A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed “sensitive”. Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.

Background: 'Neoleucinodes elegantalis' is one of the major insect pests of 'Solanum lycopersicum'. Currently, 'N. elegantalis' is present only in America and the Caribbean, and is a threat in the world's largest 'S. lycopersicum'-producing countries. In terms of potential impact on agriculture, the impact of climate change on insect invasions must be a concern. At present, no research exists regarding the effects of climatic change on the risk level of 'N. elegantalis'. The purpose of this study was to develop a model for 'S. lycopersicum' and 'N. elegantalis', utilizing CLIMEX to determine risk levels of 'N. elegantalis' in open-field 'S. lycopersicum' cultivation in the present and under projected climate change, using the global climate model CSIRO-Mk3.0. Results: Large areas are projected to be suitable for 'N. elegantalis' and optimal for open-field 'S. lycopersicum' cultivation at the present time. However, in the future these areas will become unsuitable for both species. Conversely, other regions in the future may become optimal for open-field 'S. lycopersicum' cultivation, with a varying risk level for 'N. elegantalis'. Conclusion: The risk level results presented here provide a useful tool to design strategies to prevent the introduction and establishment of 'N. elegantalis' in open-field 'S. lycopersicum' cultivation.

Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for 'Neoleucinodes elegantalis' (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of 'N. elegantalis' for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for 'N. elegantalis' and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for 'N. elegantalis'. In this study, we ensure that the simulation results are valid through our verification using field data.