The number of spots to monitor to evaluate soil respiration (Rs) is often chosen on an empirical or conventional basis. To obtain an insight into the necessary number of spots to account for Rs variability in a Mediterranean pine-dominated mixed forest, we measured Rs 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 Rs 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.

Accounting for soil respiration variability – Case study in a Mediterranean pine-dominated forest / O. Pantani, F. Fioravanti, F.M. Stefanini, R. Berni, G. Certini. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 10:1(2020), pp. 1787.1-1787.10. [10.1038/s41598-020-58664-6]

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

F.M. Stefanini;
2020

Abstract

The number of spots to monitor to evaluate soil respiration (Rs) is often chosen on an empirical or conventional basis. To obtain an insight into the necessary number of spots to account for Rs variability in a Mediterranean pine-dominated mixed forest, we measured Rs 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 Rs 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.
Carbon cycle; global warming; environmental monitoring; statistical modeling; soil chemistry
Settore SECS-S/01 - Statistica
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/834719
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