2013
DOI: 10.1002/ggge.20038
|View full text |Cite
|
Sign up to set email alerts
|

The mean composition of ocean ridge basalts

Abstract: [1] The mean composition of mid-ocean ridge basalts (MORB) is determined using a global data set of major elements, trace elements, and isotopes compiled from new and previously published data. A global catalog of 771 ridge segments, including their mean depth, length, and spreading rate enables calculation of average compositions for each segment. Segment averages allow weighting by segment length and spreading rate and reduce the bias introduced by uneven sampling. A bootstrapping statistical technique provi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

18
317
3

Year Published

2014
2014
2015
2015

Publication Types

Select...
6

Relationship

1
5

Authors

Journals

citations
Cited by 140 publications
(343 citation statements)
references
References 20 publications
18
317
3
Order By: Relevance
“…The global database of MORB compositions I statistically interrogate for evidence of CMC is that compiled by Gale et al (2013), which has been carefully curated to mitigate the effects of inter-lab biases, duplicate analyses and off-axis samples. Removing duplicate analyses is particularly important when studying the length scales at which local geochemical patterns emerge from global systematics, because the presence of duplicates will artificially create chemical similarity between samples over short distances.…”
Section: The Datasetmentioning
confidence: 99%
See 4 more Smart Citations
“…The global database of MORB compositions I statistically interrogate for evidence of CMC is that compiled by Gale et al (2013), which has been carefully curated to mitigate the effects of inter-lab biases, duplicate analyses and off-axis samples. Removing duplicate analyses is particularly important when studying the length scales at which local geochemical patterns emerge from global systematics, because the presence of duplicates will artificially create chemical similarity between samples over short distances.…”
Section: The Datasetmentioning
confidence: 99%
“…Removing duplicate analyses is particularly important when studying the length scales at which local geochemical patterns emerge from global systematics, because the presence of duplicates will artificially create chemical similarity between samples over short distances. The Gale et al (2013) dataset has also been filtered for data quality based on canonical trace element ratios. Although this filtering, if too severe, could potentially remove some of the signal of mantle derived variability required to track magma mixing, subsequent analysis will show there is still abundant geochemical variability to track CMC.…”
Section: The Datasetmentioning
confidence: 99%
See 3 more Smart Citations