Species and physiographic factors drive Indian cucumber root and Canada mayflower plant chemistry: Implications for white-tailed deer forage quality.

Nutrition is fundamental to white-tailed deer (Odocoileus virginianus) management given its relationship to habitat carrying capacity and population productivity. Ecological Sites (ESs) are a United States federal landscape management unit of specific land potential due to unique soils, topography, climate, parent material, and perhaps deer forage nutritional value. We present results of a study that extends the use of ESs to inform white-tailed deer management by evaluating indicator plant chemistry in two spring forb species, Indian cucumber root (Medeola virginiana) and Canada mayflower (Maianthemum canadense), across the northcentral Appalachians. We sampled spring forbs and underlying soils across two ESs: Dry, upland, oak-maple-hemlock hardwood forest (OMH) and Deep soil, high slope, northern hardwood forests (NHF). Plant elemental content, soil pH, and site aspect, slope and elevation were measured. Our results show that forb chemistry differs between species and within a species geographically. Indian cucumber root, as compared to Canada mayflower, has significantly higher Mg, Na, Cu, Fe, and Zn, and lower Mn. Canada mayflower in the NHF ES, versus OMH ES, was found to have significantly higher K, Mn, and B. Indian cucumber root in the NHF ES, versus the OMH ES, was found to have significantly higher Mg, Al, Fe, and Ca:P ratio but lower K. Linear discriminant analysis shows that plant tissue Mn was the best discriminator between species, and between ESs, Canada mayflower plant tissue Mn and Indian cucumber plant tissue P, K, Ca, Mg and Mn were best discriminators. Given that nutrition determines habitat carrying capacity, differences in forage nutrition between ESs may have different potentials to support deer. Forage nutrition is an important aspect of deer habitat conditions and carrying capacity, thus ESs are likely to support deer populations with different growth potential, which means that even if the same plant species occur in different ESs their nutritional value to deer may differ.

Threading the needle: How humans influence predator-prey spatiotemporal interactions in a multiple-predator system.

Perceived predation risk and the resulting antipredator behaviour varies across space, time and predator identity. Communities with multiple predators that interact and differ in their use of space, time of activity and hunting mode create a complex landscape for prey to avoid predation. Anthropogenic presence and disturbance have the potential to shift interactions among predators and prey and the where and when encounters occur. We examined how white-tailed deer Odocoileus virginianus fawn spatiotemporal antipredator behaviour differed along an anthropogenic disturbance gradient that had black bears Ursus americanus, coyotes Canis latrans, bobcats Lynx rufus and humans present. We quantified (a) spatial co-occurrence in species distributions, (b) temporal overlap across the diel cycle and (c) spatiotemporal associations between humans, bears, coyotes, bobcats, adult male deer and fawns. We also examined how deer vigilance behaviour changed across the anthropogenic disturbance gradient and survey duration. Anthropogenic disturbance influenced spatiotemporal co-occurrence across multiple scales, often increasing spatiotemporal overlap among species. In general, species' spatial co-occurrence was neutral or positive in anthropogenically disturbed environments. Bears and fawns, coyotes and adult male deer, and bobcats and fawns all had higher temporal overlap in the agriculture-development matrix sites. In addition, factors that influenced deer vigilance (e.g. distance to forest edge and predator relative abundance) in the agriculture-development matrix sites did not in the forest matrix site. By taking into account the different antipredator behaviours that can be detected and the different scales these behaviours might occur, we were able to gain a more comprehensive picture of how humans reduce available niche space for wildlife, creating the neutral and positive spatiotemporal associations between species that studies have been seeing in more disturbed areas.

Occupancy patterns of regionally declining grassland sparrow populations in a forested Pennsylvania landscape.

Organisms can be affected by processes in the surrounding landscape outside the boundary of habitat areas and by local vegetation characteristics. There is substantial interest in understanding how these processes affect populations of grassland birds, which have experienced substantial population declines. Much of our knowledge regarding patterns of occupancy and density stem from prairie systems, whereas relatively little is known regarding how occurrence and abundance of grassland birds vary in reclaimed surface mine grasslands. Using distance sampling and single-season occupancy models, we investigated how the occupancy probability of Grasshopper (Ammodramus savannarum) and Henslow's Sparrows (A. henslowii) on 61 surface mine grasslands (1591 ha) in Pennsylvania changed from 2002 through 2011 in response to landscape, grassland, and local vegetation characteristics . A subset (n = 23; 784 ha) of those grasslands were surveyed in 2002, and we estimated changes in sparrow density and vegetation across 10 years. Grasshopper and Henslow's Sparrow populations declined 72% and 49%, respectively from 2002 to 2011, whereas overall woody vegetation density increased 2.6 fold. Henslow's Sparrows avoided grasslands with perimeter-area ratios ≥0.141 km/ha and woody shrub densities ≥0.04 shrubs/m(2). Both species occupied grasslands ≤13 ha, but occupancy probability declined with increasing grassland perimeter-area ratio and woody shrub density. Grassland size, proximity to nearest neighboring grassland (x = 0.2 km), and surrounding landscape composition at 0.5, 1.5, and 3.0 km were not parsimonious predictors of occupancy probability for either species. Our results suggest that reclaimed surface mine grasslands, without management intervention, are ephemeral habitats for Grasshopper and Henslow's Sparrows. Given the forecasted decline in surface coal production for Pennsylvania, it is likely that both species will continue to decline in our study region for the foreseeable future.

Multistage time-to-event models improve survival inference by partitioning mortality processes of tracked organisms.

Advances in tagging technologies are expanding opportunities to estimate survival of fish and wildlife populations. Yet, capture and handling effects could impact survival outcomes and bias inference about natural mortality processes. We developed a multistage time-to-event model that can partition the survival process into sequential phases that reflect the tagged animal experience, including handling and release mortality, post-release recovery mortality, and subsequently, natural mortality. We demonstrate performance of multistage survival models through simulation testing and through fish and bird telemetry case studies. Models are implemented in a Bayesian framework and can accommodate left, right, and interval censorship events. Our results indicate that accurate survival estimates can be achieved with reasonable sample sizes ( n ≈ 100 + ) and that multimodel inference can inform hypotheses about the configuration and length of survival stages needed to adequately describe mortality processes for tracked specimens. While we focus on survival estimation for tagged fish and wildlife populations, multistage time-to-event models could be used to understand other phenomena of interest such as migration, reproduction, or disease events across a range of taxa including plants and insects.

Risky movements? Natal dispersal does not decrease survival of a large herbivore.

Natal dispersal is assumed to be a particularly risky movement behavior as individuals transfer, often long distances, from birth site to site of potential first reproduction. Though, because this behavior persists in populations, it is assumed that dispersal increases the fitness of individuals despite the potential for increased risk of mortality. The extent of dispersal risk, however, has rarely been tested, especially for large mammals. Therefore, we aimed to test the relationship between dispersal and survival for both males and females in a large herbivore. Using a radio-transmittered sample of 398 juvenile male and 276 juvenile female white-tailed deer (Odocoileus virginianus), we compared survival rates of dispersers and nondispersers. We predicted that dispersing deer would experience greater overall mortality than philopatric deer due to direct transfer-related risks (e.g., vehicular collision), indirect immigration-related mortality attributable to colonization of unfamiliar habitat, and increased overwinter mortality associated with energetic costs of movement and unfamiliarity with recently colonized habitat. For both male and female yearlings, survival rates of dispersers (male = 49.9%, female = 64.0%) did not differ from nondispersers (male = 51.6%, female = 70.7%). Only two individuals (both female) were killed by vehicular collision during transfer, and overwinter survival patterns were similar between the two groups. Although dispersal movement likely incurs energetic costs on dispersers, these costs do not necessarily translate to decreased survival. In many species, including white-tailed deer, dispersal is likely condition-dependent, such that larger and healthier individuals are more likely to disperse; therefore, costs associated with dispersal are more likely to be borne successfully by those individuals that do disperse. Whether low-risk dispersal of large mammals is the rule or the exception will require additional research. Further, future research is needed to evaluate nonsurvival fitness-related costs and benefits of dispersal (e.g., increased reproductive opportunities for dispersers).

Survival is negatively associated with glucocorticoids in a wild ungulate neonate.

It is unknown how ungulate physiological responses to environmental perturbation influence overall population demographics. Moreover, neonatal physiological responses remain poorly studied despite the importance of neonatal survival to population growth. Glucocorticoid (GC) hormones potentially facilitate critical physiological and behavioral responses to environmental perturbations. However, elevated GC concentrations over time may compromise body condition and indirectly reduce survival. We evaluated baseline salivary cortisol (CORT; a primary GC in mammals) concentrations in 19 wild neonatal white-tailed deer (Odocoileus virginianus) in a northern (NS) and southern (SS) area in Pennsylvania. After ranking survival models consisting of variables hypothesized to influence neonate survival (i.e. weight, sex), the probability of neonate survival was best explained by CORT concentrations, where elevated CORT concentrations were associated with reduced survival probability to 12 weeks of age. Cortisol concentrations were greater in the SS where predation rates and predator densities were lower. As the first evaluation of baseline CORT concentrations in an ungulate neonate to our knowledge, this is also the first study to demonstrate CORT concentrations are negatively associated with ungulate survival at any life stage. Glucocorticoid hormones could provide a framework in which to better understand susceptibility to mortality in neonatal white-tailed deer.

Caution is warranted when using animal space-use and movement to infer behavioral states.

BACKGROUND: Identifying the behavioral state for wild animals that can't be directly observed is of growing interest to the ecological community. Advances in telemetry technology and statistical methodologies allow researchers to use space-use and movement metrics to infer the underlying, latent, behavioral state of an animal without direct observations. For example, researchers studying ungulate ecology have started using these methods to quantify behaviors related to mating strategies. However, little work has been done to determine if assumed behaviors inferred from movement and space-use patterns correspond to actual behaviors of individuals. METHODS: Using a dataset with male and female white-tailed deer location data, we evaluated the ability of these two methods to correctly identify male-female interaction events (MFIEs). We identified MFIEs using the proximity of their locations in space as indicators of when mating could have occurred. We then tested the ability of utilization distributions (UDs) and hidden Markov models (HMMs) rendered with single sex location data to identify these events. RESULTS: For white-tailed deer, male and female space-use and movement behavior did not vary consistently when with a potential mate. There was no evidence that a probability contour threshold based on UD volume applied to an individual's UD could be used to identify MFIEs. Additionally, HMMs were unable to identify MFIEs, as single MFIEs were often split across multiple states and the primary state of each MFIE was not consistent across events. CONCLUSIONS: Caution is warranted when interpreting behavioral insights rendered from statistical models applied to location data, particularly when there is no form of validation data. For these models to detect latent behaviors, the individual needs to exhibit a consistently different type of space-use and movement when engaged in the behavior. Unvalidated assumptions about that relationship may lead to incorrect inference about mating strategies or other behaviors.

Assessment of spatial genetic structure to identify populations at risk for infection of an emerging epizootic disease.

Understanding the geographic extent and connectivity of wildlife populations can provide important insights into the management of disease outbreaks but defining patterns of population structure is difficult for widely distributed species. Landscape genetic analyses are powerful methods for identifying cryptic structure and movement patterns that may be associated with spatial epizootic patterns in such cases.We characterized patterns of population substructure and connectivity using microsatellite genotypes from 2,222 white-tailed deer (Odocoileus virginianus) in the Mid-Atlantic region of the United States, a region where chronic wasting disease was first detected in 2009. The goal of this study was to evaluate the juxtaposition between population structure, landscape features that influence gene flow, and current disease management units.Clustering analyses identified four to five subpopulations in this region, the edges of which corresponded to ecophysiographic provinces. Subpopulations were further partitioned into 11 clusters with subtle (F ST ≤ 0.041), but significant genetic differentiation. Genetic differentiation was lower and migration rates were higher among neighboring genetic clusters, indicating an underlying genetic cline. Genetic discontinuities were associated with topographic barriers, however.Resistance surface modeling indicated that gene flow was diffuse in homogenous landscapes, but the direction and extent of gene flow were influenced by forest cover, traffic volume, and elevational relief in subregions heterogeneous for these landscape features. Chronic wasting disease primarily occurred among genetic clusters within a single subpopulation and along corridors of high landscape connectivity.These results may suggest a possible correlation between population substructure, landscape connectivity, and the occurrence of diseases for widespread species. Considering these factors may be useful in delineating effective management units, although only the largest features produced appreciable differences in subpopulation structure. Disease mitigation strategies implemented at the scale of ecophysiographic provinces are likely to be more effective than those implemented at finer scales.

Soil chemistry, and not short-term (1-2 year) deer exclusion, explains understory plant occupancy in forests affected by acid deposition.

The loss of species diversity and plant community structure throughout the temperate deciduous forests of North America have often been attributed to overbrowsing by white-tailed deer (Odocoileus virginanus). Slow species recovery following removal from browsing, or reduction in deer density, has been termed a legacy effect of past deer herbivory. However, vegetation legacy effects have also coincided with changes to soil chemistry throughout the north-eastern USA. In this paper, we assess the viability of soil chemistry (i.e. pH, extractable nutrients and extractable metals) and other factors (topography, light, overstory basal area and location) as alternative explanations for a lack of vegetation recovery. We compared the relative effects of soil chemistry, site conditions and short-term (1-2 year) deer exclusion on single-species occupancy probabilities of 10 plant taxa common to oak-hickory forests in central Pennsylvania. We found detection for all modelled species was constant and high ( p ^ > 0.65), and occupancy probability of most taxa was best explained by at least one soil chemistry parameter. Specifically, ericaceous competing vegetation was more likely to occupy acidic (pH < 3.5), base cation-poor (K < 0.20 cmolc kg-1) sites, while deer-preferred plants were less likely to occur when soil manganese exceeded 0.1 cmolc kg-1. Short-term deer exclusion did not explain occupancy of any plant taxon, and site conditions were of nominal importance. This study demonstrates the importance of soil chemistry in shaping plant community composition in the north-central Appalachians, and suggests soil as an alternative, or additional, explanation for deer vegetation legacy effects. We suggest that the reliance on phyto-indicators of deer browsing effects may overestimate the effects of browsing if those species are also limited by unfavourable soil conditions. Future research should consider study designs that address the complexity of deer forest interactions, especially in areas with complex site-vegetation histories.

Bayesian analysis of wildlife age-at-harvest data.

SUMMARY: State and federal natural resource management agencies often collect age-structured harvest data. These data represent finite realizations of stochastic demographic and sampling processes and have long been used by biologists to infer population trends. However, different sources of data have been combined in ad hoc ways and these methods usually failed to incorporate sampling error. In this article, we propose a "hidden process" (or state-space) model for estimating abundance, survival, recovery rate, and recruitment from age-at-harvest data that incorporate both demographic and sampling stochasticity. To this end, a likelihood for age-at-harvest data is developed by embedding a population dynamics model within a model for the sampling process. Under this framework, the identification of abundance parameters can be achieved by conducting a joint analysis with an auxiliary data set. We illustrate this approach by conducting a Bayesian analysis of age-at-harvest and mark-recovery data from black bears (Ursus americanus) in Pennsylvania. Using a set of reasonable prior distributions, we demonstrate a substantial increase in precision when posterior summaries of abundance are compared to a bias-corrected Lincoln-Petersen estimator. Because demographic processes link consecutive abundance estimates, we also obtain a more realistic biological picture of annual changes in abundance. Because age-at-harvest data are often readily obtained, we argue that this type of analysis provides a valuable strategy for wildlife population monitoring.

Heterogeneity of a landscape influences size of home range in a North American cervid.

In the northeastern United States, chronic wasting disease has recently been detected in white-tailed deer (Odocoileus virginianus) populations, and understanding the relationship between landscape configuration and home range may improve disease surveillance and containment efforts. The objectives of our study were to compare size of home range for deer occupying a continuum of forested landscapes and to investigate relationships between size of home range and measures of landscape configuration. We used a movement-based kernel density estimator to estimate home range at five spatial scales among deer across study areas. We developed 7 linear regression models that used measures of the configuration of the forested landscape to explain size of home range. We observed differences in size of home range between sexes among areas that differed based on landscape configuration. We documented size of home range changed with various metrics that identifying connectivity of forested patches. Generally, size of home range increased with an increasing proportion of homogenous forest. Our results suggest that deer in our region occupy a landscape at hierarchically-nested scales that is controlled by the connectivity of the forested landscape across local or broad geographical regions.

Moving in the Anthropocene: Global reductions in terrestrial mammalian movements.

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.

Adjusting age and stage distributions for misclassification errors.

Ecologists often use samples from the age or stage structure of a population to make inferences about population-level processes and to parameterize matrix models. Typically, researchers make a simplifying assumption that age and stage classes are determined without error, when in fact some level of misclassification often can be expected. If unaccounted for, misclassification will lead to overly optimistic levels of precision and can cause biased estimates of age or stage structure. Although several studies have used information from known-age individuals to quantify errors in age or stage distribution, the problem of estimating the age or stage structure in face of such errors has received comparably little attention. In this paper, we describe a general statistical framework for estimating the true stage distribution of a sample when misclassification rates can be estimated. The estimation process requires auxiliary information on misclassification rates, such as data from individuals of known age. We analyze age-structured harvest records from black bears in Pennsylvania to illustrate how incorporating misclassification errors leads to changes in point estimates and provides a measure of precision.

Population and genetic outcomes 20 years after reintroducing bobcats (Lynx rufus) to Cumberland Island, Georgia USA.

In 1988-1989, 32 bobcats Lynx rufus were reintroduced to Cumberland Island (CUIS), Georgia, USA, from which they had previously been extirpated. They were monitored intensively for 3 years immediately post-reintroduction, but no estimation of the size or genetic diversity of the population had been conducted in over 20 years since reintroduction. We returned to CUIS in 2012 to estimate abundance and effective population size of the present-day population, as well as to quantify genetic diversity and inbreeding. We amplified 12 nuclear microsatellite loci from DNA isolated from scats to establish genetic profiles to identify individuals. We used spatially explicit capture-recapture population estimation to estimate abundance. From nine unique genetic profiles, we estimate a population size of 14.4 (SE = 3.052) bobcats, with an effective population size (N e) of 5-8 breeding individuals. This is consistent with predictions of a population viability analysis conducted at the time of reintroduction, which estimated the population would average 12-13 bobcats after 10 years. We identified several pairs of related bobcats (parent-offspring and full siblings), but ~75% of the pairwise comparisons were typical of unrelated individuals, and only one individual appeared inbred. Despite the small population size and other indications that it has likely experienced a genetic bottleneck, levels of genetic diversity in the CUIS bobcat population remain high compared to other mammalian carnivores. The reintroduction of bobcats to CUIS provides an opportunity to study changes in genetic diversity in an insular population without risk to this common species. Opportunities for natural immigration to the island are limited; therefore, continued monitoring and supplemental bobcat reintroductions could be used to evaluate the effect of different management strategies to maintain genetic diversity and population viability. The successful reintroduction and maintenance of a bobcat population on CUIS illustrates the suitability of translocation as a management tool for re-establishing felid populations.

Habitat availability is a more plausible explanation than insecticide acute toxicity for U.S. grassland bird species declines.

Grassland bird species have experienced substantial declines in North America. These declines have been largely attributed to habitat loss and degradation, especially from agricultural practices and intensification (the habitat-availability hypothesis). A recent analysis of North American Breeding Bird Survey (BBS) "grassland breeding" bird trends reported the surprising conclusion that insecticide acute toxicity was a better correlate of grassland bird declines in North America from 1980-2003 (the insecticide-acute-toxicity hypothesis) than was habitat loss through agricultural intensification. In this paper we reached the opposite conclusion. We used an alternative statistical approach with additional habitat covariates to analyze the same grassland bird trends over the same time frame. Grassland bird trends were positively associated with increases in area of Conservation Reserve Program (CRP) lands and cropland used as pasture, whereas the effect of insecticide acute toxicity on bird trends was uncertain. Our models suggested that acute insecticide risk potentially has a detrimental effect on grassland bird trends, but models representing the habitat-availability hypothesis were 1.3-21.0 times better supported than models representing the insecticide-acute-toxicity hypothesis. Based on point estimates of effect sizes, CRP area and agricultural intensification had approximately 3.6 and 1.6 times more effect on grassland bird trends than lethal insecticide risk, respectively. Our findings suggest that preserving remaining grasslands is crucial to conserving grassland bird populations. The amount of grassland that has been lost in North America since 1980 is well documented, continuing, and staggering whereas insecticide use greatly declined prior to the 1990s. Grassland birds will likely benefit from the de-intensification of agricultural practices and the interspersion of pastures, Conservation Reserve Program lands, rangelands and other grassland habitats into existing agricultural landscapes.

Accounting for tagging-to-harvest mortality in a Brownie tag-recovery model by incorporating radio-telemetry data.

The Brownie tag-recovery model is useful for estimating harvest rates but assumes all tagged individuals survive to the first hunting season; otherwise, mortality between time of tagging and the hunting season will cause the Brownie estimator to be negatively biased. Alternatively, fitting animals with radio transmitters can be used to accurately estimate harvest rate but may be more costly. We developed a joint model to estimate harvest and annual survival rates that combines known-fate data from animals fitted with transmitters to estimate the probability of surviving the period from capture to the first hunting season, and data from reward-tagged animals in a Brownie tag-recovery model. We evaluated bias and precision of the joint estimator, and how to optimally allocate effort between animals fitted with radio transmitters and inexpensive ear tags or leg bands. Tagging-to-harvest survival rates from >20 individuals with radio transmitters combined with 50-100 reward tags resulted in an unbiased and precise estimator of harvest rates. In addition, the joint model can test whether transmitters affect an individual's probability of being harvested. We illustrate application of the model using data from wild turkey, Meleagris gallapavo, to estimate harvest rates, and data from white-tailed deer, Odocoileus virginianus, to evaluate whether the presence of a visible radio transmitter is related to the probability of a deer being harvested. The joint known-fate tag-recovery model eliminates the requirement to capture and mark animals immediately prior to the hunting season to obtain accurate and precise estimates of harvest rate. In addition, the joint model can assess whether marking animals with radio transmitters affects the individual's probability of being harvested, caused by hunter selectivity or changes in a marked animal's behavior.

Controlling for anthropogenically induced atmospheric variation in stable carbon isotope studies.

Increased use of stable isotope analysis to examine food-web dynamics, migration, transfer of nutrients, and behavior will likely result in expansion of stable isotope studies investigating human-induced global changes. Recent elevation of atmospheric CO2 concentration, related primarily to fossil fuel combustion, has reduced atmospheric CO2 delta13C (13C/12C), and this change in isotopic baseline has, in turn, reduced plant and animal tissue delta13C of terrestrial and aquatic organisms. Such depletion in CO2 delta13C and its effects on tissue delta13C may introduce bias into delta13C investigations, and if this variation is not controlled, may confound interpretation of results obtained from tissue samples collected over a temporal span. To control for this source of variation, we used a high-precision record of atmospheric CO2 delta13C from ice cores and direct atmospheric measurements to model modern change in CO2 delta13C. From this model, we estimated a correction factor that controls for atmospheric change; this correction reduces bias associated with changes in atmospheric isotopic baseline and facilitates comparison of tissue delta13C collected over multiple years. To exemplify the importance of accounting for atmospheric CO2 delta13C depletion, we applied the correction to a dataset of collagen delta13C obtained from mountain lion (Puma concolor) bone samples collected in California between 1893 and 1995. Before correction, in three of four ecoregions collagen delta13C decreased significantly concurrent with depletion of atmospheric CO2 delta13C (n > or = 32, P < or = 0.01). Application of the correction to collagen delta13C data removed trends from regions demonstrating significant declines, and measurement error associated with the correction did not add substantial variation to adjusted estimates. Controlling for long-term atmospheric variation and correcting tissue samples for changes in isotopic baseline facilitate analysis of samples that span a large temporal range.