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是否存在单一的最佳估计值?使用曲线下面积选择栖息地范围估计值。

Is there a single best estimator? Selection of home range estimators using area-under-the-curve.

机构信息

U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, 403 Forest Resources Building, University Park, PA 16802 USA.

Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, 298 Sabal Palm Road, Naples, FL 34114 USA.

出版信息

Mov Ecol. 2015 Apr 16;3(1):10. doi: 10.1186/s40462-015-0039-4. eCollection 2015.

Abstract

BACKGROUND

Global positioning system (GPS) technology for monitoring home range and movements of wildlife has resulted in prohibitively large sample sizes of locations for traditional estimators of home range. We used area-under-the-curve to explore the fit of 8 estimators of home range to data collected with both GPS and concurrent very high frequency (VHF) technology on a terrestrial mammal, the Florida panther Puma concolor coryi, to evaluate recently developed and traditional estimators.

RESULTS

Area-under-the-curve was the highest for Florida panthers equipped with Global Positioning System (GPS) technology compared to VHF technology. For our study animal, estimators of home range that incorporated a temporal component to estimation performed better than traditional first- and second-generation estimators.

CONCLUSIONS

Comparisons of fit of home range contours with locations collected would suggest that use of VHF technology is not as accurate as GPS technology to estimate size of home range for large mammals. Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used. Furthermore, estimators that incorporate a temporal component (third-generation estimators) appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used and in comparison to first- and second-generation estimators. We defined third-generation estimators of home range as any estimator that incorporates time, space, animal-specific parameters, and habitat. Such estimators would include movement-based kernel density, Brownian bridge movement models, and dynamic Brownian bridge movement models among others that have yet to be evaluated.

摘要

背景

全球定位系统(GPS)技术可用于监测野生动物的栖息地范围和活动,这导致传统栖息地范围估计方法所需的位置样本数量过大。我们使用曲线下面积来探索 8 种栖息地范围估计方法在陆地哺乳动物佛罗里达美洲狮 Puma concolor coryi 上的 GPS 和同时使用的甚高频(VHF)技术收集的数据中的拟合情况,以评估最近开发的和传统的估计方法。

结果

与 VHF 技术相比,配备 GPS 技术的佛罗里达美洲狮的曲线下面积最高。对于我们的研究动物,将时间因素纳入估计的栖息地范围估计方法比传统的第一代和第二代估计方法表现更好。

结论

与收集的位置相比,对栖息地范围轮廓的拟合度进行比较表明,使用 VHF 技术来估计大型哺乳动物的栖息地范围不如 GPS 技术准确。无论使用哪种估计方法,使用 GPS 技术收集的栖息地范围估计值都比使用 VHF 技术收集的估计值要好。此外,无论使用基于核的算法还是基于布朗桥的算法,以及与第一代和第二代估计方法相比,纳入时间因素的估计方法(第三代估计方法)似乎更可靠。我们将第三代栖息地范围估计方法定义为任何纳入时间、空间、动物特定参数和栖息地的估计方法。这类估计方法将包括基于运动的核密度估计方法、布朗桥运动模型和动态布朗桥运动模型等,其中许多方法尚未得到评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b33a/4429481/b8e972c6524b/40462_2015_39_Fig1_HTML.jpg

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