I am looking at the short (hours and day) and mid-term (weeks and months) movement patterns of cetaceans, in particular sperm whales. Scientific literature is full of references but I am a bit confused concerning the best way to look at my data. Which are the best models to study and describe these patterns? And which are the most useful tools to investigate this aspect of animal ecology? I am aware of many GIS tools (eg. ArcGis Animal Movement tool, QGIS AniMove Tool, packages for R) but i do not know which one would better adapt to my data. I am using hourly, daily, weekly and monthly photo-identification recapture data.
Hi,
It all depends on the question at stake and what you want out of these approaches. I used to work with MARK to extract behaviour pattern, but also because you can then estimate population size from you mark-recapture study. I guess this is also one think you should do. There are very few data on sperm whale, so it could be cool to estimate population size based on your data. I think one has to try the several models and see what you could get out of it and will give the clearest answers, or clearest pattern, the one you are pleased with.
I agree with the other two posts that you question(s) will define your approach. I will try to provide some direction where to look depending on your interests.
- home range and core use areas (kernel utilization distributions) - R package 'adehabitat' or 'Home Range Tools' for ArcGIS (http://flash.lakeheadu.ca/~arodgers/hre/)
- habitat/environmental associations - Euclidean distance analysis (EDA), and/or forms of logistic/binomial models, including generalized linear models, generalized additive models (and mixed models of these forms) and general estimation equations. These can be conducted in R, or combining R with ArcGIS (example - Furey, N.B., Dance, M.A., Rooker, J.R., 2013. Fine-scale movements and habitat use of juvenile southern flounder Paralichthys lethostigma in an estuarine seascape. Journal of Fish Biology 82: 1469–1483. doi: 10.1111/jfb.12074). EDA (used in the example given) is a robust and "simple" way to look at habitat associations with telemetry data, while GAMs provide a manner to examine the impacts of variables not tied to a location.
- structure of the movement patterns themselves - fractal analysis (example: Papastamatiou, Y.P., Lowe, C.A., Caselle, J.G., Friedlander, A.M., 2009. Scale-dependent effects of habitat on movements and path structure of reef sharks at a predator-dominated atoll. Ecology 90, 996–1008.) and 'fractal' software (http://www.dal.ca/faculty/agriculture/environmental-sciences/faculty-staff/our-faculty/vilis-nams/fractal.html)
- animal behaviour during movements (foraging vs travel, etc) - state space models (examples: Breed, G.A., Jonsen, I.D., Myers, R.A., Bowen, W.D., Leonard, M.L., 2009. Sex-specific, seasonal foraging tactics of adult grey seals (Halichoerus grypus) revealed by state-space analysis. Ecology 90, 3209–3221.
Jonsen, I.D., Flemming, J.M., Myers, R.A., 2005. ROBUST STATE-SPACE MODELING OF ANIMAL MOVEMENT DATA. Ecology 86, 2874–2880.
-and a "roadmap" for state-space model use - Jonsen, I.D., Basson, M., Bestley, S., Bravington, M.V., Patterson, T. a., Pedersen, M.W., Thomson, R., Thygesen, U.H., Wotherspoon, S.J., 2013. State-space models for bio-loggers: A methodological road map. Deep Sea Research Part II: Topical Studies in Oceanography 88-89, 34–46.)
As you can see, there are a variety of potential methods, all of which (I think) can be implemented in R.
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