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    邵艳莹, 吴秀芹, 张宇清, 秦树高, 吴斌. 内蒙古地区植被覆盖变化及其对水热条件的响应[J]. 北京林业大学学报, 2018, 40(4): 33-42. DOI: 10.13332/j.1000-1522.20170414
    引用本文: 邵艳莹, 吴秀芹, 张宇清, 秦树高, 吴斌. 内蒙古地区植被覆盖变化及其对水热条件的响应[J]. 北京林业大学学报, 2018, 40(4): 33-42. DOI: 10.13332/j.1000-1522.20170414
    Shao Yanying, Wu Xiuqin, Zhang Yuqing, Qin Shugao, Wu Bin. Response of vegetation coverage to hydro-thermal change in Inner Mongolia of northern China[J]. Journal of Beijing Forestry University, 2018, 40(4): 33-42. DOI: 10.13332/j.1000-1522.20170414
    Citation: Shao Yanying, Wu Xiuqin, Zhang Yuqing, Qin Shugao, Wu Bin. Response of vegetation coverage to hydro-thermal change in Inner Mongolia of northern China[J]. Journal of Beijing Forestry University, 2018, 40(4): 33-42. DOI: 10.13332/j.1000-1522.20170414

    内蒙古地区植被覆盖变化及其对水热条件的响应

    Response of vegetation coverage to hydro-thermal change in Inner Mongolia of northern China

    • 摘要:
      目的本文以NDVI为表征,以内蒙古地区植被为研究对象,分析近32年(1982—2013年)生长期各季度植被动态变化趋势及其对气候因子的响应,旨在了解该区的生态环境变化趋势,为区域生态建设提供决策依据。
      方法本文基于1982—2013年内蒙古地区GIMMS3g NDVI数据集,结合该地区的降水和平均温度数据,运用线性回归、相关性分析和ANUSPLIN插值等方法分析了近32年来生长期各季度植被动态变化趋势及其对气候因子的响应。
      结果1982—2013年内蒙古地区植被总体上呈上升趋势,内蒙古NDVI与各气候因子的相关性不同,生长期各季度(春、夏、秋)NDVI与降水量多呈显著正相关关系,但与前期降水的相关性更密切;NDVI与温度的相关性以负相关为主。相比于温度,NDVI与降水的相关性更高。
      结论内蒙古地区植被呈持续好转态势,该区植被在不同生长阶段对水热的响应程度不同。总体上,生长季初期(春季),东北地区(呼伦贝尔市东部及东北部和锡林郭勒市东南边缘),植被对热量变化的响应较为敏感,主要体现在对同时期温度的响应;夏秋季节,中部地区(呼伦贝尔市西南部、锡林郭勒盟大部分地区、乌兰察布市北部、鄂尔多斯市大部)植被动态变化对降水的依赖性较强,突出表现为植被生长对降水的迟滞反应。研究建议,在未来生态恢复与重建工程中,要充分利用自然修复的方式恢复在当地条件下更具有持续性的植被生态系统;同时为避免盲目大规模人工造林导致土地退化,既要考虑目前的水资源承载力,还要考虑未来气候变化背景下,水资源的供给能力。

       

      Abstract:
      ObjectiveOur specific objectives were to track the dynamic changes of vegetation NDVI and its response to climatic factors for different growth stages during recent 32 years (1982-2013) in Inner Mongolia of northern China, which would provide a reference for improving regional ecological environment.
      MethodIn this study, with GIMMS3g NDVI (1982-2013) datasets and meteorological data in Inner Mongolia, the spatio-temporal patterns of changes in seasonly NDVI and their linkages with temperature and precipitation were analyzed at regional and pixel scales. Spatial interpolation of meteorological data was achieved using the thin-plate smoothing spline method of Hutchinson.To detect the trends of NDVI and climatic factors, Theil-Sen linear regression was applied. To further explore the climatic factors driving NDVI change during a given period, correlations between NDVI and climatic variables were calculated using Pearson correlation analysis.
      ResultThe results showed that the vegetation in Inner Mongolia continuously increased from 1982 to 2013, and correlations were different between NDVI and climatic factors in Inner Mongolia, NDVI mostly had a positive correlation with precipitation, but it was more closely related to pre-precipitation. The correlation between NDVI and temperature was mostly negative correlation. The correlation between NDVI and precipitation was higher than temperature.
      ConclusionThe results indicated that the vegetation in Inner Mongolia was continuously improved, and the response of vegetation NDVI to hydro-thermal change for different periods was different in Inner Mongolia. The effect of temperature on vegetation growth was more significant in the northeast region in spring, such as in the eastern and northeastern Hulun beler and the southeast edge of Xilin Gol. The response of NDVI in the central region (e.g. the southwestern Hulun Buir, the most areas of Xilin Gol, the northern Ulanchabu, the most areas of Ordos) was more sensitive to precipitation in summer and autumn, especially lagged effect of vegetation growth on precipitation. Our study suggested that, in ecological restoration and reconstruction project in the future, we should make full use of natural remediation to restore more sustainable vegetation ecosystems; at the same time, in order to avoid land degradation caused by blind large-scale artificial afforestation, it is necessary to consider the current water resources carrying capacity and water supply capacity in the future.

       

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