WP4: Hunting, sustainable harvesting and consequences for biodiversity

Relationships between hunting management and conservation of biodiversity

Miguel Delibes-Mateos & Beatriz Arroyo

Key message

Research on the impact of hunting on biodiversity has shown that hunting (and its associated management) can be a strong driver in conserving biodiversity, because many of the objectives in hunting (maintaining healthy populations, preserving natural habitats, reducing limiting factors for game) are shared with those of wildlife management and conservation at large.

However, sometimes hunting has negative consequences on biodiversity, usually because of certain management activities performed in unsustainable ways, and these are maintained because of economic or cultural reasons.

Additionally, hunting may benefit certain species, but not others, and the overall benefit of hunting for biodiversity and conservation will depend on the relative value that is attached to different animal guilds or species in different contexts.

Overall, our research indicates that hunting estates that have benefits for biodiversity should be identified and favoured over those that are not.

Social-ecological modelling for improved sustainability of hunting

Nils Bunnefeld & E.J. Milner-Gulland

Key message

Making conservation decisions to benefit species, habitats and people is challenging due to the complexity and the limited knowledge that characterises interlinked social-ecological systems.

We developed a new approach for modelling the sustainability of interventions in social-ecological systems that extends an existing framework from fisheries science and makes it more appropriate for situations with multiple interventions, multiple users and compliance challenges. This makes the framework more appropriate for many small-scale terrestrial systems in developing countries.

This framework is easily integrated into adaptive management and very flexible.
Our approach can use qualitative and quantitative information by combining different data types (e.g. social data, economic data, ecological monitoring data, harvest data) and using the full extent of time series data effectively. We show the quality and quantity of monitoring data that is needed to make informed decisions and the robustness of the decision-making process to different types and degrees of uncertainty.

Incorporating human decision making in models of the dynamics of harvested systems allows us to consider transparently the tradeoffs of different conservation actions for different stakeholders and based on different performance metrics.

More transparency has been shown to contribute to conflict resolution and builds trust between stakeholders who may have very different objectives.