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USGS2023

Efficacy of machine learning image classification for automated occupancy-based monitoring

Remote cameras have become a widespread data-collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad-scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric species with disparate body sizes and life histories – black-tailed jackrabbits ( Lepus californicus ), kit foxes ( Vulpes macrotis ), and pronghorns ( Antilocapra americana ) – as a model system to evaluate the influence of competing image classification approaches on estimates of occupancy and inferences about space use. We classified images with: (i) single review (manual), (ii) double review (manual by two observers), (iii) an automated-manual review (machine learning to cull empty images and single review of remaining images), (iv) a pretrained machine-learning algorithm that classifies images to species (base model), (v) the base model accepting only classifications with ≥95% confidence, (vi) the base model trained with regional images (trained model), and (vii) the trained model accepting only classifications with ≥95% confidence. We compared species-specific results from alternative approaches to results from double review, which reduces the potential for misclassifications and was assumed to be the best approximation of truth. Despite high classification success, species-level misclassification rates for the base and trained models were sufficiently high to produce erroneous occupancy estimates and inferences related to space use across species. Increasing the confidence thresholds for image classification to 95% did not consistently improve performance. Classifying images as empty (or not) offered a reasonable approach to reduce effort (by 97.7%) and facilitated a semi-automated workflow that produced reliable estimates and inferences. Thus, camera-based monitoring combined with machine learning algorithms for image classification could facilitate monitoring with limited manual image classification.

Utah↗

USGS2023

High-resolution thermal imagery reveals how interactions between crown structure and genetics shape plant temperature

Understanding interactions between environmental stress and genetic variation is crucial to predict the adaptive capacity of species to climate change. Leaf temperature is both a driver and a responsive indicator of plant physiological response to thermal stress, and methods to monitor it are needed. Foliar temperatures vary across leaf to canopy scales and are influenced by genetic factors, challenging efforts to map and model this critical variable. Thermal imagery collected using unoccupied aerial systems (UAS) offers an innovative way to measure thermal variation in plants across landscapes at leaf-level resolutions. We used a UAS equipped with a thermal camera to assess temperature variation among genetically distinct populations of big sagebrush ( Artemisia tridentata ), a keystone plant species that is the focus of intensive restoration efforts throughout much of western North America. We completed flights across a growing season in a sagebrush common garden to map leaf temperature relative to subspecies and cytotype, physiological phenotypes of plants, and summer heat stress. Our objectives were to (1) determine whether leaf-level stomatal conductance corresponds with changes in crown temperature; (2) quantify genetic (i.e., subspecies and cytotype) contributions to variation in leaf and crown temperatures; and (3) identify how crown structure, solar radiation, and subspecies-cytotype relate to leaf-level temperature. When considered across the whole season, stomatal conductance was negatively, non-linearly correlated with crown-level temperature derived from UAS. Subspecies identity best explained crown-level temperature with no difference observed between cytotypes. However, structural phenotypes and microclimate best explained leaf-level temperature. These results show how fine-scale thermal mapping can decouple the contribution of genetic, phenotypic, and microclimate factors on leaf temperature dynamics. As climate-change-induced heat stress becomes prevalent, thermal UAS represents a promising way to track plant phenotypes that emerge from gene-by-environment interactions.

Idaho↗

USGS2017

Weather radar data correlate to hail-induced mortality in grassland birds

Small-bodied terrestrial animals such as songbirds (Order Passeriformes) are especially vulnerable to hail-induced mortality; yet, hail events are challenging to predict, and they often occur in locations where populations are not being studied. Focusing on nesting grassland songbirds, we demonstrate a novel approach to estimate hail-induced mortality. We quantify the relationship between the probability of nests destroyed by hail and measured Level-III Next Generation Radar (NEXRAD) data, including atmospheric base reflectivity, maximum estimated size of hail and maximum estimated azimuthal wind shear. On 22 June 2014, a hailstorm in northern Colorado destroyed 102 out of 203 known nests within our research site. Lark bunting ( Calamospiza melanocorys ) nests comprised most of the sample ( n = 186). Destroyed nests were more likely to be found in areas of higher storm intensity, and distributions of NEXRAD variables differed between failed and surviving nests. For 133 ground nests where nest-site vegetation was measured, we examined the ameliorative influence of woody vegetation, nest cover and vegetation density by comparing results for 13 different logistic regression models incorporating the independent and additive effects of weather and vegetation variables. The most parsimonious model used only the interactive effect of hail size and wind shear to predict the probability of nest survival, and the data provided no support for any of the models without this predictor. We conclude that vegetation structure may not mitigate mortality from severe hailstorms and that weather radar products can be used remotely to estimate potential for hail mortality of nesting grassland birds. These insights will improve the efficacy of grassland bird population models under predicted climate change scenarios.

Remote Sensing in Ecology and Conservation↗

USGS2025

Object detection-assisted workflow facilitates cryptic snake monitoring

Camera traps are an important tool used to study rare and cryptic animals, including snakes. Time-lapse photography can be particularly useful for studying snakes that often fail to trigger a camera's infrared motion sensor due to their ectothermic nature. However, the large datasets produced by time-lapse photography require labor-intensive classification, limiting their use in large-scale studies. While many artificial intelligence-based object detection models are effective at identifying mammals in images, their ability to detect snakes is unproven. Here, we used camera data to evaluate the efficacy of an object detection model to rapidly and accurately detect snakes. We classified images manually to the species level and compared this with a hybrid review workflow where the model removed blank images followed by a manual review. Using a ≥0.05 model confidence threshold, our hybrid review workflow correctly identified 94.5% of blank images, completed image classification 6× faster, and detected large (>66 cm) snakes as well as manual review. Conversely, the hybrid review method often failed to detect all instances of a snake in a string of images and detected fewer small (<66 cm) snakes than manual review. However, most relevant ecological information requires only a single detection in a sequence of images, and study design changes could likely improve the detection of smaller snakes. Our findings suggest that an object detection-assisted hybrid workflow can greatly reduce time spent manually classifying data-heavy time-lapse snake studies and facilitate ecological monitoring for large snakes.

Florida↗

USGS2018

Looking beyond wildlife: Using remote cameras to evaluate accuracy of gridded snow data

The use of remote cameras is widespread in wildlife ecology, yet few examples exist of their utility for collecting environmental data. We used a novel camera trap method to evaluate the accuracy of gridded snow data in a mountainous region of the northeastern US. We were specifically interested in assessing (1) how snow depth observations from remote cameras compare with gridded climate data, (2) the sources of error associated with the gridded data and (3) the influence of spatial sampling on bias. We compared daily observations recorded by remote cameras with Snow Data Assimilation System (SNODAS ) gridded predictions using data from three winters (2014–2016). Snow depth observations were correlated with SNODAS predictions for sites ( R 2 = 0.20) and regions ( R 2 = 0.16), yet we detected factors associated with SNODAS bias at both scales. Specifically, SNODAS underpredicted depths at high elevations, at sites with higher solar radiation, and within conifer‐dominated forest. Depths were most underpredicted at highest elevations, up to 44 and 26 cm on average at the site and region scales, respectively. Bias was greatest when predictions were lowest, occasionally predicting snow absence when depths were >100 cm at camera sites. We also detected breakdowns in accuracy when certain environmental conditions varied within the 1 km 2 SNODAS grid cells. For example, underprediction was greatest when the solar radiation values of camera stations increased relative to the mean of the SNODAS grid cells. This relationship was most prominent in mountainous regions, suggesting that factors which influence solar radiation (e.g. topographic complexity) contribute to SNODAS inaccuracy. We caution using gridded snow data for ecological studies when bias is unknown. We suggest increased sampling to adjust for errors associated with gridded data products that arise from factors, such as forest cover and topographic variability. Increasing resolution and accuracy of climate data will improve predictions of species’ responses to climate change.

New Hampshire, Vermont↗

USGS2019

Temporal gamma-diversity meets spatial alpha-diversity in dynamically varying ecosystems

Community measures collected at a single instance or over a short temporal period rarely provide a complete accounting of biological diversity. The gap between such “snapshot” measures of diversity and actual diversity can be especially large in systems that undergo great temporal variation in environmental conditions. To adequately quantify diversity in these temporally varying ecosystems, individual measures of diversity collected throughout the range of environmental variation, i.e., temporal alpha-diversity measures, must be combined to obtain temporal gamma-diversity. Such a time-integrated gamma-diversity measure will be a much closer approximation of a site’s true alpha-diversity and provide a measure better comparable to spatial alpha-diversity measures of sites with lower temporal variation for which a single or a few “snapshot” measures may suffice. We used aquatic-macroinvertebrate community-composition data collected over a 24-year period from a complex of 16 prairie-pothole wetlands to explore the rate that taxa accumulate over time at sites with differing degrees of temporal variation. Our results show that the rate of taxa accumulation over time, i.e., the slope of the species–time relationship, is steeper for wetlands with ponds that frequently dry compared to those with more-permanent ponds. Additionally, we found that a logarithmic function better fit species accumulation data for seasonally ponded wetlands whereas a power function better fit accumulations for permanently and semi-permanently ponded wetlands. Thus, interpretations of ecological diversity measures, and conservation decisions that rely on these interpretations, can be biased if temporal variations in community composition are not adequately represented.

North Dakota↗

USGS2021

NABat: A top-down, bottom-up solution to collaborative continental-scale monitoring

Collaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.

Ambio↗

USGS2015

Implications of scale-independent habitat specialization on persistence of a rare small mammal

We assessed the habitat use patterns of the Amargosa vole Microtus californicus scirpensis , an endangered rodent endemic to wetland vegetation along a 3.5 km stretch of the Amargosa River in the Mojave Desert, USA. Our goals were to: (1) quantify the vole’s abundance, occupancy rates and habitat selection patterns along gradients of vegetation cover and spatial scale; (2) identify the processes that likely had the greatest influence on its habitat selection patterns. We trapped voles monthly in six 1 ha grids from January to May 2012 and measured habitat structure at subgrid (View the MathML source225m2) and trap (View the MathML source1m2) scales in winter and spring seasons. Regardless of scale, analyses of density, occupancy and vegetation structure consistently indicated that voles occurred in patches of bulrush (Schoenoplectus americanus ; Cyperaceae) where cover >50%. The majority of evidence indicates the vole's habitat selectivity is likely driven by bulrush providing protection from intense predation. However, a combination of selective habitat use and limited movement resulted in a high proportion of apparently suitable bulrush patches being unoccupied. This suggests the Amargosa vole's habitat selection behavior confers individual benefits but may not allow the overall population to persist in a changing environment.

Global Ecology and Conservation↗

USGS2015

Day-roost tree selection by northern long-eared bats - What do non-roost tree comparisons and one year of data really tell us?

Bat day-roost selection often is described through comparisons of day-roosts with randomly selected, and assumed unused, trees. Relatively few studies, however, look at patterns of multi-year selection or compare day-roosts used across years. We explored day-roost selection using 2 years of roost selection data for female northern long-eared bats ( Myotis septentrionalis ) on the Fort Knox Military Reservation, Kentucky, USA. We compared characteristics of randomly selected non-roost trees and day-roosts using a multinomial logistic model and day-roost species selection using chi-squared tests. We found that factors differentiating day-roosts from non-roosts and day-roosts between years varied. Day-roosts differed from non-roosts in the first year of data in all measured factors, but only in size and decay stage in the second year. Between years, day-roosts differed in size and canopy position, but not decay stage. Day-roost species selection was non-random and did not differ between years. Although bats used multiple trees, our results suggest that there were additional unused trees that were suitable as roosts at any time. Day-roost selection pattern descriptions will be inadequate if based only on a single year of data, and inferences of roost selection based only on comparisons of roost to non-roosts should be limited.

Kentucky↗

USGS2017

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Sonoran Desert↗

USGS2019

Patterns of acoustical activity of bats prior to and 10 years after WNS on Fort Drum Army Installation, New York

Previous acoustic surveys, netting, and count data have shown that overall bat activity patterns have shifted among most species between pre- and post-white-nose syndrome (WNS) years in much of North America where WNS has occurred. However, the significance of these changes is based on the species-specific susceptibility to WNS. We used acoustically recorded echolocation passes obtained at Fort Drum, New York to describe changes in bat activity pre-WNS (2004–2007) to post-WNS (2008–2018). We examined seasonal and yearly changes in bat activity as they relate to the presence of WNS at hibernacula near (<25 km) Fort Drum. A priori , we expected that overall activity for communal hibernating species would be less in years following WNS, and migratory bats or those hibernating bats that are less affected by WNS would show no response or a positive response, due to niche relaxation/competitive release. Our results indicated both an overall and seasonal decrease in activity for Myotis spp. post-WNS. For WNS-susceptible species, our results reflect the high level of mortality in regional winter hibernacula post-WNS and possibly variable reproductive effort and recruitment thereafter. Although migratory bats did show increases in post-WNS activity throughout the summer, we found little evidence that community displacement was occurring on a nightly level by any species. The continuous spread of WNS across North America has had strong negative effects on bat populations of affected species, and our research identifies how individual species (both impacted and non-impacted) respond to WNS.

New York↗

USGS2020

Ineffectiveness of light emitting diodes as underwater deterrents for Long-tailed Ducks Clangula hyemalis

Gillnet bycatch accounts for over 400,000 bird mortalities worldwide every year, affecting a wide variety of species, especially those birds that dive when foraging. Technological solutions to improve gillnet visibility or deter birds from approaching nets, such as LED lights, are essential for aiding diving birds to perceive nets as a hazard. Designing such solutions requires obtaining visual and behavioural ecology information from species to assess their ability to see the warning devices, and to examine their behavioural responses to them. Seaducks, particularly Long-tailed Ducks Clangula hyemalis, have high bycatch mortality rates. We examined the visual fields of four Long-tailed Ducks to understand their three-dimensional view around the head. The visual field characteristics of this species indicate a reliance on visual guidance for foraging associated with their capture of varied, mobile prey in their generalist diet. We subsequently conducted dive tank trials to test the effectiveness of 12 different LED treatments as visual deterrents to the underwater foraging behaviour of 8 Long-tailed Ducks. During each trial, ducks were offered food rewards from a specific underwater location in a dive tank, having the choice of whether to take the food or not. At the same time, they were exposed to either one LED light or the control (no light) to determine whether the presence of each light affected the foraging success rate of dives compared to the control. Exposure of ducks to all 13 treatment combinations was randomised over the trial period. White lights with an increasing flash rate were shown to have a significant positive effect on foraging success, and likely acted as a visual attractant, rather than as a deterrent. No light treatment significantly reduced the foraging success of ducks. LED lights did not inhibit the feeding of Long-tailed Ducks. Such lights may be ineffective as underwater visual deterrents when deployed on gillnets, while white flashing lights may make foraging sites more attractive to Long-tailed Ducks.

Global Ecology and Conservation↗

USGS2020

Genetic identification of African pangolins and their origin in illegal trade

To track the illegal pangolin trade from Africa to Asia, we analyzed 1800 DNA samples from 30 seizures of African pangolin scales in Hong Kong during the period 2012–2016. We concluded that all four African pangolin species were present in trade, and that the white-bellied pangolin ( Phataginus tricuspis ) appeared most frequently (88.5%) in our samples. All six previously described phylogeographic lineages originating from the entire distribution range of P. tricuspis were found in the seizures, and the western central African lineage alone accounted for 67.1% of the samples of this species. Confirmed by modelling data, high DNA haplotype richness was present in most of the pangolin scale seizures, including those contained in small air parcels and large-volume sea shipments. Results suggest that African pangolins were hunted across large areas of their natural range and then delivered to a small number of trade transit hubs. Our study illustrates the utility of genetic analysis for characterizing the illegal pangolin trade and identifying the geographic origin of poaching hotspots.

Global Ecology and Conservation↗

USGS2020

Climate’s cascading effects on disease, predation, and hatching success in Anaxyrus canorus, the threatened Yosemite toad

The U.S. Fish and Wildlife Service listed Anaxyrus canorus , the Yosemite toad, as federally threatened in 2014 based upon reported population declines and vulnerability to global-change factors. A. canorus lives only in California’s central Sierra Nevada at medium to sub-alpine elevations. Lands throughout its range are protected from development, but climate and other global-change factors potentially can limit populations. A. canorus reproduces in ultra-shallow wetlands that typically hydrate seasonally via melting of the winter snowpack. Lesser snowpacks in drier years can render wetland water volumes and hydroperiods insufficient to allow for successful breeding and reproduction. Additionally, breeding and embryogenesis occur very soon after wetlands thaw when overnight temperatures can be below freezing. Diseases, such as chytridiomycosis, which recently decimated regional populations of ranid species, also might cause declines of A. canorus populations. However, reported studies focused on whether climate interacts with any pathogens to affect fitness in A. canorus have been scarce. We investigated effects of these factors on A. canorus near Tioga Pass from 1996 to 2001. We found breeding subpopulations were distributed widely but inconsistently among potentially suitable wetlands and frequently consisted of small numbers of adults. We occasionally observed small but not alarming numbers of dead adults at breeding sites. In contrast, embryo mortality often was notably high, with the majority of embryos dead in some egg masses while mortality among coincidental Pseudacris regilla (Pacific treefrog) embryos in deeper water was lower. After sampling and experimentation, we concluded that freezing killed A. canorus embryos, especially near the tops of egg masses, which enabled Saprolegnia diclina (a water mold [Oomycota]) to infect and then spread through egg masses and kill more embryos, often in conjunction with predatory flatworms ( Turbellaria spp.). We also concluded exposure to ultraviolet-B radiation did not play a role. Based upon our assessments of daily minimum temperatures recorded around snow-off during years before and after our field study, the freezing potential we observed at field sites during embryogenesis might have been commonplace beyond the years of our field study. However, interactions among snow quantity, the timing of snow-off, and coincidental air temperatures that determine such freezing potential make projections of future conditions highly uncertain, despite overall warming trends. Our results describe important effects from ongoing threats to the fitness and abundance of A. canorus via reduced reproduction success and demonstrate how climate conditions can exacerbate effects from pathogens to threaten the persistence of amphibian populations.

California↗

USGS2020

Bioaccumulation of the pesticide imidacloprid in stream organisms and sublethal effects on salamanders

Neonicotinoids are one of the most widely used classes of insecticides in the world. The neonicotinoid imidacloprid is commonly applied to hemlock ( Tsuga spp.) stands in eastern North America to reduce tree mortality from infestations of the invasive hemlock woolly adelgid (HWA; Adelges tsugae ). While laboratory and mesocosm studies have determined that imidacloprid can bioaccumulate in anurans and cause sublethal effects, no field studies have investigated whether salamanders or insects in streams adjacent to HWA treatments bioaccumulate imidacloprid or if sublethal effects are detectable in wild salamanders. We assessed relationships between imidacloprid exposure and stream salamander health in West Virginia, USA, using concentration of the stress hormone corticosterone and body condition indices (BCI) as response variables. Of 107 Desmognathus salamanders from 11 sites tested for bioaccumulation, we detected imidacloprid in 47 salamanders. Of 15 benthic macroinvertebrate samples tested, we detected imidacloprid, imidacloprid-urea, and imidacloprid-olefin in 15, 13, and 1 sample, respectively. Based on 115 Desmognathus salamanders sampled at 11 sites for stress hormone responses, corticosterone concentration increased with imidacloprid concentration in stream water. For 802 salamanders sampled at 48 sites, BCI decreased as concentration of imidacloprid in stream water increased, but explanatory power was low. Our study suggests that chronic leaching of imidacloprid from treated hemlock stands into adjacent streams has the potential to negatively affect aquatic organisms and may provide a route of exposure to higher trophic levels.

West Virginia↗

USGS2021

Demography and loss of genetic diversity in two insular populations of the bobcat (Lynx rufus)

Among felids worldwide, only 6 of 38 species have stable or increasing populations, and most felid species are threatened by anthropogenic influences, especially habitat loss and fragmentation. We documented changes in genetic diversity in an isolated, reintroduced population of bobcats on Cumberland Island (CUIS), Georgia, USA, compared to another bobcat population on Kiawah Island, South Carolina, USA, that was naturally established and experiences limited immigration from the mainland. The CUIS population declined from 32 reintroduced bobcats in 1989 to 10–24 individuals during 2012–2019, and observed heterozygosity declined from 0.742 to 0.634 (SD = 0.240). Observed heterozygosity of bobcats on Kiawah was 0.699 (SD = 0.153). We estimated that one bobcat immigrated to Kiawah Island every 5.3 years. We compared the predictions of a novel population viability analysis ( PVA ) to empirical estimates of abundance and genetic diversity on CUIS and used our PVA to identify management actions that are likely to support long-term viability. Mean heterozygosity from the PVA (0.588, SD = 0.065) was within 1 standard deviation of the empirical estimate. The PVA estimated the population would decline following population restoration due to loss of genetic diversity and inbreeding depression. Translocations of one female every four years would stabilize allele heterozygosity similar to the Kiawah Island population, but even translocations of two females every two years would not restore heterozygosity to founder levels. The PVA predicted no management action would result in a one in five probability of extinction within 50 years of reintroduction, but all translocation strategies nearly eliminated extinction risk through 100 years.

Georgia, South Carolina↗

USGS2021

Effects of experimental flea removal and plague vaccine treatments on survival of northern Idaho ground squirrels and two coexisting sciurids

Plague is a non-native disease in North America that reduces survival of many mammals. Previous studies have focused on epizootic plague which causes acute mortality events and dramatic declines in local abundance. We know much less about enzootic plague which causes less punctuated reductions in survival and abundance of infected populations. As a result, enzootic plague is much more difficult to detect because changes in population attributes are more subtle and Yersinia pestis prevalence is likely lower relative to epizootic plague outbreaks. The northern Idaho ground squirrel ( Urocitellus brunneus ) is a threatened species which coexists with Columbian ground squirrels ( Urocitellus columbianus ) and yellow-pine chipmunks ( Neotamias amoenus ) throughout their restricted distribution in central Idaho. Columbian ground squirrels and yellow-pine chipmunks are more abundant and widespread than northern Idaho ground squirrels and both are known hosts for plague. Hence, enzootic plague may be one cause of rarity for northern Idaho ground squirrels but its effect on this threatened species has not been evaluated. We conducted three controlled and randomized field experiments to examine the effects of plague in northern Idaho ground squirrels and the two coexisting species: 1) a plague vaccine experiment, 2) a paired flea-reduction experiment, and 3) a non-paired flea-reduction experiment. For Experiment 1, we hypothesized that if enzootic plague is present, vaccinated animals would have higher survival. Furthermore, Experiments 2 and 3 tested the prediction that untreated, control animals should have lower survival than those in areas where fleas are experimentally removed or reduced because fleas are the main vector for plague. In the plague vaccine experiment, vaccinated chipmunks had 4.65% higher apparent survival compared to chipmunks that received a placebo for intervals when the vaccine is believed to be effective. Apparent annual survival increased for all three species on experimental flea-reduction plots compared to non-treated plots for the paired experiment but results were mixed for the non-paired experiment. Taken together, our results suggest that enzootic plague is present and negatively impacting survival of northern Idaho ground squirrels and two coexisting species.

Idaho↗

USGS2021

Automated telemetry reveals post-reintroduction exploratory behavior and movement patterns of an endangered corvid, ʻAlalā (Corvus hawaiiensis) in Hawaiʻi, USA

Continuous movement monitoring is a powerful tool for evaluating reintroduction techniques and assessing how well reintroduced animals are adjusting to the wild. However, to date, continuous monitoring has only occurred for large-bodied species capable of carrying heavy tracking devices. In this study we used an automated VHF radio telemetry array to investigate the exploratory behavior and movement patterns of critically endangered ʻAlalā ( Corvus hawaiiensis ), reintroduced to the Island of Hawaiʻi in 2017. The 11 juvenile ʻAlalā we tracked exhibited high site fidelity and initial survival. Over time the birds showed decreased time spent at the supplemental feeders, and transitioned to more focused use of the landscape, suggesting increased foraging on wild food items. Birds with seemingly less spatial neophobia at release also made larger post-release exploratory movements. This study provides the first evidence that 1) supplemental feeding can support site fidelity for reintroduced ʻAlalā without restricting a transition to independent foraging, and 2) that pre-release personality metrics may be useful predictors for predicting post-release movements of ʻAlalā. Our work is the first to demonstrate the utility and power of automated telemetry for monitoring the reintroduction of small species.

Hawaii↗