Parlato Elizabeth H, Ewen John G, McCready Mhairi, Parker Kevin A, Armstrong Doug P
Wildlife Ecology Group, Massey University, Private Bag 11-222, Palmerston North, New Zealand.
Institute of Zoology, Zoological Society of London, Regent's Park, London, UK.
Oecologia. 2021 Mar;195(3):627-640. doi: 10.1007/s00442-021-04871-5. Epub 2021 Mar 1.
A key goal of ecological research is to obtain reliable estimates of population demographic rates, abundance and trends. However, a common challenge when studying wildlife populations is imperfect detection or breeding observation, which results in unknown survival status and reproductive output for some individuals. It is important to account for undetected individuals in population models because they contribute to population abundance and dynamics, and can have implications for population management. Promisingly, recent methodological advances provide us with the tools to integrate data from multiple independent sources to gain insights into the unobserved component of populations. We use data from five reintroduced populations of a threatened New Zealand bird, the hihi (Notiomystis cincta), to develop an integrated population modelling framework that allows missing values for survival status, sex and reproductive output to be modelled. Our approach combines parallel matrices of encounter and reproduction histories from marked individuals, as well as counts of unmarked recruits detected at the start of each breeding season. Integrating these multiple data types enabled us to simultaneously model survival and reproduction of detected individuals, undetected individuals and unknown (never detected) individuals to derive parameter estimates and projections based on all available data, thereby improving our understanding of population dynamics and enabling full propagation of uncertainty. The methods presented will be especially useful for management programmes for populations that are intensively monitored but where individuals are still imperfectly detected, as will be the case for most threatened wild populations.
生态学研究的一个关键目标是获得对种群统计率、丰度和趋势的可靠估计。然而，在研究野生动物种群时，一个常见的挑战是检测或繁殖观察不完美，这导致一些个体的生存状况和繁殖产出未知。在种群模型中考虑未被检测到的个体很重要，因为它们对种群丰度和动态有贡献，并且可能对种群管理产生影响。有希望的是，最近的方法进展为我们提供了工具，可整合来自多个独立来源的数据，以深入了解种群中未被观察到的部分。我们使用来自新西兰一种濒危鸟类——吸蜜鸟（Notiomystis cincta）五个重新引入种群的数据，来开发一个综合种群建模框架，该框架允许对生存状况、性别和繁殖产出的缺失值进行建模。我们的方法结合了有标记个体的遭遇和繁殖历史的并行矩阵，以及在每个繁殖季节开始时检测到的无标记新成员数量。整合这些多种数据类型使我们能够同时对已检测到的个体、未检测到的个体以及未知（从未被检测到）个体的生存和繁殖进行建模，从而基于所有可用数据得出参数估计和预测，进而增进我们对种群动态的理解，并实现不确定性的全面传播。所提出的方法对于那些受到密集监测但个体仍未被完美检测到的种群的管理计划将特别有用，大多数受威胁的野生种群情况也是如此。
