Please use this identifier to cite or link to this item:
http://hdl.handle.net/2067/2674
Title: | Prediction of forest NPP in Italy by the combination of ground and remote sensing data | Authors: | Chirici, Gherardo Chiesi, Marta Corona, Piermaria Puletti, Nicola Mura, Matteo Maselli, Fabio |
Keywords: | Modified C-Fix BIOME-BGC;Forest inventory;Current annual increment;Regional estimates;Italy | Issue Date: | May-2015 | Publisher: | Springer-Verlag | Source: | Chirici, G. et al. 2015. Prediction of forest NPP in Italy by the combination of ground and remote sensing data. "European Journal of Forest Research" 134 (3): 453-467 | Abstract: | Our research group has recently proposed a strategy to simulate net forest carbon fluxes based on the coupling of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical model, BIOME-BGC. The outputs of the two models are combined through the use of a proxy of ecosystem distance from equilibrium condition which accounts for the occurred disturbances. This mod- eling strategy is currently applied to all Italian forest areas using an available set of NDVI images and ancillary data descriptive of an 8-year period (1999–2006). The obtained estimates of forest net primary production (NPP) are first analyzed in order to assess the importance of the main model drivers on relevant spatial variability. This analysis indicates that growing stock is the most influential model driver, followed by forest type and meteorological vari- ables. In particular, the positive influence of growing stock on NPP can be constrained by thermal and water limitations, which are most evident in the upper mountain and most southern zones, respectively. Next, the NPP estimates, aggregated over seven main forest types and twenty administrative regions in Italy, are converted into current annual increment of standing volume (CAI) by specific coefficients. The accuracy of these CAI estimates is finally assessed by comparison with the ground data collected during a recent national forest inventory. The results ob- tained indicate that the modeling approach tends to overestimate the ground CAI for most forest types. In particular, the overestimation is notable for forest types which are mostly managed as coppice, while it is negligible for high forests. The possible origins of these phenomena are investigated by examining the main model drivers to- gether with the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis. |
URI: | http://hdl.handle.net/2067/2674 | ISSN: | 1612-4669 | DOI: | 10.1007/s10342-015-0864-4 |
Appears in Collections: | DiSAFRi - Archivio della produzione scientifica |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EJFR_ppn_Italy_1.pdf | 42.72 kB | Adobe PDF | View/Open |
SCOPUSTM
Citations
10
18
Last Week
0
0
Last month
0
0
checked on Sep 18, 2023
Page view(s)
177
Last Week
0
0
Last month
3
3
checked on Mar 16, 2024
Download(s)
175
checked on Mar 16, 2024
Google ScholarTM
Check
Altmetric
All documents in the "Unitus Open Access" community are published as open access.
All documents in the community "Prodotti della Ricerca" are restricted access unless otherwise indicated for specific documents