2016
DOI: 10.3390/jmse4030063
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Uncovering Spatio-Temporal and Treatment-Derived Differences in the Molecular Physiology of a Model Coral-Dinoflagellate Mutualism with Multivariate Statistical Approaches

Abstract: In light of current global climate change forecasts, there is an urgent need to better understand how reef-building corals respond to changes in temperature. Multivariate statistical approaches (MSA), including principal components analysis and multidimensional scaling, were used herein to attempt to understand the response of the common, Indo-Pacific reef coral Seriatopora hystrix to temperature changes using data from laboratory-based temperature challenge studies performed in Southern Taiwan. S. hystrix and… Show more

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Cited by 11 publications
(6 citation statements)
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“…Although a Bonferroni adjustment may suffice in controlling for type I statistical errors, MSA can uncover relationships amongst response variables that are not evident from univariate-based statistics alone, while doing so at a lower false positive error rate [ 32 ]. Several MSA were taken herein to understand the relationship between environment and coral physiology.…”
Section: Methodsmentioning
confidence: 99%
“…Although a Bonferroni adjustment may suffice in controlling for type I statistical errors, MSA can uncover relationships amongst response variables that are not evident from univariate-based statistics alone, while doing so at a lower false positive error rate [ 32 ]. Several MSA were taken herein to understand the relationship between environment and coral physiology.…”
Section: Methodsmentioning
confidence: 99%
“…With these physiological data in hand (summarized in Table 1 ), a global team of researchers from Taiwan, the United States, the United Kingdom, Canada, Australia, and elsewhere has spent the past decade attempting to gain a better understanding of how these, as well as other Southern Taiwanese coral-dinoflagellate endosymbioses (namely Pocillopora acuta and Stylophora pistillata ) from oceanographically distinct environments, acclimate to changes in temperature in the laboratory [ 23 , 24 , 25 , 26 , 27 ], as well as acclimatize to such environmental heterogeneity and perturbation in the field [ 28 ]. As part of these efforts, it was found that variable temperature exposure can thermally harden corals to where they better withstand future increases in temperature [ 29 ], a finding later corroborated by other researchers [ 30 ].…”
Section: Introductionmentioning
confidence: 99%
“…Briefly, both univariate and multivariate statistical approaches were exploited because it was hypothesized that statistically significant, biologically meaningful differences in molecular physiology might not be identified using only the former strategy. For instance, MANOVA can identify combinations of response variables that best partition samples from different environments, even when the underlying response variables show no environmental variation when analyzed in isolation with ANOVA [ 35 ]. JMP (ver.…”
Section: Methodsmentioning
confidence: 99%