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CREA-AA

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    Knowledge about leaf inclination angle distribution is essential for determining the radiation transmission within vegetation canopies and to indirectly quantify canopy attributes such as leaf area index and G-function. For this purpose, we measured and compiled an extensive dataset of leaf inclination angles for 138 deciduous broadleaf woody species commonly found in temperate and boreal ecoclimatic regions. We released an R routine to calculate leaf inclination angle statistics, leaf inclination angle distribution type and G-function from measured leaf inclination angles, which can be used to parametrize optical measurements of light transmittance and for radiative transfer modeling purposes. The leaf inclination angle distribution type can be also used as a plant functional trait to understand light use and photosynthetic plant strategies and to perform functional diversity analyses.

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    We provided long-term stand and canopy structural data from permanent monitoring plots representative of three most diffuse temperate and Mediterranean forests, under different coppice management regimes. Periodic inventories were performed in the surveyed plots since the 70s. Annual litterfall production and its partitioning (leaf, woody, reproductive parts) and optical canopy measurements using the LAI-2000 Plant Canopy Anayzer were performed every year in these plots since the 90s. These data can be used for evaluating the influence of coppice management in the stand and canopy structure, the parametrization of radiative transfer models that require accurate ground truth data, as well as the calibration of high to medium resolution remotely-sensed data.

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    We performed replicated, repeated-measures data of height, diameter and vitality at tree level to allow analysis of the spatial and temporal structure and diversity of  a semi-natural mixed floodplain forest in Italy. Three inventories were performed in 1995, 2005 and 2016 in three ~1 ha plots with varying soil moisture regimes. The use of replicated, repeated-measures data rather than chronosequences allows the examination of true changes in spatial pattern processes through time in this forest type.