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Pubblicazioni Scientifiche

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Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR-species20K dataset
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.
TRY plant trait database – enhanced coverage and open access
Kattge , Jens , Bönisch , Gerhard , Díaz , Sandra M. , Lavorel , Sandra , Prentice , Iain Colin , Leadley , Paul W. , Tautenhahn , Susanne , Werner , Gijsbert , Aakala , Tuomas , Abedi , Mehdi , Acosta , Alicia Teresa Rosario , Adamidis , George C. , Adamson , Kairi , Aiba , Masahiro , Albert , Cécile Hélène , Alcántara , Julio M. , Alcázar C , Carolina , Aleixo , Izabela , Ali , Hamada E. , Amiaud , Bernard , Ammer , Christian , Amoroso , Mariano Martín , Anand , Madhur , Anderson , Carolyn G. , Anten , Niels P.R. , Antos , Joseph A. , Apgaua , Deborah Mattos Guimarães , Ashman , Tia Lynn , Asmara , Degi Harja , Asner , Gregory P. , Aspinwall , Michael J. , Atkin , Owen K. , Aubin , Isabelle , Baastrup-Spohr , Lars , Bahalkeh , Khadijeh , Bahn , Michael , Baker , Timothy R. , Baker , William J. , Bakker , Jan P. , Baldocchi , Dennis D. , Baltzer , Jennifer L. , Banerjee , Arindam , Baranger , Anne , Barlow , Jos B. , Barneche , Diego R. , Baruch , Zdravko , Bastianelli , Denis , Battles , John J. , Bauerle , William L. , Bauters , Marijn , Bazzato , Erika , Beckmann , Michael , Beeckman , Hans , Beierkuhnlein , Carl , Bekker , Renée M. , Belfry , Gavin , Belluau , Michaël , Beloiu Schwenke , Mirela , Benavides , Raquel , Benomar , Lahcen , Berdugo-Lattke , Mary Lee , Berenguer , Erika , Bergamin , Rodrigo Scarton , Bergmann , Joana , Carlucci , Marcos B. , Berner , Logan T. , Bernhardt-Römermann , Markus , Bigler , Christof , Bjorkman , Anne D. , Blackman , Chris J. , Blanco , Carolina Casagrande , Blonder , Benjamin Wong , Blumenthal , Dana M. , Bocanegra-González , Kelly Tatiana , Boeckx , Pascal , Bohlman , Stephanie Ann , Böhning-Gaese , Katrin , Boisvert-Marsh , Laura , Bond , William J. , Bond-Lamberty , Ben P. , Boom , Arnoud , Boonman , Coline C.F. , Bordin , Kauane Maiara , Boughton , Elizabeth H. , Boukili , Vanessa K.S. , Bowman , David M.J.S. , Bravo , Sandra Josefina , Brendel , Marco R. , Broadley , Martin R. , Brown , Kerry A. , Bruelheide , Helge , Brumnich , Federico , Bruun , Hans Henrik , Bruy , David , Buchanan , Serra Willow , Bucher , Solveig Franziska , Buchmann , Nina , Buitenwerf , Robert , Bunker , Daniel E. , Bürger , Jana
Mostra abstract
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives. © 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd
Continental Contrasts in Climate Extremes That Control Tree Fecundity
Clark , James S. , Andrus , Robert A. , Arianoutsou , Margarita , Ascoli , Davide , Bergeron , Yves , Bogdziewicz , Michał , Boivin , Thomas , Bonal , Raúl , Caignard , Thomas , Cailleret , Maxime , Calama , Rafael A. , Camarero , Jesús Julio , Chianucci , Francesco , Cienciala , Emil , Courbaud , Benoít , Delzon , Sylvain , Dietze , Michael C. , Espelta , Josep Maria , Fady , Bruno , Fyllas , Nikolaos M. , Gilbert , Gregory S. , Gratzer , Georg , Guignabert , Arthur , Hacket-Pain , Andrew J. , Hampe , Arndt , Hanley , Mick E. , Hille Ris Lambers , Janneke , Holik , Jan , Hoshizaki , K. , Hu , Miao , Ibáñez , Inés , Işık , Fatih , Jenkins , Lauren , Johnstone , Jill F. , Journé , Valentin , Kadioglu , Alper Kaan , Kızılaslan , İrem Sena , Knops , Johannes Michael Hubertus , Kobe , Richard K. , Köse , Nesibe , Külah , Eylül U. , Kunstler , Georges , LaMontagne , Jalene M. , Ledwoń , Mateusz , Lehtonen , Aleksi , Loewe-Muñoz , Verónica F. , Lutz , James A. , Mårell , Anders , Meyer , Kira , Moran , Emily V. , Motta , Renzo , Myers , Jonathan A. , Nagel , Thomas A. , Pérez-Ramos , Ignacio M. , Piechnik , Łukasz , Podgórski , Tomasz , Poulton-Kamakura , Renata , Qiu , Tong , Redmond , Miranda D. , Reid , Chantal D. , Rodman , Kyle C. , Rodríguez-Sánchez , Francisco , Šamonil , Pavel , Šebeň , Vladimír , Seget , Barbara , Sharma , Shubhi , Socha , Jarosław Ł. , Steele , Michael A. , Straub , Jacob N. , Sutton , Samantha , Thomas , Peter A. , Vacchiano , Giorgio , Venner , Marie Claude , Venner , Samuel , Zavala , Miguel A. , Zheng , Shiqi , Żywiec , Magdalena
Mostra abstract
In 2023, more than half of olive harvests (Olea europaea) across Spain, Greece, and Türkiye were lost to drought. The same year late freeze destroyed 90% of the peach crop (Prunus persica) on the Georgia Piedmont and the apple crop (Malus domestica) in central New York, Vermont, and southern Quebec. Climate extremes now rank with the costliest threats to agriculture, but their role in forest recovery from diebacks that are happening globally is unknown for lack of tree fecundity estimates in forests. Tolerance of climate extremes could depend on past exposure but constrained by phylogenetic conservatism. We report a continental scale analysis of climate extremes and forest fecundity across North America and Europe showing that responses to late freeze and drought are happening now. Species differences are not explained by the traits typically included in ecological studies and they are weakly associated with phylogeny. Late freeze, that is, freezing temperatures that follow the onset of flower development in spring, is shown to be “normal” in North America, but not Europe, potentially explaining failed seed production due to delayed onset and the resultant shorter growing period by North American transplants dating back at least to the 18th century. Drought has thus far had the greatest impacts in dry forested regions, but here too, species differences are not explained by traditional trait values. If responses have been buffered from drought and late freeze by past exposure, acclimation and local adaptation prove inadequate as extremes intensify. © 2026 John Wiley & Sons Ltd.
The Relationship Between Maturation Size and Maximum Tree Size From Tropical to Boreal Climates
Journé , Valentin , Bogdziewicz , Michał , Courbaud , Benoít , Kunstler , Georges , Qiu , Tong , Aravena Acuña , Marie Claire , Ascoli , Davide , Bergeron , Yves , Berveiller , Daniel , Boivin , Thomas , Bonal , Raúl , Caignard , Thomas , Cailleret , Maxime , Calama , Rafael A. , Camarero , Jesús Julio , Chang-Yang , Chia Hao , Chave , Jérôme , Chianucci , Francesco , Curt , Thomas , Cutini , Andrea , Das , Adrian J. , Daskalakou , Evangelia N. , Davi , Hendrik , Delpierre , Nicolas , Delzon , Sylvain , Dietze , Michael C. , Calderon , Sergio Donoso , Dormont , Laurent , Espelta , Josep Maria , Farfan-Rios , William R. , Fenner , Michael , Franklin , Jerry F. , Gehring , Catherine A. , Gilbert , Gregory S. , Gratzer , Georg , Greenberg , Cathryn H. , Guignabert , Arthur , Guo , Qinfeng , Hacket-Pain , Andrew J. , Hampe , Arndt , Han , Qingmin , Hanley , Mick E. , Hille Ris Lambers , Janneke , Holik , Jan , Hoshizaki , K. , Ibáñez , Inés , Johnstone , Jill F. , Knops , Johannes Michael Hubertus , Kobe , Richard K. , Kurokawa , Hiroko , Lageard , Jonathan G.A. , LaMontagne , Jalene M. , Ledwoń , Mateusz , Lefèvre , François , Leininger , Theodor D. , Limousin , Jean Marc , Lutz , James A. , Macias , Diana S. , Mårell , Anders , McIntire , Eliot J.B. , Moran , Emily V. , Motta , Renzo , Myers , Jonathan A. , Nagel , Thomas A. , Naoe , Shoji , Noguchi , Mahoko , Norghauer , Julian M. , Oguro , Michio , Ourcival , Jean Marc , Parmenter , Robert R. , Pearse , Ian S. , Pérez-Ramos , Ignacio M. , Piechnik , Łukasz , Podgórski , Tomasz , Poulsen , John R. , Redmond , Miranda D. , Reid , Chantal D. , Šamonil , Pavel , Scher , C. Lane , Schlesinger , William H. , Seget , Barbara , Sharma , Shubhi , Shibata , Mitsue , Silman , Miles R. , Steele , Michael A. , Stephenson , Nathan L. , Straub , Jacob N. , Sutton , Samantha , Swenson , Jennifer J. , Swift , Margaret , Thomas , Peter A. , Uríarte , María , Vacchiano , Giorgio , Whipple , Amy Vaughn , Whitham , Thomas G. , Wright , Stuart Joseph , Zhu , Kai , Zimmerman , Jess K. , Żywiec , Magdalena , Clark , James S.
Mostra abstract
The fundamental trade-off between current and future reproduction has long been considered to result in a tendency for species that can grow large to begin reproduction at a larger size. Due to the prolonged time required to reach maturity, estimates of tree maturation size remain very rare and we lack a global view on the generality and the shape of this trade-off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree species spanning tropical to boreal climates. Results show that a species' maturation size increases with maximum size, but in a non-proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. These findings on maturation size drivers are key to accurately represent forests' responses to disturbance and climate change. © 2024 John Wiley & Sons Ltd.
Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradients
Qiu , Tong , Aravena Acuña , Marie Claire , Ascoli , Davide , Bergeron , Yves , Bogdziewicz , Michał , Boivin , Thomas , Bonal , Raúl , Caignard , Thomas , Cailleret , Maxime , Calama , Rafael A. , Calderon , Sergio Donoso , Camarero , Jesús Julio , Chang-Yang , Chia Hao , Chave , Jérôme , Chianucci , Francesco , Courbaud , Benoít , Cutini , Andrea , Das , Adrian J. , Delpierre , Nicolas , Delzon , Sylvain , Dietze , Michael C. , Dormont , Laurent , Espelta , Josep Maria , Fahey , Timothy J. , Farfan-Rios , William R. , Franklin , Jerry F. , Gehring , Catherine A. , Gilbert , Gregory S. , Gratzer , Georg , Greenberg , Cathryn H. , Guignabert , Arthur , Guo , Qinfeng , Hacket-Pain , Andrew J. , Hampe , Arndt , Han , Qingmin , Holik , Jan , Hoshizaki , K. , Ibáñez , Inés , Johnstone , Jill F. , Journé , Valentin , Kitzberger , Thomas A. , Knops , Johannes Michael Hubertus , Kunstler , Georges , Kurokawa , Hiroko , Lageard , Jonathan G.A. , LaMontagne , Jalene M. , Lefèvre , François , Leininger , Theodor D. , Limousin , Jean Marc , Lutz , James A. , Macias , Diana S. , Mårell , Anders , McIntire , Eliot J.B. , Moore , Christopher M. , Moran , Emily V. , Motta , Renzo , Myers , Jonathan A. , Nagel , Thomas A. , Naoe , Shoji , Noguchi , Mahoko , Oguro , Michio , Parmenter , Robert R. , Pearse , Ian S. , Pérez-Ramos , Ignacio M. , Piechnik , Łukasz , Podgórski , Tomasz , Poulsen , John R. , Redmond , Miranda D. , Reid , Chantal D. , Rodman , Kyle C. , Rodríguez-Sánchez , Francisco , Šamonil , Pavel , Sanguinetti , Javier D. , Scher , C. Lane , Seget , Barbara , Sharma , Shubhi , Shibata , Mitsue , Silman , Miles R. , Steele , Michael A. , Stephenson , Nathan L. , Straub , Jacob N. , Sutton , Samantha , Swenson , Jennifer J. , Swift , Margaret , Thomas , Peter A. , Uríarte , María , Vacchiano , Giorgio , Whipple , Amy Vaughn , Whitham , Thomas G. , Wion , Andreas P. , Wright , Stuart Joseph , Zhu , Kai , Zimmerman , Jess K. , Żywiec , Magdalena , Clark , James S.
Mostra abstract
The benefits of masting (volatile, quasi-synchronous seed production at lagged intervals) include satiation of seed predators, but these benefits come with a cost to mutualist pollen and seed dispersers. If the evolution of masting represents a balance between these benefits and costs, we expect mast avoidance in species that are heavily reliant on mutualist dispersers. These effects play out in the context of variable climate and site fertility among species that vary widely in nutrient demand. Meta-analyses of published data have focused on variation at the population scale, thus omitting periodicity within trees and synchronicity between trees. From raw data on 12 million tree-years worldwide, we quantified three components of masting that have not previously been analysed together: (i) volatility, defined as the frequency-weighted year-to-year variation; (ii) periodicity, representing the lag between high-seed years; and (iii) synchronicity, indicating the tree-to-tree correlation. Results show that mast avoidance (low volatility and low synchronicity) by species dependent on mutualist dispersers explains more variation than any other effect. Nutrient-demanding species have low volatility, and species that are most common on nutrient-rich and warm/wet sites exhibit short periods. The prevalence of masting in cold/dry sites coincides with climatic conditions where dependence on vertebrate dispersers is less common than in the wet tropics. Mutualist dispersers neutralize the benefits of masting for predator satiation, further balancing the effects of climate, site fertility and nutrient demands. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.
Review of ground and aerial methods for vegetation cover fraction (fCover) and related quantities estimation: definitions, advances, challenges, and future perspectives
Mostra abstract
Vegetation cover fraction (fCover) and related quantities are basic yet critical vegetation structure variables in various disciplines and applications. Ground- and aerial-based proximal and remote sensing techniques have been widely adapted across multiple spatial extents. However, the definitions of fCover-related nomenclatures have not yet been fully standardized, leading to confusing terms and making comparing historic measures difficult. With the issues potentially arising from an increasing diversity of fCover and related quantities estimation methods and corresponding uncertainties, there is also a growing need to spread knowledge on the current advances, challenges, and perspectives, especially in the context of no such existing review for ground- and aerial- based estimation. This paper provides the current knowledge mainly concerning passive image-based methods and active light detection and ranging (LiDAR) -based methods. We first harmonized the definitions of fCover and its related quantities (e.g., effective canopy cover, crown cover, stratified vegetation cover, and canopy fraction). Secondly, the typical applications of fCover and related quantities over a range of scales, fields, and ecosystems were summarized. Thirdly yet importantly, we offered a comprehensive review of traditional non-imaging methods, image-based methods (e.g., segmentation, unmixing, and spectral retrieval), point cloud-based methods (e.g., rasterization), and LiDAR return-based methods (e.g., return number index and return intensity retrieval) across different platforms (i.e., ground, unmanned aerial vehicle (UAV) and airplane). Our investigation of fCover and related quantities estimation touches upon various vegetation ecosystems, including agriculture cropland, grassland, wetland, and forest. Finally, the current challenges and future directions were discussed, such as image signal processing under complex heterogeneous surfaces and stratified cover and non-photosynthesis cover retrieval. We, therefore, expect that this review may offer an insight into fCover and related quantities estimation and serve as a reference for remote sensing scientists, agronomists, silviculturists, and ecologists. © 2023 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)
Linking seed size and number to trait syndromes in trees
Bogdziewicz , Michał , Aravena Acuña , Marie Claire , Andrus , Robert A. , Ascoli , Davide , Bergeron , Yves , Brveiller , Daniel , Boivin , Thomas , Bonal , Raúl , Caignard , Thomas , Cailleret , Maxime , Calama , Rafael A. , Calderon , Sergio Donoso , Camarero , Jesús Julio , Chang-Yang , Chia Hao , Chave , Jérôme , Chianucci , Francesco , Cleavitt , Natalie L. , Courbaud , Benoít , Cutini , Andrea , Curt , Thomas , Das , Adrian J. , Davi , Hendrik , Delpierre , Nicolas , Delzon , Sylvain , Dietze , Michael C. , Dormont , Laurent , Farfan-Rios , William R. , Gehring , Catherine A. , Gilbert , Gregory S. , Gratzer , Georg , Greenberg , Cathryn H. , Guignabert , Arthur , Guo , Qinfeng , Hacket-Pain , Andrew J. , Hampe , Arndt , Han , Qingmin , Hoshizaki , K. , Ibáñez , Inés , Johnstone , Jill F. , Journé , Valentin , Kitzberger , Thomas A. , Knops , Johannes Michael Hubertus , Kunstler , Georges , Kobe , Richard K. , Lageard , Jonathan G.A. , LaMontagne , Jalene M. , Ledwoń , Mateusz , Leininger , Theodor D. , Limousin , Jean Marc , Lutz , James A. , Macias , Diana S. , Mårell , Anders , McIntire , Eliot J.B. , Moran , Emily V. , Motta , Renzo , Myers , Jonathan A. , Nagel , Thomas A. , Naoe , Shoji , Noguchi , Mahoko , Oguro , Michio , Kurokawa , Hiroko , Ourcival , Jean Marc , Parmenter , Robert R. , Pérez-Ramos , Ignacio M. , Piechnik , Łukasz , Podgórski , Tomasz , Poulsen , John R. , Qiu , Tong , Redmond , Miranda D. , Reid , Chantal D. , Rodman , Kyle C. , Šamonil , Pavel , Holik , Jan , Scher , C. Lane , van Marle , Harald Schmidt , Seget , Barbara , Shibata , Mitsue , Sharma , Shubhi , Silman , Miles R. , Steele , Michael A. , Straub , Jacob N. , Sun , I. Fang , Sutton , Samantha , Swenson , Jennifer J. , Thomas , Peter A. , Uríarte , María , Vacchiano , Giorgio , Veblen , Thomas Thorstein , Wright , Boyd R. , Wright , Stuart Joseph , Whitham , Thomas G. , Zhu , Kai , Zimmerman , Jess K. , Żywiec , Magdalena , Clark , James S.
Mostra abstract
Aim: Our understanding of the mechanisms that maintain forest diversity under changing climate can benefit from knowledge about traits that are closely linked to fitness. We tested whether the link between traits and seed number and seed size is consistent with two hypotheses, termed the leaf economics spectrum and the plant size syndrome, or whether reproduction represents an independent dimension related to a seed size–seed number trade-off. Location: Most of the data come from Europe, North and Central America and East Asia. A minority of the data come from South America, Africa and Australia. Time period: 1960–2022. Major taxa studied: Trees. Methods: We gathered 12 million observations of the number of seeds produced in 784 tree species. We estimated the number of seeds produced by individual trees and scaled it up to the species level. Next, we used principal components analysis and generalized joint attribute modelling (GJAM) to map seed number and size on the tree traits spectrum. Results: Incorporating seed size and number into trait analysis while controlling for environment and phylogeny with GJAM exposes relationships in trees that might otherwise remain hidden. Production of the large total biomass of seeds [product of seed number and seed size; hereafter, species seed productivity (SSP)] is associated with high leaf area, low foliar nitrogen, low specific leaf area (SLA) and dense wood. Production of high seed numbers is associated with small seeds produced by nutrient-demanding species with softwood, small leaves and high SLA. Trait covariation is consistent with opposing strategies: one fast-growing, early successional, with high dispersal, and the other slow-growing, stress-tolerant, that recruit in shaded conditions. Main conclusions: Earth system models currently assume that reproductive allocation is indifferent among plant functional types. Easily measurable seed size is a strong predictor of the seed number and species seed productivity. The connection of SSP with the functional traits can form the first basis of improved fecundity prediction across global forests. © 2023 John Wiley & Sons Ltd.
MASTREE+: Time-series of plant reproductive effort from six continents
Hacket-Pain , Andrew J. , Foest , Jessie J. , Pearse , Ian S. , LaMontagne , Jalene M. , Koenig , Walter D. , Vacchiano , Giorgio , Bogdziewicz , Michał , Caignard , Thomas , Celebias , Paulina , van Dormolen , Joep , Fernández-Martínez , Marcos , Moris , Jose V. , Palaghianu , Ciprian , Pesendorfer , Mario B. , Satake , Akiko , Schermer , Éliane , Tanentzap , Andrew J. , Thomas , Peter A. , Vecchio , Davide , Wion , Andreas P. , Wohlgemuth , Thomas , Xue , Tingting , Abernethy , Katharine A. , Aravena Acuña , Marie Claire , Barrera , Marcelo Daniel , Barton , Jessica H. , Boutin , Stan A. , Bush , Emma R. , Donoso Calderón , Sergio R. , Carevic , Felipe S. , Castilho , Carolina V. , Manuel Cellini , Juan , Chapman , Colin A. , Chapman , H. M. , Chianucci , Francesco , Costa , Patricia Da , Croisé , Luc , Cutini , Andrea , Dantzer , Ben J. , DeRose , Robert Justin , Dikangadissi , Jean Thoussaint , Dimoto , Edmond , da Fonseca , Fernanda Lopes , Gallo , Leonardo Ariel , Gratzer , Georg , Greene , David F. , Hadad , Martín Ariel , Huertas Herrera , Alejandro , Jeffery , Kathryn J. , Johnstone , Jill F. , Kalbitzer , Urs , Kantorowicz , Władysław , Klimas , Christie Ann , Lageard , Jonathan G.A. , Lane , Jeffrey E. , Lapin , Katharina , Ledwoń , Mateusz , Leeper , Abigail C. , Lencinas , María Vanessa , Lira-Guedes , Ana Cláudia , Lordon , Michael C. , Marchelli , Paula , Marino , Shealyn , Schmidt van Marle , Harald , McAdam , Andrew G. , Momont , Ludovic R.W. , Nicolas , Manuel , de Oliveira Wadt , Lúcia Helena , Panahi , Parisa , Martínez Pastur , Guillermo J. , Patterson , Thomas W. , Luis Peri , Pablo , Piechnik , Łukasz , Pourhashemi , Mehdi , Espinoza Quezada , Claudia , Roig , Fidel Alejandro , Peña-Rojas , Karen A. , Rosas , Yamina Micaela , Schueler , Silvio , Seget , Barbara , Soler , Rosina M. , Steele , Michael A. , Toro Manríquez , Mónica Del Rosario , Tutin , Caroline E.G. , Ukizintambara , Tharcisse , White , Lee J.T. , Yadok , Biplang Godwill , Willis , John L. , Zolles , Anita , Żywiec , Magdalena , Ascoli , Davide
Mostra abstract
Significant gaps remain in understanding the response of plant reproduction to environmental change. This is partly because measuring reproduction in long-lived plants requires direct observation over many years and such datasets have rarely been made publicly available. Here we introduce MASTREE+, a data set that collates reproductive time-series data from across the globe and makes these data freely available to the community. MASTREE+ includes 73,828 georeferenced observations of annual reproduction (e.g. seed and fruit counts) in perennial plant populations worldwide. These observations consist of 5971 population-level time-series from 974 species in 66 countries. The mean and median time-series length is 12.4 and 10 years respectively, and the data set includes 1122 series that extend over at least two decades (≥20 years of observations). For a subset of well-studied species, MASTREE+ includes extensive replication of time-series across geographical and climatic gradients. Here we describe the open-access data set, available as a.csv file, and we introduce an associated web-based app for data exploration. MASTREE+ will provide the basis for improved understanding of the response of long-lived plant reproduction to environmental change. Additionally, MASTREE+ will enable investigation of the ecology and evolution of reproductive strategies in perennial plants, and the role of plant reproduction as a driver of ecosystem dynamics. © 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach
Mostra abstract
Accurate wall-to-wall estimation of forest crown cover is critical for a wide range of ecological studies. Notwithstanding the increasing use of UAVs in forest canopy mapping, the ultrahigh-resolution UAV imagery requires an appropriate procedure to separate the contribution of understorey from overstorey vegetation, which is complicated by the spectral similarity between the two forest components and the illumination environment. In this study, we investigated the integration of deep learning and the combined data of imagery and photogrammetric point clouds for boreal forest canopy mapping. The procedure enables the automatic creation of training sets of tree crown (overstorey) and background (understorey) data via the combination of UAV images and their associated photogrammetric point clouds and expands the applicability of deep learning models with self-supervision. Based on the UAV images with different overlap levels of 12 conifer forest plots that are categorized into “I”, “II” and “III” complexity levels according to illumination environment, we compared the self-supervised deep learning-predicted canopy maps from original images with manual delineation data and found an average intersection of union (IoU) larger than 0.9 for “complexity I” and “complexity II” plots and larger than 0.75 for “complexity III” plots. The proposed method was then compared with three classical image segmentation methods (i.e., maximum likelihood, Kmeans, and Otsu) in the plot-level crown cover estimation, showing outperformance in overstorey canopy extraction against other methods. The proposed method was also validated against wall-to-wall and pointwise crown cover estimates using UAV LiDAR and in situ digital cover photography (DCP) benchmarking methods. The results showed that the model-predicted crown cover was in line with the UAV LiDAR method (RMSE of 0.06) and deviate from the DCP method (RMSE of 0.18). We subsequently compared the new method and the commonly used UAV structure-from-motion (SfM) method at varying forward and lateral overlaps over all plots and a rugged terrain region, yielding results showing that the method-predicted crown cover was relatively insensitive to varying overlap (largest bias of less than 0.15), whereas the UAV SfM-estimated crown cover was seriously affected by overlap and decreased with decreasing overlap. In addition, canopy mapping over rugged terrain verified the merits of the new method, with no need for a detailed digital terrain model (DTM). The new method is recommended to be used in various image overlaps, illuminations, and terrains due to its robustness and high accuracy. This study offers opportunities to promote forest ecological applications (e.g., leaf area index estimation) and sustainable management (e.g., deforestation). © 2022 The Author(s)
A new method to estimate clumping index integrating gap fraction averaging with the analysis of gap size distribution
Mostra abstract
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.
Comparison of seven inversion models for estimating plant andwoody area indices of leaf-on and leaf-off forest canopy using explicit 3D forest scenes
Mostra abstract
Optical methods require model inversion to infer plant area index (PAI) and woody area index (WAI) of leaf-on and leaf-off forest canopy from gap fraction or radiation attenuation measurements. Several inversion models have been developed previously, however, a thorough comparison of those inversion models in obtaining the PAI and WAI of leaf-on and leaf-off forest canopy has not been conducted so far. In the present study, an explicit 3D forest scene series with different PAI,WAI, phenological periods, stand density, tree species composition, plant functional types, canopy element clumping index, and woody component clumping index was generated using 50 detailed 3D tree models. The explicit 3D forest scene series was then used to assess the performance of seven commonly used inversion models to estimate the PAI andWAI of the leaf-on and leaf-off forest canopy. The PAI andWAI estimated from the seven inversion models and simulated digital hemispherical photography images were compared with the true PAI and WAI of leaf-on and leaf-off forest scenes. Factors that contributed to the differences between the estimates of the seven inversion models were analyzed. Results show that both the factors of inversion model, canopy element and woody component projection functions, canopy element and woody component estimation algorithms, and segment size are contributed to the differences between the PAI and WAI estimated from the seven inversion models. There is no universally valid combination of inversion model, needle-to-shoot area ratio, canopy element and woody component clumping index estimation algorithm, and segment size that can accurately measure the PAI and WAI of all leaf-on and leaf-off forest canopies. The performance of the combinations of inversion model, needle-to-shoot area ratio, canopy element and woody component clumping index estimation algorithm, and segment size to estimate the PAI and WAI of leaf-on and leaf-off forest canopies is the function of the inversion model as well as the canopy element and woody component clumping index estimation algorithm, segment size, PAI,WAI, tree species composition, and plant functional types. The impact of canopy element and woody component projection function measurements on the PAI and WAI estimation of the leaf-on and leaf-off forest canopy can be reduced to a low level ( < 4%) by adopting appropriate inversion models. © 2018 by the authors.