Community-based approach to detect and predict conflicts with large carnivores in human-dominated landscape

Area of Science:

• Wildlife ecology
• Conservation biology
• Human-wildlife interactions

Background:

• Effective conservation requires understanding human-wildlife interactions in shared landscapes.
• Community-based data is vital for adaptive management and fostering coexistence.
• Carnivore management in human-dominated areas presents significant challenges.

Purpose of the Study:

• To analyze community-reported data on grey wolves and brown bears in the Carpathian region of Poland.
• To identify key drivers and mechanisms influencing human-carnivore interactions.
• To inform conservation strategies for promoting coexistence.

Main Methods:

• Analysis of 611 community-submitted reports of grey wolves and brown bears.
• Spatial analysis of carnivore presence in built-up areas.
• Statistical modeling to determine factors influencing carnivore reporting probability.

Main Results:

• Bears and wolves were reported in 6% and 12% of built-up areas, respectively.
• Anthropogenic food resources were exploited in 53% of all reports.
• Previous observations and successful food acquisition increased the probability of carnivore reports, indicating habituation and food conditioning.

Conclusions:

• Habituation and food conditioning are critical factors in carnivore management within human-dominated landscapes.
• Engaging local communities in monitoring facilitates early conflict detection.
• Community-based monitoring provides a foundation for effective human-carnivore coexistence strategies.