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Broad-scale patterns of avian biodiversity in response to habitat heterogeneity in a semi-arid landscape.

机译：应对半干旱景观中栖息地异质性的鸟类生物多样性的大范围模式。

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摘要

The rapid decline in biodiversity makes urgent the need to understand the distribution of species over broad spatial extents. Traditionally-used classified imagery-based approaches have limited usefulness for this because they may overlook important within-habitat components in highly heterogeneous ecosystems. The main objective of my dissertation was to develop remote sensing and statistical approaches, informed by ecological theory, for mapping and understanding patterns of avian biodiversity in a semi-arid ecosystem. The study area was the McGregor Range of Fort Bliss Army Reserve in the northern Chihuahuan Desert.;In the first three chapters I tested different remote sensing approaches for understanding the ecological factors that influence bird species richness and guild abundance. I used image texture measures as proxies for habitat heterogeneity and the Normalized Difference Vegetation Index as a proxy for habitat productivity for modeling species richness. I subsequently used spectral mixture analysis to calculate proportions of discrete habitat components within each 30 m pixel of a given study plot. My results emphasize that habitat heterogeneity is a main determinant of bird species richness and the abundance of some guilds in that ecosystem.;My fourth chapter addressed the ecological factors that affect the occurrence and fitness of the Loggerhead Shrike (Lanius ludovicianus). While I found significant statistical relationships between bird occurrence and habitat variables such as NDVI texture, I found no significant relationship between the habitat variables measured and measures of fitness. These results suggest a greater need for understanding what limits individual bird fitness in that ecosystem.;My fifth chapter stems from my M.S. in biometry, and focused on testing the usefulness of Bayesian Model Averaging for building predictive models in ecology. I found that the choice of model prior influences the accuracy of the predictions and that the prior associated with AIC model averaging does not necessarily lead to improved predictions.;Finally, I implemented the tools developed in my dissertation to produce maps of species abundance and occurrence across the study area. Using measures of image texture and elevation variables is a cost-effective and easy-to-implement alternative to the traditional use of classified imagery for wildlife habitat mapping.
机译：生物多样性的迅速下降迫切需要了解物种在广泛空间范围内的分布。传统上使用的基于分类图像的分类方法在此方面的用途有限，因为它们可能会忽略高度异构生态系统中重要的栖息地内部组成部分。本文的主要目的是在生态理论的指导下开发遥感和统计方法，以绘制和理解半干旱生态系统中鸟类生物多样性的模式。研究区域是位于奇瓦瓦沙漠北部的幸福堡军备储备区的麦格雷戈山脉。在前三章中，我测试了不同的遥感方法，以了解影响鸟类物种丰富度和行会丰度的生态因素。我使用图像纹理度量作为栖息地异质性的代理，并使用归一化植被指数作为代表物种丰富度的栖息地生产力的代理。随后，我使用光谱混合分析来计算给定研究区域的每个30 m像素内离散栖息地成分的比例。我的研究结果强调说，栖息地异质性是决定鸟类物种丰富度以及该生态系统中某些行会数量的主要决定因素。我的第四章探讨了影响Loggerhead Shrike（Lanius ludovicianus）发生和适应的生态因素。虽然我发现鸟类的发生与栖息地变量（例如NDVI质地）之间存在显着的统计关系，但我发现所测量的栖息地变量与适应性指标之间没有显着的关系。这些结果表明，更需要了解限制该生态系统中个体鸟类健康的因素。;我的第五章来自我的硕士，并致力于测试贝叶斯平均模型在建立生态学预测模型方面的有效性。我发现模型先验的选择会影响预测的准确性，而与AIC模型平均相关的先验并不一定会导致改进的预测。最后，我实现了我在论文中开发的工具来绘制物种丰度和发生率图整个研究区域。与传统使用分类图像进行野生动植物栖息地制图的传统使用相比，使用图像纹理和高程变量的度量是一种经济高效且易于实现的替代方法。

著录项

  • 作者

    St-Louis, Veronique.;

  • 作者单位

    The University of Wisconsin - Madison.;

  • 授予单位 The University of Wisconsin - Madison.;
  • 学科 Agriculture Wildlife Conservation.;Biology Ecology.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 342 p.
  • 总页数 342
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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