![\"trajectorymn06_188a\"](\"http:\/\/blogs.oregonstate.edu\/geo599spatialstatistics\/files\/2015\/04\/trajectorymn06_188a.jpeg\")
<\/p>\nThe goal of this exercise was to investigate spatial autocorrelation in the movement parameters of a foraging humpback whale. I used location points of sightings of the whale at the water surface between consecutive dives to infer the path of the whale (Friedlaender et al., 2009). To facilitate the analysis, I assumed linear travel of the whale below the surface between consecutive surfacings. I projected the location points and used the adehabitatLT package in R CRAN (Calenge, 2011) to plot the location points of the whale as well as the linear travel segments between these points (see graph below).<\/p>\n
The blue triangle indicates the first, the red square the last observation of the whale at the surface.<\/p>\n
Using projected data, the adehabitatLT package calculates the distance traveled by the whale between consecutive observations, the turning angle between consecutive linear segments of the whale\u2019s path as well as the duration between the observations. Using the distance and duration data I calculated the swimming speed of the whale.<\/p>\n
Then I calculated the spatial autocorrelation in swimming speed and turning angles using Moran\u2019s I for the entire path, and also for a small section of the path which I assumed to be a foraging area of the whale (cluster of points southeast of the blue triangle). In this small area, the whale spent a comparatively large amount of its time and swam shorter distances between consecutive surfacings, possibly indicating foraging activity.<\/p>\n
A small p-value in one of the parameters would provide convincing evidence for the hypothesis that the movement of the whale is autocorrelated in the respective parameter, i.e. that neighboring locations have more similar values than locations that are further apart.<\/p>\n
The results from the current analysis (see table below) provide moderate evidence for spatial autocorrelation in swimming speed for the analysis of the entire path, indicating that the whale swam slower in certain parts of its path and faster in other parts (Calenge 2011). However there was no evidence to suggest that travel speed in the small foraging area was autocorrelated. This could be explained by the fact that in the foraging area, the whale swam at a constant, slow speed to the probability of prey detection or encounter (Benhamou, 1992). When leaving this foraging area, the whale is likely to increase its speed, resulting in separate areas of the whale\u2019s path with lower and higher swimming speeds, which would explain the autocorrelation in swimming speed observed for the entire path.<\/p>\n
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| <\/td>\n | Entire path<\/strong><\/td>\n| Foraging area<\/strong><\/td>\n<\/tr>\n | <\/td>\n | Speed<\/strong><\/td>\n | Angle<\/strong><\/td>\n | Speed<\/strong><\/td>\n | Angle<\/strong><\/td>\n<\/tr>\n | p-value<\/strong><\/td>\n | 0.017<\/td>\n | 0.841<\/td>\n | 0.702<\/td>\n | 0.651<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n | <\/p>\n <\/p>\n Benhamou, S. (1992). Efficiency of area-concentrated searching behaviour in a continuous patchy environment. Journal of Theoretical Biology – J THEOR BIOL<\/em>, 159<\/em>(1), 67\u201381. http:\/\/doi.org\/10.1016\/S0022-5193(05)80768-4<\/p>\n Calenge, C. (2011). Analysis of Animal Movements in R: the adehabitatLT Package. Saint Benoist, Auffargis, France: Office Nationale de La Chasse<\/em>. Retrieved from http:\/\/cran.gis-lab.info\/web\/packages\/adehabitatLT\/vignettes\/adehabitatLT.pdf<\/p>\n Friedlaender, A. S., Hazen, E. L., Nowacek, D. P., Halpin, P. N., Ware, C., Weinrich, M. T., Hurst, T., Wiley, D. (2009). Diel changes in humpback whale Megaptera novaeangliae<\/em> feeding behavior in response to sand lance Ammodytes<\/em> spp. behavior and distribution. Marine Ecology Progress Series<\/em>, 395<\/em>, 91\u2013100. http:\/\/doi.org\/10.3354\/meps08003<\/p>\n <\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" The goal of this exercise was to investigate spatial autocorrelation in the movement parameters of a foraging humpback whale. I used location points of sightings of the whale at the water surface between consecutive dives to infer the path of the whale (Friedlaender et al., 2009). To facilitate the analysis, I assumed linear travel of… Continue reading |