Make your trappings count: the mathematics of pest insect monitoring

Abstract

Since the beginnings of agriculture the production of crops is characterized by an ongoing battle between farmers and pests [1]. Already during biblical times swarms of the desert locust, Schistocerca gregaria, were known as major pest that can devour a field of corn within an hour. Even today, harmful organisms have the potential to threaten food production worldwide. It is estimated that about 37% of all potential crops are destroyed by pests. Harmful insects alone destroy 13%, causing financial losses in the agricultural industry of millions of dollars each year [2-4]. These numbers emphasize the importance of pest insect monitoring as a crucial step of integrated pest management [1]. The main approach to gain information about infestation levels is based on trapping, which leads to the question of how to extrapolate the sparse population counts at singularly disposed traps to a spatial representation of the pest species distribution. In their review Petrovskii et al. provide a mathematical framework to tackle this problem [5]. Their analysis reveals that this seemingly inconspicuous problem gives rise to surprisingly deep mathematical challenges that touch several modern contemporary concepts of statistical physics and complex systems theory. The review does not aim for a collection of numerical recipes to support crop growers in the analysis of their trapping data. Instead the review identifies the relevant biological and physical processes that are involved in pest insect monitoring and it presents the mathematical techniques that are required to capture these processes.