Prediction of wolf (Canis lupus) kill-sites using hidden Markov models
Prediction of wolf (Canis lupus) kill-sites using hidden Markov models
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DOI：
10.1016/j.ecolmodel.2006.02.043
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发表时间：
2006-08-10
影响因子：
3.1
通讯作者：
Hudson, Robert J.
中科院分区：
文献类型：
--
作者：
Franke, Alastair;Caelli, Terry;Hudson, Robert J.
我们探索隐马尔可夫模型（HMM）作为预测建模技术，并评估模型对常年居住在加拿大艾伯塔省中西部的三只狼群的运动和捕杀现场行为的程度进行评估。尽管 HMM 已成功用于推断个体林地驯鹿的空间使用情况，但它们的行为状态仍然是隐藏的。在我们的研究中，全球定位卫星 (GPS) 无线电项圈使我们能够导出对隐马尔可夫建模技术有意义的数据（位置之间的距离、转动角度和行进速率）。空中重新定位可以确认杀伤地点的位置（发现隐藏的状态）。我们研究的主要目的是评估 HMM 是否可以仅根据 GPS 狼迁移数据预测观察者确认的杀戮地点（正确发现隐藏状态）。 HMM 中固有的马尔可夫结构提供了对狼行为的额外洞察，例如卧铺和重新定位。我们讨论了使用 HMM 来确定野生有蹄类动物种群的捕食率的潜力，并比较捕食不同有蹄类动物物种的群体之间的模型特征。 (c) 2006 Elsevier B.V. 保留所有权利。
We explore hidden Markov models (HMMs) as a predictive modeling technique and assess the degree to which models encapsulate movement and kill-site behavior in three wolf packs that reside year-round in west central Alberta, Canada. Although HMMs have been used successfully to infer use of space by individual woodland caribou, their behavioral states remained hidden. in our study, global positioning satellite (GPS) radio-collars allowed us to derive data (distance-between-locations, turning angle and travel rate) meaningful to hidden Markov modeling techniques. Aerial relocation allowed confirmation of kill-site locations (uncover the hidden states). The primary objective of our study was to evaluate whether HMMs could predict observer-confirmed kill-sites solely from the GPS wolf relocation data (correctly discover the hidden states). The Markov structure inherent in the HMMs provided additional insight into wolf behavior, such as bedding and relocating. We discuss the potential of using HMMs to determine predation rates on populations of wild ungulates and compare model signatures between packs preying on different ungulate species. (c) 2006 Elsevier B.V. All rights reserved.