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At least 1,225 records · Page 68Linked to original sources
USGS2018

Estimating distemper virus dynamics among wolves and grizzly bears using serology and Bayesian state‐space models

Many parasites infect multiple hosts, but estimating the transmission across host species remains a key challenge in disease ecology. We investigated the within and across host species dynamics of canine distemper virus (CDV) in grizzly bears ( Ursus arctos ) and wolves ( Canis lupus ) of the Greater Yellowstone Ecosystem (GYE). We hypothesized that grizzly bears may be more likely to be exposed to CDV during outbreaks in the wolf population because grizzly bears often displace wolves while scavenging carcasses. We used serological data collected from 1984 to 2014 in conjunction with Bayesian state‐space models to infer the temporal dynamics of CDV. These models accounted for the unknown timing of pathogen exposure, and we assessed how different testing thresholds and the potential for testing errors affected our conclusions. We identified three main CDV outbreaks (1999, 2005, and 2008) in wolves, which were more obvious when we used higher diagnostic thresholds to qualify as seropositive. There was some evidence for increased exposure rates in grizzly bears in 2005, but the magnitude of the wolf effect on bear exposures was poorly estimated and depended upon our prior distributions. Grizzly bears were exposed to CDV prior to wolf reintroduction and during time periods outside of known wolf outbreaks, thus wolves are only one of several potential routes for grizzly bear exposures. Our modeling approach accounts for several of the shortcomings of serological data and is applicable to many wildlife disease systems, but is most informative when testing intervals are short. CDV circulates in a wide range of carnivore species, but it remains unclear whether the disease persists locally within the GYE carnivore community or is periodically reintroduced from distant regions with larger host populations.

Ecology and Evolution↗
USGS2018

Genetic analyses reveal cryptic introgression in secretive marsh bird populations

Hybridization is common in bird populations but can be challenging for management, especially if one of the two parent species is of greater conservation concern than the other. King rails (Rallus elegans) and clapper rails (R. crepitans) are two marsh bird species with similar morphologies, behaviors, and overlapping distributions. The two species are found along a salinity gradient with the king rail in freshwater marshes and the clapper in estuarine marshes. However, this separation is not absolute; they are occasionally sympatric, and there are reports of interbreeding. In Virginia, USA, both king and clapper rails are identified by the state as Species of Greater Conservation Need, although clappers are thought to be more abundant and king rails have a higher priority ranking. We used a mitochondrial DNA marker and 13 diagnostic nuclear single nucleotide polymorphisms (SNPs) to identify species, classify the degree of introgression, and explore the evolutionary history of introgression in two putative clapper rail focal populations along a salinity gradient in coastal Virginia. Genetic analyses revealed cryptic introgression with site-specific rates of admixture. We identified a pattern of introgression where clapper rail alleles predominate in brackish marshes. These results suggest clapper rails may be displacing king rails in Virginia coastal waterways, most likely as a result of ecological selection. As introgression can result in various outcomes from outbreeding depression to local adaptation, continued monitoring of these populations would allow further exploration of hybrid fitness and inform conservation management.

Georgia, New Jersey, North Carolina, Rhode Island,↗
USGS2019

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N ‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N ‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N ‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N ‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

Ecology and Evolution↗
USGS2019

Coast to coast: High genomic connectivity in North American scoters

Dispersal shapes demographic processes and therefore is fundamental to understanding biological, ecological, and evolutionary processes acting within populations. However, assessing population connectivity in scoters ( Melanitta sp.) is challenging as these species have large spatial distributions that span remote landscapes, have varying nesting distributions (disjunct vs. continuous), exhibit unknown levels of dispersal, and vary in the timing of the formation of pair bonds (winter vs. fall/spring migration) that may influence the distribution of genetic diversity. Here, we used double‐digest restriction‐associated DNA sequence (ddRAD) and microsatellite genotype data to assess population structure within the three North American species of scoter (black scoter, M. americana ; white‐winged scoter, M. deglandi ; surf scoter, M. perspicillata ), and between their European congeners (common scoter, M. nigra ; velvet scoter, M. fusca ). We uncovered no or weak genomic structure (ddRAD Φ ST < 0.019; microsatellite F ST < 0.004) within North America but high levels of structure among European congeners (ddRAD Φ ST > 0.155, microsatellite F ST > 0.086). The pattern of limited genomic structure within North America is shared with other sea duck species and is often attributed to male‐biased dispersal. Further, migratory tendencies (east vs. west) of female surf and white‐winged scoters in central Canada are known to vary across years, providing additional opportunities for intracontinental dispersal and a mechanism for the maintenance of genomic connectivity across North America. In contrast, the black scoter had relatively elevated levels of divergence between Alaska and Atlantic sites and a second genetic cluster found in Alaska at ddRAD loci was concordant with its disjunct breeding distribution suggestive of a dispersal barrier (behavioral or physical). Although scoter populations appear to be connected through a dispersal network, a small percentage (<4%) of ddRAD loci had elevated divergence which may be useful in linking areas (nesting, molting, staging, and wintering) throughout the annual cycle.

North America↗
USGS2019

Are polar bear habitat resource selection functions developed from 1985-1996 data still useful?

1. Greenhouse gas-induced warming in the Arctic has caused declines in sea ice extent and changed its composition, raising concerns by all circumpolar nations for polar bear conservation. 2. Negative impacts have been observed in three well-studied polar bear subpopulations. Most subpopulations, however, receive little or no direct monitoring, hence, resource selection functions (RSF) may provide a useful proxy of polar bear distributions. However, the efficacy of RSFs constructed from past data, i.e., reference RSFs, may be degraded under contemporary conditions, especially in a rapidly changing environment. 3. We assessed published Arctic-wide reference RSFs using tracking data from adult female polar bears captured in the Beaufort Sea. We compared telemetry-derived seasonal distributions of polar bears to RSF-defined optimal sea ice habitat during the period of RSF model development, 1985–1995, and two subsequent periods with diminished sea ice: 1996–2006 and 2007–2016. From these comparisons, we assessed the applicability of the reference RSFs for contemporary polar bear conservation. 4. In the two decades following the 1985–1995 reference period, use and availability of optimal habitat by polar bears declined during the ice melt, ice minimum and ice growth seasons. During the ice maximum season (i.e., winter), polar bears used the best habitat available, which changed relatively little across the three decades of study. During the ice melt, ice minimum and ice growth seasons, optimal habitat in areas used by polar bears decreased and was displaced north and east of the Alaska Beaufort Sea coast. As optimal habitat diminished in these seasons, polar bears expanded their range and occupied greater areas of sub-optimal habitat. 5. Synthesis and applications: Sea ice declines due to climate change continue to challenge polar bears and their conservation. The distribution of Southern Beaufort Sea polar bears remained similar during the ice maximum season, so the reference RSFs developed from data collected >20 years ago continue to accurately model their winter distribution. In contrast, reference RSFs for the ice transitional and minimum seasons showed diminished predictive efficacy but were useful in revealing that contemporary polar bears have been increasingly forced to use sub-optimal habitats during those seasons.

Ecology and Evolution↗
USGS2013

Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.

Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km 2 region. We partitioned a Mahalanobis D 2 model of habitat use into k separate additive components each representing independent combinations of species–habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D 2 (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.

Ecology and Evolution↗
USGS2020

Applications of deep convolutional neural networks to predict length, circumference, and weight from mostly dewatered images of fish

Simple biometric data of fish aid fishery management tasks such as monitoring the structure of fish populations and regulating recreational harvest. While these data are foundational to fishery research and management, the collection of length and weight data through physical handling of the fish is challenging as it is time consuming for personnel and can be stressful for the fish. Recent advances in imaging technology and machine learning now offer alternatives for capturing biometric data. To investigate the potential of deep convolutional neural networks to predict biometric data, several regressors were trained and evaluated on data stemming from the FishL™ Recognition System and manual measurements of length, girth, and weight. The dataset consisted of 694 fish from 22 different species common to Laurentian Great Lakes. Even with such a diverse dataset and variety of presentations by the fish, the regressors proved to be robust and achieved competitive mean percent errors in the range of 5.5 to 7.6% for length and girth on an evaluation dataset. Potential applications of this work could increase the efficiency and accuracy of routine survey work by fishery professionals and provide a means for longer‐term automated collection of fish biometric data.

Illinois, Michigan, Ohio↗
USGS2024

Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells

Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus ) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes ( Canis latrans ) and corvids ( Corvidea ). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.

Idaho↗
USGS2025

Balancing monitoring and management in the adaptive management of an invasive species

Efficient allocation of managers' limited resources is necessary to effectively control invasive species, but determining how to allocate effort between monitoring and management over space and time remains a challenge. In an adaptive management context, monitoring data are key for gaining knowledge and iteratively improving management, but monitoring costs money. Community science or other opportunistic monitoring data present an opportunity for managers to gain critical knowledge without a substantial reduction in management funds. We designed a management strategy evaluation to investigate optimal spatial allocation of resources to monitoring and management, while also exploring the potential for community science data to improve decision-making, using adaptive management of invasive flowering rush ( Butomus umbellatus ) in the Columbia River, USA, as a case study. We evaluated management and monitoring alternatives under two invasion conditions, a well-established invasion and an emerging invasion, for both risk-neutral and risk-averse decision makers. Simulations revealed that regardless of invasion condition or managers' risk tolerance, allocating effort outward from the estimated center of invasion ( Epicenter prioritization) resulted in the lowest overall level of infestation at the end of management. This allocation outperformed alternatives in which management occurred in fixed areas ( Linear prioritization) and alternatives that targeted patchily distributed areas with the highest estimated infestation level of the invasive species ( High invasion prioritization). Additionally, management outcomes improved when more resources were allocated toward removal effort than monitoring effort, and the addition of community science data improved outcomes only under certain scenarios. Finally, actions that led to the best outcomes often did not produce the most accurate and precise estimates of parameters describing system function, emphasizing the importance of using value of information principles to guide monitoring. Our adaptive management approach is adaptable to many invasive species management contexts in which ongoing monitoring allows management strategies to be updated over time.

Oregon, Washington↗
USGS2025

Interpreting a sudden population decline in a long-lived species (Malaclemys terrapin rhizophorarum)

Long-term ecological studies are critical for providing insight into population dynamics and detecting population declines, particularly for species of conservation concern. However, spatiotemporal variation and logistical challenges make the identification of sudden population declines difficult. We conducted an in-water capture-mark-recapture study of mangrove diamond-backed terrapins ( Malaclemys terrapin rhizophorarum ) within Big Sable Creek, in Everglades National Park, Florida. We used an 18-year dataset (2001 to 2019) incorporating year, sex, hurricane occurrence, and sampling effort to estimate survival using Cormack–Jolly–Seber (CJS) models in Program Mark. Annual survivorship estimates were high from 2001 to 2003 for both sexes (91%–96%) and variable from 2006 to 2014 (77%–92%). Beginning in 2015, survival estimates exhibited a steeper decline (females: 65%, males 75%), and dropped to below 36% by 2018. Because the driver of this apparent population decline is unknown, we created a population projection matrix and used model-estimated annual survival to simulate annual terrapin population size. We then generated competing scenarios of low survival at various age classes to attempt to reproduce a simulated decline mirroring what we observed from our capture data. A scenario of low adult survival (75%–85%) from 2012 to 2018, possibly in conjunction with no reproduction after 2010, provides estimates of abundance that appear to match simulated annual population size and may indicate that adult emigration/human removal or a drastic drop in recruitment could be responsible for the apparent decline in survival. We explore reasons for this apparent decline and highlight difficulties common to long-term studies that may influence how declines are interpreted.

Florida↗
USGS2025

Development of PCR blocking primers enabling DNA metabarcoding analysis of dietary composition in hematophagous sea lamprey

Conventional dietary assessments are challenging in hematophagous species, particularly in sea lamprey ( Petromyzon marinus ). However, recent technological developments and molecular approaches have provided an attractive alternative through the use of DNA metabarcoding. While DNA metabarcoding has been used for dietary analyses in numerous species, including lampreys, applications of universal primers that detect a diverse set of prey items can be limited by the amplification of predator DNA. In this study, we designed and tested eight blocking primers designed to suppress the amplification of sea lamprey DNA with vertebrate-universal primers targeting the mitochondrial 12S rRNA gene. This approach allowed for the use of a single marker to amplify a taxonomically diverse suite of host species, in contrast to previous studies that used multiple taxon-specific primer pairs (e.g., Salmonidae, Cyprinidae, and Catostomidae). Candidate blocking primers evaluated in this study differed in base pair length, end sequence modification, and purification method. Samples with different sea lamprey-to-host DNA ratios were subjected to multiple detection methods including gel electrophoresis, quantitative PCR, and DNA metabarcoding to assess the ability of each blocking primer to selectively suppress amplification of the sea lamprey 12S gene region. All blocking primers tested performed well and demonstrated high effectiveness, suppressing sea lamprey reads by > 99.9% in mock communities and improving host DNA sequence recovery across various sample types, including wild-caught lamprey. Results show that the blocking primers evaluated can facilitate molecular diet analysis in sea lamprey, allowing the amplification of a taxonomically diverse range of host fish species with universal primers.

Great Lakes↗
USGS2025

Longevity, age-specific survival, and mean generation time of Rana muscosa: Implications for conservation of possibly the longest lived Ranid frog

Life history strategies vary widely among species and play a vital role in extinction risk, especially in a rapidly changing environment. For many taxa, information on life history such as longevity, lifespan, and generation time is incomplete. This is especially true for amphibians, which have experienced large-scale declines in recent decades. The mountain yellow-legged frog ( Rana muscosa ) is a California endemic recognized as a state and federally endangered species. We evaluated a 23-year dataset of six wild R. muscosa populations in southern California. We calculated the average lifespan of individuals in these six populations to be approximately 9.5 years, with a mean generation time of 7.4 years. We did not detect a difference in longevity between sexes or a difference in apparent survival across various ages of adults. We also documented the longest-lived ranid frog ever recorded from a wild population: a male R. muscosa that was at least 21 years old. Our results suggest a relatively long generation time for this species, a characteristic that may benefit them because reproduction is regularly challenged by drought, fire activity, and disease. This information is important for understanding the complex life history of this endangered ranid frog and can help guide efforts to manage and recover the species.

California↗
USGS2026

Using demographic estimation and power analysis to inform monitoring efforts and detect declines in freshwater mussels

Population assessments can be used to determine species' viability and inform conservation efforts; however, obtaining sufficient data quality and quantity can be challenging when monitoring resources are scarce. Brook Floater ( Alasmidonta varicosa ) is a freshwater mussel that is state listed in the United States as endangered or threatened in 10 of the 14 states it occupies. Despite the conservation concern, little is known about the size and demographics of most Brook Floater populations. The primary objective of this study was to determine demographic parameters (abundance and survival) for Brook Floater at five newly established, long-term monitoring sites in Maine and Massachusetts, United States. A secondary objective was to evaluate tradeoffs of potential future sampling strategies by state natural resource agencies at these monitoring sites. Mussels were sampled at each site using visual and tactile snorkel surveys twice each summer during 2018–2020 and marked with alphanumeric tags to distinguish individuals. We considered a candidate set of capture-recapture models that allowed parameters to vary depending on year, sampling occasion, and individual shell length. Abundance estimates among sites varied widely, from 29 individuals (range: 12–119) in the Nissitissit River in Massachusetts to 311 individuals (range: 307–320) in the East Branch of the Pleasant River in Maine. Annual survival was high across all sites (0.87–0.96). Given the differences in capture probability and abundance between states, we determined the statistical power available to detect given population declines in Massachusetts and explored alternative population abundance estimators in Maine. The power analysis suggested that the existing sampling regimen in Maine is likely adequate while sampling in Massachusetts may require additional occasions each year to realistically detect population declines with sufficient statistical power. This analysis demonstrates the utility of considering sampling frequency when designing capture-recapture studies for freshwater mussels and other taxa.

Maine, Massachusetts↗
USGS2021

Transcriptome assembly and differential gene expression of the invasive avian malaria parasite Plasmodium relictum in Hawaiʻi

The malaria parasite Plasmodium relictum (lineage GRW4) was introduced less than a century ago to the native avifauna of Hawaiʻi, where it has since caused major declines of endemic bird populations. One of the native bird species that is frequently infected with GRW4 is the Hawaiʻi ʻamakihi ( Chlorodrepanis virens ). To achieve a better understanding of the transcriptional activities of this virulent parasite, we performed a controlled challenge experiment of 15 ʻamakihi that were infected with GRW4. Blood samples containing malaria parasites were collected at two time points (intermediate and peak infection stages) from host individuals that were either experimentally infected by mosquitoes or inoculated with infected blood. We then used RNA sequencing to assemble a high‐quality blood transcriptome of P. relictum GRW4, allowing us to quantify parasite expression levels inside individual birds. We found few significant differences (one to two transcripts) in GRW4 expression levels between host infection stages and between inoculation methods. However, 36 transcripts showed differential expression levels among all host individuals, indicating a potential presence of host‐specific gene regulation across hosts. To reduce the extinction risk of the remaining native bird species in Hawaiʻi, genetic resources of the local Plasmodium lineage are needed to enable further molecular characterization of this parasite. Our newly built Hawaiian GRW4 transcriptome assembly, together with analyses of the parasite's transcriptional activities inside the blood of Hawaiʻi ʻamakihi, can provide us with important knowledge on how to combat this deadly avian disease in the future.

Hawaii↗
USGS2021

Linking behavioral states to landscape features for improved conservation management

A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat-specific behaviors. Here we use behavioral change point analysis to identify behavioral states of golden eagles ( Aquila chrysaetos ) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation-relevant habitat associations. We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short-distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer-distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m). Behaviors such as perching and low-altitude hunting were associated with short-distance movements in updraft-poor environments, at higher elevations, and over steeper and more north-facing terrain. In contrast, medium-distance movements such as hunting and transiting were over gentle and south-facing slopes. Long-distance transiting occurred over the desert habitats that generate the best updraft. This information can guide management of this species, and our approach provides a template for behavior-specific habitat associations for other species of management concern.

California↗
USGS2021

Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016

The Arctic Ocean is undergoing rapid transformation toward a seasonally ice-free ecosystem. As ice-adapted apex predators, polar bears ( Ursus maritimus ) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food-web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska's SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite-telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming.

Alaska↗
USGS2022

Classifying behavior from short-interval biologging data: An example with GPS tracking of birds

Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets. We apply a framework for using K -means clustering to classify bird behavior using points from short time interval GPS tracks. K -means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K -means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free-flying bald eagles ( Haliaeetus leucocephalus ) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life-stage- and age-related variation in behavior. After filtering for data quality, the K -means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non-moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight. The K -means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short-interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high-dimensional movement data, it provides insight into small-scale variation in behavior that would not be possible with many other analytical approaches.

Ecology and Evolution↗
USGS2022

Assessing vegetation recovery from energy development using a dynamic reference approach

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush ( Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads ( n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.

Wyoming↗