Affiliation:
1. Programa de Pós‐Graduação em Ecologia e Conservação Universidade Federal Rural do Semi‐Árido Mossoró Rio Grande do Norte Brazil
2. Departamento de Biociências Universidade Federal Rural do Semi‐Árido Mossoró Rio Grande do Norte Brazil
3. College of Engineering, IT and Environment Charles Darwin University Casuarina Northern Territory Australia
Abstract
AbstractUnderstanding the distribution of rare species is important for conservation prioritisation. Traditionally, museums and other research institutions have served as depositories for specimens and biodiversity information. However, estimating abundance from these sources is challenging due to spatiotemporally biased collection methods. For instance, large‐bodied reptiles that are found near research institutions or in popular, easily accessible sites tend to be overrepresented in collections compared to smaller species found in remote areas. Recently, a substantial number of observations have been amassed through citizen (or community) science initiatives, which are invaluable for monitoring purposes. Given the unstructured nature of this sampling, these datasets are often affected by biases, such as taxonomic, spatial and temporal preferences. Therefore, analysing data from these two sources can lead to different abundance estimates. This study compiled data on Brazilian reptile species from the Global Information Biodiversity Facility (GBIF). It employed a community‐ecology approach to analyse data from research institutions and citizen science initiatives, separately and collectively, to assess taxonomic and spatial species coverage and predict species rarity. Using a 1‐degree hexagonal grid, we analysed the spatial distribution of reptile communities and calculated rarity indices for 754 reptile species. Our findings reveal that 87 species were exclusively recorded in the citizen science subset, while 212 were recorded only by research institutions. The number of observations per species in the citizen science data followed a Gambin distribution, which aligns with the expected pattern of abundance in natural communities, unlike the data from research institutions. This suggests that citizen science data may be a more accurate source for estimating species abundance and rarity. The discrepancies in rarity classifications between the datasets were likely due to differences in sample size and potentially other sampling parameters. Nevertheless, combining data collected by both research institutions and citizen science initiatives can help to fill knowledge gaps in reptile species occurrence, thus enhancing the foundation for conservation efforts on a national scale.