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Evaluating Three Modelling Frameworks for Assessing Changes in Fin Whale Distribution in the Mediterranean Sea.

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This study compared species distribution models (SDMs) for fin whale (Balaenoptera physalus) habitat. Results show bathymetry and sea surface temperature are key factors, informing conservation in the NW Mediterranean Sea.

Keywords:
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Area of Science:

  • Marine ecology
  • Conservation biology
  • Quantitative ecology

Background:

  • Species distribution models (SDMs) are crucial for understanding highly migratory species' habitats and informing conservation strategies.
  • A debate exists regarding whether to model habitat suitability (presence/absence) or density (# individuals), especially for marine mammals.
  • Zero-inflated data present a challenge in ecological modeling, necessitating methods like Hurdle Models.

Purpose of the Study:

  • To assess and compare the performance of Generalized Additive Models (GAMs) and Boosted Regression Trees (BRTs) for modeling fin whale (Balaenoptera physalus) density and habitat suitability.
  • To evaluate Hurdle Models in addressing zero-inflated data for fin whale distribution analysis.
  • To identify key environmental covariates influencing fin whale distribution in the NW Mediterranean Sea.

Main Methods:

  • Collected fin whale data from 2008-2022 along fixed transects in the NW Mediterranean Sea during summer.
  • Employed traditional line transect methodology to calculate the Effective Area Monitored.
  • Utilized GAMs, BRTs, and Hurdle Models, incorporating static (bathymetry, slope) and dynamic (SST, MLD, Chl, EKE, FSLE) covariates.

Main Results:

  • All models demonstrated good performance in distinguishing presence and absence of fin whales.
  • While density and presence patterns were similar, their environmental dependencies varied by model type.
  • Bathymetry emerged as the most significant covariate across all models, followed by sea surface temperature (SST) and pre-sighting chlorophyll concentration.

Conclusions:

  • The choice of modeling technique can influence the understanding of environmental drivers for fin whale distribution.
  • SDMs are valuable tools for marine mammal conservation, providing essential data for spatial management.
  • This research quantifies fin whale-environment relationships in a data-limited region, supporting evidence-based conservation efforts.