Explaining and Predicting the Migration and Phenology of Europe-African Migratory Birds

鸟类从温带和北极繁殖地迁徙到较低纬度的非繁殖季节是一项重大的全球野生动物活动，涉及数十亿只鸟类，是全球生态系统的重要组成部分。其中一些动作真的很令人惊叹--大约12克的鸟不停地飞行3000公里，到达它们的非繁殖地。大多数洲际陆地迁徙是由鸣鸟进行的，它们跨越广阔的战线迁徙，经常在旅途中停下来加油。尽管对繁殖地以及非繁殖地和中途停留地进行了深入的研究，但模拟迁徙过程本身或测试此类物种迁徙的理论模型的研究很少。一般的迁徙模式从未适用于进行欧洲-撒哈拉以南迁徙的鸣禽；这是本提案的一个主要目标。根据对这些物种繁殖、非繁殖和中途停留地的气候和土地利用变化的预测，迫切需要这样的模型。候鸟可能特别容易受到气候变化的影响，因为他们依赖于相距遥远的地区之间的联系，这些地区可能正在经历非常不同的变化。开发和测试鸣鸟迁徙模型的主要限制是无法监测个体的行动，以了解它们的路线和策略。地理定位器追踪器最近的发展，记录了时间和位置，并可用于构成大多数迁徙的较小物种，首次为测试迁徙模型提供了数据。在这里，我们将整理跨撒哈拉移民的跟踪、广泛的振铃和观察数据，以更好地了解他们的移民路线和决定。同时，我们将为单个物种开发飞行模型，该模型考虑物种特定的生理和形态，以确定它们的飞行范围潜力。我们将在空间显式动态规划(DP)模型中使用输出，并将测试它们复制观察到的迁移模式的能力。这将建立在使用非常简单的系统对最佳迁移进行建模的早期工作的基础上。我们已经开发了飞行员飞行范围模型，很好地复制了被跟踪的近线性迁徙物种个体的迁徙时间和路线。在这些数据的基础上，我们将使用DP模型，结合现实的景观资源/成本，在给定临时限制的目的地回报(即可能的繁殖成功)的情况下，评估最优的迁徙路线和加油位置。我们将根据物种特定的栖息地偏好和可能的食物可获得性(基于天气和NDVI)等因素，考虑具有动态资源可获得性的景观，并将包括风向、位置(相对于一年中的时间)和个人的能源储备等因素，以确定它们是否应该留下来，如果不是，它们应该转移到哪里。我们将使用这些模型来探索迁徙终点到达日期的年际变化，以帮助理解是什么驱动了迁徙物种的物候变化，并测试了决定迁徙决定的理论。建模使我们对迁徙的理解正式化，明确了我们的假设和现有数据中的任何差距。至关重要的是，它还可以让我们了解移民过程，以及未来环境变化将如何影响这一过程。最终成果将是更好地了解长途移民路线和战略的驱动因素，以及一个可应用于不同地区或在气候和土地利用变化情景下的广泛移民路线的建模框架，以模拟移民旅程的后果。

The migration of birds from temperate and arctic breeding grounds to lower latitudes for the non-breeding season is a major global wildlife event, comprising billions of birds and providing an important component of global ecosystems. Some of these movements are truly amazing - some 12 gram birds fly 3000km non-stop to reach their non-breeding grounds. The majority of inter-continental terrestrial migrations are undertaken by songbirds, which migrate across broad fronts, often stopping to refuel on their journey. Despite intensive study on the breeding grounds, and to a lesser extent the non-breeding grounds and stop-over sites, research to simulate the migratory journeys themselves, or to test theoretic models of migration for such species, is rare. A generic model of migration has never been applied to songbirds undertaking the Europe- trans-Saharan migration; this is a major objective of this proposal. In light of projections of climate and land-use changes on the breeding, non-breeding and stop-over grounds of these species, such models are urgently required. Migrants could be especially vulnerable to climate change given their reliance on the linkage between widely-separated areas, which are potentially undergoing very different changes.The main limitation to developing and testing models of songbird migration has been an inability to monitor individual movements so as to understand their routes and strategies. The recent development of geolocator trackers, which record time and location and can be used on the smaller species that comprise the majority of migrants, has provided data to test migration models for the first time. Here, we will collate tracking, and extensive ringing and observation data for trans-Saharan migrants, to better understand their migratory routes and decisions. Simultaneously, we will develop flight models for individual species, which consider species-specific physiology and form to determine their flight-range potential. We will use the outputs in spatially-explicit dynamic programming (DP) models, and will test their ability to replicate observed patterns of migration. This will build on earlier work modelling optimal migration using very simple systems. We have already developed pilot flight range models that replicate well the timing and routes of migration of tracked individuals of species with near-linear migrations. Building on these data, we will use DP models, with realistic landscape resources/costs, to evaluate optimal migratory routes and refuelling locations given temporally-constrained destination rewards (i.e., likely breeding success). We will consider landscapes with dynamic resource availability, based on factors such as species-specific habitat preferences and likely food availability (based on weather and NDVI), and will include factors such as wind direction, location (relative to time of year) and an individual's energy stores to determine whether they should stay or, if not, where they should move to. We will use these models to explore inter-annual variation in arrival dates at migratory end-points, to aid understanding of what drives phenological changes in migratory species, and to test theories of what determines migratory decisions.Modelling formalises our understanding of migration, making explicit our assumptions and any gaps in available data. Crucially, it can also inform our understanding of the migratory process and how that process will be influenced by future environmental changes. The end product will be a much better understanding of the drivers of the routes and strategies of long-distance migrants, and a modelling framework that can be applied to a wide suite of migratory passerines in different regions, or under scenarios of climate and land-use change, to simulate consequences for migratory journeys.