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At least 613 records · Page 34Linked to original sources
USGS2010

A spatial regression procedure for evaluating the relationship between AVHRR-NDVI and climate in the northern Great Plains

The relationship between vegetation and climate in the grassland and cropland of the northern US Great Plains was investigated with Normalized Difference Vegetation Index (NDVI) (1989–1993) images derived from the Advanced Very High Resolution Radiometer (AVHRR), and climate data from automated weather stations. The relationship was quantified using a spatial regression technique that adjusts for spatial autocorrelation inherent in these data. Conventional regression techniques used frequently in previous studies are not adequate, because they are based on the assumption of independent observations. Six climate variables during the growing season; precipitation, potential evapotranspiration, daily maximum and minimum air temperature, soil temperature, solar irradiation were regressed on NDVI derived from a 10-km weather station buffer. The regression model identified precipitation and potential evapotranspiration as the most significant climatic variables, indicating that the water balance is the most important factor controlling vegetation condition at an annual timescale. The model indicates that 46% and 24% of variation in NDVI is accounted for by climate in grassland and cropland, respectively, indicating that grassland vegetation has a more pronounced response to climate variation than cropland. Other factors contributing to NDVI variation include environmental factors (soil, groundwater and terrain), human manipulation of crops, and sensor variation.

International Journal of Remote Sensing↗
USGS2013

Effects of climate change and urban development on the distribution and conservation of vegetation in a Mediterranean type ecosystem

Climate and land-use changes are projected to threaten biodiversity over this century. However, few studies have considered the spatial and temporal overlap of these threats to evaluate how ongoing land-use change could affect species ranges projected to shift outside conservation areas. We evaluated climate change and urban development effects on vegetation distribution in the Southwest ecoregion, California Floristic Province, USA. We also evaluated how well a conservation network protects suitable habitat for rare plant species under these change projections and identified primary sources of uncertainty. We used consensus-based maps from three species distribution models (SDMs) to project current and future suitable habitat for 19 species representing different functional types (defined by fire-response – obligate seeders, resprouting shrubs – and life forms – herbs, subshrubs), and range sizes (large/common, small/rare). We used one spatially explicit urban growth projection; two climate models, emission scenarios, and probability thresholds applied to SDMs; and high-resolution (90 m) environmental data. We projected that suitable habitat could disappear for 4 species and decrease for 15 by 2080. Averaged centroids of suitable habitat (all species) were projected to shift tens (up to hundreds) of kilometers. Herbs showed a small-projected response to climate change, while obligate seeders could suffer the greatest losses. Several rare species could lose suitable habitat inside conservation areas while increasing area outside. We concluded that (i) climate change is more important than urban development for vegetation habitat loss in this ecoregion through 2080 due to diminishing amounts of undeveloped private land in this region; (ii) the existing conservation plan, while extensive, may be inadequate to protect plant diversity under projected patterns of climate change and urban development, (iii) regional assessments of the dynamics of the drivers of biodiversity change based on high-resolution environmental data and consensus predictive mapping, such as this study, are necessary to identify the species expected to be the most vulnerable and to meaningfully inform regional-scale conservation.

California↗
USGS2020

Climate has contrasting direct and indirect effects on armed conflicts

There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a structural equation modeling approach to uncover the direct and indirect effects of climate on violent conflicts in Africa and the Middle East (ME). We show that climate–conflict linkages in these regions are more complex than previously suggested, with multiple mechanisms at work. Warm temperatures and low rainfall direct effects on conflict risk were stronger than indirect effects through food and water supplies. Warming increases the risk of violence in Africa but unexpectedly decreases this risk in the ME. Furthermore, at the country level, warming decreases the risk of violence in most West African countries. Overall, we find a non-linear response of conflict to warming across countries that depends on the local temperature conditions. We further show that magnitude and sign of the effects largely depend on the scale of analysis and geographical context. These results imply that extreme caution should be exerted when attempting to explain or project local climate–conflict relationships based on a single, generalized theory.

Environmental Research Letters↗
USGS2021

Hibernation behavior of a federally-threatened ground squirrel: Climate change and habitat selection implications

Hibernation is an adaptation to survive periods of stress, from food limitation or harsh thermal conditions. A key question in contemporary ecology is whether rare, range-restricted species can change their behavior in response to climate change (i.e., through behavioral plasticity). The northern Idaho ground squirrel, Urocitellus brunneus (A. H. Howell, 1928), is a federally threatened species that hibernates for approximately 8 months per year within the bounds of its small range in central Idaho, USA. Changes in temperature, snow accumulation, and summer precipitation, all brought about as a result of climate change, may reduce survival or fecundity of northern Idaho ground squirrels if they cannot adapt to these climate changes. Hibernating species can respond to climate-change-induced thermal challenges in two ways: change their hibernation physiology and behavior (i.e., emergence date or number of torpor bouts) or alter their environment (i.e., change hibernacula depth or location). We explored a suite of intrinsic and extrinsic factors to document the extent to which they influenced hibernation behavior of northern Idaho ground squirrels. Emergence date was positively associated with snowpack and negatively associated with mean winter temperature. Mean minimum skin temperature was negatively associated with canopy closure and slope of a squirrel’s hibernaculum. Duration of the heterothermal period, number of euthermic bouts, and total time spent euthermic were positively associated with body mass. Immergence date and duration of the longest torpor bout were negatively associated with body mass. Warmer temperatures and less snow accumulation in the winter—caused by climate change—likely will cause altered emergence dates. Our results suggest that any future climate-induced changes in snowfall, ambient temperature, food availability, or habitat likely will impact survival of this rare ground squirrel, because such changes will cause changes in hibernation behavior, percent mass loss during hibernation, and duration of the active season when small mammals are more susceptible to predation.

Idaho↗
USGS2018

Intraspecific niche models for ponderosa pine (Pinus ponderosa) suggest potential variability in population-level response to climate change

Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine ( Pinus ponderosa ), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum ) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.

Systematic Biology↗
USGS2016

Climate, invasive species and land use drive population dynamics of a cold-water specialist

Climate change is an additional stressor in a complex suite of threats facing freshwater biodiversity, particularly for cold-water fishes. Research addressing the consequences of climate change on cold-water fish has generally focused on temperature limits defining spatial distributions, largely ignoring how climatic variation influences population dynamics in the context of other existing stressors. We used long-term data from 92 populations of bull trout Salvelinus confluentus – one of North America's most cold-adapted fishes – to quantify additive and interactive effects of climate, invasive species and land use on population dynamics (abundance, variability and growth rate). Populations were generally depressed, more variable and declining where spawning and rearing stream habitat was limited, invasive species and land use were prevalent and stream temperatures were highest. Increasing stream temperature acted additively and independently, whereas land use and invasive species had additive and interactive effects (i.e. the impact of one stressor depended on exposure to the other stressor). Most (58%–78%) of the explained variation in population dynamics was attributed to the presence of invasive species, differences in life history and management actions in foraging habitats in rivers, lakes and reservoirs. Although invasive fishes had strong negative effects on populations in foraging habitats, proactive control programmes appeared to effectively temper their negative impact. Synthesis and applications . Long-term demographic data emphasize that climate warming will exacerbate imperilment of cold-water specialists like bull trout, yet other stressors – especially invasive fishes – are immediate threats that can be addressed by proactive management actions. Therefore, climate-adaptation strategies for freshwater biodiversity should consider existing abiotic and biotic stressors, some of which provide potential and realized opportunity for conservation of freshwater biodiversity in a warming world.

Journal of Applied Ecology↗
USGS2015

Long-term plant responses to climate are moderated by biophysical attributes in a North American desert

Recent elevated temperatures and prolonged droughts in many already water-limited regions throughout the world, including the southwestern U.S., are likely to intensify according to future climate-model projections. This warming and drying can negatively affect perennial vegetation and lead to the degradation of ecosystem properties. To better understand these detrimental effects, we formulate a conceptual model of dryland ecosystem vulnerability to climate change that integrates hypotheses on how plant species will respond to increases in temperature and drought, including how plant responses to climate are modified by landscape, soil, and plant attributes that are integral to water availability and use. We test the model through a synthesis of fifty years of repeat measurements of perennial plant species cover in large permanent plots across the Mojave Desert, one of the most water-limited ecosystems in North America. Plant species ranged in their sensitivity to precipitation in different seasons, capacity to increase in cover with high precipitation, and resistance to decrease in cover with low precipitation. Our model successfully explains how plant responses to climate are modified by biophysical attributes in the Mojave Desert. For example, deep-rooted plants were not as vulnerable to drought on soils that allowed for deep water percolation, whereas shallow-rooted plants were better buffered from drought on soils that promoted water retention near the surface. Synthesis. Our results emphasize the importance of understanding climate-vegetation relationships in the context of biophysical attributes that influence water availability and provide an important forecast of climate-change effects, including plant mortality and land degradation in dryland regions throughout the world.

California, Nevada↗
USGS2022

What common-garden experiments tell us about climate responses in plants

Common garden experiments are indoor or outdoor plantings of species or populations collected from multiple distinct geographic locations, grown together under shared conditions. These experiments examine a range of questions for theory and application using a variety of methods for analysis. The eight papers of this special feature comprise a cross section of contemporary approaches, summarized and synthesized here by what they tell us about the relationships between climate-related trait spectra and fitness optima. Four of the eight papers are based on field experiments in prairie, desert, Mediterranean and boreal biomes. Representative of many common garden experiments, these experiments reveal consistent evidence of traits varying with population climate provenance, but evidence of a tradeoff between growth and tolerance traits or of consistent fitness optimization at home is scant, in contrast to trait theory. Two synthesis papers highlight dominant patterns of trait divergence, including for an exotic invasive species. One theoretical paper warned that unknown kinship relationships between populations can result in the misidentification of adaptive trait divergence. A third synthesis paper formulated novel and ambitious goals for common-garden studies through including measurement of response variables at multiple levels of biological organization. The featured papers discuss multiple avenues for improving common garden studies. Genomic analysis, together with the quantification of kinship relationships, will continue to reveal the influence of environmental drivers on gene selection. Measuring a more complete set of fitness traits, especially for traits related to regeneration, will permit the development of projection models to explicitly link trait spectra, climate patterns and fitness consequences. More standardized data reporting will additionally improve abilities to synthesize findings across experiments. Testing population performance in competition with other species will produce more robust fitness comparisons between genotypes, especially for slower-growing genotypes in higher-resource environments. Adding gardens in and beyond climatic edge locations will furthermore strengthen the understanding of population failure and species exclusion. Finally, there is unrealized potential in adding ecosystem-level observations to common-garden studies that will enhance integrative analysis across scales of biological organization and scientific domains. Synthesis . With novel, creative designs, data integration and synthesis, common garden experiments will continue to advance the understanding of trait ensembles interacting with climate across scales of biological organization, provide pivotal data for global change models and guide ecological applications such as restoration of habitats for rare and climate sensitive species.

Journal of Ecology↗
USGS2022

Mechanisms controlling climate warming impact on the occurrence of hypoxia in Chesapeake Bay

A Climate change represents an increasing stressor on estuarine and coastal ecosystems. A series of simulations were run using the Integrated Compartment Water Quality Model to determine the magnitude of various mechanisms controlling the effect of climate warming on dissolved oxygen (DO) in the Chesapeake Bay. The results suggested that the average hypoxic volume in the summer would increase by 9% (410 Mm 3 ) from 1995 to 2025 as air temperature increases by 1.06°C and water temperature by 0.9°C. The change in DO solubility contributes 55% of the total climate warming effect, biological rates 33%, and stratification 11%. The Rappahannock Shoal, a hydraulic control point, plays a major role in determining the effect of climate warming on DO in the Bay. Due to the abrupt change in bathymetry, the convergence between seaward-moving freshwater and landward-moving saltwater causes downwelling and enhanced vertical mixing which introduces surface water of higher temperature to the deep channel and accelerates organic matter remineralization and oxygen consumption in deep waters. Surface water DO concentrations will decrease under climate warming conditions due to lower DO solubility, reducing DO flux to the deep channel and contributing to hypoxia development. These findings provide critical information for future management decision making regarding the effects of climate warming on DO in Chesapeake Bay and other estuaries.

Maryland, Virginia↗
USGS2018

Hydrological regime and climate interactively shape riparian vegetation composition along the Colorado River, Grand Canyon

Question How closely do riparian plant communities track hydrological and climatic variation in space, and how do interactions among hydrological and climatic filters influence success of flow management strategies? Location Grand Canyon, Arizona, USA. Methods Multi‐year vegetation surveys were conducted across three hydrological zones – active channel, active floodplain and inactive floodplain – within each of 42 sandbars that vary geographically in temperature and precipitation along a 400‐km river segment. Ecological niche models were used to estimate locally optimal conditions of maximum inundation duration, elevation above daily peak flow, mean annual precipitation, and mean maximum and minimum temperature for 16 of the most abundant woody and 58 most abundant herbaceous plant species. These estimates were used to calculate community‐weighted mean (CWM) environmental preferences, which were used to determine how closely vegetation preferences tracked local variation in environmental factors, and to assess interactive responses of species and communities to variation in hydrology and climate. Results Communities closely tracked hydrological variation across zones, but less so within zones. Communities tracked variation in minimum temperature more closely than maximum temperature or precipitation. At the species level, woody plants that were more abundant in wetter hydrological conditions were also more abundant in wetter climatic conditions, and vice versa. This relationship was even stronger at the community level, where there were significant negative relationships between CWM preferences of inundation duration and temperature for both woody and herbaceous vegetation. Conclusions The climate‐hydrology linkages found in this system suggest that increasing temperatures and drought are likely to reduce the inundation tolerance of riparian vegetation within the Grand Canyon. Increasing the duration of high flow events would likely reduce the abundance of encroaching woody vegetation, but could also reduce the resilience of remaining vegetation to heat waves and drought. The reinforcing effects of climatic and hydrological filters are likely to generally result in greater sensitivity of species composition to environmental change than if those environmental filters acted independently. These results have implications for predicting resource responses to environmental change, as well as prescriptions for direct vegetation management to enhance resilience.

Colorado River, Grand Canyon↗
USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗
USGS2021

Toward climate change refugia conservation at an ecoregion scale

Climate change uncertainty poses serious challenges to conservation efforts. One emerging conservation strategy is to identify and conserve climate change refugia: areas relatively buffered from contemporary climate change that enable persistence of valued resources. This management paradigm may be pursued at broad scales by leveraging existing resources and placing them into a tangible framework to stimulate further collaboration that fosters management decision-making. Here, we describe a framework for moving toward operationalizing climate change refugia conservation at an ecoregion scale with an analysis for the Sierra Nevada ecoregion (CA, USA). Structured within the Climate Change Refugia Conservation Cycle, we identify a preliminary suite of conservation priorities for the ecoregion, and demonstrate how existing mapping, data, and applications could be used for identifying, prioritizing, managing, and monitoring refugia. We focus on six stakeholder-identified conservation priorities, including two process-based refugial priorities (snow and fire), and four ecosystem-based refugial priorities (meadows, giant sequoia, old growth forests, and alpine communities). This pilot overview of concepts and resources provides a foundation for both near-term implementation and further discussion in moving from science to conservation practice. Such an approach may provide new practical insights for ecosystem management at ecoregion scales in the face of climate change.

California↗
USGS2025

Integrating refugia modeling and decision science to support climate-adaptive conservation in the Sierra Nevada

To reduce detrimental impacts of anthropogenic change, natural resource managers often look for place-based solutions to minimize biodiversity loss. Climate-change refugia, areas buffered from contemporary climate change, can enable the persistence of valued natural resources and prolong the benefits of conservation action. Here we combine climate-change refugia modeling with structured decision-making to inform conservation decisions for the endangered foothill yellow-legged frog ( Rana boylii ) in the Sierra Nevada region of California, USA. We used an ensemble of species distribution models to identify areas projected to remain suitable into the 2040s and the 2080s under an RCP 8.5 emissions scenario, as well as areas projected to transition to suitable habitat during this time. We integrated these projections with a structured decision-making process to align management strategies with refugia model outcomes for R. boylii in a subset of the study area. Habitat suitability for R. boylii is projected to decline in the study area by over 90% by the 2040s and by a subsequent 15% by the 2080s. Climate-change refugia are projected to occupy ~7% of present-day suitable habitat, with high agreement between GCMs and model timesteps. Areas projected to transition to suitable habitat within the existing R. boylii clade boundaries are negligible. Collectively, climate-change refugia modeling and structured decision-making provide opportunities to improve resource allocation and empower conservation practitioners in climate change adaptation for at-risk species.

California↗
USGS2023

Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance habitats

Aim Preventing the spread of range-shifting invasive species is a top priority for mitigating the impacts of climate change. Invasive plants become abundant and cause negative impacts in only a fraction of their introduced ranges, yet projections of invasion risk are almost exclusively derived from models built using all non-native occurrences and neglect abundance information. Location Eastern USA. Methods We compiled abundance records for 144 invasive plant species from five major growth forms. We fit over 600 species distribution models based on occurrences of abundant plant populations, thus projecting which areas in the eastern United States (U.S.) will be most susceptible to invasion under current and +2°C climate change. Results We identified current invasive plant hotspots in the Great Lakes region, mid-Atlantic region, and along the northeast coast of Florida and Georgia, each climatically suitable for abundant populations of over 30 invasive plant species. Under a +2°C climate change scenario, hotspots will shift an average of 213 km, predominantly towards the northeast U.S., where some areas are projected to become suitable for up to 21 new invasive plant species. Range shifting species could exacerbate impacts of up to 40 invasive species projected to sustain populations within existing hotspots. On the other hand, within the eastern U.S., 62% of species will experience decreased suitability for abundant populations with climate change. This trend is consistent across five plant growth forms. Main Conclusions We produced species range maps and state-specific watch lists from these analyses, which can inform proactive regulation, monitoring, and management of invasive plants most likely to cause future ecological impacts. Additionally, areas we identify as becoming less suitable for abundant populations could be prioritized for restoration of climate-adapted native species. This research provides a first comprehensive assessment of risk from abundant plant invasions across the eastern U.S.

Diversity and Distributions↗
USGS2018

Ecological genomics predicts climate vulnerability in an endangered southwestern songbird

Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher ( Empidonax traillii ), and find the endangered desert southwestern subspecies ( E. t. extimus ) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability – the mismatch between current and predicted future genotype–environment relationships – indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate‐associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype–environment relationships into landscape‐scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups.

Ecology Letters↗
USGS2019

The Laurentian Great Lakes: A case study in ecological disturbance and climate change

Climate change effects are already significant, but can also magnify other ecological problems. This can be clearly seen in the Laurentian Great Lakes, which have suffered habitat degradation, fishery overharvest and dramatic alterations by invasive species. Thermal changes are expected to cause extensive loss of suitable fish habitat, and changing precipitation patterns will aggravate the problems with our highly modified lotic and lentic systems. A brief summary of the historic ecological context provided by the Great Lakes case is presented, followed by the descriptions of selected tools that help to understand and evaluate both ecological and climate change problems. Species distribution models and habitat classification combined with climate change predictions can identify the distribution and extent of optimal habitats, and identify which are most vulnerable to climate change. Ecological flow modelling can help to identify when critical flow changes are likely. Mechanistic simulation modelling specifies understanding of how aquatic systems function and can reveal cause and effect relationships. These tools can be used to help managers to protect optimal habitat, resist climate change effects to other habitats and adapt cultural systems to climate‐altered aquatic systems.

Great Lakes↗
USGS2013

Winter climate change and coastal wetland foundation species: Salt marshes vs. mangrove forests in the southeastern United States

We live in an era of unprecedented ecological change in which ecologists and natural resource managers are increasingly challenged to anticipate and prepare for the ecological effects of future global change. In this study, we investigated the potential effect of winter climate change upon salt marsh and mangrove forest foundation species in the southeastern United States. Our research addresses the following three questions: (1) What is the relationship between winter climate and the presence and abundance of mangrove forests relative to salt marshes; (2) How vulnerable are salt marshes to winter climate change-induced mangrove forest range expansion; and (3) What is the potential future distribution and relative abundance of mangrove forests under alternative winter climate change scenarios? We developed simple winter climate-based models to predict mangrove forest distribution and relative abundance using observed winter temperature data (1970–2000) and mangrove forest and salt marsh habitat data. Our results identify winter climate thresholds for salt marsh–mangrove forest interactions and highlight coastal areas in the southeastern United States (e.g., Texas, Louisiana, and parts of Florida) where relatively small changes in the intensity and frequency of extreme winter events could cause relatively dramatic landscape-scale ecosystem structural and functional change in the form of poleward mangrove forest migration and salt marsh displacement. The ecological implications of these marsh-to-mangrove forest conversions are poorly understood, but would likely include changes for associated fish and wildlife populations and for the supply of some ecosystem goods and services.

Global Change Biology↗
USGS2013

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site-specific frequency distributions of occurrence probabilities across a species’ range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.

Idaho;Montana↗