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The relationship between tree establishment patterns and positive feedback at alpine treeline.

机译:树的建立模式与高山树线正反馈之间的关系。

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The spatial pattern of trees found at alpine treeline results from the interaction of many variables. Environmental stresses, competition with herbaceous and woody tundra species, the impact of disturbance, the effects of changing climate and the ability of species to respond to climate change all influence the patterns found at alpine treeline. The alpine treeline ecotone may be particularly responsive to climatic changes as species found at this ecotone are often at some limit to their existence. Determining the significance of specific processes in determining pattern is important in order to be able to predict vegetation changes under potential climate change, as well as to determine which patterns are particularly susceptible to the invasion of vegetation as a consequence of global climate change. The aim of this research is to determine the significance of positive feedback, how trees improve local conditions and allow for the establishment of more trees, in structuring tree establishment patterns at alpine treeline. To accomplish this, a cellular automata based model was developed that captures the primary influence of a few important environmental variables. Through iterations of simple rules, the model generates complex patterns that are similar to those patterns found at alpine treeline. It is the clear logic and simplicity of this model that allow for generalizations to be made concerning the importance of underlying local processes in determining patterns at alpine treeline. Using spatial metrics, the patterns generated by different permutations of the model parameters are compared with data collected on tree establishment pattern at Lee Ridge in Glacier National Park, Montana. Results, including Multivariate Analysis of Variance and Principle Components Analysis, show that the model realizations that include a directional positive feedback produce patterns that are more similar to those found on Lee Ridge than those produced by model realizations that do not include a directional positive feedback. Further research is necessary to determine the strength of feedback necessary to produce the complex patterns of tree establishment found at Lee Ridge, and in many other treeline environments.
机译:在高山树线处发现的树木的空间格局是许多变量相互作用的结果。环境压力,与草本和木质苔原物种的竞争,干扰的影响,气候变化的影响以及物种对气候变化的响应能力都影响着高山林线的格局。高山树林过渡带可能对气候变化特别敏感,因为在该过渡带发现的物种通常在某种程度上限制了它们的生存。为了能够预测潜在气候变化下的植被变化,以及确定哪些模式特别易受全球气候变化的影响而入侵植被,确定特定过程在确定格局中的重要性很重要。这项研究的目的是确定积极反馈的意义,树木如何改善当地条件以及允许更多树木的建立,以构造高山树木线的树木建立模式。为此,开发了一种基于细胞自动机的模型,该模型捕获了一些重要环境变量的主要影响。通过简单规则的迭代,该模型生成的复杂模式类似于在高山林线发现的那些模式。正是这种模型的清晰逻辑和简单性,使得可以对确定高山树线模式中潜在的局部过程的重要性进行概括。使用空间度量,将由模型参数的不同排列生成的模式与在蒙大拿州冰川国家公园的李里奇树建立模式收集的数据进行比较。结果(包括方差的多元分析和主成分分析)表明,与不包含方向性正反馈的模型实现所产生的模式相比,包含方向性正反馈的模型实现所产生的模式与在Lee Ridge上发现的模式更为相似。为了确定产生在Lee Ridge和其他许多树线环境中发现的复杂树木建立模式所必需的反馈强度,需要进行进一步的研究。

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