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

9701053 Chazdon该提案解决了创建幼苗对环境异质性变化模式的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，将与热带森林环境中光异质性相关的植物性能研究相结合。PI将检查植物对自然光的空间和时间变化的响应水平，以将叶片生理学与整个植物结构、叶片显示和生物量分配相结合。 这一办法包括两个组成部分。首先，将沿着连续的光照梯度从林隙中心、穿过林隙边缘、进入森林林下植被，沿着种植三种耐荫树种的已知基因型。一个建筑模型将被用来从光合作用的叶片水平的措施，以整个植物的碳增益估计规模。从这些数据中，PI将开发和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。然后，这个模型将被用来预测移植幼苗的生长在次生林和本地树木种植园，两个不同的光可用性模式的栖息地类型相同的家庭线。由于不断变化的土地利用模式可以显着影响光的空间和时间模式，这些信息将有助于理解和预测植物如何应对当前和未来的土地利用变化。在热带森林中的幼苗种群的异质性光环境的后果预测需要一个明确的特征的异质性以及植物响应这种异质性的模式。

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.