1. General Model Information

Name: Phenology and populatIoN SIMulator

Acronym: INSIM


Main medium: terrestrial
Main subject: biogeochemistry
Organization level: ecosystem
Type of model: not specified
Main application:
Keywords: crop protection, pest, phenology dynamics, population dynamics,insect

Contact:

Dr.ir. P.J.M. Mols
Wageningen Agricultural University
Dept. Entomology
Binnenhaven 7
6709 PD Wageningen
THE NETHERLANDS
Phone: +31.8370.82792
Fax : +31.8370.84821
email: peter.mols@medew.ento.wau.nl

P.J.M. Mols

Author(s):

P.J.M. Mols

Abstract:

For the development of forecasting models a computer environment has been contructed which makes it possible to generate in a user friendly way a programme of the phenology and population development of an insect species. INSIM menu driven and needs only the biological information of the insect species. INSIM generates age-structured models and therefore includes modules calculating number and development of insects by using of boxcars, to account for the relative dispersion of development. The rectangular integration method is used, with a fixed time step. By means of tables all life-history data are read into the programme. For a simple phenological or population model the information needed is: life cycle, development rate and standard deviation of each insect stage, sex ratio, life expectancy of the adult and age dependent reproduction. In a spreadsheet the stages are coupled to each other which makes the programme rather flexible. The weather data are stored in an environment file. The data needed are the number of the day and the minimum and maximum daily temperature. The temperature for each time step is calculated from a sinusoid through the minimum and maximum temperature. The output of the chosen variables can be presented graphically or numerically on the screen. For the simulation of complicated predator prey interactions specific programming is still needed but this is not too complicated as the program is written in Quick basic. Examples of simple phenological and population models and more complicated pest-natural enemies models will be presented.

Author of the Abstract:

P.J.M. Mols 1995 Abstracts 4th International Symposium on Computer Modelling in Fruit Research and Orchard Management 4-8 SEPTEMBER 1995 - AVIGNON, FRANCE


II. Technical Information

II.1 Executables:

Operating System(s): > 386 SX; > 33 MHz

II.2 Source-code:

Programming Language(s): Quick BASIC

II.3 Manuals:



II.4 Data:



III. Mathematical Information


III.1 Mathematics

Rate variables: Development rate of life stages and their standard deviation, relative mortality

III.2 Quantities

Rate variables: Development rate of life stages and their standard deviation, relative mortalityrates, age dependent reproduction.

Number of rate variables: Depending on complexity of life cycle.

State variables: Amount of each stage.

Number of state variables: Maximum 24.

Development rate, relative mortality of each life stage, stages in life cycles, weather

III.2.1 Input

Development rate, relative mortality of each life stage, stages in life cycles, weatherdata (maximum and minimum daily temperature). Relative or absolute numbers of each stage, temperature sums.

III.2.2 Output

Relative or absolute numbers of each stage, temperature sums.

IV. References

Mols, P.J.M., 1990.
Forecasting orchard pests for adequate timing of control measures.
Proc. Exp. & Appl. Entomol., NEV. Amsterdam vol. 1. 75-81

Mols, P.J.M., 1992.
Forecasting an indispensable port of IPM in apple orchards.
Acta Phytop. Entom. H. 27(1-4), 449-460


V. Further information in the World-Wide-Web


VI. Additional remarks


Last review of this document by: T. Gabele: 17. 07. 1997 -
Status of the document:
last modified by Joachim Benz Mon Jul 2 18:31:37 CEST 2007

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