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

DYMEX is a modular modelling package that allows the user to develop and run deterministic population models of biological organisms rapidly. These population models are structured around species' lifecycles, which in turn consist of the growth stages that individuals pass through during their life.

Climex and Dymex Glossary

List of Climex and Dymex terms with accompanying definitions.

Climex and Dymex Suite 4.0


Climex Distribution Map

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.

The models produced with DYMEX help to summarise your understanding of an organism’s population dynamics, identify gaps in knowledge, and rapidly evaluate management options.


DYMEX enables you to interactively build and run models of fluctuating populations of organisms in changing environments. Ecologists can create a wide range of process-based population models without the need to know a programming language. Models are structured around lifecycles, which in turn consist of the stages that individuals pass through during their life. A DYMEX lifecycle describes cohorts of individuals and the processes that affect the size, age and number of individuals in the cohort.

DYMEX does not model the fate of individual organisms. Individuals are grouped into assemblages termed Cohorts, where each cohort consists of a number of individuals that belong to the same lifestage, occupy the same spatial unit, and share the same properties, like the time (day/week) they entered a stage. Cohorts are the basic units that are modelled in a DYMEX lifecycle. An example of a cohort would be all the juveniles born on a particular day during the simulation. All the individuals within a cohort experience the same conditions during the course of a simulation.

Models created within DYMEX consist of a series of modules, with each module responsible for a particular task. Modules use information from other modules as input, and supply information to other modules. DYMEX comes with a library of modules that can be incorporated into any model constructed with the Builder. Each module performs a specific function (for example, MetBase is used to read a standard set of meteorological variables from a file). Models created in the Builder can be opened in the Simulator within which simulations can be run. The results of these simulations can be displayed in tables, graphs and maps as well as exported to other programs.

Models will normally be developed around one or more Lifecycle modules. Other modules provide data to the lifecycle modules, or manipulate lifecycle output in some way. Many modules have multiple uses (e.g. Function module) and may be used in several places in a model, while others are more specialised (e.g. the Soil Moisture module). Most modules receive input from another module or from an outside source. For example, the MetBase (Meteorological Database) module reads meteorological data from text files and provides the data as variables that can be accessed by other modules.

DYMEX helps you model natural systems using the following features:

Builder and Simulator

DYMEX consists of two programs: a Builder and a Simulator that provide a user friendly platform on which to create and run population models.

MS Windows Interface

DYMEX has a graphical interface providing students and researchers with a simple means with which to build and run models in the Windows environment. Models and their components are presented in a way that is readily understood by ecologists.

Modular Format

The models are created in a modular form, with each module dealing with a separate process, allowing great flexibility to modify or extend the model.

Extensive Module Library

DYMEX contains a library of user-adjustable modules, each of which performs a particular function.

User Documentation

DYMEX comes with two comprehensive User’s Guides, step-by-step tutorials and an online Help system.

Builder - (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 Builder program.

  • Populations can be divided into separate sub-populations (demes) within the model to represent, for example, genetic types or spatial units. When this is done, variables and parameters that take part in the sub-population structure have components that correspond to each sub-population.

  • Operations on lifestage processes have been greatly simplified via a new Lifestage Window. This gives a much better overview of all the processes in the stage, allowing for a better understanding of how the model works. It also reduces the number of dialog operations that were necessary in earlier versions.

  • The Lifecycle Window has been changed to the same format as that in the Simulator. The window can now be sized, zoomed and printed.

  • The Variables Window has been much enhanced. Variables can be sorted and the window gives access to dialogs that allow the variables and associated modules to be edited.

  • The Lifecycle module now can contain factors that belong to the lifecycle as a whole (i.e., they are not part of lifestage processes). This can avoid redefining the same parameter multiple times.

Enhancements from version 1

The Builder has been considerably enhanced from Version 1. For users familiar with Version 1, the following list details the major differences. Those changes that may cause models to behave differently when moved to Version 2 are shown in italics.

  • New modules are available, as follows: Adjustable Circadian, Climate Change Scenario, Daydegree, Difference, Equation, Counter, MetManager, Discrete QueryUser, Accumulator (Running Mean), Storage, Switch and Weather.

  • Modules and their output variables can have descriptions associated with them.

  • The Event module may now have a user-defined delay between trigger and action, a programmable off condition, as well as multiple independent action factors.

  • The Lifecycle module has been considerably enhanced, allowing branching of lifecycles, nested stages (Endostages), an immigration process, "exit" processes and many more lifestage outputs.

  • By default, Chronological Age is now in units of days (not timestep, as in Version 1). If you built a model with a weekly timestep using version 1 of the Builder and it includes chronological age processes, then in order to run it in version 2 of the builder you will either need to change the manner in which chronological age is updated in the lifecycle properties dialogue box to "timesteps", or modify all the chronological age processes accordingly. Lifestage densities are calculated differently.

  • Summary Variables are now set in the Builder and can be manipulated using modules in a similar way to normal variables.

  • Models may be split into several files, with a main Model Description File and a number of auxiliary files. This allows complex models such as a multi-species model to be firstly constructed as separate models, and then combined later.

  • Parameters for a module can be placed into a separate, named Parameter File.

  • All the variables used in the model can be displayed together in a Variables window along with the source module of the variables and the modules where they are used.

Any parameter in any module may be replaced by either a function or a process. Processes can now have associated descriptions.

Simulator - (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 Simulator program.

  • Populations can be divided into separate sub-populations (demes) within the model to represent, for example, genetic types or spatial units. When this is done, variables and parameters that take part in the sub-population structure have components that correspond to each sub-population.

  • The Lifestage window has been extensively redesigned to allow a much better overview of the processes and process components within each lifestage.

  • Lifestages can be initializes with multiple cohorts. This is useful in cases where it is necessary to have each “cohort” correspond to one individual.

  • Lifecycle now can contain factors that belong to the lifecycle as a whole (i.e., they are not part of lifestage processes). This can avoid redefining the same parameter multiple times.

Simulator Enhancements from version 1

The Simulator has been extensively redesigned and there are numerous small differences from Version 1. The following list indicates the major differences:

  • The paradigm used by the Simulator is altered considerably. In Version 1, the user opened a Model (GMD) file. In Version 2, the user opens or creates a new Simulation (DXS or INI) file. The Simulation File is essentially the same as the Initialization File used in Version 1 of DYMEX, and stores settings for a particular run. With this new paradigm, it is an easy matter to save simulation settings at any time.

  • The Model Components window has been redesigned, with many new features. Many modules indicate their settings in more detail. Users can hide modules that do not require initialisation, thus simplifying the appearance of a model. More convenient access to parameters and information about the set of parameters is now available through this window. Sequences can be set more conveniently.

  • The Parameter initialisation window has been enhanced, with a tree-view of the parameters within their hierarchy. A collection of parameter values for a particular module (Parameter Set) can be named, described and saved to a separate parameter file.

  • New modules are available, as follows: Adjustable Circadian, Climate Change Scenario, Counter, Daydegree, Event with Delay, MetManager, Discrete QueryUser, Running Mean, Storage, Switch and Weather.

  • The Lifecycle module has been considerably enhanced, allowing branching of lifecycles, nested stages (Endostages), an immigration process, and many more lifestage output types.

  • Graphical output has been radically redesigned, with charts being more interactive, easier to set up and more flexible in the choice of options. Limits on number of panels and series in charts have been removed.

  • The ability to produce maps has been added for multiple runs using sequences that produce results across geographic regions (for example, those controlled by MetManager or DataFile sequences).

  • Table output is more flexible, allowing the table format to be modified "on-the-fly". Tables from multiple runs can be sorted.

  • Nested sequences and enhanced capabilities for existing sequence types have been added.

Results for individual runs within a multiple run (including detailed tables and charts) can be obtained from the multiple run output tables.

Benefits of DYMEX

No programming needed

No programming and therefore no code debugging is needed to build a DYMEX model.

No code maintenance costs

All code is already written and thoroughly tested.

Easy to use

One of the major aims in the construction of DYMEX has been ease of use, "user friendliness". Simple models can be constructed relatively easily with limited time spent on learning DYMEX. A good understanding of the biology of the organism is still needed but DYMEX takes the pain out of model building by automating many processes.

Rapid model building

A model can be created very quickly using DYMEX as the process is analogous to the use of building blocks, with a large amount of functionality available in each block. Of course, fitting the model to the data and validation are still required, though DYMEX provides facilities to ease these tasks.

Extendable models

Models created in DYMEX can easily be changed and extended using the Builder.

Transparent design

The entire structure of the model can be made visible within the Builder and Simulator.

How DYMEX is being used

Population ecology

Models of populations can easily be created quickly, allowing rapid analysis of the dynamics of populations.

Optimisation of IPM

DYMEX has modules that are designed to add management options to a model. The resultant models can automatically search for optimal strategies, e.g. Chemical, Biopesticides, Host resistance.

Weed ecology & Management

Plant population models can be built and used to explore theoretical and management issues.

Modelling workshops

DYMEX provides a means of communication and so facilitates collaborative involvement in research and applications. Models can be built and operated during workshops to great advantage.

Tertiary education

DYMEX allows biological students and researchers to concentrate their energies on scientific issues by freeing them from the need to learn computer programming.

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