Linking demographic theory and data to forecast the dynamics of spatially-structured seasonally-mobile populations

野生动物正面临前所未有的威胁。许多生境在自然上是不完整的，或因人类活动而支离破碎。许多生境的适宜性也显示出季节性的变化，气候模型预测，极端季节性天气事件（如风暴、干旱、洪水）的频率会增加，这可能导致受影响地区的高死亡率或阻止繁殖。因此，生态学的关键目标是了解和预测居住在空间结构的季节性环境中的种群的动态和持续性，包括改变人口统计学的极端季节性事件的种群反应。时空种群动态最终取决于四个主要的人口统计率：生存，繁殖，扩散（繁殖区之间的永久性运动）和迁移（可逆的季节性运动）。然而，迄今为止，还没有任何经验研究或人口动态理论或模型充分量化或考虑了迁移的时空变化以及生存、扩散和繁殖的变化。因此，我们缺乏数据，理论和模型，量化的变化和所有四个关键的人口率之间的人口动态效应，严重限制了我们的能力，预测动态的空间结构的季节性流动population.It现在很清楚，部分迁移，人口包括居民和移民个人的混合物，是非常常见的性质。部分迁移的人口可能表现出复杂的人口统计学和动态，因为迁移的结构性变化可能导致当前或随后的生存，扩散或繁殖的结构性变化，而极端事件可能导致入侵性迁移。人口动态模型和经验研究如果忽视移徙的时空变化及其所产生的遗留效应，就忽视了人口变化的基本轴。我们将提供新的经验和理论的理解，空间结构的季节性流动人口的人口学和动态，人口动态预测的新能力，通过：1）提供第一个经验估计的关键人口率和关系，驱动人口动态，包括人口对极端事件的反应。我们将使用一个优秀的大规模多年数据集，我们已经收集了一个空间结构的部分迁移欧洲沙格人口。在2009-2017年期间，我们在6个繁殖群中标记了14，500只个体，收集了44，200次冬季目击事件以识别居民和移民，并测量了个体的传播和繁殖。2012-2014年，该系统经历了极端的冬季风暴，造成高死亡率。这个系统现在提供了一个无与伦比的机会来量化个体迁移中的性别，年龄和亚种群特异性变化，以及生存，扩散和繁殖的协变，2）提供新的理论，确定人口动态响应季节性人口变化的一般原则。我们将建立和分析个人，基于模拟模型，量化涉及迁移的人口协变的人口后果。我们将量化人口增长率的敏感性，假设形式的结构化部分迁移和协变与生存，扩散和繁殖不同的生活史和空间栖息地结构，3）为预测时空人口动态提供一个新的灵活的模型框架。我们将在我们的国家-最新的“RangeShifter”软件，用于空间明确的种群动态建模，并模拟欧洲沙格系统的时空动态，从而展示了新的灵活预测能力，并为保护政策提供信息。

Wild populations are facing unprecedented threats. Many habitats are naturally patchy or being fragmented by human activities. Many habitats also show seasonal variation in suitability, and climate models predict increasing frequencies of extreme seasonal weather events (e.g. storms, droughts, floods) that could cause high mortality or prevent reproduction in affected areas. Critical aims in ecology are therefore to understand and forecast the dynamics and persistence of populations inhabiting spatially-structured seasonal environments, including population responses to extreme seasonal events that alter demography.Spatio-temporal population dynamics ultimately depend on four primary demographic rates: survival, reproduction, dispersal (permanent movements among breeding areas) and migration (reversible seasonal movements). However, to date, no empirical studies or population dynamic theory or models have fully quantified or considered spatio-temporal variation in migration alongside variation in survival, dispersal and reproduction. We consequently lack data, theory and models that quantify population dynamic effects of variation in and among all four key demographic rates, severely limiting our ability to forecast the dynamics of spatially-structured seasonally-mobile populations.It is now clear that partial migration, where populations comprise mixtures of resident and migrant individuals, is very common in nature. Partially-migratory populations could show complex demography and dynamics because structured variation in migration could cause structured variation in current or subsequent survival, dispersal or reproduction, while extreme events could cause irruptive migration. Population dynamic models and empirical studies that ignore spatio-temporal variation in migration, and resulting carry-over effects, therefore ignore fundamental axes of demographic variation. We will provide new empirical and theoretical understanding of the demography and dynamics of spatially-structured seasonally-mobile populations, and new capability for population dynamic forecasting, by:1) Providing first empirical estimates of key demographic rates and relationships that drive population dynamics, including demographic responses to extreme events.We will use an outstanding large-scale multi-year dataset that we have collected on a spatially-structured partially-migratory European shag population. During 2009-2017 we marked 14,500 individuals across 6 breeding colonies, collected 44,200 winter sightings to identify residents and migrants, and measured individual dispersal and reproduction. In 2012-2014, the system experienced extreme winter storms, causing high mortality. This system now provides an unrivalled opportunity to quantify sex-, age- and sub-population-specific variation in individual migration, and covariation with survival, dispersal and reproduction, before, during and after natural extreme seasonal events.2) Providing new theory that identifies general principles of population dynamic responses to seasonal demographic variation.We will build and analyse individual-based simulation models that quantify population consequences of demographic covariation involving migration. We will quantify sensitivities of population growth rate to hypothesised forms of structured partial migration and covariation with survival, dispersal and reproduction given varying life-histories and spatial habitat structures, and to hypothesised regimes of extreme events and resulting demographic perturbations.3) Providing a new flexible modelling framework for forecasting spatio-temporal population dynamics.We will build new migration models into our state-of-the-art 'RangeShifter' software for spatially-explicit population dynamic modelling and simulate spatio-temporal dynamics of the exemplar European shag system, thereby demonstrating new flexible forecasting capability and informing conservation policy.