Estimating wolf (Canis lupus) densities using video camera traps and spatial capture-recapture analysis

被引:4
作者
Jimenez, Jose [1 ]
Cara, Daniel [2 ]
Garcia-Dominguez, Francisco [3 ]
Barasona, Jose Angel [4 ,5 ]
机构
[1] CSIC UCLM JCCM, Inst Invest Recursos Cineget IREC, Ciudad Real, Spain
[2] TRAGSATEC, Madrid, Spain
[3] Minist Trans Ecol & Reto Demog, Madrid, Spain
[4] Univ Complutense Madrid, Fac Vet, VISAVET Hlth Surveillance Ctr, Madrid, Spain
[5] Univ Complutense Madrid, Fac Vet, Anim Hlth Dept, Madrid, Spain
来源
ECOSPHERE | 2023年 / 14卷 / 07期
关键词
camera trap; Canis lupus; gregariousness; heterogeneity; identification; population density; spatial capture-recapture; video; wolf; TROPHIC CASCADES; SARCOPTIC MANGE; WOLVES; YELLOWSTONE; MODELS; SIZE;
D O I
10.1002/ecs2.4604
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Estimating population density is critical for effective species conservation, wildlife management planning, and long-term monitoring. Obtaining accurate estimates is especially important for the wolf (Canis lupus), a widely distributed northern hemisphere apex predator whose management and conservation are highly controversial in most of its range, and whose presence usually generates high-profile media coverage. The peculiarities of wolf social spatial organization and behavior can violate the assumptions of capture-recapture models (uniformity and independence, respectively) to a greater or lesser extent and make it difficult to obtain precise and reliable density estimates. This paper presents a case study, which estimated the population density of the Iberian wolf in the Dorsal Gallega mountain ridge (Galicia, NW Spain) based on the identification of individual wolves from their traits and behavior using video camera traps and spatially explicit capture-recapture (SCR) analyses. The study followed three phases. Firstly, field data were collected by installing camera traps and changing their location until the entire area was sampled. Second, a complete morphological and behavioral study of the wolves recorded was performed to facilitate individual recognition. Third, overdispersion due to gregariousness and other sources of heterogeneity was modeled in the SCR analyses comparing Poisson and negative binomial observation models with different random effects on the baseline detection probability. We estimated a density of 2.88 (SD: 0.37) wolves/100 km(2) in the study area. We concluded that estimating wolf population size using camera trap videos, individual identification, and SCR provides a feasible method and can be used for estimating the density in similar species.
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页数:14
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