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Bioclimatic modeling the spatial distribution of mountain forests in the Qilian Mountains, Northwest of China, using down-scaled climatic models

机译:中国西北祁连山山林空间分布的生物思考

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Study on the Climate-Vegetation Coupling Relationship (CVCR) has been an attractive field in geography and ecology since the late 19th century. Its results are very helpful for decision-making of vegetation ecological restoration. However, it is hard for scientists to know precisely about the quantified relationships between a variety of vegetation types and a set of climatic parameters because of poor matching between spatially limited climatic data and high-resolution vegetation maps. In this article, the authors suggest new high-resolution distributing models that combine temperature and precipitation respectively with altitude, latitude, slope, and aspect, and perform regression analysis to deduce two equations linking temperature and precipitation respectively with readily observed altitude, slope and aspect. Using the two equations, mean annual temperature, mean monthly temperature, and annual precipitation for each cell can be calculated based upon the digital elevation model. The calculated results of models running are consistent with the actual conditions of temperature and precipitation in alpine zones of Qilian Mountains. According to the statistics of the distributing precipitation model, the regional annual precipitation maximum in Qilian Mountains occurs at 4500 m above sea level (a.s.l.). According to interpretation of Landsat TM/ETM+ imagery data, the actual areas of mountain forests in the study area are 422.94 km/sup 2/. The coupling relationship of mountain forests with both temperature and precipitation is achieved by combining the distributing temperature model with distributing precipitation model in the area of mountain forests together. The CVCR analysis indicates the mean annual temperature of -2.7/spl sim/0.8/spl deg/C, the mean July temperature of 9.3/spl sim/13.7/spl deg/C in the area of mountain forests, and the annual precipitation is more than 360 mm. According to the above-mentioned coupling relationships, a map which illustrates the potential extent of mountain forests is created. Statistics shows that under conditions without human-induced interruptions, potential areas of mountain forests would reach up to 6937.12 km/sup 2/. It means that, the present conditions of both types of forests only account for about 6% of the inferred potential areas.
机译:自19世纪末以来,气候植被偶联关系(CVCR)是一个有吸引力的地理与生态学领域。它的结果非常有助于植被生态恢复的决策。然而,科学家们很难完全了解各种植被类型与一系列气候参数之间的量化关系,因为空间有限的气候数据和高分辨率植被图之间的匹配差。在本文中,作者提出了新的高分辨率分布模型,分别与海拔,纬度,斜率和方面相结合的温度和降水,并进行回归分析,以分别用容易观察到的高度,坡度,坡度,坡度,坡度,坡度,坡度,坡度和方面推导出回归分析。 。使用两个方程,平均温度,平均每月温度和每种电池的年降水可以基于数字高度模型来计算。跑步的计算结果与祁连山的高山区的温度和降水的实际条件一致。根据分配降水模型的统计数据,祁连山区域降水最大程度发生在海拔4500米(A.L.)。根据Landsat TM / ETM +图像数据的解释,研究区的山林的实际区域为422.94 km / sup 2 /。通过将分布温度模型与分布在山林地区的分配温度模型结合在一起,实现了山林与温度和沉淀的耦合关系。 CVCR分析表明-2.7 / SPL SIM / 0.8 / SPL DEG / C的平均年度温度,平均七月温度为9.3 / SPL SIM / 13.7 / SPL DEG / C,在山林森林中,年降水量是超过360毫米。根据上述耦合关系,创建了一种说明山林潜在程度的地图。统计数据显示,在没有人类引起的中断的条件下,山林的潜在地区达到6937.12公里/ sup 2 /。这意味着,两种类型的森林的目前的条件仅占推断潜在地区的约6%。

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