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I would like to know the most suitable sampling strategies and analytical methods (possibly, with relative bibliographical references) to estimate the populational density of wolves through camera traps, without single individual recognition.

So far, I've only consulted this publication (https://besjournals.onlinelibrary.wiley.com/doi/10.1111/j.1365-2664.2008.01473.x), but I'm a beginner in the field, and I would like further advice.

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    $\begingroup$ Without being able to identify and count specific individuals, I would think any methods you find would be suspect. Are you able to identify differentiating characteristics between individuals? $\endgroup$ Nov 21, 2021 at 1:08
  • $\begingroup$ @theforestecologist, nope, no differentiating characteristics available. $\endgroup$
    – Nuthatch92
    Nov 21, 2021 at 9:17
  • $\begingroup$ I can think of ways you might be able to do it with cameras placed in a grid over area and analyzed with time-stamped co-ordination of when counts take place, but I have no idea whether that would be something feasible or not and even if it would be considered statistically reliable. $\endgroup$
    – bob1
    Nov 22, 2021 at 0:12
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    $\begingroup$ Wolves are pretty lean animals, so I'd guess their density is in the range of 0.95 - 1.05 kg/L ;-) $\endgroup$
    – acvill
    Apr 14, 2022 at 12:55
  • $\begingroup$ Density estimation can be reliable without identifying individuals. Check out the resources from St. Andrews Centre for Research into Ecological and Environmental Modeling. creem.st-andrews.ac.uk They regularly offer workshops and are friendly, helpful, top-notch scientists. $\endgroup$
    – ASimonis
    May 5, 2022 at 0:21

2 Answers 2

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Population estimation of wolf is a decade long challenge. Since wolves are wide ranging species, detection rate is very low in the camera traps. As they are difficult to identify at individual level it increase the chance of bias. However, with modern technologies we can estimate the wolf abundance using camera traps. I found two studies relevant to your question, 1. Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring- here they have identified packs and estimated the pack density. This method can be applicable over larger areas where atleast 10 packs exists. 2. Estimating wolf abundance from cameras- here they have used motion triggered cameras and used Space Time Model (STE) to estimate the abundance of wolf. Both the method have catch in it. Wolf packs are very dynamic and chances of avoiding camera traps (trap happy/trap shy) can cause possible bias. The main challenge is to extrapolate the data at landscape level.

  1. Mattioli, L., Canu, A., Passilongo, D. et al. Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring. Front Zool 15, 38 (2018). https://doi.org/10.1186/s12983-018-0281-x
  2. Ausband, David E., Lukacs, Paul M., Hurley, Mark, Roberts, Shane, Strickfaden, Kaitlyn, and Moeller, Anna K.. 2022. “ Estimating Wolf Abundance from Cameras.” Ecosphere 13( 2): e3933. https://doi.org/10.1002/ecs2.3933
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You could look into using a version of point - sampling distance sampling [1]

Also, [2] might help a bit to be more flexible than using a grid (even if it is on spatial capture recapture).

[1] Howe, E.J., Buckland, S.T., Després-Einspenner, M.-L. and Kühl, H.S. (2017), Distance sampling with camera traps. Methods Ecol Evol, 8: 1558-1565. https://doi.org/10.1111/2041-210X.12790 https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12790

[2] Durbach, I, Borchers, D, Sutherland, C, Sharma, K. Fast, flexible alternatives to regular grid designs for spatial capture–recapture. Methods Ecol Evol. 2021; 12: 298– 310. https://doi.org/10.1111/2041-210X.13517 https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13517

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    $\begingroup$ I edited your post to add full citations (in case those links ever get changed/break) $\endgroup$
    – selene
    Apr 14, 2022 at 15:55

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