The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Integrodifference model for blowfly invasion

We propose a stage-structured integrodifference model for blowflies' growth and dispersion taking into account the density dependence of fertility and survival rates and the non-overlap of generations. We assume a discrete-time, stage-structured, model. The spatial dynamics is introduced by means of a redistribution kernel. We treat one and two dimensional cases, the latter on the semi-plane, with a reflexive boundary. We analytically show that the upper bound for the invasion front speed is the same as in the one-dimensional case. Using laboratory data for fertility and survival parameters and dispersal data of a single generation from a capture-recapture experiment in South Africa, we obtain an estimate for the velocity of invasion of blowflies of the species Chrysomya albiceps. This model predicts a speed of invasion which was compared to actual observational data for the invasion of the focal species in the Neotropics. Good agreement was found between model and observations.

The anatomy, physiology, morphology and development of the blow-fly (Calliphora erythrocephala.) : A study in the comparative anatomy and morphology of insects.

An expansion of the author's previous memoir on the subject, that appeared in 1870.

Chrysomya chloropyga (Wiedemann, 1818) and C-putoria (Wiedemann, 1830) (Diptera : Calliphoridae) are two different species

The blowflies Chrysomya chloropyga (Wiedemann,1818) and Chrysomya putoria (Wiedemann, 1830) (Diptera: Calliphoridae) of veterinary and medical importance are taxonomically revised and formally reestablished as two different species. Characters in the adult morphology by which they can be distinguished, including characters in the genitalia, are described. The form with a darkened anterior margin of the wing, 'f. tacniata Bigot' sensu Zumpt 1956, is treated as a variant of C. putoria. In order to preserve stability of nomenclature, lectotypes are designated for both nominal species, fixing their identity in accordance with current usage. Somomyia cuprinitens Rondani, 1873, and Somomyia taeniata Bigot, 1877, (= C. chloropyga 'f. taeniata Bigot' of Zumpt) are considered new synonyms of C. putoria.