Key message: ICP Forests relies on a representative pan-European network based on a 16 × 16 km grid-net covering around 6000 plots. Dead wood volumes for 3243 plots, related to 19 European Countries, are presented in this data paper as a result of harmonised sampling procedure, and under compliance with FAIR Data Principles. Dataset access is at https://zenodo.org/record/1467784. Associated metadata are available athttps://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/a27d2a8f-1a2d-4a1c-b932-86ec5f4bd8a6(link to geo-network provided after acceptance). Context: ICP-Forests dataset represents unique opportunity for the assessment of forest resources sustainability and biodiversity in Europe because it monitors the status of forests under a coordinated Pan-European umbrella by standardised methods. Aims: The main goal of this paper is to provide standardized estimates of deadwood volume at European scale for a broader use among forest scientists. Methods: After quality checks, calculations of deadwood volumes distinguished by deadwood types (standing and lying dead trees, snags, coarse woody debris, stumps) have been performed. The obtained plot level data have been joined to available forest stand information (namely: forest type, forest management, and stand age) over 3,243 plots among Europe. Results: The database provides a basis for the evaluation of combined relationships between deadwood volume and forest type, deadwood type, decay status, forest management, and stand age classes at European level. Conclusion: Deadwood volume and quality is recognized as one of the most important source of information for forest biodiversity. Here, first results of a systematic and standardized European survey scheme for assessing deadwood volume are presented. This ICP Forests datasets analysis represents the base for further analysis and relationships. © 2019, INRA and Springer-Verlag France SAS, part of Springer Nature.

Mixed forests are particularly interesting for forest structure and diversity analyses, as higher complexity and diversity can be expected in these forests compared to pure ones. Integrating different approaches in the analyses of structure and diversity in these forests can provide complementary information on non-spatial, spatial and functional diversity patterns. The study aimed at evaluating the spatio-temporal dynamics in forest structure and diversity in a semi-natural mixed oak-hornbeam floodplain forest. All standing trees were mapped and inventoried in 1995, 2005 and 2016 in three 1-ha mixed forest stands, with different soil moisture regime (xeric, mesic, moist conditions). Traditional, non-spatial structure and diversity measures were coupled with spatially-explicit and functional diversity measures. Results indicated that the three stands showed limited variation in stand structure and similar non-spatial diversity attributes, despite the different species composition. Only the extension to spatial and functional analyses was able to reveal more pronounced differences of diversity patterns, as higher complexity, species mingling, and functional tree complementarity was observed in the moister stand. These findings support use of spatially-explicit measurements in traditional inventory measurement protocols to allow more refined analysis of diversity patterns. On the other hand, functional diversity can be easily implemented in diversity analyses, as it requires species abundance information (which is traditionally collected in forest inventory) and species-specific tree traits which can be inferred from literature. © 2019 Elsevier Ltd

Several studies reveal that there is a strong interconnection between climate change and biodiversity. Indeed, estimating plant biodiversity is an important issue under forest ecosystem monitoring, which allows the evaluation of carbon storage and sequestration capacity. To this end, a two-phase strategy, suitably compatible with the most adopted sampling designs in large-scale forest inventories, is proposed. In the first phase, tessellation stratified sampling is performed by partitioning the study area into a grid of quadrats and by randomly selecting a point in each quadrat. The first-phase points are classified as forest or nonforest using remotely sensed imagery. In the second phase, a sample of points is selected from those classified as forest by means of simple random sampling without replacement. The second-phase points constitute the centers of circular plots that are visited in the field to record plant species (usually trees) and their abundance. Estimators of abundance and diversity and estimators of their variances are presented. The proposed strategy is applied in a forest area from Central Italy, as a case study. With respect to the sampling effort, the resulting estimates of relative standard errors are satisfactory, especially those regarding the overall total and diversity index estimators. The proposed statistical approach represents a suitable reference for integrated forest inventory frameworks effectively supporting biodiversity monitoring and assessment. © 2018 John Wiley & Sons, Ltd.

Accurate inventory and mapping of olive (Olea europaea L.) tree attributes represents a central issue to support the olive production system. With reference to the cultivation, there is a high heterogeneity and complexity in the cultivation of olive trees, which is reflected in the large variability in olive grove surfaces. This poses some challenge in accurately estimating olive tree attributes via traditional inventory approaches, as commonly adopted in national forest inventory. From a methodological point of view, the complexity and heterogeneity of olive tree groves can be comparable to the problem of accurately estimating tree outside forests (TOF) attributes. In this study, we tested whether a plot sampling approach formerly developed for TOF is suitable for estimating olive tree attributes at large scale. We tested this approach in a case study where the census of the olive crop area and the number of olive groves was conducted from photo-interpretation of high resolution aerial orthoimagery, used as benchmark to test the effectiveness of the plot sampling approach. The main result of this study is that the plot sampling method can be applied for estimating olive tree attributes. Our obtained RSEs were below 20%, with a limited sampling effort of about 6% of the studied population; the obtained RSEs were below 6% when increasing sampling up to about 21% the studied population. Using robust statistical procedures among countries, should allow obtaining harmonized and comparable information, which can increase the knowledge of olive geographical distribution and structure at its relevant Mediterranean scale. © 2019, Italian Society of Remote Sensing. All rights reserved.

Water availability is a major limiting factor in plant productivity and plays a key role in plant species distribution over a given area. New technologies, such as terahertz quantum cascade lasers (THz‐QCLs) have proven to be non‐invasive, effective, and accurate tools for measuring and monitoring leaf water content. This study explores the feasibility of using an advanced THz-QCL device for measuring the absolute leaf water content in Corylus avellana L., Laurus nobilis L., Ostrya carpinifolia Scop., Quercus ilex L., Quercus suber L., and Vitis vinifera L. (cv. Sangiovese). A recently proposed, simple spectroscopic technique was used, consisting in determining the transmission of the THz light beam through the leaf combined with a photographic measurement of the leaf area. A significant correlation was found between the product of the leaf optical depth (τ) and the leaf surface area (LA) with the leaf water mass (Mw) for all the studied species (Pearson’s r test, p ≤ 0.05). In all cases, the best fit regression line, in the graphs of τLA as a function of Mw, displayed R2 values always greater than 0.85. The method proposed can be combined with water stress indices of plants in order to gain a better understanding of the leaf water management processes or to indirectly monitor the kinetics of leaf invasion by pathogenic bacteria, possibly leading to the development of specific models to study and fight them. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.

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.