Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes
-
Published:2024-01-06
Issue:2
Volume:16
Page:232
-
ISSN:2072-4292
-
Container-title:Remote Sensing
-
language:en
-
Short-container-title:Remote Sensing
Author:
Chiesi Marta1ORCID, Fibbi Luca12ORCID, Vanucci Silvana3, Maselli Fabio1ORCID
Affiliation:
1. CNR IBE, 50019 Sesto Fiorentino, Italy 2. LaMMA Consortium, 50019 Sesto Fiorentino, Italy 3. Department of Chemical, Biological, Pharmaceutical and Environmental Sciences (ChiBioFarAm), University of Messina, 98166 Messina, Italy
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. This strategy is based on the use of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical 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.
Subject
General Earth and Planetary Sciences
Reference24 articles.
1. Waring, H.R., and Running, S.W. (2007). Analysis at Multiples Scales, Academic Press. [3rd ed.]. 2. A large and persistent carbon sink in the world’s forests;Pan;Science,2011 3. Su, Y., Zhang, W., Liu, B., Tian, X., Chen, S., Wang, H., and Mao, Y. (2022). Forest carbon flux simulation using multi-source data and incorporation of remotely sensed model with process-based model. Remote Sens., 14. 4. Yan, M., Tian, X., Li, Z., Chen, E., Wang, X., Han, Z., and Sun, H. (2016). Simulation of forest carbon fluxes using model incorporation and data assimilation. Remote Sens., 8. 5. An integrated remote sensing and model approach for assessing forest carbon fluxes in China;Zhao;Sci. Total Environ.,2022
|
|