Doctoral Dissertation Research: Causes and Consequences of Forest Dieback in Temperate Rainforests Across Western Patagonia: A Multi-Scale Approach

在世界各地的许多森林中，影响大量树木的相对同步的树木死亡事件已被证明有复杂的原因，涉及生物和非生物因素的相互作用。 在智利南部的温带雨林中，这种森林枯梢病长期以来一直被报道为针叶树Pilgerodendron uviferum。 这个博士论文项目将调查以前无法解释的立场在这个受威胁的树种在智利南部的这个物种的范围的大部分水平的死亡率。 博士生将测试的主要假设，即森林枯死的时间与气候变化有关，这是最有可能的诱发因素在区域范围内运作。 学生将研究气候变化的差异影响与当地的网站因素（如海拔，地形位置，土壤排水，和其他土壤变量）和当地的干扰因素（如地震和火灾）在造成林分水平树死亡。 他将使用地理信息系统为基础的方法，遥感，树木年轮分析和实地采样相结合，对影响这些森林的枯死类型进行分类，并阐明枯死的诱发因素和触发因素。 基于大量的环境因子的空间关系的定量化的枯死，逻辑回归模型将开发预测映射的栖息地容易受到未来的Pilgerodendron枯死，这项研究的结果将加强基本的了解，区域气候变化如何与当地的网站因素和干扰事件，产生林分水平的树木死亡率在Pilgerodendron种群。 许多受枯死影响的Pilgerodendron森林位于国家公园和森林保护区，资源管理人员目前缺乏有关枯死原因和后果的信息。 该项目的研究结果将为管理决策提供信息，以了解枯梢病是由于自然还是人为影响。 当前顶枯模式和对未来顶枯敏感性的GIS层对资源管理员特别有用。 了解森林枯死原因的复杂性将有助于预测气候变化对森林资源和生物多样性的威胁，并可能有助于减轻其影响。 作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立的研究生涯。

In many forests around the world, episodes of relatively synchronous tree mortality affecting large populations of trees have been shown to have complex causes involving interactions of biotic and abiotic factors. In the temperate rainforests of southern Chile, such forest diebacks have long been reported for the coniferous tree Pilgerodendron uviferum. This doctoral dissertation project will investigate the previously unexplained stand-level mortality in this threatened tree species across a large part of the range of this species in southern Chile. The doctoral candidate will test the primary hypothesis that the timing of forest dieback is related to climatic variation, which is the most likely predisposing factor operating at a regional scale. The student will examine differential impacts of climatic variation in relation to local site factors (such as elevation, topographic position, soil drainage, and other soil variables) and local disturbance factors (such as earthquakes and fire) in causing stand level tree mortality. He will use a combination of geographic information system-based methods, remote sensing, tree ring analysis, and field sampling to classify the types of dieback affecting these forests and to elucidate the predisposing and triggering factors of dieback. Based on quantifying spatial relationships of dieback to a large range of environmental factors, logistic regression models will be developed for predictive mapping of habitats susceptible to future Pilgerodendron dieback.The results of this study will enhance basic understanding regarding how regional climatic variation interacts with local site factors and disturbance events to produce stand-level tree mortality in Pilgerodendron populations. Many of the Pilgerodendron forests affected by dieback are in national parks and forest reserves, and resource managers currently lack information about the causes and consequences of dieback. The findings of this project will inform management decisions in the context of understanding whether the dieback is due to natural or human-related influences. The GIS layers of present dieback patterns and susceptibility to future dieback will be particularly useful to resource managers. Understanding such complexity in the causes of forest dieback will help to predict threats to forest resources and biodiversity from climate change, and may aid in mitigating their effects. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.