4.7 Article

Linking temperature sensitivity of soil CO2 release to substrate, environmental, and microbial properties across alpine ecosystems

Journal

GLOBAL BIOGEOCHEMICAL CYCLES
Volume 30, Issue 9, Pages 1310-1323

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2015GB005333

Keywords

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Funding

  1. National Basic Research Program of China on Global Change [2014CB954001, 2015CB954201]
  2. National Natural Science Foundation of China [31322011, 41371213]
  3. Chinese Academy of Sciences-Peking University Pioneer Collaboration Team
  4. Thousand Young Talents Program

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Our knowledge of fundamental drivers of the temperature sensitivity (Q(10)) of soil carbon dioxide (CO2) release is crucial for improving the predictability of soil carbon dynamics in Earth System Models. However, patterns and determinants of Q(10) over a broad geographic scale are not fully understood, especially in alpine ecosystems. Here we addressed this issue by incubating surface soils (0-10 cm) obtained from 156 sites across Tibetan alpine grasslands. Q(10) was estimated from the dynamics of the soil CO2 release rate under varying temperatures of 5-25 degrees C. Structure equation modeling was performed to evaluate the relative importance of substrate, environmental, and microbial properties in regulating the soil CO2 release rate and Q(10). Our results indicated that steppe soils had significantly lower CO2 release rates but higher Q(10) than meadow soils. The combination of substrate properties and environmental variables could predict 52% of the variation in soil CO2 release rate across all grassland sites and explained 37% and 58% of the variation in Q(10) across the steppe and meadow sites, respectively. Of these, precipitation was the best predictor of soil CO2 release rate. Basal microbial respiration rate (B) was the most important predictor of Q(10) in steppe soils, whereas soil pH outweighed B as the major regulator in meadow soils. These results demonstrate that carbon quality and environmental variables coregulate Q(10) across alpine ecosystems, implying that modelers can rely on the carbon-quality temperature hypothesis for estimating apparent temperature sensitivities, but relevant environmental factors, especially soil pH, should be considered in higher-productivity alpine regions.

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