Dissertation Research: Modeling the Consequences of Heterogeneous Light Environments for Seedling Perfomance in Tropical Wet Forests: A Multi-Scale Approach

这一建议解决了建立幼苗对环境异质性变化模式响应的预测模型的迫切需要。pi建议开发全植物碳增益的机制模型，该模型将与热带森林环境中与光异质性相关的植物性能研究相结合。pi将研究植物对自然光的时空变化的响应水平，将叶片生理学与整个植物结构、叶片展示和生物量分配相结合。这种方法包括两个部分。首先，已知基因型的三种耐荫树种将沿着从林隙中心，穿过林隙边缘，进入林下植被的连续光效梯度种植。一个建筑模型将用于从叶片水平的光合作用测量到整个植物的碳增益估计。根据这些数据，pi将开发并参数化全植物碳增益和生长的最大似然模型，作为光可用性连续变化的函数。该模型将用于预测同一科系移栽苗在次生林和原生人工林中的生长情况，这两种生境类型在光照模式上存在差异。由于不断变化的土地利用模式可以极大地影响光的空间和时间模式，这些信息将有助于了解和预测植物如何应对当前和未来的土地利用变化。预测异质光环境对热带森林幼苗种群的影响需要明确地描述异质性模式以及植物对这种异质性的响应模式。

9701053 Chazdon This proposal addresses the critical need to create predictive models of seedling response to changing patterns of environmental heterogeneity. The PIs propose to develop mechanistic models of whole-plant carbon gain that will be coupled with studies of plant performance in relation to light heterogeneity in tropical forest environments. The PIs will examine levels of plant response to natural spatial and temporal variation of light to integrate leaf physiology with whole-plant architecture, leaf display, and biomass allocation. The approach involves two components. First, known genotypes of three shade-tolerant tree species will be planted along a continuous gradient of light availability from the center of a gap, through gap edges, and into the forest understory. An architectural model will be used to scale from leaf-level measures of photosynthesis to whole-plant estimates of carbon gain. From these data the PIs will develop and parameterize a maximum likelihood model of whole-plant carbon gain and growth as a function of continuous variation in light availability. This model will then be used to predict growth of transplanted seedlings of the same family lines in secondary forest and native tree plantations, two habitat types differing in patterns of light availability. Since changing land use patterns can dramatically affect both spatial and temporal patterning of light, this information will help to understand and predict how plants may respond to current and future land use changes. Predicting the consequences of heterogeneous light environments for seedling populations in tropical forests requires an explicit characterization of the pattern of heterogeneity as well as patterns of plant response to this heterogeneity.