4.7 Article

A global meta-analysis on the responses of C and N concentrations to warming in terrestrial ecosystems

Journal

CATENA
Volume 208, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.catena.2021.105762

Keywords

Global climate change; Elevated temperature; Ecological stoichiometry; Plant-soil-microorganism; Soil microbial biomass

Funding

  1. Natural Science Foundation of Jiangsu Province [BE2020673]
  2. Jiangsu Agriculture Science and Technology Innovation Fund [CX(18)3027]
  3. National Natural Science Foundation of China [31672267]

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Global warming increases carbon concentrations in plant leaves, stems, and microbial biomass, as well as nitrogen concentrations in stems, while decreasing soil carbon concentrations and carbon-to-nitrogen ratios. These effects are more pronounced with longer duration and greater magnitude of warming.
Global warming has significantly affected the terrestrial C and N cycling processes. Whereas, it is unclear how global warming impacts the C and N concentrations in the above- and belowground ecosystems. We performed a meta-analysis with the results presented in 136 papers and 1886 observations. The data reveals that global warming increased C concentrations in leaf, shoot, and microbial biomass and N concentrations in the shoot. The C:N ratios of microbial biomass also increased under conditions of warming. However, the soil C concentration and soil C:N ratios decreased. Furthermore, these responses are more evident with longer warming duration and elevated warming magnitudes. The warming effects on C and N concentrations and C:N ratios never changed with warming methods, ecosystem types, or background climates. Also, in response to warming, soil moisture was negatively correlated with leaf C concentration as well as C:N ratio in microbial biomass. Soil pH response to warming was in a negative correlation with those of soil C concentration, soil C:N ratio, and microbial biomass C concentration. Our analysis has identified some key ecosystem processes that can be potentially implemented into the ecosystem models for predicting how warming affects future terrestrial C and N dynamics.

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