Hi,

I have been analyzing our SLAMM out put data two ways: 1) using the SLAMM output data tables (and converting ha to ac), and 2) using GIS (calculating ac and ha by converting pixel counts in attribute tables based on pixel size). The GIS analysis is necessary for post-processing some information, like which lands are already conserved, or tracking specific changes in SLAMM classes (e.g. how much area converted from RFM to TF).

I've noticed a significant difference in acreages between the two methods. For example, at time 0 there is a difference of 5 acres in my study area (of about 7,000 acres). But looking at total tidal wetland acreage by 2100, one simulation has a difference of 85 acres. I find these differences even when I'm not aggregating classes (i.e. when comparing the acreages of a single class, like RFM).

Have you encountered this before? Do you have any thoughts on what might be causing these differences?
I would like to continue to use both data sets, as the one from SLAMM reports on all the time steps (which would take a long time to do in GIS).

Thanks,
Nava.

When running an uncertainty analysis, are there any down sides to including the DEM uncertainty as a parameter? Is there strong criticism of uncertainty model results that don't include it?

If I understand correctly, the historic trend is used both to estimate local subsidence/uplift (the difference between global and local SLR) and to reconcile the DEM to the NWI photo date. The global trend is measured over 100 years (1900-2000), while the difference between my DEM and NWI photo is only 6 years, and much more recent. So the local SLR measured over the time 1900-2000 is much lower than that measure for the period between the NWI and DEM dates (something like 2.8 vs 6.8 mm/yr). How would you advise choosing just one historic trend number (or is there a way to specify more than one, for each specific use)?

In running SLAMM with somewhat customized wetland categories (for the Hudson River), we are seeing a progression where cells don't convert to a couple of our categories (tidal swamp and vegetated tidal flat). We are thinking this could be because of elevation range overlap that each of these categories have with other categories. Does this make sense? Any other possible reasons?

In running SLAMM for the Hudson River (a long estuary), we have a variety of tide ranges along the river. Is specifying subsites the best way to deal with this variation (or can SLAMM use some file with tide information for the entire estuary to process this automatically)?
Thanks!

I just running SLAMM for the first time, and I'm getting and error: "Unable to write to C:\
Program Files\SLAMM 6.2 Beta\SLAMM6.INI" when I try to save a simulation. Any ideas?
Thanks!