Some installations of SDR 4 did not include the LIFEScore.scr data file, so LIFE Score analyses will fail, with the error message "Cannot open file 'C:\Program Files\Species Diversity and Richness\LIFEScore.scr'. The system cannot find the file specified".
To fix this error, please download the missing file from here
(right-click and choose 'Save As'). Unzip the file, and save 'LIFEScore.scr' into the \Species Diversity and Richness folder indicated in the error message. The analysis should now run correctly.
Issues with older versions of the program:
When running a comparison of the alpha diversity indices of two samples, if you press Stop before the program completes all its iterations, the program will from then on run only one randomisation. The solution is to close down and restart the program. This bug was fixed in version 2.6.
In the Renyi, Right-tailed sum and Rank Abundance calculations, selecting different years' data for analysis did not result in the correct data being plotted. This was fixed in version 2.6.
Other known issues and FAQs are described below:
I entered the data in a spreadsheet program, and saved it as a csv file. When I try to open it in SDR, the numbers are separated by ; not , so the analysis will not run.
This is because some non-British systems use ; instead of , to separate values in a csv file. Open Windows Explorer, and change the file extension from csv to txt (i.e. Filename.csv becomes Filename.txt). Open the txt file in Word or another word-processing program. Use the Find/Replace function to replace every ; with a , then save the file again. Change the txt file extension back to csv. It should now open and run perfectly in SDR.
When a data file is opened, all the data are dumped into the first cell, rather than opening in the grid properly
This is usually because there are one or more blank cells in the second row of data. If the
blanks are replaced by zeros, or another row with no blanks is put in the second position, the problem should disappear. Row 2 is the crucial one; blank cells are tolerated elsewhere.
'' is not a valid floating point value.
This will occur if the raw data holds blank columns or rows. Remove blank columns and rows by using 0 issues in the working data window. It may also occur if the raw data holds a blank cell. In some cases SDR II will identify the problem cell which should be edited. Normally it is because the data has been prepared in a spreadsheet using blanks to represent zero values.
I/O error 32 - access denied
This will occur if the data file you are trying to open is currently being used by another program - normally the spreadsheet which was used to organise the data. Close the file in other programs and try again.
My files do not appear to be saved
This is often caused by the lack of the correct file extension. The program only shows files with the .csv extension. To see other files in the open file dialog type *.* into the file name box and press return. - WARNING this will show all the files in the directory - whether they are compatible with the program or not. If you have saved a file without an extension either add the extension outside the program or open the file and save with the correct extension using Save As.
How can I analyse biomass data?
With biomass data the Shannon index can be used to compare samples as this measures the information content. However, remember that you cannot compare the index calculated with that found using numbers. Species diversity & Richness also requires integer input so if your biomass data are real values you will need to multiply them by a suitable factor to use the program. e.g. if you have say 1.2 grams per sq. m. change it to 1200 mg per sq m. The Q statistic will probably also be useful.
A final approach worth examining is to see if your biomass data fits a parametric distribution e.g. log series or log normal. If it does then you can use the parameters of the model as an index. For example, if a log series fits reasonably well, the alpha parameter is an excellent diversity index.
Percentage frequency data is a problem. If you are dealing with percentage coverage data for plants then see if it fits a truncated log normal. But, you will need a lot of data for this to be testable.
How can I analyse real numbers (e.g. 4.5)?
Species Diversity and Richness is designed to work with whole numbers (integers). To work on a derived dataset that includes real numbers simply multiply the data set by a suitable factor to make all the values integers.
How can I analyse % cover data?
The Shannon-Weiner Index can be used with % cover data when you want to compare sites which have all been sampled in the same way. Care must be taken not to compare the diversity measures calculated with those generated from full quantitative data.
A site with cover values 4,1,1,1,1 will have a higher Shannon diversity than a site with 5,1,1,1,1 because the former is more equitable. A site with 5,5,5,5,5 will have a higher diversity still. This is all quite reasonable and works as one would expect. You should note that the Shannon-Weiner value calculated for percentage cover data will tend to just reflect the species number. This is because the values can only range from 1-5 rather than from 0-infinity thus the resolution of differences in equitability between sites is much reduced.
The question is, do you really need to use the Shannon index? Perhaps you might be better using species richness. From your vegetation surveys you could use one of the recently developed total species richness estimators such as the Chao equation to estimate the total species set for each sample and its variance. You could then consider if the sites are significantly different.
Alternatively a vegetation classification procedure such as TWINSPAN might be the best approach. This is designed to use % cover data.
We sell programs which can help you with all the above tasks - contact us
My data set has a large number of columns (sites/samples), but Excel will only allow me to have up to 255
A common problem with large data sets. Use our ListCombiner
utility to combine large data sets effortlessly!