Catch-effort model used as a management tool in exploited populations: Wild boar as a case study

Abstract

For sustainable management of exploited populations, it is required to have good knowledge on temporal trends in population density to adapt the harvest. In this regard, hunting statistics are often collected routinely by government agencies and associations. These data are used to assess demographic trends through the development of indices, which are in turn used to manage exploited populations in a sustainable way. However, these population indices depend on features of the hunting process (e.g. hunting effort, hunting conditions, probability of catch). In this study, we show how to use hunting logs to assess demographic trends in exploited populations while accounting for the components of the hunting process. In particular, we developed a catch-effort model to study how the hunting effort leads to mortality rate – hunting pressure – within a given habitat type and during a given period. We illustrated the usefulness of this approach using exploited wild boar (Sus scrofa) populations as a case study. We used a large hunting logs dataset to perform our study, with several hundreds of thousands hunting events for more than 10 years in two French departments in France, including information about the number of hunters, of wild boars culled and the date of the hunt. We showed that catchability is a key parameter to assess hunting pressure at a given time and place. This parameter varies both within the hunting season and between habitat types. Once this variation in catchability was accounted for, our catch-effort model allowed us to obtain estimates of relative densities of wild boar populations over the study period at the management unit scale. Thus, catch-effort models are powerful tools to assess population density and to understand the underlying hunting process. Our study offers straightforward and reproducible conceptual framework that can be applied routinely by wildlife managers on exploited populations and practitioners from hunting statistics logs.

Keywords

• Catchability
• Population density
• Hunting effort
• Hunting pressure
• Sus scrofa
• Wildlife management tool