Mapping biocrust distribution in China's drylands under changing climate

Sci Total Environ. 2023 Dec 20:905:167211. doi: 10.1016/j.scitotenv.2023.167211. Epub 2023 Sep 18.

Abstract

Biological soil crusts (biocrusts) are widely distributed in global drylands and have multiple significant roles in regulating dryland soil and ecosystem multifunctionality. However, maps of their distribution over large spatial scales are uncommon and sometimes unreliable, because our current remote sensing technology is unable to efficiently discriminate between biocrusts and vascular plants or even bare soil across different ecosystem and soil types. The lack of biocrust spatial data may limit our ability to detect risks to dryland function or key tipping points. Here, we indirectly mapped biocrust distribution in China's drylands using spatial prediction modeling, based on a set of occurrences of biocrusts (379 in total) and high-resolution soil and environmental data. The results showed that biocrusts currently cover 13.9 % of China's drylands (or 5.7 % of China's total area), with moss-, lichen-, and cyanobacterial-dominated biocrusts each occupying 5.7 % to 10.7 % of the region. Biocrust distribution is mainly determined by soil properties (soil type and contents of gravel and nitrogen), aridity stress, and altitude. Their most favorable habitat is arenosols with low contents of gravel and nitrogen, in climate with a drought index of 0.54 and an altitude of about 500 m. By 2050, climate change will lead to a 5.5 %-9.0 % reduction in biocrust cover. Lichen biocrusts exhibit a high vulnerability to climate change, with potential reductions of up to 19.0 % in coverage. Biocrust cover loss is primarily caused by the combined effects of the elevated temperature and increased precipitation. Our study provides the first high-resolution (250 × 250 m) map of biocrust distribution in China's drylands and offers a reliable approach for mapping regional or global biocrust colonization. We suggest incorporating biocrusts into Earth system models to identify their significant impact on global or regional-scale processes under climate change.

Keywords: Biological soil crust; Climate change; Dryland; Spatial distribution; Spatial prediction modeling.

MeSH terms

  • Bryophyta* / physiology
  • China
  • Climate Change
  • Cyanobacteria* / physiology
  • Ecosystem
  • Lichens* / physiology
  • Nitrogen
  • Soil
  • Soil Microbiology

Substances

  • Soil
  • Nitrogen