Carrying capacity for vegetation across northern China drylands

Jutao Zhang; Yuqing Zhang; Shugao Qin; Bin Wu; Guodong Ding; Xiuqin Wu; Yan Gao; Yakun Zhu

doi:10.1016/j.scitotenv.2019.136391

Carrying capacity for vegetation across northern China drylands

Sci Total Environ. 2020 Mar 25:710:136391. doi: 10.1016/j.scitotenv.2019.136391. Epub 2020 Jan 3.

Authors

Jutao Zhang¹, Yuqing Zhang², Shugao Qin³, Bin Wu⁴, Guodong Ding⁴, Xiuqin Wu³, Yan Gao¹, Yakun Zhu¹

Affiliations

¹ Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China.
² 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. Electronic address: zhangyqbjfu@gmail.com.
³ 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.
⁴ 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.

PMID: 31926422
DOI: 10.1016/j.scitotenv.2019.136391

Abstract

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 m²/m²) and Safe-LAI threshold (0.29-0.70 m²/m²) 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.

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

MeSH terms

Biomass
China
Conservation of Natural Resources*
Ecosystem*