Using ds function in R Distance package

[Gemma Veneruso]

Hi Listers,

 

I am trying to calculate abundance estimates of harbour porpoises from line-transect survey data (CDS). I have only VERY BASIC R knowledge and have got stuck along the way! I am using the ‘Distance’ package. Using the ds function I successfully produced estimates using a flatfile at first. However, I have a number of samples where no detections were recorded. Since each row in the flatfile represents a detection I figure I cannot include effort and samples where there were no detections in this table. So I presume I need to use the separate tables region.table, sample.table and obs.table. I have created these in what I think is the correct format but have two queries:

1)      How do I input these into the function? I have tried to read the csv files of each table and then:

 

Abund<-ds(data, truncation=400, key="hr", order=0, region.table = region.table, sample.table = sample.table, obs.table = obs.table). I tried this to try to tell R that these tables are not NULL, I suspect this is not correct. Can you tell me how I should tell the function to use these tables? ‘Data’ refers to a table with object and distance columns. I would also like to include cluster size and eventually sea state to run MCDS (Can I include these in this table?)

 

I get the following error: Error in checkdata(data, region.table, sample.table, obs.table, formula) : 

  obs.table must have columns names 'Region.Label', 'Sample.Label' and 'object'

 

This brings me onto my second query:

2)      The error suggests that obs.table is incorrect. I have a table with the three requested columns so I am not sure why it will not accept this. My only uncertainty about this table is the object column, is this simply a column from 1 to ….. representing the detection number and linking to the data table?

 

Any guidance would be much appreciated. Apologies for my R ignorance!

 

Many thanks,

 

Gemma Veneruso

 

 

 

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[Eric Rexstad]

Gemma

Rather than answer your questions 1 and 2; I'll stop you at the point where you say

"Since each row in the flatfile represents a detection I figure I cannot include effort and samples where there were no detections in this table."

That is not an accurate statement, it is very common for there to be transects without detections, so there must be some way to accommodate that in the data files.  The answer lies by looking at an example data file associated with the Distance R package

http://distancesampling.org/R/vignettes/minke.csv

If you examine that comma-delimited text file, you will see that transect 5 in the South stratum as well as transect 6 in that stratum had no detections (lines 26 and 27 in the file).  The way to determine this is to note that those rows contain stratum name, stratum size, transect label, transect length, *but no distance*.  There is a comma after transect length but no value following the comma.

That is the way in which you construct a 'flatfile' for surveys that include transects with no sightings. If you are happy with the 'flatfile' format, then I will not answer your questions about region/sample/obs tables.  See if that works for you.

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Eric Rexstad
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