Modelling Insect Populations in Agricultural Landscapes
Modelling Insect Populations in Agricultural Landscapes
复制标题
模拟农业景观中的昆虫种群
DOI：
10.1007/978-3-031-43098-5_10
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Mimnagh N
中科院分区：
文献类型：
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作者：
Mimnagh N
估计动物丰度是许多自然资源保护者和种群生态学家感兴趣的领域。在使用计数数据获得丰度估计值时，必须考虑到探测不完善的问题。由Royle提出的N-混合物模型（Biometrics，60（1），108-115，2004）通过将检测概率结合在丰度估计中来提供对该问题的解决方案。我们研究了原始的N-混合模型，并评估其用途，优势和假设。然后，我们研究扩展到这个香草N-混合物模型，允许使用一系列原始模型不支持的数据来估计丰度，包括包含多个动物的观察数据，包含大量零计数的数据和长时间收集的数据。最后，我们说明了原始N混合模型和针对几年来收集的多个物种提出的模型的适用性（Mimnagh等人，环境和生态统计，1-24，2022年），通过从2016年和2019年收集的数据中估计蜜蜂物种的觅食种群，作为英国蜜蜂步行调查的一部分。
Estimating animal abundance is an area of interest for many conservationists and population ecologists. When using count data to obtain abundance estimates, issues of imperfect detection must be taken into account. The N-mixture model proposed by Royle (Biometrics, 60(1), 108–115, 2004) provides a solution to this issue by incorporating detection probability in the estimate of abundance. We examine the original N-mixture model and assess its uses, advantages and assumptions. We then examine extensions to this vanilla N-mixture model which allow for the estimation of abundance using a range of data unsupported by the original model, including data that contain observations of multiple animals, data that contain large numbers of zero-counts and data that are collected over long periods of time. We finish by illustrating the applicability of both the original N-mixture model and a model proposed for multiple species collected over several years (Mimnagh et al., Environmental and Ecological Statistics, 1–24, 2022) by estimating foraging populations for bee species from data collected in 2016 and 2019 as part of the BeeWalk Survey in the UK.