Abstract
Bird harvest for recreational purposes or as a source for food is an important activity worldwide. Assessing or mitigating the impact of these additional sources of mortality on bird populations is therefore crucial issue. The sustainability of harvest levels is however rarely documented, because knowledge of their population dynamics remains rudimentary for many bird species. Some helpful approaches using limited demographic data can be used to provide initial assessment of the sustainable use of harvested bird populations, and help adjusting harvest levels accordingly. The Demographic Invariant Method (DIM) is used to detect overharvesting. In complement, the Potential Take Level (PTL) approach may allow setting a level of take with regard to management objectives and/or to assess whether current harvest levels meet these objectives. Here, we present the R package popharvest that implements these two approaches in a simple and straightforward way. The package provides users with a set of flexible functions whose arguments can be adapted to existing knowledge about population dynamics. Also, popharvest enables users to test scenarios or propagate uncertainty in demographic parameters to the assessment of sustainability through easily programming Monte Carlo simulations. The simplicity of the package makes it a useful toolbox for wildlife managers or policymakers. This paper provides them with backgrounds about the DIM and PTL approaches and illustrates the use of popharvest's functionalities in this context.