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Published on: March 13, 2011

What spatial data do we need to develop global mammal conservation strategies?

Luigi Boitani1, Luigi Maiorano, Daniele Baisero

  • 1Department of Biology and Biotechnologies, Global Mammal Assessment programme, Sapienza Università di Roma, Viale dell'Università 32, 00185 Rome, Italy. luigi.boitani@uniroma1.it

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|August 17, 2011
PubMed
Summary
This summary is machine-generated.

Spatial data on species distributions, including point locations and distribution maps, require specific attributes for effective conservation planning. Current global mammal databases often lack these essential data qualities, limiting their conservation utility.

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Area of Science:

  • Ecology
  • Conservation Biology
  • Geographic Information Systems (GIS)

Background:

  • Species distribution data exist as point locations or distribution maps (polygons, grids).
  • Point location data often exhibit temporal and spatial biases, limiting direct use in spatial analyses.
  • Modeling approaches transform point data into distribution maps.

Purpose of the Study:

  • To discuss essential attributes for species distribution data (point locations and maps) in conservation planning.
  • To recommend criteria for assessing point location datasets before use in distribution modeling.
  • To identify necessary attributes for distribution maps used in conservation analyses.

Main Methods:

  • Review of attributes required for point location data (sample size, age, coverage, accuracy, relevance, presence representation).
  • Review of additional attributes for distribution maps (error minimization, source credibility, public screening).
  • Evaluation of global mammal databases against these criteria.

Main Results:

  • Point location data require rigorous assessment for conservation applications.
  • Distribution maps need specific qualities like minimized errors and credible sources.
  • Global mammal databases show significant variability in meeting these data quality standards.

Conclusions:

  • The heterogeneity and limitations of current spatial data significantly constrain their effectiveness for global and sub-global conservation planning.
  • Improving data quality and standardization is crucial for advancing conservation efforts.
  • Further research and database development are needed to enhance the utility of species distribution data.