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At least 1,279 records · Page 71Linked to original sources
USGS2022

Evaluating temporal and spatial transferability of a tidal inundation model for foraging waterbirds

For ecosystem models to be applicable outside their context of development, temporal and spatial transferability must be demonstrated. This presents a challenge for modeling intertidal ecosystems where spatiotemporal variation arises at multiple scales. Models specializing in tidal dynamics are generally inhibited from having wider ecological applications by coarse spatiotemporal resolution or high user competency. The Tidal Inundation Model of Shallow-water Availability (TiMSA) uniquely simulates tides to empirically derive a time-integrated measure of availability for a shallow-water depth range defined by the user. To evaluate temporal and spatiotemporal transferability, we employed TiMSA at the development site in the Florida Keys and at novel subsites in the Florida Bay (application site) under a different time period (application period). We used foraging little blue herons ( Egretta caerulea ) as the ecological unit with which to constrain the model's “water depth window,” that is, range of water depths to estimate shallow-water availability. At the development site, temporally consistent water depth windows contrasted with interannual variation in shallow-water availability, which revealed short-term changes in Little Blue Heron foraging habitat. At the application site, water depth accuracy varied by subsite and was correlated with spatial error in bathymetric elevation. Although TiMSA parameters were sensitive to environmental temporal variation and uncertainty in spatial data, a spatially explicit water depth window generated reliable estimates of shallow-water conditions over space and time at the development and application sites. By exploring the contributing factors to model error, we provide solutions to reduce uncertainty of TiMSA parameters at potential application sites and recommendations for addressing bathymetric inaccuracy in digital elevation models. Accurately quantifying spatiotemporal changes of shallow water has implications for monitoring habitat conditions for tidally influenced species and projecting future changes to coastal ecosystems in response to anthropogenic stressors and natural disturbances such as sea level rise.

Florida↗
USGS2022

The researcher's lament: Why do they ignore my science?

The researcher's lament is shared by many environmental and conservation scientists who complain about the little support they receive for their research proposals during the review and selection process. Understandably, any hopes of having their anticipated scientific findings applied toward the formulation of environmental management decisions or natural resource policy action are shattered. They attribute this lack of endorsement to shortcomings and limitations among decision makers and proposal selection officials when, in many cases, the rejection of project proposals is often a function of a handful of self-inflicted failures by applied scientists who anchor themselves stubbornly to doomed approaches. Familiar deficiencies in their research proposals perpetuate the disconnect between the enterprise of science and real-world resource management challenges. Researchers themselves can affect conditions that turn up the appetite for their scientific endeavors as a more meaningful component of the decision-making process, namely, to stage and deliver science that is more readily "actionable." Perhaps it is time for them to consider a course correction to improve the viability of their actionable science proposals. A few basic steps may help rejigger the science planning process in this direction and, consequently, help avoid the researcher's lament. The likelihood of gaining support during the proposal review and award adjudication process, and securing practical application of scientific products, increases when the products are (1) the result of active engagement of researchers with decision makers; (2) better connected to social and political priorities; (3) clearly designed to inform specific management decisions; and (4) tailored to fit the needs of targeted end users. These considerations and activities exist beyond the comfort zone of many environmental or conservation scientists. Yet, those who adopt them will spend less time lamenting rejection and become more influential in the production of actionable knowledge.

Ecosphere↗
USGS2022

Fuel reduction treatments reduce modeled fire intensity in the sagebrush steppe

Increased fire size and frequency coupled with annual grass invasion pose major challenges to sagebrush ( Artemisia spp.) ecosystem conservation, which is currently focused on protecting sagebrush community composition and structure. A common strategy for mitigating potential fire is to use fuel treatments that alter the structure and amount of burnable material, thus reducing fire behavior and creating access points for fire suppression resources. While there is some recent information on the impacts of fuel treatments on ecological communities, we have little information on fuel treatment effectiveness at modifying fire behavior in sagebrush ecosystems. We present 10 years of data on fuel accumulation and the resultant modeled fire behavior in prescribed fire, mowed, herbicide (tebuthiuron or imazapic), and untreated control plots in the Sagebrush Treatment Evaluation Project (SageSTEP) network in the Great Basin, USA. Fuel data (i.e., aboveground burnable live and dead biomass) were collected in each treatment plot at Years 0 (pretreatment), 1, 2, 3, 6, and 10 posttreatment. We used the Fuel and Fire Tool fire behavior modeling program to test whether treatments impacted potential fire behavior. Prescribed fire initially removed 49% of the total fuel load and 75% of shrubs, and fuel loads remained reduced through Year 10. Mowing shifted fuels from the shrub canopy to the ground surface but did not change the total fuel amount. Prescribed fire and mowing increased herbaceous fuel by the second posttreatment year and that trend persisted through Year 10. Tebuthiuron treatments were ineffective at altering fuel loads. Imazapic suppressed herbaceous vegetation by 30% in Years 2 and 3 following treatment. The modified fuel beds in fire and mow treatments resulted in modeled flame lengths that were significantly lower than untreated control plots for the duration of the study, with shorter term reductions in reaction intensity and rate of spread. Understanding fuel treatment effectiveness will allow natural resource managers to evaluate trade-offs between protecting wildlife habitat and reducing the potential for high-intensity wildfire.

Ecosphere↗
USGS2022

Statistical assessment on determining local presence of rare bat species

Surveying cryptic, sparsely distributed taxa using autonomous recording units, although cost-effective, provides imperfect knowledge about species presence. Summertime bat acoustic surveys in North America exemplify the challenges with characterizing sources of uncertainty: observation error, inability to census populations, and natural stochastic variation. Statistical uncertainty, if not considered thoroughly, hampers determining rare species presence accurately and/or estimating rangewide status and trends with suitable precision. Bat acoustic data are processed using an automated workflow in which proprietary or open-source algorithms assign a species label to each recorded high-frequency echolocation sequence. A false-negative occurs, if a species is actually present but not recorded and/or all recordings from the species are of such poor quality that a correct species identity cannot be assigned to any observation. False positives for a focal species are a direct result of the presence and incorrect identification of a recording from another species. We compare four analytical approaches in terms of parameter estimation and their resulting (in)correct decisions regarding species presence or absence using realistic data-generating scenarios for bat acoustic data within a simulation study. The current standard for deciding species presence or absence uses a multinomial likelihood-ratio test p value (maximum likelihood estimate [MLE]-metric) that accounts for known species misidentifications, but not imperfect detection and only returns a binary outcome (evidence of presence or not). We found that the MLE-metric had estimated median correct decisions less than 60% for presence and greater than 85% for absence. Alternatively, a multispecies count detection model was equivalent to or better than the MLE-metric for correct claims of rare species presence or absence using the posterior probability a species was present at a site and, importantly, provided unbiased estimates of relative activity and probability of occurrence, creating opportunities for reducing posterior uncertainty through the inclusion of meaningful covariates. Single-species occupancy models with and without false-positive detections removed were insufficient for determining local presence because of substantially biased occurrence and detection probabilities. We propose solutions to potential barriers for integrating local, short-term and rangewide, long-term acoustic surveys within a cohesive statistical framework that facilitates determining local species presence with uncertainty concurrent with estimating species–environment relationships.

Ecosphere↗
USGS2022

Spatial scale selection for informing species conservation in a changing landscape

Identifying the relevant spatial scale at which species respond to features in a landscape (scale of effect) is a pressing research need as managers work to reduce biodiversity loss amid a variety of environmental challenges. Until recently, researchers often evaluated a subset of potential scales of effect inferred from previous studies in other locations, often based on different biological responses and environmental variables. These approaches, however, can create uncertainty as to whether relevant spatial scales were identified, and whether the effects of environmental variables at scale were accurately estimated. Identifying scales of effect is particularly relevant for the greater sage-grouse ( Centrocercus urophasianus ), a sagebrush-obligate species of conservation concern requiring large areas of intact sagebrush cover ( Artemisia spp.) for habitat. We demonstrate the application of a scale selection approach that jointly estimates the scale of effect and the effect of sagebrush cover on trends in population size using counts from 584 sage-grouse leks in southwestern Wyoming (2003–2019) and annual estimates of sagebrush cover from a remote sensing product. From this approach, we estimated a positive effect of mean sagebrush cover with a 95% probability that the scale of effect occurred within 5.02 km of leks. In an average year, we found that lower levels of sagebrush cover within these estimated scales could support increasing trends in sage-grouse population size when populations were small, but higher levels of sagebrush cover were needed to sustain growing populations when populations were larger. With standardized monitoring and annual estimates of vegetation from remote sensing, this scale selection approach can be applied to identify relevant scales for other populations, species, and biological responses such as demography and movement.

Wyoming↗
USGS2022

Freshwater corridors in the conterminous US: A coarse-filter approach based on lake-stream networks

Maintaining regional-scale freshwater connectivity is challenging owing to the dendritic, easily fragmented structure of freshwater networks, but is essential for promoting ecological resilience under climate change. Although the importance of stream network connectivity has been recognized, lake-stream network connectivity has largely been ignored. Furthermore, protected areas are generally not designed to maintain or encompass entire freshwater networks. We applied a coarse-filter approach to identify potential freshwater corridors for diverse taxa by calculating connectivity scores for 385 lake-stream networks across the conterminous US based on network size, structure, resistance to fragmentation, and dam prevalence. We also identified 2080 disproportionately important lakes for maintaining intact networks (i.e., “hubs”; 2% of all network lakes) and analyzed the protection status of hubs and potential freshwater corridors. Just 3% of networks received high connectivity scores based on their large size and structure (medians of 1303 lakes, 498.6 km north-south stream distance), but these also contained a median of 454 dams. In contrast, undammed networks (17% of networks) were considerably smaller (medians of 6 lakes, 7.2 km north-south stream distance), indicating that the functional connectivity of the largest potential freshwater corridors in the conterminous US currently may be diminished compared to smaller, undammed networks. Network lakes and hubs were protected at similar rates nationally across different levels of protection (8-18% and 6-20%, respectively), but were generally more protected in the western US. Our results indicate that conterminous US protection of major freshwater corridors and the hubs that maintain them generally fell short of the international conservation goal of protecting an ecologically representative, well-connected set of fresh waters (≥ 17%) by 2020 (Aichi Target 11). Conservation planning efforts might consider focusing on restoring natural hydrologic connectivity at or near hubs, particularly in larger networks, less protected, or biodiverse regions, to support freshwater biodiversity conservation under climate change.

Ecosphere↗
USGS2023

Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA

Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally, we evaluated how housing growth and changes in burn probability influenced risk individually and combined. Fires burned 9055 km 2 and exposed more than 8500 homes from 1990 to 2019. Observed burned area increased 632% from the 1990s to the 2000s, which combined with housing growth, resulted in a 1342% increase in homes exposed. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC = 0.88 and r = 0.9). Observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000 (exposure). However, our model overpredicted in years with low observed burned area and underpredicted in years with high observed burned area. Overpredictions in risk resulted in lower rates of change in predicted risk compared with change in observed exposure. Increases in risk between the 1990s and 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases between the 2000s and 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide decision-making. Because the drivers behind risk shift over time, strategies to mitigate risk may need to account for multiple drivers simultaneously.

Colorado, New Mexico, Wyoming↗
USGS2023

Decoupling of species and plant communities of the U.S. Southwest: A CCSM4 climate scenario example

Climate change is predicted to alter the current climate suitability under which plant species and communities occur. Predictions of change have focused on individual species or entire communities, but theory indicates plants will not respond uniformly to climate change within or between communities. We developed models of the current climate suitability (the baseline) of 66 plant species characteristic of 29 plant communities of the arid Southwest, made predictions of climate suitability for the species under two climate change scenarios for the years 2041–2060 (Community Climate System Model version 1.4 [CCSM4] global climate model [GCM], Representative Concentration Pathway [RCP] 4.5 and 8.5 scenarios), and calculated changes in suitability between the future scenarios and baseline for each species. Climate change exposure for the entire community was then evaluated as the composite change of the predicted future climate suitability of the communities' characteristic species. Loss of 25% or more of favorable climate suitability was predicted for 39 (RCP4.5) and 51 (RCP8.5) species within their communities. The proportion of the study area with all species in a community having unfavorable suitability was 17.9% (RCP4.5) and 21.3% (RCP8.5) compared to 6.2% for baseline. We show that suitable climates for species within a plant community are not expected to be a single community-wide trajectory, but rather changes in climate suitability will be unique to the species and not experienced uniformly across the extant communities. This decoupling of plant species within their traditional plant communities may lead to a cascade of unanticipated ecological responses and unprecedented challenges to resource management. Our study results can inform hypotheses of the future successional track of plant communities, characteristic species, and the decisions resource managers must make for management.

Ecosphere↗
USGS2023

BioLake: A first assessment of lake temperature-derived bioclimatic predictors for aquatic invasive species

Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature-derived “BioLake” bioclimatic layers for distribution modeling of aquatic species and compared “climatch” climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization.

Ecosphere↗
USGS2023

PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations

Feral horse ( Equus caballus ) population management is a challenging problem around the world because populations often exhibit density-independent growth, can exert negative ecological effects on ecosystems, and require great cost to be managed. However, strong value-based connections between people and horses cause contention around management decisions. To help make informed decisions, natural resource managers might benefit from more detailed understanding of how horse management alternatives, including combinations of removals and fertility control methods, could achieve objectives of sustainable, multiple-use ecosystems while minimizing overall horse handling and fiscal costs. Here, we describe a modeling tool that simulates horse management alternatives and estimates trade-offs in predicted metrics related to population size, animal handling, and direct costs of management. The model considers six management actions for populations (removals for adoption or long-term holding; fertility control treatment with three vaccines, intrauterine devices, and mare sterilization), used alone or in combination. We simulated 19 alternative management scenarios at 2-, 3-, and 4-year management return intervals and identified efficiency frontiers among alternatives for trade-offs between predicted population size and six management metrics. Our analysis identified multiple alternatives that could maintain populations within target population size ranges, but some alternatives (e.g., removal and mare sterilization, removal and GonaCon treatment) performed better at minimizing overall animal handling requirements and management costs. Cost savings increased under alternatives with more effective, longer lasting fertility control techniques over longer management intervals compared with alternatives with less-effective, shorter lasting fertility control techniques. We built a user-friendly website application, PopEquus , that decision makers and interested individuals can use to simulate management alternatives and evaluate trade-offs among management and cost metrics. Our results and website application provide quantitative trade-off tools for horse population management decisions and can help support value-based management decisions for wild or feral horse populations and ecosystems at local and regional scales around the world.

Ecosphere↗
USGS2024

A habitat-centered framework for wildlife climate change vulnerability assessments: Application to Gunnison sage-grouse

The persistence of threatened wildlife species depends on successful conservation and restoration of habitats, but climate change and other stressors make these tasks increasingly challenging. Applying climate change vulnerability analyses to contemporary wildlife management can be difficult because most analyses predict direct effects of future climate on wildlife species at broad geographic scales, rather than assessing their habitats at local scales (<1 km) that correspond to site-specific habitat management actions. We present a framework that synthesizes vegetation-focused vulnerability assessments to assess multiple effects on wildlife species' diverse habitat needs, providing a scenario-driven climate vulnerability assessment that maps differences in vulnerability of populations within a species' range. Our flexible habitat-centered synthesis approach leverages available spatial datasets describing projected exposure to vegetation changes due to climate change and other potentially synergistic stressors, reclassifies and weights them based on available estimates of species' sensitivity to these changes, and recombines them to create <1-km resolution maps of overall species vulnerability and threat-specific habitat vulnerability . To demonstrate its potential to guide decision-making, we applied this approach to the Gunnison sage-grouse ( Centrocercus minimus ), a federally threatened habitat specialist that depends on sagebrush and mesic habitats that are imperiled by climate change. We mapped six threats forecasted out to the year 2070: direct effects of climate on (1) sagebrush cover loss and (2) mesic habitat drying, indirect changes in invasion risk from (3) pinyon–juniper conifers and (4) annual grasses, and potentially synergistic risk of (5) development and (6) wildfire. We then assessed species vulnerability for each of the eight extant populations under three climate scenarios: Optimistic, Continuation, and Pessimistic. We found that the extent of cumulative species vulnerability due to multiple habitat changes was far greater than the extent of any single habitat vulnerability. Over 75% of critical habitats were at risk under the Pessimistic scenario, and nearly two thirds of habitats were at high risk for three or more threats. Invasive species were the most widespread threat, highlighting the importance of indirect effects of climate change. We illustrate how our approach can be applied to the existing management planning strategies to better prioritize conservation of habitats for the persistence of threatened species.

Colorado, Utah↗
USGS2024

Multiple stressors mediate the effects of warming on leaf decomposition in a large regulated river

Predicting how increasing temperatures interact with other global change drivers to influence the structure and dynamics of Earth's ecosystems is a primary challenge in ecology. Our study made use of multiple simultaneous “natural experiments” to examine how rapid warming, declining nutrients, invasive consumers, and riparian invasive species management interact to influence leaf decomposition in a large and regulated river. Specifically, we compared the breakdown of cottonwood ( Populus fremontii ), willow ( Salix exigua ), and saltcedar ( Tamarix sp.) leaf litter in 2022 to a previous experiment from 1998 that occurred under much cooler water temperatures, and had higher water phosphorus concentrations, low numbers of invasive New Zealand mudsnails ( Potamopyrgus antipodarum ), and unaltered litter chemistry from the herbivory of saltcedar leaf beetles ( Diorhabda carinulata ). We found that the effects of up to 10°C warmer temperatures on leaf decomposition were mediated by the establishment and management of invasive species and declining water nutrient concentrations arising from upstream reservoir lowering. Such interactions led to accelerated breakdown of saltcedar, but relatively minor effects of warming on the rate of cottonwood and willow decomposition. Additionally, our results demonstrate the potential for favorable invasive species management outcomes in the terrestrial environment to produce unintended responses in adjacent freshwater ecosystems. As temperatures continue to rise, it is critical that future studies consider how warming interacts with multiple stressors and environmental factors to influence processes such as decomposition in freshwater ecosystems.

Arizona↗
USGS2024

Phenology forecasting models for detection and management of invasive annual grasses

Non-native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well-timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range-wide phenology forecasts for two problematic invasive annual grasses: cheatgrass ( Bromus tectorum ), and red brome ( Bromus rubens ). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat-insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within-season or within-year decision support.

Ecosphere↗
USGS2024

Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations

Climate-induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector-borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecast of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits which may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life-history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait-based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi-scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.

Michigan, Wisconsin↗
USGS2025

Spatiotemporal interactions facilitate sympatry in a diverse mammalian community

Understanding mechanisms underlying coexistence among potential competitors, and between predators and prey, is a persistent challenge in community ecology. Using 6 years (2013–2018) of camera-trapping data and species interaction models, we investigated the spatiotemporal patterns of inter- and intra-guild interspecific interactions in a diverse terrestrial mammalian community in Pakke Wildlife Sanctuary and Tiger Reserve (PTR), Northeast India. We found no evidence of spatial interaction among apex predators (tiger Panthera tigris , leopard Panthera pardus , and dhole Cuon alpinus ). However, dholes temporally separated themselves from tigers and leopards. Among small carnivores, marbled cat ( Pardofelis marmorata ) and leopard cat ( Prionailurus bengalensis ) exhibited temporal separation, whereas leopard cat overlapped spatially and temporally with other small carnivores. Herbivores exhibited neither spatial nor temporal separation with each other. All apex predators exhibited diel activity and space-use patterns to overlap with their preferred prey. Our results suggest that the assembly of the diverse mammalian community of PTR is a complex process, and coexistence among potential competitors, and predators and prey is likely facilitated by several mechanisms including spatial and temporal segregation, and potentially dietary separation.

Arunachal Pradesh↗
USGS2024

A comparative framework to develop transferable species distribution models for animal telemetry data

Species distribution models (SDMs) have become increasingly popular for making ecological inferences, as well as predictions to inform conservation and management. In predictive modeling, practitioners often use correlative SDMs that only evaluate a single spatial scale and do not account for differences in life stages. These modeling decisions may limit the performance of SDMs beyond the study region or sampling period. Given the increasing desire to develop transferable SDMs, a robust framework is necessary that can account for known challenges of model transferability. Here, we propose a comparative framework to develop transferable SDMs, which was tested using satellite telemetry data from green turtles ( Chelonia mydas ). This framework is characterized by a set of steps comparing among different models based on (1) model algorithm (e.g., generalized linear model vs. Gaussian process regression) and formulation (e.g., correlative model vs. hybrid model), (2) spatial scale, and (3) accounting for life stage. SDMs were fitted as resource selection functions and trained on data from the Gulf of Mexico with bathymetric depth, net primary productivity, and sea surface temperature as covariates. Independent validation datasets from Brazil and Qatar were used to assess model transferability. A correlative SDM using a hierarchical Gaussian process regression (HGPR) algorithm exhibited greater transferability than a hybrid SDM using HGPR, as well as correlative and hybrid forms of hierarchical generalized linear models. Additionally, models that evaluated habitat selection at the finest spatial scale and that did not account for life stage proved to be the most transferable in this study. The comparative framework presented here may be applied to a variety of species, ecological datasets (e.g., presence-only, presence-absence, mark-recapture), and modeling frameworks (e.g., resource selection functions, step selection functions, occupancy models) to generate transferable predictions of species–habitat associations. We expect that SDM predictions resulting from this comparative framework will be more informative management tools and may be used to more accurately assess climate change impacts on a wide array of taxa.

Ecosphere↗
USGS2025

Ecological thresholds and transformations due to climate change: The role of abiotic stress

An ecological threshold is the point at which a comparatively small environmental change triggers an abrupt and disproportionately large ecological response. In the face of accelerating climate change, there is concern that abrupt ecosystem transformations will become more widespread as critical ecological thresholds are crossed. There has been ongoing debate, however, regarding the prevalence of ecological thresholds across the natural world. While ecological thresholds are ubiquitous in some ecosystems, thresholds have been difficult to detect in others. Some studies have even concluded that threshold responses are uncommon in the natural world and overly emphasized in the ecological literature. As ecologists who work in ecosystems chronically exposed to high abiotic stress, we consider ecological thresholds and ecosystem transformations to be critical concepts that can greatly advance understanding of ecological responses to climate change and inform ecosystem management. But quantifying ecological thresholds can be challenging, if not impossible, without data that are strategically collected for that purpose. Here, we present a conceptual framework built upon linkages between abiotic stress, climate-driven ecological threshold responses, and the risk of ecosystem transformation. We also present a simple approach for quantifying ecological thresholds across abiotic stress gradients. We hypothesize that climate-driven threshold responses are especially influential in ecosystems chronically exposed to high abiotic stress, where autotroph diversity is low and foundation species play a prominent ecological role. Abiotic conditions in these environments are often near physiological tolerance limits of foundation species, which means that small abiotic changes can trigger landscape-level ecological transformations. Conversely, the alleviation of stress near thresholds can allow foundation species to thrive and spread into previously inhospitable locations. We provide examples of this climate-driven threshold behavior from four high-stress environments: coastal wetlands, coral reefs, drylands, and alpine ecosystems. Our overarching aim in this review is to clarify the strong relationships between abiotic stress, climate-driven ecological thresholds, and the risk of ecosystem transformation under climate change.

Ecosphere↗
USGS2025

Dynamic environments generate geographic fluctuations in population structure of an inland shorebird

Species distributions depend on fine-scale ecological processes and population growth trajectories and are influenced by climate and weather changes. However, the characterization of inter-population dynamics underlying the geographic distributions of migratory organisms remains challenging. We adopted a stable isotope approach to investigate the dynamic population geography of a terrestrial migratory bird across multiple generations. We found that the age-specific geographic source of Mountain Plovers sampled during winter shifted over four years across a latitudinal gradient. Moreover, our results show that differential effects of climate on the probability of occurrence at the wintering ground could be a driver of population turnover in a migratory species adapted to extreme environmental stochasticity (i.e., drought occurrence). We propose a framework for the identification of spatial and temporal climate and weather components and respective effects on population composition and recruitment into migratory wintering populations. Our approach is useful to reveal population compositional shifts through hydrogen stable isotope analysis while accounting for cumulative drought effects.

Ecosphere↗