@article{
 title = {Null model analysis of species co-occurrence patterns},
 type = {article},
 year = {2000},
 identifiers = {[object Object]},
 keywords = {Monte Carlo simulation,assembly rules,checkerboard distribution,co-occurrence,coexistence,community structure,competition,null model,presence–absence matrix,randomization test,species combinations},
 pages = {2606-2621},
 volume = {81},
 websites = {http://www.esajournals.org/doi/abs/10.1890/0012-9658(2000)081[2606:NMAOSC]2.0.CO;2},
 month = {9},
 day = {11},
 id = {59055551-a505-3a81-a6d1-4e37e302188d},
 created = {2015-09-18T15:33:47.000Z},
 accessed = {2015-09-18},
 file_attached = {false},
 profile_id = {a62f6426-dbc3-3650-9707-e4d7e7b16a25},
 group_id = {12e8e32d-35d4-383c-84bf-15a1caa83291},
 last_modified = {2015-10-06T20:32:51.000Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Gotelli2000},
 language = {EN},
 abstract = {The analysis of presence–absence matrices with “null model” randomization tests has been a major source of controversy in community ecology for over two decades. In this paper, I systematically compare the performance of nine null model algorithms and four co-occurrence indices with respect to Type I and Type II errors. The nine algorithms differ in whether rows and columns are treated as fixed sums, equiprobable, or proportional. The three models that maintain fixed row sums are invulnerable to Type I errors (false positives). One of these three is a modified version of the original algorithm of E. F. Connor and D. Simberloff. Of the four co-occurrence indices, the number of checkerboard combinations and the number of species combinations may be prone to Type II errors (false negatives), and may not reveal significant patterns in noisy data sets. L. Stone and A. Robert's checkerboard score has good power for detecting species pairs that do not co-occur together frequently, whereas D. Schluter's V ratio r...},
 bibtype = {article},
 author = {Gotelli, Nicholas J.},
 journal = {Ecology},
 number = {9}
}

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