Modeling temporal and large‐scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

Abstract

[1] Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 mmol m À2 s À1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q 10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by Raich et al. [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 17, NO. 4, 1104, doi:10.1029/2003GB002035, 2003 15 -1 index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.INDEX TERMS: 1615 Global...

Inverse estimation of Vcmax, leaf area index, and the Ball‐Berry parameter from carbon and energy fluxes

“…[59] Reichstein et al [2003] used an elaborate model inversion approach in which Vc max -m and LAI-m were independently fitted to Fc and LE relationships. Using a single response variable to fit two parameters, they averaged the best fit parameter combination for Fc and LE to infer the pair of either Vc max -m or LAI-m relationships that best fit the two fluxes.…”

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Partitioning sources of soil‐respired CO2 and their seasonal variation using a unique radiocarbon tracer

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Evaluation of effects of sustained decadal precipitation manipulations on soil carbon stocks

“…Numerous studies have shown that decomposition rates are lower during drier soil conditions independent of a change in temperature (e.g. Reichstein et al 2003;Borken et al 2006). Soil moisture may, however, aVect microbial activity negatively both during dry conditions by limiting the availability of water, and during wet conditions by limiting diVusion of O 2 through the soil.…”