Chiesi, M.; Fibbi, L.; Vanucci, S.; Maselli, F. Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes. Remote Sens.2024, 16, 232.
Chiesi, M.; Fibbi, L.; Vanucci, S.; Maselli, F. Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes. Remote Sens. 2024, 16, 232.
Chiesi, M.; Fibbi, L.; Vanucci, S.; Maselli, F. Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes. Remote Sens.2024, 16, 232.
Chiesi, M.; Fibbi, L.; Vanucci, S.; Maselli, F. Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes. Remote Sens. 2024, 16, 232.
Abstract
The current communication presents the application of a consolidated model combination strategy to analyze the medium-term carbon fluxes in two Mediterranean pine wood ecosystems. The modelling strategy is based on the use of a NDVI-driven parametric model, Modified C-Fix, and of a bio-geochemical model, BIOME-BGC, the outputs of which are combined taking into account the actual development phase of each ecosystem. The two pine ecosystems examined correspond to an old-growth forest and to a secondary succession after clearcuts, which differently respond to the same climatic condition during a ten-year period (2013-2022). Increasing dryness, in fact, exerts a fundamental role in controlling the gross primary and net ecosystem production of the mature stand, while the effect of forest regeneration is prevalent for the uprising of the same variables in the other stand. In particular, the simulated net carbon exchange fluctuates around 200 g C m-2 year-1 in the first stand and rises to over 600 g C m-2 year-1 in the second stand; correspondingly, the accumulation of new biomass is nearly undetectable in the former case while becomes notable in the latter. The study therefore supports the potential of the applied strategy for predicting the forest carbon balances consequent on diversified natural and human-induced factors.
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