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Systematic data in biodiversity studies: use it or lose it.

V A Funk1, K S Richardson

  • 1U.S. National Herbarium, Smithsonian Institution, Washington, D.C. 20560-0166, USA. funkv@nmnh.si.edu

Systematic Biology
|May 25, 2002
PubMed
Summary

Biodiversity studies can use collections data to map species distributions. New modeling methods combine collections and abiotic data to predict distributions and identify high-priority conservation sites.

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Area of Science:

  • Biodiversity research
  • Conservation science
  • Biogeography

Background:

  • Collections data are crucial for understanding species distributions but are prone to collection bias.
  • Existing methods for biodiversity studies sometimes avoid collections data due to bias concerns.

Purpose of the Study:

  • To evaluate new methods for modeling species distributions using collections data combined with abiotic factors.
  • To identify high-priority biodiversity sites based on irreplaceability.

Main Methods:

  • Modeling species distributions using 25,111 records (5,123 species) from Guyana, incorporating abiotic data.
  • Utilizing a subset of 320 species for some modeling approaches.
  • Assessing modeled distributions and selecting sites using the irreplaceability metric.

Main Results:

  • The study examined the effectiveness of new modeling techniques for predicting species distributions.
  • High-priority conservation areas were identified based on species uniqueness and predicted distributions.
  • Challenges in data accessibility and systematist engagement were highlighted.

Conclusions:

  • Modeling approaches integrating collections and abiotic data offer a robust way to assess biodiversity and guide conservation efforts.
  • Addressing data formatting and engaging systematists are key to advancing biodiversity research.
  • Irreplaceability is a valuable concept for prioritizing conservation sites.

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