Riparian forests are critically endangered many anthropogenic pressures and natural hazards. The importance of riparian zones has been acknowledged by European Directives, involving multi-scale monitoring. The use of this very-high-resolution and hyperspatial imagery in a multi-temporal approach is an emerging topic. The trend is reinforced by the recent and rapid growth of the use of the unmanned aerial system (UAS), which has prompted the development of innovative methodology. Our study proposes a methodological framework to explore how a set of multi-temporal images acquired during a vegetative period can differentiate some of the deciduous riparian forest species and their health conditions. More specifically, the developed approach intends to identify, through a process of variable selection, which variables derived from UAS imagery and which scale of image analysis are the most relevant to our objectives.The methodological framework is applied to two study sites to describe the riparian forest through two fundamental characteristics: the species composition and the health condition. These characteristics were selected not only because of their use as proxies for the riparian zone ecological integrity but also because of their use for river management.The comparison of various scales of image analysis identified the smallest object-based image analysis (OBIA) objects (ca. 1 m 2 ) as the most relevant scale. Variables derived from spectral information (bands ratios) were identified as the most appropriate, followed by variables related to the vertical structure of the forest. Classification results show good overall accuracies for the species composition of the riparian forest (five classes, 79.5 and 84.1 % for site 1 and site 2). The classification scenario regarding the health condition of the black alders of the site 1 performed the best (90.6 %).The quality of the classification models developed with a UAS-based, cost-effective, and semi-automatic approach competes successfully with those developed using more expensive imagery, such as multi-spectral and hyperspectral airborne imagery. The high overall accuracy results obtained by the classification of the diseased alders open the door to applications dedicated to monitoring of the health conditions of riparian forest. Our methodological framework will allow UAS users to manage large imagery metric datasets derived from those dense time series.

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Technology advances can revolutionize Precision Forestry by providing accurate and fine forest information at tree level. This paper addresses the question of how and particularly when Unmanned Aerial System (UAS) should be used in order to efficiently discriminate deciduous tree species. The goal of this research is to determine when is the best time window to achieve an optimal species discrimination. A time series of high resolution UAS imagery was collected to cover the growing season from leaf flush to leaf fall. Full benefit was taken of the temporal resolution of UAS acquisition, one of the most promising features of small drones. The disparity in forest tree phenology is at the maximum during early spring and late autumn. But the phenology state that optimized the classification result is the one that minimizes the spectral variation within tree species groups and, at the same time, maximizes the phenologic differences between species. Sunlit tree crowns (5 deciduous species groups) were classified using a Random Forest approach for monotemporal, two-date and three-date combinations. The end of leaf flushing was the most efficient single-date time window. Multitemporal datasets definitely improve the overall classification accuracy. But single-date high resolution orthophotomosaics, acquired on optimal time-windows, result in a very good classification accuracy (overall out of bag error of 16%).

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Aim: Formalized classifications synthesizing vegetation data at the continental scale are being attempted only now, although they are of key importance for nature conservation planning. Therefore, we aim to provide a vegetation classification and to describe the main biogeographical patterns of floodplain forests and alder carrs in Europe. Location: Europe.Methods: A database of more than 40 000 vegetation plots of floodplain forests and alder carrs across Europe was compiled. After geographic stratification, 16 392 plots were available for classification, which was performed using the supervised method Cocktail. We also searched for new associations using semi-supervised Kmeans classification. The main biogeographic patterns and climate-related gradients in species composition were determined using detrended correspondence analysis and cluster analysis.Results: Thirty associations of floodplain forests and alder carrs were distinguished, which belong to five alliances. The Alnion incanae includes riparian, seepage and hardwood floodplain forests in the nemoral and hemiboreal zones (dominated by Alnus glutinosa and Fraxinus excelsior) and in the boreal zone (dominated by A. incana). The Osmundo-Alnion represents oceanic vegetation dominated by Alnus glutinosa, Fraxinus angustifolia and F. excelsior distributed mostly on the Iberian Peninsula and composed of species with Atlantic distribution and Iberian endemics. The Populion albae comprises floodplain forests frequently dominated by Fraxinus angustifolia, Populus alba and P. nigra that are widespread in floodplains of large rivers under summer-dry climates in the Mediterranean region. The Platanion orientalis represents eastern Mediterranean floodplain forests dominated by Platanus orientalis. The Alnion glutinosae includes forest swamps dominated by Alnus glutinosa distributed mostly in the nemoral and hemiboreal zones. The main biogeographic patterns within European floodplain forests and alder carrs reflect the climatic contrasts between the Mediterranean, nemoral, boreal and mountain regions. Oceanic floodplain forests differ from those in the rest of Europe. The hydrological regime appears to be the most important factor influencing species composition within regions.Conclusions: This study is the first applying a formalized classification at the association level for a broad vegetation type at the continental scale. The proposed classification provides the scientific basis for the necessary improvement of the habitat classification systems used in European nature conservation.

The growth of past, present, and future forests was, is and will be affected by climate variability. This multifaceted relationship has been assessed in several regional studies, but spatially resolved, large-scale analyses are largely missing so far. Here we estimate recent changes in growth of 5800 beech trees (Fagus sylvatica L.) from 324 sites, representing the full geographic and climatic range of species. Future growth trends were predicted considering state-of-the-art climate scenarios. The validated models indicate growth declines across large region of the distribution in recent decades, and project severe future growth declines ranging from −20% to more than −50% by 2090, depending on the region and climate change scenario (i.e. CMIP6 SSP1-2.6 and SSP5-8.5). Forecasted forest productivity losses are most striking towards the southern distribution limit of Fagus sylvatica, in regions where persisting atmospheric high-pressure systems are expected to increase drought severity. The projected 21st century growth changes across Europe indicate serious ecological and economic consequences that require immediate forest adaptation.

Five commercial tree species comprise nearly 80% of the forest standing stock volume in Western Europe. Nowadays, there is a strong need to consider a wider diversity of tree species, as evidenced by the impact of climate change and the forest health crises over the past decades. In this context, this study focuses on the potential of birch (Betula pendula Roth and Betula pubescens Ehrh.), a neglected indigenous species, for forestry and the forest-based industry sector. We have therefore compiled, analyzed, and discussed literature regarding the strengths and weaknesses of the species and the opportunities and threats of its use for this purpose. Among the strengths, birch tolerates various climates and sites, and high genetic variability promotes its adaptability. Birch improves forest resilience by colonizing forest gaps and quickly increasing soil functioning and biodiversity. Birch is also remarkably resistant to game overpopulation-associated damage. Large-sized logs are produced within relatively short periods with proper silvicultural treatment, and the wood characteristics allow versatile and valuable uses, as shown in Northern Europe. However, its weaknesses include high sensitivity to crown competition and to wood rot as challenges for silviculture. Among the opportunities, birch is well-suited to the global changes with its adaptability to climate change and its possible integration in diverse productive mixed tree stands. In the context of societal evolutions and customer perceptions, birch wood could play an increasing role in the building and furniture sectors, and among non-wood forest products. In Western Europe, the main obstacle to birch development is the lack of information on the wood uses and, consequently, the lack of interest among forest managers and wood processing professionals, which have led to a poor quality of the resource and to insufficient demand for its wood. Moreover, its fast height growth can affect the vitality of other species in mixed stands. Our analysis highlighted the potential of birch in the Western European forestry considering societal, ecological, and economic purposes in a changing climatic and socio-economic context and the need to (i) develop opportunities for industrial uses of birch wood, (ii) inform forest owners, managers, and industrial professionals about the potential value of birch, and (iii) define silvicultural guidelines.