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通过照片捕捉-再捕捉法优化在瑞士阿尔卑斯山监测欧亚猞猁(猞猁)种群的调查区域大小。

Optimizing the size of the area surveyed for monitoring a Eurasian lynx (Lynx lynx) population in the Swiss Alps by means of photographic capture-recapture.

作者信息

Zimmermann Fridolin, Breitenmoser-Würsten Christine, Molinari-Jobin Anja, Breitenmoser Urs

机构信息

KORA, Muri, Switzerland Institute of Veterinary Virology, University of Bern, Bern, Switzerland.

出版信息

Integr Zool. 2013 Sep;8(3):232-43. doi: 10.1111/1749-4877.12017.

DOI:10.1111/1749-4877.12017
PMID:24020463
Abstract

We studied the influence of surveyed area size on density estimates by means of camera-trapping in a low-density felid population (1-2 individuals/100 km(2) ). We applied non-spatial capture-recapture (CR) and spatial CR (SCR) models for Eurasian lynx during winter 2005/2006 in the northwestern Swiss Alps by sampling an area divided into 5 nested plots ranging from 65 to 760 km(2) . CR model density estimates (95% CI) for models M0 and Mh decreased from 2.61 (1.55-3.68) and 3.6 (1.62-5.57) independent lynx/100 km(2) , respectively, in the smallest to 1.20 (1.04-1.35) and 1.26 (0.89-1.63) independent lynx/100 km(2) , respectively, in the largest area surveyed. SCR model density estimates also decreased with increasing sampling area but not significantly. High individual range overlaps in relatively small areas (the edge effect) is the most plausible reason for this positive bias in the CR models. Our results confirm that SCR models are much more robust to changes in trap array size than CR models, thus avoiding overestimation of density in smaller areas. However, when a study is concerned with monitoring population changes, large spatial efforts (area surveyed ≥760 km(2) ) are required to obtain reliable and precise density estimates with these population densities and recapture rates.

摘要

我们通过相机捕捉法,研究了调查区域大小对低密度猫科动物种群(1 - 2只个体/100平方公里)密度估计的影响。2005/2006年冬季,我们在瑞士阿尔卑斯山西北部,通过对一个划分为5个嵌套样地(面积从65平方公里到760平方公里不等)的区域进行采样,运用非空间捕获 - 重捕(CR)模型和空间CR(SCR)模型对欧亚猞猁进行了研究。对于M0和Mh模型,CR模型的密度估计值(95%置信区间)分别从最小样地中的2.61(1.55 - 3.68)只独立猞猁/100平方公里和3.6(1.62 - 5.57)只独立猞猁/100平方公里,下降到最大调查区域中的1.20(1.04 - 1.35)只独立猞猁/100平方公里和1.26(0.89 - 1.63)只独立猞猁/100平方公里。SCR模型的密度估计值也随采样面积的增加而下降,但不显著。相对较小区域内较高的个体活动范围重叠(边缘效应)是CR模型中出现这种正偏差的最合理原因。我们的结果证实,与CR模型相比,SCR模型对诱捕阵列大小的变化更具稳健性,从而避免了在较小区域高估密度。然而,当一项研究关注种群变化监测时,对于这些种群密度和重捕率,需要进行大规模的空间调查(调查面积≥760平方公里)才能获得可靠且精确的密度估计值。

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