Using simulation and modeling techniques, CLIMEX predicts the effect of climate change on species distribution. CLIMEX attempts to mimic the biological mechanisms that limit species' geographical distribution and determine their seasonal phenology and relative abundance.

Case Study: GM Crop

Future distribution patterns for species: Prediction of the naturalisation potential and weediness risk of transgenic cotton in Australia

CLIMEX 3.0.2

Climex

CLIMEX helps you understand the impact of climate change on species distribution and the potential risk from invasive species to an agricultural region.

CLIMEX 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 almost 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.

CLIMEX helps you understand the impact of climate on species distribution using the following features:

  • MS Windows Interface
    Users are able to display several maps, graphs and tables simultaneously as well as having the option of including one or two species in a run. This package includes the MetManager and MapManager modules that facilitate the manipulation of meteorological data and customisation of maps. CLIMEX offers graphical capabilities, drop-down menus, easy-to-use dialog boxes and a detailed online Help system.

  • Climate/Irrigation Scenarios
    CLIMEX allows users to consider the potential implications of climate change or of irrigation on the abundance and distribution of species. The 'Greenhouse' option simulates the impact of different temperature and rainfall conditions, and the 'Irrigation' option allows users to apply a given amount of water per week. With either option, different scenarios can be applied in summer and winter months.

  • Maps/Graphs/Tables
    CLIMEX contains tools for customising maps and for manipulating meteorological data. MapManager allows editing, selection and customisation of map displays, whilst MetManager allows extra meteorological data to be reformatted into the CLIMEX format and added to the database, and subsets of data to be created.

  • User's Guide & Help System and Tutorials
    CLIMEX comes with an extensive User's Guide that explains the theory behind CLIMEX, its algorithms and parameter setting procedures. CLIMEX also comes with an Online Help system and 50 pages of tutorials and answers that act as a 'Teachers Resource'.

  • CLIMEX Meteorological Database
    CLIMEX is shipped with a database of records from about 2400 meteorological stations worldwide. It needs monthly long term average maximum and minimum temperatures, rainfall, and relative humidity. The Metmanager allows the user to edit lists of stations into subsets, and to add new data for specific locations of interest. It also allows the use of grid-based data so long as it conforms to the CLIMEX format with space delimited data.

New Features

The following list includes the major differences between Version 2 and Version 3. In addition, a large number of minor improvements have been made to the program.

  • Two species can now be fitted with interactions between them (either competition or synergy) specified via parameters. 

  • Radiation is available as an additional component to the Growth Index.

  • Two non-specific components (definable by the user) can be added to the Growth Index. These are the Physical Substrate Index and the Biotic Substrate Index. The variables determining these indices can either be specified as a single value for all locations or they can be location specific and read from the MetManager.

  • Automatic fitting of the parameter values that determine the Stress indices is available via a genetic algorithm based fitting routine.

  • “Regional matching” (i.e, the use of a set of locations for the ‘Home’ location in the Match Climates function) is available.

  • The MetManager application has been extended to allow the importation of up to 5 user-defined location constants as well as up to 5 user-defined variables.


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