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James W. Cain

Publications and source records attributed to James W. Cain.

At least 55 records · Page 3Linked to original sources
USGS2019

Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data

Increasing tree canopy cover has led to increasing wildfire activity in conifer dominated areas of the southwestern United States. Estimating historical changes in the spatial distribution of tree canopy cover can provide further insights into the dynamics of forest and fuel conditions in these landscapes and help prioritize areas for restoration to mitigate wildfire risks and restore biological functioning. In this study, we explored the relationship between LiDAR derived canopy cover data and Landsat reflectance values, and derived a model to estimate percent canopy cover (PCC) on historical Landsat data from 1987 to 2015 for the Valles Caldera National Preserve (VCNP), located in the southwest Jemez Mountains of New Mexico. We developed a regression model between LiDAR generated canopy cover collected in June 2010 and Landsat Thematic Mapper (TM) reflectance values (bands 1–7 except band 6) and vegetation indices collected for the same date. About 5% (17,000) of the total LiDAR points (329,102) were used as training points and a separate, non-overlapping set of 17,000 points as test points to validate the regression model. A simple linear model with the red band (band 3; R 2 = 0.70) was selected as the best model to predict PCC in the rest of the images for 1987–2015. In general, we found a strong consistency between the spatial dynamics of modelled tree canopy cover based on historical Landsat data, wildfire events and forest management practicesthat occurred during the same period. Results showed that about 11% of the study area experienced an increase in PCC for the period of 1987–2015 while 41% of the study area experienced a reduction in PCC during the same time period, mostly in the areas which were affected by stand replacing wildfires in 2011 and 2013. The results indicate an overall increase in medium and high canopy cover classes in specific regions of the study area, which could lead to hazardous wildfires such as those in 2011 and 2013. In the context of ongoing ecological restoration of these montane forests, predicted PCC of contemporary forests could help local managers to identify the areas in the need of immediate restoration efforts by focusing management practices on the areas with closed canopy.

New Mexico↗
USGS2019

Validating the performance of occupancy models for estimating habitat use and predicting the distribution of highly-mobile species: A case study using the American black bear

Occupancy models have become a valuable tool for estimating wildlife-habitat relationships and for predicting species distributions. Highly-mobile species often violate the assumption that sampling units are geographically closed shifting the probability of occupancy to be interpreted as the probability of use. We used occupancy models, in conjunction with noninvasive sampling, to estimate habitat use and predict the distribution of a highly-mobile carnivore, the American black bear ( Ursus americanus ) in New Mexico, USA. The top model indicated that black bears use areas with higher primary productivity and fewer roads. The predictive performance of such models is rarely validated with independent data, so we validated our model predictions with 2-independent datasets. We first assessed the correlation between predicted and observed habitat use for 28 telemetry-collared bears in the Jemez Mountains. Predicted habitat use was positively correlated with observed use for all 3 years (2012: ρ = 0.81; 2013: ρ = 0.87; 2014: ρ = 0.90). We then predicted the probability of use within a cell where a bear mortality was documented using 2043 mortality locations from sport harvest, depredation, and vehicle collisions. The probability of habitat use at a mortality location was also positively correlated with observed use by the species (2012: ρ = 0.74; 2013: ρ = 0.89; 2014: ρ = 0.93). Our validation procedure supports the notion that occupancy models can be an effective tool for estimating habitat use and predicting the distribution of highly-mobile species when the assumption of geographic closure has been violated. Our findings may be of interest to studies that are estimating habitat use for highly-mobile species that are secretive or rare, difficult to capture, or expensive to monitor with other more intensive methods.

New Mexico↗
USGS2019

Forest restoration, wildfire, and habitat selection by female mule deer

Decades of fire suppression, logging, and overgrazing have led to increased densities of small diameter trees which have been associated with decreases in biodiversity, reduced habitat quality for wildlife species, degraded foraging conditions for ungulates, and more frequent and severe wildfires. In response, land managers are implementing forest restoration treatments using prescribed fire and thinning to mitigate the risk of catastrophic wildfires and improve habitat conditions for a variety of wildlife species. We monitored habitat selection by female mule deer ( Odocoileus hemionus ) in relation to forest restoration treatments and wildfires in northern New Mexico in 2015. Our specific objectives were to assess changes in forage abundance and determine habitat selection patterns of mule deer in relation to recent wildfires, forest restoration treatments, including duration of the post-treatment recovery, and other habitat characteristics. Herbaceous forage biomass was greater in wildfire-burned areas than in untreated areas or those treated with prescribed burns or thinning. Oak forage biomass was greater in wildfire-burned areas compared to prescribed burns, forest thinning, and untreated areas. However, thinned areas tended to have higher oak forage biomass than untreated areas. Mule deer selected for areas burned by prescribed fire and generally avoided wildfire-burned and thinned areas <5 years old. Mule deer strongly selected for thinned areas ≥5 years old. At both the landscape and home-range scale, grasslands were avoided during most seasons, pinyon-juniper woodlands were selected in winter, and oak vegetation and mixed-conifer forests were selected during summer. Our data suggests that mule deer may benefit from recent prescribed burns and older forest thinning, but the duration of post-treatment vegetation recovery influences the strength and direction of selection. Knowledge of the short- and long-term effects of restoration treatments will provide managers with the means to make more informed decisions regarding implementation of forest restoration and other vegetation treatments intended to benefit mule deer.

New Mexico↗
USGS2019

Pathogen prevalence in American black bears (Ursus americanus) of the Jemez Mountains, New Mexico, USA

Informed management of American black bears ( Ursus americanus ) requires knowledge of the distribution and pathology of diseases affecting the species. Little information is available on pathogen prevalence from black bear populations in the Southwest, US, and it is unknown how these infections may influence black bear populations or disease transmission. We captured New Mexico black bears ( Ursus americanus amblyceps ) during 2016–17 as part of a long-term monitoring project and opportunistically collected 36 blood samples from 12 female and 17 male black bears. We wanted to determine prior exposure to canine distemper virus, canine parvovirus, Yersinia pestis , Francisella tularensis , West Nile virus, Toxoplasma gondii , and the tick-borne pathogens, Anaplasma spp., Ehrlichia spp., Borrelia burgdorferi , Rickettsia spp., and Babesia spp. Approximately half (55%, 16/29) of the individuals sampled had antibodies to Y. pestis , and 37% (10/27) had antibodies to T. gondii . Prevalence of antibodies to West Nile virus, F. tularensis , and canine parvovirus were lower (i.e., 11, 10, and 3%, respectively). We detected no antibodies to canine distemper, B. burgdorferi , Rickettsia spp., or Babesia spp. We documented changes in antibody titer levels for both sexes of several recaptured black bears. Our data will inform managers of pathogen prevalence and distribution in black bears in north-central New Mexico and provide a vital baseline dataset for future pathogen monitoring. Additionally, these data support actions to minimize exposure through handling wild individuals or through hunter harvest activities.

New Mexico↗
USGS2018

Survival and cause-specific mortality of desert bighorn sheep lambs

Juvenile recruitment in desert bighorn sheep (Ovis canadensis mexicana) is highly variable, yet the mechanisms driving neonate survival are not well understood for the species. Few studies have equipped desert bighorn sheep lambs with radiocollars. As a result, definitive data on cause-specific mortality and lamb survival estimates are lacking. Our objectives were to estimate lamb survival rates and determine cause-specific mortality for desert bighorn sheep lambs during a period of mountain lion (Puma concolor) and coyote (Canis latrans) removal in southwestern New Mexico. We captured pregnant adult females each fall and fitted them with a telemetry collar and a vaginal implant transmitter to aid with neonate captures. We captured and radiocollared 12 desert bighorn sheep lambs in 2012 and 14 in 2013 within 48 hrs of parturition in the Peloncillo Mountains, New Mexico. We used the nest survival model in program MARK to estimate lamb survival to 6 months of age. Across both years there were 14 mortalities, 12 (86%) of which were due to predation. Mountain lions killed 5 lambs (2 in 2012 and 3 in 2013), coyotes killed 4 lambs (all in 2013), a gray fox (Urocyon cinereoargenteus) killed 1 lamb in 2012; 2 lambs were killed by unknown predators in 2013. Staged-based survival estimates indicated the highest mortality rates occurred in the first week post birth; 33% to 36% of all lamb mortalities occurred before 7 days of age. Lamb survival was substantially lower in 2013 (0.20 ± 0.11 [SE]) than in 2012 (0.69 ± 0.16) with the differences in survival attributed to increased coyote predation in 2013. We did not detect differences in body mass, chest girth, or neck circumference between lambs that were killed by predators and those that survived. Coyotes, mountain lions and gray fox killed lambs <8 weeks of age, but only mountain lions killed lambs > 8 weeks old. Studies that fail to capture desert bighorn lambs near parturition will likely produce negatively biased survival estimates and inaccurate appraisals of primary causes of mortality due to early mortality of lambs.

New Mexico↗
USGS2018

Evaluation of key scientific issues in the report, “State of the mountain lion—A call to end trophy hunting of America’s lion”

In their recently published report, State of the Mountain Lion: A Call to End Trophy Hunting of America’s Lion , the Humane Society of the United States suggested that mountain lion ( Puma concolor ) hunting should be abolished in the United States. The report claims this recommendation is based on scientific arguments that demonstrate the overharvest of mountain lions throughout much of their current range in the United States. We reviewed the science presented by the Humane Society to support their call for the cessation of mountain lion hunting. Rather than provide a rigorous assessment of the peer-reviewed scientific literature and available data on mountain lion ecology, population dynamics and management, the report uses a fundamentally unscientific approach that starts with an a priori assumption that hunting is detrimental to the long-term persistence of mountain lion populations, then attempts to use scientific arguments to support this value-based position. The report frequently ignores or selectively interprets relevant peer-reviewed literature, weakening the scientific credibility of the report. The report relies on imprecise and inadequate demographic measures, questionable data, and simplistic methodologies to derive dubious estimates of potential lion densities; it compares these estimates to various measures produced by State agencies (which themselves vary in reliability as estimates of abundance) to purportedly illustrate the detrimental effects of hunting. The approach used in the report to support the predetermined supposition that mountain lion populations are over-hunted fails to serve as a scientifically defensible foundation for management recommendations range-wide or at the State level.

Open-File Report↗
USGS2018

An individual-based model for predicting dynamics of a newly established Mexican wolf (Canis lupus baileyi) population—Final report

Project Summary The Mexican wolf recovery team proposed to establish other populations of Mexican wolves ( Canis lupus baileyi ) in the Southwest (U.S. Fish and Wildlife Service, 1982). We were tasked to conduct an extensive simulation modeling exercise to determine release strategies (in conjunction with management actions) that best predict establishment of a new Mexican wolf population. Our objectives were to determine optimal release and management strategies for population establishment and growth. This is a retrospective analysis utilizing data from 1998 to 2014, and during this period, we divided management strategies into two phases; (1) 1998–2008, where nuisance wolves (i.e., wolves that exhibit nuisance behavior or depredate livestock) were managed primarily through lethal removals and removals to captivity, and (2) 2009–2014, when lethal removals ceased and diversionary feeding was provided to denning packs to dissuade wolves from conflict with humans. Management strategies from the second phase are being used for management of the current Mexican wolf population, and demographic rates derived from alternate population modeling in Vortex incorporating post-2008 wolf data are being used to guide future recovery efforts. Therefore, demographic rates estimated from our retrospective analysis will differ (i.e., due to our unique approach to the analyses and the demographic rates being derived from a different dataset), and are intended solely to address the objectives of this report, and are not intended as basis for the development of management recommendations for the current Mexican wolf population. Using individual-based models, we tested dozens of scenarios and derived an optimal release strategy that had the highest probability of establishing a new population and which maximized subsequent post-release growth, and in this report, we present these model results. Findings from this research will improve our understanding of release strategies that yield growing populations, advance our understanding of the demands of reintroducing large carnivores, and provide insight into beneficial strategies that could aid other species reintroduction programs.

Arizona, New Mexico↗
USGS2018

Density of American black bears in New Mexico

Considering advances in noninvasive genetic sampling and spatially explicit capture–recapture (SECR) models, the New Mexico Department of Game and Fish sought to update their density estimates for American black bear ( Ursus americanus ) populations in New Mexico, USA, to aide in setting sustainable harvest limits. We estimated black bear density in the Sangre de Cristo, Sandia, and Sacramento Mountains, New Mexico, 2012–2014. We collected hair samples from black bears using hair traps and bear rubs and used a sex marker and a suite of microsatellite loci to individually genotype hair samples. We then estimated density in a SECR framework using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We sampled the populations using 554 hair traps and 117 bear rubs and collected 4,083 hair samples. We identified 725 (367 male, 358 female) individuals. Our density estimates varied from 16.5 bears/100 km 2 (95% CI = 11.6–23.5) in the southern Sacramento Mountains to 25.7 bears/100 km 2 (95% CI = 13.2–50.1) in the Sandia Mountains. Overall, detection probability at the activity center (g0) was low across all study areas and ranged from 0.00001 to 0.02. The low values of g0 were primarily a result of half of all hair samples for which genotypes were attempted failing to produce a complete genotype. We speculate that the low success we had genotyping hair samples was due to exceedingly high levels of ultraviolet (UV) radiation that degraded the DNA in the hair. Despite sampling difficulties, we were able to produce density estimates with levels of precision comparable to those estimated for black bears elsewhere in the United States.

New Mexico↗
USGS2018

Predicting spatial factors associated with cattle depredations by the Mexican wolf (Canis lupus baileyi) with recommendations for depredation risk modeling

Aim Predation on livestock is one of the primary concerns for Mexican wolf ( Canis lupus baileyi ) recovery because it causes economic losses and negative attitudes toward wolves. Our objectives were to develop a spatial risk model of cattle depredation by Mexican wolves in the USA portion of their recovery area to help reduce the potential for future depredations. Location Arizona and New Mexico, USA. Methods We used a presence-only maximum entropy modeling approach (Maxent) to develop a risk model based on confirmed depredation incidents on public lands . In addition to landscape and human variables, we developed a model for annual livestock density using linear regression analysis of Animal Unit Month (AUM), and models for abundance of elk ( Cervus canadensis ), mule deer ( Odocoileus hemionus ) and white-tailed deer ( Odocoileus virginiana ) using Maxent, to include them as biotic variables in the risk model. We followed current recommendations for controlling model complexity and other sources of bias. Results The primary factors associated with increased risk of depredation by Mexican wolf were higher canopy cover variation and higher relative abundance of elk. Additional factors with increased risk but smaller effect were gentle and open terrain, and greater distances from roads and developed areas. Main conclusions The risk map revealed areas with relatively high potential for cattle depredations that can inform future expansion of Mexican wolf distribution (e.g., by avoiding hotspots) and prioritize areas for depredation risk mitigation including the implementation of active non-lethal methods in depredation hotspots. We suggest that livestock be better protected in or moved from potential hotspots, especially during periods when they are vulnerable to depredation (e.g. calving season). Our approach to create natural prey and livestock abundance variables can facilitate the process of spatial risk modeling when limitations in availability of abundance data are a challenge, especially in large-scale studies.

Arizona, New Mexico↗
USGS2018

Survival and cause-specific mortality of translocated female mule deer in southern New Mexico, USA

Context: Many mule deer ( Odocoileus hemionus ) populations in New Mexico have failed to recover from previous population declines, while some populations near urban areas have increased, resulting in more frequent human–wildlife conflicts. Translocations were used in an effort to simultaneously reduce an urban mule deer population and augment two low-density populations in south-western New Mexico, USA. Aims: Because of insufficient monitoring, the efficacy of many ungulate translocations is unknown. Our goal was to monitor cause-specific mortality and 1 year post-release survival of mule deer translocated during 2013 and 2014. We compared survival rates of mule deer released with a hard- versus soft-release during the 2014 translocation. Methods: . We translocated 218 mule deer in 2013 and 2014 into the Peloncillo Mountains (PM) and San Francisco River Valley (SFRV); 106 adult female mule deer were fitted with telemetry collars to determine cause-specific mortality and estimate survival 1 year post-release. All deer were hard-released in 2013. In 2014, translocated mule deer were either held in a soft-release pen (0.81 ha) for approximately 3 weeks or hard-released into their new environment. We used a Kaplan–Meier approach to estimate survival of translocated mule deer at each release area and to compare survival of mule deer translocated using each release method (i.e. hard- versus soft-release). Key results: In 2013–14, survival of hard-released deer in the PM was 0.627 (s.e. = 0.09), compared with 0.327 (s.e. = 0.10) in the SFRV. In 2014–15, survival of hard–released deer in the PM was 0.727 (s.e. = 0.13) and survival of soft-released deer was 0.786 (s.e. = 0.11). In the SFRV, survival of hard- and soft-released deer was 0.656 (s.e. = 0.14) and 0.50 (s.e. = 0.16), respectively. Causes of mortality were predation (51%), potential disease (9%; blue tongue or epizootic haemorrhagic disease), accident (5%), poaching (5%) and unknown (20%). Conclusions: Translocations can be an effective management tool to augment populations of mule deer while reducing overabundant urban populations. Soft-released mule deer did not have higher survival than hard-released mule deer, although the length and conditions of the acclimation period were limited in our study. Implications: Overabundant mule deer populations in urban areas may serve as sources of animals to bolster declining populations. Soft-release pens of smaller size and short period of acclimation did not influence survival.

New Mexico↗
USGS2017

Identifying ecologically relevant scales of habitat selection: diel habitat selection in elk

Although organisms make resource selection decisions at multiple spatiotemporal scales, not all scales are ecologically relevant to any given organism. Ecological patterns and rhythms such as behavioral and climatic patterns may provide a consistent method for identifying ecologically relevant scales of habitat selection. Using elk ( Cervus canadensis ) as an example species, we sought to test the ability of behavioral patterns to empirically partition diel scales for modeling habitat selection. We used model selection to partition diel scales by shifts in dominant behavior and then used resource selection probability functions to model elk habitat selection hierarchically at diel scales within seasons. Model selection distinguished four diel temporal partitions following elk crepuscular behavioral patterns: dawn, midday, dusk, and night. Across seasons, model‐averaged coefficients indicated that elk shifted from selecting grassland cover at dawn/dusk, to selecting for greater canopy and forest cover at midday, and then to areas with greater herbaceous biomass at night. Top models changed between diel intervals in spring and fall but stayed the same across diel intervals in winter and summer. In winter, elk selected for southern aspects during midday, for unburned areas at dawn/dusk, and for areas burned within 1–3 yr at dawn/dusk and night. In spring, elk selected for northern aspects and for areas burned within 1–3 yr at midday, for areas farther from roads at dawn/dusk and midday, and for areas farther from water at midday. In summer, elk changed diel preferences for fewer covariates: At dawn/dusk and midday, elk selected for areas farther from water and avoided forest cover, and at night, elk selected for areas burned within 1–3 yr. In fall, elk selected for areas burned the previous year at dawn/dusk and night, for higher elevations at midday, and for areas closer water at night. Using behavioral patterns to identify ecologically relevant scales can help identify overlooked habitat requirements such as diel changes in preference for fire history, forage availability, and cover. We show that the ecological relevancy of a given scale (e.g., a diel temporal scale) can change throughout a given extent (e.g., across seasons).

New Mexico↗
USGS2017

Mapping tree density in forests of the southwestern USA using Landsat 8 data

The increase of tree density in forests of the American Southwest promotes extreme fire events, understory biodiversity losses, and degraded habitat conditions for many wildlife species. To ameliorate these changes, managers and scientists have begun planning treatments aimed at reducing fuels and increasing understory biodiversity. However, spatial variability in tree density across the landscape is not well-characterized, and if better known, could greatly influence planning efforts. We used reflectance values from individual Landsat 8 bands (bands 2, 3, 4, 5, 6, and 7) and calculated vegetation indices (difference vegetation index, simple ratios, and normalized vegetation indices) to estimate tree density in an area planned for treatment in the Jemez Mountains, New Mexico, characterized by multiple vegetation types and a complex topography. Because different vegetation types have different spectral signatures, we derived models with multiple predictor variables for each vegetation type, rather than using a single model for the entire project area, and compared the model-derived values to values collected from on-the-ground transects. Among conifer-dominated areas (73% of the project area), the best models (as determined by corrected Akaike Information Criteria (AICc)) included Landsat bands 2, 3, 4, and 7 along with simple ratios, normalized vegetation indices, and the difference vegetation index ( R 2 values for ponderosa: 0.47, piñon-juniper: 0.52, and spruce-fir: 0.66). On the other hand, in aspen-dominated areas (9% of the project area), the best model included individual bands 4 and 2, simple ratio, and normalized vegetation index ( R 2 value: 0.97). Most areas dominated by ponderosa, pinyon-juniper, or spruce-fir had more than 100 trees per hectare. About 54% of the study area has medium to high density of trees (100–1000 trees/hectare), and a small fraction (4.5%) of the area has very high density (>1000 trees/hectare). Our results provide a better understanding of tree density for identifying areas in need of treatment and planning for more effective treatment. Our analysis also provides an integrated method of estimating tree density across complex landscapes that could be useful for further restoration planning.

New Mexico↗
USGS2017

Extreme precipitation variability, forage quality and large herbivore diet selection in arid environments

Nutritional ecology forms the interface between environmental variability and large herbivore behaviour, life history characteristics, and population dynamics. Forage conditions in arid and semi-arid regions are driven by unpredictable spatial and temporal patterns in rainfall. Diet selection by herbivores should be directed towards overcoming the most pressing nutritional limitation (i.e. energy, protein [nitrogen, N], moisture) within the constraints imposed by temporal and spatial variability in forage conditions. We investigated the influence of precipitation-induced shifts in forage nutritional quality and subsequent large herbivore responses across widely varying precipitation conditions in an arid environment. Specifically, we assessed seasonal changes in diet breadth and forage selection of adult female desert bighorn sheep Ovis canadensis mexicana in relation to potential nutritional limitations in forage N, moisture and energy content (as proxied by dry matter digestibility, DMD). Succulents were consistently high in moisture but low in N and grasses were low in N and moisture until the wet period. Nitrogen and moisture content of shrubs and forbs varied among seasons and climatic periods, whereas trees had consistently high N and moderate moisture levels. Shrubs, trees and succulents composed most of the seasonal sheep diets but had little variation in DMD. Across all seasons during drought and during summer with average precipitation, forages selected by sheep were higher in N and moisture than that of available forage. Differences in DMD between sheep diets and available forage were minor. Diet breadth was lowest during drought and increased with precipitation, reflecting a reliance on few key forage species during drought. Overall, forage selection was more strongly associated with N and moisture content than energy content. Our study demonstrates that unlike north-temperate ungulates which are generally reported to be energy-limited, N and moisture may be more nutritionally limiting for desert ungulates than digestible energy.

Arizona↗
USGS2017

Diet composition, quality and overlap of sympatric American pronghorn and gemsbok

Species with a long evolutionary history of sympatry often have mechanisms for resource partitioning that reduce competition. However, introduced non-native ungulates often compete with native ungulates and competitive effects can be exacerbated in arid regions due to low primary productivity. Our objectives were to characterize diet composition, quality, and overlap between American pronghorn Antilocapra americana and introduced non-native gemsbok Oryx gazella in southcentral New Mexico, USA. Severe drought occurred between 2010 and 2011, which allowed us to evaluate drought impacts on diet composition, quality, and overlap. Using feces collected from each species, we assessed diet composition and overlap with microhistological analysis and diet quality using fecal nitrogen (FN) and fecal 2,6-diaminopimelic acid (FDAPA). Pronghorn diet was primarily composed of shrubs in the cool—dry season (64.5%) then shifted to forbs in the warm—dry (64.7%) and warm—wet (54.1%) seasons. Pronghorn diet also shifted to shrubs during drought (50.7%). Gemsbok diets were evenly distributed across forage types. Fifty-three percent of the species of plants consumed by pronghorn and gemsbok were shared; diet overlap averaged 0.44 ± 0.06 (SE) and 0.49 ± 0.06 during the warm—dry seasons of 2010 and 2011, respectively. During drought, key forage species shared between pronghorn and gemsbok included yucca Yucca spp., prickly pear Opuntia spp., globemallow Sphaeralcea coccinea and horsenettle Solanum elaeagnifolium, comprising 50% of the pronghorn and 40% of the gemsbok diets. Fecal nitrogen and FDAPA decreased in pronghorn by 26% and 27% between the warm—dry season of 2010 (non-drought) and the warm—dry season of 2011 (drought), respectively. Drought had little effect on dietary quality for gemsbok. Gemsbok can use forage with lower nutritional content giving them an advantage over pronghorn, particularly during drought periods. Pronghorn are more dependent upon precipitation, which may be important to consider in light of increasing drought frequency associated with climate change.

New Mexico↗
USGS2016

Application of activity sensors for estimating behavioral patterns

The increasing use of Global Positioning System (GPS) collars in habitat selection studies provides large numbers of precise location data points with reduced field effort. However, inclusion of activity sensors in many GPS collars also grants the potential to remotely estimate behavioral state. Thus, only using GPS collars to collect location data belies their full capabilities. Coupling behavioral state with location data would allow researchers and managers to refine habitat selection models by using diel behavioral state changes to partition fine-scale temporal shifts in habitat selection. We tested the capability of relatively unsophisticated GPS-collar activity sensors to estimate behavior throughout diel periods using free-ranging female elk ( Cervus canadensis ) in the Jemez Mountains of north-central New Mexico, USA, 2013–2014. Collars recorded cumulative number of movements (hits) per 15-min recording period immediately preceding GPS fixes at 0000, 0600, 1200, and 1800 hr. We measured diel behavioral patterns of focal elk, categorizing active (i.e., foraging, traveling, vigilant, grooming) and inactive (i.e., resting) states. Active behaviors (foraging, traveling) produced more average hits (0.87 ± 0.69 hits/min, 4.0 ± 2.2 hits/min, respectively; 95% CI) and inactive (resting) behavior fewer hits (−1.1 ± 0.61 95% CI). We differentiated active and inactive behavioral states with a bootstrapped threshold of 5.9 ± 3.9 hits/15-min recording period. Mean cumulative activity-sensor hits corresponded with observed diel behavioral patterns: hits increased during crepuscular (0600, 1800 hr) observations when elk were most active (0000–0600 hr: d = 0.19; 1200–1800 hr: d = 0.64) and decreased during midday and night (0000 hr, 1200 hr) when elk were least active (1800–0000 hr: d = −0.39; 0600–1200 hr: d = −0.43). Even using relatively unsophisticated GPS-collar activity sensors, managers can remotely estimate behavioral states, approximate diel behavioral patterns, and potentially complement location data in developing habitat selection models.

New Mexico↗
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↗
USGS2016

Genetic structure and viability selection in the golden eagle (Aquila chrysaetos), a vagile raptor with a Holarctic distribution

Molecular markers can reveal interesting aspects of organismal ecology and evolution, especially when surveyed in rare or elusive species. Herein, we provide a preliminary assessment of golden eagle ( Aquila chrysaetos ) population structure in North America using novel single nucleotide polymorphisms (SNPs). These SNPs included one molecular sexing marker, two mitochondrial markers, 85 putatively neutral markers that were derived from noncoding regions within large intergenic intervals, and 74 putatively nonneutral markers found in or very near protein-coding genes. We genotyped 523 eagle samples at these 162 SNPs and quantified genotyping error rates and variability at each marker. Our samples corresponded to 344 individual golden eagles as assessed by unique multilocus genotypes. Observed heterozygosity of known adults was significantly higher than of chicks, as was the number of heterozygous loci, indicating that mean zygosity measured across all 159 autosomal markers was an indicator of fitness as it is associated with eagle survival to adulthood. Finally, we used chick samples of known provenance to test for population differentiation across portions of North America and found pronounced structure among geographic sampling sites. These data indicate that cryptic genetic population structure is likely widespread in the golden eagle gene pool, and that extensive field sampling and genotyping will be required to more clearly delineate management units within North America and elsewhere.

Conservation Genetics↗