Eco-evolutionary dynamics of seasonally mobile systems

许多野生种群现在正在经历环境条件的戏剧性变化，包括季节性的变化以及极端气候事件的频率和严重性的增加。跨越种群和进化生物学的迫切雄心是了解生态和进化对这种扰动的反应如何相互作用来塑造种群动态和持久性，并进一步了解受影响的种群如何保持对未来环境变化的反应能力。这些进展是确定在经历动荡环境的复杂野生系统中可能出现的生态进化动力学的基本原理，并最终提供有效的和面向未来的种群管理策略所必需的。然而，有用的预测目前严重受阻，因为野生种群中可能出现的生态进化动态的关键组成部分从未被量化，甚至从未被明确地概念化。因此，我们的首要目标是提供开创性的概念、分析和经验进展，以产生对涉及可变季节性迁徙的生态进化动态的新理解，从而揭示季节性流动种群如何适应并持续面对不断变化和日益极端的季节性环境。季节迁徙，定义为离散繁殖和非繁殖地点之间的可逆季节性移动，是分类学上普遍存在的特征，允许空间逃脱不断恶化的环境，并直接塑造空间-季节种群动态。因此，迁徙是一条直接将表型进化和种群动态联系起来的“热线”。然而，尽管有这样的基本联系，涉及季节性迁徙的生态进化动态的关键组成部分从未在野生种群中得到量化。因此，我们还不能理解或预测季节性迁徙中可能出现什么形式的快速变化，或者这种变化将如何转化为空间-季节性人口动态结果。因此，我们的项目将通过以下方式取得重大进展：1)首次估计作用于空间结构季节性变化环境中的季节性迁徙形式(或全年居住)的复杂的自然选择景观，设定快速表型变化的可能性。2)首次估计季节性迁徙的数量遗传进化能力，3)首先推断这种选择景观和数量遗传变异如何结合在一起，产生生态进化的空间-季节动态，并在短时间和更长时间内维持季节性运动的遗传和表型变化。此外，我们将量化极端气候事件对这种选择景观、数量遗传结构和生态进化结果的显著重塑程度，作为预测气候变化的先兆。我们将通过设计先进的统计模型来实现这些目标，包括多状态定量遗传‘动物模型’，以促进从野外数据中对关键的微观进化参数进行无偏见的估计。我们将把这些模型应用于一个史无前例的大规模多年全年度周期数据集，该数据集涉及受气候威胁的部分迁徙的欧洲粪便的个体迁徙、存活和繁殖。这个鸟类野外系统和数据集目前是唯一能够支持拟议的前沿分析的。因此，我们将提供重大的概念、分析和经验进展，整合目前独立的迁徙生态学和进化数量遗传学领域，为进化生态学注入广泛的新动力，并为快速空间-季节种群变化的潜力提供基本的新见解。

Many wild populations are now experiencing dramatic changes in environmental conditions, including changing seasonalities and increasing frequencies and severities of extreme climatic events. Urgent ambitions spanning population and evolutionary biology are to understand how ecological and evolutionary responses to such perturbations can interact to shape population dynamics and persistence and, further, to understand how impacted populations can retain capacity to respond to future environmental changes.Such advances are required to identify fundamental principles of eco-evolutionary dynamics that can emerge in complex wild systems experiencing turbulent environments and, ultimately, to inform effective and future-proof population management strategies. Yet, useful prediction is currently severely impeded because key components of eco-evolutionary dynamics that could arise in wild populations have never been quantified, or even explicitly conceptualised.Hence, our overarching objective is to provide ground-breaking conceptual, analytical and empirical advances that generate new understanding of eco-evolutionary dynamics involving variable seasonal migration, thereby revealing how seasonally mobile populations could adapt and persist in the face of changing and increasingly extreme seasonal environments.Seasonal migration, defined as reversible seasonal movements between discrete breeding and non-breeding locations, is a taxonomically widespread trait that allows spatial escape from deteriorating environments and directly shapes spatio-seasonal population dynamics. Migration therefore acts as a 'hotline' that directly links phenotypic evolution and population dynamics. Yet, despite such fundamental links, key components of eco-evolutionary dynamics involving seasonal migration have never been quantified in wild populations. Consequently, we cannot yet understand or predict what forms of rapid changes in seasonal movements could arise, or how such changes will translate into spatio-seasonal population dynamic outcomes.Accordingly, our project will achieve major advances by providing:1) First estimates of complex landscapes of natural selection acting on forms of seasonal migration (or year-round residence) in spatially-structured seasonally-varying environments, setting the potential for rapid phenotypic change.2) First estimates of quantitative genetic 'evolvabilities' of seasonal migration, setting the potential for rapid micro-evolution of spatio-seasonal population dynamics.3) First inferences on how such landscapes of selection and quantitative genetic variation can combine to generate eco-evolutionary spatio-seasonal dynamics, and also maintain genetic and phenotypic variation in seasonal movement over short and longer timeframes.Further, we will quantify to what degree such selection landscapes, quantitative genetic architectures and eco-evolutionary outcomes can be dramatically reshaped by extreme climatic events, acting as harbingers of projected climate change.We will achieve these objectives by devising advanced statistical models, including multi-state quantitative genetic 'animal models', that facilitate unbiased estimation of key micro-evolutionary parameters from field data. We will apply these models to an unprecedented large-scale multi-year full-annual-cycle dataset on individual movements, survival and reproduction from a climate-threatened partially-migratory meta-population of European shags. This bird field system and dataset is currently uniquely able to support the proposed cutting-edge analyses.We will thereby provide major conceptual, analytical and empirical advances that integrate the currently separate fields of migration ecology and evolutionary quantitative genetics, injecting wide new impetus in evolutionary ecology, and providing fundamental new insights into the potential for rapid spatio-seasonal population change.