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Diversity in the boreal forest of Alaska: Distribution and impacts on ecosystem services.

机译：阿拉斯加北方森林的多样性：分布及其对生态系统服务的影响。

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摘要

Within the forest management community, diversity is often considered as simply a list of species present at a location. In this study, diversity refers to species richness and evenness and takes into account vegetation structure (i.e. size, density, and complexity) that characterize a given forest ecosystem and can typically be measured using existing forest inventories. Within interior Alaska the largest forest inventories are the Cooperative Alaska Forest Inventory and the Wainwright Forest Inventory. The limited distribution of these inventories constrains the predictions that can be made. In this thesis, I examine forest diversity in three distinct frameworks; Recruitment, Patterns, and Production. In Chapter 1, I explore forest management decisions that may shape forest diversity and its role and impacts in the boreal forest. In Chapter 2, I evaluate and map the relationships between recruitment and species and tree size diversity using a geospatial approach. My results show a consistent positive relationship between recruitment and species diversity and a general negative relationship between recruitment and tree size diversity, indicating a tradeoff between species diversity and tree size diversity in their effects on recruitment. In Chapter 3, I modeled and mapped current and possible future forest diversity patterns within the boreal forest of Alaska using machine learning. The results indicate that the geographic patterns of the two diversity measures differ greatly for both current conditions and future scenarios and that these are more strongly influenced by human impacts than by ecological factors. In Chapter 4, I developed a method for mapping and predicting forest biomass for the boreal forest of interior Alaska using three different machine-learning techniques. I developed first time high resolution prediction maps at a 1 km2 pixel size for aboveground woody biomass. My results indicate that the geographic patterns of biomass are strongly influenced by the tree size class diversity of a given stand. Finally, in Chapter 5, I argue that the methods and results developed for this dissertation can aid in our understanding of forest ecology and forest management decisions within the boreal region.
机译：在森林管理社区中，多样性通常被简单地认为是某个地点存在的物种清单。在这项研究中，多样性是指物种的丰富性和均匀性，并考虑到了代表给定森林生态系统特征的植被结构（即大小，密度和复杂性），并且通常可以使用现有森林清单进行衡量。在阿拉斯加内部，最大的森林清单是合作阿拉斯加森林清单和温赖特森林清单。这些库存的有限分配限制了可以进行的预测。在本文中，我在三个不同的框架中研究了森林多样性。招聘，模式和生产。在第一章中，我探讨了可能影响森林多样性及其在北方森林中的作用和影响的森林管理决策。在第二章中，我使用地理空间方法评估和绘制了招聘与物种和树木大小多样性之间的关系。我的研究结果表明，募集与物种多样性之间存在着一致的正向关系，而募集与树木大小多样性之间存在着通常的负向关系，这表明物种多样性与树木大小多样性之间对它们的影响之间存在权衡。在第3章中，我使用机器学习对阿拉斯加寒带森林中当前和将来的森林多样性模式进行了建模和映射。结果表明，两种多样性测度的地理格局在当前条件和未来情景中都存在很大差异，而且受人类影响比受生态因素影响更大。在第4章中，我开发了一种使用三种不同的机器学习技术对阿拉斯加内陆北方森林的森林生物量进行制图和预测的方法。我为地上木质生物量开发了第一次高分辨率预测地图，像素大小为1 km2。我的结果表明，生物量的地理格局在很大程度上受到给定林分的树木大小类别多样性的影响。最后，在第5章中，我认为为该论文开发的方法和结果可以帮助我们了解北方地区的森林生态和森林管理决策。

著录项

  • 作者

    Young, Brian D.;

  • 作者单位

    University of Alaska Fairbanks.;

  • 授予单位 University of Alaska Fairbanks.;
  • 学科 Biology Biostatistics.;Agriculture Forestry and Wildlife.;Biology Ecology.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 261 p.
  • 总页数 261
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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