The ECAT dataset: expert-validated distribution data of endemic and sub-endemic trees of Central Africa (Dem. Rep. Congo, Rwanda, Burundi)
2022
Tack, Wesley | Engledow, Henry | Veríssimo Pereira, Nuno | Amani, Christian | Bachman, Steven, P. | Barberá, Patricia | Beentje, Henk Jaap | Bouka, Gaël, U D | Cheek, Martin | Cosiaux, Ariane | Dauby, Gilles | de Block, Petra | Ewango, Corneille, E N | Fischer, Eberhard | Gereau, Roy, E | Hargreaves, Serene | Harvey-Brown, Yvette | Ikabanga, Davy, U | Ilunga Wa Ilunga, Edouard | Kalema, James | Kamau, Peris | Lachenaud, Olivier | Luke, Quentin | Mwanga Mwanga, Ithe | Ndolo Ebika, Sydney, T | Nkengurutse, Jacques | Nsanzurwimo, Aimable | Ntore, Salvator | Richards, Sophie, L | Shutsha Ehata, Reddy | Simo-Droissart, Murielle | Stévart, Tariq | Sosef, Marc, S M | Meise Botanic Garden [Belgium] (Plantentuin) | Université officielle de Bukavu | Royal Botanic Gardens [Kew] | Missouri Botanical Garden | International Union for Conservation of Nature (IUCN) | University of Yaoundé 1 = Université de Yaoundé I | Université de Montpellier (UM) | Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Montpellier (UM) | Université libre de Bruxelles (ULB) | Université de Yaoundé I (UY1)
International audience
Show more [+] Less [-]English. In this data paper, we present a specimen-based occurrence dataset compiled in the framework of the Conservation of Endemic Central African Trees (ECAT) project with the aim of producing global conservation assessments for the IUCN Red List. The project targets all tree species endemic or sub-endemic to the Central African region comprising the Democratic Republic of the Congo (DR Congo), Rwanda, and Burundi. The dataset contains 6361 plant collection records with occurrences of 8910 specimens from 337 taxa belonging to 153 genera in 52 families. Many of these tree taxa have restricted geographic ranges and are only known from a small number of herbarium specimens. As assessments for such taxa can be compromised by inadequate data, we transcribed and geo-referenced specimen label information to obtain a more accurate and complete locality dataset. All specimen data were manually cleaned and verified by botanical experts, resulting in improved data quality and consistency.
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