Syncrosim › Forums › ST-Sim & State-and-Transition Simulation Models › Temporal transition multipliers
Tagged: MCM, MCM structure, Temporal transition multipliers
- This topic has 1 reply, 2 voices, and was last updated 6 years ago by Colin Daniel.
May 24, 2017 at 11:44 pm #4410istvanParticipant
I just started using ST-Sim, and I am looking for a way to incorporate ‘global’ transition multipliers, like climatic effects which would alter several transition probabilities.
For example: a high early season precipitation could occur with a given probability and would increase the probability for fire and for establishment.
So my questions are:
1. Could this be accomplished with an MCM file? And: how does the structure of an MCM file look like?
2. Are there any other ways than the MCM method?
3. In the advanced Tab, there is an option to create custom distributions besides normal and beta. How does that function work? I could not figure out how to parameterize a custom distribution.
Thanks for Help!
IstvanMay 26, 2017 at 5:58 pm #4412Colin DanielKeymaster
An MCM file is a very particular approach for setting up variability in transitions over time that was developed in the 1990s for use specifically with a software product called VDDT. With ST-Sim there are now unlimited possibilities for how to specify variability in transitions, including covariance between model inputs, so it no longer makes much sense to restrict oneself to something so specific as the old MCM approach. I occasionally hear of former VDDT users in Oregon still referring to the approach, but that’s about it. Everyone else seems to have moved on.
There are many ways to specify spatial and temporal variability in transitions. How you do this depends on the processes you are trying to represent. Some of us have spent a large part of our careers trying to do this properly. There are also many examples of it being done naively and thus, I would argue, poorly. I suggest looking at the paper by Daniel et al (2016) to get a sense of some of the opportunities and challenges of characterizing variability in model inputs. I’m afraid it’s not something that can be really be covered in a forum post.
We are planning to offer an advanced course in ST-Sim this fall, however, where this kind of question would be discussed. The final dates for the next training session have not yet been finalized, but if you check back regularly on our home page (or subscribe to our news feed) then you should see the announcement soon.
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