Modeling Avian Responses to Climate Change using Evolving Occurrence Models

鸟类的分布受环境因素的限制。不同的物种有不同的环境条件范围。鸟类受限制的一些条件会随着气候变化而改变。事实上，一些物种已经将它们的活动范围向两极或更高的海拔转移。研究人员使用统计模型将空间环境数据与鸟类物种的发生联系起来。然后，他们改变数据，以反映未来可能出现的情况，并使用模型来预测鸟类物种将如何改变其分布。这种方法受到了批评，因为它忽略了物种之间的相互作用，物种可以适应新的环境，一些物种比其他物种更善于分散。本项目将采用一种避免这些限制的新方法。统计模型将用于预测美国各地鸟类的出现和相对丰度，这些模型建立在对鸟类出现情况的长期调查和一套空间数据的基础上。然后，这些模型将被纳入使用基于主体的框架的模拟模型中，其中主体是占据一小部分景观的单个物种的一组鸟类。描述鸟类分布方式的模型将被允许根据可用的环境和其他物种的存在而进化。例如，当一个物种进入新的环境时，它的温度范围可能会发生微小的变化。然后将对模拟模型进行调整，直到鸟类的分布与真实的、当前的分布相似。最后，反映气候变化影响的响应面将取代代表当前条件的响应面，模拟将继续进行。考虑到物种之间的相互作用和物种自身的适应能力，鸟类物种的分布将因此而进化，结果将反映鸟类分布和群落在未来气候下可能发生的变化。在物种如何分布的研究中，代表个体如何应对不断变化的环境条件的模型是罕见的。这里使用的方法有可能解决各种各样的问题，并使分析动态，在计算机模拟过程中，物种分布的模式随着时间的推移而发展。这项工作将支持博士候选人与一个新的团队合作，使用新的数据集，并学习新的研究技能。研究结果将用于大学课程和研讨会，并用于培训高中生。研究结果将发表在期刊文章中，并在项目网站上进行总结。

The distributions of bird species are limited by factors of the environment. Different species have different ranges of environmental conditions that they tolerate. Some of the conditions that birds are constrained by will shift as climate changes. In fact, some species are already shifting their ranges toward the poles or to higher elevations. Researchers have used statistical models to relate spatial environmental data and the occurrence of bird species. They then change the data to reflect the way conditions may appear in the future and use the models to predict the ways in which bird species will shift their distributions as a result. This approach has been criticized because it ignores the interactions between species, that species can adapt to new environments, and that some species are better at dispersing than others. A new method that avoids these limitations will be used in this project. Statistical models will be used to predict the occurrence and relative abundance of birds across the United States that build on a long running survey of bird occurrences along with a suite of spatial data. The models will then be incorporated into a simulation model using an agent-based framework, where agents are the group of birds of an individual species that occupy a small part of the landscape. The models that describe the ways in which birds are distributed will be allowed to evolve in response to the environments available and the presence of other species. For example, small changes in the temperature range of a species may occur as it moves into new landscapes. Adjustments will then be made to the simulation model until the distribution of birds is similar to their real, current distributions. Finally, response surfaces that reflect climate change effects will replace those that represent current conditions and the simulations will be continued. The distributions of bird species will thus evolve in response to the new conditions and the results will reflect how bird distributions and communities may change under a future climate, considering interactions between species and the ability of the species themselves to adapt.Models that represent how individuals respond to changing environmental conditions are rare in studies of how species are distributed. The method used here has the potential to address a variety of questions and to make analyses dynamic, with patterns of species distributions developing over time during the computer simulations. The effort will support a PhD candidate who will work with a new team, with new data sets, and learn new research skills. The results will be used in university courses and workshops and to train high school students. Results will be published in journal articles and summarized on a project web site.