The ECAT dataset: Expert-validated distribution data of endemic and sub-endemic trees of Central Africa (Dem. Rep. Congo, Rwanda, Burundi)

Tack Wesley, Engledow Henry, Veríssimo Pereira Nuno, Amani Christian, Bachman Steven P., Barberá Patricia, Beentje Henk J., Bouka-Dipelet Ulrich Gaël, Cheek Martin, Cosiaux Ariane, Dauby Gilles, De Block Petra, Ewango Corneille, 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.. 2022. The ECAT dataset: Expert-validated distribution data of endemic and sub-endemic trees of Central Africa (Dem. Rep. Congo, Rwanda, Burundi). PhytoKeys, 206 : 137-151.

https://doi.org/10.3897/phytokeys.206.77379

Article de revue ; Data paper ; Article de revue à facteur d'impact Revue en libre accès total

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Url - jeu de données - Entrepôt autre : https://zenodo.org/record/7007770

Résumé : 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.

Mots-clés Agrovoc : distribution géographique, biodiversité, Magnoliophyta, taxonomie, flore, herbier, phylogénie

Mots-clés géographiques Agrovoc : Afrique centrale, République démocratique du Congo, Burundi, République centrafricaine, Congo, Rwanda, Afrique

Mots-clés libres : Africa, Conservation, Data capture, Data cleaning, Endemics, Flora, Lowering plants, Geographic range, Herbarium, IUCN Red List, Threatened