Estimating deer density and abundance using spatial mark–resight models with camera trap data

Bengsen, Andrew J.; Forsyth, David M.; Ramsey, Dave; Amos, Matt; Brennan, Michael; Pople, Anthony; Comte, Sébastien; Crittle, Troy

doi:10.1093/jmammal/gyac016

Cited by 14 publications

(11 citation statements)

References 52 publications

(81 reference statements)

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“…We found that sambar deer activity decreased in the treatment area relative to the non-treatment area. Detection rates of deer on camera traps were positively correlated with deer densities estimated using spatial mark-resight models for white-tailed deer (Odocoileus virginianus) across 20 sites in the United States (Parsons et al 2017) and for sambar deer across fives sites in eastern Australia (Bengsen et al 2022). We therefore believe that sambar deer activity on camera traps is a reliable index of sambar deer relative abundance in our study areas.…”

Section: Discussionmentioning

confidence: 66%

Seasonal and daily activity of non-native sambar deer in and around high-elevation peatlands, south-eastern Australia

et al. 2022

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Context Of the six species of non-native deer present in Australia, the sambar deer is the largest and has been identified as a major threat to high-elevation peatlands in south-eastern Australia. However, little is known about sambar deer activity in high-elevation peatlands. Aims The aims of this study were to quantify sambar deer activity (including wallowing) seasonally and daily in response to biotic and abiotic variables, and how activity was impacted by ground-based shooting. Methods To estimate sambar deer activity, camera traps were continuously deployed for 4 years in two ~4300-ha areas in Alpine National Park, Victoria, south-eastern Australia. One area was subject to management operations using ground-based shooting to target deer and the other was not. Monthly activity of sambar deer was modelled using biotic (woody vegetation cover), abiotic (snow depth, aspect, slope, distance to water, road and peatland) and management (treatment versus non-treatment) covariates. Additional camera traps were deployed to monitor sambar deer activity at wallows. Key results Sambar deer activity decreased when snow depth increased (between July and September), and was highest in easterly and northerly aspects with dense woody vegetation close to high-elevation peatlands and roads. During our 4-year study, sambar deer activity decreased in the treatment area but increased in the non-treatment area. Sambar deer exhibited a crepuscular diel cycle, with greatest activity around sunset. Only male sambar deer were observed to wallow, with most wallowing occurring in the afternoon during October–June. Conclusions Sambar deer utilised high-elevation peatlands during October–June. Daily activity was crepuscular and was greatest in dense tree cover close to roads. Ground-based shooting reduced sambar deer activity in and around high-elevation peatlands. Implications Control operations targeting sambar deer at high elevations in south-eastern Australia should be conducted during October–June. Outside this period sambar deer appear to use lower-elevation habitats. The effectiveness of ground-based shooting could be improved by focusing this control action around sunset (when sambar deer are most active) and in places with dense vegetation close to roads and high-elevation peatlands.

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Section: Discussionmentioning

confidence: 66%

Seasonal and daily activity of non-native sambar deer in and around high-elevation peatlands, south-eastern Australia

et al. 2022

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“…In more densely vegetated areas, camera trap (Ramsey et al . 2019; Bengsen et al . 2022 b ), faecal DNA (Brazeal et al .…”

Section: Discussionmentioning

confidence: 99%

“…Aerial survey methods, as used in this study, are best suited to treeless or open woodland habitats (Forsyth et al 2022), such as the predominantly agricultural landscapes that we studied. In more densely vegetated areas, camera trap (Ramsey et al 2019;Bengsen et al 2022b), faecal DNA (Brazeal et al 2017) or thermal imaging surveys (T. Cox, E. O'Dwyer-Hall, R. Matthews, C. Wilsdon, D. Forsyth, A. Bengsen, G. Halverson, unpubl. data) could be used to estimate deer density (Forsyth et al 2022).…”

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confidence: 99%

Effectiveness and costs of helicopter-based shooting of deer

Bengsen,

Forsyth,

Pople

et al. 2022

Wildlife Res.

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Context. Helicopter-based shooting has been widely used to harvest deer or control overabundant populations in Australasia, but the effectiveness and cost of this method as a deer control tool has seldom been evaluated. Aims. We evaluated the effectiveness and costs of helicopter-based shooting of fallow deer (Dama dama) and chital deer (Axis axis) in eastern Australia by quantifying (1) reductions in density, (2) the relationship between numbers killed per hour and deer density (i.e. the functional response), (3) the costs of control and (4) the effort-outcome and cost-outcome relationships. Methods. We evaluated the costs and effectiveness of 12 aerial shooting operations aiming to reduce fallow deer (n = 8) or chital deer (n = 4) population densities at nine sites in eastern Australia. Sites were characterised by fragmented woodland, and all but one operation aimed to reduce grazing competition with livestock. We used precontrol population density estimates and operational monitoring data to estimate the costs and outcomes of each operation. We combined data from all operations to estimate the relationship between shooting effort and population reduction, as well as costs associated with different levels of effort. Key results. Population reductions for operations ranged from 5% to 75% for fallow deer, and from 48% to 88% for chital deer. The greatest population reductions occurred when effort per unit area was greatest, and the largest reductions in deer density occurred when shooting was conducted in consecutive years. The functional response of hourly kills to deer density was best described by a modified Ivlev model, with the asymptotic kill rate estimated to be 50 deer per hour. There was no support for the existence of a prey refuge, that is, a threshold population density below which no deer could be shot. Helicopter charter was the primary cost of helicopter-based shooting programs, followed by labour; firearm and ammunition costs were relatively minor. Conclusions. Helicopter-based shooting can rapidly reduce deer populations over large geographic areas, but the magnitude of the reduction depends on the effort (hours of shooting) per deer per km 2 . Implications. Aerial shooting operations should include a pre-control population survey so that (1) measurable objectives can be established, (2) the likely level of effort and cost required for objectives to be met can be estimated and planned for, and (3) the realised population reduction can be estimated.

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“…First, the declining cost of genetic analysis means that techniques using information collected from feces, hair, and tissue to identify individuals is becoming more feasible for estimating deer abundance at management scales (Brinkman et al 2011, Brazeal et al 2017). Second, recent advances in statistical methods allow deer abundance and density to be estimated using motion‐sensitive camera images using either spatial CR (Parsons et al 2017, Macaulay et al 2020, Bengsen et al 2022) or point‐based DS (Bessone et al 2020) methods. Third, methods that identify individuals using multiple techniques, such as fecal DNA and motion‐sensitive cameras, and perform analyses using spatial CR methods (Borchers and Efford 2008, Royle and Young 2008, Royle et al 2013) are promising for providing relatively precise deer abundance estimates (Furnas et al 2020), at least for small‐ to medium‐sized study areas.…”

Section: Discussionmentioning

confidence: 99%

Methodology matters when estimating deer abundance: a global systematic review and recommendations for improvements

et al. 2022

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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.

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Estimating deer density and abundance using spatial mark–resight models with camera trap data

Cited by 14 publications

References 52 publications

Seasonal and daily activity of non-native sambar deer in and around high-elevation peatlands, south-eastern Australia

Seasonal and daily activity of non-native sambar deer in and around high-elevation peatlands, south-eastern Australia

Effectiveness and costs of helicopter-based shooting of deer

Methodology matters when estimating deer abundance: a global systematic review and recommendations for improvements

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