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USGS2025

An analytical approach to explore prospects and limits of nutrition-sensitive fisheries governance under climate change

Researchers and policymakers increasingly recognize the contribution of aquatic food systems, such as fisheries, to food security and nutrition. Yet governing fisheries for nutrition objectives is complicated by the multiple overlapping processes that shape availability and access to nutrients over time, including fishing sustainability, climate change, trade dynamics, and consumer preferences. Anticipating the effect of governance interventions to sustain or enhance nutritional benefits from fisheries entails accounting for these multiple interacting influences. We develop an analytical approach to link available data on aquatic foods production, nutrition, distribution, and potential climate impacts to evaluate the nutrition implications of fishery management and post-harvest allocation interventions. We demonstrate this approach using national and publicly available datasets for five case study countries: Peru, Chile, Indonesia, Sierra Leone, and Malawi. As examples, we evaluate the potential to enhance domestic supply of key nutrients to nutritionally-vulnerable populations by (a) dynamically adjusting fishing effort in response to climate impacts on fish stocks, and (b) retaining aquatic foods currently diverted via trade or foreign fishing. The results indicate substantial differences across countries in terms of anticipated climate change effects, with potential for substantially increased nutrition yield in Chile and Peru under adaptive management, vs more modest yield increases in Indonesia. The impacts of post-harvest allocation policies related to foreign fishing, exports, fishing sector, and subnational trade also vary, with exports weighing heavily on nutrient availability in Sierra Leone. This methodological approach represents a step toward operationalizing calls to manage fisheries as part of national food and nutrient supplies, in light of climate change risks.

Environmental Research: Food Systems↗

USGS2025

Relationship-centered engagement bridges the divide between science and management, and enhances climate adaptation

The rapid pace of climate change demands changes in management practices. Despite abundant climate adaptation research, the implementation of climate adaptation can lag in the management space. In the present article, we argue that relationship-centered engagement—establishing and maintaining relationships among researchers and natural resource managers—is critical for bridging the research–management gap. We evaluated researcher–manager partnerships within the US Northeast Climate Adaptation Science Center and identified three cultural shifts that institutions, funders, researchers, and managers could adopt to boost the odds of translating findings into action: acknowledging and supporting the central role of relationships in creating and implementing actionable science, lengthening funding timelines to better support establishing and maintaining relationships, and aligning institutional rewards to support relationship building. A renewed focus on relationships can lead to more diverse and effective partnerships that bridge knowledge to practice and hasten adaptation to climate change.

BioScience↗

USGS2022

Animal tracing with sulfur isotopes: Spatial segregation and climate variability in Africa likely contribute to population trends of a migratory songbird

Climatic conditions affect animals but range-wide impacts at the population level remain largely unknown, especially in migratory species. However, studying climate–population relationships is still challenging in small migrants due to a lack of efficient and cost-effective geographic tracking method. Spatial distribution patterns of environmental stable isotopes (so called ‘isoscapes’) generally overcome these limitations but none of the currently available isoscapes provide a substantial longitudinal gradient in species-rich sub-Saharan Africa. In this region, sulphur ( δ 34 S) has not been sufficiently explored on a larger scale. We developed a δ 34 S isoscape to trace animal origins in sub-Saharan Africa by coupling known-origin samples from tracked migratory birds with continental remotely sensed environmental data building on environment– δ 34 S relationships using a flexible machine learning technique. Furthermore, we link population-specific nonbreeding grounds with interannual climatic variation that might translate to breeding population trends. The predicted δ 34 S isotopic map featured east–west and coast-to-inland isotopic gradients and was applied to predict nonbreeding grounds of three breeding populations of Eurasian Reed Warblers Acrocephalus scirpaceus with two distinct migratory phenotypes. Breeding populations as well as migratory phenotypes exhibited large-scale segregation within the African nonbreeding range. These regions also differed substantially in the interannual climatic variation, with higher interannual variability in the eastern part of the range during 2001–2012. Over the same period, the eastern European breeding population seemed to have experienced a more steep decline in population size. The link between migratory patterns and large-scale climatic variability appears important to better understand population trajectories in many declining migratory animals. We believe animal tracing using sulphur isotopes will facilitate these efforts and offers manifold ecological and forensic applications in the biodiversity hotspot of sub-Saharan Africa.

Journal of Animal Ecology↗

USGS2017

Harvesting wildlife affected by climate change: a modelling and management approach for polar bears

The conservation of many wildlife species requires understanding the demographic effects of climate change, including interactions between climate change and harvest, which can provide cultural, nutritional or economic value to humans. We present a demographic model that is based on the polar bear Ursus maritimus life cycle and includes density-dependent relationships linking vital rates to environmental carrying capacity ( K ). Using this model, we develop a state-dependent management framework to calculate a harvest level that (i) maintains a population above its maximum net productivity level (MNPL; the population size that produces the greatest net increment in abundance) relative to a changing K , and (ii) has a limited negative effect on population persistence. Our density-dependent relationships suggest that MNPL for polar bears occurs at approximately 0·69 (95% CI = 0·63–0·74) of K . Population growth rate at MNPL was approximately 0·82 (95% CI = 0·79–0·84) of the maximum intrinsic growth rate, suggesting relatively strong compensation for human-caused mortality. Our findings indicate that it is possible to minimize the demographic risks of harvest under climate change, including the risk that harvest will accelerate population declines driven by loss of the polar bear's sea-ice habitat. This requires that (i) the harvest rate – which could be 0 in some situations – accounts for a population's intrinsic growth rate, (ii) the harvest rate accounts for the quality of population data (e.g. lower harvest when uncertainty is large), and (iii) the harvest level is obtained by multiplying the harvest rate by an updated estimate of population size. Environmental variability, the sex and age of removed animals and risk tolerance can also affect the harvest rate. Synthesis and applications . We present a coupled modelling and management approach for wildlife that accounts for climate change and can be used to balance trade-offs among multiple conservation goals. In our example application to polar bears experiencing sea-ice loss, the goals are to maintain population viability while providing continued opportunities for subsistence harvest. Our approach may be relevant to other species for which near-term management is focused on human factors that directly influence population dynamics within the broader context of climate-induced habitat degradation.

Journal of Applied Ecology↗

USGS2026

Spatially concentrating logging could mitigate climate-magnified fragmentation risks to a globally endangered bird

1. Rising timber demand is transforming forest structure globally, profoundly affecting biodiversity and climate resilience. Logging-driven fragmentation is potentially a major driver of biodiversity loss in production landscapes, yet its interactions with escalating climate stressors remain poorly understood. 2. We combine two decades of Landsat-derived habitat metrics with 29,000 surveys of the marbled murrelet ( Brachyramphus marmoratus )—an iconic Pacific Northwest old-forest specialist seabird affecting management of >10 million hectares. Controlling for habitat amount and detection probability, increasing landscape-scale forest edge amount sharply reduces murrelet occupancy, with impacts worsening under unfavourable climate-driven ocean conditions. 3. Comparing alternative landscape-scale timber harvest strategies, spatially concentrated logging consistently supports higher murrelet populations than fragmented approaches producing equivalent wood volumes, with benefits amplified under adverse ocean conditions. However, historical harvesting policies in the Pacific Northwest have instead driven severe habitat fragmentation, which we show is eroding the value of core set-aside forests on federal and conservation lands and ultimately rendering murrelets more vulnerable to climate change. 4. Synthesis and applications : We map key opportunities to boost populations by reducing edginess around remaining nesting habitat and investigate these opportunities' spatial distribution across land ownership and timber productivity gradients. Concentrating logging could be critical for mitigating fragmentation and climate threats for murrelets and potentially other forest-dependent species amid rising timber demand.

California, Oregon, Washington↗

USGS2014

Functional diversity supports the physiological tolerance hypothesis for plant species richness along climatic gradients

1. The physiological tolerance hypothesis proposes that plant species richness is highest in warm and/or wet climates because a wider range of functional strategies can persist under such conditions. Functional diversity metrics, combined with statistical modeling, offer new ways to test whether diversity-environment relationships are consistent with this hypothesis. 2. In a classic study by R. H. Whittaker (1960), herb species richness declined from mesic (cool, moist, northerly) slopes to xeric (hot, dry, southerly) slopes. Building on this dataset, we measured four plant functional traits (plant height, specific leaf area, leaf water content and foliar C:N) and used them to calculate three functional diversity metrics (functional richness, evenness, and dispersion). We then used a structural equation model to ask if ‘functional diversity’ (modeled as the joint responses of richness, evenness, and dispersion) could explain the observed relationship of topographic climate gradients to species richness. We then repeated our model examining the functional diversity of each of the four traits individually. 3. Consistent with the physiological tolerance hypothesis, we found that functional diversity was higher in more favorable climatic conditions (mesic slopes), and that multivariate functional diversity mediated the relationship of the topographic climate gradient to plant species richness. We found similar patterns for models focusing on individual trait functional diversity of leaf water content and foliar C:N. 4. Synthesis. Our results provide trait-based support for the physiological tolerance hypothesis, suggesting that benign climates support more species because they allow for a wider range of functional strategies.

Oregon↗

USGS2017

A hydrologic drying bias in water-resource impact analyses of anthropogenic climate change

For water-resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration ( E p ) as inputs. Because E p is not a climate-model output, an intermediary model of E p must be introduced to connect the climate model to the hydrologic model. Several E p methods are used. The suitability of each can be assessed by noting a credible E p method for offline analyses should be able to reproduce climate models’ ACC-driven changes in actual evapotranspiration in regions and seasons of negligible water stress ( E w ). We quantified this ability for seven commonly used E p methods and for a simple proportionality with available energy (“energy-only” method). With the exception of the energy-only method, all methods tend to overestimate substantially the increase in E p associated with ACC. In an offline hydrologic model, the E p -change biases produce excessive increases in actual evapotranspiration ( E ), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC-induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water-resource impact analyses.

Journal of the American Water Resources Associatio↗

USGS2016

Accounting for adaptive capacity and uncertainty in assessments of species’ climate-change vulnerability

Climate change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. Here, we provide a more comprehensive CCVA approach that incorporates all three elements used for assessing species’ climate change vulnerability: exposure, sensitivity, and adaptive capacity. We illustrate our approach using case studies of two threatened salmonids with different life histories – anadromous steelhead trout ( Oncorhynchus mykiss ) and non-anadromous bull trout ( Salvelinus confluentus ) – within the Columbia River Basin, USA. We identified general patterns of high vulnerability in low-elevation and southernmost habitats for both species. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the two species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multi-species conservation. Our results highlight how CCVAs should be considered within a broader conceptual and computational framework for refining hypotheses, guiding research, and comparing plausible scenarios of species’ vulnerability for ongoing and projected climate change.

Columbia River Basin↗

USGS2022

Reducing uncertainty in climate change responses of inland fishes: A decision-path approach

Climate change will continue to be an important consideration for conservation practitioners. However, uncertainty in identifying appropriate management strategies, particularly for understudied species and regions, constrains the implementation of science-based solutions and adaptation strategies. Here, we share a decision-path approach to reduce uncertainty in climate change responses of inland fishes to inform conservation and adaptation planning. With the Fish and Climate Change database (FiCli), a comprehensive, online, public database of peer-reviewed literature on documented and projected climate impacts to inland fishes, users can identify relevant studies and associated management recommendations via geographic regions, response types (i.e., fish assemblage dynamics, demographic, distributional, evolutionary, phenological), fish taxa, and traits (e.g., thermal guilds, feeding type, parental care, habitat type) and use a suite of summary tools to make more informed decisions. For both data-rich and data-poor scenarios, we demonstrate that this approach can reduce uncertainty in understanding climate change responses. Using thermal sensitivity as an example, we also establish the utility of FiCli database to address other user-defined, management-relevant questions via supplementary analyses. This decision-path approach can be applied to rapid assessments, management decisions, and policy development and may serve as a model for other conservation decision-making processes.

Conservation Science and Practice↗

USGS2017

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental conditions when inferring the dynamics of migratory species.

Illinois↗

USGS2021

The climate envelope of Alaska’s northern treelines: Implications for controlling factors and future treeline advance

Understanding the key mechanisms that control northern treelines is important to accurately predict biome shifts and terrestrial feedbacks to climate. At a global scale, it has long been observed that elevational and latitudinal treelines occur at similar mean growing season air temperature (GSAT) isotherms, inspiring the growth limitation hypothesis (GLH) that cold GSAT limits aboveground growth of treeline trees, with mean treeline GSAT ~6–7°C. Treelines with mean GSAT warmer than 6–7°C may indicate other limiting factors. Many treelines globally are not advancing despite warming, and other climate variables are rarely considered at broad scales. Our goals were to test whether current boreal treelines in northern Alaska correspond with the GLH isotherm, determine which environmental factors are most predictive of treeline presence, and identify areas beyond the current treeline where advance is most likely. We digitized ~12 400 km of treelines (>26 K points) and computed seasonal climate variables across northern Alaska. We then built a generalized additive model predicting treeline presence to identify key factors determining treeline. Two metrics of mean GSAT at Alaska's northern treelines were consistently warmer than the 6–7°C isotherm (means of 8.5°C and 9.3°C), indicating that direct physiological limitation from low GSAT is unlikely to explain the position of treelines in northern Alaska. Our final model included cumulative growing degree-days, near-surface (≤1 m) permafrost probability and growing season total precipitation, which together may represent the importance of soil temperature. Our results indicate that mean GSAT may not be the primary driver of treeline in northern Alaska or that its effect is mediated by other more proximate, and possibly non-climatic, controls. Our model predicts treeline potential in several areas beyond current treelines, pointing to possible routes of treeline advance if unconstrained by non-climatic factors.

Alaska↗

USGS2024

Combining past and contemporary species occurrences with ordinal species distribution modeling to investigate responses to climate change

Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species-distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time-varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pika Ochotona princeps , a climate-sensitive mammal. Sampling over five years across the species' southernmost, warm-edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors – ordinal modeling highlighted chronic cold as the most-important predictor of occurrence, whereas binary modeling indicated primacy of average summer-long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater-provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal- and binary-analysis top models included climatic and biogeographic factors, results constitute important considerations for climate-adaptation planning. Cross-time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi-state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time.

New Mexico↗

USGS2016

Climate-induced seasonal changes in smallmouth bass growth rate potential at the southern range extent

Temperature increases due to climate change over the coming century will likely affect smallmouth bass ( Micropterus dolomieu ) growth in lotic systems at the southern extent of their native range. However, the thermal response of a stream to warming climate conditions could be affected by the flow regime of each stream, mitigating the effects on smallmouth bass populations. We developed bioenergetics models to compare change in smallmouth bass growth rate potential (GRP) from present to future projected monthly stream temperatures across two flow regimes: runoff and groundwater-dominated. Seasonal differences in GRP between stream types were then compared. The models were developed for fourteen streams within the Ozark–Ouachita Interior Highlands in Arkansas, Oklahoma and Missouri, USA, which contain smallmouth bass. In our simulations, smallmouth bass mean GRP during summer months decreased by 0.005 g g −1 day −1 in runoff streams and 0.002 g g −1 day −1 in groundwater streams by the end of century. Mean GRP during winter, fall and early spring increased under future climate conditions within both stream types (e.g., 0.00019 g g −1 day −1 in runoff and 0.0014 g g −1 day −1 in groundwater streams in spring months). We found significant differences in change in GRP between runoff and groundwater streams in three seasons in end-of-century simulations (spring, summer and fall). Potential differences in stream temperature across flow regimes could be an important habitat component to consider when investigating effects of climate change as fishes from various flow regimes that are relatively close geographically could be affected differently by warming climate conditions.

Ecology of Freshwater Fish↗

USGS2022

Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus)

An essential goal in conservation biology is delineating population units that maximize the probability of species persisting into the future and adapting to future environmental change. However, future-facing conservation concerns are often addressed using retrospective patterns that could be irrelevant. We recommend a novel landscape genomics framework for delineating future “Geminate Evolutionary Units” (GEUs) in a focal species: (1) identify loci under environmental selection, (2) model and map adaptive conservation units that may spawn future lineages, (3) forecast relative selection pressures on each future lineage, and (4) estimate their fitness and likelihood of persistence using geo-genomic simulations. Using this process, we delineated conservation units for the Yosemite toad ( Anaxyrus canorus ), a U.S. federally threatened species that is highly vulnerable to climate change. We used a genome-wide dataset, redundancy analysis, and Bayesian association methods to identify 24 candidate loci responding to climatic selection ( R 2 ranging from 0.09 to 0.52), after controlling for demographic structure. Candidate loci included genes such as MAP3K5, involved in cellular response to environmental change. We then forecasted future genomic response to climate change using the multivariate machine learning algorithm Gradient Forests. Based on all available evidence, we found three GEUs in Yosemite National Park, reflecting contrasting adaptive optima: YF-North (high winter snowpack with moderate summer rainfall), YF-East (low to moderate snowpack with high summer rainfall), and YF-Low-Elevation (low snowpack and rainfall). Simulations under the RCP 8.5 climate change scenario suggest that the species will decline by 29% over 90 years, but the highly diverse YF-East lineage will be least impacted for two reasons: (1) geographically it will be sheltered from the largest climatic selection pressures, and (2) its standing genetic diversity will promote a faster adaptive response. Our approach provides a comprehensive strategy for protecting imperiled non-model species with genomic data alone and has wide applicability to other declining species.

California↗

USGS2025

Ice Age biogeography corresponds with current climate vulnerability of freshwater fishes

1. Both local environmental factors and historical biogeography shape ecological communities, but determining which historical biogeographical patterns correspond with contemporary climate vulnerability is an underused conservation method. The historical colonization patterns of freshwater fishes following the Pleistocene (“Ice Age”) glaciations offers an ideal model for comparing historical biogeography and climate-change vulnerability. 2. We used current thermal niches and future stream-temperature projections to estimate the climate vulnerability of 29 Great Plains and Rocky Mountain fishes that we classified as either early or late colonists of the region in the wake of glacial retreat (~19,000 years ago). 3. Ninety-three percent of the most vulnerable species were amongst the earliest colonists of the region and we consider them “postglacial-pioneer species”. Median predicted site loss (number of historically occupied sites predicted to become too warm by end-of-century) was 0% for late colonizing species and 33% for early colonizing species. 4. We provide empirical evidence that postglacial-pioneer fishes are uniquely vulnerable to climate change, and we suggest this may apply to many taxa from formerly glaciated regions. More broadly, we demonstrate that evaluating the relationship between current species-environment patterns and historical biogeography may be a fruitful avenue for future climate change and conservation research.

North America↗

USGS2013

Climate-associated population declines reverse recovery and threaten future of an iconic high-elevation plant

Although climate change is predicted to place mountain-top and other narrowly endemic species at severe risk of extinction, the ecological processes involved in such extinctions are still poorly resolved. In addition, much of this biodiversity loss will likely go unobserved, and therefore largely unappreciated. The Haleakalā silversword is restricted to a single volcano summit in Hawai‘i, but is a highly charismatic giant rosette plant that is viewed by 1–2 million visitors annually. We link detailed local climate data to a lengthy demographic record, and combine both with a population-wide assessment of recent plant mortality and recruitment, to show that after decades of strong recovery following successful management, this iconic species has entered a period of substantial climate-associated decline. Mortality has been highest at the lower end of the distributional range, where most silverswords occur, and the strong association of annual population growth rates with patterns of precipitation suggests an increasing frequency of lethal water stress. Local climate data confirm trends toward warmer and drier conditions on the mountain, and signify a bleak outlook for silverswords if these trends continue. The silversword example foreshadows trouble for diversity in other biological hotspots, and illustrates how even well-protected and relatively abundant species may succumb to climate-induced stresses.

Hawai'i↗

USGS2014

Climate remains an important driver of post-European vegetation change in the eastern United States

The influence of climate on forest change during the past century in the eastern United States was evaluated in a recent paper (Nowacki & Abrams, 2014 ) that centers on an increase in ‘highly competitive mesophytic hardwoods’ (Nowacki & Abrams, 2008 ) and a concomitant decrease in the more xerophytic Quercus species. Nowacki & Abrams ( 2014 ) concluded that climate change has not contributed significantly to observed changes in forest composition. However, the authors restrict their focus to a single element of climate: increasing temperature since the end of the Little Ice Age ca. 150 years ago. In their study, species were binned into four classifications (e.g., Acer saccharum – ‘cool-adapted’, Acer rubrum – ‘warm-adapted’) based on average annual temperature within each species range in the United States, reducing the multifaceted character of climate into a single, categorical measure. The broad temperature classes not only veil the many biologically relevant aspects of temperature (e.g., seasonal and extreme temperatures) but they may also mask other influences, both climatic (e.g., moisture sensitivity) and nonclimatic (e.g., competition).

Global Change Biology↗

USGS2016

Climate-induced glacier and snow loss imperils alpine stream insects

Climate warming is causing rapid loss of glaciers and snowpack in mountainous regions worldwide. These changes are predicted to negatively impact the habitats of many range-restricted species, particularly endemic, mountaintop species dependent on the unique thermal and hydrologic conditions found only in glacier-fed and snowmelt-driven alpine streams. Though progress has been made, existing understanding of the status, distribution, and ecology of alpine aquatic species, particularly in North America, is lacking, thereby hindering conservation and management programs. Two aquatic insects – the meltwater stonefly Lednia tumana and the glacier stonefly Zapada glacier – were recently proposed for listing under the U.S. Endangered Species Act due to climate-change-induced habitat loss. Using a large dataset (272 streams, 482 total sites) with high-resolution climate and habitat information, we describe the distribution, status, and key environmental features that limit L. tumana and Z. glacier across the northern Rocky Mountains. Lednia tumana was detected in 113 streams (175 sites) within Glacier National Park (GNP) and surrounding areas. The probability of L. tumana occurrence increased with cold stream temperatures and close proximity to glaciers and permanent snowfields. Similarly, densities of L. tumana declined with increasing distance from stream source. Zapada glacier was only detected in 10 streams (20 sites), six in GNP and four in mountain ranges up to ~600 km southwest. Our results show that both L. tumana and Z. glacier inhabit an extremely narrow distribution, restricted to short sections of cold, alpine streams often below glaciers predicted to disappear over the next two decades. Climate warming-induced glacier and snow loss clearly imperils the persistence of L. tumana and Z. glacier throughout their ranges, highlighting the role of mountaintop aquatic invertebrates as sentinels of climate change in mid-latitude regions.

Global Change Biology↗