PREDICTING VEGETATION AT TREELINE USING TOPOGRAPHY AND BIOPHYSICAL DISTURBANCE VARIABLES
PREDICTING VEGETATION AT TREELINE USING TOPOGRAPHY AND BIOPHYSICAL DISTURBANCE VARIABLES
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DOI：
10.2307/3235880
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发表时间：
1994-11-01
影响因子：
2.8
通讯作者：
BROWN, DG
中科院分区：
文献类型：
--
作者：
BROWN, DG
四种植被类型和变量之间的关系，代表地形和生物物理干扰梯度建模的研究区域中东部冰川国家公园，蒙大拿州。 通过对卫星数据的分类和随后的实地验证，确定了四种树线过渡植被类型，包括封闭冠层森林、开放冠层森林、草甸和无植被表面（例如岩石、雪和冰），并绘制了地图。 地形特征表示使用数字高程模型和三个变量来自地形气候潜力模型（太阳辐射潜力，积雪潜力，土壤饱和潜力）。 广义加法和广义线性模型（GAM和GLM，分别）技术的组合被用来构建逻辑回归模型，代表四种植被类型的分布。 这些变量解释了植被类型的大量变化，但高水平的变化仍然无法解释。 “预期”和“观察到的”植被格局的比较表明，一些无法解释的变化可能发生在流域尺度。 一套工具和技术，有利于预测景观尺度的植被格局和测试这些模式的空间控制的假设。
The relationships between four vegetation types and variables representing topography and biophysical disturbance gradients were modeled for a study area in east-central Glacier National Park, Montana. Four treeline transition vegetation types including closed-canopy forest, open-canopy forest, meadow, and unvegetated surfaces (e.g. rock, snow, and ice) were identified and mapped through classification of satellite data and subsequent field verification. Topographic characteristics were represented using a digital elevation model and three variables derived from topoclimatic potential models (solar radiation potential, snow accumulation potential, and soil saturation potential). A combination of generalized additive and generalized linear modeling (GAM and GLM, respectively) techniques was used to construct logistic regression models representing the distributions of the four vegetation types. The variables explained significant amounts of variation in the vegetation types, but high levels of variation remained unexplained. A comparison of 'expected' and 'observed' vegetation patterns suggested that some unexplained variation may have occurred at the basin scale. A suite of tools and techniques is presented that facilitates predicting land-scape-scale vegetation patterns and testing hypotheses about the spatial controls on those patterns.