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In the present study,the interplay and higher-order terms of environmental and spatial variables areconsidered to evaluate the relations of environment and space-species richnessrankings at global scale. Three taxonomic groups composed of mammals, birds andamphibians were analyzed for the study. Thek-meansclustering method was introduced for richness rankings detection and analysisfrom published digital maps; and simple regression analysis and AIC criteria wereused for identifying mostimportant correlated explanatory variables.When comparing eachsingle variable, I found that latitude was the most important one influencingglobal vertebrate richness rankings. When onlyconsidering environmental variables, I foundthatprecipitation was the only predictor of vertebrate richness rankings. However,when the interaction and high-order terms of different independent variableswere considered, it was found that the interaction between latitude and temperaturecould better explain the global bird richness ranking, while the second-powereffectof latitude wasthe best predictor for amphibianand mammalian richness rankings, as evidenced bythe AIC model selection and comparison among the regression models. In conclusion,the inclusion of high-order and interaction terms of environmental and spatialvariables could offer more insights into the understanding of global speciesdiversity patterns.

KEYWORDS

Global Species Distribution; Nonlinearity; Richness Ranking; Diversity Mapping; Environment Envelope

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Chen, Y. 2013 Global environment- and space-richness ranking relationships: The effects of interaction and high-order terms of explanatory variables. Open Journal of Ecology, 3, 389-394. doi: 10.4236-oje.2013.36044.





Author: Youhua Chen

Source: http://www.scirp.org/



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