Abstract
Geographic profiling (GP) was originally developed as a statistical tool to help police forces prioritize lists of suspects in investigations of serial crimes. GP uses the location of related crime sites to make inferences about where the offender is most likely to live, and has been extremely successful in criminology. Here, we show how GP is applicable to experimental studies of animal foraging, using the bumble-bee Bombus terrestris. GP techniques enable us to simplify complex patterns of spatial data down to a small number of parameters (2–3) for rigorous hypothesis testing. Combining computer model simulations and experimental observation of foraging bumble-bees, we demonstrate that GP can be used to discriminate between foraging patterns resulting from (i) different hypothetical foraging algorithms and (ii) different food item (flower) densities. We also demonstrate that combining experimental and simulated data can be used to elucidate animal foraging strategies: specifically that the foraging patterns of real bumble-bees can be reliably discriminated from three out of nine hypothetical foraging algorithms. We suggest that experimental systems, like foraging bees, could be used to test and refine GP model predictions, and that GP offers a useful technique to analyse spatial animal behaviour data in both the laboratory and field.
Highlights
Geographic profiling (GP) is a statistical technique originally designed to help police forces to prioritize large lists of suspects typically generated in cases involving serial crime, for instance, murder and rape (Rossmo 2000)
We fit model variables to known anchor points for both experimental and simulated foraging data
A test hit score of 25 indicates that the model finds the arena entrance in half the time, and a test hit score of 0.1 indicates that the model finds the entrance 500 times faster than a random search. This confirms that GP can be used to speed up the process of locating the arena entrance from the observed patterns of flower visitation by foraging bees
Summary
Geographic profiling (GP) is a statistical technique originally designed to help police forces to prioritize large lists of suspects typically generated in cases involving serial crime, for instance, murder and rape (Rossmo 2000). We fit model variables to known anchor points (in criminology, usually the criminal’s residence or work place, to which they return between crimes, but in animal foraging the location of a nest, roost or den) for both experimental and simulated foraging data. We use these variables as the basis for hypothesis tests to compare patterns of foraging at different densities of food items (flowers), and to compare different foraging algorithms. (4) Can GP be used to compare the actual foraging behaviour of B. terrestris with that expected under different hypothetical models of foraging?
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