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经历着环境条件的巨大变化，包括季节性的变化以及极端气候事件的频率和严重程度的增加。跨越种群和进化生物学的紧迫目标是了解生态和进化对这种扰动的反应如何相互作用，以塑造种群动态和持久性，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。这些进展需要确定生态的基本原则，进化动力学可以在经历动荡环境的复杂野生系统中出现，并最终为有效和面向未来的种群管理策略提供信息。然而，有用的预测目前严重阻碍，因为生态进化动力学的关键组成部分，可能出现在野生种群从来没有被量化，甚至明确conceptualised.因此，我们的总体目标是提供突破性的概念，分析和实证的进展，产生新的理解生态进化动力学涉及变量季节性迁移，从而揭示了季节性移动的种群如何在不断变化和日益极端的季节性环境中适应和持续存在。季节性迁移，定义为离散繁殖和非繁殖地点之间的可逆季节性迁移，是一个分类学上广泛的特点，允许空间逃离恶化的环境，并直接形状的空间-季节性人口动态。因此，迁移充当了直接联系表型进化和种群动态的“热线”。然而，尽管有这些基本的联系，涉及季节性迁徙的生态进化动力学的关键组成部分从来没有在野生种群中被量化。因此，我们还不能理解或预测季节性流动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，我们的项目将通过提供以下方面取得重大进展：1）自然选择作用于季节性迁移形式的复杂景观的初步估计（或全年居住）在空间结构的季节性变化的环境，设置快速表型变化的潜力。2）季节性迁移的定量遗传“进化”的第一次估计，3）首次推断这种选择景观和数量遗传变异如何联合收割机产生生态进化的空间-季节动态，并在短期和长期的时间框架内保持季节运动中的遗传和表型变异。进一步，我们将量化这种选择景观的程度，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”，这些模型有助于从实地数据中无偏地估计关键的微观进化参数。我们将把这些模型应用到一个前所未有的大规模多年全年周期数据集上，这个数据集是关于受气候威胁的部分迁徙的欧洲沙格人的个体运动、生存和繁殖的。这个鸟场系统和数据集目前是唯一能够支持拟议的尖端分析。我们将提供重大的概念，分析和经验的进展，整合目前独立的领域的迁移生态学和进化数量遗传学，注入广泛的新动力进化生态学，并提供基本的新见解的潜力，快速的空间-季节性人口变化。