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Carrying capacity for vegetation across northern China drylands

机译:中国北方干旱地区植被的承载力

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摘要

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_(max) and CCV_(safe), 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~2/m~2) and Safe-LAI threshold (0.29-0.70 m~2/m~2) 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.
机译:整个干旱地区的植被恢复和绿化以建立可持续的生态系统,需要对区域范围内植被的承载能力有全面的了解。为了确定中国北方干旱地区的CCV,我们基于两种叶面积指数(LAI)指标(最大LAI(Max-LAI)和安全LAI(Safe-LAI))及其阈值CCV_(max )和CCV_(安全),使用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,奥蒂达格,穆斯,腾格和准Jung尔)进行了干旱。我们还预测了未来十年(2015年)干旱地区CCV的动态-2024),然后根据环境因素(温度,降水,潜在的蒸散量和海拔)建立最佳的预测模型。根据这些模型,随着干旱程度的降低,Max-LAI阈值(范围:0.36-1.03 m〜2 / m〜2)和Safe-LAI阈值(0.29-0.70 m〜2 / m〜2)从东向西降低指数。在当前的气候变化和人为干扰下,在接下来的十年中,除科尔沁(约-15%)和腾格(略有变化)外,大多数旱地的CCV都会有正增量(约15%)。这表明除科尔沁和腾格之外,大多数旱地都有改善植被覆盖的空间。我们的结果表明,应在区域范围内进行植被恢复和生态系统管理,以防止正在进行的荒漠化。尽管它不考虑生物结壳,人为引入的植被,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对于评估区域生态安全和指导中国北方干旱地区的植被恢复具有重要价值。

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  • 来源
    《The Science of the Total Environment》 |2020年第25期|136391.1-136391.11|共11页
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  • 作者单位

    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;

    Yanchi Research Station School of Soil and Water Conservation Beijing Forestry University Beijing 100083 PR China Engineering Research Center of Forestry Ecological Engineering Ministry of Education Beijing Forestry University Beijing 100083 PR China;

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  • 正文语种 eng
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  • 关键词

    Dryland ecosystem; Leaf area index; Multivariate empirical dynamic modelling; Vegetation threshold; Vegetation sensitivity;

    机译:旱地生态系统;叶面积指数;多元经验动态建模;植被阈值;植被敏感性;

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