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Testing for optimal large-scale vegetation properties for maximum terrestrial productivity and quantifying future uncertainty of vegetation response to anticipated climate change.

机译:测试最佳的大型植被特性,以实现最大的陆地生产力,并量化植被对预期气候变化的未来不确定性。

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摘要

In this study, I present a new approach to quantifying a range of uncertainty associated with the carbon-climate feedback over the period 1850 to 2100 within an earth system model of intermediate complexity. The degree to which terrestrial vegetation adaptively self-organizes to shape its own climatic conditions is still an open question. Nonetheless, one can simulate a best case scenario, in which terrestrial productivity is periodically maximized with respect to several macroscopic vegetation parameters, commonly held constant in other models such as maximum stomatal conductance. The results of this dynamically optimized simulation are compared to a simulation where the vegetation parameters are held static at the values optimized for pre-industrial conditions. With this comparison, the degree to which terrestrial productivity is underestimated when vegetation parameterizations remain static compared to those reflecting optimal adaptation to new conditions can be quantified.
机译:在这项研究中,我提出了一种新方法,用于量化中等复杂程度地球系统模型中1850至2100年期间与碳气候反馈相关的不确定性范围。陆地植被适应性自我组织以形成自身气候条件的程度仍是一个悬而未决的问题。但是,可以模拟一种最佳情况,在这种情况下,相对于几个宏观植被参数(通常在其他模型(例如最大气孔导度)中保持不变)的宏观植被参数,周期性地使陆地生产力最大化。将此动态优化模拟的结果与模拟进行比较,在模拟中,植被参数保持静态,并保持针对工业化前条件优化的值。通过这种比较,可以确定与反映最佳适应新条件的植被参数设置保持静态相比,地面生产力被低估的程度。

著录项

  • 作者

    Pavlick, Ryan.;

  • 作者单位

    University of Maryland, College Park.$bGeography.;

  • 授予单位 University of Maryland, College Park.$bGeography.;
  • 学科 Geography.; Biogeochemistry.
  • 学位 M.A.
  • 年度 2007
  • 页码 47 p.
  • 总页数 47
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然地理学;生物地球化学、气体地球化学;
  • 关键词

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