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Influence of harvesting pressure on demographic tactics: implications for wildlife management

Published on Aug 1, 2011in Journal of Applied Ecology5.78
· DOI :10.1111/j.1365-2664.2011.02017.x
Sabrina Servanty9
Estimated H-index: 9
(CSU: Colorado State University),
Jean-Michel Gaillard68
Estimated H-index: 68
(University of Lyon)
+ 3 AuthorsOlivier Gimenez39
Estimated H-index: 39
(CNRS: Centre national de la recherche scientifique)
Abstract
Summary 1. Demographic tactics within animal populations are shaped by selective pressures. Exploitation exerts additional pressures so that differing demographic tactics might be expected among populations with differences in levels of exploitation. Yet little has been done so far to assess the possible consequences of exploitation on the demographic tactics of mammals, even though such information could influence the choice of effective management strategies. 2. Compared with similar-sized ungulate species, wild boar Sus scrofa has high reproductive capabilities, which complicates population management. Using a perturbation analysis, we investigated how population growth rates (λ) and critical life-history stages differed between two wild boar populations monitored for several years, one of which was heavily harvested and the other lightly harvested. 3. Asymptotic λ was 1·242 in the lightly hunted population and 1·115 in the heavily hunted population, while the ratio between the elasticity of adult survival and juvenile survival was 2·63 and 1·27, respectively. A comparative analysis including 21 other ungulate species showed that the elasticity ratio in the heavily hunted population was the lowest ever observed. 4. Compared with expected generation times of similar-sized ungulates (more than 6 years), wild boar has a fast life-history speed, especially when facing high hunting pressure. This is well illustrated by our results, where generation times were 3·6 years in the lightly hunted population and only 2·3 years in the heavily hunted population. High human-induced mortality combined with non-limiting food resources accounted for the accelerated life history of the hunted population because of earlier reproduction. 5. Synthesis and applications. For wild boar, we show that when a population is facing a high hunting pressure, increasing the mortality in only one age-class (e.g. adults or juveniles) may not allow managers to limit population growth. We suggest that simulations of management strategies based on context-specific demographic models are useful for selecting interventions for population control. This type of approach allows the assessment of population response to exploitation by considering a range of plausible scenarios, improving the chance of selecting appropriate management actions.
  • References (54)
  • Citations (68)
References54
Newest
#1Luis-Miguel Chevin (Imperial College London)H-Index: 18
#2Russell Lande (Imperial College London)H-Index: 74
Last.Georgina M. Mace (Imperial College London)H-Index: 75
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#1Stephen Richards (BCM: Baylor College of Medicine)H-Index: 43
#2Richard A. Gibbs (BCM: Baylor College of Medicine)H-Index: 137
Last.Christie Kovar (BCM: Baylor College of Medicine)H-Index: 39
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#1Laura B. Hanson (AU: Auburn University)H-Index: 4
#2Michael S. Mitchell (UM: University of Montana)H-Index: 26
Last.Stephen S. Ditchkoff (AU: Auburn University)H-Index: 19
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#1Fred W. Allendorf (UM: University of Montana)H-Index: 72
#2Phillip R. England (O&A: CSIRO Marine and Atmospheric Research)H-Index: 18
Last.Nils Ryman (Stockholm University)H-Index: 50
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Cited By68
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#1Claudia Bieber (University of Veterinary Medicine Vienna)H-Index: 14
#2Evelyn Rauchenschwandtner (University of Veterinary Medicine Vienna)
Last.Sebastian G. Vetter (University of Veterinary Medicine Vienna)H-Index: 3
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#1Johanna StaerkH-Index: 1
#2Dalia Amor Conde (University of Southern Denmark)H-Index: 10
Last.Fernando Colchero (University of Southern Denmark)H-Index: 11
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#2Christophe Barbraud (CNRS: Centre national de la recherche scientifique)H-Index: 43
Last.X. Bonnet (CNRS: Centre national de la recherche scientifique)
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#1M Zedda (University of Sassari)H-Index: 8
#2Desiré Brits (University of the Witwatersrand)H-Index: 4
Last.Vittorio Farina (University of Sassari)H-Index: 7
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#2Maxwell da Rosa Oliveira (UFMS: Federal University of Mato Grosso do Sul)
Last.A. O. Pellegrin (Empresa Brasileira de Pesquisa Agropecuária)H-Index: 8
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#1Joanie Van de Walle (Laval University)H-Index: 4
#2Gabriel Pigeon (Université de Sherbrooke)H-Index: 5
Last.Fanie Pelletier (Laval University)H-Index: 29
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