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Globally, many wild deer populations are actively studied or managed for conservation, hunting, or damage mitigation purposes. These studies require reliable estimates of population state parameters, such as density or abundance, with a level of precision that is fit for purpose. Such estimates can be difficult to attain for many populations that occur in situations that are poorly suited to common survey methods. We evaluated the utility of combining camera trap survey data, in which a small proportion of the sample is individually recognizable using natural markings, with spatial mark–resight (SMR) models to estimate deer density in a variety of situations. We surveyed 13 deer populations comprising four deer species (Cervus unicolor, C. timorensis, C. elaphus, Dama dama) at nine widely separated sites, and used Bayesian SMR models to estimate population densities and abundances. Twelve surveys provided sufficient data for analysis and seven produced density estimates with coefficients of variation (CVs) ≤ 0.25. Estimated densities ranged from 0.3 to 24.6 deer km−2. Camera trap surveys and SMR models provided a powerful and flexible approach for estimating deer densities in populations in which many detections were not individually identifiable, and they should provide useful density estimates under a wide range of conditions that are not amenable to more widely used methods. In the absence of specific local information on deer detectability and movement patterns, we recommend that at least 30 cameras be spaced at 500–1,000 m and set for 90 days. This approach could also be applied to large mammals other than deer.

Lead toxicity threatens scavenging wildlife globally. To allow inexpensive measurement of long-term lead exposure from archived wildlife tissues, portable X-ray fluorescence (XRF)1devices have been validated to measure lead concentrations in bone samples from bird species. In this study, we evaluated the efficacy of portable XRF for hair lead measurement in a specialist mammalian scavenger, the threatened Tasmanian devil (Sarcophilus harrisii). We attempted to first validate the method by analyzing relatively large (∼1.0 g) hair samples from 39 deceased animals initially with XRF, and then with inductively coupled plasma mass spectrometry (ICP-MS) (validation study). We then measured lead concentrations via XRF only in a further 61 hair samples taken from live devils trapped in a plantation forestry landscape, where devils may scavenge on browsing marsupials that are regularly culled using lead ammunition (plantation study). Portable XRF measures of hair lead levels were positively correlated with ICP-MS values (R2= 0.95), although the relationship was weak at low lead concentrations. In the validation study, 95% of sampled Tasmanian devils had relatively low lead levels (≤ 3 mg/kg), but the remaining two animals showed considerably elevated lead levels (> 15 mg/kg), suggesting that harmful long-term lead exposure can occur in this species. In the plantation study, lead levels were comparable to those found in the hair of mammals in other studies, though a higher proportion (11%) of devils showed levels > 3 mg/kg than in the validation study, suggesting devils may have higher exposure to lead in a landscape subjected to regular culling of browsing mammals. Our results suggests that portable XRF is a promising emerging technology, and after some refinement, may allow non-invasive real-time measurement of lead concentrations in the hair of mammals.

Context Helicopter-based shooting has been widely used to kill deer in Australasia, but the animal welfare outcomes of this technique have not been evaluated. Aim To assess the animal welfare outcomes of helicopter-based shooting of deer in Australia by quantifying the fates of deer seen and shot at, the duration of procedures and the number and location of bullet wounds in deer. Methods Three deer control operations were assessed. These operations targeted: (1) chital deer (Axis axis) in Queensland, (2) fallow deer (Dama dama) in Australian Capital Territory and (3) fallow deer in New South Wales. For each operation, an independent veterinarian conducted ante-mortem (i.e. from the helicopter as shooting occurred) and post-mortem (i.e. from the ground after shooting had ceased) observations. The ante-mortem data were used to estimate the proportion of deer seen that were shot, chase time (CT), time to insensibility (TTI) and total time (TT; CT + TTI). The numbers and locations of bullet wounds were recorded post-mortem. Key results Ante-mortem and post-mortem observations were performed for 114–318 and 60–105 deer, respectively, in the three operations. Shots were fired at 69–76% of deer that were observed. Median CT ranged from 73 to 145 s. Median TTI ranged from 17 to 37 s and median TT ranged from 109 to 162 s. The mean number of bullet wounds per deer ranged from 1.43 to 2.57. Animal welfare outcomes were better in the two fallow deer operations than in the chital deer operation. In both fallow deer operations, most deer were shot multiple times and at least once in the head or thorax. In contrast, chital deer were shot fewer times and less often in the head or thorax, and non-fatal wounding was observed. Conclusions The best animal welfare outcomes were achieved when helicopter-based shooting operations followed a fly-back procedure and mandated that multiple shots were fired into each animal. Implications Animal welfare outcomes for helicopter-based deer shooting in Australia could be improved with a national-level standard operating procedure requiring helicopters to fly back over shot animals and repeatedly shoot animals in the head or thorax.

Deer (Cervidae) are key components of many ecosystems and estimating deer abundance or density is important to understanding these roles. Many field methods have been used to estimate deer abundance and density, but the factors determining where, when, and why a method was used, and its usefulness, have not been investigated. We systematically reviewed journal articles published during 2004–2018 to evaluate spatio-temporal trends in study objectives, methodologies, and deer abundance and density estimates, and determine how they varied with biophysical and anthropogenic attributes. We also reviewed the precision and bias of deer abundance estimation methods. We found 3,870 deer abundance and density estimates. Most estimates (58%) were for white-tailed deer (Odocoileus virginianus), red deer (Cervus elaphus), and roe deer (Capreolus capreolus). The 6 key methods used to estimate abundance and density were pedestrian sign (track or fecal) counts, pedestrian direct counts, vehicular direct counts, aerial direct counts, motion-sensitive cameras, and harvest data. There were regional differences in the use of these methods, but a general pattern was a temporal shift from using harvest data, pedestrian direct counts, and aerial direct counts to using pedestrian sign counts and motion-sensitive cameras. Only 32% of estimates were accompanied by a measure of precision. The most precise estimates were from vehicular spotlight counts and from capture–recapture analysis of images from motion-sensitive cameras. For aerial direct counts, capture–recapture methods provided the most precise estimates. Bias was robustly assessed in only 16 studies. Most abundance estimates were negatively biased, but capture–recapture methods were the least biased. The usefulness of deer abundance and density estimates would be substantially improved by 1) reporting key methodological details, 2) robustly assessing bias, 3) reporting the precision of estimates, 4) using methods that increase and estimate detection probability, and 5) staying up to date on new methods. The automation of image analysis using machine learning should increase the accuracy and precision of abundance estimates from direct aerial counts (visible and thermal infrared, including from unmanned aerial vehicles [drones]) and motion-sensitive cameras, and substantially reduce the time and cost burdens of manual image analysis.