Irregular Sampling Schedules - CTMM variogram

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Guus

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Jan 29, 2026, 10:16:13 AM (6 days ago) Jan 29
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Hi CTMM community,

I'm currently working with a GPS GSM dataset from Northern Lapwings (Vanellus vanellus), and I'm a bit struggling fitting the variogram. I found that my variogram has quite a spiky appearance, which probably is caused by the different frequency in sampling rate (in my dataset, during day time GPS locations were saved roughly every two minutes, while during nighttime only one point per hour was recorded. According to the variogram vignette (https://ctmm-initiative.github.io/ctmm/articles/variogram.html) I should use the dt argument within the variogram function, which I tried, but I still seem to have a large confidence interval. 

The R code I used for fitting the variogram:

# Set dt interval
 dt <- c(2, 60) %#% "minutes"
 
  # Calculate variogram
  vg <- variogram(c_data, dt = dt)
 
  # Fit variogram
  variogram.fit(vg) 

Am I missing a crucial step in the preprocessing? I would like to hear from you!! 

Cheers!

Guus

CTMM unfiltered.pngCTMM filtered.png



Alex Brunswick

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Jan 29, 2026, 7:04:22 PM (6 days ago) Jan 29
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Hi Guus,

You said that the relocations are saved roughly every 2 minutes, and hourly at night. Did you figure that out using the dt.plot function? There is info in the vignettes but it will let you visualise the time-lags between fixes. You can use this to more accurately decide on your dt argument in the variogram.

As far as my knowledge goes, an animal can still be a range resident if it’s variogram is ‘spiky’.

Hope this helps
Alex

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Guus

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Jan 30, 2026, 8:36:59 AM (5 days ago) Jan 30
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Hi Alex,

Thank you for your response! I figured the relocations interval by checking the timestamp column of my dataset. 

I will look into the vignette to visualise the time-lags between fixes!! 

Thanks!

Cheers,

Guus



Op vrijdag 30 januari 2026 om 01:04:22 UTC+1 schreef alexbrun...@gmail.com:
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