Increasing accuracy: The advantage of using open access species occurrence database in the Red List assessment

Abstract

Abstract. Robiansyah I, Wardani W. 2020. Increasing accuracy: The advantage of using open access species occurrence database in the Red List assessment. Biodiversitas 21: 3658-3664. IUCN Red List is the most widely used instrument to assess and advise the extinction risk of a species. One of the criteria used in IUCN Red List is geographical range of the species assessed (criterion B) in the form of extent of occurrence (EOO) and/or area of occupancy (AOO). While this criterion is presumed to be the easiest to be completed as it is based mainly on species occurrence data, there are some assessments that failed to maximize freely available databases. Here, we reassessed the conservation status of Cibotium arachnoideum, a tree fern distributed in Sumatra and Borneo. This species was previously assessed by Praptosuwiryo (2020, Biodiversitas 21 (4): 1379-1384) which classified the species as Endangered (EN) under criteria B2ab(i,ii,iii); C2a(ii). Using additional data from herbarium specimens recorded in the Global Biodiversity Information Facility (GBIF) website and from peer-reviewed scientific papers, in the present paper we show that C. arachnoideum has a larger extent of occurrence (EOO) and area of occupancy (AOO), more locations and different conservation status compared to those in Praptosuwiryo (2020). Our results are supported by the predicted suitable habitat map of C. arachnoideum produced by MaxEnt modelling method. Based on our assessment, we propose the category of Vulnerable (VU) C2a(i) as the global conservation status for C. arachnoideum. Our study implies the advantage of using open access databases to increase the accuracy of extinction risk assessment under the IUCN Red List criteria in regions like Indonesia, where adequate taxonomical information is not always readily available.

To clean or not to clean: Cleaning open‐source data improves extinction risk assessments for threatened plant species

“…However, a consequence of aggregating data in this way is the potential inclusion of unclean data that can influence subsequent analysis, with measures such as EOO shown to be sensitive to outliers (Burgman & Fox, 2003). Both BIEN and GBIF data have already featured in extinction risk research (Doughty et al, 2016; Robiansyah & Wardani, 2020) but differences between data sources for the estimation of metrics such as EOO and resulting threat categories have yet to be examined.…”

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

“…Similar georeferencing deficits were identified in DAI for plant species endemic to the Brazilian Atlantic Forest, one of the best‐documented phytogeographic domains in Brazil; 75% of occurrence records lacked valid spatial information and 22% of species lacked any spatial data in GBIF (Colli‐Silva & al., 2020). This deficit of high‐quality geospatial data is particularly concerning in light of the increasing tendency to estimate extinction risk based on DAI alone (e.g., Pelletier & al., 2018; Stévart & al., 2019; Robiansyah & Wardani, 2020). Such an approach tends not only to overstate the proportions of assessed species deemed threatened (by up to 50%), but also to overlook the species most likely to be threatened because their georeferenced occurrence records are often too few to meet thresholds for inclusion in such analyses (Nic Lughadha & al., 2019; Walker & al., 2019).…”