Complex interactions between wildlife, landscapes and human activities, makes it often very difficult to predict the consequences of different management initiatives. In this project we develop models with the ability to account for links between nature and society. These models can be used as an effective tool when making informed decisions in nature management.

 

Objective

To develop an effective model tool to predict the impact of different hunting-related management initiatives on the harvest of hunted goose species.

Project description

In modern adaptive wildlife management the ability to make informed decisions is highly dependent on reliable impact assessments of the chosen management initiatives. In complex socio-economic systems such as hunting management, it is often necessary to test a wide range of possible management scenarios on regional scales, which in practice preclude a pure experimental approach. In this regard agent-based models are an important tool. These models can be developed to be extremely flexible and dynamic, include interactions between many species, actors and the surrounding environment, and is often spatially explicit so that results can easily be transferred to the real world. These strengths enables us to test different management scenarios in a realistic way, and predict the effect of potential initiatives on all species and actors (here geese and hunters) in the entire system.

In this project we demonstrate the potential for agent-based models as a tool for adaptive goose management, by predicting how different management initiatives (length of the hunting season, organisation of hunters, quotas etc.) influence the harvest of hunted goose species. The development of such a socio-economic model that incorporates the surrounding landscape, the wildlife and the hunters, can prove to be a very useful tool for stakeholders and decision-makers to assess the implications of different management initiatives on the complex interplay between animals, people and the environment. 

Publications and references

• Projekt forbedret gåsejagt - faglige konklusioner og anbefalinger