Whale Shark SDM Framework with Targeted Pseudo-Absence Selection

A 2026 methodological study by Soeon Ahn presents a species distribution modeling framework for data-deficient marine environments. It uses whale shark occurrences in Korean waters (n=33) as a case study to develop a Long-term Inverse-Weighted pseudo-absence generation method. The framework is designed to support proactive marine conservation under data scarcity.

Use Cases

• Evaluating species distribution modeling algorithms based on the described LIW, uniform random, and seasonal inverse-weighted methods.
• Identifying seasonal range edges for marine megafauna based on the framework's ability to predict habitat.
• Developing proactive conservation strategies in data-limited frontier zones based on the integrated SDM approach.
• Comparing performance of boosted regression trees, random forest, XGBoost, and MaxEnt models for marine species.

Strengths

• The methodology is explicitly described with a concrete case study of whale sharks (Rhincodon typus) in Korean waters.
• The framework integrates spatial expansion of the modeling domain with a novel pseudo-absence generation method.
• Performance is evaluated across four distinct modeling algorithms.

Limitations

• The dataset is a 1.6 MB DOCX document, likely containing a research paper or supplementary material rather than structured data.
• Column-level documentation and sample data are unavailable, limiting direct analysis of underlying data.
• The row count and specific data format are unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

The description suggests the data likely originates from a research study modeling whale shark occurrences.

Freshness

Last updated 2026-05-06 12:13:41.

Geography

Korean waters