A modelling strategy is proposed to obtain spatially explicit estimates of net carbon accumulation in Italian beech forests. This approach is based on the use of a biogeochemical model, BIOME-BGC, which is capable of simulating all main processes of ecosystems in quasi-equilibrium conditions. The model predictions are then corrected for actual forest biomass (growing stock volume) and stand age. The method is applied to predict the current annual increment (CAI) of 30 beech forest stands in Molise, Central Italy, which have been sampled during several measurement campaigns. A preliminary test is conducted to assess the model’s ability to reproduce the interannual production variations of these stands. Trials are then carried out driving the modelling strategy with both growing stock measurements collected in the field and a recently produced growing stock map. The final CAI estimates are validated through comparison with conventionally collected dendrochronological measurements. The results obtained indicate that the modelling approach is capable of reproducing interannual variations of net primary production and estimating the ground CAIs with an acceptable accuracy and when driven by the mapped growing stock. Additionally, the CAI estimates are not affected by the silvicultural system and development stage of the observed stands.

Mapping the accumulation of woody biomass in Mediterranean beech forests by the combination of BIOME-BGC and ancillary data / Lombardi, F.; Chiesi, M.; Maselli, F.; Di Benedetto, S.; Marchetti, M.; Chirici, G.; Tognetti, R.. - In: CANADIAN JOURNAL OF FOREST RESEARCH. - ISSN 0045-5067. - ELETTRONICO. - (2016), pp. 1122-1131. [10.1139/cjfr-2016-0162]

Mapping the accumulation of woody biomass in Mediterranean beech forests by the combination of BIOME-BGC and ancillary data

CHIRICI, GHERARDO;
2016

Abstract

A modelling strategy is proposed to obtain spatially explicit estimates of net carbon accumulation in Italian beech forests. This approach is based on the use of a biogeochemical model, BIOME-BGC, which is capable of simulating all main processes of ecosystems in quasi-equilibrium conditions. The model predictions are then corrected for actual forest biomass (growing stock volume) and stand age. The method is applied to predict the current annual increment (CAI) of 30 beech forest stands in Molise, Central Italy, which have been sampled during several measurement campaigns. A preliminary test is conducted to assess the model’s ability to reproduce the interannual production variations of these stands. Trials are then carried out driving the modelling strategy with both growing stock measurements collected in the field and a recently produced growing stock map. The final CAI estimates are validated through comparison with conventionally collected dendrochronological measurements. The results obtained indicate that the modelling approach is capable of reproducing interannual variations of net primary production and estimating the ground CAIs with an acceptable accuracy and when driven by the mapped growing stock. Additionally, the CAI estimates are not affected by the silvicultural system and development stage of the observed stands.
2016
1122
1131
Lombardi, F.; Chiesi, M.; Maselli, F.; Di Benedetto, S.; Marchetti, M.; Chirici, G.; Tognetti, R.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1046305
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