System Dynamic Modelling

 

 



 





















 






















 
 
Models Developed Using FLORES Architecture
   
 

Our research in Zimbabwe, Indonesia and Cameroon produce four different models, which meet local needs.

There are four FLORES models currently developed:

1. The Rantau Pandan model:

This is the first FLORES model and is pretty complex and unwieldy, but has some interesting knowledge expression. It deals with people-forest interface issues in Jambi province in Indonesia, i.e. rice farmers, shifting cultivation, jungle rubber and social and ecological issues. It has been fairly well documented.

Fergus Sinclair has been working on this model over the last couple of years, although Jerry Vanclay started the ball rolling initially.


2. The Zimbabwe (Mafungutsi) FLORES model:

This is the second FLORES model. Considerably 'leaner' than the first model, this one deals with people-forest interface situations in Zimbabwe. The thinking has advanced here, particularly on the 'people' side of the model. The model is very well documented, however it is still pretty complex and shows some peculiar behaviour - it has not been finished callibration yet.

The lead researcher is Mandy Haggith.

Download Model and Documentation (523 KB)
See Related Papers


3.

East Kalimantan FLORES model:

This one is fairly simple, but does not follow the 'typical' FLORES architecture. It has been fairly well
documented as well.

Herry Purnomo is working on this and is happy to share it.

Download Model (27 KB)
See Related Papers

4.

Cameroon FLORES model:

This will be another 'big' FLORES model once it is finished.

Chris Legg is the person to contact.

See Related Papers
Download Model (372 KB)

Note: The model is by no means fully operational yet, but seems to run reasonably stably, and I think that it is time to put it on the web to attract comments and hopefully suggestions. Feel free to do what you like with it. It should be run withtime step 1 = 0.5 and time step 2 = 0.02. Display interval should be 0.08(one month) for long runs with coarse detail and 0.02 (one week) for shorter more detailed runs. I run the model on a Pentium 4 desktop with 512 Mb of RAM, and it goes quite fast. The data required after building the model in C is is the two *.csv files.