Collaborative Research on Process and Pattern at Alpine Treeline

乔治·P·马兰森丹尼尔·G·布朗爱荷华大学密歇根州立大学这项研究将通过使用空间明确的模拟模型来评估模式和过程之间可能的关系，该模型产生的空间模式将与陆地资源卫星图像记录的模式进行比较。这项工作将允许测试不同的正反馈强度、种子雨和环境梯度对交错带树种丰度的影响。为此，将在冰川国家公园内确定30至40个矩形山坡的样本。在景观上观察到的模式和在模型运行中模拟的模式将使用景观格局的通用度量来量化。进一步，将生成一个混合度量，该度量最好地描述了采样单元之间的主要变化。预测观测指标的模型将从模拟参数化中拟合出来。结果将是通过更强的模式和过程之间的概念化，更深入地了解过渡带的基本生态学。这项工作也与过渡带作为气候变化影响指标的概念密切相关。

George P Malanson Daniel G Brown University of Iowa Michigan State University The research will assess the possible relations between pattern and process by using a spatially explicit simulation model that produces spatial patterns which will be compared to patterns recorded by Landsat imagery. The work will allow testing of the effects of different positive feedback strength, seed rain, and environmental gradient on the abundance of tree species at an ecotone. A sample of 30 to 40 rectangular hillslopes will be identified for this purpose in Glacier National Park. The patterns observed on the landscape and simulated in the model runs will be quantified using common metrics of landscape pattern. Further a hybrid metric will be generated which best describes the dominant variation among the sampled units. A model to predict the observed metrics will be fit from the simulation parameterizations. The outcome will be a deeper understanding of the basic ecology of ecotones through a stronger conceptualization between pattern and process. The work is also germane to the notion of ecotones as indicators of the impacts of climate change.