The local-regional species richness relationship: new perspectives on the null-hypothesis
Despite considerable criticism in recent years, the use of local (S L ) and regional species richness (S R ) plots has a long tradition to test for community saturation. The traditional approach has been to compare linear and polynomial regression models of untransformed measures of S L and S R with...
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| Veröffentlicht in: | Oikos 2012-03, Vol.121 (3), p.321-326 |
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| creator | Szava-Kovats, Robert C. Zobel, Martin Pärtel, Meelis |
| description | Despite considerable criticism in recent years, the use of local (S L ) and regional species richness (S R ) plots has a long tradition to test for community saturation. The traditional approach has been to compare linear and polynomial regression models of untransformed measures of S L and S R with a statistically significant linear or polynomial model indicating unsaturated and saturated communities, respectively. This approach has been the target of much controversy owing to statistical issues, the confounding effects of the arbitrary choice for the size of the local and regional area, and the difficulty in attributing ecological processes to the underlying S L — S R pattern. The statistical issues and effects of scale stem from the lack of statistical independence and induced correlation between S L -S R arising from the mathematical constraint, S L |
| doi_str_mv | 10.1111/j.1600-0706.2011.19603.x |
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The traditional approach has been to compare linear and polynomial regression models of untransformed measures of S L and S R with a statistically significant linear or polynomial model indicating unsaturated and saturated communities, respectively. This approach has been the target of much controversy owing to statistical issues, the confounding effects of the arbitrary choice for the size of the local and regional area, and the difficulty in attributing ecological processes to the underlying S L — S R pattern. The statistical issues and effects of scale stem from the lack of statistical independence and induced correlation between S L -S R arising from the mathematical constraint, S L <S R .However, by removing this mathematical constraint by means of a logratio transformation, S L -S R relationships can be calculated using ordinary linear regression and with a logical and definitive null-hypothesis based solely on the presence of a statistically significant slope, which provides a quantitative measure of curvature. Simulations of S L -S R relationships with varying curvature and S L :S R eratio demonstrate that the logratio model can accurately measure curvature independent of the S L :S R ratio. Therefore, the tendency for studies with high local: regional area ratio to result in linear S L -S R trends when analysed by traditional regression methods may be mitigated by reanalysis by the logratio model. 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Psychology</topic><topic>General aspects</topic><topic>Hypothesis testing</topic><topic>Linear regression</topic><topic>Population ecology</topic><topic>Regression analysis</topic><topic>Simulations</topic><topic>Species diversity</topic><topic>Statistical significance</topic><topic>Statistics</topic><topic>Synecology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Szava-Kovats, Robert C.</creatorcontrib><creatorcontrib>Zobel, Martin</creatorcontrib><creatorcontrib>Pärtel, Meelis</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><jtitle>Oikos</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Szava-Kovats, Robert C.</au><au>Zobel, Martin</au><au>Pärtel, Meelis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The local-regional species richness relationship: new perspectives on the null-hypothesis</atitle><jtitle>Oikos</jtitle><addtitle>Oikos</addtitle><date>2012-03</date><risdate>2012</risdate><volume>121</volume><issue>3</issue><spage>321</spage><epage>326</epage><pages>321-326</pages><issn>0030-1299</issn><eissn>1600-0706</eissn><coden>OIKSAA</coden><abstract>Despite considerable criticism in recent years, the use of local (S L ) and regional species richness (S R ) plots has a long tradition to test for community saturation. 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The statistical issues and effects of scale stem from the lack of statistical independence and induced correlation between S L -S R arising from the mathematical constraint, S L <S R .However, by removing this mathematical constraint by means of a logratio transformation, S L -S R relationships can be calculated using ordinary linear regression and with a logical and definitive null-hypothesis based solely on the presence of a statistically significant slope, which provides a quantitative measure of curvature. Simulations of S L -S R relationships with varying curvature and S L :S R eratio demonstrate that the logratio model can accurately measure curvature independent of the S L :S R ratio. Therefore, the tendency for studies with high local: regional area ratio to result in linear S L -S R trends when analysed by traditional regression methods may be mitigated by reanalysis by the logratio model. 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| subjects | Animal and plant ecology Animal, plant and microbial ecology Biodiversity Biological and medical sciences Curvature Ecological modeling Flowers & plants Fundamental and applied biological sciences. Psychology General aspects Hypothesis testing Linear regression Population ecology Regression analysis Simulations Species diversity Statistical significance Statistics Synecology |
| title | The local-regional species richness relationship: new perspectives on the null-hypothesis |
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