Accounting for soil respiration variability - Case study in a Mediterranean pine-dominated forest

The number of spots to monitor to evaluate soil respiration (R_s) is often chosen on an empirical or conventional basis. To obtain an insight into the necessary number of spots to account for R_s variability in a Mediterranean pine-dominated mixed forest, we measured R_s all year long on sixteen dates with a portable gas-analyser in 50 spots per date within an area 1/3 ha wide. Linear mixed-effects models with soil temperature and litter moisture as descriptors, were fitted to the collected data and then evaluated in a Monte Carlo simulation on a progressively decreasing number of spots to identify the minimum number required to estimate R_s with a given confidence interval. We found that monitoring less than 14 spots would have resulted in a 10% probability of not fitting the model, while monitoring 20 spots would have reduced the same probability to about 5% and was the best compromise between field efforts and quality of the results. A simple rainfall index functional to select sampling dates during the summer drought is proposed.