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GIS-assisted modelling of the spatial distribution of Qinghai spruce (Picea crassifolia) in the Qilian Mountains, northwestern China based on biophysical parameters

机译:基于生物物理参数的GIS辅助的西北祁连山青海云杉(Picea crassifolia)空间分布的建模

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There has been an increasing use of predictive spatial distribution of main communities or dominant species at the landscape scale for ecological restoration planning, biodiversity conservation planning and regional management decisions in the Qilian Mountains, northwest China. Understanding the spatial distribution of dominant species at the regional scale is also essential for assessing the impacts of environmental change or human effects on vegetation distribution. Based on the spatial distribution of resource variables that correlate with or control plant distribution, this study focused on the prediction of Qinghai spruce (Picea crassifolia) distribution at the regional scale, i.e., where the extent of the prediction was within the biogeographic range of Qinghai spruce in the upper reach of Heihe River. The development of the predictive model in the study required the integration of geographical information system (GIS) with remote sensing (RS), spatial analytic and statistical tools. First, we selected the main resource variables such as mean July temperature, water and solar radiation. These variables were spatialized as functions of elevation and horizontal coordinates or as functions of aspect and slope via a GIS. Second, the niche spaces of Qinghai spruce were determined by incorporating the spatially-distributed resource variables with the current distribution of the species, which came from remote sensing data (Landsat TM image). The niche spaces defined then were extrapolated over the study area. Third, the distribution pattern was validated by field investigations. The study showed that the scope of mean July temperature ranged from 8.5 degrees C to 13.5 degrees C, average annual precipitation from 370 mm to 660 mm, the soil moisture index from 2.3 m(3) m(-1) year(-1) to 4.5 m(3) m(-1) year(-1) and the shortwave radiation for an average July day from 3.8 mm m(-2) day(-1) to 7.8 mm m(-2) day(-1). The elevation range belonging to Qinghai spruce in Qilian Mountains was also determined according to the mean July temperature space occupied by the forest. The elevation occupied by Qinghai spruce was about from 2600 m to 3400 m. We found that the density of the species has higher value from 2650 m to 3100 m based on the field investigation, and from 3 100 m the density decreased with elevation increase. The basal area of Qinghai spruce had the same change as the density. That is, the suitable niche of the species ranged from 2650 m to 3 100 m. (c) 2005 Elsevier B.V. All rights reserved.
机译:在中国西北祁连山,越来越多地利用景观尺度上主要群落或优势物种的预测性空间分布来进行生态恢复规划,生物多样性保护规划和区域管理决策。了解区域尺度上优势物种的空间分布对于评估环境变化或人类对植被分布的影响也至关重要。基于与植物分布相关或控制植物分布的资源变量的空间分布,本研究着重于区域规模的青海云杉(Picea crassifolia)分布预测,即预测范围在青海生物地理范围内云杉在黑河上游。研究中预测模型的发展需要将地理信息系统(GIS)与遥感(RS),空间分析和统计工具集成在一起。首先,我们选择了主要的资源变量,例如7月平均温度,水和太阳辐射。这些变量通过GIS在空间上作为高程和水平坐标的函数或作为纵横比和坡度的函数。其次,通过将空间分布的资源变量与物种的当前分布相结合来确定青海云杉的生态位空间,这些变量来自遥感数据(Landsat TM图像)。然后将定义的利基空间外推到研究区域。第三,通过实地调查验证了分布模式。研究表明,7月平均温度范围为8.5摄氏度至13.5摄氏度,年平均降水量为370毫米至660毫米,土壤湿度指数为2.3 m(3)m(-1)年(-1)。至4.5 m(3)m(-1)年(-1),平均短波辐射从3.8 mm m(-2)day(-1)到7.8 mm m(-2)day(-1) )。祁连山青海云杉的海拔范围也根据森林所占据的平均七月温度空间来确定。青海云杉占据的海拔约为2600 m至3400 m。根据野外调查,我们发现该物种的密度在2650 m至3100 m之间具有较高的值,而从3 100 m开始,密度随着海拔的升高而降低。青海云杉的基底面积与密度变化相同。即,该物种的合适生态位在2650m至3100m的范围内。 (c)2005 Elsevier B.V.保留所有权利。

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