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Related Experiment Video

Updated: Mar 13, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Expert-based versus habitat-suitability models to develop resistance surfaces in landscape genetics.

Pietro Milanesi1,2, R Holderegger3,4, R Caniglia5

  • 1Laboratorio di Genetica, Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), Via Ca` Fornacetta 9, 40064, Ozzano dell'Emilia, Bologna, Italy. pietro.milanesi@unipv.it.

Oecologia
|October 13, 2016
PubMed
Summary

Habitat suitability models improve landscape genetics by creating more accurate resistance surfaces than expert knowledge. This enhances understanding of gene flow and functional connectivity in wild populations.

Keywords:
Canis lupusExpert knowledgeLeast-cost path distancesLinear mixed effect modelsSpecies distribution models

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Area of Science:

  • Ecology
  • Genetics
  • Conservation Biology

Background:

  • Landscape genetics analyzes how landscape features influence gene flow among wild populations.
  • Least-cost path (LCP) distances, derived from resistance surfaces, often better explain genetic distances than Euclidean distances.
  • Resistance surfaces traditionally rely on expert knowledge due to limited movement data, introducing potential bias.

Purpose of the Study:

  • To compare the effectiveness of least-cost path (LCP) distances derived from habitat suitability models versus expert knowledge in landscape genetics.
  • To evaluate how different resistance surface methods explain genetic distances and functional connectivity.

Main Methods:

  • Generated LCP distances using both expert-based and habitat suitability model-derived resistance surfaces.
  • Related LCP distances to genetic distances using linear mixed-effect models.
  • Utilized an empirical dataset of Italian wolves (Canis lupus).

Main Results:

  • Both LCP methods significantly explained genetic distances (P ≤ 0.0001).
  • LCP distances derived from habitat suitability models consistently showed higher explanatory power than those from expert knowledge.
  • All LCP distances outperformed simple Euclidean distances in explaining genetic patterns.

Conclusions:

  • Habitat suitability models offer a more objective and effective approach for estimating resistance surfaces in landscape genetics.
  • Using habitat suitability-based resistance surfaces can improve the accuracy of assessing gene flow and functional connectivity.
  • Researchers are encouraged to adopt habitat suitability models for more robust landscape genetics analyses.