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USGS2025

A system dynamics model to understand the integrated ecological and human dimension aspects of wildlife health and disease management

Chronic wasting disease (CWD) presents an ongoing challenge for the management of deer populations and sustaining harvest opportunities across North America. Existing disease models often fail to fully capture the complex interplay between disease dynamics, host ecology, and socio-economic factors. We developed a comprehensive system dynamics (SD) model that integrates demographic, epidemiological, ecological, and socio-economic processes within a single model to more fully characterize the complex network of causal feedbacks throughout the system. The model was calibrated using a Bayesian approach that incorporates prior knowledge to generate biologically interpretable outcomes, even with sparse data. For estimating the joint posterior distribution of model parameters, we leveraged time series of deer abundance, harvest composition, genetic profiles, CWD surveillance, and hunter demographics and behavior. Model outputs reproduced key system behaviors, including observed CWD prevalence trends, deer population dynamics, and hunter license purchasing patterns. Model predictions were most sensitive to parameters governing initial deer population size and recruitment. While model predictions generally aligned with observed data, discrepancies in early CWD detection and overestimation of the reactivation of long-inactive hunters reflect data limitations and modeling challenges. Key results suggest that indirect transmission is necessary to explain observed prevalence, that transmission is moderately density-dependent, and that observed population-level genetic shifts driven by CWD may play a role in transmission and progression. The SD modelling approach enabled estimation of difficult-to-measure parameters and identified potential leverage points for management—such as prioritizing increasing participation in antlerless harvest of existing hunters over the recruitment of new hunters. This integrated modeling approach offers a flexible foundation for adaptive wildlife disease management and emphasizes the value of unifying biological and human dimension processes to better inform effective, evidence-based policy.

BioRxiv↗
USGS2025

A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters

Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.

BioRxiv↗
USGS2025

Understanding abundances and behaviors of shorebirds in coastal Louisiana

Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and provision of wildlife habitat. Over time, barrier islands may become eroded and experience land loss, which can require management actions to restore island integrity. Barrier island restoration can create or modify habitats, which can impact the organisms depending on them. Our objective was to understand how the abundance and behaviors of a suite of shorebird species responded to restoration and habitat factors at two restored sites in coastal Louisiana (USA). For five focal species, we used abundance from the breeding and non-breeding seasons as well as breeding, foraging, and maintenance behaviors as response variables in boosted regression tree models to determine the importance of various geospatial and remotely sensed predictor variables related to restoration. Across sites and species, remotely sensed variables, particularly a brightness index, tended to be more important than restoration phases as predictors of bird abundance and behavior. Our results suggest that sediment composition, moisture, and vegetative cover are related to shorebird coastal habitat selection, although the direction and strength of relationships differ among these variables and our focal species. Tying these remote sensing metrics to restoration design and management actions can help land managers better understand factors that attract and benefit birds. Additional research can advance understanding in how remote sensing can be used to monitor the availability of functional habitats for shorebirds.

BioRxiv↗
USGS2026

A chromosome-level genome assembly of a vernal pool specialist amphibian, the Western Spadefoot, Spea hammondii

We assembled and annotated a chromosome-level reference genome for the Western Spadefoot, Spea hammondii (Anura, Scaphiopodidae) representing one of only three amphibians included in the California Conservation Genomics Project (CCGP). Spea hammondii is a vernal pool breeding anuran native to California and northwestern Baja California which has undergone both range contractions and local extirpations across its distribution, primarily due to habitat loss and degradation and drought. The species is recognized by the state of California as a Species of Special Concern and is proposed for listing under the United States Endangered Species Act. Using the established CCGP pipeline, this S. hammondii genome was produced using Pacific Biosciences HiFi long-reads and Omni-C proximity ligation, resulting in a de novo genome assembly 1.14 Gb in length, distributed across 479 scaffolds (scaffold N50 = 120.8 Mb; largest scaffold = 183.6 Mb) with a BUSCO completeness score of 90.9% using a conserved tetrapod ortholog set. Our assembly shows high base accuracy (QV = 63.7) and low frameshift error in coding regions (QV 50.42). Annotation of this genome yielded 20,434 genes with a BUSCO completeness score of 94.7%. This reference genome, in combination with range-wide resequencing data from CCGP, will facilitate statewide population genomic assessments to delineate conservation units, quantify inbreeding and genomic load, and test for adaptive variation associated with vernal pool hydrology and drought tolerance, all of which are important considerations in the proposed federal listing.

BioRxiv↗
USGS2026

A snapshot of Joshua tree (Yucca brevifolia and Y. jaegeriana) stand structure in the eastern Mojave Desert of California

The long-term viability of the iconic Joshua tree of the Mojave Desert is being evaluated. In 2022, we measured the abundance and heights of Joshua tree stems on 62 1000 m2 plots in the eastern Mojave Desert of California. The 2022 plots were represented by 33 plots in a population of western Joshua trees (Yucca brevifolia) and 29 plots in a population of eastern Joshua trees (Y. jaegeriana). Five plots had no Joshua trees; two of which in the western Joshua tree population were destroyed by fire. The 57 plots with Joshua trees supported 627 stems ranging from stems less than 25 cm to mature trees. The plots were examined by abundance and four size classes of the stems, as indicated by their height and indicative of their reproductive status. The western Joshua tree population had more stems (407) than the eastern population (220 stems) although the median difference was not significant. The western population had significantly more stems in pre-reproductive size classes, juvenile (> 25 cm to one-meter, p = 0.001) and sub_adult (> one- to two-meters, p = 0.001), than the eastern population but significantly fewer adult (> two-meters, p < 0.001) stems. The eastern population had significantly greater mean height of adult trees (302 cm +/- 75.3 cm) than the western population (263 cm +/- 52.9 cm) and a larger proportion of stems taller than two-meters (56%) than the western population (39%). In contrast, the western population has 77% of its population in younger size classes (> 25 cm to < 2 meters). These abundance and size class measures alone do not predict whether either population has sufficient natural stand regeneration for long term persistence, but the younger size class structure of the western population suggests greater long-term resilience than for the eastern population.

BioRxiv↗
USGS2026

Genomic structural variation rescues a classic biological invader from a population bottleneck

Invasion genetics presents a classic paradox: how do species successfully spread despite severe population bottlenecks? The brown treesnake ( Boiga irregularis ) in Guam represents a striking example of this phenomenon, having been introduced with only a handful of individuals. We show that the population endured an extreme bottleneck, with roughly half of the genome exhibiting runs of homozygosity, comparable to species of conservation concern. Despite this, we uncovered extensive diversity in the form of nearly 19,000 genomic structural variants, which affect almost eight times more of the genome than single-nucleotide variants and provide material for ‘rescuing’ the population from inbreeding-driven declines. Structural variant density was highest in gene promoters, where recombination and DNA repair often occur, providing a mechanism for rapid evolution of gene-linked diversity. This diversity is enriched in genes vital for adaptive immunity and olfaction, suggesting genomic diversity in key chromosomal regions can rescue populations from inbreeding. This work has critical implications for invasion biology and conservation genetics practitioners.

BioRxiv↗
USGS2026

Stopover population estimate and migration ecology of Red Knots C. c. rufa at the Delaware Bay, USA, 2025

Red Knots ( Calidris canutus rufa ) rely on Atlantic horseshoe crab ( Limulus polyphemus ) eggs in the Delaware Bay to refuel during northward migration. Intensive harvest of horseshoe crabs in the 1990s contributed to declines in Red Knot numbers. In 2013, the Atlantic States Marine Fisheries Commission adopted an Adaptive Resource Management (ARM) framework to balance sustainable horseshoe crab harvest with ecosystem integrity and Red Knot recovery, requiring annual stopover population estimates. We estimated the 2025 passage population of Red Knots at Delaware Bay using a Bayesian analysis of a Jolly–Seber mark–resight model which accounts for population turnover and imperfect detection. We also evaluated change in migration timing between 2011 and 2025 with model-derived estimates of arrival at the Delaware Bay each year. The 2025 passage population was 54,043 individuals (95% credible interval: 47,926–61,928), an increase of approximately 17% over 2024 and only the second year since 2011 to exceed 50,000 individuals. Despite the increase, overlapping credible intervals across years indicate a stable stopover population. Migration timing has remained consistent, with 50% of the population typically arriving by 18 May and no evidence of advancement since 2011. These findings provide meaningful input for the ARM framework, supporting sustainable harvest of horseshoe crabs while maintaining adequate foraging opportunities for Red Knots and other shorebirds.

BioRxiv↗
USGS2026

Status of round goby invasion fronts in New York and Quebec: Implications for Lake Champlain

Invasive round goby Neogobius melanostomus have advanced eastward through the state of New York and provinces of Ontario and Quebec over the past two decades and are approaching Lake Champlain, one of the largest lakes in North America. This manuscript describes international efforts to monitor round goby populations during 2021–2025 on (a) the southern approach to Lake Champlain via the Hudson River and Champlain Canal, and (b) the northern approach to Lake Champlain via the Saint Lawrence River and Richelieu River. Monitoring utilized environmental DNA (eDNA), backpack electrofishing, beach seining, benthic trawling, and viral hemorrhagic septicemia virus (VHSV) testing. In the Champlain Canal, round goby were captured as far north as the downstream side of the C1 dam (97 kilometers [km] from Lake Champlain) while eDNA detections occurred as far north as the upstream side of the C2 dam (90 km from Lake Champlain). In the Richelieu River, round goby were captured as far south as Saint-Marc-sur-Richelieu (82 km from Lake Champlain) while the southern-most eDNA detections occurred near the Canadian side of the international border (4 km from Lake Champlain). Water temperature influenced habitat usage of round goby in the Champlain Canal, with catch rates in near-shore areas declining at < 10 °C. All VHSV test results were non-detections at the mouth of the Richelieu River, while one positive and two inconclusive results occurred along the Champlain Canal. Together, these data have informed multiple mitigation measures and have implications for management of aquatic invasive species across North America.

BioRxiv↗
USGS2026

Columbia Basin pygmy rabbit recovery planning through structured decision making

The endangered Columbia Basin pygmy rabbit (CBPR) faces multiple threats, particularly increasing risk of larger and more intense wildfires due to climate change, emerging disease, and sagebrush habitat loss due to agriculture and development. Through the use of conservation breeding, the CBPR wild population grew from a low of 16 individuals captured in 2001 to over 100 individuals in two subpopulations in 2024. However, these subpopulations are geographically proximate, with potential risk that both subpopulations could be affected by a single wildfire or disease event. Additionally, a succession of setbacks in the breeding program has prompted a natural re-evaluation point for the CBPR conservation program. We undertook a structured decision-making (SDM) process with participants from both Washington Department of Fish and Wildlife (WDFW) and US Fish and Wildlife Service (USFWS) to develop a strategy that is sustainable and implementable for guiding management in the coming decades across the range of the CBPR, taking into account changing conditions and updated information. A population model that incorporated both demographic and high impact event uncertainties was developed to test how alternative strategies – defined by conservation breeding program, vaccination, and translocation components – affect CBPR population growth and cost objectives. Based on analysis of the model results, we identified the following actions that appear to have the greatest potential to allow WDFW and USFWS to meet their conservation objectives for CBPR: Continue conservation breeding program, and possibly expand to include an island subpopulation (an isolated, unfenced area that can serve as a source for rabbits while requiring fewer management inputs) Continue Rabbit Hemorrhagic Disease Virus (RHDV2) annual vaccinations in both breeding and wild populations When juveniles are available for translocation, prioritize recovery areas that are in the establishing phase In addition, while not analyzed explicitly in the model, discussions during the SDM process led to the identification of the following actions, which the group considered to have potential to benefit the CBPR either directly or indirectly: Increase the amount of suitable habitat available to pygmy rabbits Increase protections for existing and potential recovery areas Design future monitoring to better estimate survival and reproduction, with an emphasis on understanding how these vital rates vary between wild and semi-captive individuals, between vaccinated and unvaccinated individuals, and as a function of habitat factors

BioRxiv↗
USGS2026

A genomic tool to tackle cryptic diversity demonstrates the potential for off-target use of GT-seq panels

A comprehensive understanding of life history is vital to successful species conservation and management. When different life history stages are accompanied by considerable morphological or cryptic variation, such as the egg and larval phases exhibited by most fishes, genomic tools are essential for identifying species so that early-life ecology questions can be studied. Genotyping-in-thousands by sequencing (GT-seq) has recently emerged as a targeted and efficient approach for species identification. We leveraged existing genomic and transcriptomic data to develop a GT-seq panel capable of differentiating the members of the Coregonus artedi complex, a radiation of salmonids in the Laurentian Great Lakes whose members are indistinguishable with mitochondrial DNA barcoding loci and are the focus of bi-national conservation initiatives. Our panel of 494 loci was able to assign fishes in the C. artedi complex to species and lake. We examined cross-amplification in other coregonines with overlapping distributions and found that congeneric Lake Whitefish ( C. clupeaformis ) cross-amplified at 94% of loci and confamilial Round and Pygmy Whitefish ( Prosopium spp.) cross-amplified at 42% and 38% of loci, respectively. We adapted bioinformatic probes to account for Prosopium -specific variants including 22 new SNPs and developed a whitelist of 428 SNPs capable of distinguishing these whitefishes. Finally, we demonstrated performance by identifying 3,066 coregonine larvae and juveniles collected in spring 2019-2021 from Lake Superior. These results hold promise for future insights into the species-specific ecology of early life coregonines and demonstrate the flexibility of GT-seq panels, which may cross-amplify hundreds of informative genome-wide loci in related taxa.

BioRxiv↗
USGS2026

Comparative genomics reveals potential mechanisms of invasion in Phragmites australis (common reed)

Biological invasions are transforming ecosystems worldwide, yet the genomic bases enabling certain species to dominate new environments remain poorly understood. Phragmites australis , a widespread wetland grass with invasive and native subspecies co-occurring in North America, provides a powerful system to investigate genomic mechanisms of invasiveness. We generated independent chromosome-scale genome assemblies for invasive P. australis ssp. australis and co-occurring native ssp. americanus and used comparative genomic and transcriptomic analyses to identify lineage-specific innovations associated with invasive success. The invasive subspecies exhibits genomic novelties through functionally-biased single-copy orthologs, intronless genes, and subgenome expression asymmetry, along with a stress-ready basal transcriptome relative to the native subspecies. Following the removal of aboveground shoots (“cutback”), which measures the ability to recover from damage, the invasive subspecies undergoes stronger transcriptional reprogramming, increased shoot production, and higher biomass accumulation compared to the native. It also displays expansion of gene families and coordinately expressed gene modules that support resource mobilization, growth responses to light, and stress tolerance. Beyond Phragmites , comparative analyses across multiple grass genomes, including eight invasive species with related non-invasive species, revealed repeated expansion of gene families associated with abiotic stress tolerance and developmental regulation, suggesting convergent adaptive strategies in the grass family for invasive success. Together, these results demonstrate genomic architecture linked to invasion success and highlight potential targets for managing invasive grasses.

BioRxiv↗
USGS2026

Distributions of host heterogeneity in susceptibility show signatures of pathogen geographic structure in an insect baculovirus

Segregated variation between populations is a fundamental evolutionary process leading to parasite specialization, yet the resulting impacts on infection heterogeneity within populations are theoretically and empirically understudied. We asked whether the distribution of host susceptibility to infection within populations carries the signatures of geographic structure from pathogen local adaptation, maladaptation, or generalism in a nuclear polyhedrosis virus that infects the Gulf Fritillary butterfly Dione vanillae . For this virus, there is genetic support for two geographically distinct groups within San Diego County, based on whole genome sequencing of 16 virus isolates. Reciprocal laboratory infections showed evidence of two contrasting viral life history strategies: a ‘generalist’ phenotype that consistently infected variable hosts and a ‘specialist’ that performed slightly better in its local host population. As predicted by our theoretical model, the more consistent infection displayed by the generalist across populations corresponded to lower heterogeneity in susceptibility within populations, modeled as gamma distribution. Furthermore, the generalist phenotype was collected over a wider geographic range despite having a tenfold-lower mean infection rate than the specialist, suggesting that a strategy of more consistent infection provides key fitness advantages across diverse host populations. Intriguingly, when there is variation in host susceptibility, interpretations of pathogen local adaptation are dose-dependent. Measuring infectivity across multiple doses enables estimation of the whole distribution of susceptibility, which provides more reliable identification of pathogen specialization to its local host. Our work demonstrates how trait distributions and not only their mean values can carry quantifiable signatures of eco-evolutionary processes in interspecific interactions.

BioRxiv↗
USGS2026

A Lake Charr pangenome reveals highly conserved Ohnologs as drivers of phenotypic diversity

Whole-genome duplication (WGD) is hypothesized to spur evolutionary diversification by producing genome-wide duplicate gene sets (Ohnologs) that are initially functionally redundant but can diverge markedly as the effects of relaxed selection accumulate over time. However, the underlying mechanisms remain unclear, in part because genomic studies often reconstruct Ohnolog evolution over millions of years, during which subsequent mutations can obscure deep-time signals. Investigating the relationship between Ohnolog evolution and diversification on a contemporary timescale offers clearer insights. We explore this relationship in Lake Charr ( Salvelinus namaycush ), where ∼10% of genes are retained highly conserved polyploid duplicates following the Salmonid-Specific Fourth Round WGD. Using 31 chromosome-level assemblies of Lake Charr from morphologically and ecologically diverse populations, joined into a pangenome graph, we characterized 189,555 structural variants (SVs) that were significantly less likely to affect genes retained as sequence-conserved Ohnolog pairs, nuancing the hypothesis that gene redundancy, relaxed selection, and functional diversification are intertwined. However, we found that SVs affecting such conserved Ohnologs may be potent drivers of adaptive evolution. Notably, we identified a putative 938-Kb interchromosomal translocation containing 25 genes with highly conserved Ohnologs in a paralogous (but untranslocated) genomic block. This putative translocation appears to have facilitated Ohnolog divergence in ankrd11 and hp , genes putatively linked to craniofacial and lipid metabolic diversity in sympatric Lake Superior morphs. This research reveals that conserved Ohnologs previously presumed to be redundant remain a reservoir for adaptive change.

BioRxiv↗
USGS2026

Decision analysis in support of proactive planning for chronic wasting disease in Vermont, USA

Chronic wasting disease (CWD), a fatal, transmissible disease in white-tailed deer ( Odocoileus virginianus ) and related species, is spreading across North America but has not yet been detected in Vermont, United States (U.S.). The Vermont Department of Fish and Wildlife, along with partner agencies, wants to develop a proactive prevention and response plan in anticipation of the eventual detection of the disease. Between September 2023 and September 2025, staff from the U.S. Geological Survey and the University of Vermont facilitated a structured decision-making (SDM) process with seven State and Federal agencies that have jurisdiction over some aspect of CWD management in Vermont. The aim of this process was to generate and evaluate alternative response plans against a range of long-term objectives important to the agencies. To aid in the evaluation of the alternatives, we developed a linked set of models for white-tailed deer population and disease dynamics, hunter participation and health, forest health, economic consequences, and agricultural opportunities related to the actions being contemplated as part of the response plan. We evaluated over 256 different permutations of management actions and used multi-criteria decision analysis, a branch of decision analysis designed to help decision makers navigate tradeoffs among competing objectives, to summarize the performance of those alternative strategies against the desired outcomes. Proactive actions—those designed to slow the arrival of CWD to Vermont—were moderately effective, but the most important proactive action was surveillance to detect the disease early after arrival, which triggered response actions after detection. With the insights generated by the SDM process and the results of the analyses, the participating agencies were able to identify a preferred strategy and outline the elements of a proactive response plan. This report describes the SDM process, the technical details of the modeling work, and the results of the analyses. It is intended to serve as the technical basis for Vermont’s response plan.

BioRxiv↗
USGS2026

Classifying and mapping wetland vegetation assemblages in coastal Louisiana with Landsat imagery, 1985-2025

The tidal wetlands of Louisiana comprise about 25% of those found throughout the conterminous United States yet estimates of wetland loss rates in the region between 1932 and 2016 have exceeded 60 km 2 yr -1 . To mitigate further degradation and wetland loss in the region, a globally unprecedented $50B, 50-year plan for coastal Louisiana is driving restoration efforts, and demand exists from multiple stakeholders for regularly updated, regional-scale, accurate land cover information. We used machine learning (random forests; RF) and cloud computing to develop a new Landsat-based, marsh vegetation community geospatial dataset. The dataset depicts wetland vegetation community types defined in a previous study at annual (1985–2025) time steps at 30-m resolution. An RF algorithm was used to integrate training samples with feature variables derived from Landsat imagery, and the resulting geospatial data product achieved an overall correct classification rate of 78%. The approach for development of the land cover dataset presented here has potential for application in other coastal wetland habitats throughout the world.

BioRxiv↗
USGS2026

Southern (California) sea otter population status and trends at San Nicolas Island, 2023–winter 2026

The southern sea otter ( Enhydra lutris nereis ) population at San Nicolas Island, California, has been monitored annually since the translocation of 140 sea otters to the island was completed in 1990. Monitoring efforts have varied in frequency and method across years. In 2017, in accordance with the National Defense Authorization Act for Fiscal Year 2016, the U.S. Navy and the U.S. Fish and Wildlife Service formally initiated a sea otter monitoring and research plan to determine the effects of military readiness activities on the growth or decline of the southern sea otter population at San Nicolas Island. The monitoring program, at its basic level, includes quarterly seasonal surveys of population abundance, distribution, and foraging activity. This report presents data from the program with a focus on the recent three years from winter 2023 through winter (February) 2026. From 2023 to 2026, we measured an 8.1-percent per annum decrease in population abundance (95-percent confidence interval =1.1–14.6 percent), with 106 total individuals counted as of February 2026. Historically, sea otter habitat usage at San Nicolas Island was concentrated on the west end of the island. Between 2017 and 2019, we observed increased seasonal usage of the north and south sides of the island, and in 2020-2022, a large (approximately 30-40 individuals) group of sea otters (raft) took up residence off the east end. During 2023-2026 the east end raft disappeared, and sea otters returned to their historical habitat usage patterns at the west end of the island. Foraging data were collected from summer 2023 to winter 2026 on a total of 461 foraging dives in 32 foraging bouts, and the majority of identified prey on successful dives (n=325) were sea urchins (124) followed by snails (48), bivalves (41) and crabs (23). One lobster and one octopus were also identified among the sea otter prey items. We combined these data with data from 2020-2022 to estimate overall energy intake rates that averaged 7.7 kilocalories per minute (95-percent credible interval =6.6–9.1 kilocalories per minute). These results can be useful to the planning of future monitoring and research of sea otters at San Nicolas Island.

BioRxiv↗
USGS2026

Movement mechanisms explain current animal density patterns and predict their reorganization under global change

Aim: To test whether individual movement mechanisms inferred from animal tracking data can be scaled up to explain landscape-scale patterns of population density and improve predictions of population redistribution under future environmental change. Location: Texas Gulf Coast, USA Time Period: 2009-2018 Major Taxa Studied: Whooping Crane (Grus americana) Methods: We parameterized individual-level step-selection functions using 14,898 GPS locations from 22 Whooping Cranes and propagated the resulting movement and habitat-selection mechanisms across the landscape to derive steady-state distributions of space use. We compared these movement-informed predictions with correlative species distribution models fitted to the same data. Predictions were evaluated using withheld tracking observations and fully independent population-level aerial-survey data. We then projected both approaches under sea-level-rise scenarios to assess how future habitat loss and fragmentation alter crane space use. Results: Movement mechanisms derived from individual-level tracking data captured the mechanistic dependence of population density on habitat quality and spatial configuration. When projected across the landscape, these mechanisms reproduced fully independently observed density patterns and outperformed conventional species distribution models. Because predictions arose from movement mechanisms rather than occurrence-environment correlations, movement-informed models also captured the effects of habitat reconfiguration under sea-level rise. They projected pronounced population redistribution and an expansion of core space-use areas of up to 80% which conventional models missed. Main Conclusions: Individual movement mechanisms derived from biologging data can scale up to explain current population structure and predict future redistribution under environmental change. By mechanistically accounting for how habitat configuration constrains accessibility, movement-informed models reveal severe impacts of fragmentation that are missed by conventional distribution models. Rapidly expanding biologging datasets therefore offer a scalable basis for connecting individual behavior to macroecological patterns and improving biodiversity forecasts in changing landscapes.

BioRxiv↗