{"paper_id":"41e28341-e21a-4454-bdee-3db9964d9cf7","body_text":"1 \n \nPhytoKeys xxx: xx–xx (202X)  \ndoi:                                                             RESEARCH ARTICLE                           PHYTOKEYS \nLOGO \nhttp://phytokeys.pensoft.net \nA digital multi-access key for easy identification of large tree \nspecies of ebony wood in Madagascar \nHasina N. Rakouth*1, 2, Sylvie Andriambololonera2, Bakolimalala Rakouth1, Peter B. Phillipson3, 4, Porter \nP. Lowry II3, 4 and Nicholas Wilding3, 5 \n \n1 Plant Biology and Ecology Department, University of Antananarivo, Antananarivo, Madagascar. 2 Missouri Botanical Garden, \nMadagascar Research and Conservation Program, B.P. 3391, Antananarivo 101, Madagascar. 3 Missouri Botanical Garden, Africa \nand Madagascar Program, 4344 Shaw Blvd., St. Louis, Missouri 63110, USA. 4 Institut de Systématique, Évolution et Biodiversité \n(ISYEB), Muséum National d'Histoire Naturelle, Centre National de la Recherche Scientifique, Sorbonne Université, École Pratique des \nHautes Études, Université des Antilles, C.P. 39, 57 rue Cuvier, 75005 Paris, France. 5 UMR PVBMT- Pôle de Protection des Plantes \nUniversité de La Réunion, La Réunion, France . \nCorresponding author: Hasina N. Rakouth (hasinomen@yahoo.com; Hasina.Rakouth@mobot.mg) \nAcademic editor:….. | Received       2024 | Accepted     202X | Published     202X \nCitation: Rakouth HN, Andriambololonera S, Rakouth B, Phillipson PB, Lowry II PP, Wilding N \n(202X) A digital multi-access key newly designed for easy identification of large tree species of ebony \nwood in Madagascar. PhytoKeys xxx: x–xx. https://doi.org/10.3897/ phytokeys xxx xxxx \nAbstract \nIn 2013, all populations of the precious wood g enera Dalbergia (Fabaceae) and Diospyros \n(Ebenaceae) from Madagascar were placed on CITES Appendix II in an effort to combat unsustainable \nand illicit over -exploitation and illegal exportation for the international market. The accompanying \nAction Plan adopted by CITES identified several information and cap acity gaps, which undermine the \nsustainable and equitable management of these valuable resources. These gaps include the lack of \npractical, reliable tools to identify species along the entire value chain, from standing trees to cut wood \nand finished products. To address this need, we developed simple, user-friendly, multi-access keys for \nthe two genera in Madagascar using the Lucid application. This new tool provides highly accurate \nidentification of standing and felled trees to assist actors in the forestry, regulatory, and natural resource \nmanagement sectors, including customs officials and law enforcement authorities as well as \nconservationists and protected area managers. In this paper, we focus on the development of the \nDiospyros identification tool. Th is interactive, electronic key employs 109 informative characters, \nincluding morphological features, emphasizing vegetative structures such as bark, stems, and leaves that \nare present even in the absence of flowers and fruits, in conjunction with eco -geographic characters \n(bioclimate, elevation, and geography). The key is supplemented with photos, illustrations, and a \ncomprehensive glossary, to deliver accurate identification of the 88 Diospyros species that are large \nenough to be potential sources of comme rcially valuable ebony wood (≥ 20 cm DBH and/or ≥ 20 m \nheight). This is the first use of Lucid to develop an identification key for species in Madagascar, paving \nthe way for its application to other taxa for which practical electronic field identification is needed. \nKey words: CITES, Diospyros, ebony, Lucid 4, Madagascar, multi-access key, precious woods. \n \n \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n2 \n \nIntroduction \nOver the last two decades’ members of the precious wood genera Diospyros (Ebenaceae) and \nDalbergia (Fabaceae) have faced rapidly growing pressure and worsening threats due to unsustainable \nlevels of illicit exploitation, primarily within legally protected areas. Most of the ebony and rosewood \ntimber obtained from them has been harvested illegally and exported fo r the international market, \nprimarily to China (Global Witness & Environmental Investigation Agency 2009, 2010; Schuurman and \nLowry 2009; Wilmé et al. 2009; Randriamalala and Liu 2010; Randriamalala et al. 2011; Ballet et al. \n2011; Waeber et al. 2015; Andriamanana 2019).  \nAs part of Madagascar’s obligations under the Convention on Biological Diversity (CBD) signed in \nRio de Janeiro in 1992 (Stone 1996) and the Convention on International Trade of Endangered Species \n(CITES 1978), the government is responsibl e for ensuring the sustainable management and protection \nof all its species and for guaranteeing that their utilization does not threaten their survival. Measures to \nachieve a permanent halt to illegal exploitation in order to establish policies for rational and sustainable \nmanagement of precious woods as well as for the equitable sale of these valuable resources have recently \nbeen initiated (Innes 2010 ; Pepke et al. 2015) . Furthermore, in 2013, all Malagasy species of both \nDiospyros (which produces ebony wood) and Dalbergia (the primary source of rosewood) were listed \non CITES Appendix II in an attempt to reduce over -exploitation and commercial trafficking \n(Andriambololonera et al. 2013; CITES 2013a, b). That same year, at the 16 th CITES Conference of \nParties, an Action Plan was adopted (Decision 16.152 and subsequently Decision 17.203) requiring the \nestablishment of an embargo on the export of wood stockpiles that had accumulated following seizure \nby the Malagasy authorities and prohibiting commercial excha nge of ebony and rosewood \n(Andriamanana 2019). Yet despite these efforts, exploitation has continued (Ballet et al. 2011; Mason \net al. 2016; Ratsimbazafy et al. 2016). Moreover, significant gaps were identified regarding the scientific \nknowledge base of th ese precious wood genera, which prompted a series of recommendations in the \nAction Plan to address them (CITES 2018). \nOne of the most important issues identified in the Action Plan was the inability to provide correct \nscientific names and reliable identifi cations for species, which are the principal unit of CITES \nmanagement and a key element of biodiversity. This situation is due in large part to the lack of efficient \nidentification tools (Delaunay 2020). Moreover, actors involved in the Malagasy forestry s ector use \ngeneralized designations for various types of precious wood, either in the form of common (vernacular) \nnames (which vary regionally) or commercial names based on the color and other characteristics of the \nwood being exploited. However, these names often apply to two or more distinct species, and they are \nused inconsistently. For example, all species of Diospyros with black heartwood are called ‘ebony’ or \n‘hazomainty’ in Malagasy, and species of Dalbergia with red or deep pink-violet heartwood are called \n‘rosewood’, or ‘andramena’. Consequently, commercial and scientific names represent fundamentally \ndifferent concepts in the context of the sustainable management of these important resources and the \nspecies from which they are sourced (Rakotovao et al. 2012). Addressing the challenges associated with \nthe accurate identification and naming of species is a major hurdle for the eventual relaxing or lifting of \nthe current embargo on these two genera by means of establishing a non-detriment finding (NDF) for a \nspecies whose exploitation would be possible without compromising its survival (Mason et al. 2016) or \nby removing them for CITES Appendix II . Therefore, it is crucial to develop methods and tools that \nallow for the accurate, precise, and unambiguous identification of species. This is particularly important \nwhen evaluating and managing populations of precious wood species, as it informs decision -making \nregarding their conservation, management, and exploitation. \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n3 \n \nTo help address the objective s of the CITES Action Plan  for Madagascar , a consortium was \nestablished in 2017 to develop scientific knowledge and tools in support of the sustainable management \nof the country’s precious wood genera Dalbergia and Diospyros (the consortium is known by its French \nacronym G3D – Gestion Durable des bois précieux Dalbergia et Diospyros de Madagascar). The \nmanagement and control of these species requires reliable identification along the entire value chain, \nfrom standing trees and cut logs in the forest to sawn  wood and finished products, and each of these \nstages requires its own methods and tools. A multi -disciplinary approach was therefore adopted that \ncomprises four complementary components:  \n• Taxonomy (documentation of populations, field collection of represe ntative samples, and \nclarification of species delimitation). \n• Development of practical, reliable identification tools for standing trees and for specimens with \nleaves, flowers and/or fruits. \n• Establishment of forensic identification methods based on the stud y of a) comparative wood \nanatomy, b) DNA sequencing (barcoding), and c) near infrared spectroscopy. \n• Development of effective management strategies for the conservation of wild populations. \nCollectively the main objective of these components is to establish a solid scientific base of research \nmaterial and associated knowledge to inform accurate delimitation and identification of potentially \nexploitable species of Diospyros and Dalbergia for their effective management and for forensics. As \npart of this initiative, work was undertaken to develop practical identification tools for both genera based \non morphological and eco -geographic characters, as part of the G3D taxonomy component led by the \nMissouri Botanical Garden’s Madagascar Program.  \nIdentification keys are generally based on morphological characters of plant organs and are \nprimarily used to distinguish species based, as far as possible, on easily observed features. Keys \nprimarily make use of the inflorescence structure and of characteristics of the flowe rs and fruits, often \ncomplemented by characters of the leaves as well as other aspects such as the plant’s growth form or \nhabit. They are nearly always dichotomous and are generally structured for publication in scientific \narticles or in floras and guidebooks. In this type of key, the sequence in which information is presented \nto the user is pre-determined by the author, usually by offering the user two mutually exclusive choices \n(a “couplet”) at each step by means of a text description of one or more alternative diagnostic characters \n(Judd et al. 1999; Hagedorn et al. 2010;  Griffing 2011), leading either to another couplet or to an \nidentification. However, when attempting to make an identification in the field, and especially if \nconfronted with a sterile individual (lacking flowers and fruits, which is often the case when conducting \nforest inventories), dichotomous keys based primarily or exclusively on reproductive organs are difficult \nif not impossible to use. Even when flowers and/or fruits are available, a key that employs specialized \nterminology can present problems that render it impractical to users not familiar with technical jargon. \nMoreover, published dichotomous keys cannot easily be modified or updated if new information \nbecomes available or new, morphologically similar species are recognized (Hardisty & Roberts 2013; \nMangold 2013; Zuquim et al. 2017). \nOne way to overcome these constraints is to develop keys that combine traditionally used characters \nwith new, informative featu res that have been underutilized or ignored, such as those involving \nvegetative structures, which are more likely to be observable regardless of the phenological stage, even \nin the absence of flowers and fruits. Leaf features are particularly pertinent in that they often enable \nrecognizing and distinguishing among closely related taxa (Hickey et al. 1999, Ellis et al. 2009) . \nSimilarly, while the utility of bark features for recognizing tree species is well known in temperate areas \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n4 \n \nfor genera such as Acer, B etula, Picea , Populus, and  Quercus, among others (Biswas et al. 2016; \nCarpentier et al. 2018; Wu et al. 2021; Juola et al. 2022), bark characters have not been used widely in \ntropical regions and very little in Madagascar. While bark characters have not be en utilized previously \nfor species delimitation and recognition of Malagasy Diospyros, field observations have clearly revealed \nsignificant variation among species, suggesting that they are of potential use for field identification. \nSimilarly, eco-geographic characters such as bioclimate, vegetation type, and elevation, which have \nproven to exhibit species-specific patterns and to be highly informative for species delimitation (Lowry \net al. 1999; Vences et al. 2009; Rabarimanarivo et al. 2015; Crameri et al . 2022), are also of potential \nvalue for informing accurate identification. \nIn the age of global access to information via the internet and the rapid development of \nbioinformatics tools and technologies, it is now possible to build interactive and richly illustrated, multi-\naccess identification keys that are simple, practical, and efficient. Moreover, these keys can be accessed \nthrough portable platforms that function independently, without needing an internet connection. This is \nprecisely the type of tool that is required to enable reliable identification of Malagasy Diospyros and \nDalbergia, employing a data matrix (or character/species) multi-access type of key, a model that is now \nbeing widely used (Begum et al. 2012; Wati et al. 2021) . Early multi-access keys were based on the \npunch card approach (Hansen & Rahn 1969), in which an array of characters with two or more states \nthat are not necessarily mutually exclusive are presented to the user, who is not required to follow a pre-\ndetermined sequence of steps (in contrast to conventional keys), but which can instead be used to select \nfeatures in the order that best corresponds to the material being identified. This type of key is particularly \nadvantageous when dealing with incomplete material (Ju dd et al. 1999, 2002). Several computer \nprograms have recently been developed to produce interactive, matrix-based, multi-access identification \nkeys (Dallwitz 2007; Gaubert et al. 2008; Hagedorn et al. 2010) such as DELTA and INTKEY (Dallwitz \n1993), FRIDA (Martellos 2010), LINNAEUS (Wati et al. 2018), Lucid (Norton et al. 2000), and Xper \nversions 2 et 3 (Ung et al. 2010; Vignes -Lebbe et al. 2016; Lombard et al. 2021). They all exploit \npractical and flexible methods for coding characters, and some can incorp orate illustrations (photos, \ndrawings, and maps), as well as videos, links to internet sites, and a glossary. The major advantages of \nthese keys are that they facilitate identification even when material is incomplete and are accessible for \na wide range of users, including those less familiar with the organisms being identified than professional \ntaxonomists. \nOne of the main objectives of the taxonomic component of the G3D project is to produce a tool \nthat can be used at the beginning of the precious wood va lue chain to obtain a reliable species \nidentification for each potentially exploitable tree  of Diospyros and Dalbergia, a required step for the \nsustainable management of these resources. To meet this need, the identification tool must work reliably \nfor trees that are still standing or that were recently felled, even if flowers or fruits are absent. After a \ncareful comparison of the advantages and drawbacks of each of the applications mentioned above, Lucid \nwas considered to be the best adapted to meet Madag ascar’s current needs for accurate field \nidentification. Lucid has already proven to be effective for the development of practical identification \nkeys for a wide diversity of objects, ranging from minerals to fossil bacteria and living animals, such as \ncertain insect groups, as well as algae and vascular plants (many examples in these and other groups can \nbe found on the Lucid website: http://lucidcentral.org/). \nThe work presented in this paper summarizes the development of a practical key using Lucid 4 to \nfacilitate the accurate and reliable identification of Malagasy species of Diospyros that are potential \nsources of commercially valuable ebony wood. As for large tree species of Dalbergia (Phillipson et al. \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n5 \n \n2023), a separate key has been developed  using the same software and following the same principles \nand methods but is not discussed further in this paper. \nDiospyros comprises an estimated 903 species of which 763 have been described to date, distributed \nacross the main tropical regions (see the following for examples of recent taxonomic accounts of \nDiospyros spp. from various parts of the world: Tang et al. 2019; Schatz et al. 2021b; Puglisi et al. 2022; \nHassler 2023; POWO 2023) and the remainder are currently in the process of being formally described. \nMadagascar represents one of the main centers of diversity for the genus, as indicated by the first \ncomprehensive revision for the island publi shed by Perrier de la Bâthie (1952a, b), who recognized a \ntotal of 97 species. However, collections and field observations made over the following decades clearly \nrevealed the presence of far greater species diversity, and this catalyzed a new effort to do cument and \ndescribe Malagasy Diospyros starting some 15 years ago. This has led to the recognition of an estimated \n285 species on the island, 145 of which have now been described and all but two of which are endemic \nto Madagascar (Schatz and Lowry 2018; Sc hatz and Lowry 2020; Schatz et al. 2020, 2021a, 2021b; \nLinan et al. 2021; Mestre et al. in press; Rakouth et al. 2023), while an additional ca. 140 endemic \nspecies remain to be described (Madagascar Catalogue 2024). Field work conducted as part of the G3D \nproject has contributed significantly to the available collection base, whose taxonomic component has \nnow clarified the delimitation and completed the description of all 88 ‘large tree’ species (Lowry et al. \n2024), each of which is regarded as a potential source of commercially valuable ebony wood by virtue \nof the fact that it has been documented to reach a diameter at breast height (DBH) of ≥ 20 cm and/or a \nheight of ≥ 20 m (Schatz et al. 2021b). \nSpecies of Diospyros are found throughout all regions of Mad agascar, but depending on a given \nspecies’ ecological preferences (altitude, substrate, habitat, etc.), they will generally be found in just one \nor two of Madagascar’s principal native vegetation types, including evergreen humid forest in the east, \nwoodland or shrubland in the west, and deciduous dry forest in the north (often on karstic limestone, \nknown as ‘tsingy’) or the south, as well as spiny thickets in the south and southwest (species of \nDiospyros are rare in montane vegetation).  Some have wide geographical ranges, occurring across large \nproportion of one or two of the island’s main bioclimatic regions, as defined by Cornet (1975) and \nsimplified by Schatz (2000), while others have highly restricted ranges (Madagascar Catalogue 202 4). \nA species’ eco -geographic preferences comprise valuable information that can complement \nmorphological characters for developing identification keys (Wati et al. 2018; Lombard et al. 2021). \nWith this in mind, we tested the value of including eco-geography in building our identification tool for \nlarge tree Diospyros species using the Lucid platform. \nThe tool we present here was designed primarily to assist an array of actors involved in various \naspects of the management and control of Madagascar’s forestry sector, in particular with regard to \ninventories of standing trees. These stakeholders include forestry agents, operators involved in wood \nharvest (including both landowners and concession holders), managers of protected areas and other \nconservation sites, customs of ficials, and officers of the judiciary police, among others. Moreover, \nbecause the key we have developed enables users to identify dried collections (i.e., herbarium \nspecimens) as well as living material, it will also be of value to researchers, field botanists, and students \nto improve their knowledge of the Malagasy species that are potential sources of commercially valuable \nebony wood and strengthen their ability to recognize them. \nMaterials and methods \nLucid 4 software \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n6 \n \nFor an identification tool to perform well and respond to Madagascar’s needs for managing precious \nwoods by enabling accurate identification of standing trees and dried specimens, it must be simple, \npractical, interactive, and portable. Among the various programs available to produce i nteractive, \nelectronic, matrix -based or multi -access keys, we selected Lucid version 4.0.4 \n(https://www.lucidcentral.org), which meets all of Madagascar’s needs for identifying large tree species \nof Diospyros in the field and herbarium. To our knowledge, Lucid keys have never been used before in \nMadagascar for species-level identification, even though keys can be distributed free of charge; only the \ndevelopers are required to obtain a license to produce an operational tool. Utilization of a Lucid -based \nkey does not require internet access, and it can easily be modified, corrected, and updated with little \neffort by the developer. However, the main reason we opted to employ this program is because it is \nsimple to use and functions without an internet connectio n, making it particularly well suited for field \nidentification in Madagascar, where there is usually no internet access. Moreover, Lucid keys can easily \nbe shared and transferred (by e -mail, USB key, etc.) and can be used freely in any browser and on a \nwide range of platforms (laptops and tablets, or smartphones via a mobile application). Lucid is also \npractical and intuitive, allowing users to access a wide range of visual and text-based descriptors as well \nas species profiles (Vignes -Lebbe et al. 2016; Pi nel et al. 2017). The developer is provided with an \nefficient interface containing all the tools and functionality needed to organize and deliver \nsupplementary information to the user (photos, line drawings, links to on-line sites, glossaries, etc.) for \neach species and for important of difficult-to-interpret characters, greatly increasing the user’s ability to \ngrasp and understand terminology, thus improving their ability to obtain an accurate identification. To \noptimize the functionality and utility of th e Lucid-based tool we have developed, it was designed to \nperform well even in the absence of flowers and fruits and to remain robust and reliable even if the user \nmisinterprets some characters. The tool thus provides efficient, multi -access entry according  to the \nuser’s needs and can deliver rapid and  accurate identifications as well as valuable diagnostic \ninformation. \nTaxa \nAmong the ca. 285 species of Diospyros recognized in Madagascar, 88 develop into large enough \ntrees to be potentially exploitable for ebony wood (Lowry et al. 2024) and are therefore included in the \nLucid key we have developed. Each species has its own particular geographic and bioclimatic \ndistribution range, reflecting its ecological preferences. For example, within the island’s humid \nbioclimatic zone, D. squamosa is widely distributed in dense, humid, evergreen forests of the northwest \nand along the eastern escarpment (Schatz and Lowry 2020), whereas D. littoralis is restricted to littoral \nforests on sand near the eastern coastline (Schatz et al. 2021a). Other species have narrow ranges and \nare known from only a few sites, such as D. lowryi and D. ultima, both from low elevation humid forests \nin the northeast and known from only 2 and 4 localities, respectively (Schatz and Lowry 2018; Schatz \net al. 2021a; Madagascar Catalogue, 202 4). Some species of Diospyros occur in dry, semi -deciduous \nforest on karstic limestone in the extreme north of the island, such as D. vescoi (which has a rather large \nrange) and D. crassifolia (much more narrowly distributed) (Linan et al. 2021). Still other species occur \nin areas with similar vegetation in the west, such as D. tropophylla and D. sakalavarum, which have \nfairly large ranges, and D. subtrinervis, known from a single locality. The risk of extinction for each of \nthe 88 large tree species was assessed between 2018 and 2021 according to the IUCN Red List criteria. \nA total of 45 species (51%) were a ssessed as threatened, including 5 that were found to be Critically \nEndangered (CR), 18 Endangered (EN), and 22 Vulnerable (VU), whereas 11 species were assessed as \nNear Threatened (NT), and 31 were regarded as Least Concern (LC). One species was Data Defi cient \n(DD) (IUCN Red List 2022). \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n7 \n \nBuilding the key \nThe key was constructed in four steps, implemented in the application’s key -building interface (Lucid \nBuilder), which comprises three tabs at the base of the tree panels [Tree View], [Spreadsheet Scoring] \nand [Score Analyser], as follows:  \n1) Data compilation within the [Tree View] tab \n2) Data coding and entry within the [Spreadsheet Scoring] tab \n3) Development of the key \n4) Testing, feedback, and improvement \nThe [Score Analyser] tab provides analyses of character differences and species polymorphism to assess \nand indicate where improvements can be made to the key. \nData compilation within the [Tree View] tab \nTaxonomic entities backbone  \nThe first tab [Tree View] enables the developer to view the structure (sequence and hierarchy) of \ncharacters and character states in the ‘features’ panel as well as a list of the species in the ‘entities’ panel. \nThe taxonomic entities backbone was establis hed by alphabetically entering the names of the 88 large \ntree Diospyros species in the [TreeView] tab. The species for which the key was developed are listed in \nAppendix 1 and can also be found on a dedicated page via the Catalogue of the Plants of Madagas car \n(Lowry et al., 2024). \nFeatures backbone \nThe initial step of selecting characters and scoring character states involved preparing a list of \npotentially informative features of the stems, leaves, flowers, and fruits that vary among the large tree \nspecies of Malagasy Diospyros. Additional characters that could facilitate reliable field identification \nwere then incorporated, in particular those that can only be observed in fresh material, including \nmacroscopic features of vegetative organs such as the bark, which are easily observable throughout the \nyear, even when an individual tree is sterile. For a key based exclusively on morphological data, the \nassumption is usually that any given species can occur anywhere within the geographic area being \nconsidered. This is clearly not the case, however, for Diospyros in Madagascar. We therefore compiled \nadditional information on the ecological preferences of each species (bioclimate, altitudinal range, and \nvegetation type) as well as the potential geographic range for each species, to improve ease of \nidentification by reducing the list of candidate species for a given site (Wati et al. 2018). The final \nselection of character features and the corresponding terminology included those that were determined \nto be the most pertinent for discriminating among the species and the easiest for users to interpret. The \nlist of characters and states was entered into the ‘features’ panel on the [TreeView] tab of Lucid Builder. \nThe features backbone of the key for the 88 species comprises data for morphological and eco -\ngeographic characters, including a total of 109 characters and 356-character states (Table in Appendix \n2). \nCompilation of data on morphological characters \nData on morphological character states exhibited by each species were primarily collected from \ndescriptions available in the literature, complemented and refined based on examination of specimens \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n8 \n \navailable in the herbaria of the Parc Botanique et Zoologique de Tsimbazaza, Antananarivo, Madagascar \n(TAN), the Missouri Botanical Garden, St. Louis, Missouri, USA (MO), and the Muséum National \nd’Histoire Naturelle (MNHN), Paris, France (P), as well as scans of selected specimens available online. \nThis was further enriched with field observations recorded by collec tors on specimen labels (Lombard \n2021) and photos of living material, notably taken as part of the G3D project, showing details of habit, \nbranching, bark, leafy branches, flowers, and fruits, which provide more precise information on \ncharacter states seen on standing trees, whereas information obtained from the literature and pressed \nspecimens is more informative for  making identifications of herbarium material (Figure 1, Table in \nAppendix 2). \nAs mentioned above, bark characters have been shown to be of val ue for species identification in \ntemperate genera but have been less widely used in the tropical areas , including Madagascar, where \nscientists have only rarely used bark characters. In the absence of a standard method for describing bark \nfeatures, we drew from the works of several authors (Letouzey 1969-1972; Junikka 1994; Rakotovao et \nal. 2012; Biswas et al. 2016; Carpentier et al. 2018 ) to identify those of potential value for Malagasy \nDiospyros. Three types of easy -to-observe characters were retained: bark surface texture (smooth, \nfissured, scaly, rugose), the presence of distinctive structures (lenticels, fissures, longitudinal and \ntransverse striations, scales, a crust, crevasses, etc.), and overall color, both in vivo and in sicco (Figure \n2). To compile information on these characters for each species, we examined photos of tree trunks and \nbark samples taken in the field, along with high resolution images of dried bark material associated with \nherbarium specimens (Figure 2). High resolution photos were taken at the Scientific Imaging Workshop \n(UAR 2700 2AD, BAOBAB facilities, DIM -MAP Île-de-France, CNRS and MNHN) located at the \nMuséum in Paris. For Madagascar, the use of bark features to identify species for the development of a \npractical identification tool represents pioneering work. \nCompilation of data on eco-geographical characters  \nInformation on ecological preferences and geographic distribution is also useful for facilitating the \nidentification of Malagasy species of Diospyros given that each of them has its own distinctive \nspecificities. We used QGIS (3.16.8 with GRASS 7.8.5) to visualize distribution data for each species \n(as a .kml points layer) and to record their eco-geographic characteristics using three key descriptors: \n• Madagascar’s five main bioclimatic regions (humid, subhumid, dry, subarid, and montane), \nbased on the bioclimatic map of Cornet (1974) as simplified by Schatz (2000) \n• Five altitudinal classes between 0 and 2500 m (in 500 m increments); <500 m, <1000 m, <1500 \nm, <2000, and 2000 m or more. \n• Potential geographic distribution: actual and potential presence in Madagascar was recorded in \ncells of 1˚×1˚ resolution; potential presence was extrapolated from known occurrence points. \n \n \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n9 \n \n \nFigure 1. Photographs of selected large tree species of Diospyros, showing various morphological features of their leaves, \nfruit, and fruiting calyx. 1 D. aculeata, leaf apices terminating in a thorn and  fruiting calyx completely enclosing the fruit  \n(photograph by F. Ratovoson)  2 D. antsirananae , densely pubescent leaves and fruit, with reddish brown to ferruginous   \ntrichomes (photograph by S. Rakotonandrasana) 3 D. bernieriana, margins of the leaves undulate and fruiting calyx expanding \nto enclose the fruit completely and form a prominent collar (photograph by G.E. Schatz) 4 D. crassifolia, coriaceous, elliptic \nleaves and erect fruiting calyx lobes (photograph by S. Rakotonandrasana) 5 D. humbertiana, small, obovate leaves and fruiting \ncalyx with 4 spreading lobes (photograph by P. Lowry) 6 D. labatiana, fruit surface and inner portion of calyx lobes covered \nby a white waxy substance (photograph by S. Andrianarivelo) 7 D. maculata, glabrous leaves and fruit with an entire (unlobed), \ncupuliform calyx (photograph by P. Lowry) 8 D. parifolia, subopposite to opposite, coriaceous, glabrous leaves  (photograph \nby S. Andrianarivelo) 9 D. plicaticalyx, lenticellate, gray/grayish twigs and fruiting calyx with undulate and plicate margins \n(photograph by G.E. Schatz). \n \nFigure 2. Examples of the three bark characters utilized in the Lucid key for Malagasy Diospyros (texture, presence of \ndistinctive structures, and color). A smooth, lenticellate, gray/grayish bark of D. ferrea. B smooth, fissured, gray/grayish to \nlight brown bark of D. chitoniophora (left) and D. bardotiae (right). C rugose, light brown bark with longitudinal striations of \nD. brevipedicellata. D rugose, deeply fissured, cracked, dark brown to black/blackish bark of D. clusiifolia  (left) and D. \ntoxicaria (right) (all photographs by H.N. Rakouth). \n \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n10 \n \nData scoring within the [Spreadsheet Scoring] tab \nScoring of features and states that correspond to each species was done for both qualitative and \nquantitative characters using the second tab in the key-building interface [Spreadsheet Scoring], which \ncontains the data matrix of characters and species . Those that can potentially be misinterpreted, e.g. \ncertain leaf shapes (elliptic, oblong, ovate, etc.), can be recorded in Lucid in a way that accommodates \nfor potential user error. By using this feature, species are retained in the final list of potential results that \nwould otherwise have been excluded due to the incorrect selection a character state that is in fact not \nfound in material belonging to the taxon. This is a helpful option since the interpretation of character \nstates is not always straightforward  and can vary between users. For a species that exhibits \nmorphological variability, all possible character states are coded, enabling the user to select more than \none state for a polymorphic feature. On the other hand, even if certain character states have not actually \nbeen observed on material of a given species, the person building the key can nevertheless select states \nthat could reasonably be expected to be expressed and could therefore be encountered by a user or could \nbe inadvertently selected due to a misinterpretation. To record information on the reliability of the states \nknown for a particular character, a blue symbol is selected when the interpretation is verified and \nunambiguous, whereas a red symbol is chosen in situations where misinterpretatio n by the user is \npossible or likely. Rare or exceptional character states are indicated by a green symbol and those that \nare both rare and prone to misinterpretation are indicated in yellow. Finally, a question mark is used for \ncharacters whose state(s) is (are) uncertain or for which data are unavailable (Figure 3). The Lucid tool \nfor Malagasy Diospyros has thus been designed to function regardless of which plant organs are \navailable for identification and to be reliable even when there is a risk of potent ial errors for certain \ncharacters due to user misunderstanding or misinterpretation. \nQuantitative characters were counted or measured to code numerical values (#) in the data matrix \ntable. This information was recorded in a table comprising four columns: o utside minimum value, \nnormal minimum value, normal maximum value, and outside maximum value, in which the normal \nvalues are calculated as the most frequent class of observations [normal min - normal max] in all \nmeasured samples. For example, in Figure 3, the normal values are comprised in the class [0.8–0.9 cm] \nof the character “width of the largest leaf”, among 10 measured leaves. Counts or measurements were \nsystematically made on an organ or structure regarded as being fully mature, and in order to standardize \nand facilitate comparison, the largest values were always used. For example, leaf dimensions were \nmeasured on the largest leaf on a leafy branch (Figure 3). \nTo score the potential geographic distribution of each species treated in the key, a gr id comprising \n75 cells, each with an area of 1˚×1˚, was superimposed over a map of Madagascar, which is situated \nbetween 11° to 25° S latitude and 43° to 50° E longitude. Taking into consideration the known range of \neach of the 88 Diospyros species as well  as its eco -geographic preferences, the potential geographic \nrange was scored in the appropriate cells. The convention used to name a given cell was based on the \ndegree values for longitude and latitude corresponding to the points it encompasses. For examp le, the \ncell containing the coordinates of a population of D. aculeata located at 45°16’23” E longitude and \n22°54’05” S latitude was labeled 4522, as shown in Figure 4 A-D. This allowed for scoring of \nlongitudinal bands of presence, which, given the shape of Madagascar, were comparatively fewer in \nnumber than the alternative, using latitudinal bands of presence. Hence, the potential distribution of each \nspecies was characterized as a range within one or more longitudinal bands, and these were entered into \nLucid as a quantitative variable with multiple independent ranges. We intentionally used a conservative \napproach for the process of estimating potential range, including all grid cells in which the species could \nreasonably be anticipated to occur. The resulting potential distribution was then systematically reviewed \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n11 \n \nand validated by comparison with expert information provided by field botanists and taxonomists \nworking on Malagasy Diospyros. \n \nFigure 3 . A Screenshot of the Diospyros Lucid key -builder showing the data matrix table and the methods for scoring \ncharacter data. B Inner pop-up table for numeric scores (#) of quantitative characters (here, width of largest leaf in cm) . C \nThe 5 types of usable interpretation scores for qualitative characters colored differently depending on the level of the \ncharacter’s certainty: ver ified and unambiguous (blue), possible or likely to be misinterpreted (red), rare (green), rare and \nprone to misinterpretation (yellow), uncertain (?). \nDevelopment of the key \nThe process of developing the Diospyros key involved making changes and fine -tuning it to enhance \nboth its functionality and visual aspects in an effort to make it as user -friendly and straight forward as \npossible while retaining the ability to incorporate various types of supplementary information to improve \nidentification accuracy. As English is the default language for Lucid, it was utilized in the development \nof the prototype Diospyros key. Considering the varying levels of botanical knowledge and familiarity \nwith terminology among users in Madagascar, the key was designed to employ concise terminology for \ncharacters (features) while avoiding complex technical terms. Nevertheless, certain scientific terms were \nretained to maintain precision. For example, the technical term “brochidodromous” was used to define \nleaf venation in which s econdary veins do not terminate at the margin but join to form a series of \nprominent arches, which form a submarginal nerve (Ellis et al. 2009).  \n \n \n \n A \n B \n C \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n12 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \nFigure 4. A & B Screenshot from QGIS 3.16.8 C & D Screenshot of Lucid key builder. A current distribution map visualized \non QGIS within Madagascar  B Map of the southern part of Madagascar showing grid cells (red dashes) encompassing the \npotential range visualized on QGIS C some of the eco-geographic features employed (elevation and geographic coordinates) \nD Coordinate position coding system using the degree values of each 1 x 1 degree cell. \nMedia tool function  \nTo augment the utility of the key, images were incorporated for  each species, including photos of \nliving plants as well as details of particular organs and distinctive features, accompanied by scans of \nherbarium specimens and line drawings as exemplars. Using the image viewer function of Lucid, the \nuser can thus scrol l among images and zoom in as needed to facilitate comparison with the material \nbeing identified. Selected images were recomposed to highlight key characters and character states in \nthe ‘features’ window, and photos were taken of informative structures from herbarium specimens (e.g., \nleaves, fruits, bark samples, etc.) using the high-resolution imaging equipment at the MNHN in Paris (a \nNikon D7100 camera with a Nikkor AF-S 60 mm macro lens mounted on a Kaiser light stand equipped \nwith a Cognisys StackShot Macro rail). Two methods were employed. For two-dimensional objects such \nas leaves, photos were taken using the macro mode in the Nikon Camera Control software (ver. 2.0), \nwhereas for large objects such as fruits or those with significant relief (e.g., bark), z-stacking was done \nusing the Helicon Remote program (ver. 3.9.12) and Helicon Focus (ver. 8.1.1), which creates a final \nimage with unlimited depth of field by electronically superimposing the in-focus portions of a series of \nshots taken at distinct lev els and combining them into a single image that clearly shows the entire \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n13 \n \nstructure being photographed. A total of ca. 4,500 images were taken from 200 bark samples \nrepresenting 40 of the 88 large tree species of Diospyros (bark material was not available for the other \n48 species).  \nAn integrated glossary provides quick access to clear definitions of all technical terms, often \naccompanied by photos and/or illustrations. The definitions presented to the user were compiled from \nseveral widely used sources, including Beentje (2016) and H arris & Harris (2001) for general \nterminology, and Ellis et al. (2009) for features relating to leaf architecture. The utility of the Diospyros \nkey was further strengthened by providing links to internet sources for each species, including the \ncorresponding pages in the Madagascar Catalogue (2024) and the IUCN Red List (2023), although these \ncan only be accessed when connected to the internet. However, because precise information on the \ndistribution of precious wood species is potentially sensitive, access to maps and full data on known \noccurrences is limited in these on-line sources and is not available to the general public. \nTesting the key and integrating feedback \nEarly iterations of the Diospyros key underwent thorough evaluation and testing by botanists \nfamiliar with Madagascar's precious woods, particularly Diospyros, as well as by non-specialists. This \nwas done during a series of working sessions in which participants provided feedback through evaluation \nforms. The results were utilized to enhance and fine -tune both the structure and content of the key. \nSubsequently, three initial trial identification workshops using herbarium specimens were held (in June \nand September 2021, and October 2022) fo r groups of participants with varying levels of knowledge \nand experience. The main objectives were to: \n1) Review and discuss the multi -access structure of the key and ease of interpretation of the \ncharacters \n2) Determine which of the morphological and eco-geographic characters were the most informative \nfor making accurate species-level identifications \n3) Test the overall performance of the key and identify problems or gaps \nIn April 2022, an additional test workshop was conducted for students participating i n the \nMadagascar precious woods project at the University of Antananarivo, and six regional training \nworkshops were organized between November 2022 and August 2023 for various important stakeholder \ngroups such as customs agents, members of the judiciary po lice, police officers, forestry agents, and \nconservation site managers. The purpose of these workshops was to introduce the key to the participants \nand gather their comments and suggestions. \nResults \nKey efficacy, character performance, and limits \nDuring the initial test sessions, participants were able to achieve correct identifications from 65 –\n75% of the time. The feedback received after each workshop was then used to make improvements to \nthe Diospyros key. Specifically, adjustments were made rega rding the organization and structure of \ncharacters and character states. The presentation to the user was also modified based on the logical \nprogression from basal to apical organs and from macro - to microscopic features. Additionally, the \ncharacters were re-categorized into two main groups within the key, “Morphology” and “EcoGeo”. \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n14 \n \nThe results obtained from the trials indicated that the initial versions of the key were  highly \nsuccessful at leading users to the correct identification. The fact that the key is designed to allow multi-\naccess utilization was clearly a strength because it enabled the users to follow their intuition when \nselecting the order of characters to be entered. The botanists who tested the key made several suggestions \nfor its improvement and for how it can be used most efficiently. They first recommended that a user first \nnote any obvious and striking features of the material being identified. For example, one of the most \nevident characters in fresh material of Diospyros rubripetiolata is the red tinge of the petiole, and if the \nuser goes directly to the ‘features’ window and selects Morphology/Leaves/Petiole/Color_in_vivo/Red, \nthe number of ‘discarded entities’ that do not express this particular character state (which is indicated \nin the lower left of the window) is indicated as 87, while the number of ‘remaining entities’ is indicated \nas 1 in the upper right, corresponding to D. rubripetiolata (Figure 5). By clicking on the first photo in \nthe species profile, the ‘image viewer’ displays a ll 11 images corresponding to the species, several of \nwhich clearly show the red petioles, thereby rapidly facilitating verification of the identification. \nThe second suggestion made during the test phase was that, in the absence of obvious and \ninformative morphological characters, the user should start by focusing on eco-geographic parameters. \nIn particular, they should begin by entering the geographic coordinates (longitude and latitude) of the \nlocation where the sample was obtained, which prov ides an efficient way to reduce the number of \ncandidate species. For example, when one enters the coordinates corresponding to the 1˚×1˚ cell for \nlocalities with a longitude starting with 46˚E and a latitude starting with 15˚S (using the format called \nfor in the key, ‘4615’), 74 entities are excluded and only 14 candidate species are retained (i.e., just 16% \nof the 88 large tree species of Diospyros occurring in Madagascar). \nA third suggestion was that, when using vegetative characters, leaf features should be considered \nfirst because they are often the most effective for distinguishing species from one another. For example, \nthe cordate leaf shape of Diospyros vescoi combined with the presence of indument on both surfaces of \nthe leaf blade are diagnostic for this species.  When reproductive organs are available, the fruit is often \nuseful and informative, especially features of the fruiting calyx, such as the degree to which it c overs \nthe fruit surface and the presence/absence of lobes. As an example, if the initial entry of characters \nindicates D. mapingo and D. tropophylla as the two remaining candidate species, they can easily be \ndistinguished based respectively on the presence or absence of lobes on the fruiting calyx. \nRegarding characters seen as difficult to interpret or not particularly useful or pertinent for \nidentification in the field or the herbarium (and thus rarely chosen during testing), the participants \nmentioned that subjective or ambiguous features requiring the user to make a personal interpretation, \nsuch as color (for both fresh or dried material) and leaf texture, were frequently scored differently by \ndifferent persons. Likewise, it can be challenging to select t he correct character state for features such \nas trichome type and length, which often requires using a hand lens or microscope, and is thus not always \npossible or practical in the field, especially for someone who is not familiar with the corresponding \ntechnical terminology. These characters are therefore more appropriate for identifying herbarium \nspecimens and for use by experienced botanists. \nAfter incorporating user feedback and remarks to improve the overall accuracy, appearance, and \nuser-friendliness of the Diospyros key, it is now fully operational, enabling error -free identification of \nspecies 90-100% of the time. \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n15 \n \n \nFigure 5. Screenshot of the deployed key in the Lucid player interface showing use of the characters that are most obvious \nwhen examining a sample with the naked eye. The example shown here assumes that the key had already been used to identify \na sample taken from a tree in the field whose leaves have a red petiole. A By selecting the character state “red” for petiole color \nin vivo, a single candidate species is retained. B Window showing the number of selected features and the chosen path.  C \nWindow showing the numb er of remaining entities after one or more characters have been selected, in this case, the single \nentity corresponding to Diospyros rubripetiolata; the image viewer can be accessed by clicking on the first image displayed. \nD Window indicating the number of discarded entities; in this case, the 87 species that did not meet the selected identification \ncriterion ‘red petioles in vivo’. \nSeveral practical aspects should be considered when developing and refining Lucid keys such as the \none we have prepared for Malagasy Diospyros. The use of English could be an issue for some users not \nintimately familiar with terminology in this language. Several participants suggested during the testing \nphase that it would be helpful to have a vers ion in French or even in Malagasy (which would be more \nchallenging to develop as many technical terms do not exist in this language). It would also be helpful \nto have a version developed for use on smartphones, which are more portable and would facilitate use \nat remote field sites lacking internet access. Conversion of the Lucid tool into a mobile application for \nAndroid or iOS can be done, but publication of a fully functional key would involve an additional 5 -\nstep development phase requiring paid services that can only be provided by the Lucid team. \nConclusions and perspectives \nAs part of a coordinated effort to promote the sustainable and equitable use of precious woods \nresources in Madagascar in response to the CITES Action Plan regarding the genera Diospyros and \nDalbergia, and in particular with respect to the development of practical and reliable identification tools \nfor species that are of potential commercial interest, we have developed a key using Lucid that can be \nemployed to identify standing and recently felled trees as well as herbarium specimens. This powerful, \ninteractive, multi-access key can be used without an internet connection and is accessible to a broad \ngroup of users, ranging from non -specialists to experienced botanists. Moreover, s ince most trees \nencountered during forest inventories lack flowers and fruits, the key was designed specifically to enable \naccurate identification of sterile material using characters that can be observed in the field throughout \nthe year. Special attention  was given to incorporating vegetative characters, including bark features, \nwhich have been shown to be useful and informative for distinguishing Diospyros species in the field \n(further work is being conducted to explore the taxonomic value of bark charact ers). Eco-geographic \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n16 \n \nfeatures were also used to develop the key and were found to be particularly valuable for increasing the \nspeed and accuracy of identifications by returning only candidate species that are known or inferred to \noccur within a given 1˚×1˚ cell. \nThe morphological and eco -geographic characters employed in our key enable accurate \nidentification of all 88 species of Diospyros in Madagascar that form large enough trees to be potential \nsources of commercially valuable ebony wood. Each species is  accompanied by its own set of images \nto help verify initial identifications, along with links to additional information available online, and most \ntechnical terms are likewise illustrated to facilitate accurate comprehension and interpretation. Lucid is \na tried and tested platform that is flexible and offers many useful options, enabling regular improvements \nand updates, including the addition of new species and informative characters. For example, as work \nprogresses on developing a comprehensive understanding of characters based on anatomy, spectroscopy, \nand even DNA barcoding of Malagasy Diospyros, taxonomically informative features can be \nincorporated into our key. As part of the G3D project focusing on precious woods in Madagascar, a key \nhas also been developed for the 56 large tree species of Dalbergia from which rosewood and palisander \nare obtained. \nThere remain some aspects that could be refined for further improvement of the current version of \nthe key. Additional field testing encompassing multiple p opulations of each species (especially those \nthat exhibit significant morphological variation) would be valuable. This could improve our knowledge \nof character variation, add new features while removing those that are less informative or more difficult \nto interpret, and fill gaps in character states for some species (notably for bark features), identifying and \ncorrecting errors that may have inadvertently been introduced into the character data matrix. After an \nongoing round of improvements now being completed, the key will be translated into French to render \nit more accessible for francophone users and in parallel we will seek support to develop and test a stand-\nalone, portable version for smartphones. Finally, the methods and approach used to develop this practical \nidentification tool for exploitable Malagasy Diospyros species could easily be expanded to include all \nca. 285 members of the genus occurring on Madagascar and all 83 species of Dalbergia (Madagascar \nCatalogue, 202 4) as well as to other groups (genera and even families) of plants and animals of \ncommercial and/or scientific interest. \nKey security and accessibility \nBecause many of the Diospyros species harvested in Madagascar as sources of ebony wood are \nthreatened by over -exploitation and illegal logging, information relating to their characterization and \ndistribution is potentially sensitive. To ensure that access to and use of the prototype key presented here \nfor identifying large tree species can be adequately controlled, we have opted to host it on a password \nprotected server, making it available to appropriate users when a request is sent to the first author. Upon \nobtaining a password, the user will be able to access an html link that can be opened on any web browser, \nboth online or offline. \n \n \n \n \nAuthor-formatted, not peer-reviewed document posted on 16/08/2024. DOI:  https://doi.org/10.3897/arphapreprints.e134616\n\n17 \n \nAcknowledgments \nWe are grateful to the G3D consortium, the Fondation Franklinia, and the “Bourse du Gouvernement \nFrançais” (BGF) through the French Embassy in Madagascar (SCAC) for financial support, and to the \nherbarium of the MNHN in Paris for providing the first author with full access to its collections. Many \nthanks go to the MBG field botanists in Madagascar for the collection of materials used in this study \nand for their beautiful field photos available in the Tropicos image gallery. Special thanks to the Atelier \nd’Iconographie Scientifique, UMS 2700 2AD MNHN and Didier Geffard for the use of the photographic \nequipment and help with the capturing and processing of images. The curators of the herbaria whose \nmaterial was consulted (MO, P, TAN, TEF) are gratefully acknowledged. Roger Lala Andriamiarisoa \nand Alain Jouy kindly provided excellent illustrations used in the key and we thank the participants in \nthe testing workshops, who contributed much to improving the current version of the key by offering \nfeedback and comments. \nReferences \nAndriamanana DJ (2019) Gouvernance du secteur forestier à Madagascar : analyse du mécanis me de \nprise de décision dans le cadre de la lutte contre le trafic de bois précieux. Thèse de doctorat en \nSciences Agronomiques et Environnementales. École Supérieure des Sciences Agronomiques. \nAntananarivo.  \nAndriambololonera S, Andrianarivelo S, Ravololomanana N, Randriambololomamonjy O (2013) \nRapport de l’étude sur les taxons de bois précieux Diospyros spp. et Dalbergia spp. en vue de leur \ninscription dans l’annexe II de la CITES. 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WSN 42 (2016) 143-155.pdf \nCarpentier M, Giguere P, Gaudreault J (2018) Tree species identification from bark images u sing \nconvolutional neural networks. In: IEEE International Conference on Intelligent Robots and \nSystems (IROS), pp. 1075–1081. https://doi.org/10.1109/IROS.2018.8593514 \nCITES (1978) Convention on International Trade in Endangered Species of wild fauna and flora. \nEnvironmental Policy and Law 4: 51–52. https://doi.org/10.1016/S0378-777X (78)80178-4 \nCITES (2013a) Convention on International Trade in Endangered Species of wild fauna and flora. \nCoP16 Prop. 58. Consideration of proposals for amendment of Appendic es I and II.  \nhttps://www.cites.org:sites/default/files/eng/cop/16/prop/E-CoP16-Prop-58.pdf  \nCITES (2013b) Convention on International Trade in Endangered Species of wild fauna and flora. \nCoP16 Prop. 63. 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