{"action":"created","issue":{"url":"https://api.github.com/repos/MoBiodiv/mobr/issues/128","repository_url":"https://api.github.com/repos/MoBiodiv/mobr","labels_url":"https://api.github.com/repos/MoBiodiv/mobr/issues/128/labels{/name}","comments_url":"https://api.github.com/repos/MoBiodiv/mobr/issues/128/comments","events_url":"https://api.github.com/repos/MoBiodiv/mobr/issues/128/events","html_url":"https://github.com/MoBiodiv/mobr/issues/128","id":207333020,"number":128,"title":"Nonspatial curve and ind-based curve not exactly identical","user":{"login":"rueuntal","id":1157182,"avatar_url":"https://avatars.githubusercontent.com/u/1157182?v=3","gravatar_id":"","url":"https://api.github.com/users/rueuntal","html_url":"https://github.com/rueuntal","followers_url":"https://api.github.com/users/rueuntal/followers","following_url":"https://api.github.com/users/rueuntal/following{/other_user}","gists_url":"https://api.github.com/users/rueuntal/gists{/gist_id}","starred_url":"https://api.github.com/users/rueuntal/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/rueuntal/subscriptions","organizations_url":"https://api.github.com/users/rueuntal/orgs","repos_url":"https://api.github.com/users/rueuntal/repos","events_url":"https://api.github.com/users/rueuntal/events{/privacy}","received_events_url":"https://api.github.com/users/rueuntal/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2017-02-13T20:40:37Z","updated_at":"2017-02-14T02:05:52Z","closed_at":null,"body":"@dmcglinn @ngotelli This is kind of a nuance but I'd love to hear what folks think. If we think about the nonspatial curve as being created by randomly shuffling the individuals across plots, then the two curves are only exactly identical when all plots within the treatment have exactly the same abundance (density). The more \"uneven\" they are in abundance, the more divergence we'd see in the two types of calculations. \r\n\r\nConsider the following extreme example - a treatment with three species and two plots, c(100, 100, 100) and c(1, 0, 0). No matter how we reshuffle the individuals, plot 1 would always have three species while plot 2 would always have 1. So the expected S at plot = 1 for the nonspatial curve is 2:\r\n```\r\nmean(c(rarefaction(c(101, 100, 100), 'indiv', c(1, 300))))\r\n```\r\nHowever, calculated from the ind-based curve, the expected abundance for plot = 1 is 150 or 151, and \r\n```\r\nrarefaction(c(101, 100, 100), 'indiv', 150)\r\n```\r\nis 3. \r\n\r\n"},"comment":{"url":"https://api.github.com/repos/MoBiodiv/mobr/issues/comments/279585686","html_url":"https://github.com/MoBiodiv/mobr/issues/128#issuecomment-279585686","issue_url":"https://api.github.com/repos/MoBiodiv/mobr/issues/128","id":279585686,"user":{"login":"dmcglinn","id":1190381,"avatar_url":"https://avatars.githubusercontent.com/u/1190381?v=3","gravatar_id":"","url":"https://api.github.com/users/dmcglinn","html_url":"https://github.com/dmcglinn","followers_url":"https://api.github.com/users/dmcglinn/followers","following_url":"https://api.github.com/users/dmcglinn/following{/other_user}","gists_url":"https://api.github.com/users/dmcglinn/gists{/gist_id}","starred_url":"https://api.github.com/users/dmcglinn/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dmcglinn/subscriptions","organizations_url":"https://api.github.com/users/dmcglinn/orgs","repos_url":"https://api.github.com/users/dmcglinn/repos","events_url":"https://api.github.com/users/dmcglinn/events{/privacy}","received_events_url":"https://api.github.com/users/dmcglinn/received_events","type":"User","site_admin":false},"created_at":"2017-02-14T02:05:52Z","updated_at":"2017-02-14T02:05:52Z","body":"Above you say;\r\n\r\n>If we think about the nonspatial curve as being created by randomly shuffling the individuals across plots, then the two curves are only exactly identical when all plots within the treatment have exactly the same abundance (density).\r\n\r\nWhich two curves are you referring to?\r\n\r\nI understand `rarefaction(c(101, 100, 100), 'indiv', 150)` where 150 is the mean number of individuals in a plot but I don't understand `mean(c(rarefaction(c(101, 100, 100), 'indiv', c(1, 300))))` can you walk me through how you came up with that, thanks!\r\n"}}
{"actor":{"display_login":"dmcglinn"}}