{"id":326,"date":"2013-04-26T00:45:05","date_gmt":"2013-04-26T07:45:05","guid":{"rendered":"http:\/\/blogs.oregonstate.edu\/geo599spatialstatistics\/?p=326"},"modified":"2015-03-30T10:07:23","modified_gmt":"2015-03-30T17:07:23","slug":"autocorrelation-and-movement-patterns","status":"publish","type":"post","link":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/2013\/04\/26\/autocorrelation-and-movement-patterns\/","title":{"rendered":"Autocorrelation and movement patterns"},"content":{"rendered":"

My objective was to see if the displacement of the birds showed particular patterns. For this, I decided to analyze the distribution of speed and rotation angles in space. Speed at a particular point is calculated as distance to previous point over time taken to move between points. Rotation angle refers to the angle between two consecutive movement lines (i.e., lines joining point A to B and B to C).
\nI first tried the Spatial Autocorrelation function, which indicated a clustered distribution of the values.<\/p>\n

\n \"\"<\/a>\n
Example of output of the Spatial Autocorrelation tool applied to rotation angles.<\/figcaption>\n <\/figure>\n

These results weren\u2019t meaningful for me though, as I was interested in the variability within the observations. Studies on different animals species have shown that the analysis of variability within movement patterns can be used to infer behavioral patterns. I expected the birds would show varying speeds and rotation angles in response to the habitat where they were living (e.g., move slower inside the forest and quicker between forest patches; straighter movement lines in non-forest habitat). Thus, I decided to apply the Incremental Spatial Autocorrelation function, as this tool would indicate if the spatial clustering of values varied in the study area.<\/p>\n

The results show mixed responses from each bird, with no clear interpretation for the observed patterns.<\/p>\n

\n \"\"<\/a>\n
Example of output of the Incremental Spatial Autocorrelation tool applied to speed.<\/figcaption>\n <\/figure>\n
\n \"\"<\/a>\n
Example of output of the Incremental Spatial Autocorrelation tool applied to rotation angles.<\/figcaption>\n <\/figure>\n

Most of them have non-significant z-scores, and those that do have no clear relationship to any environmental factor. \u00a0Hot spot analyses don\u2019t show a particular concentration of values at any point either.<\/p>\n

\n \"\"<\/a>\n
Example of output of the Hot Spots tool as applied to rotation angles.<\/figcaption>\n <\/figure>\n

 <\/p>\n

In conclusion, speed and rotation angles are either A) not affected by the disposition of forest or B) bad indicators of behavioral changes associated to space use.<\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

My objective was to see if the displacement of the birds showed particular patterns. For this, I decided to analyze the distribution of speed and rotation angles in space. Speed at a particular point is calculated as distance to previous point over time taken to move between points. Rotation angle refers to the angle between… Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":5013,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-326","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/posts\/326","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/users\/5013"}],"replies":[{"embeddable":true,"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/comments?post=326"}],"version-history":[{"count":8,"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/posts\/326\/revisions"}],"predecessor-version":[{"id":343,"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/posts\/326\/revisions\/343"}],"wp:attachment":[{"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/media?parent=326"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/categories?post=326"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dev.blogs.oregonstate.edu\/geo599spatialstatistics\/wp-json\/wp\/v2\/tags?post=326"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}