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At least 595 records · Page 33Linked to original sources
USGS2021

Hydropeaking intensity and dam proximity limit aquatic invertebrate diversity in the Colorado River Basin

River biodiversity is threatened globally by hydropower dams, and there is a need to understand how dam management favors certain species while filtering out others. We examined aquatic invertebrate communities within the tailwaters 0–24 km downstream of seven large hydropower dams in the Colorado River Basin of the western United States. We quantified aquatic invertebrate dominance, richness, abundance, and biomass at multiple locations within individual tailwaters and across the basin and identified biological community responses associated with dam operations and distance from dam. We found that each tailwater was dominated by 3–7 invertebrate taxa, accounting for 95% of total abundance. Half of these dominant taxa were non-insect, non-flying species and thus were unavailable to terrestrial consumers. Consistent with previous studies, aquatic insects and sensitive taxa were negatively associated with hydropeaking intensity (magnitude of daily flow fluctuations associated with hydropower generation), which limits the composition and potentially the quality of the invertebrate food base. While total invertebrate abundance and biomass did not change with increasing distance downstream from dams, insect and sensitive taxa richness, abundance, and biomass all increased, suggesting that impacts of hydropeaking are most acute immediately downstream of dams. Our results demonstrate that tailwaters experiencing hydropeaking support high abundances of aquatic invertebrate, but the diversity of these communities is low.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2021

Thermal stability of an adaptable, invasive ectotherm: Argentine giant tegus in the Greater Everglades ecosystem, USA

Invasive species globally threaten biodiversity and economies, but the ecophysiological mechanisms underlying their success are often understudied. For those alien species that also exhibit high phenotypic plasticity, such as habitat generalists, adaptations in response to environmental pressures can take place relatively quickly. The Argentine giant tegu ( Salvator merianae ; tegu) is a large omnivorous lizard from South America that is prolific, long-lived, vagile, and highly adaptable to disturbed environments. They are well suited to the climate of southeastern United States, introduced to several disjunct areas, including the Everglades, where their voracious appetite threatens native wildlife. Tegus undergo winter dormancy (hibernation) to cope with colder temperatures, and while this behavior may facilitate invasion into more temperate regions, it may also present management opportunities. We studied the thermal habits of wild S. merianae within their invaded range in southern Florida, USA. We used radiotelemetry and trail cameras to verify aboveground behaviors, and temperature dataloggers to monitor surface (sun-exposed [ T e ] and shaded [ T s ]), ambient ( T a ), subsurface ground ( T h ), and internal body ( T b ) temperatures of a population of free-ranging tegus over several seasons. We evaluated thermal and behavioral data and identified five biologically significant periods: pre-hibernal, hibernal, cold snaps, hibernal-basking, and post-hibernal. We found tegus maintained thermal stability throughout the hibernal period, frequently at temperatures above available thermal microhabitats. Variation in T b was lowest during hibernation and cold snaps and was less variable than subsurface temperatures despite not leaving their hibernaculum. Hibernal ingress and egress were best predicted by temperature differentials between exposed soil and ambient daily mean temperatures ( T e − T a ) and daylength. Though we detected no sex differences, larger animals started hibernation sooner, stayed in hibernation longer, and retained higher fat stores over the study period. One individual did not hibernate, representing only the second record of this behavior. Despite limitations of these descriptive data, this is the first study finely detailing T b of a population of wild, free-ranging S. merianae over multiple biologically significant time periods and to associate T b with thermal habitats within its invasive range. Tegus' apparent ability for thermal stability expands the adaptability breadth of this species and underscores the invasion threat.

Florida↗
USGS2021

A greener future for the Galapagos: Forecasting ecosystem productivity by finding climate analogs in time

Forecasting ecosystem response to climate change is critical for guiding policymaking but challenging due to: complicated relationships between microclimates and regional climates; species’ responses that are driven by extremes rather than averages; the multifaceted nature of species’ interactions; and the lack of historical analogs to future climates. Given these challenges, even model systems such as the Galapagos Islands, a world-famous biodiversity hotspot and World Heritage Site, lack clear forecasts for future environmental change. Here, we developed a novel nonparametric method for simulating the ecosystem futures based on observed vegetation productivity (NDVI) during analogous weather observed historically. Using satellite images taken from the past to piece together a simulated future, we projected that productivity of terrestrial vegetation of the Galapagos will increase over the next century by approximately one standard deviation archipelago-wide, with largest increases during the wet season (January to June) and in the arid zones. Such greening would impact a variety of ecological and evolutionary processes, species of conservation concern, and agricultural practices. Our straightforward approach can be applied to many other regions, particularly those with rapid ecosystem responses to stochastic inter-annual climatic fluctuations that provide appropriate climate analogs for forecasting.

Galápagos Islands↗
USGS2022

Models combining multiple scales of inference capture hydrologic and climatic drivers of riparian tree distributions

Predicting species geographic distributions is key to managing invasive species, conserving biodiversity, and understanding species' environmental requirements. Species distribution models (SDMs) commonly focus on climatic predictors, but other environmental factors can also be essential, particularly for species with specialized habitats defined by hydrologic, topographic, or edaphic conditions (e.g., riparian, wetland, alpine, coastal, serpentine). Here, we demonstrate a novel approach for capturing strong effects of both hydrologic and climatic predictors in SDMs for riparian plants, by merging analyses targeted at environmental drivers within riparian ecosystems and across the western USA (3.8 × 10 6 km 2 ). We developed presence-background SDMs from five algorithms for three invasive riparian trees ( Tamarix ramossisima / chinensis [saltcedar], Elaeagnus angustifolia [Russian olive], and Ulmus pumila [Siberian elm]) and three native Populus spp. (cottonwoods). We used separate background datasets to develop models with different spatial scales of inference: (1) spatially filtered random points to represent available habitat across the study area and (2) target-group points from Salix (willow) occurrences to represent available riparian habitat. Random-background models captured hydrologic drivers of riparian tree distributions relative to the largely upland western USA, whereas Salix -background models captured climatic drivers within the context of riparian ecosystems. Combining predictions from the two backgrounds identified hydrologically suitable habitats within climatically suitable regions, resulting in fewer false “absences” than either background alone, improving predictions over previous SDMs, and providing more complete information to guide management decisions. Surprisingly, the predicted habitat for U. pumila , a newly recognized riparian invader, was as or more extensive than Populus deltoides / fremontii , T. ramossisima / chinensis , and E. angustifolia , the most common riparian tree complexes in the western USA. Watersheds constituting 20% of U. pumila predicted habitat contained no occurrence records, indicating high risk of future and unrecognized invasions. Combining models from random and ecosystem-specific target-group backgrounds may improve SDMs for species from many specialized habitats, providing a method to link predicted distributions to localized geographic features while capturing broad-scale climatic requirements.

western United States↗
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↗
USGS2023

Marmots do not drink coffee: Human urine contributions to the nitrogen budget of a popular national park destination

Reactive nitrogen (Nr) concentrations are higher than expected for mountain lakes in Rocky Mountain National Park, and for many years, high Nr concentrations have been attributed to atmospheric Nr deposition from regional and more distant emission sources, including combustion of fossil fuels and agricultural activities. Here, we estimated the contribution from a very local source, that of human urine, related to intensive use by visitors in Loch Vale Watershed (LVWS). Not only does urine convey hormones, pharmaceuticals, antibiotic-resistant bacteria, and antibiotic-resistant genes to the environment, but it also contributes Nr, which contributes to loss of biodiversity and eutrophication. Using caffeine as a specific marker for human urine, we compared the calculated maximum potential input of urine with that from wet atmospheric Nr deposition. The maximum potential input is a worst-case scenario. Nearly 30,000 and 45,000 people hiked the 4.0 km to the Loch, the lowest lake in LVWS, in June–September 2019 and 2020, respectively. Informal trails and informal latrine sites were mapped, and the contribution of human urine was calculated based on several assumptions, including that each visitor voided their bladder on the ground once per visit somewhere in Loch Vale. The resulting Nr input from urine in Loch Vale for the summer months of June through September was 0.02 kg Nr ha −1 , and prorated to a full year, the 2019 potential contribution of human waste was 0.06 kg ha −1 year −1 . These values are compared with June–September 1.2 kg Nr ha −1 from wet atmospheric deposition or annual measured 2019 deposition of 2.5 kg Nr ha −1 year −1 , to indicate a contribution of 2% Nr to the waters of Loch Vale from local human urine. Most Nr in this alpine and subalpine watershed is still attributable to emissions and subsequent wet atmospheric deposition, but a 2% contribution from human waste is not insignificant. In the very broadest sense, our results document an ecological disturbance from an unprecedented level of human activity in a protected and designated wilderness area. Local solutions to this local problem could include greater outreach to visitors of public lands about the consequences of their activities and installation of latrines.

Colorado↗
USGS2023

Integrating community science and agency-collected monitoring data to expand monitoring capacity at large spatial scales

Monitoring species to better understand their status, ecology, and management needs is a major expense for agencies tasked with biodiversity conservation. Community science data have the potential to improve monitoring for minimal cost, given appropriate analytical frameworks. We describe a framework for integrating data from the eBird community science platform with agency-collected monitoring data using a multistate occupancy model. Our model accounts for the structural differences across datasets and allows for estimation of both occupancy and breeding probabilities. The framework was applied to Common Loons ( Gavia immer ) in Washington State. A total of 766 sites had observation effort, of which 713 sites had only eBird effort, 26 sites had only Washington Department of Fish and Wildlife (WDFW) effort, and 27 sites had both. We predicted that the probability of occupancy was only 0.07 (95% Bayesian credible interval, BCI = 0.02–0.51) at the 2324 sites in our sampling frame, though the probability that Common Loons were breeding at occupied sites was 0.95 (95% BCI = 0.71–1.00). We found that probability of occupancy was positively related to waterbody size (probability of a positive effect = 0.88) and negatively related to an index of human influence (probability of a negative effect = 0.94). We found that probability of breeding at occupied sites was positively related to tree canopy cover (0.86), negatively related to elevation (0.99), and negatively related to barren, scrub/shrub, and herbaceous land cover (0.98). We found that state agency biologists were 16 times more likely to detect breeding Common Loons at a site than were eBird users (0.94, 95% BCI = 0.78–0.99 for agency biologists vs. 0.08, 95% BCI = 0.06–0.10 for eBird users). However, the amount of effort expended by eBird users meant that they confirmed Common Loons at 94 sites while agency biologists confirmed them at just 24 sites, although evidence of reproduction was only contributed by agency biologists. Our results provide a better understanding of the distribution of Common Loons in Washington, while further demonstrating that community science data can be a valuable complement to agency-collected data, if appropriate frameworks are developed to integrate these data sources.

Ecosphere↗
USGS2023

Identifying drivers of population dynamics for a stream breeding amphibian using time series of egg mass counts

The decline in amphibian populations is one of the starkest examples of the biodiversity crisis. For stream breeding amphibians, alterations to natural flow regimes by dams, water diversions, and climate change have been implicated in declines and extirpations. Identifying drivers of amphibian declines requires long time series of abundance data because amphibian populations can exhibit high natural variability. Multiple population viability analysis (MPVA) models integrate abundance data and share information from different populations to estimate how environmental factors influence population growth. Flow alteration has been linked to declines and extirpations in the Foothill Yellow-legged Frog ( Rana boylii ), a stream breeding amphibian native to California and Oregon. To date, no study has jointly analyzed abundance data from populations throughout the range of R. boylii in an MPVA model. We compiled time series of egg mass counts (an index of adult female abundance) from R. boylii populations in 36 focal streams and fit an MPVA model to quantify how streamflow metrics, stream temperature, and surrounding land cover affect population growth. We found population growth was positively related to stream temperature and was higher in the years following a wet year with high total annual streamflow. Density dependence was weakest (i.e., carrying capacity was highest) for streams with high seasonality of streamflow and intermediate rates of change in streamflow during spring. Our results highlight how altered streamflow can further increase the risk of decline for R. boylii populations. Managing stream conditions to better match natural flow and thermal regimes would benefit the conservation of R. boylii populations.

California, Oregon↗
USGS2023

Fire regime shapes butterfly communities through changes in nectar resources in an Australian tropical savanna

Fire-dependent savanna provides key habitat for butterflies globally, but we know little about how fire regimes, including fire frequency and season, affect them. These impacts are likely to be primarily indirect, through changes in overall habitat structure, the abundance of larval host plants, and/or the provision of nectar resources for adults. We examined the relationships among fire regime, butterfly abundance and diversity, and vegetation structure and floral resources within a long-term fire experiment near Darwin in the Australian monsoon tropics. We surveyed butterflies and floral resources throughout the 2019–2020 wet season in three replicate plots of each of six experimental treatments that had been operating for 15 years. All plots subject to fire had been burned in the previous dry season. We observed 24 butterfly species and 280 individuals representing all five butterfly families found in Northern Australia. Butterfly abundance was highest under early dry-season (June) fire regimes (mean = 11.9 individuals per plot survey) compared with a late dry-season (October) regime (mean = 6.7) and in the long-term absence of fire (mean = 5.3), and this was correlated with the abundance of floral resources. The distribution of butterflies was also highly associated with floral resources within plots regardless of fire treatment. Butterfly species richness was significantly higher in early dry-season (mean = 6.8) compared with unburned (mean = 3.3) plots but did not differ between early and late dry-season (mean = 4.7) plots. Butterfly and floral diversity were similar across all early dry-season fire treatments regardless of whether they had been burned every 1, 2, 3, or 5 years. Our finding that early dry-season burning promotes butterfly diversity and abundance by increasing the supply of nectar resources has important implications for biodiversity management more broadly, given that nectar is a critical resource for many animal taxa.

Territory Wildlife Park↗
USGS2024

Spatial extent drives patterns of relative climate change sensitivity for freshwater fishes of the United States

Assessing the sensitivity of freshwater species to climate change is an essential component of prioritizing conservation efforts for threatened freshwater ecosystems and organisms. Sensitivity to climate change can be systematically evaluated for multiple species using geographic attributes such as range size and climate niche breadth, and using species traits associated with climate change sensitivity. These systematic evaluations produce relative rankings of species sensitivity to aid conservation prioritization and to identify relatively sensitive species that may otherwise be understudied or overlooked. Due in part to biogeographic constraints, species assemblages change across regions and spatial extents; yet, the degree to which spatial factors influence relative rankings of species sensitivity is unclear. The spatial extent of multispecies analyses may alter relative rankings of species climate sensitivity; alternatively, relative climate sensitivity may be conserved among spatial scales, resulting in consistent identification of sensitive species among regions and spatial extents. We investigated how spatial extent influences our understanding of relative climate sensitivity for 137 native freshwater fishes of the United States that were representative of taxonomic, trait, and geographic diversity. Using publicly available occurrence data from the Global Biodiversity Information Facility, we calculated a systematic, geographically derived index of climate change sensitivity for study species at national and regional extents, including within four major hydrologic subregions of the United States. We examined the effects of spatial extent on the relative ranking of climate sensitivity among species, and we explored relationships among climate sensitivity, species traits, and conservation status at regional and national extents. We found that climate sensitivity rankings of species were influenced by spatial extent in some specific instances, but that relative rankings were largely conserved across spatial scales. However, correlations among geographically derived climate sensitivity rankings and species traits associated with climate sensitivity were variable across scales and regions, suggesting that links between geographic rarity and species traits may be scale-dependent in some cases. Finally, we found few associations between climate sensitivity and current conservation status among species. Systematic approaches to quantifying climate sensitivity may offer an opportunity to identify sensitive but overlooked species for pre-listing actions such as monitoring or conservation agreements.

Ecosphere↗
USGS2024

Dryland fungi are spatially heterogeneous and resistant to global change drivers

Fungi are considered particularly important in regulating the structure and function of dryland ecosystems, yet the response of dryland fungal communities to global change remains notably understudied. Without a clear understanding of how fungi respond to global change drivers, mitigation plans—required for biodiversity and ecosystem service conservation and restoration—are impossible to develop. In this study, we asked the following: (1) How does the fungal community respond to the individual and interactive effects of physical disturbance and drought in a heterogeneous dryland landscape comprised of drought-adapted shrubs separated by adjacent open areas of soil? (2) What are the larger scale impacts of this response? We assessed fungal communities (using fungal-specific DNA metabarcoding analyses) of surface soil samples in an in situ global change experiment that included disturbance and drought in a full factorial design in the northern extent of the Chihuahuan Desert. We found that the fungal community was spatially heterogenous and remarkably resistant to disturbance and drought. We also show that dryland soils harbor high shares of facultative pathogenic and obligately pathogenic fungal taxa, with several concerning taxa reaching high relative abundances under drought. Our results suggest that the fungal community is highly influenced by microclimatic conditions associated with the presence or absence of vegetation. Moreover, our results imply that the fungal community in our experiment was already adapted to the magnitude of stress imposed by two years of experimental disturbance and drought treatments. Overall, our study shows that the fungal community is spatially heterogeneous and resistant to global change drivers and houses many fungal species known for being stress tolerant and pathogenic.

New Mexico↗
USGS2025

Elk personality and anthropogenic food subsidy: Managing conflict and migration loss

The continued decline of long-distance ungulate migrations threatens to decouple important ecological processes that increase biodiversity and wildlife abundance. Past research has focused on preserving migration paths where habitat fragmentation and loss disrupt movement corridors. However, shifting residency-migration trade-offs are the stronger driver of migration loss in some populations. Suburban residential developments may provide ungulates with anthropogenic food sources and refuge from predators, which can increase population growth among short-distance migrants relative to long-distance migrants. This trend can increase wildlife vehicle collisions and other human–wildlife conflicts while simultaneously reducing hunting opportunities. Yet, individual animals vary in their tolerance of human disturbance. We investigated how interindividual variation relative to conflict and human habituation influences elk migration and space use on shared winter range. We used a clustering algorithm applied to GPS collar data to identify elk use of anthropogenic food resources in suburban habitat. Cluster locations identified all known anthropogenic subsidy locations during the study period. Elk that used suburban anthropogenic food sources also migrated 60% shorter distances between summer and winter ranges than elk with no known use of these food subsidies. Elk use of protected wintering grounds was spatially structured such that conflict-prone, short-distance migrants disproportionately used areas with more human activity. Clustering algorithms applied to GPS collar data may allow managers to identify foci of concentrated use that generates human–wildlife conflict, and where prion deposition and environmental contamination facilitate the spread of chronic wasting disease, particularly in suburban areas with anthropogenic food subsidies. The apparent spatial structuring of shared winter range according to the conflict potential and migration strategy of individual elk may also permit managers to assess relative recruitment among cryptic population segments using different migration strategies and facilitate targeted, adaptive management actions. These associations between conflict, human habituation, and migration shed light on the urbanization of wildlife species, inform efforts to manage human–wildlife conflict and disease spread, and emphasize that a multipronged approach beyond maintaining habitat corridors may be necessary to conserve long-distance migrations for species that can become human-habituated.

Wyoming↗
USGS2020

Direct and indirect effects of a keystone engineer on a shrubland-prairie food web

Keystone engineers are critical drivers of biodiversity throughout ecosystems worldwide. Within the North American Great Plains, the black‐tailed prairie dog is an imperiled ecosystem engineer and keystone species with well‐documented impacts on the flora and fauna of rangeland systems. However, because this species affects ecosystem structure and function in myriad ways (i.e., as a consumer, a prey resource, and a disturbance vector), it is unclear which effects are most impactful for any given prairie dog associate. We applied structural equation models (SEM) to disentangle direct and indirect effects of prairie dogs on multiple trophic levels (vegetation, arthropods, and birds) in the Thunder Basin National Grassland. Arthropods did not show any direct response to prairie dog occupation, but multiple bird species and vegetation parameters were directly affected. Surprisingly, the direct impact of prairie dogs on colony‐associated avifauna (Horned Lark [ Eremophila alpestris ] and Mountain Plover [ Charadrius montanus ]) had greater support than a mediated effect via vegetation structure, indicating that prairie dog disturbance may be greater than the sum of its parts in terms of impacts on localized vegetation structure. Overall, our models point to a combination of direct and indirect impacts of prairie dogs on associated vegetation, arthropods, and avifauna. The variation in these impacts highlights the importance of examining the various impacts of keystone engineers, as well as highlighting the diverse ways that black‐tailed prairie dogs are critical for the conservation of associated species.

Wyoming↗
USGS2021

Intraspecific variation mediates density dependence in a genetically diverse plant species

Interactions between neighboring plants are critical for biodiversity maintenance in plant populations and communities. Intraspecific trait variation and genome duplication are common in plant species and can drive eco-evolutionary dynamics through genotype-mediated plant–plant interactions. However, few studies have examined how species-wide intraspecific variation may alter interactions between neighboring plants. We investigate how subspecies and ploidy variation in a genetically diverse species, big sagebrush ( Artemisia tridentata ), can alter the demographic outcomes of plant interactions. Using a replicated, long-term common garden experiment that represents range-wide diversity of A. tridentata , we ask how intraspecific variation, environment, and stand age mediate neighbor effects on plant growth and survival. Spatially explicit models revealed that ploidy variation and subspecies identity can mediate plant–plant interactions but that the effect size varied in time and across experimental sites. We found that demographic impacts of neighbor effects were strongest during early stages of stand development and in sites with greater growth rates. Within subspecies, tetraploid populations showed greater tolerance to neighbor crowding compared to their diploid variants. Our findings provide evidence that intraspecific variation related to genome size and subspecies identity impacts spatial demography in a genetically diverse plant species. Accounting for intraspecific variation in studies of conspecific density dependence will improve our understanding of how local populations will respond to novel genotypes and biotic interaction regimes. As introduction of novel genotypes into local populations becomes more common, quantifying demographic processes in genetically diverse populations will help predict long-term consequences of plant–plant interactions.

Idaho, Utah↗
USGS2024

Integrated distance sampling models for simple point counts

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new “ IDS() ” function in the R package unmarked . Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

Ecology↗
USGS2024

Abundance-mediated species interactions

Species interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly center around occupancy states. Here, we use simulations to illuminate the inadequacies of modeling species interactions solely as a function of occupancy, as is common practice in ecology. We demonstrate erroneous inference into species interactions due to error in parameter estimates when considering species occupancy alone. To address this critical issue, we propose, develop, and demonstrate an abundance-mediated interaction framework designed explicitly for modeling species interactions involving two or more species from detection/non-detection data. We present Markov chain Monte Carlo (MCMC) samplers tailored for diverse ecological scenarios, including intraguild predation, disease- or predator-mediated competition, and trophic cascades. Illustrating the practical implications of our approach, we compare inference from modeling the interactions in a three-species network involving coyotes ( Canis latrans ), fishers ( Pekania pennanti ), and American marten ( Martes americana ) in North America as a function of occupancy states and as a function of abundance. When modeling interactions as a function of abundance rather than occupancy, we uncover previously unidentified interactions. Our study emphasizes that accounting for abundance-mediated interactions rather than simple co-occurrence patterns can fundamentally alter our comprehension of system dynamics. Through an empirical case study and comprehensive simulations, we demonstrate the importance of accounting for abundance when modeling species interactions, and we present a statistical framework equipped with MCMC samplers to achieve this paradigm shift in ecological research.

Ecology↗
USGS2025

The relative influence of climate extremes and species richness on the temporal variability of bird communities

Understanding the relationship between biodiversity and ecological stability is increasingly urgent as rapid species extinction continues. Though evidence of positive diversity–stability relationships is accumulating, empirical results are inconsistent, and effect sizes tend to be small, raising questions about relative contributions of intrinsic (i.e., species composition/interactions) and extrinsic (i.e., environmental) drivers of stability. Community stability may be more strongly influenced by environmental conditions than by community diversity in some contexts, yet little is known about the comparative importance of diversity and climate means, extremes, and variability in regulating stability. We used a half-century of continental-scale bird data to quantify avian community temporal variability (a metric often used to approximate ecological stability) at 1379 sites and compared relative effects of climatic variables and species richness. We found that extreme heat and extremely low precipitation at decadal scales are associated with high bird community variability and these climate variables outperformed species richness in terms of variance explained and magnitude of effect. This provides empirical support for the theoretical concept that, at a continental, decadal scale, environmental conditions can play a larger role than intrinsic factors in determining community stability. Our findings also increase understanding of how climate extremes cause diverse ecological responses.

Ecology↗
USGS2026

Fragmentation as a population rate-changer: A field experiment

Experimental and observational studies of effects of fragmentation on biodiversity and population dynamics have produced mixed results, with some reviews concluding strong evidence of negative effects and others concluding small positive effects. In addition, many factors (e.g., interspecific interactions, edge effects, nutrient cycling) have been identified as potential explanations underlying the various results. We carried out a population-level fragmentation study on meadow voles, focusing on changes in vital rates caused by reduced movements in experimental 2-patch systems. We developed predictions of fragmentation effects by decomposing rates of apparent survival and recruitment (parameters directly estimated using capture–recapture models) into components that do and do not include movement. Fragmentation was predicted to reduce movement rates, and reduced movement was predicted to increase apparent survival rates, decrease immigration rates, and slightly increase population growth rates. We found evidence of increased adult and juvenile apparent survival and adult population growth rate on fragmented grids, whereas results for recruitment were ambiguous and did not support our predictions. The recruitment results led to the hypothesis that immigration into suitable habitat may not be reduced by fragmentation as much as permanent emigration from that habitat. A focus on effects of reduced movement on vital rates should be a reasonable starting point for investigations of fragmentation effects. This focus suggests that explanations underlying fragmentation effects will require additional effort devoted to isolating movement components of vital rates.

Ecology↗