Hello,

I am currently evaluating different ways to analyse a specific multiple
species monitoring system. One idea is to identify the important covariates
with random forest. However, there are some points I have problems to get my
head around.

1. I have observations from a GRID with 25 systematic plots, as well as 5
random plots within the GRID. To analyze observations of a single species
with rf, can I pool those 30 plots together, or is this invalidly mixing of
random and systematic plots?

2. The systematic plots are 100 m apart from each other. I have distance
data for each observation (DISTANCE sampling is another tool used). If I
truncate the data at 50 m, I get truly independent data for each plot (apart
from the 5 random plots, that is). Is there an advantage doing it this way,
or is it more plausible to use untruncated data and have more observations?

3. As I said, I have multiple species. Is there a difference between running
rf analysis on data of a single species only (presence/absence) versus
pooling all species into one analysis and separating the results?

4. For birds, I have aural and visual detections. This has a big influence
on detectability, so I keep analysis in DISTANCE apart. I assume that I can
pool them together for rf if I use aural/visual as a covariate, right?
Any comments are greatly appreciated.

Best regards,

Dirk Nemitz


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Dirk Nemitz
Zeppelinstr. 11a
37083 Göttingen
Germany

Tel:     +49 (0)551 492 32 51
Mobil: +49 (0)175 709 31 92
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