Stochastic Modeling for Geographic Diversity of Plant Species Richness in South Africa

0089801. 约翰·西兰德 这个提议解决了生物学中两个长期存在的、基本的、相互关联的问题：（1）决定物种分布的环境因素是什么？（2）导致物种丰富度空间变异的生态和地理机制是什么？ 为了回答这些问题，拟议中的研究利用了一个有据可查的数据库，该数据库涉及来自南非开普敦植物王国的物种丰富的Protea植物群，这是一个全球生物多样性热点。 PI将分布式数据集成到地理信息系统（GIS）中，然后从两个定量角度分析它们，包括分层或贝叶斯模型以及基于元胞自动机和模拟的混合模型。 建模将是广泛的，包括环境变量，物种属性（包括系统发育关系），明确的空间位置（而不仅仅是范围）和种群动态（例如，出生、死亡和迁移的生命率）以及进化特征（例如，物种形成）。 完整的分析方案将包括模型构建、验证和比较。 建模将有助于从机制上理解和预测特定物种将在哪里出现，以及这种物种特异性机制如何产生更广泛的物种丰富度模式。

0089801. John Silander. This proposal addresses two long-standing, fundamental, and interrelated questions in biology: (1) what are the environmental factors that determine the distribution of species, and (2) what are the ecological and biogeographic mechanisms that cause spatial variation in species richness? To answer these questions, the proposed research takes advantage of a well-documented database concerning the species-rich Protea flora from the Cape Floristic Kingdom of South Africa, a global hot spot of biodiversity. The PIs will integrate distributional data into a geographic information system (GIS), and subsequently analyze them from two quantitative perspectives, including hierarchical or Bayesian models and hybrid models based on cellular automata and simulation. Modeling will be expansive and include considerations of environmental variables, species attributes (including phylogenetic relationships), explicit spatial location (not simply ranges), and population dynamic (e.g., vital rates of birth, death, and migration) as well as evolutionary characteristics (e.g., speciation) of taxa. The full analytical protocol will include model construction, validation, and comparison. Modeling will facilitate a mechanistic understanding and the prediction of where a particular species will occur, and how such species-specific mechanisms give rise to broader-scale patterns of species richness.