Collaborative Research on process and Pattern at Alpine Tree Line

丹尼尔G布朗 乔治·P·马兰森 密歇根州立大学 爱荷华州大学 该研究将通过使用一个空间上明确的模拟模型来评估模式和过程之间可能存在的关系，该模型将产生空间模式，并将其与陆地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生态交错带树种丰度的影响。 为此目的，将在冰川国家公园确定30至40个矩形山坡的样本。 在景观上观察到的模式和模拟的模型运行将量化使用景观格局的共同指标。 此外，将生成混合度量，其最好地描述采样单元之间的主要变化。 将根据模拟参数化拟合预测观测指标的模型。 其结果将是更深入地了解生态交错带的基本生态，通过更强的模式和过程之间的概念化。 这项工作也与生态交错区作为气候变化影响指标的概念密切相关。

Daniel G Brown George P Malanson Michigan State University University of Iowa 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.