Eco-evolutionary dynamics of seasonally mobile systems

季节性移动系统的生态进化动力学

• 批准号: NE/Y000684/1
• 负责人: Jane Reid
• 金额: $ 117.44万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FY000684%2F1
• 关键词: Eco; evolutionary; dynamics; seasonally; mobile

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.

许多野生种群现在正在经历环境条件的巨大变化，包括季节性变化以及极端气候事件的频率和严重程度增加。跨越人口和进化生物学的迫切目标是了解生态和进化对此类扰动的反应如何相互作用，从而塑造人口动态和持久性，并进一步了解受影响的人口如何保持应对未来环境变化的能力。确定生态进化动力学的基本原理，这些原理可以在经历动荡环境的复杂野生系统中出现，并最终为有效且面向未来的种群管理策略提供信息。然而，有用的预测目前受到严重阻碍，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，甚至没有被明确概念化。因此，我们的首要目标是提供突破性的概念、分析和经验进展，产生对涉及可变季节性迁徙的生态进化动力学的新理解，从而揭示季节性流动种群如何在面对不断变化和日益极端的季节性环境时适应和持续。季节性迁徙，定义为离散繁殖之间的可逆季节性运动和非繁殖地点，是一种分类学上广泛存在的特征，可以使人们逃离日益恶化的环境并直接塑造时空种群动态。因此，迁徙充当了直接连接表型进化和种群动态的“热线”。然而，尽管存在这些基本联系，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，我们尚无法理解或预测季节性运动可能出现何种形式的快速变化，或者这种变化将如何转化为时空人口动态结果。因此，我们的项目将通过提供以下内容来取得重大进展：1）对复杂的情况的首次估计自然选择的景观作用于空间结构的季节性变化环境中的季节性迁徙（或全年居住）的形式，设定了快速表型变化的潜力。2）对季节性迁徙的定量遗传“进化性”的首次估计，设置时空种群动态快速微观进化的潜力。3）首次推断这种选择景观和定量遗传变异如何结合起来产生生态进化时空动态，并在季节性运动中维持遗传和表型变异在短期和较长的时间范围内。此外，我们将量化极端气候事件可以在多大程度上显着重塑这种选择景观、定量遗传结构和生态进化结果，作为预计气候变化的先兆。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”，以促进根据现场数据对关键微观进化参数进行公正的估计。我们将把这些模型应用于前所未有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鸬鹚种群的个体运动、生存和繁殖。该鸟类领域系统和数据集目前能够支持所提出的前沿分析。因此，我们将提供重大的概念、分析和实证进展，整合目前独立的迁徙生态学和进化定量遗传学领域，为进化注入广泛的新动力生态学，并为人口时空快速变化的潜力提供基本的新见解。