of each stage of the continuum is then compared in contrasting ecosystems and for climate change drivers. From the perspective of the continuum, we draw three conclusions to inform future research. First, controls on necromass persistence are more clearly defined when viewed through the lens of the continuum; second, destabilization is the least understood stage of the continuum with recycling also poorly evidenced outside of a few ecosystems; and third, the response of necromass process rates to climate change is unresolved for most continuum stages and ecosystems. Future mechanistic research focused on the role of biotic and abiotic soil microscale structure in determining necromass process rates and the relative importance of organo–mineral and organo–organo interactions can inform necromass persistence in different climate change scenarios. Our review demonstrates that deconstructing the necromass continuum is key to predicting the vulnerability and persistence of necromass carbon in a changing world.

Functional Ecology↗
USGS2017

Estimating thermal performance curves from repeated field observations

Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.

Ecology↗
USGS2023

Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon

Introduction: Forecasting range shifts in response to climate change requires accurate species distribution models (SDMs), particularly at the margins of species' ranges. However, most studies producing SDMs rely on sparse species occurrence datasets from herbarium records and public databases, along with random pseudoabsences. While environmental covariates used to fit SDMS are increasingly precise due to satellite data, the availability of species occurrence records is still a large source of bias in model predictions. We developed distribution models for hybridizing sister species of western and eastern Joshua trees ( Yucca brevifolia and Y. jaegeriana , respectively), iconic Mojave Desert species that are threatened by climate change and habitat loss. Methods: We conducted an intensive visual grid search of online satellite imagery for 672,043 0.25 km 2 grid cells to identify the two species' presences and absences on the landscape with exceptional resolution, and field validated 29,050 cells in 15,001 km of driving. We used the resulting presence/absence data to train SDMs for each Joshua tree species, revealing the contemporary environmental gradients (during the past 40 years) with greatest influence on the current distribution of adult trees. Results: While the environments occupied by Y. brevifolia and Y. jaegeriana were similar in total aridity, they differed with respect to seasonal precipitation and temperature ranges, suggesting the two species may have differing responses to climate change. Moreover, the species showed differing potential to occupy each other's geographic ranges: modeled potential habitat for Y. jaegeriana extends throughout the range of Y. brevifolia , while potential habitat for Y. brevifolia is not well represented within the range of Y. jaegeriana . Discussion: By reproducing the current range of the Joshua trees with high fidelity, our dataset can serve as a baseline for future research, monitoring, and management of this species, including an increased understanding of dynamics at the trailing and leading margins of the species' ranges and potential for climate refugia.

Frontiers Ecology and Evolution↗
USGS2007

Cloud water in windward and leeward mountain forests: The stable isotope signature of orographic cloud water

Cloud water can be a significant hydrologic input to mountain forests. Because it is a precipitation source that is vulnerable to climate change, it is important to quantify amounts of cloud water input at watershed and regional scales. During this study, cloud water and rain samples were collected monthly for 2 years at sites on windward and leeward East Maui. The difference in isotopic composition between volume‐weighted average cloud water and rain samples was 1.4‰ δ 18 O and 12‰ δ 2 H for the windward site and 2.8‰ δ 18 O and 25‰ δ 2 H for the leeward site, with the cloud water samples enriched in 18 O and 2 H relative to the rain samples. A summary of previous literature shows that fog and/or cloud water is enriched in 18 O and 2 H compared to rain at many locations around the world; this study documents cloud water and rain isotopic composition resulting from weather patterns common to montane environments in the trade wind latitudes. An end‐member isotopic composition for cloud water was identified for each site and was used in an isotopic mixing model to estimate the proportion of precipitation input from orographic clouds. Orographic cloud water input was 37% of the total precipitation at the windward site and 46% at the leeward site. This represents an estimate of water input to the forest that could be altered by changes in cloud base altitude resulting from global climate change or deforestation.

Water Resources Research↗
USGS2022

Human and ecosystem health in coastal systems

U.S. coastal economies and communities are facing an unprecedented and growing number of impacts to coastal ecosystems including beach and fishery closures, harmful algal blooms, loss of critical habitat, as well as shoreline damage. This paper synthesizes our present understanding of the dynamics of human and ecosystem health in coastal systems with a focus on the need to better understand nearshore physical process interactions with coastal pollutants and ecosystems (e.g. fate and transport, circulation, depositional environment, climate change). It is organized around two major topical areas and six subtopic areas: 1) Identifying and mitigating coastal pollutants, including fecal pollution, nutrients and harmful algal blooms, and microplastics; and 2) Resilient coastal ecosystems, which focuses on coastal fisheries, shellfish and natural and nature-based features (NNBF). Societal needs and the tools and technologies needed to address them are discussed for each subtopic. Recommendations for scientific research, observations, community engagement, and policies aim to help prioritize future research and investments. A better understanding of coastal physical processes and interactions with coastal pollutants and resilient ecosystems (e.g. fate and transport, circulation, depositional environment, climate change) is a critical need. Other research recommendations include the need to quantify potential threats to human and ecosystem health through accurate risk assessments and to quantify the resulting hazard risk reduction of natural and nature-based features; improve pollutant and ecosystem impacts forecasting by integrating frequent and new data points into existing and novel models; collect environmental data to calibrate and validate models to predict future impacts on coastal ecosystems and their evolution due to anthropogenic stressors (land-based pollution, overfishing, coastal development), climate change, and sea level rise; and develop lower cost and rapid response tools to help coastal managers better respond to pollutant and ecosystem threats.

Shore and Beach↗
USGS2015

Final project memorandum: sea-level rise modeling handbook: resource guide for resource managers, engineers, and scientists

Coastal wetlands of the Southeastern United States are undergoing retreat and migration from increasing tidal inundation and saltwater intrusion attributed to climate variability and sea-level rise. Much of the literature describing potential sea-level rise projections and modeling predictions are found in peer-reviewed academic journals or government technical reports largely suited to reading by other Ph.D. scientists who are more familiar or engaged in the climate change debate. Various sea-level rise and coastal wetland models have been developed and applied of different designs and scales of spatial and temporal complexity for predicting habitat and environmental change that have not heretofore been synthesized to aid natural resource managers of their utility and limitations. Training sessions were conducted with Federal land managers with U.S. Fish and Wildlife Service, National Park Service, and NOAA National Estuarine Research Reserves as well as state partners and nongovernmental organizations across the northern Gulf Coast from Florida to Texas to educate and to evaluate user needs and understanding of concepts, data, and modeling tools for projecting sea-level rise and its impact on coastal habitats and wildlife. As a result, this handbook was constructed from these training and feedback sessions with coastal managers and biologists of published decision-support tools and simulation models for sea-level rise and climate change assessments. A simplified tabular context was developed listing the various kinds of decision-support tools and ecological models along with criteria to distinguish the source, scale, and quality of information input and geographic data sets, physical and biological constraints and relationships, datum characteristics of water and land elevation components, utility options for setting sea-level rise and climate change scenarios, and ease or difficulty of storing, displaying, or interpreting model output. The handbook is designed to be a primer to understanding sea-level rise and a practical synthesis of the current state of knowledge and modeling tools as a resource guide for DOl land management needs and facilitating Landscape Conservation Cooperative (LCC) research and conservation initiatives.

Conference Paper↗
USGS2025

Protected from Pterygoplichthys? Predicting thermal habitat suitability for nonnative armored catfish in the Suwannee River

Objective Nonnative fishes can modify ecosystems and harm economies when they are introduced to new environments. Climate change is likely to assist the spread and establishment of some nonnative fishes (e.g., warmwater species), but spatiotemporal gaps in water temperature monitoring and modeling may prevent ecologists and managers from forecasting thermal habitat suitability for these taxa. The purpose of this study was to develop a predictive model of winter water temperatures and thermal habitat suitability for two priority nonnative armored catfish, Vermiculated Sailfin Catfish Pterygoplichthys disjunctivus and Orinoco Sailfin Catfish P. multiradiatus , in the Suwannee River, Florida and Georgia. Methods Precipitation- and groundwater-corrected air–water temperature models were developed and evaluated using a model selection procedure to predict water temperatures at four sites in the Suwannee River. These models were chosen because they blend the simplicity of air–water temperature models with the accuracy of hydrometeorological models to create an efficient, economical, management-relevant approach for analyzing and forecasting water temperature. Results Most of the top-performing water temperature models (92%) had precipitation or groundwater corrections to air–water temperature formulations. Projected mean and maximum water temperatures increased as simulated climate change intensified. All four Suwannee River sites studied were projected to be thermally hospitable to the survival of Vermiculated Sailfin Catfish. Lower river sites, noticeably warmer than upper river sites, were conducive to the survival of Orinoco Sailfin Catfish throughout the winter months. The upper river sites were too cold for Orinoco Sailfin Catfish survival in some climate-change scenarios, but the Suwannee River has an abundance of constant-temperature springs that are likely hospitable to Vermiculated Sailfin Catfish and Orinoco Sailfin Catfish throughout the year. Conclusions The findings suggest that winter water temperatures will likely not be a barrier to the survival of Pterygoplichthys catfish in the Suwannee River, amplifying the importance of conservation and management approaches to inhibit their spread and establishment. If the Pterygoplichthys population remains small and isolated and decision makers are able to devote required staff time and resources to managing these species, removal and eradication at local if not broader scales may be reasonable goals. This study provides a water temperature modeling approach that can aid ecologists and managers in prioritizing sites to prevent the introduction, slow the dispersal, eradicate, and control Pterygoplichthys catfish and other nonnative fishes in the Suwannee River and beyond.

Florida, Georgia↗