Inclusion of photosynthetic activity and exogenous antecedent conditions significantly improves predictability of soil respiratory efflux from multiple microhabitats
Abstract
Because soil respiration (Rsoil) is such a large component of ecosystem carbon flux, it is important to quantify how variations in the major exogenous abiotic (temperature and available moisture) and endogenous biotic (vegetative growth form, phenology) drivers might regulate CO2 efflux under a range of current and projected climate scenarios. A growing body of evidence suggests that antecedent conditions can be important determinants of how Rsoil responds to current environmental factors or resource stimuli. Within a semiarid savanna in southern Arizona, we made concurrent measurements of net photosynthetic uptake and soil respiration throughout an annual period. Due to historical woody plant encroachment, the site is a mosaic of native grasses and woody shrubs, and all measurements were made in association with these two contrasting growth-forms and soil microhabitats. We employed a simple linear model to estimate daily peak photosynthetic rates and a hierarchical Bayesian model to estimate daily Rsoil rates from these field measurements. Using these daily predictions of carbon assimilation and efflux, we developed a hierarchical Bayesian model framework to quantify the influence of antecedent environmental conditions and photosynthetic input on rates of Rsoil within each microhabitat. We specifically focused on quantifying the relative influence of endogenous (due to biotic inputs from previous days' photosynthetic uptake) versus exogenous (as related to current and antecedent soil moisture and temperature conditions) antecedent conditions on the predictability of current rates of Rsoil. Across an entire growing season, current-day Rsoil under mesquite shrubs appeared to be significantly influenced by maximum photosynthetic rates (Amax), and thus carbon input, from up to four days prior. Inclusion of this endogenous antecedent term increased model goodness of fit by 93%. Inclusion of the antecedent Amax term significantly enhanced model fit for the grass microhabitat, but to a lesser extent (by 64%). Antecedent exogenous factors, primarily antecedent soil water conditions were more influential on Rsoil under grasses. Together, these results illustrate the importance of the inclusion of endogenous antecedent conditions and provide a quantifiable link between these above- and below-ground fluxes.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2011
- Bibcode:
- 2011AGUFM.B41E0252B
- Keywords:
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- 0426 BIOGEOSCIENCES / Biosphere/atmosphere interactions;
- 0439 BIOGEOSCIENCES / Ecosystems;
- structure and dynamics