Monitoring partially marked populations using camera and telemetry data.

Long-term monitoring is an important component of effective wildlife conservation. However, many methods for estimating density are too costly or difficult to implement over large spatial and temporal extents. Recently developed spatial mark-resight (SMR) models are increasingly being applied as a cost-effective method to estimate density when data include detections of both marked and unmarked individuals. We developed a generalized SMR model that can accommodate long-term camera data and auxiliary telemetry data for improved spatiotemporal inference in monitoring efforts. The model can be applied in two stages, with detection parameters estimated in the first stage using telemetry data and camera detections of instrumented individuals. Density is estimated in the second stage using camera data, with all individuals treated as unmarked. Serial correlation in detection and density parameters is accounted for using time-series models. The two-stage approach reduces computational demands and facilitates the application to large data sets from long-term monitoring initiatives. We applied the model to 3 years (2015-2017) of white-tailed deer (Odocoileus virginianus) data collected in three study areas of the Big Cypress Basin, Florida, USA. In total, 59 females marked with ear tags and fitted with GPS-telemetry collars were detected along with unmarked females on 180 remote cameras. Most of the temporal variation in density was driven by seasonal fluctuations, but one study area exhibited a slight population decline during the monitoring period. Modern technologies such as camera traps provide novel possibilities for long-term monitoring, but the resulting massive data sets, which are subject to unique sources of observation error, have posed analytical challenges. The two-stage spatial mark-resight framework provides a solution with lower computational demands than joint SMR models, allowing for easier implementation in practice. In addition, after detection parameters have been estimated, the model may be used to estimate density even if no synchronous auxiliary information on marked individuals is available, which is often the case in long-term monitoring.

Modeling abundance, distribution, movement and space use with camera and telemetry data.

Studies of animal abundance and distribution are often conducted independently of research on movement, despite the important links between processes. Movement can cause rapid changes in spatial variation in density, and movement influences detection probability and therefore estimates of abundance from inferential methods such as spatial capture-recapture (SCR). Technological developments including camera traps and GPS telemetry have opened new opportunities for studying animal demography and movement, yet statistical models for these two data types have largely developed along parallel tracks. We present a hierarchical model in which both datasets are conditioned on a movement process for a clearly defined population. We fitted the model to data from 60 camera traps and 23,572 GPS telemetry locations collected on 17 male white-tailed deer in the Big Cypress National Preserve, Florida, USA during July 2015. Telemetry data were collected on a 3-4 h acquisition schedule, and we modeled the movement paths of all individuals in the region with a Ornstein-Uhlenbeck process that included individual-specific random effects. Two of the 17 deer with GPS collars were detected on cameras. An additional 20 male deer without collars were detected on cameras and individually identified based on their unique antler characteristics. Abundance was 126 (95% CI: 88-177) in the 228 km2 region, only slightly higher than estimated using a standard SCR model: 119 (84-168). The standard SCR model, however, was unable to describe individual heterogeneity in movement rates and space use as revealed by the joint model. Joint modeling allowed the telemetry data to inform the movement model and the SCR encounter model, while leveraging information in the camera data to inform abundance, distribution and movement. Unlike most existing methods for population-level inference on movement, the joint SCR-movement model can yield unbiased inferences even if non-uniform sampling is used to deploy transmitters. Potential extensions of the model include the addition of resource selection parameters, and relaxation of the closure assumption when interest lies in survival and recruitment. These developments would contribute to the emerging holistic framework for the study of animal ecology, one that uses modern technology and spatio-temporal statistics to learn about interactions between behavior and demography.

Winter roost selection of Lasiurine tree bats in a pyric landscape.

Day-roost selection by Lasiurine tree bats during winter and their response to dormant season fires is unknown in the southeastern United States where dormant season burning is widely applied. Although fires historically were predominantly growing season, they now occur in the dormant season in this part of the Coastal Plain to support a myriad of stewardship activities, including habitat management for game species. To examine the response of bats to landscape condition and the application of prescribed fire, in the winter of 2019, we mist-netted and affixed radio-transmitters to 16 Lasiurine bats, primarily Seminole bats (Lasiurus seminolus) at Camp Blanding Joint Training Center in northern Florida. We then located day-roost sites to describe roost attributes. For five Seminole bats, one eastern red bat (Lasiurus borealis), and one hoary bat (Lasiurus cinereus), we applied prescribed burns in the roost area to observe bat response in real-time. Generally, Seminole bats selected day-roosts in mesic forest stands with high mean fire return intervals. At the roost tree scale, Seminole day-roosts tended to be larger, taller and in higher canopy dominance classes than surrounding trees. Seminole bats roosted in longleaf (Pinus palustris), slash (Pinus elliotii) and loblolly pine (Pinus taeda) more than expected based on availability, whereas sweetbay (Magnolia virginiana), water oak (Quercus nigra) and turkey oak (Quercus laevis), were roosted in less than expected based on availability. Of the seven roosts subjected to prescribed burns, only one male Seminole bat and one male eastern red bat evacuated during or immediately following burning. In both cases, these bats had day-roosted at heights lower than the majority of other day-roosts observed during our study. Our results suggest Seminole bats choose winter day-roosts that both maximize solar exposure and minimize risks associated with fire. Nonetheless, because selected day-roosts largely were fire-dependent or tolerant tree species, application of fire does need to periodically occur to promote recruitment and retention of suitable roost sites.

Chronology of reproductive investment determines predation risk aversion in a felid-ungulate system.

Fear of predators can behaviorally mediate prey population dynamics, particularly when predation risk influences reproductive investment. However, the costs of reproductive investment may mitigate predation risk aversion relative to periods when the link between reproductive output and prey behavior is weaker.We posit that intensity of reproductive investment in ungulates may predict their response to predation risk such that the sexes increase risk exposure during biological seasons that are pivotal to reproductive success, such as the fawn-rearing and breeding seasons for females and males, respectively.We examined the activity patterns of sympatric white-tailed deer (Odocoileus virginianus), a sexually segregated polygynous ungulate, and Florida panthers (Puma concolor coryi) in the context of the "risky times - risky places hypothesis" and the reproductive strategy hypothesis. We compared detection rates and diel activity overlap of both species using motion-triggered camera traps positioned on (n = 120) and off (n = 60) anthropogenic trails across five reproductive seasons.Florida panthers were nocturnal and primarily observed on-trail providing an experimental framework with risky times and risky places. Contrary to studies in other taxa inversely correlating prey reproductive investment to predation risk, the sexes of deer were more risk prone during sex-specific seasons associated with intense reproductive investment.Our results suggest spatiotemporally variable predation risk influences sex-specific behavioral decision-making in deer such that reproductive success is maximized.

Effects of mycoplasmal upper respiratory tract disease on morbidity and mortality of gopher tortoises in northern and central Florida.

Gopher tortoise (Gopherus polyphemus) populations on four tracts of public lands in northern and central Florida were studied from 1998 to 2001 to assess the effects of mycoplasmal upper respiratory tract disease (URTD). Adult gopher tortoises (n=205) were marked for identification, serum and nasal flush samples were obtained for mycoplasmal diagnostic assays, and clinical signs of URTD (nasal discharge, ocular discharge, palpebral edema, and conjunctivitis) were evaluated. A subset of tortoises (n=68) was radio-instrumented to facilitate repeated sampling and document potential mortality. Presence of serum antibody to Mycoplasma agassizii was determined by enzyme-linked immunosorbent assay (ELISA), and mollicutes species were detected in nasal flushes by polymerase chain reaction (PCR). Antibody prevalence varied among sites and years but was highest in 1998, exceeding 70% at two sites. Only 11 tortoises (5%) were positive by PCR, and three species (M. agassizii, M. testudineum, and a nonpathogenic Acholeplasma) were identified in nasal flush specimens. Nasal discharge, though rare (6% of tortoises), was significantly correlated with higher ELISA ratios, study site, and positive PCR status. Mortality events (n=11) occurred on two of the three M. agassizii-positive sites; no mortality was observed on the M. agassizii-negative control site. However, none of the tested variables (ELISA result, study site, year, sex, presence of clinical signs, or carapace length) showed significant ability to predict the odds of death. Mycoplasmal URTD is believed to be a chronic disease with high morbidity but low mortality, and follow-up studies are needed to detect long-term effects.