Comparison of the predicted impact of a screwworm fly outbreak in Australia using a growth index model and a life‐cycle model

Abstract

The spatial population dynamics of an Old World screwworm fly, Chrysomya bezziana Villeneuve (OWS), outbreak in Australia have been modelled in two ways. The first model uses weekly growth indices derived from climatic data to predict the adult female population. The second is a detailed cohort life-cycle model. Due to technical and time constraints, the growth index model is preferred as the biological component of a much larger bioeconomic model because of its smaller program size and faster execution. In deciding whether adoption of the growth index model would be at the expense of scientific accuracy, the life-cycle model was developed as a yardstick. We showed that the growth index model was a practical and adequate substitution for the OWS life-cycle model and a novel spatial/temporal modelling approach with generic qualities. We elaborate on the previously reported growth index model, describe the life-cycle model and compare the results of both models. In the event of an OWS incursion in northern or eastern Australia, given average climatic conditions, both models predict that most of the suitable range (some 2.3M km2) will be colonized within 4-5 years if an eradication campaign is not attempted. Much of its permanent range would be in tropical and subtropical extensive grazing regions. Where computer or funding resources are restrictive, models incorporating growth indices may prove adequate for spatial population studies of some species.

Applying GIS and high performance agent-based simulation for managing an Old World Screwworm fly invasion of Australia

“…It is designed to address the short-comings of the former model by providing an updated, individual insect-based implementation of the lifecycle population model proposed initially by Atzeni et al (1994) and a fully stochastic dispersal model, based on the work by Mayer et al (1993Mayer et al ( , 1995Mayer et al ( , 1994, which was originally conducted to develop the deterministic dispersal approximations for the CLIMEX-based model . The approach adopted for our agent-based implementation uses a much higher resolution of 1 km × 1 km (as compared to 20 km × 20 km in the former model) grid square arrangement with 2880 rows and 4060 columns.…”

“…Following the OWS fly lifecycle proposed by Atzeni et al (1994), within each of these cells, the OWS fly population is broken down into thirty-six cohorts that cover the Egg, Larval, Pupal and Adult stages of the fly's lifecycle. Conceptually, the model is agentbased with agent-level calculations determining daily survivability, development and insect dispersal.…”

“…In the lifecycle model proposed by Atzeni et al (1994), the first operation in the daily cycle is the calculation and application of the survivorship rates for each insect. This operation models the daily deaths of the insects at each stage in the lifecycle from a range of natural causes that are dependent on that stage.…”

“…Through applying the ABM approach, a new national-scale agent-based model that addresses key short-comings of the former model is proposed in this research. The model developed makes use of the lifecycle based approach outlined by Atzeni et al (1994), combined with stochastic sampling at the individual insect level to produce a highly detailed simulation. In order to meet the challenges surrounding the development of such a simulation system with increased levels of detail and immense processing overhead, this paper outlines a high performance simulation platform that uses NVidia's CUDA GPU technology and its data-parallel programming paradigm.…”

Land Surface Temperature

“…A growth index model and a life-cycle model were coupled to predict the risk of OWS spread in northern Australia (Atzeni et al 1994). However, this approach simply quantified the spread of OWS in an area already identified at risk using CLIMEX, i.e.…”