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Abundance estimation for line transect sampling: A comparison of distance sampling and spatial capture-recapture models

机译:线路横梁采样的丰富估计:距离采样和空间捕获 - 重新捕获模型的比较

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Accurate and precise abundance estimation is vital for informed wildlife conservation and management decision-making. Line transect surveys are a common sampling approach for abundance estimation. Distance sampling is often used to estimate abundance from line transect survey data; however, search encounter spatial capture-recapture can also be used when individuals in the population of interest are identifiable. The search encounter spatial capture-recapture model has rarely been applied, and its performance has not been compared to that of distance sampling. We analyzed simulated datasets to compare the performance of distance sampling and spatial capture-recapture abundance estimators. Additionally, we estimated the abundance of North Atlantic right whales in the southeastern United States with two formulations of each model and compared the estimates. Spatial capture-recapture abundance estimates had lower root mean squared error than distance sampling estimates. Spatial capture-recapture 95% credible intervals for abundance had nominal coverage, i.e., contained the simulating value for abundance in 95% of simulations, whereas distance sampling credible intervals had below nominal coverage. Moreover, North Atlantic right whale abundance estimates from distance sampling models were more sensitive to model specification compared to spatial capture-recapture estimates. When estimating abundance from line transect data, researchers should consider using search encounter spatial capture-recapture when individuals in the population of interest are identifiable, when line transects are surveyed over multiple occasions, when there is imperfect detection of individuals located on the line transect, and when it is safe to assume the population of interest is closed demographically. When line transects are surveyed over multiple occasions, researchers should be aware that individual space use may induce spatial autocorrelation in counts across transects. This is not accounted for in common distance sampling estimators and leads to overly precise abundance estimates.
机译:准确精确的丰富估算对于知情的野生动物保护和管理决策至关重要。线路横断调查是丰富估计的常见采样方法。距离采样通常用于估计线路横断测量数据的丰富;但是,当兴趣群中的个人是可识别的时,也可以使用搜索遇到空间捕获重量。搜索遇到空间捕获 - 重新捕获模型很少应用,并且其性能尚未与距离采样的性能进行比较。我们分析了模拟数据集,以比较距离采样和空间捕获 - 重新捕获丰度估计的性能。此外,我们估计了美国东南部大西洋右鲸的丰富,每种模型的两种配方,并比较估计数。空间捕获 - 重新捕获丰度估计具有比距离采样估计的较低的根均匀误差。空间捕获 - 重新捕获95%的丰富间隔具有标称覆盖率,即,在仿真的95%中包含了丰富的模拟值,而距离采样可信间隔具有低于标称覆盖率。此外,与空间捕获 - 重新捕获估计相比,距离采样模型的北大西洋右鲸丰度估计对模型规范更敏感。当从线路横断数据估计丰度时,研究人员应考虑使用在感兴趣群体中的个体识别时使用搜索遇到空间捕获 - 当在多个场合调查线路横断面时,当线路横断面的个体检测不完美时,当安全就是安全的时候,人口人口在人口统计学上封闭。当多次调查线路横断面时,研究人员应该意识到各个空间使用可能会导致横断面的计数中的空间自相关。这在公共距离采样估计中并未占据,并导致过度精确的丰富估计。

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