Abstract
Reliable hunting bag statistics are a prerequisite for sustainable harvest management based on quantitative modeling. Estimating the total hunting bag for a given game species is faced with a multiplicity of error sources. Of particular concern is the nonresponse error. We consider that the major cause of nonresponse bias is when the reluctance to respond is related to a null harvest, which leads to a potentially important overestimation. For tackling the nonresponse bias issue, we advocate the repeated subsampling of nonrespondents, with a final phase of personal interview by phone, intended to be without nonresponse. When a 100% response rate is actually reached at the last phase, both total and sampling variance can be estimated without bias, whatever the response rates at the previous phases. The actual case of imperfect response at the last phase is studied using Monte Carlo simulations. For imperfect response at the last phase, we show that the estimators we advocate are biased downwards but that these bias remain very moderate if the response rate at the last phase is high enough, depending on the circumstances. Furthermore, we illustrate that increasing the number of phases improves the nonresponse bias attenuation. In case of a hunting bag collecting scheme prone to a high nonresponse rate, for obtaining a very satisfying nonresponse bias attenuation we advocate relying on the multiphase sampling strategy with two- or three-phases, and a response rate in the last phase of at least 90%.
Highlights
Management of harvested wildlife populations increasingly moves towards a science-based approach where the sustainability of the populations and the hunting activity itself are ensured by adequate data collection (e.g. [4] for waterfowl in North America)
Attenuating the nonresponse bias in hunting bag surveys estimates based on counts of animals, or estimates of the total harvest
To given game species, spatial domain and time period, let yk denote the bag for hunter k 2 U, where U is the population of active huntersP
Summary
Management of harvested wildlife populations increasingly moves towards a science-based approach (but see [1,2,3]) where the sustainability of the populations and the hunting activity itself are ensured by adequate data collection (e.g. [4] for waterfowl in North America). Adaptive harvest management (see [5]) is increasingly used in this context, and relies on continuous monitoring of the populations and hunting bags as minimum required information [6]. Such management is often based on estimates of the population parameters, such as population size. We consider situations in which the parameter of interest is the total hunting bag t 1⁄4 k2Uyk 1⁄4 N y, with N the size of U. Knowing the total hunting bag at several geographical scales is needed for wildlife management, according to species biology (migratory or sedentary) and population status (threatened, of no concern, invasive, overabundant).
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