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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
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Assumption-versus data-based approaches to summarizing species' ranges.

A Townsend Peterson1, Adolfo G Navarro-Sigüenza2, Alejandro Gordillo2

  • 1Biodiversity Institute, University of Kansas, Lawrence, KS, 66045, U.S.A.

Conservation Biology : the Journal of the Society for Conservation Biology
|August 5, 2016
PubMed
Summary
This summary is machine-generated.

Simple species distribution maps are often inaccurate for conservation planning. Data-driven ecological niche models offer a more reliable, validated approach for mapping species ranges at fine resolutions.

Keywords:
animalsbiogeographybirdsconservation planningmapas de extensión de presenciapatrones de distribuciónpredictive modelingpruebas de modelosreserve designresolución espacial

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Area of Science:

  • Ecology
  • Conservation Biology
  • Geographic Information Systems

Background:

  • Species' geographic distributions are crucial for conservation decision-making.
  • Current methods often downscale coarse-resolution extent-of-occurrence maps for fine-scale conservation planning.

Purpose of the Study:

  • To evaluate the accuracy of extent-of-occurrence maps as range summaries.
  • To assess the utility of refining these maps into fine-resolution distributional hypotheses.
  • To compare traditional mapping methods with data-driven approaches like ecological niche modeling.

Main Methods:

  • Analysis of extent-of-occurrence maps for simplicity and omission/inclusion errors.
  • Examination of refinement steps involving habitat and elevational assumptions.
  • Contrast with data-driven ecological niche modeling (ENM) and species distribution modeling (SDM) integrating occurrence data and remote sensing.

Main Results:

  • Extent-of-occurrence maps are often overly simplistic, omit known populations, and include areas without populations.
  • Refinement processes introduce errors due to unsubstantiated typological assumptions.
  • Lack of model evaluation in traditional methods leads to unnoticed inaccuracies.
  • ENM/SDM provide data-driven, quantitatively validated alternatives.

Conclusions:

  • Traditional extent-of-occurrence map refinement is not advisable for fine-resolution conservation due to assumptions and lack of validation.
  • Ecological niche modeling and species distribution modeling offer superior, data-driven, and validated methods for summarizing species distributions.
  • Data-driven approaches are recommended for accurate, on-the-ground conservation applications.