TY - JOUR
T1 - An improved method for assessing the degree of geochemical similarity (DOGS2) between samples from multi-element geochemical datasets
AU - de Caritat, P.
AU - Mann, A.
N1 - Publisher Copyright:
© 2018 Commonwealth of Australia (Geoscience Australia).
PY - 2019/2/1
Y1 - 2019/2/1
N2 - The multi-element aqua regia National Geochemical Survey of Australia (NGSA) database is used to demonstrate an improved method for quantifying the degree of geochemical similarity (DOGS2) between soil samples. The improvements introduced here address issues relating to compositional data (closure, relative scale). After removing the elements with excessive censored (below detection) values, the rank-based Spearman correlation coefficient (rs ) between samples is calculated for the remaining 51 elements. Each element is given equal weight through the rank-based correlation. The rs values for pairs of samples of known similar origin (e.g. granitoid-derived) are significantly positive, whereas they are significantly negative for pairs of samples of known dissimilar origin (e.g. granitoid-v. greenstone-derived). Maps of rs for all samples in the database against various reference samples are used to obtain correlation maps for lithological derivations. Likewise, the distribution of soils having a geochemical fingerprint similar to established mineralized provinces can be mapped, providing a simple, first order mineral prospectivity tool. Sensitivity of results to the removal of up to a dozen elements from the correlation indicates the method to be extremely robust. The new method is compliant with contemporary compositional data analysis principles and is applicable to various digestion methods.
AB - The multi-element aqua regia National Geochemical Survey of Australia (NGSA) database is used to demonstrate an improved method for quantifying the degree of geochemical similarity (DOGS2) between soil samples. The improvements introduced here address issues relating to compositional data (closure, relative scale). After removing the elements with excessive censored (below detection) values, the rank-based Spearman correlation coefficient (rs ) between samples is calculated for the remaining 51 elements. Each element is given equal weight through the rank-based correlation. The rs values for pairs of samples of known similar origin (e.g. granitoid-derived) are significantly positive, whereas they are significantly negative for pairs of samples of known dissimilar origin (e.g. granitoid-v. greenstone-derived). Maps of rs for all samples in the database against various reference samples are used to obtain correlation maps for lithological derivations. Likewise, the distribution of soils having a geochemical fingerprint similar to established mineralized provinces can be mapped, providing a simple, first order mineral prospectivity tool. Sensitivity of results to the removal of up to a dozen elements from the correlation indicates the method to be extremely robust. The new method is compliant with contemporary compositional data analysis principles and is applicable to various digestion methods.
KW - Aqua regia digestion
KW - Compositional data analysis
KW - Geochemical signature
KW - National geochemical survey of Australia
KW - Ranking
KW - Spearman correlation
UR - http://www.scopus.com/inward/record.url?scp=85061270324&partnerID=8YFLogxK
U2 - 10.1144/geochem2018-021
DO - 10.1144/geochem2018-021
M3 - Article
SN - 1467-7873
VL - 19
SP - 58
EP - 73
JO - Geochemistry: Exploration, Environment, Analysis
JF - Geochemistry: Exploration, Environment, Analysis
IS - 1
ER -