The impact of interacting processes on population dynamics.

为了广泛的应用（害虫控制、疾病爆发、收获策略）和根本原因（气候变化），生态学家不仅需要了解是什么决定了物种的丰度，还需要了解丰度是如何随时间变化的，以及为什么这些模式在一个地方到另一个地方不同。人们已经投入了相当大的努力来探索这个问题，特别是在动力学不稳定的物种中，但我们现在只有在少数情况下才对主要机制有了深入的了解。这些研究倾向于关注单一生物因素的作用，如捕食或寄生，一些研究也考虑了生物过程与气候之间的相互作用。然而，我们知道种群是由各种生物过程控制的，这些过程通常相互作用。因此，一个主要的挑战，也是这个提议的总体目标，是量化生物因素之间的相互作用，以及它们的气候环境对人口动态的影响。我们将研究红松鸡，这是英国高地上的一种物种，其种群通常表现出循环动态。松鸡种群动态在不同地区间存在较大差异，有些种群不具有周期性，强周期性种群的周期在4 ~ 12年之间。这个研究系统及其内部的变化为我们提供了一个极好的机会来量化生物过程之间相互作用的影响。松鸡已经得到了很好的研究，因此我们可以识别和操纵两种主要的生物过程：寄生和领土行为。此外，我们还知道领土行为和寄生虫强度相互影响。然而，我们不知道非生物因素如何影响这些相互作用，以及相互作用如何反过来影响个体适应度和涌现动力学。我们的具体目的是验证我们在松鸡循环动力学中观察到的空间变化是寄生虫和领土行为在降雨梯度内相互作用的结果的假设。为了实现这一目标，我们与两位精通动态博弈论和人口模型的理论家合作，建立了一个成功的经验主义者团队。与这个团队一起，我们将通过实验、建模和测试长期时间序列的预测来检验我们的假设。我们将进行两个实验，这将告诉我们a)寄生虫强度如何随领土行为而变化，反之亦然；b)这些相互作用如何影响跨环境梯度的繁殖成功和生存；c)雌雄松鸡之间的传播率。将以前的模型和数据结合起来，有必要对两性之间的传播进行量化。考虑到更具攻击性的松鸡会捡到更多的寄生虫，我们将使用博弈论来探索这种相互作用的含义，即雄性个体应该在领土行为上投入多少。通过实验和博弈论的输入，策略决策的种群动态后果将通过种群模型进行研究。对于在给定降雨量的地区的松鸡种群，种群模型将预测出预期的周期模式。我们将把这些预测与全国管理松鸡沼地的长期收获记录进行对比。我们的研究结果将突出生物因素之间的相互作用在种群动态中所起的作用。这是一个重要的问题，因为它将帮助我们了解气候变化和管理将如何相互作用，影响丰度和动态。在英国，就我们目前的知识和在部分高地观察到的戏剧性生态变化而言，这些研究都是及时的。

For a wide range of applied (pest control, disease outbreak, harvesting strategies) and fundamental reasons (climate change) ecologists need to understand not only what determines the abundance of a species but also how abundance varies over time and why these patterns differ from one location to another. Considerable effort has been devoted to exploring this issue, especially in species with unstable dynamics but in only a few instances do we now have the insight into the major mechanisms. These studies have tended to focus attention on the role of single biotic factors, such as predation or parasitism, and some studies have also considered the interaction between a biotic process and climate. Yet we know that populations are governed by a variety of biotic processes and that these commonly interact. So, a major challenge, and the overall aim of this proposal, is to quantify the impact of interactions between biotic factors in relation to their climatic context on population dynamics. We will work on the red grouse, a species in the British uplands whose populations commonly show cyclic dynamics. There is considerable variation in grouse population dynamics between areas, with some populations not cyclic, and the cycle period of the strongly cyclic populations varying from 4 to 12 years. This study system and the variation within it provides us with an excellent opportunity to quantify the impact of interactions between biotic processes. Grouse have been well studied, so we can identify and manipulate the two dominant biotic processes: parasitism and territorial behaviour. Moreover, we also know that territorial behaviour and parasite intensity affect each other. However, we do not know how abiotic factors affect these interactions and how the interactions in turn affect individual fitness and emergent dynamics. Our specific aim is to test the hypothesis that the spatial variation we observe in the cyclic dynamics of grouse is the result of parasites and territorial behaviour interacting within a gradient of rainfall. To achieve this aim we have built on a successful team of empiricists by collaborating with two theoreticians, skilled in dynamic game theory and population modelling. With this team we will test our hypothesis through experimentation, modelling and testing predictions on long-term time series. We will conduct two experiments that will tell us a) how parasite intensity varies with territorial behaviour and vice-versa, b) how these interactions influence breeding success and survival across an environmental gradient; and c) what the transmission rate is between male and female grouse within pairs. A quantification of transmission between sexes is necessary to combine previous models and data. Given that more aggressive grouse pickup more parasites, we will use game theory to explore the implications of this interaction for how much individual males should invest in territorial behaviour. With input from the experiments and game theory, the population dynamic consequences of the strategy decisions will be investigated through population models. For grouse populations in locations with given values of rainfall the population models will predict what cyclic patterns would be expected. We will the test these predictions against the long-term time series of harvest records available from managed grouse moorlands across the country. Our findings will highlight the role played by interactions between biotic factors on population dynamics. This is an important issue, as it will help us understand how climate change and management will interact to influence abundance and dynamics. In Britain, these studies are both timely with respect to our current knowledge and the dramatic ecological changes being observed in parts of the uplands.