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At least 1,117 records · Page 62Linked to original sources
USGS2014

Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

Open-File Report↗
USGS2024

Asymmetric mate preference and reproductive interference mediate climate-induced changes in mate availability in a small mammal hybrid zone

Range expansion and contraction are among the most common biotic responses to changing environmental conditions, yet much is to be learned about the mechanisms that underlie range-edge population dynamics, especially when those areas are points of secondary contact between closely related species. Here, we present field-measured parentage data that document the reproductive outcomes of changes in mate availability at a secondary contact zone between two species of woodrat in the genus Neotoma . Changes in mate availability resulted from drought-driven differential survival between the species and their hybrids. As the availability of conspecifc mates declined, rates of hybridization increased, leading to the accumulation of admixed individuals in the zone of contact. Patterns of reproductive success in the wild appear to be the result of a combination of both pre-mating isolation and post-zygotic selection resulting from genomic incompatibilities between the parental lineages. Evidence of asymmetric mate preference between the parental lineages came from both skewed reproductive output in the field and laboratory preference trials. Moreover, partial genomic incompatibility was evident from the near-zero reproductive success of F1 males and because nearly all surviving hybrids had one pure parent. Nonetheless, the high reproductive success of F1 females and backcrossing in both parental directions allow for introgression between the parental species. These findings reveal how climate change may alter evolutionary outcomes for species at the edge of their ranges through an interplay of behavioral, demographic, and genetic mechanisms.

California↗
USGS2026

Alternative future vegetation pathways reveal potential transformations of western US ecosystems

Managing ecosystems in an era of rapid change is inherently challenging not only because of uncertainty in future climate but also due to diverse responses of ecosystems to climate. Projections of ecological transformation alongside information about plausible vegetation trajectories can help land managers explore divergent scenarios and consider how modeled outcomes match their observations. Climate-analog impact models (AIMs) compare environmental information (e.g., vegetation types) between sets of climatically similar locations to infer change and can be used to identify multiple outcomes. We used AIMs to project changes in vegetation across the western United States under a mid-21st century climate scenario, characterize ecological transformation vulnerability based on projection divergence, and demonstrate how AIMs can inform decision-making. We projected high or very high vulnerability to ecological transformation across 29% of the western US, nearly 1 M km 2 . Vulnerability varied among vegetation groups; 75% of alpine vegetation had high or very high vulnerability vs. 6% of desert scrub. We estimate that 9% of the study area faces a high likelihood of transformation based on combined measures of vulnerability and projection agreement. Transformation at the vegetation type ( n = 50) level is projected for 40% (1.4 M km 2 ) of the study area, based on primary projections. As vegetation shifts towards types supported by a more arid climate, forested area is expected to contract by 9% and subalpine forests specifically by 54%. Elsewhere, vulnerability is low or trajectories are uncertain, implying opportunities for managers to intervene. Dry forests, for example, could be stabilized through vegetation management and intentional fire use. Our findings suggest likely ecological transformations with significant downstream consequences for ecosystem services and natural resources. They are best used within decision-making frameworks that draw on multiple lines of evidence including local expertise and complementary knowledge systems.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2021

Linking climate niches across seasons to assess population vulnerability in a migratory bird

Global loss of biodiversity has placed new urgency on the need to understand factors regulating species response to rapid environmental change. While specialists are often less resilient to rapid environmental change than generalists, species-level analyses may obscure the extent of specialization when locally adapted populations vary in climate tolerances. Until recently, quantification of the degree of climate specialization in migratory birds below the species level was hindered by a lack of genomic and tracking information, but recent technological advances have helped to overcome these barriers. Here we take a genome-wide genetic approach to mapping population-specific migratory routes and quantifying niche breadth within genetically distinct populations of a migratory bird, the willow flycatcher ( Empidonax traillii ), which exhibits variation in the severity of population declines across its breeding range. While our sample size is restricted to the number of genetically distinct populations within the species, our results support the idea that locally adapted populations of the willow flycatcher with narrow climatic niches across seasons are already federally listed as endangered or in steep decline, while populations with broader climatic niches have remained stable in recent decades. Overall, this work highlights the value of quantifying niche breadth within genetically distinct groups across time and space when attempting to understand the factors that facilitate or constrain the response of locally adapted populations to rapid environmental change.

Global Change Biology↗
USGS2019

Remote sensing of dryland ecosystem structure and function: Progress, challenges, and opportunities

Drylands make up roughly 40% of the Earth's land surface, and billions of people depend on services provided by these critically important ecosystems. Despite their relatively sparse vegetation, dryland ecosystems are structurally and functionally diverse, and emerging evidence suggests that these ecosystems play a dominant role in the trend and variability of the terrestrial carbon sink. More, drylands are highly sensitive to climate and are likely to have large, non-linear responses to hydroclimatic change. Monitoring the spatiotemporal dynamics of dryland ecosystem structure (e.g., leaf area index) and function (e.g., primary production and evapotranspiration) is therefore a high research priority. Yet, dryland remote sensing is defined by unique challenges not typically encountered in mesic or humid regions. Major challenges include low vegetation signal-to-noise ratios, high soil background reflectance, presence of photosynthetic soils (i.e., biological soil crusts), high spatial heterogeneity from plot to regional scales, and irregular growing seasons due to unpredictable seasonal rainfall and frequent periods of drought. Additionally, there is a relative paucity of continuous, long-term measurements in drylands, which impedes robust calibration and evaluation of remotely-sensed dryland data products. Due to these issues, remote sensing techniques developed in other ecosystems or for global application often result in inaccurate, poorly constrained estimates of dryland ecosystem structural and functional dynamics. Here, we review past achievements and current progress in remote sensing of dryland ecosystems, including a detailed discussion of the major challenges associated with remote sensing of key dryland structural and functional dynamics. We then identify strategies aimed at leveraging new and emerging opportunities in remote sensing to overcome previous challenges and more accurately contextualize drylands within the broader Earth system. Specifically, we recommend: 1) Exploring novel combinations of sensors and techniques (e.g., solar-induced fluorescence, thermal, microwave, hyperspectral, and LiDAR) across a range of spatiotemporal scales to gain new insights into dryland structural and functional dynamics; 2) utilizing near-continuous observations from new-and-improved geostationary satellites to capture the rapid responses of dryland ecosystems to diurnal variation in water stress; 3) expanding ground observational networks to better represent the heterogeneity of dryland systems and enable robust calibration and evaluation; 4) developing algorithms that are specifically tuned to dryland ecosystems by utilizing expanded ground observational network data; and 5) coupling remote sensing observations with process-based models using data assimilation to improve mechanistic understanding of dryland ecosystem dynamics and to better constrain ecological forecasts and long-term projections.

Remote Sensing of Environment↗
USGS2016

A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example

In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon ( Scaphirhynchus albus ) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.

Missouri River↗
USGS2023

Northwest Forest Plan — The first 25 years (1994–2018): Watershed condition status and trends

This report describes status and trends in watershed condition across the Northwest Forest Plan (NWFP) area over the first 25 years since its inception in 1994. The program charged with this task is the Aquatic and Riparian Effectiveness Monitoring Program (AREMP), which has assembled information from field data collection, spatial datasets, and a host of landscape models to evaluate the status and trends in aquatic resources in streams and watersheds. Field data included hydrologic measurements (stream wetted widths and temperatures), geomorphic responses (instream wood and sediment), and biological responses (macroinvertebrates and aquatic organism passage). Novel statistical models were used to estimate trends in these measured responses. A suite of complementary modeled results was also employed to describe hydrometeorological drivers (e.g., drought indices and stream discharge), forest cover (upslope and riparian vegetation), and geomorphic conditions (e.g., road-related estimates of chronic and shallow landslide sediment delivery risk). Collectively, information on these responses allowed us to rigorously evaluate instream responses and hypothesize watershed drivers of those responses across the NWFP area and over time. The majority of responses we observed indicated widespread and incremental improvements from active management of forests, forest roads, and road-stream crossings as envisioned by the aquatic conservation strategy of the NWFP. Additionally, many of the responses we observed were consistent with those expected under the influences of changing climates in the Pacific Northwest. Ultimately, the long-term, broad-scale information provided by AREMP is a critical foundation for evaluating the effectiveness of federal land management and the effects of changing climates on water resources that sustain the Pacific Northwest’s human and natural landscapes.

California, Oregon, Washington↗
USGS1997

Using remote sensing to monitor global change

To properly respond to natural and human-induced stresses to wetlands, resource managers must consider their functions and values. Remote sensing is an important tool for monitoring wetland responses to changes in the hydrologic regime and water quality caused by global climate change and sea-level rise.

St. Marks National Wildlife Refuge↗
USGS2021

USGS Chesapeake Science Strategy 2021-2025

The Chesapeake Bay ecosystem is a national treasure that provides almost $100 billion annually of goods and services. The Chesapeake Bay Program (CBP), is one of the largest federal-state restoration partnerships in the United States and is underpinned by rigorous science. The U.S. Geological Survey (USGS) has a pivotal role as a science provider for assessing ecosystem condition and response in the Chesapeake watershed. Despite significant CBP accomplishments, the pressures of climate change and competing demands on land use and change require an acceleration of progress towards the 10 goals in the Chesapeake Bay Watershed Agreement. USGS Chesapeake studies are increasing efforts to provide integrated science and are engaging stakeholders to inform the multi-faceted restoration and conservation decisions to improve habitat for fish and waterfowl, and socio-economic benefits to the 18 million people living in the watershed.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2023

Seasonal abundance and habitat associations of American Kestrels on the Southern High Plains of Texas

American Kestrel ( Falco sparverius ) populations are generally declining across the species' North American distribution but the population in the Southern High Plains region currently appears to be stable. Historical evidence suggests the region formerly had a low abundance of kestrels, and that their current numbers are due to landscape changes associated with European settlement. We conducted monthly surveys for American Kestrels across 2 yr to estimate seasonal densities and identify land cover associations in the Southern High Plains of Texas. We found an overall estimated density of 0.99 birds/km 2 (95% CI = 0.406, 1.582) across the 2-yr period, with seasonal estimated densities highest in autumn and winter (0.92–2.53/ km 2 ), and lowest in spring (0.49–0.67/km 2 ). Whereas other studies have found that temperature influenced detection of wintering kestrels, we found an interaction of drought conditions and snow most strongly influenced the number of kestrels in our study area. Kestrels largely used land cover types in proportion to availability but there was some evidence of seasonal shifts. Generally, they tended to avoid cotton fields and sometimes selected for areas with woodlots, abandoned or occupied houses, and barns, all of which likely provided nesting and roosting opportunities. Our study provides the first contemporary assessment of seasonal abundance and habitat associations of American Kestrels in the Southern High Plains, where their presence and abundance has been unintentionally facilitated by landscape changes following settlement. We provide a baseline for population monitoring and studies assessing response to additional landscape changes (e.g., development of wind energy facilities) and a changing climate.

Journal of Raptor Research↗
USGS2011

Biological review of 82 species of coral petitioned to be included in the Endangered Species Act

list 83 coral species as threatened or endangered under the U.S. Endangered Species Act. The petition was based on a predicted decline in available habitat for the species, citing anthropogenic climate change and ocean acidification as the lead factors among the various stressors responsible for the potential decline. The NMFS identified 82 of the corals as candidate species, finding that the petition provided substantive information for a potential listing of these species. The NMFS established a Biological Review Team (BRT) to prepare this Status Review Report that examines the status of these 82 candidate coral species and evaluates extinction risk for each of them. This document makes no recommendations for listing, as that is a separate evaluation to be conducted by the NMFS. The BRT considered two major factors in conducting this review. The first factor was the interaction of natural phenomena and anthropogenic stressors that could potentially contribute to coral extinction. After extensive review of available scientific information, the BRT considers ocean warming, disease, and ocean acidification to be the most influential threats in posing extinction risks to the 82 candidate coral species between now and the year 2100. Threats of local origin but having widespread impact, such as sedimentation, nutrient enrichment, and fishing, were considered of medium importance in determining extinction risks. It is acknowledged that many other threats (e.g., physical damage from storms or ship groundings, invasive species or predator outbreaks, collection and trade) also negatively affect corals, often acutely and dramatically, but generally at relatively small local scales. These local threats were considered to be of limited scope and not deemed to contribute appreciably to the risk of species extinction, except in those special cases where species have restricted geographic or habitat ranges or species have already undergone precipitous population declines such that these local threats further contribute to depensatory processes that can magnify extinction risks (e.g., feedback-loops whereby individual survival decreases with smaller population size). The BRT acknowledges that local and global threats operate on different time scales and, though there is high confidence in the general progression of some key global threats, such as ocean warming and ocean acidification, there is much less certainty in the timing and spatial patterns of these threats. There is also substantial uncertainty in the abilities of the 82 candidate coral species to tolerate or adapt to each of the threats examined, as well as uncertainty in the dynamics of multiple simultaneous stresses. The BRT specifically identified increasing human population levels and the intensity of their collective human consumption as the root drivers of almost all global and local threats to coral species. In evaluating future threat impacts, the BRT attempted to project current trends, without assumptions of future policy changes or technological advances that could potentially alter the projections used in this analysis.

NOAA Technical Memorandum↗
USGS2018

Characterizing local and range wide variation in demography and adaptive capacity of a forest indicator species

The red-backed salamander ( Plethodon cinereus ) is considered an indicator of forest health. The range of the species covers much of the eastern and central US, and is often locally abundant where it occurs, primarily in deciduous forest. While there are expectations that changes in climate will result in changes in forest ecosystems, the ability of a forest indicator such as the red-backed salamanderto adapt to those changes, has not been assessed. We found that the red-backed salamander may have little adaptive capacity, but that changes in climate conditions may be buffered by salamander behavior, including its typical response to retreat underground during times of high temperature or during short-term drought. Effective conservation measures will likely need to increase the range of within-population climate tolerance in order for populations to persist locally.

Final Report↗
USGS2008

Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem

Vegetation growth and community composition in semi-arid environments is determined by water availability and carbon assimilation mechanisms specific to different plant types. Disturbance also impacts vegetation productivity and composition dependent on area affected, intensity, and frequency factors. In this study, a new spatially explicit ecosystem model is presented for the purpose of simulating vegetation cover type changes associated with fire disturbance in the northern Chihuahuan Desert region. The model is called the Landscape and Fire Simulator (LAFS) and represents physiological activity of six functional plant types incorporating site climate, fire, and seed dispersal routines for individual grid cells. We applied this model for Big Bend National Park, Texas, by assessing the impact of wildfire on the trajectory of vegetation communities over time. The model was initialized and calibrated based on landcover maps derived from Landsat-5 Thematic Mapper data acquired in 1986 and 1999 coupled with plant biomass measurements collected in the field during 2000. Initial vegetation cover change analysis from satellite data showed shrub encroachment during this time period that was captured in the simulated results. A synthetic 50-year climate record was derived from historical meteorological data to assess system response based on initial landcover conditions. This simulation showed that shrublands increased to the detriment of grass and yucca-ocotillo vegetation cover types indicating an ecosystem-level trajectory for shrub encroachment. Our analysis of simulated fires also showed that fires significantly reduced site biomass components including leaf area, stem, and seed biomass in this semi-arid ecosystem. In contrast to other landscape simulation models, this new model incorporates detailed physiological responses of functional plant types that will allow us to simulated the impact of increased atmospheric CO2 occurring with climate change coupled with fire disturbance. Simulations generated from this model are expected to be the subject of subsequent studies on landscape dynamics with specific regard to prediction of wildlife distributions associated with fire management and climate change.

Ecological Modelling↗
USGS2021

Global response of terrestrial gross primary productivity to climate extremes

Extreme climate events undoubtedly have essential impacts on ecosystem gross primary productivity (GPP), but the global spatio-temporal patterns of GPP responses to climate extremes are unclear. In this study, we analyzed the responses of GPP to temperature and precipitation extremes during historical (1901–2016) and future (2006–2100) periods using climate extreme indices (CEIs) developed by the Expert Team on Climate Change Detection and Indices. Eight temperature-related CEIs and eight precipitation-related CEIs were used for this analysis, along with three future greenhouse gas concentration trajectory scenarios generated by the IPCC: RCP 2.6, RCP 4.5, and RCP 8.5. Our results show that under RCP 4.5 and RCP 8.5, most climate extremes are increasing from the historical period into the future, indicating a warming globe with more frequent and more intense extreme climate events. But the increasing rate is only persistently enhanced with time under scenario RCP 8.5. GPP shows a continuous negative relationship with cold CEIs and positive relationship with wet CEIs from the historical period into the future. In all zonal scales, the changed magnitude of GPP responds strongly to extreme value-related temperature extremes under different scenarios. However, the precipitation-related extremes with the strongest GPP response are various in different regions. In the future, GPP is most sensitive to temperature extremes in upper northern latitudes and in high-altitude regions (e.g., Qinghai-Tibet Plateau) and to precipitation extremes in the tropical zone. This study may provide a basis for predicting how GPP responds to climate extremes and explaining the underlying changes in the carbon cycle.

Science of the Total Environment↗
USGS2008

Principal hydrologic responses to climatic and geologic variability in the Sierra Nevada, California

Sierra Nevada snowpack is a critical water source for California’s growing population and agricultural industry. However, because mountain winters and springs are warming, on average, precipitation as snowfall relative to rain is decreasing, and snowmelt is earlier. The changes are stronger at mid-elevations than at higher elevations. The result is that the water supply provided by snowpack is diminishing. In this paper, we describe principal hydrologic responses to climatic and spatial geologic variations as gleaned from a series of observations including snowpack, stream-flow, and bedrock geology. Our analysis focused on peak (maximum) and base (minimum) daily discharge of the annual snowmelt-driven hydrographs from 18 Sierra Nevada watersheds and 24 stream gage locations using standard correlation methods. Insights into the importance of the relative magnitudes of peak flow and soil water storage led us to develop a hydrologic classification of mountain watersheds based on runoff versus base flow as a percentage of peak flow. Our findings suggest that watersheds with a stronger base flow response store more soil water than watersheds with a stronger peak-flow response. Further, the influence of antecedent wet or dry years is greater in watersheds with high base flow, measured as a percentage of peak flow. The strong correlation between 1) the magnitude of peak flow, and 2) snow water equivalent can be used to predict peak flow weeks in advance. A weaker but similar correlation can be used to predict the magnitude of base flow months in advance. Most of the watersheds show a trend that peak flow is occurring earlier in the year.

California↗
USGS2016

Developing fish trophic interaction indicators of climate change for the Great Lakes

This project addressed regional climate change effects on aquatic food webs in the Great Lakes. We sought insights by examining Lake Erie as a representative system with a high level of anthropogenic impacts, strong nutrient gradients, seasonal hypoxia, and spatial overlap of cold- and cool-water fish guilds. In Lake Erie and in large embayments throughout the Great Lakes basin, this situation is a concern for fishery managers, as climate change may exacerbate hypoxia and reduce habitat volume for some species. We examined fish community composition, fine-scale distribution, prey availability, diets, and biochemical tracers for dominant fishes from study areas with medium-high nutrient levels (mesotrophic, Fairport study area), and low nutrient levels (oligotrophic, Erie study area). This multi-year database (2011-2013) provides the ability to contrast years with wide variation in rainfall, winter ice-cover, and thermal stratification. In addition, multiple indicators of dietary and distributional responses to environmental variability will allow resource managers to select the most informative approach for addressing specific climate change questions. Our results support the incorporation of some relatively simple and cost-efficient approaches into existing agency monitoring programs to track the near-term condition status of fish and fish community composition by functional groupings. Other metrics appear better suited for understanding longer-term changes, and may take more resources to implement on an ongoing basis. Although we hypothesized that dietary overlap and similarity in selected species would be sharply different during thermal stratification and hypoxic episodes, we found little evidence of this. Instead, to our surprise, this study found that fish tended to aggregate at the edges of hypoxia, highlighting potential spatial changes in catch efficiency of the fishery. This work has had several positive impacts on a wide range of resource management and stakeholder activities, most notably in Lake Erie. The results were instrumental in the development of an interim decision rule for dealing with data collected during hypoxic events to improve stock assessment of Yellow Perch. In addition, novel findings from this study regarding spatial and temporal variability in hypoxia have aided US-Environmental Protection Agency in the development of a modified sampling protocol to more accurately quantify the central basin hypoxic zone, and this directly addressed a goal of the Great Lakes Water Quality Agreement of 2012 to reduce the extent and severity of hypoxia. Finally, the study areas developed in this project formed the basis for food web sampling in the 2014 bi-national Coordinated Science and Monitoring Initiative work in Lake Erie.

Report↗
USGS2021

Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for Eleutherodactylus frogs

Conducting managed species translocations and establishing climate change refugia are adaptation strategies to cope with projected consequences of global warming, but successful implementation requires on-the-ground validation of demographic responses to transient climate conditions. Here we estimated the effect of nine abiotic and biotic factors on local occupancy and an index of abundance (few or chorus) for four amphibian species ( Eleutherodactylus wightmanae , E. brittoni , E. antillensis, and E. coqui ) in Puerto Rico, USA. We also assessed how the same factors influenced reproductive activity of E. coqui and how species responded to hurricane María (20 September 2017). As predicted, occupancy and abundance of E. wightmanae , E. brittoni and E. coqui were positively and strongly influenced by abiotic covariates (e.g., relative humidity) that characterize high elevation, mesic habitats. E. antillensis exhibited the opposite pattern, with highest probabilities (≥0.6) recorded at ≤300 m and with average relative humidity<75%. Biotic covariates (e.g., canopy cover) had a weak influence on both parameters, regardless of species. High probabilities (≥0.9) of detecting an E. coqui chorus and active nests occurred at sites experiencing average relative humidity of>80% and temperature of ≤26 °C. Moderate to high probabilities of detecting a chorus (0.4–0.7) were recorded at sites with average temperatures>26 °C, but no reproductive activity was detected, implying that monitoring abundance alone could misrepresent the capacity of a local population to sustain itself. The possibility underscores the importance of understanding the interplay between local demographic and environmental parameters in the advent of global warming to help guide monitoring and management decisions, especially for high elevation specialists. Hurricanes can inflict marked reductions in population numbers, but impacts vary by location and species. We found that the abundance (chorus) of E. antillensis and E. brittoni increased after the hurricane, but the abundance of the other two species did not differ between years. Lack of impacts was probably mediated by low structural damage to forest tracts (e.g., 9% canopy loss). Our findings help assess habitat suitability in terms of parameters that foster local population growth, which provides a basis for testing spatio-temporal predictions about demographic rates in potential climate refugia and for designing criteria to help guide managed translocations.

Puerto Rico↗
USGS2015

Scale dependence of disease impacts on quaking aspen (Populus tremuloides) mortality in the southwestern United States

Depending on how disease impacts tree exposure to risk, both the prevalence of disease and disease effects on survival may contribute to patterns of mortality risk across a species' range. Disease may accelerate tree species' declines in response to global change factors, such as drought, biotic interactions, such as competition, or functional traits, such as allometry. To assess the role of disease in mediating mortality risk in quaking aspen ( Populus tremuloides ), we developed hierarchical Bayesian models for both disease prevalence in live aspen stems and the resulting survival rates of healthy and diseased aspen near the species' southern range limit using 5088 individual trees on 281 United States Forest Service Forest Inventory and Analysis plots in the southwestern United States. We found that disease prevalence depended primarily on tree size, tree allometry, and spatial variation in precipitation, while mortality depended on tree size, allometry, competition, spatial variation in summer temperature, and both temporal and spatial variation in summer precipitation. Disease prevalence was highest in large trees with low slenderness found on dry sites. For healthy trees, mortality decreased with diameter, slenderness, and temporal variation in summer precipitation, but increased with competition and spatial variation in summer temperature. Mortality of diseased trees decreased with diameter and aspen relative basal area and increased with mean summer temperature and precipitation. Disease infection increased aspen mortality, especially in trees of intermediate size and trees on plots at climatic extremes (i.e., cool, wet and warm, dry climates). By examining variation in disease prevalence, mortality of healthy trees, and mortality of diseased trees, we showed that the role of disease in aspen tree mortality depended on the scale of inference. For variation among individuals in diameter, disease tended to expose intermediate-size trees experiencing moderate risk to greater risk. For spatial variation in summer temperature, disease exposed lower risk populations to greater mortality probabilities, but the magnitude of this exposure depended on summer precipitation. Furthermore, the importance of diameter and slenderness in mediating responses to climate supports the increasing emphasis on trait variation in studies of ecological responses to global change.

Ecology, Evolution, and Systematics↗