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Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR-species20K dataset
Puliti , Stefano , Lines , Emily R. , Müllerová , Jana , Frey , Julian , Schindler , Zoe , Straker , Adrian , Allen , Matthew J. , Winiwarter , Lukas , Rehush , Nataliia , Hristova , Hristina S. , Murray , Brent A. , Calders , Kim , Coops , Nicholas C. , Höfle , Bernhard , Irwin , Liam A.K. , Junttila , Samuli , Kruček , Martin , Krok , G. , Král , Kamil , Levick , Shaun R. , Lück , Linda , Missarov , Azim , Mokroš , M. , Owen , Harry Jon Foord , Stereńczak , Krzysztof Jan , Pitkänen , Timo P. , Puletti , Nicola , Saarinen , Ninni , Hopkinson , Chris Dennis , Terryn , Louise , Torresan , C. , Tomelleri , Enrico , Weiser , Hannah , Astrup , Rasmus
lidar remote sensing biodiversity deep learning point cloud classification single-tree inventory
Mostra abstract
Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single-tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification. To address the above limitations, we compiled the FOR-species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR-species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view 2D-based methods (SimpleView, DetailView, YOLOv5). 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods. © 2025 The Author(s). Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
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2025
Rivista
Methods in Ecology and Evolution
Dettagli
Vol. 16 (4) pp. 801 - 818
DOI
Managed forests are a stronghold of non-native beetles in Europe
Basile , Marco , Lachat , Thibault , Balducci , Lorenzo , Chianucci , Francesco , Chojnacki , Lucas , Archaux , Frédéric , N Avtzis , Dimitrios N. , Bouget , Christophe , de Smedt , Pallieter , Doerfler , Inken , Dumas , Yann , Elek , Zoltán , Gosselin , Marion , Goßner , Martin M. , Heilmann-Clausen , Jacob , Hofmeister , Jeňýk , Hošek , Jan , Janssen , Philippe , Justesen , Mathias Just , Hansen , Aslak Kappel , Schmidt , Inger Kappel , Kepfer-Rojas , Sebastian , Mårell , Anders , Matula , Radim , Müller , Jörg C. C. , Nordén , Björn , Ódor , Péter , Paillet , Yoan , Ravera , Sonia , Sitzia , Tommaso , Tinya , Flóra , Burrascano , Sabina , Brockerhoff , Eckehard G.
biodiversity biological invasions biotic resistance coleoptera unmanaged forests vascular plants
Mostra abstract
The species richness of vascular plants in forests can have contrasting effects on the occurrence of non-native insects. The establishment of non-native insect populations may be facilitated by low plant species richness, which reflects the availability of few but easily accessible resources, or hampered by high plant species richness due to spatial dilution of resources or biotic resistance (i.e., resistance against biological invasions). The relationship between the species richness of plants and non-native insects is likely influenced by disturbance regimes, which, in European forests, mostly consists of timber harvesting. We investigated this relationship considering two major forest attributes: (i) species richness of non-native vascular plants and (ii) forest management. From 1101 forest plots in Europe, we gathered occurrences of 1212 vascular plant species, including 160 non-native species, and of 2404 beetle species, including 29 non-native species. We tested the relationship between the species richness of non-native beetles and plants using non-linear quantile regressions. We disentangled the effect of non-native plant species richness from that of management on the species richness of non-native beetles, while accounting for forest structural variables, using structural equation models. We found clear evidence of a hump-shaped relationship between non-native beetle and plant species richness. The general shape of the relationship persisted when considering only woody or non-woody plants, as well as only non-native plants. The relationship was also similar between managed and unmanaged forests. However, the proportion of non-native beetles in managed forests was higher than in unmanaged forests at the same plant species richness. Management had a direct negative effect on non-native beetle species richness, whereas non-native plant species richness had a direct positive effect. When considering all direct and indirect effects, management facilitated the occurrence of non-native beetles indirectly via non-native plants rather than directly. Synthesis and applications. Species richness of native and non-native vascular plants modulates the species richness of non-native beetles through relationships with opposite signs. The interplay with management regimes and forest structures determines whether non-native beetles are promoted. Forest management aimed at reducing the intensity of disturbance while encouraging native plant species richness could promote the dominance of dilution effects and biotic resistance and could moderate the establishment of non-native insects. © 2025 The Author(s). Journal of Applied Ecology © 2025 British Ecological Society.
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2025
Rivista
Journal of Applied Ecology
Dettagli
Vol. 62 (5) pp. 1243 - 1257
DOI
Handbook of field sampling for multi-taxon biodiversity studies in European forests
Burrascano , Sabina , Trentanovi , Giovanni , Paillet , Yoan , Heilmann-Clausen , Jacob , Giordani , P. , Bagella , Simonetta , Bravo-Oviedo , Andrés , Campagnaro , Thomas , Campanaro , Alessandro , Chianucci , Francesco , de Smedt , Pallieter , Itziar , García Mijangos , Matošević , Dinka , Sitzia , Tommaso , Aszalós , Réka , Brazaitis , Gediminas , Cutini , Andrea , D'Andrea , Ettore , Doerfler , Inken , Hofmeister , Jeňýk , Hošek , Jan , Janssen , Philippe , Kepfer-Rojas , Sebastian , Korboulewsky , Nathalie , Kozák , Daniel , Lachat , Thibault , Lõhmus , Asko , López , Rosana , Mårell , Anders , Matula , Radim , Mikoláš , Martin , Munzi , Silvana , Nordén , Björn , Pärtel , Meelis , Penner , Johannes , Runnel , Kadri , Schall , Peter , Svoboda , Miroslav , Tinya , Flóra , Ujházyová , Mariana , Vandekerkhove , Kris , Verheyen , Kris , Xystrakis , Fotios , Ódor , Péter
biodiversity forest stand structure multi-taxon field methods indicators sampling protocol
Mostra abstract
Forests host most terrestrial biodiversity and their sustainable management is crucial to halt biodiversity loss. Although scientific evidence indicates that sustainable forest management (SFM) should be assessed by monitoring multi-taxon biodiversity, most current SFM criteria and indicators account only for trees or consider indirect biodiversity proxies. Several projects performed multi-taxon sampling to investigate the effects of forest management on biodiversity, but the large variability of their sampling approaches hampers the identification of general trends, and limits broad-scale inference for designing SFM. Here we address the need of common sampling protocols for forest structure and multi-taxon biodiversity to be used at broad spatial scales. We established a network of researchers involved in 41 projects on forest multi-taxon biodiversity across 13 European countries. The network data structure comprised the assessment of at least three taxa, and the measurement of forest stand structure in the same plots or stands. We mapped the sampling approaches to multi-taxon biodiversity, standing trees and deadwood, and used this overview to provide operational answers to two simple, yet crucial, questions: what to sample? How to sample? The most commonly sampled taxonomic groups are vascular plants (83% of datasets), beetles (80%), lichens (66%), birds (66%), fungi (61%), bryophytes (49%). They cover different forest structures and habitats, with a limited focus on soil, litter and forest canopy. Notwithstanding the common goal of assessing forest management effects on biodiversity, sampling approaches differed widely within and among taxonomic groups. Differences derive from sampling units (plots size, use of stand vs. plot scale), and from the focus on different substrates or functional groups of organisms. Sampling methods for standing trees and lying deadwood were relatively homogeneous and focused on volume calculations, but with a great variability in sampling units and diameter thresholds. We developed a handbook of sampling methods (SI 3) aimed at the greatest possible comparability across taxonomic groups and studies as a basis for European-wide biodiversity monitoring programs, robust understanding of biodiversity response to forest structure and management, and the identification of direct indicators of SFM. © 2021 The Authors
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2021
Rivista
Ecological Indicators
Dettagli
Vol. 132
DOI