Efficacy of N-mixture models for surveying and monitoring white-tailed deer populations

Automated cameras have become increasingly common for monitoring wildlife populations and estimating abundance. Most analytical methods, however, fail to account for incomplete and variable detection probabilities, which biases abundance estimates. Methods which do account for detection have not been thoroughly tested, and those that have been tested were compared to other methods of abundance estimation. The goal of this study was to evaluate the accuracy and effectiveness of the N-mixture method, which explicitly incorporates detection probability, to monitor white-tailed deer (Odocoileus virginianus) by using camera surveys and a known, marked population to collect data and estimate abundance. Motion-triggered camera surveys were conducted at Auburn University’s deer research facility in 2010. Abundance estimates were generated using N-mixture models and compared to the known number of marked deer in the population. We compared abundance estimates generated from a decreasing number of survey days used in analysis and by time periods (DAY, NIGHT, SUNRISE, SUNSET, CREPUSCULAR, ALL TIMES). Accurate abundance estimates were generated using 24 h of data and nighttime only data. Accuracy of abundance estimates increased with increasing number of survey days until day 5, and there was no improvement with additional data. This suggests that, for our system, 5-day camera surveys conducted at night were adequate for abundance estimation and population monitoring. Further, our study demonstrates that camera surveys and N-mixture models may be a highly effective method for estimation and monitoring of ungulate populations.     

Bias associated with baited camera sites for assessing population characteristics of deer

Camera surveys often involve placing bait in front of the camera to capture animals more frequently, which could introduce biases in parameter estimates. From September 2008 to March 2009, we monitored cameras placed at random, along game trails, and at feed stations to determine if camera placement influenced measures of population demographics in a herd of white-tailed deer (Odocoileus virginianus). There was no time period in which cameras placed at feed stations provided sex ratio and recruitment estimates similar to those acquired from randomly placed cameras. Trail-based camera surveys provided population estimates similar to those from random sites and may provide a feasible alternative to using baited camera stations. © 2011 The Wildlife Society.     

Using spotlight observations to predict resource selection and abundance for white-tailed deer

Spotlight surveys for white-tailed deer (Odocoileus virginianus) can yield large presence-only datasets applicable to a variety of resource selection modeling procedures. By understanding how populations distribute according to a given resource for a reference area, density and abundance can be predicted across new areas assuming the relationship between habitat quality (measured by an index of selection) and species distribution are equivalent. Habitat-based density estimators have been applied to wildlife species and are useful for addressing conservation and management concerns. Although achieving reliable population estimates is a primary goal for spotlighting studies, presence-only models have yet to be applied to spotlight data for estimating habitat selection and abundance for deer. From 2012 to 2017, we conducted spring spotlight surveys in each of 99 counties in Iowa, USA, and collected spatial locations for 20,149 groups of deer (n = 71,323 individuals). We used a resource selection function (RSF) based on deer locations to predict the relative probability of use for deer at the population level and to estimate statewide abundance. The number of deer observed statewide increased significantly with increasing RSF value for all years and the mean RSF value along survey transects explained 59% of the variability in county-level deer counts, indicating that a functional response between habitat quality and deer distribution existed at landscape scales. We applied our RSF to a habitat-based density estimator (extrapolation) and zero-inflated Poisson (ZIP) and negative binomial (ZINB) count models to predict statewide abundance from spotlight counts. Population estimates for 2012 were variable, indicating that atypical weather conditions may affect spotlight counts and population estimates in some years. For 2013–2017, we predicted a mean population of 439,129 (95% CI ∼ ± 55,926), 440,360 (∼ ± 43,676), and 465,959 (∼ ± 51,242) deer across years for extrapolation, ZIP, and ZINB models, respectively. Estimates from all models were not significantly different than estimates from an existing deer population accounting model in Iowa for 2013 and 2016, and differed by <76,000 deer for all models from 2013–2017. Extrapolation and ZIP models performed similarly and differed by <2,897 deer across all years, whereas ZINB models showed inconsistencies in model convergence and precision of estimates. Our results indicate that presence-only models are capable of producing reliable and precise estimates of resource selection and abundance for deer at broad landscape scales in Iowa and provide a tool for estimating deer abundance in a spatially explicit manner. © 2019 The Wildlife Society.     

Habitat Interference by Axis Deer on White-Tailed Deer

Abstract: Many studies of interactions between exotic and native ungulates have not had temporal and spatial controls nor have they considered the types of competitive interactions that would allow coexistence. For exotic axis deer (Axis axis) and native white-tailed deer (Odocoileus virginianus) to coexist one species should be superior at interference competition and the other species should be superior at exploitative competition. We generated and tested predictions, based on body size and diet breadth, about habitat selection by white-tailed deer in the presence and absence of axis deer, dominance relationships, and time at sites provisioned with high quality forage. We conducted our study in treatment (axis and white-tailed deer) and control (white-tailed deer only) areas when both species were present and after axis deer were removed. We conducted vehicle surveys to determine habitat use of both species. At provisioned feeding sites we recorded aggressive behaviors and amount of time species spent at feeding sites alone and together. In the treatment area white-tailed deer selection for wooded habitat increased 2.1 times after axis deer were removed, whereas habitat selection by white-tailed deer was constant in the control area over the same time. At feeding sites axis deer were dominant to white-tailed deer; both species spent a significantly greater amount of time alone than at feeders together, but amount of time that individuals of each species spent at feeders did not differ. Axis deer were superior at interference competition, but white-tailed deer were not superior at exploitative competition; thus, species coexistence is unlikely. Whether white-tailed deer are negatively impacted by axis deer at spatial scales larger than our experiment probably depends on abundance of axis deer at larger spatial scales. Experiments of species interactions with temporal and spatial controls that consider types of competitive interactions increase a manager's understanding of when and how native ungulates may be negatively impacted by exotic ungulates.     

Spotlight surveys for white-tailed deer: Monitoring panacea or exercise in futility?

Many monitoring programs for white-tailed deer (Odocoileus virginianus) on both private and public lands across the United States have long relied on the use of road-based spotlight surveys for monitoring population size and trends. Research has suggested spotlight surveys are ineffective and that road-based surveys for deer are biased because of highly variable detection rates. To evaluate variability in detection rates relative to the assumption that repeated surveys along roads will provide reliable trend data for use in calculating deer density estimates, we collected 5 years of thermal-imager and spotlight survey data using a multiple-observer, closed-capture approach. Using a Huggin's closed capture model, data bootstrapping, and variance components analyses, our results suggest that density estimates for white-tailed deer generated from data collected during road-based spotlight surveys are likely not reflective of the standing deer population. Detection probabilities during individual spotlight surveys ranged from 0.00 to 0.80 (median = 0.45) across all surveys, and differed by observer, survey, management unit, and survey transect replicate. Mean spotlight detection probability (0.41) and process standard deviation (0.12) estimates indicated considerable variability across surveys, observers, transects, and years, which precludes the generation of a correction factor or use of spotlight data to evaluate long-term trends at any scale. Although recommended by many state, federal, and non-governmental agencies, our results suggest that the benefit of spotlight survey data for monitoring deer populations is limited and likely represents a waste of resources with no appreciable management information gained. © 2012 The Wildlife Society.     

Estimating sika deer abundance using camera surveys

Cameras have been used throughout the world to estimate wildlife abundance and occupancy. Abundance estimates generated by camera surveys tend to be less invasive, less costly, and more accurate than other means in certain situations. We sought to expand and test the effectiveness of camera surveys on sika deer in Maryland. In 2008, we setup surveys with a 7-day pre-bait period followed by a 7-day active camera survey with 15 cameras. In 2009, we ran the cameras for the entire 14-day survey and moved cameras after each survey to determine if biases occur when using the same camera sites. During both years and all surveys, camera density was approximately 1-camera/65-ha. The abundance estimates were similar between years and estimators. In 2009, increasing photo intervals from 1-min to 5- and 10-min intervals reduced the number of pictures by 66 and 81%, respectively, while providing similar abundance estimates. We calculated the daily detection probabilities for all identifiable deer and we used radio-collared males that occurred within 2 km of the survey grid to assist in determining the optimum survey length. Detection probability did not vary between surveys in the same year, but varied between 2008 and 2009, most likely due to unlimited bait being available during 2008 surveys. Camera surveys have proven to be an accurate and cost effective means of estimating wildlife abundance and can be used successfully to determine sika deer abundance.     

Survey of haircoat fungal flora for the presence of dermatophytes in a population of white-tailed deer (Odocoileus virginianus) in Virginia

Before releasing rehabilitated wildlife, patients should be cured of all infectious agents that pose a risk to free-roaming wildlife or humans after release. Dermatophyte fungi, commonly known as "ringworm," have zoonotic potential and may be carried as normal flora on the haircoats of certain species. Outbreaks of ringworm are anecdotally reported to occur in white-tailed deer (Odocoileus virginianus) fawns, but no prevalence surveys have been conducted on the haircoat flora of free-roaming individuals. In November 2008, we tested 60 legally hunted white-tailed deer for dermatophyte flora by using a modified MacKenzie technique. Results indicate it is unlikely that wild, mature white-tailed deer in Virginia, USA, carry dermato-phyte fungi as normal haircoat flora. Therefore, wildlife rehabilitators and hunters are at low risk for dermatophyte infection by direct contact with this species. In addition, the RapidVet-D 3 Day Test for Veterinary Dermatophytosis was determined to have poor specificity for presence of dermatophyte fungi on asymptomatic white-tailed deer in Virginia.     

AnimalFinder: A semi-automated system for animal detection in time-lapse camera trap images

Although the use of camera traps in wildlife management is well established, technologies to automate image processing have been much slower in development, despite their potential to drastically reduce personnel time and cost required to review photos. We developed AnimalFinder in MATLAB® to identify animal presence in time-lapse camera trap images by comparing individual photos to all images contained within the subset of images (i.e. photos from the same survey and site), with some manual processing required to remove false positives and collect other relevant data (species, sex, etc.). We tested AnimalFinder on a set of camera trap images and compared the presence/absence results with manual-only review with white-tailed deer (Odocoileus virginianus), wild pigs (Sus scrofa), and raccoons (Procyon lotor). We compared abundance estimates, model rankings, and coefficient estimates of detection and abundance for white-tailed deer using N-mixture models. AnimalFinder performance varied depending on a threshold value that affects program sensitivity to frequently occurring pixels in a series of images. Higher threshold values led to fewer false negatives (missed deer images) but increased manual processing time, but even at the highest threshold value, the program reduced the images requiring manual review by ~ 40% and correctly identified > 90% of deer, raccoon, and wild pig images. Estimates of white-tailed deer were similar between AnimalFinder and the manual-only method (~ 1–2 deer difference, depending on the model), as were model rankings and coefficient estimates. Our results show that the program significantly reduced data processing time and may increase efficiency of camera trapping surveys.     

Estimating Deer Populations Using Camera Traps and Natural Marks

Despite the ubiquity of camera traps in wildlife monitoring projects, the data gathered are rarely used to estimate wildlife population demographics, a critical step in detecting declines, managing populations, and understanding ecosystem health. In contrast to abundant white-tailed deer (Odocoileus virginianus) in the eastern United States, black-tailed deer (Odocoileus hemionus columbianus) in the western United States have declined over the past several decades. We tested whether passively operating camera traps can be used to quantify population characteristics for black-tailed deer. We used images of naturally occurring physical characteristics of deer to develop movement and activity data and inform a Bayesian spatial mark-resight model that estimates deer abundance, density, sex ratio, ratio of fawns to adult females, and home range size. We developed the model to account for the effect of attractants (bait) on encounter rate. We placed 13 cameras on all known water sources of a private ranch in California and provided bait once a month in front of each camera. Over 9,000 visits occurred between 24 May 2012 and 21 January 2013, and we identified 50 individual deer from ear notches or antler characteristics. We estimated density at 7.7 deer/km² in summer and 8.6 deer/km² in fall. In the summer, home ranges were 2.3 km² for females and fawns and 16.8 km² for males. Home ranges constricted slightly in fall. We estimated a sex ratio of 12.5 males/100 females, and a ratio of 47.0 fawns/100 adult females. Bait increased baseline encounter rates (visits/week) by 3.7 times in summer and 4.95 times in fall. We found slightly higher densities of deer in our study area compared to other recent studies in more mountainous areas of California, and lower male:female sex ratios. This approach shows that commonly deployed camera traps can be used to quantify population characteristics, monitor populations, and inform harvest or habitat management decisions. © 2019 The Wildlife Society.     

Incorporating harvest rates into the sex-age-kill model for white-tailed deer

Although monitoring population trends is an essential component of game species management, wildlife managers rarely have complete counts of abundance. Often, they rely on population models to monitor population trends. As imperfect representations of real-world populations, models must be rigorously evaluated to be applied appropriately. Previous research has evaluated population models for white-tailed deer (Odocoileus virginianus); however, the precision and reliability of these models when tested against empirical measures of variability and bias largely is untested. We were able to statistically evaluate the Pennsylvania sex-age-kill (PASAK) population model using realistic error measured using data from 1,131 radiocollared white-tailed deer in Pennsylvania from 2002 to 2008. We used these data and harvest data (number killed, age-sex structure, etc.) to estimate precision of abundance estimates, identify the most efficient harvest data collection with respect to precision of parameter estimates, and evaluate PASAK model robustness to violation of assumptions. Median coefficient of variation (CV) estimates by Wildlife Management Unit, 13.2% in the most recent year, were slightly above benchmarks recommended for managing game species populations. Doubling reporting rates by hunters or doubling the number of deer checked by personnel in the field reduced median CVs to recommended levels. The PASAK model was robust to errors in estimates for adult male harvest rates but was sensitive to errors in subadult male harvest rates, especially in populations with lower harvest rates. In particular, an error in subadult (1.5-yr-old) male harvest rates resulted in the opposite error in subadult male, adult female, and juvenile population estimates. Also, evidence of a greater harvest probability for subadult female deer when compared with adult (≥2.5-yr-old) female deer resulted in a 9.5% underestimate of the population using the PASAK model. Because obtaining appropriate sample sizes, by management unit, to estimate harvest rate parameters each year may be too expensive, assumptions of constant annual harvest rates may be necessary. However, if changes in harvest regulations or hunter behavior influence subadult male harvest rates, the PASAK model could provide an unreliable index to population changes. © 2012 The Wildlife Society.     

Effects of supplemental feeding and density of white-tailed deer on rodents

Spatial distribution, population density, and reproductive success of many wildlife species may be altered by changes in vegetation composition, habitat structure, and availability of food. Altered distributions of key herbivores such as white-tailed deer (Odocoileus virginianus) may impact all of these factors. Our objective was to determine the direct and indirect effects of supplemental feeding of deer on rodent populations in south Texas. We modeled effects of supplemental feeding and habitat change due to deer browsing through surveys of rodents. Rodents have a short generation time and populations respond quickly to change, so they are a suitable indicator of changes in habitat structure brought about by deer browsing pressure. We sampled rodent populations near to and far from deer feeders within twelve 81-ha enclosures containing three different densities of deer with and without supplemental feed. The three deer densities were low (8.1 ha/deer), medium (3.2 ha/deer), and high (2 ha/deer). We conducted rodent trapping during March and April of 2007 and 2008. Abundance of rodents was much higher (P < 0.001) in 2008 than in the previous year due to an increase in rainfall. However, we found little effect of deer density, supplemental feeding of deer, or distance from deer feeders on rodent populations. Thus we conclude that supplemental feeding of deer and deer density had little influence on rodent communities in this environment. Rodent species native to semi-arid environments are probably adapted to large changes in vegetative productivity brought about by the highly variable annual rainfall patterns, therefore they can adapt to the less abrupt habitat changes resulting from changing densities of deer. Conservation concerns that providing supplemental feed to deer in semi-arid rangeland will disrupt the ecology of the land through changes in rodent populations were not supported. © 2011 The Wildlife Society.     

Spatio-temporal variation in male white-tailed deer harvest rates in Pennsylvania: Implications for estimating abundance

The performance of 2 popular methods that use age-at-harvest data to estimate abundance of white-tailed deer is contingent on assumptions about variation in estimates of subadult (1.5 yr old) and adult (≥2.5 yr old) male harvest rates. Auxiliary data (e.g., estimates of survival or harvest rates from radiocollared animals) can be used to relax some assumptions, but unless these population parameters exhibit limited temporal or spatial variation, these auxiliary data may not improve accuracy. Unfortunately maintaining sufficient sample sizes of radiocollared deer for parameter estimation in every wildlife management unit (WMU) is not feasible for most state agencies. We monitored the fates of 397 subadult and 225 adult male white-tailed deer across 4 WMUs from 2002 to 2008 using radio telemetry. We investigated spatial and temporal variation in harvest rates and investigated covariates related to the patterns observed. We found that most variation in harvest rates was explained spatially and that adult harvest rates (0.36–0.69) were more variable among study areas than subadult harvest rates (0.26–0.42). We found that hunter effort during the archery and firearms season best explained variation in harvest rates of adult males among WMUs, whereas hunter effort during only the firearms season best explained harvest rates for subadult males. From a population estimation perspective, it is advantageous that most variation was spatial and explained by a readily obtained covariate (hunter effort). However, harvest rates may vary if hunting regulations or hunter behavior change, requiring additional field studies to obtain accurate estimates of harvest rates. © 2011 The Wildlife Society.     

Comparison of occupancy modeling and radiotelemetry to estimate ungulate population dynamics

Radiotelemetry and unmarked occupancy modeling have been used to estimate animal population growth, but have not been compared for ungulates. We compared white-tailed deer (Odocoileus virginianus) population growth estimates from radiomarked individuals and occupancy modeling of unmarked individuals and evaluated advantages and disadvantages of each method. Estimates of population growth were obtained using remote camera (N = 54/year) detection/non-detection occupancy surveys of unmarked deer and from survival and recruitment data of radiomarked adult females (N = 87) and neonate fawns (N = 127) in a predominantly forested region of the Upper Peninsula of Michigan, USA, 2009–2011. We hypothesized that occupancy models and radiotelemetry data would have similar population growth trends because both methods sampled the same temporally closed population. Percent changes in camera trap data generally reflected finite population growth (λ) of radiomarked deer which increased (λ = 1.10 ± 0.01) from 2009 to 2010, but decreased (λ = 0.87 ± 0.02) from 2010 to 2011. Also, unmarked adult female abundance and fawn:adult female ratios generally reflected trends in radiomarked deer survival and recruitment. Royle–Nichols occupancy model abundance estimates had wide confidence intervals, which may preclude using this method from accurately estimating deer population growth. Radiotelemetry provided more precise population growth estimates, while allowing collection of vital rates and location data. However, the Royle–Nichols occupancy model may be preferred to radiotelemetry because it reflected yearly variation in population growth with reduced labor and no invasive marking. Researchers should consider the objectives and logistics of their study when choosing a specific method.     

Investigations of spawning migration and assessment of abundance of the Kamchatka steelhead (<Emphasis Type="Italic">Parasalmo mykiss</Emphasis>) from the Utkholok River by means of Didson dual-frequency identification sonar

Quantative estimates of abundance of anadromous Kamchatka steelhead Parasalmo mykiss in the period of its maximum spawning migration in the shallow Utkholok River by the instrumental method using Didson dual-frequency identification sonar are presented. Equipment and methods are described for the stationary observation of spawning run of Kamchatka steelhead through the river cross section and mobile surveys of the water area of the Utkholok R. As a result of stationary observations, the abundance and size composition of Kamchatka steelhead migrating to the upper reaches of the river are determined. Peculiarities of the diurnal dynamics of migration of Kamchatka steelhead characterized by two sharp peaks of run intensity in the morning and evening were revealed. During the period of observations from September 22 to October 20, 2007, in the seasonal dynamics of migration two peaks of intensity of run of Kamchatka steelhead depending on an abrupt decrease in water temperature by 2°C were also registered. Mobile surveys supplied data on the abundance and size composition of Kamchatka steelhead in the surveyed water area of the river, on its spatial distribution, and dynamics of accumulation of fish in the river. The abundance of Kamchatka steelhead in the river almost doubled every three-four days and the spatial distribution was aggregated, producing maximum concentration mainly in areas of increasing depth and channel meandering before and after riffles. Comparison of the results of assessment of abundance of Kamchatka steelhead that arrived for spawning in 2006 and 2007 showed significant fluctuations in population abundance.     

Comparing contemporary models to traditional indices to estimate abundance of desert bighorn sheep

Aerial surveys for large ungulates produce count data that often underrepresent the number of animals. Errors in count data can lead to erroneous estimates of abundance if they are not addressed. Our objective was to address imperfect detection probability by developing a framework that produces realistic and defensible estimates of bighorn sheep (Ovis canadensis) abundance. We applied our framework to a population of desert bighorn sheep (O. c. nelsoni) in the Great Basin, Nevada, USA. We captured and marked 24 desert bighorn sheep with global positioning system (GPS)-collars and then conducted helicopter surveys naïve to the locations of collared animals. We developed a Bayesian integrated data model to leverage information from telemetry data, helicopter survey counts, and habitat characteristics to estimate abundance while accounting for availability and perception probability (i.e., detection given availability). Distance to ridgeline, terrain ruggedness, tree cover, and slope influenced perception probability of sheep given they were viewable from the helicopter. There was also annual variation in perception probability (2018: median = 0.64, credible interval [CrI] = 0.37–0.87; 2019: median = 0.81, CrI = 0.49–0.97). The abundance estimates from the integrated data model decreased from 2018 (594; 95% CrI = 537–656) to 2019 (487; 95% CrI = 436–551). In addition, accounting for availability and imperfect perception resulted in greater estimates of abundance compared to traditional directed search methods, which were 340 for 2018 and 320 for 2019. Our modeling framework can be used to generate more defensible population estimates of bighorn sheep and other large mammals that have been surveyed in a similar manner.     

Evaluating Differences in Harvest Data Used in the Sex-Age-Kill Deer Population Model

Abstract: A steady increase in archery hunting participation and frequent changes in hunter regulations led to an evaluation of harvest data used in a common white-tailed deer (Odocoileus virginianus) population model. Our goal was to determine if model parameters and population estimates traditionally estimated solely by firearm harvest data were biased with respect to altered sex and age ratios brought about by increases in archery hunting and harvest success. The sex-age-kill (SAK) model, commonly used by state agencies, was developed in the mid-1900s when deer numbers were low and firearm harvest was predominant. Management actions were concentrated on increasing deer numbers, and model assumptions relied heavily on a stable age distribution and a minimal antlerless deer harvest. We evaluated the reliance of SAK in a modern hunting scenario using a 10-year dataset obtained from Michigan, USA, that encompassed a variety of climatic regions, hunting seasons, and regulation scenarios. We found that firearm and archery harvest sex and age ratios differed among 5 geographic groups and study years for males, females, and fawns (P<0.001, P = 0.001, and P = 0.037, respectively). Also, the addition of archery harvest data increased population estimates but did not alter overall trends. We recommend that managers reassess harvest-based population estimates in 2 situations: 1) if regulation changes affect antlerless deer harvest, and 2) when trends in hunter success rates cause fluctuations in harvest data.     

An Evaluation of Sex-Age-Kill (SAK) Model Performance

ABSTRACT The sex-age-kill (SAK) model is widely used to estimate abundance of harvested large mammals, including white-tailed deer (Odocoileus virginianus). Despite a long history of use, few formal evaluations of SAK performance exist. We investigated how violations of the stable age distribution and stationary population assumption, changes to male or female harvest, stochastic effects (i.e., random fluctuations in recruitment and survival), and sampling efforts influenced SAK estimation. When the simulated population had a stable age distribution and λ > 1, the SAK model underestimated abundance. Conversely, when λ < 1, the SAK overestimated abundance. When changes to male harvest were introduced, SAK estimates were opposite the true population trend. In contrast, SAK estimates were robust to changes in female harvest rates. Stochastic effects caused SAK estimates to fluctuate about their equilibrium abundance, but the effect dampened as the size of the surveyed population increased. When we considered both stochastic effects and sampling error at a deer management unit scale the resultant abundance estimates were within ±121.9% of the true population level 95% of the time. These combined results demonstrate extreme sensitivity to model violations and scale of analysis. Without changes to model formulation, the SAK model will be biased when λ ≠ 1. Furthermore, any factor that alters the male harvest rate, such as changes to regulations or changes in hunter attitudes, will bias population estimates. Sex-age-kill estimates may be precise at large spatial scales, such as the state level, but less so at the individual management unit level. Alternative models, such as statistical age-at-harvest models, which require similar data types, might allow for more robust, broad-scale demographic assessments.     

Combining genetic structure and demographic analyses to estimate persistence in endangered Key deer (<Emphasis Type="Italic">Odocoileus virginianus clavium</Emphasis>)

Recent improvements in genetic analyses have paved the way in using molecular data to answer questions regarding evolutionary history, genetic structure, and demography. Key deer are a federally endangered subspecies assumed to be genetically unique, homogeneous, and have a female-biased population of approximately 900 deer. We used 985 bp of the mitochondrial cytochrome b gene and 12 microsatellite loci to test two hypotheses: (1) that Key deer are isolated and have reduced diversity compared to mainland deer and (2) that isolation of the Florida Keys has led to a small population size and a high risk of extinction. Our results indicate that Key deer are indeed genetically isolated from mainland white-tailed deer and that there is a lack of genetic substructure between islands. While Key deer exhibit reduced levels of genetic diversity compared to their mainland counterparts, they contain enough diversity to uniquely identify individual deer. Based on genetic identification, we estimated a census size of around 1000 individuals with a heavily skewed female-biased adult sex ratio. Furthermore, our genetic and contemporary demographic data were used to generate a species persistence model of the Key deer. Sensitivity tests within the population viability analysis brought to light the importance of fetal sex ratio and female survival as the primary factors at risk of driving the subspecies to extinction. This study serves as a prime example of how persistence models can be used to evaluate population viability in natural populations of endangered organisms.     

Variation in the herd composition counts of sika deer

Herd composition counts (HCC) are commonly used to assess population status in deer. We evaluated the reliability of HCC of sika deer (Cervus nippon Temminck) using repeated counts and by comparing estimated sex ratios and calf-to-female ratios of marked deer on Nakanoshima Island, Hokkaido, Japan between April 1999 and October 2000. Although both total counts and sex and age ratios fluctuated greatly by month, seasonal changes showed a relatively small variance. This suggested that seasonal changes in behavior within sex and age classes contributed to biased ratio estimates obtained from HCC. Route counts should be used as a relative population abundance index with estimates of detection probability, especially for females. Adult sex ratios and age ratios from HCC were unbiased during the rutting season (October–November), and age ratios in spring could be used if yearlings are counted as adults.