首页> 外文期刊>International Journal of Forestry Research >Developing a Topographic Model to Predict the Northern Hardwood Forest Type within Carolina Northern Flying Squirrel (Glaucomys sabrinus coloratus) Recovery Areas of the Southern Appalachians
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Developing a Topographic Model to Predict the Northern Hardwood Forest Type within Carolina Northern Flying Squirrel (Glaucomys sabrinus coloratus) Recovery Areas of the Southern Appalachians

机译:开发地形模型以预测南阿巴拉契亚山脉的卡罗来纳州北部飞鼠(Glaucomys sabrinus coloratus)恢复区中的北部硬木森林类型

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The northern hardwood forest type is an important habitat component for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) for den sites and corridor habitats between boreo-montane conifer patches foraging areas. Ourstudy related terrain data to presence of northern hardwood forest type in the recovery areas of CNFS in the southern Appalachian Mountains of western North Carolina, eastern Tennessee, and southwestern Virginia. We recorded overstory species composition and terrain variables at 338 points, to construct a robust, spatially predictive model. Terrain variables analyzed included elevation, aspect, slope gradient, site curvature, and topographic exposure. We used an information-theoretic approach to assessseven models based on associations noted in existing literature as well as an inclusive global model. Our results indicate that, on a regional scale, elevation, aspect, and topographic exposure index (TEI) are significant predictors of the presence of the northern hardwood forest type in the southern Appalachians. Our elevation + TEI model was the best approximating model (the lowest AICc score) for predicting northern hardwood forest type correctly classifying approximately 78% of our sample points. We then used these data to create region-wide predictive maps of the distribution of the northern hardwood forest type within CNFS recovery areas.
机译:北部硬木森林类型是濒临灭绝的卡罗来纳州北部flying鼠(CNFS; Glaucomys sabrinus coloratus)的重要栖息地组成部分,这些栖息地位于北山针叶树针叶林觅食区之间的巢穴和走廊栖息地中。我们研究的地形数据与北卡罗来纳州西部,田纳西州东部和弗吉尼亚州西南部阿巴拉契亚山脉南部CNFS恢复地区北部硬木森林类型的存在有关。我们在338个点记录了地上物种的组成和地形变量,以构建健壮的空间预测模型。分析的地形变量包括海拔,坡向,坡度,场地曲率和地形暴露。我们使用了一种信息理论方法,根据现有文献中提到的关联以及包容性全球模型评估了七个模型。我们的结果表明,在区域范围内,海拔,纵横比和地形暴露指数(TEI)是阿巴拉契亚南部北部硬木森林类型存在的重要预测指标。我们的高程+ TEI模型是预测北部硬木森林类型的最佳近似模型(最低AICc得分),可以正确分类约78%的样本点。然后,我们使用这些数据创建了CNFS回收区内北部阔叶林类型分布的区域性预测地图。

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