Predicting the responsiveness of soil biodiversity to deforestation: a cross-biome study

Glob Chang Biol. 2014 Sep;20(9):2983-94. doi: 10.1111/gcb.12565. Epub 2014 Apr 1.

Abstract

The consequences of deforestation for aboveground biodiversity have been a scientific and political concern for decades. In contrast, despite being a dominant component of biodiversity that is essential to the functioning of ecosystems, the responses of belowground biodiversity to forest removal have received less attention. Single-site studies suggest that soil microbes can be highly responsive to forest removal, but responses are highly variable, with negligible effects in some regions. Using high throughput sequencing, we characterize the effects of deforestation on microbial communities across multiple biomes and explore what determines the vulnerability of microbial communities to this vegetative change. We reveal consistent directional trends in the microbial community response, yet the magnitude of this vegetation effect varied between sites, and was explained strongly by soil texture. In sandy sites, the difference in vegetation type caused shifts in a suite of edaphic characteristics, driving substantial differences in microbial community composition. In contrast, fine-textured soil buffered microbes against these effects and there were minimal differences between communities in forest and grassland soil. These microbial community changes were associated with distinct changes in the microbial catabolic profile, placing community changes in an ecosystem functioning context. The universal nature of these patterns allows us to predict where deforestation will have the strongest effects on soil biodiversity, and how these effects could be mitigated.

Keywords: Deforestation; Ecosystem functioning; Metagenomic sequencing; Microbial community; Soil Biodiversity.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Analysis of Variance
  • Base Sequence
  • Biodiversity*
  • Carbon Dioxide / metabolism
  • Conservation of Natural Resources / statistics & numerical data*
  • Fatty Acids / metabolism
  • Forests*
  • High-Throughput Nucleotide Sequencing
  • Linear Models
  • Microbiota / genetics*
  • Molecular Sequence Data
  • Puerto Rico
  • Soil / chemistry*
  • Soil Microbiology*
  • Species Specificity
  • United States

Substances

  • Fatty Acids
  • Soil
  • Carbon Dioxide