Plants display a large number of traits which are reflected in physiological and ecological functions (functional traits). Leaf traits are amongst the most important functional traits. However, a great challenge in measuring leaf traits in the field is that direct methods are limited by the cost of the instruments and the time and work required by direct measurements, which are often destructive. As an alternative, we developed and tested a non-destructive methodology to assess a suite of leaf traits using different digital photographic approaches, with the intimate aim to develop a rapid, robust and cheap protocol for leaf trait measurements in the field. The proposed digital photographic approaches were tested in broadleaved tree species Digital photography allowed to assess a morphological foliar trait (leaf area; LA) and physiological foliar traits (leaf reflectance in red (R), green (G) and blue (B) bands; leaf venation attributes). Leaf area derived from photography significantly agreed with that directly measured with a leaf area meter (LA<inf>PHOTO</inf> = 0.98 LA<inf>AREA METER</inf> + 0.84, R² = 0.99, p < 0.001); leaf reflectance in the R, G, B channels derived from photography significantly agreed with that directly measured with a field spectroradiometer (SPEC) (R<inf>PHOTO</inf> = 0.77 R<inf>SPEC</inf> + 0.05, R² = 0.61, p < 0.001; G<inf>PHOTO</inf> = 0.79 G<inf>SPEC</inf> + 0.06, R² = 0.58, p < 0.001; B<inf>PHOTO</inf> = 0.56 B<inf>SPEC</inf> + 0.00, R² = 0.51, p < 0.001). Leaf venation traits estimated from photography agreed to within ±20% measurements obtained in cleared leaves of the same species. Based on the obtained results, we demonstrated that digital photography can be an effective tool to obtain a fast, cheap, reliable and non-destructive assessment of morphological and physiological leaf traits in broadleaf tree species, being highly suitable for use in long-term research and monitoring programs. © 2019 Elsevier Ltd

Key message: We provided long-term stand and canopy structural data from permanent monitoring plots representative of some most diffuse temperate and Mediterranean forests, under different coppice management regimes. Periodic inventories were performed in the surveyed plots since the 1970s. Annual litterfall production and its partitioning (leaf, woody, reproductive parts) and optical canopy measurements using the LAI-2000 Plant Canopy Analyzer were performed every year in fully equipped plots since the 1990s. 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, and the calibration of high to medium resolution remotely sensed data. Dataset access is at https://doi.org/10.17632/z8zm3ytkcx.2. Associated metadata is available at https://agroenvgeo.data.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/2bd2d77f-3cf8-43da-b1b5-9f8196dc017f . © 2019, INRA and Springer-Verlag France SAS, part of Springer Nature.

Estimates of clumping index (Ω) are required to improve the indirect estimation of leaf area index (L) from optical field-based instruments such as digital hemispherical photography (DHP). A widely used method allows estimation of Ω from DHP using simple gap fraction averaging formulas (LX). This method is simple and effective but has the disadvantage of being sensitive to the spatial scale (i.e., the azimuth segment size in DHP) used for averaging and canopy density. In this study, we propose a new method to estimate Ω (LXG) based on ordered weighted gap fraction averaging (OWA) formulas, which addresses the disadvantages of LX and also accounts for gap size distribution. The new method was tested in 11 broadleaved forest stands in Italy; Ω estimated from LXG was compared with other commonly used clumping correction methods (LX, CC, and CLX). Results showed that LXG yielded more accurate Ω estimates, which were also more correlated with the values obtained from the gap size distribution methods (CC and CLX) than Ω obtained from LX. Leaf area index estimates, adjusted by LXG, are only 5%–6% lower than direct measurements obtained from litter traps, while other commonly used clumping correction methods yielded more underestimation. © 2019, Canadian Science Publishing. All rights reserved.