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首页> 外文期刊>Journal of King Saud University >Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem
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Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem

机译：应用混合模型减少居住在寒冷沙漠生态系统中的麋鹿（ Cervus elaphus ）的种群估计，减少偏倚并提高其准确性

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Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model M H ), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final estimate and demonstrates why each is necessary.
机译：准确估计野生动植物种群的数量对于野生动植物的管理和物种保护至关重要。原始计数或“最小计数”仍被用作野生动植物管理决策的基础。未校正的原始计数不仅由于无法解释未发现的动物而造成负偏倚，而且也无法提供判断计数效用的精确度估计。我们应用了混合种群估计技术，该技术结合了可见度建模，基于无线电项圈的标记识别和同时双计数（double-observer）建模来估计高海拔沙漠生态系统中麋鹿的种群规模。组合多个模型可以最大程度地发挥每个模型的优势，同时最大程度地减少它们的奇异缺点。我们通过空中直升机调查收集了2005年和2007年美国圣路易斯谷和美国科罗拉多州邻近山区的麋鹿种群的数据。我们提供了7种替代分析的估算值：3种基于获得原始计数的不同方法，而4种基于在不同的统计模型上纠正瞄准概率偏差。这些方法中最可靠的是混合双观察者可见性模型（模型M H），该模型使用直升机中2个独立观察者的检测模式以及基于无线电遥测的麋鹿群的遥测技术。数据适合于具有单个瞄准协变量的自定义标记检查模型。错误估计是通过自举程序获得的。混合方法是对常用替代方法的改进，与可见性建模相比具有更高的精度，而与双观察者建模相比则具有更低的偏差。结果得出的人口估计数已针对多种低估偏向的来源进行了校正，如果不进行校正，这将使实际人口规模低估多达22.9％。我们对这些替代方法的比较证明了我们方法的各个组成部分如何有助于改进最终估算值，并证明了为什么每个组成部分都是必要的。

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