Simulating the efficacy of wolf-dog hybridization management with individual-based modeling

Area of Science:

• Conservation biology
• Ecology
• Population genetics

Background:

• Introgressive hybridization between wolves and dogs poses evolutionary risks.
• European legislation mandates mitigation of wolf-dog hybridization.
• Understanding hybridization dynamics is crucial for effective conservation management.

Purpose of the Study:

• To develop an individual-based model (IBM) simulating gray wolf life cycles and hybridization.
• To inform decision-making for managing wolf-dog hybridization.
• To project hybridization dynamics under various scenarios.

Main Methods:

• Developed an individual-based model (IBM) incorporating wolf sociality affecting hybridization.
• Simulated hybridization dynamics under different mate choice and immigration scenarios.
• Contrasted removal versus sterilization and release of admixed individuals.

Main Results:

• Lack of management led to complete admixture in several scenarios.
• Reactive management interventions effectively reduced wolf population admixture.
• Management effectiveness was contingent on mate choice, immigration, and anthropogenic mortality.

Conclusions:

• Conservation management interventions can successfully reduce wolf-dog hybridization.
• Model simulations highlight the critical influence of ecological and anthropogenic factors.
• The developed IBM serves as a valuable tool for conservation efforts facing hybridization threats.