A comparative analysis of parallel processing 1 and super - individual methods for improving

6 Individual-based modelling approaches are being used to simulate larger complex 7 spatial systems in ecology and in other fields of research. Several novel model de8 velopment issues now face researchers: in particular how to simulate large num9 bers of individuals with high levels of complexity, given finite computing resources. 10 A case study of a spatially-explicit simulation of aphid population dynamics was 11 used to assess two strategies for coping with a large number of individuals: the use 12 of ‘super-individuals’ and parallel computing. Parallelisation of the model main13 tained the model structure and thus the simulation results were comparable to the 14 original model. However, the super-individual implementation of the model caused 15 significant changes to the model dynamics, both spatially and temporally. When 16 super-individuals represented more than around 10 individuals it became evident 17 that aggregate statistics generated from a super-individual model can hide more 18 detailed deviations from an individual-level model. Improvements in memory use 19 and model speed were perceived with both approaches. For the parallel approach, 20 significant speed-up was only achieved when more than five processors were used 21 and memory availability was only increased once five or more processors were used. 22 The super-individual approach has potential to improve model speed and memory 23 use dramatically, however this paper cautions the use of this approach for a density24 dependent spatially-explicit model, unless individual variability is better taken into 25 account. 26