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At least 307 records · Page 17Linked to original sources

USGS2019

Global change-driven use of onshore habitat impacts polar bear faecal microbiota

The gut microbiota plays a critical role in host health, yet remains poorly studied in wild species. Polar bears (Ursus maritimus), key indicators of Arctic ecosystem health and environmental change, are currently affected by rapid shifts in habitat that may alter gut homeostasis. Declining sea ice has led to a divide in the southern Beaufort Sea polar bear subpopulation such that an increasing proportion of individuals now inhabit onshore coastal regions during the open-water period (‘onshore bears’) while others continue to exhibit their typical behaviour of remaining on the ice (‘offshore bears’). We propose that bears that have altered their habitat selection in response to climate change will exhibit a distinct gut microbiota diversity and composition, which may ultimately have important consequences for their health. Here, we perform the first assessment of abundance and diversity in the faecal microbiota of wild polar bears using 16S rRNA Illumina technology. We find that bacterial diversity is significantly higher in onshore bears compared to offshore bears. The majority of unique bacterial taxa for onshore bears belonged to the phyla Proteobacteria (a proposed indicator of poor health in adult humans), whereas for offshore bears, Firmicutes (associated with adiposity) dominated. We conclude that climate-driven changes in polar bear land use are associated with distinct microbial communities. In doing so, we present the first case of global change mediated alterations in the gut microbiota of a free-roaming wild animal.

Alaska↗

USGS2021

Influence of water temperature and biotic interactions on the distribution of westslope cutthroat trout (Oncorhynchus clarkii lewisi) in a population stronghold under climate change

Climate warming is expected to have substantial impacts on native trout across the Rocky Mountains, but there is little understanding of how these changes affect future distributions of co-occurring native fishes within population strongholds. We used mixed-effects logistic regression to investigate the role of abiotic (e.g., temperature) and biotic factors (bull trout presence, Salvelinus confluentus ) on distributions of westslope cutthroat trout ( Oncorhynchus clarkii lewisi ; WCT) in the North Fork Flathead River, USA and Canada. The probability of WCT presence increased with stream temperature and decreased with channel gradient and bull trout presence, yet the effect of bull trout was reduced with increasing pool densities. Combining this model with spatially explicit stream temperature projections, we predict a 29% increase in suitable habitat under high emissions through 2075, with gains at mid-elevation sites predicted to exceed bull trout thermal tolerances and high-elevation sites expected to become more thermally suitable for WCT. Our study illustrates the importance of considering abiotic and biotic drivers to assess species response to climate change, helping to guide local-scale climate adaptation and management.

Alberta, British Columbia, Montana↗

USGS2008

A multi-model framework for simulating wildlife population response to land-use and climate change

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Ecological Modelling↗

USGS2020

Insects in high-elevation streams: Life in extreme environments imperiled by climate change

Climate change is altering conditions in high-elevation streams worldwide, with largely unknown effects on resident communities of aquatic insects. Here, we review the challenges of climate change for high-elevation aquatic insects and how they may respond, focusing on current gaps in knowledge. Understanding current effects and predicting future impacts will depend on progress in three areas. First, we need better descriptions of the multivariate physical challenges and interactions among challenges in high-elevation streams, which include low but rising temperatures, low oxygen supply and increasing oxygen demand, high and rising exposure to ultraviolet radiation, low ionic strength, and variable but shifting flow regimes. These factors are often studied in isolation even though they covary in nature and interact in space and time. Second, we need a better mechanistic understanding of how physical conditions in streams drive the performance of individual insects. Environment-performance links are mediated by physiology and behavior, which are poorly known in high-elevation taxa. Third, we need to define the scope and importance of potential responses across levels of biological organization. Short-term responses are defined by the tolerances of individuals, their capacities to perform adequately across a range of conditions, and behaviors used to exploit local, fine-scale variation in abiotic factors. Longer term responses to climate change, however, may include individual plasticity and evolution of populations. Whether high-elevation aquatic insects can mitigate climatic risks via these pathways is largely unknown.

Global Change Biology↗

USGS2015

Testing hypotheses on distribution shifts and changes in phenology of imperfectly detectable species

With ongoing climate change, many species are expected to shift their spatial and temporal distributions. To document changes in species distribution and phenology, detection/non-detection data have proven very useful. Occupancy models provide a robust way to analyse such data, but inference is usually focused on species spatial distribution, not phenology. We present a multi-season extension of the staggered-entry occupancy model of Kendall et al . (2013, Ecology , 94, 610), which permits inference about the within-season patterns of species arrival and departure at sampling sites. The new model presented here allows investigation of species phenology and spatial distribution across years, as well as site extinction/colonization dynamics. We illustrate the model with two data sets on European migratory passerines and one data set on North American treefrogs. We show how to derive several additional phenological parameters, such as annual mean arrival and departure dates, from estimated arrival and departure probabilities. Given the extent of detection/non-detection data that are available, we believe that this modelling approach will prove very useful to further understand and predict species responses to climate change.

Methods in Ecology and Evolution↗

USGS2020

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R 2 , RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year ( p < 0.01), and harvesting dates were delayed by 0.78 days/year ( p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2012

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

Missouri River↗

USGS2013

MODIS phenology image service ArcMap toolbox

Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales. A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends. This work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.

Open-File Report↗

USGS2015

Tree mortality from drought, insects, and their interactions in a changing climate

Climate change is expected to drive increased tree mortality through drought, heat stress, and insect attacks, with manifold impacts on forest ecosystems. Yet, climate-induced tree mortality and biotic disturbance agents are largely absent from process-based ecosystem models. Using data sets from the western USA and associated studies, we present a framework for determining the relative contribution of drought stress, insect attack, and their interactions, which is critical for modeling mortality in future climates. We outline a simple approach that identifies the mechanisms associated with two guilds of insects – bark beetles and defoliators – which are responsible for substantial tree mortality. We then discuss cross-biome patterns of insect-driven tree mortality and draw upon available evidence contrasting the prevalence of insect outbreaks in temperate and tropical regions. We conclude with an overview of tools and promising avenues to address major challenges. Ultimately, a multitrophic approach that captures tree physiology, insect populations, and tree–insect interactions will better inform projections of forest ecosystem responses to climate change.

New Phytologist↗

USGS2011

Flow regime, temperature, and biotic interactions drive differential declines of trout species under climate change

Broad-scale studies of climate change effects on freshwater species have focused mainly on temperature, ignoring critical drivers such as flow regime and biotic interactions. We use downscaled outputs from general circulation models coupled with a hydrologic model to forecast the effects of altered flows and increased temperatures on four interacting species of trout across the interior western United States (1.01 million km 2 ), based on empirical statistical models built from fish surveys at 9,890 sites. Projections under the 2080s A1B emissions scenario forecast a mean 47% decline in total suitable habitat for all trout, a group of fishes of major socioeconomic and ecological significance. We project that native cutthroat trout Oncorhynchus clarkii , already excluded from much of its potential range by nonnative species, will lose a further 58% of habitat due to an increase in temperatures beyond the species' physiological optima and continued negative biotic interactions. Habitat for nonnative brook trout Salvelinus fontinalis and brown trout Salmo trutta is predicted to decline by 77% and 48%, respectively, driven by increases in temperature and winter flood frequency caused by warmer, rainier winters. Habitat for rainbow trout, Oncorhynchus mykiss , is projected to decline the least (35%) because negative temperature effects are partly offset by flow regime shifts that benefit the species. These results illustrate how drivers other than temperature influence species response to climate change. Despite some uncertainty, large declines in trout habitat are likely, but our findings point to opportunities for strategic targeting of mitigation efforts to appropriate stressors and locations.

Proceedings of the National Academy of Sciences of↗

USGS2022

Expression plasticity regulates intraspecific variation in the acclimatization potential of a reef-building coral

Phenotypic plasticity is an important ecological and evolutionary response for organisms experiencing environmental change, but the ubiquity of this capacity within coral species and across symbiont communities is unknown. We exposed ten genotypes of the reef-building coral Montipora capitata with divergent symbiont communities to four thermal pre-exposure profiles and quantified gene expression before stress testing 4 months later. Here we show two pre-exposure profiles significantly enhance thermal tolerance despite broadly different expression patterns and substantial variation in acclimatization potential based on coral genotype. There was no relationship between a genotype’s basal thermal sensitivity and ability to acquire heat tolerance, including in corals harboring naturally tolerant symbionts, which illustrates the potential for additive improvements in coral response to climate change. These results represent durable improvements from short-term stress hardening of reef-building corals and substantial cryptic complexity in the capacity for plasticity.

Nature Communications↗

USGS2017

The effect of Holocene temperature fluctuations on the evolution and ecology of Neotoma (woodrats) in Idaho and northwestern Utah

Animals respond to climatic change by adapting or by altering distributional patterns. How an animal responds is influenced by where it is positioned within its geographic range; the probability of extirpation is increased near range boundaries. Here, we examine the impact of Holocene climatic fluctuations on a small mammalian herbivore, the bushy-tailed woodrat (Neotoma cinerea), at five locations within south central Idaho and northwestern Utah. Previous work demonstrated that woodrats adapt to temperature shifts by altering body size. We focus here on the relationship between body mass, temperature, and location within the geographic range. Body mass is estimated by measuring fossil fecal pellets, a technique validated in earlier work. Overall, we find the predicted phenotypic response to climate change: Animals were larger during cold periods, and smaller during warmer episodes. However, we also identify several time periods when changes in environmental temperature exceeded the adaptive flexibility of N. cinerea. A smaller-bodied species, the desert woodrat (N. lepida) apparently invaded lower elevation sites during the mid-Holocene, despite being behaviorally and physically subordinate to N. cinerea. Analysis of contemporary patterns of body size and thermal tolerances for both woodrat species suggests this was because of the greater heat tolerance of N. lepida. The robust spatial relationship between contemporary body size and ambient temperature is used as a proxy to reconstruct local climate during the Holocene. ?? 2003 Elsevier Science (USA). All rights reserved.

Quaternary Research↗

USGS2021

Nonlinear shifts in infectious rust disease due to climate change

Range shifts of infectious plant disease are expected under climate change. As plant diseases move, emergent abiotic-biotic interactions are predicted to modify their distributions, leading to unexpected changes in disease risk. Evidence of these complex range shifts due to climate change, however, remains largely speculative. Here, we combine a long-term study of the infectious tree disease, white pine blister rust, with a six-year field assessment of drought-disease interactions in the southern Sierra Nevada. We find that climate change between 1996 and 2016 moved the climate optimum of the disease into higher elevations. The nonlinear climate change-disease relationship contributed to an estimated 5.5 (4.4–6.6) percentage points (p.p.) decline in disease prevalence in arid regions and an estimated 6.8 (5.8–7.9) p.p. increase in colder regions. Though climate change likely expanded the suitable area for blister rust by 777.9 (1.0–1392.9) km 2 into previously inhospitable regions, the combination of host-pathogen and drought-disease interactions contributed to a substantial decrease (32.79%) in mean disease prevalence between surveys. Specifically, declining alternate host abundance suppressed infection probabilities at high elevations, even as climatic conditions became more suitable. Further, drought-disease interactions varied in strength and direction across an aridity gradient—likely decreasing infection risk at low elevations while simultaneously increasing infection risk at high elevations. These results highlight the critical role of aridity in modifying host-pathogen-drought interactions. Variation in aridity across topographic gradients can strongly mediate plant disease range shifts in response to climate change.

California↗

USGS2023

Effects of climate change on the hydrologic and hydraulic response of the Caulks Creek basin, Wildwood, Missouri

The city of Wildwood, Missouri, has identified fluvial erosion along Caulks Creek as a management priority due to potential effects to infrastructure and property. The upper and middle reaches of Caulks Creek flow intermittently (only immediately after precipitation), whereas the lower reach flows perennially. This study examines the effects of climate change and added storage on the hydrologic and hydraulic response of the Caulks Creek Basin to design storms. The study uses hydrologic (Hydrologic Engineering Center Hydrologic Modeling System – HEC-HMS) and hydraulic (Hydrologic Engineering Center River Analysis System – HEC-RAS) models furnished by the Federal Emergency Management Agency (FEMA). HEC-HMS simulations were used to quantify the peak, volume, and timing of the flow response to a suite of design storms under both normal and wet antecedent conditions and for both the existing storage structures and new storage in the basin. The suite of design storms included all combinations of the following: (a) storm durations: 6-hour and 24-hour, (b) annual exceedance probabilities: 0.5, 0.2, 0.1, 0.04, 0.02, and 0.01, (c) climate conditions: current, 30-year, and 80-year predictions of future climate from the Coupled Model Intercomparison Project (CMIP) Climate Data Processing Tool. Additionally, for a selection of scenarios, results from the HEC-HMS simulations were used as boundary conditions for two-dimensional (2D) HEC-RAS simulations aimed at understanding how the distribution of velocity, shear stress, and stream power throughout the stream may be affected by projected changes in climate.

Missouri↗

USGS2013

Space can substitute for time in predicting climate-change effects on biodiversity

“Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

Proceedings of the National Academy of Sciences↗

USGS2020

Accounting for temporal variability of streamflow in estimates of travel time

Retention, processing, and transport of solutes and particulates in stream corridors are influenced by the travel time of streamflow through stream channels, which varies dynamically with discharge. The effects of streamflow variability across sites and over time cannot be addressed by time-averaged models if parameters are based solely on the characteristics of mean streamflow. We develop methods to account for the effects of streamflow variability on travel time and compare our estimates to flow-weighted (“effective”) travel time at 100 streams in the southeastern United States. Velocity time series were generated for each stream from multiple-year (median 15.5 years), high-frequency (15 min interval) records of instantaneous streamflow and field measurements of velocity and inverted to produce time series of specific travel time [T/L]. The effective travel times for streams are 60–90% of the specific travel time of mean streamflow because a large fraction of the total streamflow volume is discharged during higher flows with higher velocities. We find that adjusting the specific travel time of mean streamflow at a site by a factor of 0.81 generally accounts for the effect of a skewed streamflow distribution, but at-site estimates of the coefficient of variation of streamflow are necessary to resolve differences in streamflow variability between streams or changes in variability over time. For example, the effective travel time of urban streams is less than the effective travel of forested streams in the southeastern United States as a result of increased streamflow variability in urban streams. Effective travel time accounts for both the variation in velocity with streamflow and the large fraction of streamflow discharged during high flows in most streams and provides time-averaged models with limited capability to account for effects of streamflow variability that otherwise they lack. This capability is needed for continental-scale modeling where streamflow variability is not uniform because of heterogeneous surficial geology, hydro-climatology, and vegetation and for applications where streamflow variability is not stationary as a response to climate change or hydrologic alteration.

Alabama, Georgia, North Carolina, Virginia, South ↗

USGS2024

Declining groundwater storage expected to amplify mountain streamflow reductions in a warmer world

Groundwater interactions with mountain streams are often simplified in model projections, potentially leading to inaccurate estimates of streamflow response to climate change. Here, using a high-resolution, integrated hydrological model extending 400 m into the subsurface, we find groundwater an important and stable source of historical streamflow in a mountainous watershed of the Colorado River. In a warmer climate, increased forest water use is predicted to reduce groundwater recharge resulting in groundwater storage loss. Losses are expected to be most severe during dry years and cannot recover to historical levels even during simulated wet periods. Groundwater depletion substantially reduces annual streamflow with intermittent conditions predicted when precipitation is low. Expanding results across the region suggests groundwater declines will be highest in the Colorado Headwater and Gunnison basins. Our research highlights the tight coupling of vegetation and groundwater dynamics and that excluding explicit groundwater response to warming may underestimate future reductions in mountain streamflow.

Nature Water↗

USGS2014

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

Minnesota, North Dakota, South Dakota↗