An analysis of sensitivity of CLIMEX parameters in mapping species potential distribution and the broad-scale changes observed with minor variations in parameters values: an investigation using open-field Solanum lycopersicum and Neoleucinodes elegantalis as an example
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.
Dry stress decreases areas suitable for Neoleucinodes elegantalis (Lepidoptera: Crambidae) and affects its survival under climate predictions in South America
Projections of climate change show some regions of the world getting warmer, colder, dryer or wetter. Consequently, the effects of climate change on insect pests can alter the threat to agricultural systems. As a result of changed climate, areas can become more or less suitable for insect pests. Neoleucinodes elegantalis is one of the major pests of solanaceous crops in South America. Host plants for N. elegantalis are widely present in South America, however, N. elegantalis is absent from many regions in South America. Hence, future climate effects on suitability for development and spread of N. elegantalis in South America should be investigated. Due to these reasons, we developed a model of the climate for N. elegantalis using CLIMEX software for South America using A2 Special Report on Emissions Scenarios (SRES) for 2030, 2050, 2070 and 2100 and using two models, CSIROMk3.0 and MIROC-H. The results of both models indicate that areas in South America that are climatically suitable at the present time will become climatically unsuitable for N. elegantalis by 2100 as a consequence of progressive increase of dry stress. This was confirmed using developmental bioassays, where survival was lowest at low relative humidity levels. There are also altering areas that are currently unsuitable that become suitable in the future. These results are helpful in developing future strategies to take advantage of new opportunities in solanaceous crops in regions that may be unsuitable for N. elegantalis and provide important information for anticipated possible risks of infestation of N. elegantalis.
Climate model for seasonal variation in Bemisia tabaci using CLIMEX in tomato crops
The whitefly, Bemisia tabaci, is considered one of the most important pests for tomato Solanum lycopersicum. The population density of this pest varies throughout the year in response to seasonal variation. Studies of seasonality are important to understand the ecological dynamics and insect population in crops and help to identify which seasons have the best climatic conditions for the growth and development of this insect species. In this research, we used CLIMEX to estimate the seasonal abundance of a species in relation to climate over time and species geographical distribution. Therefore, this research is designed to infer the mechanisms affecting population processes, rather than simply provide an empirical description of field observations based on matching patterns of meteorological data. In this research, we identified monthly suitability for Bemisia tabaci, with the climate models, for 12 commercial tomato crop locations through CLIMEX (version 4.0). We observed that B. tabaci displays seasonality with increased abundance in tomato crops during March, April, May, June, October and November (first year) and during March, April, May, September and October (second year) in all monitored areas. During this period, our model demonstrated a strong agreement between B. tabaci density and CLIMEX weekly growth index (GIw), which indicates significant reliability of our model results. Our results may be useful to design sampling and control strategies, in periods and locations when there is high suitability for B. tabaci.
Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX
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.