Water hyacinth population dynamics.

Neochetina eichhorniae and N. bruchi have in some locations been very successful in controlling water hyacinth infestations. Understanding the conditions under which the weevils are not successful is a key area of research. We have used simple analytical tractable models to investigate this problem. We argue that biomass density and percentage coverage are the two most useful parameters to measure in a monitoring program. We modelled water hyacinth as a population of biomass. Under stable conditions, the logistic growth model accurately describes water hyacinth growth. Understanding how abiotoic conditions alter the parameters of the model is essential for accurate prediction of water hyacinth growth. There appear to be five main factors limiting infestations of water hyacinth: salinity, temperature, nutrients, disturbance and natural enemies. The models are modified to include the effect of weevil damage. Simple deterministic models are developed that incorporate developmental delays and population stage structure. For realistic parameter values, the models predict eradication of water hyacinth. We discuss how this prediction is altered in a dynamic environment. The factors that may limit the weevil population under stable conditions, and so prevent eradication, are explored. In order to test these ideas, information on areas where control has and has not been successful needs to be collated. THE current status of water hyacinth control has been well reviewed in these proceedings and elsewhere (Julien et al. 1996, 1999). Models have been used to investigate the effect of different management strategies (Ewel et al. 1975; Mitsch 1976; Lorber et al. 1984; Musil and Breen 1985b) drawing on the wealth of information from many studies conducted worldwide. However, there has been only one published model investigating the effect of biological control agents (Akbay et al. 1991). Models used to understand when an insect biological control agent will control a weed have produced insights into how control can be achieved (Lonsdale et al. 1995; Rees and Paynter 1997). Furthermore, the Lotka–Volterra model has been successfully used to simulate the growth of another aquatic weed (Salvinia molesta) before and during control by Cyrtobagous salvinae (Room 1990). This approach can be useful in drawing together existing knowledge, as well as to identify areas where research needs to be concentrated. The aim of the current research is to develop a predictive model for the control of water hyacinth addressing the following questions: • what causes variability in water hyacinth infestations? • how does the introduction of Neochetina eichhorniae affect the size of the infestation? • what can be done to improve control? In this paper we will outline some preliminary results of modelling work and the hypotheses generated from this work. Modelling Water Hyacinth Biomass When building a model, an appropriate state variable, which describes the state of the system at any moment in time, must be selected. With animal populations, the state variable chosen is usually the number of individuals. When modelling diseases, the number infected, * NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks, SL5 7PY, UK. Email: j.r. wilson@ic.ac. uk