内蒙古草地地下生物量空间格局分析

Spatial interpolation analysis of grassland below-ground biomass in the Inner Mongolia Autonomous Region,China

本文以内蒙古地区198个草地样地地下生物量调查测定数据为基础,结合遥感及气象数据,进行草地地下生物量与海拔、年均气温、年均降雨、≥10℃年积温、湿润度和NDVI等6个生态因子间的回归分析。根据回归拟合方程,借助ArcGIS平台进行单因素插值,并通过插值预测结果与实测数据的拟合程度赋予各因素不同的权重,加权叠加估算,并综合插值出内蒙古草地地下生物量1km×1km栅格的空间分布图。结果表明:内蒙古地区草地地下生物量平均值为1364.06g/m^2,其中温性草原类草地的地下生物量最大,为1916.64g/m^2,温性荒漠类最小,为80.39g/m^2;草地地下生物量与年均气温、年均降雨、≥10℃年积温、湿润度和NDVI均有着极显著的相关性;空间格局上,自东北向西南方向草地地下生物量呈现由高向低过渡的趋势,呼伦贝尔盟和锡林郭勒盟东部地区的地下生物量最高,阿拉善盟大部分地区地下生物量较低;内蒙古草地植被地下生物量空间插值数据通过了检验,预测精度为66.62%。

This study combines survey data on the below-ground biomass of 198 grassland plots in the Inner Mongolia Autonomous Region with remote sensing and meteorological data.Correlation and regression analy-ses have been conducted between the recorded below-ground biomass and elevation,annual average tempera-ture,precipitation,≥10℃ annual accumulated temperature,moisture index and NDVI （normalized difference vegetation index）.Based on the regression equation,a single factor interpolation was undertaken using the ArcGIS platform,with different weights assigned to different factors based on the degree of fit between the predicted results of the interpolation and the measured results.In terms of the weighted superposition of val-ues,the integrated underground biomass interpolation is graphed as a 1 km＆#215;1 km grid.The results show that the average below-ground biomass of grasslands in the Inner Mongolia Autonomous Region is 1364.06 g/m2 . The below-ground biomass of temperate steppe is the highest （1916.64 g/m2 ）while that of temperate desert is the lowest （80.39 g/m2 ）.There is a significant correlation between below-ground biomass and annual average temperature,precipitation,≥10℃ annual accumulated temperature,moisture index,and NDVI in the Inner Mongolia district.In terms of spatial pattern,the below-ground biomass of grasslands shows a decreasing trend from northeast to southwest,with the highest scores in the east of Hulunbeir League and Xilin Gol League and the lowest scores in Alxa League.This study demonstrates the value of the spatial interpolation of data on below-ground vegetation biomass in Inner Mongolia grasslands,with a forecast accuracy of 66.62%.