Modelling population dynamics of banana plant-parasitic nematodes : A contribution to the design of sustainable cropping systems

This article describes the biological background, the model-building methodology and some applications of SIMBA-NEM, a new model to simulate the population dynamics of two major plant-parasitic nematode species of banana, Radopholus similis and Pratylenchus coffeae. For each species, each generation is represented by one cohort. Cohorts of the same species form a chain representing the developmental stages of nematodes. A logistic function describes population growth in relation with: (i) an environmental carrying capacity (K) that depends on available banana root biomass, (ii) an intrinsic growth rate (c) and (iii) competition between nematode species. Soil water content and the quantity of nematicides used are considered to be the main variables influencing the intrinsic population growth rate of each species. SIMBA-NEM was calibrated and validated using datasets from banana cropping systems in Guadeloupe (French West Indies). By analysing the sensitivity of the model to the main parameters and performing simulations of validation for various cropping systems (banana monoculture with or without nematicide applications use and a banana/sugarcane rotation) we were able to test the ability of the model to predict nematode population dynamics under a range of conditions. SIMBA-NEM is able to predict long-term nematode population size, while taking interspecific competition into account. It also helped to define knowledge gaps in nematology and modelling. SIMBA-NEM was used to optimise the effect of nematicide applications. SIMBA-NEM can already be a very helpful tool for designing sustainable and more environment-friendly banana cropping systems. In the SIMBA global crop-modelling environment, SIMBA-NEM is a key sub-model which pro-vides essential information concerning the sustainability of the simulated system and thus permits planning environmentally friendly cropping systems. © 2006 Elsevier B.V. All rights reserved