Landscape Genetics Regression Analysis Methods and Critique

An opinion paper by William E. Peterman of The Ohio State University outlines appropriate and inappropriate uses of multiple regression models in landscape genetic analyses. The paper critiques the prevalent practice of using independent effective distance variables to explain genetic differences and advocates for univariate modeling approaches. It highlights statistical challenges like suppression and discusses ongoing advances in modeling genetic covariance with landscape variables.

Use Cases

• Critiquing the misuse of multiple regression with independent effective distance variables based on the methodological discussion.
• Designing univariate regression models for landscape resistance effects on gene flow based on the recommended framework.
• Understanding statistical suppression in genetic distance models based on the described analytical challenges.
• Reviewing covariance modeling advances for allele frequencies and landscape variables based on the mentioned statistical developments.

Strengths

• Authored by a researcher from The Ohio State University, providing academic credibility.
• Focuses on a specific methodological critique within the rapidly evolving field of landscape genetics.
• Published as an Open Access (green) paper, ensuring availability for review.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

William E. Peterman, The Ohio State University

Collection Method

Academic opinion paper and methodological critique.