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At least 181 records · Page 10Linked to original sources
USGS2023

High-frequency time series comparison of Sentinel-1 and Sentinel-2 for open and vegetated water across the United States (2017-2021)

Frequent observations of surface water at fine spatial scales will provide critical data to support the management of aquatic habitat, flood risk and water quality. Sentinel-1 and Sentinel-2 satellites can provide such observations, but algorithms are still needed that perform well across diverse climate and vegetation conditions. We developed surface inundation algorithms for Sentinel-1 and Sentinel-2, respectively, at 12 sites across the conterminous United States (CONUS), covering a total of >536,000 km 2 and representing diverse hydrologic and vegetation landscapes. Each scene in the 5-year (2017–2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables from Sentinel-1 and Sentinel-2, as well as variables derived from topographic and weather datasets. The Sentinel-1 algorithm was developed distinct from the Sentinel-2 model to explore if and where the two time series could potentially be integrated into a single high-frequency time series. Within each model, open water and vegetated water (vegetated palustrine, lacustrine, and riverine wetlands) classes were mapped. The models were validated using imagery from WorldView and PlanetScope. Classification accuracy for open water was high across the 5-year period, with an omission and commission error of only 3.1% and 0.9% for the Sentinel-1 algorithm and 3.1% and 0.5% for the Sentinel-2 algorithm, respectively. Vegetated water accuracy was lower, as expected given that the class represents mixed pixels. The Sentinel-2 algorithm showed higher accuracy (10.7% omission and 7.9% commission error) relative to the Sentinel-1 algorithm (28.4% omission and 16.0% commission error). Patterns over time in the proportion of area mapped as open or vegetated water by the Sentinel-1 and Sentinel-2 algorithms were charted and correlated for a subset of all 12 sites. Our results showed that the Sentinel-1 and Sentinel-2 algorithm open water time series can be integrated at all 12 sites to improve the temporal resolution, but sensor-specific differences, such as sensitivity to vegetation structure versus pixel color, complicate the data integration for mixed-pixel, vegetated water. The methods developed here provide inundation at 5-day (Sentinel-2 algorithm) and 12-day (Sentinel-1 algorithm) time steps to improve our understanding of the short- and long-term response of surface water to climate and land use drivers in different ecoregions.

continental United States↗
USGS2022

Predicting flood damage probability across the conterminous United States

Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. From this, we produced the first spatially complete map of flood damage probability for the nation, along with spatially explicit standard errors for four selected cities. We trained models using the locations of historical reported flood damage events ( n = 71,434) and a suite of geospatial predictors (e.g., flood severity, climate, socio-economic exposure, topographic variables, soil properties, and hydrologic characteristics). We developed independent models for each hydrologic unit code level 2 watershed and generated a flood damage probability for each 100-m pixel. Our model classified damage or no damage with an average area under the curve accuracy of 0.75; however, model performance varied by environmental conditions, with certain land cover classes (e.g., forest) resulting in higher error rates than others (e.g., wetlands). Our results identified flood damage probability hotspots across multiple spatial and regional scales, with high probabilities common in both inland and coastal regions. The highest flood damage probabilities tended to be in areas of low elevation, in close proximity to streams, with extreme precipitation, and with high urban road density. Given rapid environmental changes, our study demonstrates an efficient approach for updating flood damage probability estimates across the nation.

Environmental Research Letters↗
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↗
USGS2024

Delayed positive responses of snowshoe hares to prescribed burning in a fire-adapted ecosystem

Wildlife populations near the periphery of a species’ range are vulnerable to changes in habitat conditions and climate. However, habitat management and maintenance can help with the persistence of these susceptible populations. Snowshoe hare ( Lepus americanus ) populations near the southern extent of their range are at risk of extirpation because of changing winter conditions, coupled with reduced early-successional habitat. Prescribed fire has been used to restore and maintain early-successional habitat in the southern range of snowshoe hares, but previous research suggests that burned areas might initially be unsuitable for hares. Therefore, more information is needed on the time required for hares to start using an area post-burning, and the long-term effects of prescribed fire on hare survival. We studied snowshoe hare habitat use and survival in northeastern Pennsylvania, where prescribed fire has been used for scrub oak barrens restoration. We used GPS locations from 71 hares and used resource selection functions to analyze hare selection for burned habitats of varying ages (0–12 years post-burn) and known-fate survival models to evaluate the effects of burning on survival. Hares started using burned areas ≥7 years post-burning but avoided areas burned 0–6 years prior. In addition, hare survival was positively associated with the amount of old burn habitat (≥7 years post-burn) used by an individual. Our results indicate that prescribed burning can be beneficial for hares, but that a time lag of ≥7 years is necessary for positive responses to occur. Planning burns within a mosaic of unburned areas could allow hares to persist during the 0–6 years post-burn when areas are not suitable for hares, which in turn could benefit the persistence of southern snowshoe hare populations. Collectively, our results highlight the importance of long-term demographic monitoring to understand wildlife population responses to management actions.

Pennsylvania↗
USGS2013

Land use planning and wildfire: development policies influence future probability of housing loss

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

California↗
USGS2023

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

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

California↗
USGS2019

Evaluating community-level response to management actions across a diverse Hawaiian forest bird community

Although species‐specific approaches are necessary to understand the dynamics of individual species composing a community, they do not offer a framework for making optimal management decisions at the community level. Here, we present a simple framework for comparing the response of entire communities to multiple management scenarios. Our approach uses a weighted average of standardized species‐specific responses to produce a single integrative measure of the community response and employs mixed‐effect linear models to quantify the increase in the community response due to each management action, or combination of actions. We demonstrate our approach with a simulation study assessing the potential benefits of multiple management actions on the avian community of Hakalau Forest National Wildlife Refuge, Hawaiʻi, which is composed of eight native species with conservation status varying from endangered to least concern. Management actions considered included a reduction of avian malaria transmission risk, reducing rat predation, and increasing forest habitat. We used three different prioritization (weighting) schemes to assess whether the response to management actions differed along a conservation gradient (from endangered to least concern). We also investigated whether future changes in disease distribution as a result of climate change will alter the relationship between management practices and community response. Our community‐level analysis produced three important insights, highlighting the need to consider the response from multiple species to changing threats and management actions. First, increasing the amount of habitat always had the greatest positive impact on the avian community, regardless of the weighting scheme. Second, the community response to management was different under current vs. future conditions, with increased benefit in the future when disease risks were higher. Third, the response to management varied along the conservation gradient. Reducing malaria transmission risk in 2100 had the greatest benefit to endangered species, while increasing forest habitat had the greatest benefit to “least concern” species. However, reducing rat predation appeared to benefit a subset of species based on ecological factors unrelated to rarity, such as nest accessibility. Our approach is widely applicable using experimental, observational, or simulation‐based data, allowing managers to consider the response of all species while weighting their priority levels.

Hawaii↗
USGS2016

Risk and efficacy of human-enabled interspecific hybridization for climate-change adaptation: Response to Hamilton and Miller (2016)

Hamilton and Miller ( 2016 ) provide an interesting and provocative discussion of how hybridization and introgression can promote evolutionary potential in the face of climate change. They argue that hybridization—mating between individuals from genetically distinct populations—can alleviate inbreeding depression and promote adaptive introgression and evolutionary rescue. We agree that deliberate intraspecific hybridization (mating between individuals of the same species) is an underused management tool for increasing fitness in inbred populations (i.e., genetic rescue; Frankham 2015 ; Whiteley et al. 2015 ). The potential risks and benefits of assisted gene flow have been discussed in the literature, and an emerging consensus suggests that mating between populations isolated for approximately 50–100 generations can benefit fitness, often with a minor risk of outbreeding depression (Frankham et al. 2011 ; Aitken & Whitlock 2013 ; Allendorf et al. 2013 ).

Conservation Biology↗
USGS2022

Premature mortality observations among Alaska’s Pacific salmon during record heat and drought in 2019

Widespread mortality of Pacific salmon Oncorhynchus spp. returning to spawn in Alaska coincided with record-breaking air temperatures and prolonged drought in summer 2019. Extreme environmental conditions are expected to happen more frequently with rapid climate change and challenge the notion that Alaska could indefinitely provide abundant, cool freshwater habitat for Pacific salmon. A total of 110 geographically widespread opportunistic observations of premature mortality (carcasses) were collected from a variety of sources. Premature mortalities were documented for Pink Salmon Oncorhynchus gorbuscha , Sockeye Salmon O. nerka , Chum Salmon O. keta , Chinook Salmon O. tshawytscha , and Coho Salmon O. kisutch . Additionally, observations of Pink Salmon returning to spawn in Prince William Sound streams in 2019, obtained from systematic aerial surveys conducted annually, revealed low migration success in 87% of rain-driven streams ( n = 30), 52% of snow-driven streams ( n = 65), and only 18% of glacier-driven streams ( n = 11). Salmon mortality observations were consistent with death due to heat stress resulting from high water temperatures or drought caused hypoxia and stranding. Developing a better understanding of how broad-scale climate patterns manifest at the stream scale can help us determine whether a major shift in Pacific salmon productivity is underway and inform fisheries management plans to better mitigate future risks.

Alaska↗
USGS2025

Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire

Watershed sediment yield commonly increases after wildfire, often causing negative impacts to downstream infrastructure and water resources. Post-fire erosion is important to understand and quantify because it is increasingly placing water supplies, habitat, communities, and infrastructure at risk as fire regimes intensify in a warming climate. However, measurements of post-fire sediment mobilization are lacking from many regions. We measured sediment yield from a forested, heavily managed 25.4-km 2 watershed in the western Sierra Nevada, California, over 2 years following the 2021 Caldor Fire, by repeat mapping of a reservoir where sediment accumulated from terrain with moderate to high soil burn severity. Sediment yield was less than the geochronology-derived long-term average in the first year post-fire (conservatively estimated at 21.8–28.0 t/km 2 ), low enough to be difficult to measure with uncrewed airborne system (UAS) and bathymetric sonar survey methods that are most effective at detecting larger sedimentary signals. In the second year post-fire the sediment delivery was 1,560–2,010 t/km 2 , an order of magnitude above long-term values, attributable to greater precipitation and intensive salvage logging. Hillslope erosion simulated by the Water Erosion Prediction Project (WEPP) model overestimated the measured amount by a factor of 90 in the first year and in the second year by a factor (1.9) that aligned with previously determined model performance in northern California. We encourage additional field studies, and validation of erosion models where feasible, to further expand the range of conditions informing post-fire hazard assessments and management decisions.

California↗
USGS2023

Riparian vegetation response amid variable climate conditions across the Upper Gila River watershed: Informing Tribal restoration priorities

Riparian systems across the Southwest United States are extremely valuable for the human and ecological communities that engage with them. However, they have experienced substantial changes and stresses over the past century, including non-native vegetation expansion, vegetation die-offs, and increased fire activity. Vegetation management approaches, such as ecological restoration, may address some of these stressors as well as reduce the risk of future impacts. We apply remote sensing to inform restoration priorities along the upper Gila River within the San Carlos Apache Reservation and Upper Gila River watershed. First, we develop a spatially and temporally explicit trend analysis across three observed climate periods (1985–1993, 1993–2014, 2014–2021) using the Landsat-derived indices to quantify changes in riparian vegetation conditions. These maps can be used to identify areas potentially more at risk for degradation. Second, we analyze changes in riparian vegetation within a climate framework to better understand trends and the potential effect of climate change. Vegetation greenness has largely increased throughout the watershed despite intensifying drought conditions across our study period, though areas within the lower watershed have shown increased stress and higher rates of wildfire and other disturbances over the past 5-years. Nevertheless, small-scale restoration activities appear to show improving vegetation conditions, suggesting efficacy of these restoration activities. Results from this study may be integrated with restoration objectives to develop a restoration plan that will help riparian vegetation communities adapt to change.

Arizona↗
USGS2024

Multi-decadal vegetation transformations of a New Mexico ponderosa pine landscape after severe fires and aerial seeding

Wildfires and climate change are having transformative effects on vegetation composition and structure, and post-fire management may have long-lasting impacts on ecosystem reorganization. Post-fire aerial seeding treatments are commonly used to reduce runoff and soil erosion, but little is known about how seeding treatments affect native vegetation recovery over long periods of time, particularly in type-converted forests which have been dramatically transformed by the effects of repeated, high-severity fire. In this study, we analyze and report on a rare long-term (23-year) dataset that documents vegetation dynamics following a 1996 post-fire aerial seed treatment and subsequent 2011 high-severity reburn in a dry conifer forest of northern New Mexico in the southwestern United States. Repeated surveys between 1997 – 2019 of 49 permanent transects were used to test for differences in vegetation cover, richness, and diversity between seeded and unseeded areas, and to characterize the development of seeded and unseeded vegetation communities through time and across gradients of burn severity, elevation, and soil-available water capacity. Post-fire seeding led to a clear and sustained divergence in herbaceous community composition. Seeded plots had much higher cover of non-native graminoids, primarily Bromus inermis , a likely contaminant in the seed mix. High-severity reburning in all plots in 2011 reduced native graminoid cover by half at seeded plots compared to both pre-fire levels and to plots that were unseeded following the initial 1996 fire. In addition, increased fire severity was associated with increased non-native graminoid cover and reduced native graminoid cover, native species richness, and species diversity. This study documents a fire-driven ecosystem transformation from a former conifer forest into a shrub-grass system, reinforced by aerial seeding of grasses and high-severity reburning. This unique long-term dataset illustrates that post-fire seeding carries significant risk of unwanted non-native species invasions that persist through subsequent fires – indicating that alternative post-fire management actions merit consideration to better support native ecosystem resilience in the face of emergent climate change and increasing disturbance. Lastly, this study highlights the importance of long-term monitoring of post-fire vegetation dynamics, as short-term assessments will miss key elements of the full complexity of ecosystem responses to fire and post-fire management actions.

New Mexico↗
USGS2019

Using scenarios to evaluate vulnerability of grassland communities to climate change in the Southern Great Plains of the United States

Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario, and for contemporary climatic conditions, we predicted the spatial patterns of relative productivity for indicator grass species using statistical models of relative above-ground net primary productivity (hereafter, productivity) based on temperature, precipitation, and soil texture (percent sand, silt, or clay). Two indicator grass species were selected to represent each of four focal grassland communities: semi-desert grasslands, shortgrass prairie, mixed-grass prairie, and tallgrass prairie. Changes in spatial patterning of bioclimatic conditions conducive for each indicator species as predicted for each climate scenario relative to current land use were used to evaluate potential vulnerability and conservation opportunities for grassland communities. Specifically, the following questions were addressed for each focal grassland community: (1) Where is the productivity of each species predicted to increase, decrease, or remain stable relative to estimated contemporary productivity for the SGP and LCD pilot area, (2) where is the productivity of the two indicator species for each community predicted to increase, decrease, or remain stable, (3) which grassland communities are most vulnerable to changes in composition and vertical structure, (4) how do current land-use patterns contribute to potential vulnerabilities of grassland communities for the climate scenarios evaluated, and (5) how can managers use the vulnerabilities identified to evaluate conservation opportunities in the SGP and LCD? Current land-use patterns, in combination with the potential effects of a changing climate, pose greater risks to mixed-grass and tallgrass prairies of the SGP compared to semi-desert grasslands and shortgrass prairie. For most climate scenarios evaluated, bioclimatic conditions conducive to the taller species were predicted to contract within some or all the current distribution of mixed-grass and tallgrass prairies within the SGP. An increase in precipitation, however, could potentially ameliorate the negative effects of increasing temperatures as evidenced by higher productivity for the hot-wet scenario compared to the other scenarios for the most vulnerable species. Compounding their greater vulnerability to increasing temperatures coupled with decreasing precipitation, the mixed-grass and tallgrass prairies have been greatly fragmented and converted, primarily by agriculture. In contrast, the climate scenarios evaluated are generally conducive to stable or increasing productivity of indicator species for semi-desert grasslands and shortgrass prairie. In addition, conversion and fragmentation of semi-desert grasslands and shortgrass prairie were relatively low. These results suggest that the synergistic effects of land use and changing climatic conditions could have the greatest effects on the composition and structure of mixed-grass and tallgrass prairies in the SGP. ScienceBase data release files that support this report are available at https://doi.org/10.5066/P9DGJHEP (Manier and others, 2019).

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗
USGS2025

Geochemistry and Soils of the Big Smoky Valley Fens, Nevada

Fens are groundwater-fed wetlands that can provide habitat for plants and animals. Due to anthropogenic activities and climate change, many fens around the world are at risk. This paper presents the results of a study of the hydrology and geochemistry of fens in Big Smoky Valley, central Nevada to support the Bureau of Land Management’s activities in the area. A water sample from the largest fen in the study area was analyzed for its water chemistry and compared to a nearby alluvial aquifer and hot spring. The high SiO 2 concentration of the fen sample implies that the fen water may originate from geothermal water. A soil core was taken to analyze radiocarbon age and soil type. A majority of the core was composed of silt and clay interlayered with water-filled voids. Changes in the character of the clay with depth suggest that there may have been changes in the depositional environment over time. Radiocarbon dating of Ruppia seeds showed longevity of the fen, with the minimum 14 C age of the core as 4,375±40 years. This paper provides reconnaissance-level information on the Big Smoky Valley fens, but further information would be needed to better understand the source of water to the fens or how the fen environment has changed over time with climate.

Nevada↗
USGS2025

Assessing risk for enhanced cyanobacteria, phytoplankton, and pathogens with changes in water level regime with potential application to Lake Powell and Lake Mead: A mixed methods literature review

Water levels in freshwater reservoirs worldwide are changing due to altered climate, management practices, and increasing human demand for water. In the desert southwestern USA, managers are considering significant changes to reservoir operation strategies and water management in response to consumptive use and ongoing drought. To inform reservoir management decision-making, we reviewed current peer-reviewed literature to identify the effects of decreasing or increasing water level on phytoplankton, cyanobacteria, Escherichia coli , and Naegleria spp. We identified 34 studies containing 42 individual waterbodies that investigated the effects of water level increases or decreases on phytoplankton or cyanobacteria. We found that water level decreases resulted in a higher likelihood of increased cyanobacteria, and that phytoplankton were more likely to decrease in response to water level increases. Most of the waterbodies included in the literature review were eutrophic or hypereutrophic, underscoring the need to explore the effects of water level fluctuations on oligotrophic systems. We only identified five studies on E. coli through our review, and no studies on Naegleria spp. We supplemented our review with regional white papers and case studies within the Colorado River Basin and the Rio Grande River Basin to highlight relevant research. Prior and ongoing research highlights the need to explore impacts of water level fluctuations on phytoplankton and cyanobacteria to guide future management decision-making.

Arizona, Utah, Nevada↗
USGS2021

Climate change risks and adaptation options for Madagascar

Climate change poses an increasing threat to achieving development goals and is often considered in development plans and project designs. However, there have been challenges in the effective implementation of those plans, particularly in the sustained engagement of the communities to undertake adaptive actions, but also due to insufficient scientific information to inform management decisions. Madagascar is a country rich in natural capital and biodiversity but with high levels of poverty, food insecurity, population growth, and exploitation of natural resources. The country faces development and environmental challenges that may be intensified by climate change. The objective of this review is to provide a synthesis of the best-available information regarding climate change impacts on sectoral interests in Madagascar. To do this, we conducted a review of recent literature and conducted formal discussions with development agencies, non-government organizations (NGOs), and other stakeholders. Climate risks in Madagascar include increasing temperatures, reduced and more variable precipitation, more frequent droughts, more intense cyclones, and rising sea levels. We synthesized the observed and projected impacts of climate change on water resources, agriculture, human health, coastal ecosystems, fisheries, and terrestrial ecosystems and ecosystem services, and we discuss ongoing climate adaptation and mitigation activities. Because sectoral challenges and opportunities are linked, coordination among development organizations would be beneficial as they create new climate adaptation and mitigation initiatives.

Ecology and Society↗
USGS2025

Modeling climate and hydropower influences on the movement decisions of an anadromous species

In large river basins, migratory fish populations are threatened by the combination of hydropower and climate change. With river temperatures rising and hydropower development increasing globally, the longstanding monitoring programs for threatened Pacific salmon populations in the Columbia River Basin present an opportunity to study these impacts over extended time scales. We fit a statistical model to 20 years of PIT-tagging data to jointly model the effects of temperature and dam operations (spill management) on the movement of Steelhead (anadromous Oncorhynchus mykiss ) during their adult pre-spawn migration. We modeled the relationship between these factors and behaviors that pose mortality risks, including natal tributary overshoot (ascending a dam upstream of a natal tributary) and non-natal tributary use. We then used the posterior distributions of model-estimated parameters to predict the homing success of fish to natal tributaries under different climate and hydropower scenarios. Across the populations in our study, movement decisions were consistently thermally influenced, with temperature having a negative relationship with natal homing and a positive relationship with both natal tributary overshoot and non-natal tributary use. Another consistent finding across the populations in our study was that higher overshoot rates were associated with lower homing rates. Despite data limitations associated with the PIT-tag array network, we found evidence for population-specific benefits of winter spill on natal homing success, which is currently being implemented to assist the downstream migration of overshooting Steelhead. We demonstrate how integrating the effects of climate and hydropower management actions with movement ecology provides powerful insights into how species may respond to future scenarios. In our case study, we found that pre-spawn mortality of Steelhead is likely to increase with future climate change due to temperature-driven interactions with the hydrosystem, but there is potential for hydropower managers to partially offset these impacts.

Idaho, Montana, Oregon, Washington↗
USGS2024

Approaches for using CMIP projections in climate model ensembles to address the ‘hot model’ problem

Several recent generation global-climate models were found to have anomalously high climate sensitivities and may not be useful for certain applications. Four approaches for developing ensembles of climate projections for applications that address this issue are: Using an “all models” approach; Screening using equilibrium climate sensitivity and (or) transient climate response; Bayesian model averaging; and Using global warming levels. Advantages and disadvantages of each approach are described by using example applications to study the effects of climate change on an imaginary at-risk species. Choosing the right approach is dependent on the location, goals, and system focus of each application and the risk-tolerance and resource-management context.

Open-File Report↗