Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China.
Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China; Key Laboratory of State Forestry Administration on Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China.
Sci Total Environ. 2020 Mar 25;710:136391. doi: 10.1016/j.scitotenv.2019.136391. Epub 2020 Jan 3.
Revegetation and afforestation across drylands for establishing sustainable ecosystems requires a comprehensive understanding of the carrying capacity for vegetation (CCV) at the regional scale. To determine the CCV across drylands in northern China, we developed a technical framework based on two measures of leaf area index (LAI): maximum LAI (Max-LAI) and safe LAI (Safe-LAI), and their thresholds, CCV and CCV, for six drylands (Horqin, Hulun Buir, Otindag, Mu Us, Tengger, and Junggar) using remote sensing datasets from 2000 to 2014. We also predicted dynamics of CCV of the drylands over the next decade (2015-2024) by establishing optimal prediction models based on environmental factors (temperature, precipitation, potential evapotranspiration, and elevation). According to these models, the Max-LAI threshold (range: 0.36-1.03 m/m) and Safe-LAI threshold (0.29-0.70 m/m) declined from east to west with decreases in aridity index. Under current climatic variability and anthropogenic disturbances, the CCV in most drylands would have positive increments (approximately 15%), except in the Horqin (approximately -15%) and Tengger (slight changes), during the following decade. This indicates that there is scope for improving vegetation coverage in most drylands, except in the Horqin and Tengger. Our results suggest that revegetation and ecosystem management to prevent ongoing desertification should be carried out at the regional scale. Although it does not account for biocrusts, artificially introduced vegetation, underground water, and other vegetation attributes (e.g., density and biomass), our technical framework and results might nonetheless be valuable in evaluating regional ecological security and guiding vegetation restoration of drylands across northern China.
在中国北方的干旱地区建立可持续生态系统的植被承载力(CCV)需要综合理解。为了确定中国北方干旱地区的 CCV,我们根据叶面积指数(LAI)的两个指标(最大 LAI(Max-LAI)和安全 LAI(Safe-LAI)及其阈值),开发了一个技术框架,利用 2000 年至 2014 年的遥感数据集,对六个干旱地区(科尔沁、呼伦贝尔、浑善达克、毛乌素、腾格里和准噶尔)进行了分析。我们还通过建立基于环境因素(温度、降水、潜在蒸散量和海拔)的最优预测模型,预测了未来十年(2015-2024 年)干旱地区 CCV 的动态变化。根据这些模型,最大 LAI 阈值(范围:0.36-1.03 m/m)和安全 LAI 阈值(0.29-0.70 m/m)从东向西随着干旱指数的降低而降低。在当前气候变异性和人为干扰下,除了科尔沁(约-15%)和腾格里(略有变化)外,未来十年大部分干旱地区的 CCV 将呈现正增长(约 15%)。这表明,除了科尔沁和腾格里,大多数干旱地区都有提高植被覆盖的空间。我们的研究结果表明,在区域尺度上应进行植被恢复和生态系统管理,以防止正在发生的荒漠化。尽管它没有考虑生物结皮、人工引入的植被、地下水和其他植被属性(例如,密度和生物量),但我们的技术框架和结果可能在评估区域生态安全和指导中国北方干旱地区的植被恢复方面具有价值。