Estimating red deer abundance using the pellet-based distance sampling method

R.T. Torres, A.M. Valente, T.A. Marques and C. Fonseca
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R.T. Torres: CESAM, Department of Biology, University of Aveiro, Aveiro, Portugal
A.M. Valente: CESAM, Department of Biology, University of Aveiro, Aveiro, Portugal
T.A. Marques: Centre for Research into Ecological and Environmental Modelling, University of St Andrews, St Andrews, Scotland
C. Fonseca: CESAM, Department of Biology, University of Aveiro, Aveiro, Portugal

Journal of Forest Science, 2015, vol. 61, issue 10, 422-430

Abstract: Many European agricultural landscapes have been abandoned facilitating the comeback of large ungulates. In Portugal, the increase in red deer numbers caused local conflicts with landowners reporting economic losses in forest and agricultural plantations. A great effort is needed to mitigate human-red deer conflicts through management strategies. Successful management strategies require reliable information on population trends. Here we propose an easy and readily applied method to estimate an increasing ungulate population. We estimated the red deer population density in a Mediterranean environment located in northeastern Portugal: Lombada National Hunting Area (LNHA) and Serra de Montesinho (SM), using pellet group counts coupled with distance sampling to account for pellet detectability. The estimated red deer density using a stratified detection function was 5.81 indd per 100 ha for LNHA and 1.34 indd per 100 ha for SM (95% CI: 3.65-9.25 and 0.74-2.42, respectively). For the entire area, the estimated density was 3.38 deer per 100 ha (95% CI: 2.18-5.24). Monitoring population trends is crucial to assess the impact of methods aimed at reducing the population size or impact and here we provided an example of a robust method that can be implemented to continuously monitor expanding populations.

Keywords: cervidae; distance sampling; deer density; pellet group counting; rural areas (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:61:y:2015:i:10:id:52-2015-jfs

DOI: 10.17221/52/2015-JFS

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