Statistical Ecology @ Kent, National Centre for Statistical Ecology, School of Mathematics, Statistics and Actuarial Science, University of Kent, Canterbury, United Kingdom.
PLoS One. 2021 Mar 4;16(3):e0229965. doi: 10.1371/journal.pone.0229965. eCollection 2021.
Removal models were proposed over 80 years ago as a tool to estimate unknown population size. More recently, they are used as an effective tool for management actions for the control of non desirable species, or for the evaluation of translocation management actions. Although the models have evolved over time, in essence, the protocol for data collection has remained similar: at each sampling occasion attempts are made to capture and remove individuals from the study area. Within this paper we review the literature of removal modelling and highlight the methodological developments for the analysis of removal data, in order to provide a unified resource for ecologists wishing to implement these approaches. Models for removal data have developed to better accommodate important features of the data and we discuss the shift in the required assumptions for the implementation of the models. The relative simplicity of this type of data and associated models mean that the method remains attractive and we discuss the potential future role of this technique.
移除模型早在 80 多年前就被提出,作为一种估计未知种群数量的工具。最近,它们被用作控制非目标物种或评估转移管理措施的有效管理工具。尽管这些模型随着时间的推移而发展,但本质上,数据收集的协议仍然相似:在每次采样时,都会尝试从研究区域捕获并移除个体。在本文中,我们回顾了移除建模的文献,并强调了分析移除数据的方法学发展,以便为希望实施这些方法的生态学家提供一个统一的资源。移除数据的模型已经发展到更好地适应数据的重要特征,我们讨论了实施模型所需假设的转变。这种类型的数据和相关模型相对简单,这意味着该方法仍然具有吸引力,我们讨论了该技术的潜在未来作用。