RAMAS Red List Technical Support |
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![]() Frequently Asked Questions |
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| Q. RAMAS Red List gives a different threat classification than I expected. Why is the difference? A. In almost all cases, the difference between the IUCN classification that RAMAS Red List gives and one that you obtain by running through the IUCN criteria stems from the parameters you did not specify. If you leave a parameter blank (empty), RAMAS Red List assumes that it is "unknown" and assigns the widest possible range to this parameter. (Why? See below.) For example, if you leave the Future reduction parameter blank, the program assumes the interval [0, 100]%. To correct, make sure that all parameters are specified. If you have no data on a parameter, but you believe that it should not make
a difference in the threat status of the species, you may choose to ignore this
parameter. To do this, click on the button next to the parameter
field. This button looks like We do not recommend ignoring any parameters. Please see the User Manual for a discussion of unknown values. Other reasons for getting a classification that differs from what you expected may include mistaken or different interpretations of the rules. See the "Text results" to follow each step of the program's calculation. Also, read the section on "Assumptions in RAMAS Red List" in the User Manual.
Q. Why does RAMAS Red List assign the widest possible range to parameters that are left blank? A. This issue was discussed at an IUCN workshop on uncertainty in Sydney, Australia, in May 1999. The participants felt that it was more precautionary to assume a blank parameter meant "unknown" rather than "ignored". When a parameter is "ignored", the program assumes that the criteria that refer to that parameter are not met. This is the same as "skipping over" or "omitting" a criterion. However, when a parameter is specified as "unknown", the program sets it to the widest possible range. This is both more precautionary and consistent. The alternative of ignoring or omitting a criterion when data are lacking is inconsistent for the following reason. Suppose there is no data on population size, and thus Criterion D is omitted. Suppose the assessment then is least concern (LC). Then, more data are collected, and it is realized that 500-5000 is a realistic range for the population size. When these data are entered, the assessment covers the range from VU to LC. Thus, the assessment becomes more uncertain with more data! This is not only illogical, but may also be undesirable because it might discourage data collection. A consistent approach would result in less, not more, uncertainty when more data become available. Note that this problem has nothing to do with the particular software or the method of propagating uncertainty. Any consistent or formal method will have the same problem, if unknown parameters are routinely ignored.
In the above example, omitting Criterion D is the same as assuming that Akçakaya, H. R., S. Ferson, M. A. Burgman, D. A. Keith, G. M. Mace and C. R. Todd. 2000. Making consistent IUCN classifications under uncertainty. Conservation Biology 14: 1001-1013.
Q. RAMAS Red List gives an error message asking for an updated version of comctl32.dll. What should I do? A. This happens if the version of the file comctl32.dll you have is not recent. To update, please go to http://www.microsoft.com/msdownload/ieplatform/ie/comctrlx86.asp and select Download 50comupd.exe (x86) to download an executable file. This is a self extracting archive. After downloading, run this file. It will update the system file comctl32.dll on your computer.
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Date modified: 3-20-01