Continent-wide recent emergence of a global pathogen in African amphibians
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These datasets are associated with the study entitled, "Continent-wide recent emergence of a global pathogen in African amphibians." In this study we describe the historical and recent biogeographical spread of a fungal pathogen of amphibians, <em>Batrachochytrium dendrobatidis</em> (<em>Bd</em>) and assess its risk to amphibians across the continent of Africa. The larger combined file, "AfricaBd_CombinedFile_LitReview_BdMaps_GhoseData.xlsx", contains <em>Bd</em> occurrence records processed by the authors of the study (N=4,623) and previously published records (N=12,297). Of the previously published records, 12,234 records came from studies reporting both <em>Bd</em>-negative and <em>Bd</em>-positive records (i.e. prevalence) that we used along with our data (N=4,623) to assess emergence of <em>Bd</em> in African amphibians. The file "AfricaBd_Ghosedata_Hirschfelddata_ZimkusCameroondata.xlsx" contains all georeferenced <em>Bd </em>records collected by the authors of this study, data from Hirschfeld et al. 2016, and data for Cameroon from Zimkus et al. 2020. This file includes more metadata including amphibian species tested, and includes infection intensity data detected by qPCR for <em>Bd</em>-positive records. Using these datasets we document a pattern of <em>Bd </em>emergence beginning largely at the turn of the century (the year 2000). From 1852–1999, we found low <em>Bd</em> prevalence (3.2% overall) and limited geographic spread, but after 2000 we documented a sharp increase in prevalence (18.7% overall), wider geographic spread, and our genotyping revealed multiple <em>Bd </em>lineages with indications of hybridization. Our habitat suitability model showed that <em>Bd</em> risk to amphibians was highest in much of eastern, central, and western Africa. Our study documents a largely overlooked yet significant increase in a fungal pathogen that could pose a threat to amphibians across an entire continent. We emphasize the need to bridge historical and contemporary datasets to better describe and predict host-pathogen dynamics over larger temporal scales.
