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Big data-big problems? How to circumvent problems in biodiversity mapping and ensure meaningful results
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  • Alice Hughes,
  • James Dorey,
  • Silas Bossert,
  • Huijie Qiao,
  • Michael Orr
Alice Hughes
Xishuangbanna Tropical Botanical Garden

Corresponding Author:[email protected]

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James Dorey
Flinders University of South Australia
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Silas Bossert
Washington State University
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Huijie Qiao
Institute of Zoology Chinese Academy of Sciences
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Michael Orr
Institute of Zoology Chinese Academy of Sciences
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Our knowledge of biodiversity hinges on sufficient data, reliable methods, and realistic models. Without an accurate assessment of species distributions, we cannot effectively target and stem biodiversity loss. Species range maps are the foundation of such efforts, but countless studies have failed to account for the most basic assumptions of reliable species mapping practices, undermining the credibility of their results and potentially misleading and hindering conservation and management efforts. Here, we use examples from the recent literature and broader conservation community to highlight the substantial shortfalls in current practices and their consequences for both analyses and conservation management. We detail how different decisions on data filtering impact the outcomes of analysis and provide practical recommendations and steps for more reliable analysis, whilst understanding the limits of what available data will reliably allow and what methods are most appropriate. Whilst “perfect” analyses are not possible for many taxa given limited data, and biases, ensuring we use data within reasonable limits and understanding inherent assumptions is crucial to ensure appropriate use. By embracing and enacting such best practices, we can ensure both the accuracy and improved comparability of biodiversity analyses going forward, ultimately enhancing our ability to use data to facilitate our protection of the natural world.
18 Sep 2023Submitted to Ecography
19 Sep 2023Assigned to Editor
19 Sep 2023Submission Checks Completed
19 Sep 2023Review(s) Completed, Editorial Evaluation Pending
21 Sep 2023Reviewer(s) Assigned