Comparison Of Water Hyacinth And Cornops Aquaticum

Model of water hyacinth and Cornops aquaticum

Models provide a pivotal role in the prediction and simulation of complex systems, increasing the understanding of the system in question (Freckleton and Stephen 2008). As a result, a variety of models exist and can be tailored to a particular system (Ogden et al.2005). Mathematical modelling of population dynamics have been particularly useful in the ecological understanding of invasion and control protocols (Wilson et al. 2005; Kriticos et al. 2009). Niche models are most commonly utilized as they allow matching of meteorological values between the area of invasion and the native range (Zalucki and Klinken 2006). These ‘climatic envelopes’ provide information of the theoretical or potential physiological

These include the estimation of gas production of methane as well as in invasive plant control management (Lorber et al., 1984; Akbay et al., 1991; Wilson et al., 2001). Although, each utilises an estimation of the biomass of water hyacinth, many omit factors affecting population. As water hyacinth is limited in its growth due to physical area of water bodies, logistic growth models are particularly suited to this (Wilson et al. 2005). Lorber et al. (1984) used multiple parameters such as solar radiation and nutrients, to closely replicate field data. Wilson et al. (2005) used a logistic model of water hyacinth largely approximated on water temperature and nutrient concentration parameter calculated from the literature. These models are largely not ideal for small-scale water hyacinth populations experiencing numerous confounding factors. Hauptfleisch (2016) built upon these and incorporated herbivory of the Neochetina weevils. The impact of herbivory has been modelled using the Lotka-Volterra equations to describe the relationship between plant and herbivore (Room 1990; Wilson et al. 2001). These models can be reformed to investigate the biomass removal potential of Cornops

Models can be useful to demonstrate growth in the weed population throughout the season due to external factors such as temperature and interactions with biological control agents at various sites (Sims et al. 2006). Models provide insight into mechanisms which may underpin biological control success or failure (Kriticos 2003; Sheppard et al. 2003; Holst et al. 2007). The biological control of water hyacinth highlights a system whose mechanisms are not fully understood and whose control mechanisms themselves are intricately linked. The understanding of a key biological control agent that is having problems establishing may prove be extremely important to the control of the invasive weed water hyacinth.

Water hyacinth growth has been shown to be more accurately described by the logistic growth equation than other growth models (Wilson et al. 2001; Wilson et al. 2005). The density (kg of biomass/ m2) can be represented by the equation: dV/dt=r_v xV(1-V/K) (Equation 3) where rv is the growth rate per day and K is the carrying capacity.

Fresh weight of water hyacinth will be utilized for feeding programs and for the modelling of water hyacinth populations in order to compare to field measures and previous work (Byrne et al. 2010). Dry weights of the plants will be taken after feeding experiments and be