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At least 757 records · Page 42Linked to original sources
USGS2025

Hydrophone placement yields high variability in detection of Epinephelus striatus calls at a spawning site.

Passive acoustic monitoring is a cost-effective, minimally invasive technology commonly used to study behavior and population dynamics of soniferous fish species. To understand the strengths and limitations of acoustic monitoring for this purpose at fish spawning aggregations (FSA) requires an assessment of the variability in aggregation-associated sounds (AAS) as a function of time, space, and proximity for spawning fishes of interest. Here, we evaluate temporal and spatial trends in the detection of AAS by Nassau Grouper ( Epinephelus striatus ) using an array of six hydrophones deployed across a large Nassau Grouper FSA at Little Cayman, Cayman Islands. We collected continuous data for nine days during a winter spawning season and subsequently used an automatic classifier to extract the embedded Nassau Grouper AAS. Using these data, we analyzed variability in spatiotemporal AAS detection rates across the array with a Bayesian mixed effects model. We found high variability in the detection of AAS across the spawning site, with positive correlations among neighboring hydrophone pairs trending toward negative correlations with distances exceeding 350 m. Indeed, temporal trends in AAS rates at the spawning site were approximately inverted at the two most distant hydrophones (~600 m). Across the hydrophone network, our model predicted strong positive effects of fish proximity, spawning behavior, and crepuscular periods on detected AAS. Our findings suggest hydrophone placement can strongly influence AAS detection rates and even basic temporal patterns in AAS across the spawning season. Given both the vagaries of movement and behavior of aggregating fish at spawning sites and the limits of AAS detection using standard monitoring tools, we suggest spawning site acoustic monitoring programs deploy hydrophone arrays of sufficient size to capture the site-wide trends in AAS rates if possible; this is particularly true if researchers hope to compare/contrast AAS rates between spawning sites or across seasons for the purpose of population assessment.

Ecological Applications↗
USGS2023

Backpack satellite transmitters reduce survival but not nesting propensity or success of greater sage-grouse

Telemetry technology is ubiquitous for studying the behavior and demography of wildlife, including the use of traditional very high frequency (VHF) radio telemetry and more recent methods that record animal locations using global positioning systems (GPS). Satellite-based GPS telemetry allows researchers to collect high spatial–temporal resolution data remotely but may also come with additional costs. For example, recent studies from the southern Great Basin suggested GPS transmitters attached via backpacks may reduce the survival of greater sage-grouse ( Centrocercus urophasianus ) relative to VHF transmitters attached via collars that have been in use for decades. While some evidence suggests GPS backpacks reduce survival, no studies have examined the effects of GPS backpacks on breeding behavior and success. Therefore, we compared survival, breeding behavior, and nest success of sage-grouse hens marked with both VHF collars and GPS backpack transmitter over a 7-year period in central Idaho, USA. GPS backpacks reduced spring–summer survival of sage-grouse hens relative to hens with VHF collars, where daily mortality probability was 68%–82% higher from March 1 to August 1. Yet satellite GPS backpacks did not consistently affect nest success or the likelihood or timing of nest initiation relative to VHF collars. Daily nest survival varied annually and with timing of nest initiation and nest age, but marginal effects of transmitter type were statistically insignificant and interactions between transmitter type and study year produced no meaningful patterns. Our results corroborate recent studies for the effect of satellite GPS backpacks on sage-grouse survival, but also suggest that these transmitters do not appear to affect components of fecundity. Our results therefore add important context to recent debate surrounding the effects of GPS backpacks on sage-grouse, and the relative strengths and weaknesses of different transmitter types for understanding behavior and population dynamics.

Idaho↗
USGS2015

Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies

1. Determining the detailed movements of individual animals often requires them to carry tracking devices, but tracking broad-scale movement of small bats (< 30g) has been limited by transmitter technology and long-term attachment methods. This limitation inhibits our understanding of bat dispersal and migration, particularly in the context of emerging conservation issues like fatalities at wind turbines and diseases. 2. We tested a novel method of attaching lightweight global positioning system (GPS) tags and geolocating data loggers to small bats. We used monofilament, synthetic, absorbable sutures to secure GPS tags and data loggers to the skin of anesthetized big brown bats (Eptesicus fuscus) in Colorado and hoary bats (Lasiurus cinereus) in California. 3. GPS tags and data loggers were sutured to 17 bats in this study. Three tagged bats were recaptured seven months after initial deployment, with tags still attached; none of these bats showed ill effects from the tag. No severe injuries were apparent upon recapture of 6 additional bats that carried tags up to 26 days after attachment, however one of the bats exhibited skin chafing. 4. Use of absorbable sutures to affix small tracking devices seems to be a safe, effective method for studying movements of bats over multiple months, although additional testing is warranted. This new attachment method has the potential to quickly advance our understanding of small bats, particularly as more-sophisticated miniature tracking devices (e.g., satellite tags) become available.

Ecology and Evolution↗
USGS2018

Quantitative acoustic differentiation of cryptic species illustrated with King and Clapper rails

Reliable species identification is vital for survey and monitoring programs. Recently, the development of digital technology for recording and analyzing vocalizations has assisted in acoustic surveying for cryptic, rare, or elusive species. However, the quantitative tools that exist for species differentiation are still being refined. Using vocalizations recorded in the course of ecological studies of a King Rail ( Rallus elegans ) and a Clapper Rail ( Rallus crepitans ) population, we assessed the accuracy and effectiveness of three parametric (logistic regression, discriminant function analysis, quadratic discriminant function analysis) and six nonparametric (support vector machine, CART, Random Forest, k ‐nearest neighbor, weighted k ‐nearest neighbor, and neural networks) statistical classification methods for differentiating these species by their kek mating call. We identified 480 kek notes of each species and quantitatively characterized them with five standardized acoustic parameters. Overall, nonparametric classification methods outperformed parametric classification methods for species differentiation (nonparametric tools were between 57% and 81% accurate, parametric tools were between 57% and 60% accurate). Of the nine classification methods, Random Forest was the most accurate and precise, resulting in 81.1% correct classification of kek notes to species. This suggests that the mating calls of these sister species are likely difficult for human observers to tell apart. However, it also implies that appropriate statistical tools may allow reasonable species‐level classification accuracy of recorded calls and provide an alternative to species classification where other capture‐ or genotype‐based survey techniques are not possible.

Ecology and Evolution↗
USGS2019

Estimating the energy expenditure of free‐ranging polar bears using tri‐axial accelerometers: A validation with doubly labeled water

Measures of energy expenditure can be used to inform animal conservation and management, but methods for measuring the energy expenditure of free‐ranging animals have a variety of limitations. Advancements in biologging technologies have enabled the use of dynamic body acceleration derived from accelerometers as a proxy for energy expenditure. Although dynamic body acceleration has been shown to strongly correlate with oxygen consumption in captive animals, it has been validated in only a few studies on free‐ranging animals. Here, we use relationships between oxygen consumption and overall dynamic body acceleration in resting and walking polar bears Ursus maritimus and published values for the costs of swimming in polar bears to estimate the total energy expenditure of 6 free‐ranging polar bears that were primarily using the sea ice of the Beaufort Sea. Energetic models based on accelerometry were compared to models of energy expenditure on the same individuals derived from doubly labeled water methods. Accelerometer‐based estimates of energy expenditure on average predicted total energy expenditure to be 30% less than estimates derived from doubly labeled water. Nevertheless, accelerometer‐based measures of energy expenditure strongly correlated ( r 2 = 0.70) with measures derived from doubly labeled water. Our findings highlight the strengths and limitations in dynamic body acceleration as a measure of total energy expenditure while also further supporting its use as a proxy for instantaneous, detailed energy expenditure in free‐ranging animals.

Alaska, Northwest Territories, Yukon↗
USGS2019

Does perspective matter? A case study comparing Eulerian and Lagrangian estimates of common murre (Uria aalge) distributions

Studies estimating species' distributions require information about animal locations in space and time. Location data can be collected using surveys within a predetermined frame of reference (i.e., Eulerian sampling) or from animal‐borne tracking devices (i.e., Lagrangian sampling). Integration of observations obtained from Eulerian and Lagrangian perspectives can provide insights into animal movement and habitat use. However, contemporaneous data from both perspectives are rarely available, making examination of biases associated with each sampling approach difficult. We compared distributions of a mobile seabird observed concurrently from ship, aerial, and satellite tag surveys during May, June, and July 2012 in the northern California Current. We calculated utilization distributions to quantify and compare variability in common murre (Uria aalge) space use and examine how sampling perspective and platform influence observed patterns. Spatial distributions of murres were similar in May, regardless of sampling perspective. Greatest densities occurred in coastal waters off southern Washington and northern Oregon, near large murre colonies and the mouth of the Columbia River. Density distributions of murres estimated from ship and aerial surveys in June and July were similar to those observed in May, whereas distributions of satellite‐tagged murres in June and July indicated northward movement into British Columbia, Canada, resulting in different patterns observed from Eulerian and Lagrangian perspectives. These results suggest that the population of murres observed in the northern California Current during spring and summer includes relatively stationary individuals attending breeding colonies and nonstationary, vagile adults and subadults. Given the expected growth of telemetry studies and advances in survey technology (e.g., unmanned aerial systems), these results highlight the importance of considering methodological approaches, spatial extent, and synopticity of distribution data sets prior to integrating data from different sampling perspectives.

Washington↗
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↗
USGS2021

Genomic association with pathogen carriage in bighorn sheep (Ovis canadensis)

Genetic composition can influence host susceptibility to, and transmission of, pathogens, with potential population‐level consequences. In bighorn sheep ( Ovis canadensis ), pneumonia epidemics caused by Mycoplasma ovipneumoniae have been associated with severe population declines and limited recovery across North America. Adult survivors either clear the infection or act as carriers that continually shed M. ovipneumoniae and expose their susceptible offspring, resulting in high rates of lamb mortality for years following the outbreak event. Here, we investigated the influence of genomic composition on persistent carriage of M. ovipneumoniae in a well‐studied bighorn sheep herd in the Wallowa Mountains of Oregon, USA. Using 10,605 SNPs generated using RADseq technology for 25 female bighorn sheep, we assessed genomic diversity metrics and employed family‐based genome‐wide association methodologies to understand variant association and genetic architecture underlying chronic carriage. We observed no differences among genome‐wide diversity metrics (heterozygosity and allelic richness) between groups. However, we identified two variant loci of interest and seven associated candidate genes, which may influence carriage status. Further, we found that the SNP panel explained ~55% of the phenotypic variance (SNP‐based heritability) for M. ovipneumoniae carriage, though there was considerable uncertainty in these estimates. While small sample sizes limit conclusions drawn here, our study represents one of the first to assess the genomic factors influencing chronic carriage of a pathogen in a wild population and lays a foundation for understanding genomic influence on pathogen persistence in bighorn sheep and other wildlife populations. Future research should incorporate additional individuals as well as distinct herds to further explore the genomic basis of chronic carriage.

Oregon↗
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

Sapsucker wells as a keystone nutritional resource: Evaluating methods for detection of secondary sap consumers

North American sapsuckers are considered double keystone species because they (1) excavate nest cavities that are used by other birds, small mammals, and invertebrates, and (2) create and maintain sap wells, a temporary nutritional resource available to a variety of secondary consumers. Most previous reports of secondary sap consumption relied on human observers and were based on either brief or incidental observations. However, modern technology can greatly enhance observational techniques and provide additional insights into the functional, community-level importance of sap wells. We used visual surveys, camera traps, and environmental DNA (eDNA) to identify secondary consumers of sap from wells created by red-naped ( Sphyrapicus nuchalis ) and Williamson's ( S. thyroideus ) sapsuckers among three functional groups of shrubs and trees in south-central Colorado: shrub willows ( Salix spp.), Rocky Mountain maple ( Acer glabrum ), and conifer trees (Pinopsida). Camera traps and eDNA revealed additional sap-well visitors not identified from direct observations. Camera traps were effective for detecting nocturnal sap-well visitors such as small rodents as well as occasional diurnal visitors. Environmental DNA analyses corroborated findings from other methods and identified four additional taxa as possible sap consumers. The physiology of sap-well visitors, such as the ability to taste and assimilate compounds within sap, may aid in determining consumption versus contact when evaluating the results of eDNA analyses. Total vertebrate taxa detected using all 3 methods included 17 bird taxa in 10 families within 3 orders and 8 mammal taxa in 6 families within 4 orders. Shrub-willow sap wells attracted the most diverse vertebrate taxa (23), followed by Rocky Mountain maple (13) and conifer trees (10). Invertebrates in 13 families within 3 orders were observed feeding from sap wells during visual surveys. Because many secondary sap consumers perform ecological services such as pollination, seed dispersal, and pest control, the methods described here may aid in elucidating the importance of sap-well creators in supporting biodiversity and ecosystem functioning.

Colorado↗
USGS2022

Optimizing trilateration estimates for tracking fine-scale movement of wildlife using automated radio telemetry networks

A major advancement in the use of radio telemetry has been the development of automated radio tracking systems (ARTS), which allow animal movements to be tracked continuously. A new ARTS approach is the use of a network of simple radio receivers (nodes) that collect radio signal strength (RSS) values from animal-borne radio transmitters. However, the use of RSS-based localization methods in wildlife tracking research is new, and analytical approaches critical for determining high-quality location data have lagged behind technological developments. We present an analytical approach to optimize RSS-based localization estimates for a node network designed to track fine-scale animal movements in a localized area. Specifically, we test the application of analytical filters (signal strength, distance among nodes) to data from real and simulated node networks that differ in the density and configuration of nodes. We evaluate how different filters and network configurations (density and regularity of node spacing) may influence the accuracy of RSS-based localization estimates. Overall, the use of signal strength and distance-based filters resulted in a 3- to 9-fold increase in median accuracy of location estimates over unfiltered estimates, with the most stringent filters providing location estimates with a median accuracy ranging from 28 to 73 m depending on the configuration and spacing of the node network. We found that distance filters performed significantly better than RSS filters for networks with evenly spaced nodes, but the advantage diminished when nodes were less uniformly spaced within a network. Our results not only provide analytical approaches to greatly increase the accuracy of RSS-based localization estimates, as well as the computer code to do so, but also provide guidance on how to best configure node networks to maximize the accuracy and capabilities of such systems for wildlife tracking studies.

Ecology and Evolution↗
USGS2019

An analysis of autocorrelation and bias in home range estimation

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function AKDE, Silvermans rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area ) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area . To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animals movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area . While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area , AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.

Ecological Monographs↗
USGS2016

Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear

The capacity to describe and quantify predation by large carnivores expanded considerably with the advent of GPS technology. Analyzing clusters of GPS locations formed by carnivores facilitates the detection of predation events by identifying characteristics which distinguish predation sites. We present a performance assessment of GPS cluster analysis as applied to the predation and scavenging of an omnivore, the American black bear ( Ursus americanus ), on ungulate prey and carrion. Through field investigations of 6854 GPS locations from 24 individual bears, we identified 54 sites where black bears formed a cluster of locations while predating or scavenging elk ( Cervus elaphus ), mule deer ( Odocoileus hemionus ), or cattle ( Bos spp.). We developed models for three data sets to predict whether a GPS cluster was formed at a carnivory site vs. a non-carnivory site (e.g., bed sites or non-ungulate foraging sites). Two full-season data sets contained GPS locations logged at either 3-h or 30-min intervals from April to November, and a third data set contained 30-min interval data from April through July corresponding to the calving period for elk. Longer fix intervals resulted in the detection of fewer carnivory sites. Clusters were more likely to be carnivory sites if they occurred in open or edge habitats, if they occurred in the early season, if the mean distance between all pairs of GPS locations within the cluster was less, and if the cluster endured for a longer period of time. Clusters were less likely to be carnivory sites if they were initiated in the morning or night compared to the day. The top models for each data set performed well and successfully predicted 71–96% of field-verified carnivory events, 55–75% of non–carnivory events, and 58–76% of clusters overall. Refinement of this method will benefit from further application across species and ecological systems.

New Mexico↗
USGS2020

Distance effects of gas field infrastructure on pygmy rabbits in southwestern Wyoming

As domestic energy development activity continues in the western United States, wildlife conservation planning in affected regions is increasingly important. The geologic basins where oil and gas energy exploration is occurring are primarily sagebrush steppe rangelands. Sagebrush steppe habitats may support more than 20 vertebrate species of conservation concern, and for many of these species, information is lacking on the effects of gas energy development. In earlier work, we demonstrated a negative relationship among development density of gas field infrastructure and pygmy rabbits ( Brachylagus idahoensis ). We now examine the spatial relationship among gas field infrastructure, pygmy rabbits, and their habitat on four major gas fields in southwest Wyoming. Using data collected from 120 plots over three years (2011–2013) and 2012 National Agriculture Imagery Program (NAIP) imagery, we evaluated (1) whether well pads are more likely to be located in areas of pygmy rabbit habitat, (2) whether the presence and abundance of pygmy rabbits are related to distance from infrastructure, and, if so, (3) how much of the total surface area on a gas field is affected. Well pads on three gas fields occurred in higher quality pygmy rabbit habitat than did a set of randomly generated points, and the abundance and probability of pygmy rabbits being present were lower within approximately 0.5–1.5 km of the nearest road and 2 km of well pads and utilities. Buffering a digital layer of roads and well pads on one gas field revealed that nearly 82% of the (4417 km 2 ) surface area was within 1 km of infrastructure, and over 95% of the gas field surface area was within 2 km. This need not be the case on future gas fields. Directional and horizontal well drilling technologies now make it possible for gas to be recovered from a greater area per well pad, enabling future gas field developments that require fewer well pads, roads, and pipeline corridors. Such changes would enable increased well pad spacing and provide the opportunity to locate gas field infrastructure in areas of poor quality wildlife habitat, avoid high priority habitat, and conserve a greater amount of on‐field wildlife habitat overall.

Wyoming↗
USGS2021

Differential landscape use by forest owls two years after a mixed-severity wildfire

Owls are important avian predators in forested systems, but little is known about landscape use by most forest-adapted owl species in environments impacted by mixed-severity wildfire. To better understand species-specific patterns of post-wildfire landscape use within an owl guild, we used passive acoustic monitoring using autonomous recording units. The technology is effective for multi-species surveys, especially if some species are rare, nocturnal, or difficult to detect by traditional means. In 2017, we surveyed the interior and adjacent unburned areas of a 10,700-ha mixed-severity wildfire that burned in 2015 in southwest Oregon. We used occupancy modeling to identify patterns of landscape use by five species of forest owls: barred owls ( Strix varia ), great horned owls ( Bubo virginianus ), western screech-owls ( Megascops kennicottii ), northern pygmy-owls ( Glaucidium gnoma ), and northern saw-whet owls ( Aegolius acadicus ). Our results showed a positive relationship between increasing fire severity and probability of use by western screech-owls and a similar but somewhat weaker relationship for northern pygmy-owls. Barred owls were rarely detected in severely burned areas and their use decreased with increased fire severity. We observed generally low landscape use for great horned owls, which decreased with increased fire severity and at higher elevations. Thus, four out of the five species appeared to use recently burned forests at different levels, with only northern saw-whet owls showing near-complete avoidance of the burned area. These findings increase our understanding of the basic ecology of each species and highlight the varied use of burned areas within this community. These previously undocumented patterns of landscape use in burned landscapes should provide insights to managers and policymakers in the Pacific Northwest as climate shifts, and fires may increase in size, frequency, and severity.

Oregon↗
USGS2021

Asynchronous flowering patterns in saguaro cacti (Carnegiea gigantea)

The saguaro cactus ( Carnegiea gigantea [Engelm.] Britton & Rose) is a keystone species endemic to the Sonoran Desert of northern Mexico and the southwestern United States. The saguaro produces large white flowers near its stem apex (crown) during April–June, which bloom at night and close the following day. In 1924, Duncan Johnson reported that saguaro floral buds are likely to have an asymmetrical distribution in which buds occur in higher densities on the eastern half of a plant's crown. Using technology not available to Johnson, we tested his observations to determine whether flowers are asymmetrically distributed using repeat photography. We also tested whether there is a seasonal pattern of flowering that may explain Johnson’s observations. We tracked intra-individual flowering phenology of 20 saguaros and measured 2372 flowers across two reproductive seasons in Saguaro National Park, Tucson, Arizona. Flowers first appeared on the east side of all saguaro crowns at the start of the reproductive season, and then spread radially in a counterclockwise direction as the season progressed. In contrast to previous reports, saguaro flowers were consistently more abundant on the northern part of the crown than in the eastern part. To our knowledge, this study is the first to document a seasonal, counterclockwise pattern of asynchronous flowering in saguaro or any angiosperm. We discuss potential drivers of this phenomenon as well as implications for saguaros responding to climate change.

Arizona↗
USGS2022

Estimating wolf abundance from cameras

Monitoring the abundance of rare carnivores is a daunting task for wildlife biologists. Many carnivore populations persist at relatively low densities, public interest is high, and the need for population estimates is great. Recent advances in trail camera technology provide an unprecedented opportunity for biologists to monitor rare species economically. Few studies, however, have conducted rigorous analyses of our ability to estimate abundance of low-density carnivores with cameras. We used motion-triggered trail cameras and a space-to-event model to estimate gray wolf ( Canis lupus ) abundance across three study areas in Idaho, USA, 2016–2018. We compared abundance estimates between cameras and noninvasive genetic sampling that had been extensively tested in our study areas. Estimates of mean wolf abundance from camera and genetic surveys were within 22% of one another and 95% CIs overlapped in 2 of the 3 years. A single camera with many detections appeared to bias camera estimates high in 2018. A subsequent bootstrapping procedure produced a population estimate from cameras equal to that derived from genetic sampling, however. Camera surveys were less than half the cost of genetic surveys once initial camera purchases were made. Our results suggest that cameras can be a viable method for estimating wolf abundance across broad landscapes (>10,000 km 2 ).

Idaho↗
USGS2023

Diverse migratory portfolios drive inter-annual switching behavior of elk across the Greater Yellowstone Ecosystem

A growing body of evidence shows that some ungulates alternate between migratory and nonmigratory behaviors over time. Yet it remains unclear whether such short-term behavioral changes can help explain reported declines in ungulate migration worldwide, as opposed to long-term demographic changes. Furthermore, advances in tracking technology reveal that a simple distinction between migration and nonmigration may not sufficiently describe all individual behaviors. To better understand the dynamics and drivers of ungulate switching behavior, we investigated 14 years of movement data from 361 elk in 20 herds across the Greater Yellowstone Ecosystem (GYE). First, we categorized yearly individual behaviors using a clustering algorithm that identified similar migratory tactics across a continuum of behaviors. Then, we tested seven hypotheses to explain why some ungulates switch behaviors, and we evaluated how behavioral changes affected the proportions of different behaviors across the system. We identified four distinct behavioral tactics: residents (4.8% of elk-years), short-distance migrants (53.7%), elevational migrants (21.9%) and long-distance migrants (19.6%). Of the 20 herds, 18 were partially migratory, and 5 had all four movement tactics present. We observed switches between migratory tactics in all sets of consecutive years during our study period, with an average of 22.5% of individual elk changing movement tactics from one year to the next. Elk in herds with higher movement tactic diversity were significantly more likely to switch tactics and often responded more effectively to adverse environmental conditions, compared to those in herds with low movement tactic diversity. During our study period, switching increased the prevalence of both short- and long-distance migrants, decreased the prevalence of elevational migrants, and had no effect on the prevalence of residents. Our findings suggest that rather than contributing to the declining migratory behavior found in the GYE, switching behavior may enable greater resiliency to continuously changing environmental and anthropogenic conditions.

Wyoming↗