Complex Effects of Landscape Modification on Plant Functional Connectivity

加拿大自然资源的可持续管理受到人类景观改变和气候变化的危害，这以多种复杂的方式影响物种。在植物中，残留栖息地斑块中的小型孤立种群可能会遭受局部灭绝的风险增加，减少克隆化的机会，遗传多样性的损失，从而适应气候变化的潜力，以及由于近亲繁殖而降低的适应性。人类改变景观的这些后果在很大程度上取决于种子和花粉在景观中的传播情况。许多植物依赖于不同的载体（例如，风、鸟类、哺乳动物或昆虫）进行授粉和种子传播，因此，生境斑块之间个体及其基因的交换（功能连通性）取决于传播媒介与干扰景观（基质抗性）的相互作用，而这在花粉和种子之间可能有所不同。为了解决这些问题，我的实验室将利用一项为期20年的景观改造实验，旨在通过轮流放牧将废弃的斑块与完整的草原重新连接起来，恢复石灰质草原的功能连通性。 我们将结合联合收割机的生态和遗传数据，梳理除了景观对动物介导的种子和花粉传播的保护关注的物种。我们将使用计算机模拟实验来评估花粉和种子传播过程的景观决定因素，并模拟景观改造对种群持久性和种群遗传结构的级联效应。最后，我们将整合生态和人口遗传数据分析方法在一个新的“空间成分回归”的框架，允许联合统计建模和测试的假设多个过程，有助于空间模式的数据。总的来说，新的统计方法将提供急需的集成和发展的方法，适合景观遗传数据的复杂性。这些研究项目将培养六名研究生和五名本科生的技能，包括国际实地考察，分子遗传分析，统计建模，空间分析和计算机模拟建模。

Sustainable management of Canada's natural resources is jeopardized by human landscape alteration and climate change, which affect species in multiple and complex ways. In plants, small isolated populations in remnant habitat patches may suffer from increased risk of local extinction, reduced chance of recolonization, loss of genetic diversity and thus potential for adaptation to climate change, and reduced fitness due to inbreeding. These consequences of human landscape alteration depend largely on how well seeds and pollen move across the landscape. Many plants rely on different vectors (e.g., wind, birds, mammals, or insects) for pollination and seed dispersal, so that the exchange of individuals and their genes between habitat patches (functional connectivity) depends on the interaction of the dispersal vectors with the intervening landscape (matrix resistance), which may differ between pollen and seeds. To address these issues, my lab will capitalize on a 20-year landscape modification experiment aimed at restoring functional connectivity of calcareous grasslands by reconnecting abandoned patches with intact grasslands through rotational shepherding. We will combine ecological and genetic data to tease apart landscape effects on animal-mediated seed and pollen dispersal in a species of conservation concern. We will use computer simulation experiments to assess landscape determinants of pollen and seed dispersal processes and to simulate the cascading effects of landscape modification on population persistence and population genetic structure. Finally, we will integrate ecological and population genetic data analysis methods in a novel 'spatial component regression' framework that allows the joint statistical modeling and testing of hypotheses about multiple processes that contribute to spatial patterns in the data. Overall, the novel statistical approach will provide much needed integration and development of methods suitable for the complexity of landscape genetic data. These research projects will train six graduate students and five undergraduate students in skills including international fieldwork, molecular genetic analysis, statistical modeling, spatial analysis, and computer simulation modeling.