Towards the harmonization between National Forest Inventory and Forest Condition Monitoring. Consistency of plot allocation and effect of tree selection methods on sample statistics in Italy - Gasparini, Patrizia; Di Cosmo, Lucio; Cenni, Enrico; Pompei, Enrico; Ferretti, Marco (ENVIRONMENTAL MONITORING AND ASSESSMENT, 2013)
In the frame of a process aiming at harmonizing National Forest Inventory (NFI) and ICP Forests Level I Forest Condition Monitoring (FCM) in Italy, we investigated (a) the long-term consistency between FCM sample points (a subsample of the first NFI, 1985, NFI_1) and recent forest area estimates (after the second NFI, 2005, NFI_2) and (b) the effect of tree selection method (tree-based or plot-based) on sample composition and defoliation statistics. The two investigations were carried out on 261 and 252 FCM sites, respectively. Results show that some individual forest categories (larch and stone pine, Norway spruce, other coniferous, beech, temperate oaks and cork oak forests) are over-represented and others (hornbeam and hophornbeam, other deciduous broadleaved and holm oak forests) are under-represented in the FCM sample. This is probably due to a change in forest cover, which has increased by 1,559,200 ha from 1985 to 2005. In case of shift from a tree-based to a plot-based selection method, 3,130 (46.7 %) of the original 6,703 sample trees will be abandoned, and 1,473 new trees will be selected. The balance between exclusion of former sample trees and inclusion of new ones will be particularly unfavourable for conifers (with only 16.4 % of excluded trees replaced by new ones) and less for deciduous broadleaves (with 63.5 % of excluded trees replaced). The total number of tree species surveyed will not be impacted, while the number of trees per species will, and the resulting (plot-based) sample composition will have a much larger frequency of deciduous broadleaved trees. The newly selected trees have-in general-smaller diameter at breast height (DBH) and defoliation scores. Given the larger rate of turnover, the deciduous broadleaved part of the sample will be more impacted. Our results suggest that both a revision of FCM network to account for forest area change and a plot-based approach to permit statistical inference and avoid bias in the tree sample composition in terms of DBH (and likely age and structure) are desirable in Italy. As the adoption of a plot-based approach will keep a large share of the trees formerly selected, direct tree-by-tree comparison will remain possible, thus limiting the impact on the time series comparability. In addition, the plot-based design will favour the integration with NFI_2.
The following values have no corresponding Zotero field: pub-location: VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS publisher: SPRINGER
Keywords: Forest condition monitoring; Forest inventory; Italy; Plot allocation; Sample statistics; Tree selection methods

Aboveground tree volume and phytomass prediction equations for forest species in Italy - Tabacchi, Giovanni; Di Cosmo, Lucio; Gasparini, Patrizia (European Journal of Forest Research, 2011)
In this article, we present equations derived for the prediction of the aboveground tree volume and phytomass for twenty-ﬁve of the most important forest species growing in Italy. These equations result from ongoing research aiming to ﬁll a gap in the models available at the national scale. With regard to volume, the results are particularly important for thirteen species or groups of species that were once scaled with models, conventionally assumed as reference models, available for other species. In Italy, phytomass models had never been constructed at the national level before. For any single tree, speciﬁc equations allow estimations of the following tree components to be made: stem and large branches (for either volume or phytomass), small branches (phytomass), stump (phytomass) and the whole tree phytomass. The models have been constructed on the basis of nearly 1,300 sampling units (sample trees). Although these equations must be considered intermediate results of the ongoing research because only half the scheduled number of samples has been collected, they have already been used in the practice, for example in the estimates reported in the recently published second national forest inventory.
Keywords: Aboveground tree phytomass; Phytomass prediction equations; Tree biomass; Volume functions; Volume prediction equations