Limiting scaring activities reduces economic costs associated with foraging barnacle geese: results from an individual-based model
Data files
May 22, 2023 version files 32.03 MB
Abstract
- With increasing numbers of large grazing birds on agricultural grassland, conflict with farmers is rising. One management approach to alleviate conflict allows foraging on dedicated agricultural land (accommodation areas) and nature reserves, combined with scaring on remaining agricultural land. Here, we examine the cost-effectiveness of these measures by studying the influence on barnacle goose distribution and associated economic damage.
- We present an individual/agent-based model of barnacle geese (Branta leucopsis) foraging on grasslands in Fryslân, the Netherlands. The model is parameterized using field observations and GPS-tracks and allows simulation of management scenarios, differing in scaring probability and accommodation area size, with different potential management costs.
- Our model shows that, while yield loss decreases with higher scaring probabilities, costs of damage appraisal increase because geese graze on more fields. With small accommodation areas, achieving high scaring probabilities takes more effort and could result in goose population decline. Total management costs are lowest without scaring activity.
- Synthesis and applications: Considering costs of active scaring and the need to maintain the barnacle goose population in a favourable conservation status, our model suggests that the most cost-effective scenario is to prevent disturbance of geese. A high scaring probability could be beneficial if applied in small areas, for example around sensitive crops or airfields. Scaring in large areas could result in costs outweighing benefits and a declining barnacle goose population.
Methods
This dataset was generated using an individual-based model. The model is also included in this Dryad data collection.
Usage notes
The dataset is in Excel format, in order to have a tab with metadata on top of the actual dataset. The C++ model was created in Visual Studio. Data can be analysed using R, as we have done as well.