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At least 109 records · Page 6Linked to original sources
USGS2020

Using movement to inform conservation corridor design for Mojave desert tortoise

Background Preserving corridors for movement and gene flow among populations can assist in the recovery of threatened and endangered species. As human activity continues to fragment habitats, characterizing natural corridors is important in establishing and maintaining connectivity corridors within the anthropogenic development matrix. The Mojave desert tortoise ( Gopherus agassizii ) is a threatened species occupying a variety of habitats in the Mojave and Colorado Deserts. Desert tortoises have been referred to as corridor-dwellers, and understanding how they move within suitable habitat can be crucial to defining corridors that will sustain sufficient gene flow to maintain connections among populations amidst the increases in human development. Methods To elucidate how tortoises traverse available habitat and interact with potentially inhospitable terrain and human infrastructure, we used GPS dataloggers to document fine-scale movement of individuals and estimate home ranges at ten study sites along the California/Nevada border. Our sites encompass a variety of habitats, including mountain passes that serve as important natural corridors connecting neighboring valleys, and are impacted by a variety of linear anthropogenic features. We used path selection functions to quantify tortoise movements and develop resistance surfaces based on landscape characteristics including natural features, anthropogenic alterations, and estimated home ranges with autocorrelated kernel density methods. Using the best supported path selection models and estimated home ranges, we determined characteristics of known natural corridors and compared them to mitigation corridors (remnant habitat patches) that have been integrated into land management decisions in the Ivanpah Valley. Results Tortoises avoided areas of high slope and low perennial vegetation cover, avoided moving near low-density roads, and traveled along linear barriers (fences and flood control berms). Conclusions We found that mitigation corridors designated between solar facilities should be wide enough to retain home ranges and maintain function. Differences in home range size and movement resistance between our two natural mountain pass corridors align with differences in genetic connectivity, suggesting that not all natural corridors provide the same functionality. Furthermore, creation of mitigation corridors with fences may have unintended consequences and may function differently than natural corridors. Understanding characteristics of corridors with different functionality will help future managers ensure that connectivity is maintained among Mojave desert tortoise populations.

California, Nevada↗
USGS2021

Drivers of realized satellite tracking duration in marine turtles

Background Satellite tags have revolutionized our understanding of marine animal movements. However, tags may stop transmitting for many reasons and little research has rigorously examined tag failure. Using a long-term, large-scale, multi-species dataset, we evaluated factors influencing tracking duration of satellite tags to inform study design for future tracking studies. Methods We leveraged data on battery status transmitted with location data, recapture events, and number of transmission days to probabilistically quantify multiple potential causes of failure (i.e., battery failure, premature detachment, and tag damage/fouling). We used a combination of logistic regressions and an ordinary linear model including several predictor variables (i.e., tag type, battery life, species, sex, size, and foraging region). Results We examined subsets of data from 360 satellite tags encompassing 86,889 tracking days deployed on four species of marine turtles throughout the Gulf of Mexico, Caribbean, and Bahamas from 2008 to 2019. Only 4.1% of batteries died before failure due to other causes. We observed species-specific variation in how long tags remain attached: hawksbills retained 50% of their tags for 1649 days (95% CI 995–1800), loggerheads for 584 days (95% CI 400–690), and green turtles for 294 days (95% CI 198–450). Estimated tracking duration varied by foraging region (Caribbean: 385 days; Bahamas: 356; southern Gulf of Mexico [SGOM]: 276, northern Gulf of Mexico [NGOM]: 177). Additionally, we documented species-specific variation in estimated tracking duration among foraging regions. Based on sensor data, within the Gulf of Mexico, across species, we estimated that 50% of tags began to foul after 83 95% CI (70–120) days. Conclusions The main factor that limited tracking duration was tag damage (i.e., fouling and/or antenna breakage). Turtles that spent most of their time in the Gulf of Mexico had shorter tracking durations than those in the Bahamas and Caribbean, with shortest durations observed in the NGOM. Additionally, tracking duration varied by species, likely as a result of behaviors that damage tags. This information will help researchers, tag companies, permitting agencies, and funders better predict expected tracking durations, improving study designs for imperiled marine turtles. Our results highlight the heterogeneity in telemetry device longevity, and we provide a framework for researchers to evaluate telemetry devices with respect to their study objectives.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2021

Identifying resting locations of a small elusive forest carnivore using a two-stage model accounting for GPS measurement error and hidden behavioral states

Studies of animal movement using location data are often faced with two challenges. First, time series of animal locations are likely to arise from multiple behavioral states (e.g., directed movement, resting) that cannot be observed directly. Second, location data can be affected by measurement error, including failed location fixes. Simultaneously addressing both problems in a single statistical model is analytically and computationally challenging. To both separate behavioral states and account for measurement error, we used a two-stage modeling approach to identify resting locations of fishers ( Pekania pennanti ) based on GPS and accelerometer data.

California, Oregon↗
USGS2021

Dispersal distance is driven by habitat availability and reproductive success in Northern Great Plains piping plovers

Background Dispersal is a critical life history strategy that has important conservation implications, particularly for at-risk species with active recovery efforts and migratory species. Both natal and breeding dispersal are driven by numerous selection pressures, including conspecific competition, individual characteristics, reproductive success, and spatiotemporal variation in habitat. Most studies focus on dispersal probabilities, but the distance traveled can affect survival, fitness, and even metapopulation dynamics. Methods We examined sources of variation in dispersal distances with 275 natal dispersal and 1335 interannual breeding events for piping plovers ( Charadrius melodus ) breeding in the Northern Great Plains between 2014 and 2019. Results Natal dispersal was on average longer (mean: 81.0 km, median: 53 km) than adult breeding movements (mean: 23.7 km, median: 1 km). Individuals moved the shortest distances when hatched, previously nested, or settling on river habitats. When more habitat was available on their natal area than in the year prior, hatch-year birds moved shorter distances to their first breeding location. Similarly, adults also moved shorter distances when more habitat was available at the settling site and when in closer proximity to other known nesting areas. Additionally, adult movement distance was shorter when successfully hatching a nest the year prior, retaining a mate, or initiating a current nest earlier. Conclusion Habitat availability appears to be associated with dispersal distance for both hatch-year and adult piping plovers. Conservation efforts that integrate dispersal distances may benefit from maintaining nesting habitat within close proximity to other areas for adults and a network of clustered sites spread out across a larger landscape for natal dispersal.

Montana, North Dakota, South Dakota↗
USGS2022

Environmental drivers of autumn migration departure decisions in midcontinental mallards

Background The timing of autumn migration in ducks is influenced by a range of environmental conditions that may elicit individual experiences and responses from individual birds, yet most studies have investigated relationships at the population level. We used data from individual satellite-tracked mallards ( Anas platyrhynchos ) to model the timing and environmental drivers of autumn migration movements at a continental scale. Methods We combined two sets of location records (2004–2007 and 2010–2011) from satellite-tracked mallards during autumn migration in the Mississippi Flyway, and identified records that indicated the start of long-range (≥ 30 km) southward movements during the migration period. We modeled selection of departure date by individual mallards using a discrete choice model accounting for heterogeneity in individual preferences. We developed candidate models to predict the departure date, conditional on daily mean environmental covariates (i.e. temperature, snow and ice cover, wind conditions, precipitation, cloud cover, and pressure) at a 32 × 32 km resolution. We ranked model performance with the Bayesian Information Criterion. Results Departure was best predicted (60% accuracy) by a “winter conditions” model containing temperature, and depth and duration of snow cover. Models conditional on wind speed, precipitation, pressure variation, and cloud cover received lower support. Number of days of snow cover, recently experienced snow cover (snow days) and current snow cover had the strongest positive effect on departure likelihood, followed by number of experienced days of freezing temperature (frost days) and current low temperature. Distributions of dominant drivers and of correct vs incorrect prediction along the movement tracks indicate that these responses applied throughout the latitudinal range of migration. Among recorded departures, most were driven by snow days (65%) followed by current temperature (30%). Conclusions Our results indicate that among the tested environmental parameters, the dominant environmental driver of departure decision in autumn-migrating mallards was the onset of snow conditions, and secondarily the onset of temperatures close to, or below, the freezing point. Mallards are likely to relocate southwards quickly when faced with snowy conditions, and could use declining temperatures as a more graduated early cue for departure. Our findings provide further insights into the functional response of mallards to weather factors during the migration period that ultimately determine seasonal distributions.

Movement Ecology↗
USGS2022

Individual heterogeneity influences the effects of translocation on urban dispersal of an invasive reptile

Background Invasive reptiles pose a serious threat to global biodiversity, but early detection of individuals in an incipient population is often hindered by their cryptic nature, sporadic movements, and variation among individuals. Little is known about the mechanisms that affect the movement of these species, which limits our understanding of their dispersal. Our aim was to determine whether translocation or small-scale landscape features affect movement patterns of brown treesnakes ( Boiga irregularis ), a destructive invasive predator on the island of Guam. Methods We conducted a field experiment to compare the movements of resident (control) snakes to those of snakes translocated from forests and urban areas into new urban habitats. We developed a Bayesian hierarchical model to analyze snake movement mechanisms and account for attributes unique to invasive reptiles by incorporating multiple behavioral states and individual heterogeneity in movement parameters. Results We did not observe strong differences in mechanistic movement parameters (turning angle or step length) among experimental treatment groups. We found some evidence that translocated snakes from both forests and urban areas made longer movements than resident snakes, but variation among individuals within treatment groups weakened this effect. Snakes translocated from forests moved more frequently from pavement than those translocated from urban areas. Snakes translocated from urban areas moved less frequently from buildings than resident snakes. Resident snakes had high individual heterogeneity in movement probability. Conclusions Our approach to modeling movement improved our understanding of invasive reptile dispersal by allowing us to examine the mechanisms that influence their movement. We also demonstrated the importance of accounting for individual heterogeneity in population-level analyses, especially when management goals involve eradication of an invasive species.

Movement Ecology↗
USGS2022

Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl

Background Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”. Methods Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models. Results Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting). Conclusions Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.

Movement Ecology↗
USGS2023

Variation in herbivore space use: Comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa

Background The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. Methods We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. Results Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent. Conclusions Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens.

Etosha National Park, Kruger National Park↗
USGS2023

Movement and behavioral states of common carp (Cyprinus carpio) in response to a behavioral deterrent in a navigational lock

Freshwater ecosystems are some of the most affected by biological invasions due, in part, to the introduction of invasive carp worldwide. Where carp have become established, management programs often seek to limit further range expansion into new areas by reducing their movement through interconnected rivers and waterways. Lock and dams are important locations for non-physical deterrents, such as carbon dioxide (CO 2 ), to reduce unwanted fish passage without disrupting human use. The purpose of this study was to evaluate the behavioral responses of common carp ( Cyprinus carpio ) to non-physical deterrents within a navigation structure on the Fox River, Wisconsin. Acoustic telemetry combined with hidden Markov models (HMMs) was used to analyze variation in carp responses to treatments. Outcomes may inform CO 2 effectiveness at preventing invasive carp movement through movement pinch-points.

Wisconsin↗
USGS2023

Fall migration, oceanic movement, and site residency patterns of eastern red bats (Lasiurus borealis) on the mid-Atlantic Coast

Along the mid-Atlantic coast of the United States, eastern red bats ( Lasiurus borealis ) are present during fall mating and migration, though little is currently known about most aspects of bat migration. To reveal migration patterns, and understand drivers of over-water flight, we captured and radio-tagged 115 eastern red bats using novel technology, and subsequently tracked and described their movements throughout the region. We compared over-water flight movements to randomly generated patterns using a use-availability framework, and subsequently used a generalized linear mixed effects model to assess the relationship of over-water flight to atmospheric variables. We used hidden Markov models to assess daily activity patterns and site residency. Most bats with long-distance movements traveled in a southwesterly direction, however path vectors were often oriented interior toward the continental landmass rather than along the coastline. We observed that some bats transited wide sections of the Chesapeake and Delaware bays, confirming their ability to travel across large water bodies. This over-water flight typically occurred in the early hours of the night and during favorable flying conditions. If flight over large water bodies is a proxy for over-ocean flight, then collision risk at offshore wind turbines – a major source of migratory bat fatalities – may be linked nightly to warm temperatures that occur early in the fall season. Risk, then, may be somewhat predictable and manageable with mitigation options linking wind-energy operation to weather conditions and seasonality.

Delaware, Maryland, New Jersey, Virginia↗
USGS2023

Dispersal of juvenile Barrow’s goldeneyes (Bucephala islandica) mirrors that of breeding adults

Barrow’s goldeneyes across western North America have been shown to have a high degree of subpopulation independence using several data types. However, evidence for structured populations based on mitochondrial DNA, band recoveries, and tracking of adults is discordant with evidence from autosomal DNA. We used satellite tracking data from both juveniles and adults marked on natal and breeding grounds, respectively, in British Columbia, Canada to evaluate the hypothesis that male-biased juvenile dispersal maintains genetic panmixia of Pacific Barrow’s goldeneyes otherwise structured by migratory movements and high winter and breeding site fidelity of adults. We found that juvenile males traveled to overwintering sites located within the range of the overwintering sites of juvenile females, adult males, and adult females. Juvenile males migrated at the same time, travelled the same distance when moving between natal and overwintering sites, and had the same winter dispersion as juvenile females. Although juveniles did not travel with attendant females, all juveniles overwintered within the wintering range of adults. We tracked some juveniles into the following spring/summer and even second winter. Prospecting juveniles of both sexes travelled from their wintering grounds to potential breeding sites in the proximity of Riske Creek and within the bounds of the breeding locations used by adults. Juveniles tracked for more than a year also showed relatively high winter site fidelity. Because Barrow’s goldeneyes pair on wintering grounds, our tracking data are not consistent with the hypothesis that male-biased juvenile dispersal explains the genetic structure in the mitochondrial DNA and panmixia in the autosomal DNA of Barrow’s goldeneye. We suggest that uncommon or episodic dispersal of males might be enough to homogenize autosomal DNA but is unlikely to influence demographic population structure relevant to contemporary population management.

British Columbia, Washington↗
USGS2023

Change-point models for identifying behavioral transitions in wild animals

Animal behavior can be difficult, time-consuming, and costly to observe in the field directly. Innovative modeling methods, such as hidden Markov models (HMMs), allow researchers to infer unobserved animal behaviors from movement data, and implementations often assume that transitions between states occur multiple times. However, some behavioral shifts of interest, such as parturition, migration initiation, and juvenile dispersal, may only occur once during an observation period, and HMMs may not be the best approach to identify these changes. We present two change-point models for identifying single transitions in movement behavior: a location-based change-point model and a movement metric-based change-point model. We first conducted a simulation study to determine the ability of these models to detect a behavioral transition given different amounts of data and the degree of behavioral shifts. We then applied our models to two ungulate species in central Pennsylvania that were fitted with global positioning system collars and vaginal implant transmitters to test hypotheses related to parturition behavior. We fit these models in a Bayesian framework and directly compared the ability of each model to describe the parturition behavior across species. Our simulation study demonstrated that successful change point estimation using either model was possible given at least 12 h of post-change observations and 15 min fix interval. However, our models received mixed support among deer and elk in Pennsylvania due to behavioral variation between species and among individuals. Our results demonstrate that when the behavior follows the dynamics proposed by the two models, researchers can identify the timing of a behavioral change. Although we refer to detecting parturition events, our results can be applied to any behavior that results in a single change in time.

Movement Ecology↗
USGS2023

Site fidelity of migratory shorebirds facing habitat deterioration: Insights from satellite tracking and mark-resighting

Background Site fidelity, the tendency to return to a previously visited site, is commonly observed in migratory birds. This behaviour would be advantageous if birds returning to the same site, benefit from their previous knowledge about local resources. However, when habitat quality declines at a site over time, birds with lower site fidelity might benefit from a tendency to move to sites with better habitats. As a first step towards understanding the influence of site fidelity on how animals cope with habitat deterioration, here we describe site fidelity variation in two species of sympatric migratory shorebirds (Bar-tailed Godwits Limosa lapponica and Great Knots Calidris tenuirostris ). Both species are being impacted by the rapid loss and deterioration of intertidal habitats in the Yellow Sea where they fuel up during their annual long-distance migrations. Methods Using satellite tracking and mark-resighting data, we measured site fidelity in the non-breeding (austral summer) and migration periods, during which both species live and co-occur in Northwest Australia and the Yellow Sea, respectively. Results Site fidelity was generally high in both species, with the majority of individuals using only one site during the non-breeding season and revisiting the same sites during migration. Nevertheless, Great Knots did exhibit lower site fidelity than Bar-tailed Godwits in both Northwest Australia and the Yellow Sea across data types. Conclusions Great Knots encountered substantial habitat deterioration just before and during our study period but show the same rate of decline in population size and individual survival as the less habitat-impacted Bar-tailed Godwits. This suggests that the lower site fidelity of Great Knots might have helped them to cope with the habitat changes. Future studies on movement patterns and their consequences under different environmental conditions by individuals with different degrees of site fidelity could help broaden our understanding of how species might react to, and recover from, local habitat deterioration.

Movement Ecology↗
USGS2024

Deep vs shallow: GPS tags reveal a dichotomy in movement patterns of loggerhead turtles foraging in a coastal bay

Background Individual variation in movement strategies of foraging loggerhead turtles have been documented on the scale of tens to hundreds of kilometers within single ocean basins. Use of different strategies among individuals may reflect variations in resources, predation pressure or competition. It is less common for individual turtles to use different foraging strategies on the scale of kilometers within a single coastal bay. We used GPS tags capable of back-filling fine-scale locations to document movement patterns of loggerhead turtles in a coastal bay in Northwest Florida, U.S.A. Methods Iridium-linked GPS tags were deployed on loggerhead turtles at a neritic foraging site in Northwest Florida. After filtering telemetry data, point locations were transformed to movement lines and then merged with the original point file to define travel paths and assess travel speed. Home ranges were determined using kernel density function. Diurnal behavioral shifts were examined by examining turtle movements compared to solar time. Results Of the 11 turtles tagged, three tracked turtles remained in deep (~ 6 m) water for almost the entire tracking period, while all other turtles undertook movements from deep water locations, located along edges and channels, to shallow (~ 1–2 m) shoals at regular intervals and primarily at night. Three individuals made short-term movements into the Gulf of Mexico when water temperatures dropped, and movement speeds in the Gulf were greater than those in the bay. Turtles exhibited a novel behavior we termed drifting. Conclusions This study highlighted the value provided to fine-scale movement studies for species such as sea turtles that surface infrequently by the ability of these GPS tags to store and re-upload data. Future use of these tags at other loggerhead foraging sites, and concurrent with diving and foraging data, would provide a powerful tool to better understand fine-scale movement patterns of sea turtles.

Florida↗
USGS2024

A benchmark for computational analysis of animal behavior, using animal-borne tags

Background Animal-borne sensors (‘bio-loggers’) can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community. Methods To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers. Results We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available. Conclusions In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE , to enable community use of BEBE.

Movement Ecology↗
USGS2025

Shortening migration by 4500 km does not affect nesting phenology or increase nest success for black brant (Branta bernicla nigricans) breeding in Arctic and subarctic Alaska

Background Since the 1980s, Pacific Black Brant ( Branta bernicla nigricans , hereafter brant) have shifted their winter distribution northward from Mexico to Alaska (approximately 4500 km) with changes in climate. Alongside this shift, the primary breeding population of brant has declined. To understand the population-level implications of the changing migration strategy of brant, it is important to connect movement and demographic data. Our objectives were to calculate migratory connectivity, a measure of spatial and temporal overlap during the non-breeding period, for Arctic and subarctic breeding populations of brant, and to determine if variation in migration strategies affected nesting phenology and nest survival. Methods We derived a migratory network using light-level geolocator migration tracks from an Arctic site (Colville River Delta) and a subarctic site (Tutakoke River) in Alaska. Using this network, we quantified the migratory connectivity of the two populations during the winter. We also compared nest success rates among brant that used different combinations of winter sites and breeding sites. Results The two breeding populations were well mixed during the winter, as indicated by a migratory connectivity score close to 0 (− 0.06) at the primary wintering sites of Izembek Lagoon, Alaska (n = 11 brant) and Baja California, Mexico (n = 48). However, Arctic birds were more likely to migrate the shorter distance to Izembek (transition probability = 0.24) compared to subarctic birds (transition probability = 0.09). Nest survival for both breeding populations was relatively high (0.88–0.92), and we did not detect an effect of wintering site on nest success the following year. Conclusions Nest survival of brant did not differ among brant that used wintering sites despite a 4500 km difference in migration distances. Our results also suggested that the growing Arctic breeding population is unlikely to compensate for declines in the larger breeding population of brant in the subarctic. However, this study took place in 2011–2014 and wintering at Izembek Lagoon may have greater implications for reproductive success under future climate conditions.

Movement Ecology↗
USGS2025

Linking bathythermal habitat selection to management of a migratory freshwater fish

Background For migratory fishes, habitat selection in dimensions of temperature and depth may be jointly used to define the bathythermal niche. Seasonal and long-term changes in the availability of bathythermal habitat can cause behavioral responses that have consequences for managing interjurisdictional fisheries that target migratory fishes. Management of such fisheries typically relies on standardized surveys to provide knowledge of stock status, yet changes in fish behavior may complicate interpretation of survey results. For example, changes in bathythermal habitat selection could uncouple fish availability from surveys designed to intercept migrating fish in predefined bathythermal habitats. Methods We applied electronic tagging methods to Lake Erie walleye ( Sander vitreus ) to address spatial management and stock assessment questions regarding bathythermal habitat. Specifically, we sought to determine if bathythermal habitat use varied in relation to body size, season, and time of day, with a particular focus on how these may influence availability to fisheries-independent surveys conducted during September-November. Results As predicted, bathythermal habitat distribution fluctuated substantially throughout the year, was most limited during spawning months, and most expansive during fall migration. During the summer stratified months, walleye primarily selected epilimnetic habitats, despite the prevailing notion that colder hypolimnetic waters would be preferred during this time. Conclusions While our results did not support a previous hypothesis that smaller fish were more available to assessment survey gears, our results did support previous assertions that walleye were more active and available to suspended gill nets during late crepuscular periods in fall. Considering uncertainties in water quality and long-term warming trends, our case study could improve decisions regarding spatial management of this species in the context of independent water quality management objectives.

Detroit River, Lake Erie, Lake St. Clair↗
USGS2025

Identifying presence or absence of grizzly and polar bear cubs from the movements of adult females with machine learning

Background Information on reproductive success is crucial to understanding population dynamics but can be difficult to obtain, particularly for species that birth while denning. For grizzly ( Ursus arctos ) and polar bears ( U. maritimus ), den visits are impractical because of safety and logistical considerations. Reproduction is typically documented through direct observation, which can be difficult, costly, and often occurs long after den departure. Reproduction could be documented remotely, however, from post-denning movement data if discernable differences exist between females with and without cubs. Methods We trained support vector machines (SVMs) with eight variables derived from telemetry data of female grizzly (2000–2022) and polar bears (1985–2016) with or without cubs during seven periods with lengths ranging from 5 to 60 days starting at den departure. We assessed SVM classification accuracy by withholding two samples (one cub-present, one cub-absent), training SVMs with the remaining data, predicting classification of the withheld samples, and repeating this process for each sample combination. Additionally, we evaluated how classification accuracy for grizzly bears was influenced by sample size, length of the post-departure period, and frequency of standardized location estimates. Results Accuracy of predicting cub presence or absence was 87% for grizzly bears with only 5 days of post-departure data and increased to a maximum of 92% with 20 days of data. For polar bears, accuracy was 86% at 5 days post-departure and increased to a maximum of 93% at 50 days. Classification accuracy for grizzly bears increased from 76 to 90% when sample size increased from 10 to 30 bears while holding period length constant (30 days) but did not increase at larger sample sizes. When sample size was held constant, increasing the length of the post-departure period did not affect classification accuracy markedly. Conclusion Presence or absence of grizzly and polar bear cubs can be identified with high accuracy even when SVM models are trained with limited data. Detecting cub presence or absence remotely could improve estimates of reproductive success and litter survival, enhancing our understanding of factors affecting cub recruitment.

Alaska, Idaho, Montana, Wyoming↗