Geology topics

Jacqueline L. Frair

Publications and source records attributed to Jacqueline L. Frair.

10 recordsLinked to original sources

USGS2026

Exploring management options for moose at their southern range limits considering growing disease risk

1. Populations of cold-adapted species are increasingly vulnerable along their low-latitude range limits due to shifting environmental conditions, biotic interactions, and anthropogenic pressures. Managing these populations is particularly challenging because of complex ecological dynamics, conflicting stakeholder interests, and decision-making under uncertainty. 2. We explored population growth (λ) of moose ( Alces alces ) under different hypothetical management scenarios, simulating combinations of five hypothetical harvest levels with three levels of disease impact. 3. Facing current disease, the population could support multiple levels of conservative harvest. Under elevated levels of disease-caused mortality, projections indicated declines for all harvest scenarios. We projected increases across all harvest scenarios when overlap with white-tailed deer ( Odocoileus virginianus ) was hypothetically reduced and disease mortality in moose minimized. We investigated whether uncertainty in moose demographic parameters altered population trajectory, and found changes in adult fecundity and calf survival could alter harvest decisions when λ<1. 4. Practical implication . While moose population trajectories may remain stable under current conditions, management of white-tailed deer that reduces moose exposure to lethal parasites may provide the greatest utility in sustaining moose in New York given the potential for increased disease. Continued monitoring of population size, growth, and disease prevalence would inform sustainable moose harvest levels that balance social and ecological management considerations.

New York↗

USGS2025

Moose survival and habitat‐associated risk of endoparasites

Parasite-induced morbidity and mortality can alter the trajectories of incidental host populations. Yet, parasites rarely act in isolation and may be one of a multitude of biotic and abiotic stressors that collectively shape mortality risk in vertebrate populations. We quantified sources of mortality in a low-density population of moose ( Alces alces ) in New York State and investigated factors including parasite infection, nutritional limitation, and thermal stress influencing mortality risk in calf moose. We observed high rates of annual survival (0.81–0.92) in adult ( n = 25) and calf ( n = 27) moose monitored 2015–2018 and 2022–2024, respectively. The majority of cause-specific mortality was attributed to disease induced by giant liver fluke ( Fascioloides magna ; 75% in adults, 67% in calves). Calf mortality risk increased by 72% for every unit increase in giant liver fluke infection risk, measured as cumulative monthly proportion of wetlands used by moose, and decreased by 16% with each additional unit of nutritional energy available. The combination of flukes, coinfecting parasites, and available nutritional energy is important to calf survival in this population, highlighting the importance of managing multiple stressors for species conservation, although the effects are hard to disentangle given the high rates of survival observed. Identifying causes of mortality and mechanisms underlying increased mortality risk contributes to the continued conservation of moose in fluctuating populations and highlights the importance of managing parasite-induced disease.

New York↗

USGS2025

Parasite‐mediated competition limits dominant cervid competitor

Species interactions structure ecological communities through direct and indirect pathways with ecosystem-wide implications. Despite mounting interest in the importance of indirect interactions, empirical evidence remains limited. Here, we demonstrate the critical role of parasite-mediated competition in driving community outcomes in a multi-species system of conservation and management concern. We leveraged 2 years of detection/non-detection data of moose ( Alces alces ) and white-tailed deer ( Odocoileus virginianus ) and parasite loads in faecal samples within a hierarchical abundance-mediated interaction model to test hypotheses regarding interactions between these cervids and their shared parasites ( Parelaphostrongylus tenuis , Fascioloides magna ). We demonstrate that moose occupancy was limited by parasite-mediated competition, with no evidence of population-level effects of direct competitive interactions between moose and white-tailed deer. Such evidence of the importance of indirect interactions and resulting community outcomes is critical for species conservation and managing range contractions due to increasing pressures from habitat loss, disease and climate change.

New York↗

USGS2024

Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale

Estimating species distribution and abundance is foundational to effective management and conservation. Using an integrated species distribution model that combines presence-only data from various sources with detection/non-detection data from structured surveys, we estimated the distribution and expected abundance of three difficult-to-monitor mammals of management concern across New York State, namely, coyotes ( Canis latrans ), bobcats ( Lynx rufus ) and black bears ( Ursus americanus ). Three distinct landscape-scale camera trap surveys provided detection/non-detection data over 9 years between 2013 and 2021, and we augmented those data with incidental records of our focal species from public repositories. We used an inhomogeneous Poisson point process to construct an integrated model that fit both data types simultaneously. We demonstrate a simple application of spatial point density of all species records in the accessed public databases to inform the thinning process to account for unknown spatial sampling in the presence-only data, often referred to as the ‘magic covariate’. Using this approach, we examine habitat associations and provide spatially explicit estimates in expected abundance across the entirety of New York State for all three focal species. As expected, coyotes were the most widely distributed and abundant species, with a strong positive association with agricultural land uses. Bobcats exhibited low expected abundance throughout the state and showed positive associations with deciduous forest and forest edge, and a negative association with road density. Finally, we observed considerable spatial variation in abundance of black bears with expected abundance increasing in association with various forest cover and composition covariates and decreasing with crop cover. We present insights into habitat associations and spatial variation in abundance, and provide management implications for each of the species of interest. Synthesis and applications . Our integrated modelling method allows for managers to use citizen sightings combined with detection/non-detection surveys to estimate robust indices of abundance for both high- and low-density, and wide-spread versus patchily distributed species. Through comparison with previous studies, we highlight how broad-scale programmes, such as the statewide efforts to estimate species distributions undertaken here, can benefit substantively from integrated models that leverage additional data (here, incidental records) from a larger region of space, and thus capture more landscape heterogeneity than is plausible within formalized surveys alone.

New York↗

USGS2021

Habitat use as indicator of adaptive capacity to climate change

Aim Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose ( Alces alces ), a charismatic species of conservation and public interest. Location The northeastern United States, along the trailing edge of the moose geographic range in North America. Methods We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use. Results We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times. Main conclusionsOur results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation.

New York, Vermont, New Hampshire, Massachusetts↗

USGS2018

Movement behavior preceding autumn mortality for white-tailed deer in central New York

A common yet largely untested assumption in the theory of animal movements is that increased rates and a wider range of movements, such as occurs during breeding, make animals more vulnerable to mortality. We examined mortality among 34 white-tailed deer (Odocoileus virginianus) wearing GPS collars during the autumn breeding season of 2006 and 2007 in a heavily hunted, forest-agricultural landscape of central New York state. We evaluated whether individuals having higher rates of movement incurred higher rates of mortality and whether mortality risk was higher when deer were in less familiar areas. We used a Cox proportional hazards model to analyze how mortality risk changes with movement rates measured over 3 time periods: < 1 day, up to 2 weeks prior to death, and 3–4 weeks prior to death. Overall, deer increased their movement rates as autumn progressed, males more so than females. However, deer that died moved at a slower rate relative to surviving deer up to 2 weeks prior to death (ß = -2.22 ± 0.81; 95% confidence interval [CI] = -3.91 to -0.51) and a slower rate on their day of death compared to deer that survived (ß = -1.77 ± 0.73; 95% CI = -3.19 to -0.33). Site familiarity was not significantly related to mortality risk. Deer were equally likely to die within their 50% core use area as elsewhere within their autumn home range. We hypothesize that increased sociality associated with breeding may make animals more vulnerable to harvest mortality. Our findings contradict general assumptions about the influences of movement behavior on mortality risk, suggesting that patterns may be sensitive to the spatiotemporal context of the movement analysis.

New York↗

USGS2017

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 10 6 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Oikos↗

USGS2016

Allometric and temporal scaling of movement characteristics in Galapagos tortoises

Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life-history trade-offs. We investigated how the temporal scaling of allometric patterns in movement varies over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour – giant Galapagos tortoises ( Chelonoidis spp.) – to test how movement metrics estimated on a monthly basis scaled with body size. We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics and contrasted relationships by species and sex. Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected one-fourth scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates. Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises.

Journal of Animal Ecology↗

USGS2016

Flexible characterization of animal movement pattern using net squared displacement and a latent state model

Background Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g., migratory vs. sedentary behavior) and fine (e.g., resting vs. foraging) scales. A popular approach for classifying movements at coarse resolutions involves fitting time series of net-squared displacement (NSD) to models representing different conceptualizations of coarse movement strategies (i.e., migration, nomadism, sedentarism, etc.). However, the performance of this method in classifying actual (as opposed to simulated) animal movements has been mixed. Here, we develop a more flexible method that uses the same NSD input, but relies on an underlying discrete latent state model. Using simulated data, we first assess how well patterns in the number of transitions between modes of movement and the duration of time spent in a mode classify movement strategies. We then apply our approach to elucidate variability in the movement strategies of eight giant tortoises ( Chelonoidis sp.) using a multi-year (2009–2014) GPS dataset from three different Galapagos Islands. Results With respect to patterns of time spent and the number of transitions between modes, our approach out-performed previous efforts to distinguish among migration, dispersal, and sedentary behavior. We documented marked inter-individual variation in giant tortoise movement strategies, with behaviors indicating migration, dispersal, nomadism and sedentarism, as well as hybrid behaviors such as “exploratory residence”. Conclusions Distilling complex animal movement into discrete modes remains a fundamental challenge in movement ecology, a problem made more complex by the ever-longer duration, ever-finer resolution, and gap-ridden trajectories recorded by GPS devices. By clustering into modes, we derived information on the time spent within one mode and the number of transitions between modes which enabled finer differentiation of movement strategies over previous methods. Ultimately, the techniques developed here address limitations of previous approaches and provide greater insights with respect to characterization of movement strategies across scales by more fully utilizing long-term GPS telemetry datasets.

Movement Ecology↗

USGS2015

Pairing call-response surveys and distance sampling for a mammalian carnivore

Density estimates accounting for differential animal detectability are difficult to acquire for wide-ranging and elusive species such as mammalian carnivores. Pairing distance sampling with call-response surveys may provide an efficient means of tracking changes in populations of coyotes ( Canis latrans ), a species of particular interest in the eastern United States. Blind field trials in rural New York State indicated 119-m linear error for triangulated coyote calls, and a 1.8-km distance threshold for call detectability, which was sufficient to estimate a detection function with precision using distance sampling. We conducted statewide road-based surveys with sampling locations spaced ≥6 km apart from June to August 2010. Each detected call (be it a single or group) counted as a single object, representing 1 territorial pair, because of uncertainty in the number of vocalizing animals. From 524 survey points and 75 detections, we estimated the probability of detecting a calling coyote to be 0.17 ± 0.02 SE, yielding a detection-corrected index of 0.75 pairs/10 km 2 (95% CI: 0.52–1.1, 18.5% CV) for a minimum of 8,133 pairs across rural New York State. Importantly, we consider this an index rather than true estimate of abundance given the unknown probability of coyote availability for detection during our surveys. Even so, pairing distance sampling with call-response surveys provided a novel, efficient, and noninvasive means of monitoring populations of wide-ranging and elusive, albeit reliably vocal, mammalian carnivores. Our approach offers an effective new means of tracking species like coyotes, one that is readily extendable to other species and geographic extents, provided key assumptions of distance sampling are met.

New York↗