Climex from Hearne Scientific Software enables you to assess the risk of a pest establishing in a new location and the potential success or failure of a biological control agent with no knowledge of the species, except for knowing the current locations they do occur.
In forty countries around the world, Climex is used to model, predict and help control invasive insects.
Insect infestation destroys billions of dollars worth of commercial crops annually and monitoring and controlling invasive insects in a warming world is increasingly important.
The Climex software contains two quite different climate-matching tools. There is the Climex model (referred to as Climex or as the Climex model), and the Climex Match Climates function.
The latter is a tool for comparing the meteorological data of different places without reference to any particular species.
The Climex simulation model was first described by Sutherst and Maywald (1985) and a number of enhancements and further caveats and insights into using the model have been described in a series of publications listed at the end of the user manual, particularly (Sutherst et al 1995, Sutherst 1998).
The model is based on the assumption that if you know where a species lives you can infer what climatic conditions it can tolerate.
In other words, Climex attempts to mimic the mechanisms that limit species’ geographical distributions and determine their seasonal phenology and to a lesser extent their relative abundance.
Climex enables the user to estimate the potential geographical distribution and seasonal abundance of a species in relation to climate.
It does not try to match the patterns of climate and species’ distribution in the same way that a statistical fitting would seek to achieve.
Climex is applied to a species by selecting values for a set of parameters that describe its response to temperature, moisture and light.
The term population is used as the target entity, representing an average population of an animal or plant species or biotype for example.
An Annual Growth Index (GIA) describes the potential for growth of a population during the favourable season. Four stress indices (cold, hot, wet and dry), and in some cases their interactions, describe the extent to which the population is reduced during the unfavourable season.
The growth and stress indices are combined into an Ecoclimatic Index (EI), to give an overall measure of favourableness of the location or year for permanent occupation by the target species.
Two limiting conditions, ie the length of the growing season and obligate diapause, act as overall constraints to the EI value where relevant. Results are presented as tables, graphs, or maps.
A species’ climatic requirements are inferred from its known geographical distribution (either in its native range or in another region where it has been established for a long time), relative abundance and seasonal phenology.
Some laboratory data, such as developmental threshold temperatures, can be used to fit or fine tune Climex parameter values.
Initial estimates of parameter values are fine-tuned by comparing the indices with the known presence or absence, seasonal phenology and, preferably, relative abundance of the species in each location.
Once the parameter values have been estimated and where possible validated against independent data, Climex can be used to make predictions for other, independent locations.
Independent data means that there is no connection between the data and those data used for fitting the model; hence it is not appropriate to sub-sample a geographical distribution and then use the remaining data to test the model.