Maronde Lea, McClintock Brett T, Breitenmoser Urs, Zimmermann Fridolin
Carnivore Ecology and Wildlife Management KORA Muri bei Bern Switzerland.
Alaska Fisheries Science Center Marine Mammal Laboratory NOAA-NMFS Seattle Washington USA.
Ecol Evol. 2020 Dec 2;10(24):13968-13979. doi: 10.1002/ece3.6990. eCollection 2020 Dec.
In Switzerland, the European wildcat (), a native felid, is protected by national law. In recent decades, the wildcat has slowly returned to much of its original range and may have even expanded into new areas that were not known to be occupied before. For the implementation of efficient conservation actions, reliable information about the status and trend of population size and density is crucial. But so far, only one reliable estimate of density in Switzerland was produced in the northern Swiss Jura Mountains. Wildcats are relatively rare and elusive, but camera trapping has proven to be an effective method for monitoring felids. We developed and tested a monitoring protocol using camera trapping in the northern Jura Mountains (cantons of Bern and Jura) in an area of 100 km. During 60 days, we obtained 105 pictures of phenotypical wildcats of which 98 were suitable for individual identification. We identified 13 individuals from both sides and, additionally, 5 single right-sided flanks and 3 single left-sided flanks that could not be matched to unique individuals. We analyzed the camera-trap data using the R package multimark, which has been extended to include a novel spatial capture-recapture model for encounter histories that include multiple "noninvasive" marks, such as bilaterally asymmetrical left- and right-sided flanks, that can be difficult (or impossible) to reliably match to individuals. Here, we present this model in detail for the first time. Based on a "semi-complete" data likelihood, the model is less computationally demanding than Bayesian alternatives that rely on a data-augmented complete data likelihood. The spatially explicit capture-recapture model estimated a wildcat density (95% credible interval) of 26 (17-36) per 100 km suitable habitat. Our integrated model produced higher abundance and density estimates with improved precision compared to single-sided analyses, suggesting spatially explicit capture-recapture methods with multiple "noninvasive" marks can improve our ability to monitor wildcat population status.
在瑞士，欧洲野猫（一种本土猫科动物）受到国家法律的保护。在最近几十年里，野猫已慢慢回到其大部分原始分布区域，甚至可能已扩张到之前未知的新区域。为了实施有效的保护行动，有关种群数量和密度的现状及趋势的可靠信息至关重要。但到目前为止，瑞士仅在汝拉山脉北部对密度进行过一次可靠估计。野猫相对稀少且难以捉摸，但相机诱捕已被证明是监测猫科动物的有效方法。我们在汝拉山脉北部（伯尔尼州和汝拉州）100平方公里的区域内开发并测试了一种使用相机诱捕的监测方案。在60天内，我们获得了105张具有野猫表型的照片，其中98张适合用于个体识别。我们从两侧识别出了13只个体，此外，还有5个无法与特定个体匹配的右侧单边侧翼和3个无法与特定个体匹配的左侧单边侧翼。我们使用R软件包multimark分析了相机诱捕数据，该软件包已得到扩展，纳入了一种新颖的空间捕获再捕获模型，用于分析包含多个“非侵入性”标记（如左右两侧不对称的侧翼）的遭遇历史记录，这些标记可能难以（或无法）可靠地与个体匹配。在此，我们首次详细介绍该模型。基于“半完整”数据似然性，该模型在计算上比依赖数据扩充完整数据似然性的贝叶斯方法要求更低。空间明确的捕获再捕获模型估计，每100平方公里适宜栖息地的野猫密度（95%可信区间）为26只（17 - 36只）。与单边分析相比，我们的综合模型得出了更高的丰度和密度估计值，且精度有所提高，这表明具有多个“非侵入性”标记的空间明确捕获再捕获方法能够提高我们监测野猫种群状况的能力。
