I run the model successfully after your help with some errors and I am trying to interpret the output data. It seems that despite the habitat role value differs along the shore points, the relative percentage does not. To be more specific, a short calculation for the extraction of the habitats’ contribution to the total exposure (“habitat_role”/“exposure” *100%) gives the same result for every point (with habitat_role other than 0). Would it be more reasonable for such a value to vary? There is only 1 kind of habitat in this study, does this matter? I would appreciate any comments.
Hi @byron each shore point is either protected by each habitat or not. There is nothing in between. So for all points protected by “habitat A”, there is no variation in how much protection that habitat is providing.
“habitat role” is simply calculated as the difference in exposure between two scenarios: one where the habitat is present as given by your input data, and one where the habitat is magically removed. “habitat_role” can vary while “R_hab” does not only because other factors of exposure are varying at that shore point. For example, if a shore point is well-protected along all the other dimensions of risk, then the role of the habitat - even when present - will be relatively low. The idea is to use “habitat role” as a way to find areas of the shore where habitat is especially important because the area is otherwise very exposed to hazards.
Ok, so for visualization of the habitat contribution to the exposure reduction, the “habitat_role” values are used but only for spatial identification of the coastal points and not for quantification.
Still, the higher “habitat_role” values, although varying due to the other factors as you described, induce higher habitat effect. I mean they can’t be used to quantify the role numerically, but it is right to classify the areas upon this vaue for the level of habitat contribution, is that correct?