Doctoral Dissertation Research: Multi-Scale Tree Diversity Conservation Implementation in the Western Amazon Based on Remote Sensing and Tree Inventory Data

地理学家和其他环境科学家有兴趣了解与森林树木多样性变化相关的空间格局，包括由于不同树种分布造成的空间变化。空间变异的变化通常可以与不同尺度的不同栖息地联系起来，从而深入了解森林景观的组织方式。亚马逊西部潮湿的森林是世界上生物多样性最丰富的热带森林之一，但由于难以进入而鲜为人知。增加对植物区系格局及其与生境类型的关系的了解，特别是在这些森林等偏远地区，不仅有助于科学研究，而且有助于促进生物多样性的保护。传统的实地植被调查本身既费时又费力，已不能满足在不同热带森林开展区域尺度保护项目时对大面积植被进行记录的需要。本博士论文研究项目的目标是利用来自树木清查、遥感和保护评估的数据，研究树木的空间分布和森林多样性模式在精细的局部尺度上与在较粗的区域尺度上可探测到的空间分布之间的相似性。并在数据采集和分析方面采取多尺度方法，为厄瓜多尔亚马逊部分地区的土著领土提供基于尺度的保护建议。因此，该项目将有助于几个不同的知识学科，包括生物地理学，热带生态学和生物多样性保护。它还将允许评估规模对模式和过程的影响。在局部尺度上，博士候选人将使用高分辨率卫星图像，如Quickbird，来检查森林结构和多样性的模式，从而结合地面（与树木清查图）和高空（通过遥感）对树木群落分布的空间分析。她将在空间和概念上结合Quickbird和Landsat TM/ETM等传感器的多尺度卫星图像，以预测区域尺度上不同植被和栖息地类型的林分特征和树木多样性模式。研究区域位于亚马逊西部的生物多样性地区。将建立标准化的1公顷树木清查样地，以记录林分组成。该项目有望提供植被和树木多样性模式的基本基线知识，促进对生物多样性丰富的偏远地区森林生物地理的了解。它在实施热带环境下的区域系统保护规划中具有相当的适用性。该项目有望帮助启动亚马逊西部地区的综合保护实施。本研究通过多尺度遥感植被分析来识别树木和生境多样性丰富的地区，为确定仍然保持丰富环境和生物多样性的地区提供了一种高效、经济的方法。通过整合其他数据层，这些数据层包含影响保护实施策略的其他因素，如气候、地形和社会方面，本研究将使用多种标准确定和定位保护优先区域。研究区域包括厄瓜多尔亚马逊东南部的Achuar、Shiwiar和Zapara土著地区，这些地区以前没有进行过树木清查、遥感分析或保护实施。研究结果将分发给土著社区供其反馈和评价，从而使土著人民的需要和意见能够帮助在一个物种丰富但脆弱的生态系统中实现可持续自然资源管理和生物多样性保护之间的平衡。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研究生涯。

Geographers and other environmental scientists are interested in understanding the spatial patterns associated with changes in the diversity of forest trees, including spatial variations due to differing tree species distributions. Changes in spatial variation often can be associated with different habitats at multiple scales, giving insights on how forested landscapes are organized. The humid forests of the western Amazon are some of the most biodiverse tropical forests in the world but are poorly known because of their inaccessibility. An increased understanding of floristic patterns and their associations with habitat type, especially in remote areas such as these forests, not only contributes to scientific research but also makes it possible to facilitate biodiversity conservation. A traditional time-consuming, labor-intensive field survey of vegetation itself can no longer suffice for the needs of documenting vegetation in large areas in order to conduct regional-scale conservation projects in diverse tropical forests. The objectives of this doctoral dissertation research project are to use data from tree inventories, remote sensing, and conservation assessments to examine the similarities among the spatial distributions of trees and the forest diversity patterns as measured at a fine, local scale with the spatial distributions detectable at a coarser, regional scale, and to take a multi-scale approach in terms of data acquisition and analysis to produce scale-dependent conservation recommendations for indigenous territories in a part of the Ecuadorian Amazon. As such, this project will contribute to several different intellectual disciplines, including biogeography, tropical ecology, and biodiversity conservation. It also will allow for evaluation of the effect of scale on pattern and process. At the local scale, the doctoral candidate will use high-resolution satellite imagery, such as Quickbird, to examine patterns of forest structure and diversity, thus combining spatial analysis of the distribution of tree communities at ground level (with tree inventory plots) and from above (through remote sensing). She will spatially and conceptually combine multiple scales of satellite imagery from sensors like Quickbird and Landsat TM/ETM for predicting forest stand characteristics and tree diversity patterns among different vegetation and habitat types at a regional scale. The study region is located in a biodiverse part of the western Amazon. Standardized 1-ha tree inventory plots will be established to document the forest stand composition.This project is expected to provide fundamental baseline knowledge about vegetation and tree diversity patterns, facilitating understanding of forest biogeography in remote areas with great biodiversity. It has considerable applicability in implementing regional systematic conservation planning, which is a great need in tropical environments. The project is expected to help initiate integrative conservation implementation in the western Amazon. By using multi-scale remote sensing vegetation analysis to identify areas with great tree and habitat diversity, this study will provide an efficient, cost-effective method to locate the areas that still retain abundant environmental and biological diversity. By integrating other data layers that contain other factors influencing strategies for conservation implementation, such as climate, topography, and social aspects, this study will identify and target conservation prioritization zones using multiple criteria. The study area covers the Achuar, Shiwiar, and Zapara indigenous territories in the southeastern Ecuadorian Amazon where no previous tree inventory, remote sensing analysis, or conservation implementation has been conducted. Research results will be disseminated to the indigenous communities for their feedback and evaluation, thereby enabling the needs and opinions of the indigenous people to help attain balance between sustainable natural resource management and biodiversity conservation in a highly species-rich but fragile ecosystem. 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.