RESUMO
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.
RESUMO
Wild coffee species are critical for coffee crop development and, thus, for sustainability of global coffee production. Despite this fact, the extinction risk and conservation priority status of the world's coffee species are poorly known. Applying IUCN Red List of Threatened Species criteria to all (124) wild coffee species, we undertook a gap analysis for germplasm collections and protected areas and devised a crop wild relative (CWR) priority system. We found that at least 60% of all coffee species are threatened with extinction, 45% are not held in any germplasm collection, and 28% are not known to occur in any protected area. Existing conservation measures, including those for key coffee CWRs, are inadequate. We propose that wild coffee species are extinction sensitive, especially in an era of accelerated climatic change.
Assuntos
Coffea/fisiologia , Espécies em Perigo de Extinção , Extinção Biológica , Etiópia , Banco de Sementes , Desenvolvimento SustentávelRESUMO
Herbarium specimens provide verifiable and citable evidence of the occurrence of particular plants at particular points in space and time, and are vital resources for assessing extinction risk in the tropics, where plant diversity and threats to plants are greatest. We reviewed approaches to assessing extinction risk in response to the Convention on Biological Diversity's Global Strategy for Plant Conservation Target 2: an assessment of the conservation status of all known plant species by 2020. We tested five alternative approaches, using herbarium-derived data for trees, shrubs and herbs in five different plant groups from temperate and tropical regions. All species were previously fully assessed for the IUCN Red List. We found significant variation in the accuracy with which different approaches classified species as threatened or not threatened. Accuracy was highest for the machine learning model (90%) but the least data-intensive approach also performed well (82%). Despite concerns about spatial, temporal and taxonomic biases and uncertainties in herbarium data, when specimens represent the best available evidence for particular species, their use as a basis for extinction risk assessment is appropriate, necessary and urgent. Resourcing herbaria to maintain, increase and disseminate their specimen data is essential to guide and focus conservation action.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.