Other people using ABMS for spatially explicit ecological modelling

I recently went to a talk by Lael Parrot who was visiting Southampton University for the week. Not a name I had heard of before but I'm quite surprised at this now considering she is involved in very similar work to me!

The most relevant paper I found from her was the one she talked about at the seminar she gave:

Anwar, S.M., Jeanneret, C.A., Parrot, L. & Marceau, D.J. (2007) Conceptualization and implementation of a multi agent model to simulate whale-wathcing tours in the St. Lawrence Estuary in Quebec, Canada. Environmental Modelling and Software 22 1775-1787.

Not only was this paper spatially explicit and employed agent-based modelling, but it was done using the Repast Simphony toolkit!! Finally, an ecological example of someone doing a peer-reviewed and published piece of research using Repast.

I've not yet management to dive into the paper in depth but some of the simulations Lael showed during her talk have me very impressed - linking the repast output with GIS data and creating some pretty good looking 3D models of the system. They also re-integrated the model output with the original GIS data to do some spatial analysis and statistics, so I wonder whether this might also be my best option... definitely something to look into in more detail.

Its a much bigger model than mine will be so I have no doubt that I'll be able to pick up some interesting tips from Lael and the paper. I'll report back with any useful bits of information.

Policy placement with the National Assembly for Wales

So i've been quiet for a while now due to me doing a PhD placement for 3 months with the Research Service of the National Assembly for Wales. I'd definitely recommend doing something similar if given the opportunity and you are thinking about a career outside of academia. This particular placement was quite politics heavy which isn't necessarily what I want to get involved with, but it did give me a tremendous insight into how policy is formed and amended and what goes into devising and publishing national strategy documents.

I was based in the Environment and Sustainability research team meaning I got to be involved with a lot for work currently being undertaken within the Assembly - namely a review of all things Energy in Wales, the publication of the 'Sustaining a Living Wales' Green Paper and the review of merging the three statutory environmental bodies (Countryside Council for Wales, Environment Agency Wales and Forestry Commission Wales) in Wales into a Single Environment Body. Some really interesting topics which meant I got to develop, prepare and publish useful documents on these subjects to the Assembly Members and the general public.

A list of my contributions during the placement:

1. An introduction to natural environment policy in Wales and a comparison with natural environment policies for other parts of the UK (Research paper)
2. Ecosystems and the Ecosystem Approach (Quick Guide)
3. Nature Conservation Designations (Quick Guide)
4. Briefing on Legal Enforcement of European Statutory Legislation (internal briefing to the Environment and Sustainability Committee)
5. Briefing on Tidal Flooding and Coastal Erosion (internal briefing to the Environment and Sustainability Committee)
6. Briefing on Technical Report to Environment Agency Wales on an Investigation into Cockle Mortalities at Burry Inlet (internal briefing to Petitions Committee).

Repast Batch runs

Ok, so I have successfully got my model to work in batch mode ! :)

Am VERY happy!

The key things seems to be that you can only access parameters from the batch_params.xml file that have been explicitly set up within the model to be controlled by the user (i.e. included within the parameters.xml file in the 'projectName'.rs folder of the project.

Also, if there are any parameters set up in this way that are not included in the batch_params.xml file, the model will not run in batch mode. This only seems to apply to parameters included in the contextCreator file, not those set up within other classes of the model.

Some information seems to be misleading.... in the previous batch post I alluded to a webpage that might be useful from the repast.sourceforge website. This information relates to running a model in batch mode but goes through a quite complicated scenario of installing GridGain and using this to run the model.
This is NOT required to run a simple batch run within eclipse on the local computer. It appears to be most useful for distributing the model to other sources, and using grid computing to run batches...

I doubt I'll need anything quite this complicated as of yet....

Today is a good repast day!

Model Decision-Making

Ok, so following on from the 'model dilemma' post, I have decided, rather than choosing between the two separate movement decision options, to combine them together.

So, instead of having my agents move around looking for food and ignoring the type of habitat, they now make a decision based on 4 factors:

1. amount of food
2. habitat cost
3. pheromone cost
4. road cost

Decisions are now based on a weighting of these 4 parameters, with the need to move still driven by food requirements, but the decision inherently based on weighing up pros of food availability vs the cons of habitat/pheromone/road cost (which implicitly include a range of other factors that may be important to movement decision making by jaguars).

A total 'cell quality' value now exists for each neighbour and the jaguar choose the cell with the best cell quality, calculated as follows:

cellQuality = food - (0.1*habitatCost) - (0.1*pheromoneCost) - roadCost

Food is explicitly linked to habitat, with the food reaching a maximum of 10 in good quality preferential forest habitats.

habitatCost and pheromoneCost reach a maximum level of 100 and so are multiplied by 0.1 to standardise the relative values to that of food. 

roadCost is a tricky one, I haven't yet decided whether to go to a maximum cost of 10 here or to 100, to provide a better relative difference between road types..... The main tricky aspect here is that I want to encourage males to use the trails (classed as a type of road) but discourage the females from doing the same. In this way, males view the smaller forest trails as either of no cost or negative cost (TBC) whereas females see them of some low cost value.

This method of combining the food and cost decision making loops takes out around 3/4 of the steps required in the food loop, making only one additional step to the cost loop - a biased choice towards maximising food if the jaguar has low food reserves. 

Adding in different costs for the trails also provides some inherent decision making towards using trails or not, versus the hard-coding probabilistic choice to avoid or prefer trails that was used in both the food and cost loops.