Global priorities for an effective information basis of biodiversity distributions
- Published
- Accepted
- Subject Areas
- Biodiversity, Biogeography, Bioinformatics, Conservation Biology, Ecology
- Keywords
- Species distributions, Aichi targets, biodiversity data mobilization, knowledge gaps, geographical bias, Wallacean shortfall
- Copyright
- © 2015 Meyer et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Global priorities for an effective information basis of biodiversity distributions. PeerJ PrePrints 3:e856v1 https://doi.org/10.7287/peerj.preprints.856v1
Abstract
Severe gaps and biases in digital accessible information (DAI) of species distributions hamper prospects of safeguarding biodiversity and ecosystem services and reliably addressing central questions in ecology and evolution. Accordingly, governments have agreed on improving and sharing biodiversity knowledge by 2020 (United Nations Convention on Biological Diversity’s Aichi target 19). To achieve this target, gaps in DAI must be identified, and actions prioritized to address their root causes. We take terrestrial vertebrates, an iconic and comparatively well-studied group, as a model and present the first globally comprehensive assessment of patterns and drivers of gaps in DAI, based on an integration of 157 million validated point records with 21,170 expert-based distribution maps. We demonstrate that outside a few well-sampled regions, DAI provides a very limited and spatially highly biased inventory of actual biodiversity. Coarser spatial grains result in more complete inventories, but provide insufficient detail for conservation and resource management. Surprisingly, large emerging economies are particularly under-represented in global DAI, even more so than species-rich, developing countries in the tropics. Multi-model inference reveals that completeness is mainly limited by distance to researchers, locally available research funding, and political participation in data-sharing networks, rather than transportation infrastructure, or size and funding of Western data contributors as often assumed. Our study provides an empirical baseline to advance strategies of enhancing the global information basis of biodiversity. In particular, our results highlight the need for targeted data integration from non-Western data holders and intensified cooperation to more effectively address societal biodiversity information needs.
Author Comment
This work is currently submitted to another journal.