School of Conservation Sciences, Bournemouth University, Talbot Campus, Poole, Dorset, BH12 5BB, UK.
Biol Rev Camb Philos Soc. 2010 Aug;85(3):413-34. doi: 10.1111/j.1469-185X.2009.00106.x. Epub 2009 Nov 24.
Conservation objectives for non-breeding coastal birds (shorebirds and wildfowl) are determined from their population size at coastal sites. To advise coastal managers, models must predict quantitatively the effects of environmental change on population size or the demographic rates (mortality and reproduction) that determine it. As habitat association models and depletion models are not able to do this, we developed an approach that has produced such predictions thereby enabling policy makers to make evidence-based decisions. Our conceptual framework is individual-based ecology, in which populations are viewed as having properties (e.g. size) that arise from the traits (e.g. behaviour, physiology) and interactions of their constituent individuals. The link between individuals and populations is made through individual-based models (IBMs) that follow the fitness-maximising decisions of individuals and predict population-level consequences (e.g. mortality rate) from the fates of these individuals. Our first IBM was for oystercatchers Haematopus ostralegus and accurately predicted their density-dependent mortality. Subsequently, IBMs were developed for several shorebird and wildfowl species at several European sites, and were shown to predict accurately overwinter mortality, and the foraging behaviour from which predictions are derived. They have been used to predict the effect on survival in coastal birds of sea level rise, habitat loss, wind farm development, shellfishing and human disturbance. This review emphasises the wider applicability of the approach, and identifies other systems to which it could be applied. We view the IBM approach as a very useful contribution to the general problem of how to advance ecology to the point where we can routinely make meaningful predictions of how populations respond to environmental change.
非繁殖期沿海鸟类(涉禽和水禽)的保护目标是根据其在沿海地点的种群规模确定的。为了向沿海管理人员提供建议,模型必须定量预测环境变化对种群规模或决定种群规模的人口统计率(死亡率和繁殖力)的影响。由于栖息地关联模型和消耗模型无法做到这一点,我们开发了一种方法,该方法能够进行此类预测,从而使决策者能够做出基于证据的决策。我们的概念框架是基于个体的生态学,其中种群被视为具有由其组成个体的特征(例如行为、生理学)和相互作用产生的属性(例如大小)。个体与种群之间的联系是通过遵循个体的最大适应度决策并从这些个体的命运中预测种群水平的结果(例如死亡率)的基于个体的模型(IBMs)建立的。我们的第一个 IBM 是针对蛎鹬 Haematopus ostralegus,并准确地预测了其密度依赖性死亡率。随后,在几个欧洲地点为几种涉禽和水禽物种开发了 IBM,并证明它们可以准确地预测越冬死亡率以及由此得出的觅食行为。它们已被用于预测海平面上升、栖息地丧失、风力发电场开发、贝类养殖和人为干扰对沿海鸟类生存的影响。这篇综述强调了该方法的更广泛适用性,并确定了其他可以应用该方法的系统。我们认为 IBM 方法是对如何将生态学推进到我们可以常规地对种群如何对环境变化做出响应做出有意义的预测这一一般性问题的非常有用的贡献。