Water Chemistry: Are New Challenges Possible from CoDA (Compositional Data Analysis) Point of View?

John Aitchison died in December 2016 leaving behind an important inheritance: to continue to explore the fascinating world of compositional data. However, notwithstanding the progress that we have made in this field of investigation and the diffusion of the CoDA theory in different researches, a lot of work has still to be done, particularly in geochemistry. In fact most of the papers published in international journals that manage compositional data ignore their nature and their consequent peculiar statistical properties. On the other hand, when CoDA principles are applied, several efforts are often made to continue to consider the log-ratio transformed variables, for example the centered log-ratio ones, as the original ones, demonstrating a sort of resistance to thinking in relative terms. This appears to be a very strange behavior since geochemists are used to ratios and their analysis is the base of the experimental calibration when standards are evolved to set the instruments. In this chapter some challenges are presented by exploring water chemistry data with the aim to invite people to capture the essence of thinking in a relative and multivariate way since this is the path to obtain a description of natural processes as complete as possible.

[1]  A. Lima,et al.  Measuring the change under compositional data analysis (CoDA): Insight on the dynamics of geochemical systems , 2017, Journal of Geochemical Exploration.

[2]  I. Prigogine,et al.  Exploring Complexity: An Introduction , 1989 .

[3]  M. Engle,et al.  The isometric log-ratio (ilr)-ion plot: A proposed alternative to the Piper diagram , 2018, Journal of Geochemical Exploration.

[4]  V. Pawlowsky-Glahn,et al.  Modelling and Analysis of Compositional Data: Pawlowsky-Glahn/Modelling and Analysis of Compositional Data , 2015 .

[5]  M. Bayani Cardenas,et al.  Surface water‐groundwater interface geomorphology leads to scaling of residence times , 2008 .

[6]  V. Pawlowsky-Glahn,et al.  Exploring Compositional Data with the CoDa-Dendrogram , 2011 .

[7]  M. Engle,et al.  Interpretation of Na–Cl–Br Systematics in Sedimentary Basin Brines: Comparison of Concentration, Element Ratio, and Isometric Log-ratio Approaches , 2012, Mathematical Geosciences.

[8]  M. Engle,et al.  Geochemical evolution of produced waters from hydraulic fracturing of the Marcellus Shale, northern Appalachian Basin: A multivariate compositional data analysis approach , 2014 .

[9]  Andrew J. E. Seely,et al.  Fractal variability: an emergent property of complex dissipative systems. , 2012, Chaos.

[10]  P. Guttorp,et al.  Statistical Interpretation of Species Composition , 2001 .

[11]  V. Pawlowsky-Glahn,et al.  Compositional data analysis as a robust tool to delineate hydrochemical facies within and between gas‐bearing aquifers , 2016 .

[12]  M. Cardenas,et al.  Groundwater flow, transport, and residence times through topography‐driven basins with exponentially decreasing permeability and porosity , 2010 .

[13]  K. Pearson Mathematical contributions to the theory of evolution.—On a form of spurious correlation which may arise when indices are used in the measurement of organs , 1897, Proceedings of the Royal Society of London.

[14]  M. Engle,et al.  Linking compositional data analysis with thermodynamic geochemical modeling: Oilfield brines from the Permian Basin, USA , 2014 .

[15]  V. Pawlowsky-Glahn,et al.  Compositional data analysis : theory and applications , 2011 .

[16]  S. Carpenter,et al.  Anticipating Critical Transitions , 2012, Science.

[17]  S. Carpenter,et al.  Resilience indicators: prospects and limitations for early warnings of regime shifts , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[18]  Axel Kleidon,et al.  Life, hierarchy, and the thermodynamic machinery of planet Earth. , 2010, Physics of life reviews.

[19]  W. E. Scott,et al.  Seismic and acoustic recordings of an unusually large rockfall at Mount St. Helens, Washington , 2008 .

[20]  S. Carpenter,et al.  Early-warning signals for critical transitions , 2009, Nature.

[21]  A. Buccianti,et al.  Weathering reactions and isometric log-ratio coordinates: Do they speak to each other? , 2016 .

[22]  A. Buccianti,et al.  Metric concepts and implications in describing compositional changes for world river's water chemistry , 2011, Comput. Geosci..

[23]  John G. Holden,et al.  A fractal approach to dynamic inference and distribution analysis , 2013, Front. Physio..

[24]  V. Pawlowsky-Glahn,et al.  Groups of Parts and Their Balances in Compositional Data Analysis , 2005 .

[25]  S. Shvartsev Water-Rock Interaction: Implications for the Origin and Program of Global Evolution , 2013 .

[26]  Michael Mitzenmacher,et al.  A Brief History of Generative Models for Power Law and Lognormal Distributions , 2004, Internet Math..

[27]  R. Goebel,et al.  Local Discriminability Determines the Strength of Holistic Processing for Faces in the Fusiform Face Area , 2013, Front. Psychology.

[28]  S. Shvartsev Self-organizing Abiogenic Dissipative Structures in the Geologic History of the Earth , 2009 .

[29]  Zaihua Liu,et al.  ATMOSPHERIC CO2 SINK:SILICATE WEATHERING OR CARBONATE WEATHERING , 2011 .

[30]  Jesús Carrera,et al.  Coupling of mass transfer and reactive transport for nonlinear reactions in heterogeneous media , 2010 .

[31]  Lei Dai,et al.  Relation between stability and resilience determines the performance of early warning signals under different environmental drivers , 2015, Proceedings of the National Academy of Sciences.

[32]  N. Fisher,et al.  Statistical Analysis of Circular Data , 1993 .

[33]  V. Pawlowsky-Glahn,et al.  New Perspectives on Water Chemistry and Compositional Data Analysis , 2005 .

[34]  Vera Pawlowsky-Glahn,et al.  Balance-dendrogram. A new routine of CoDaPack , 2008, Comput. Geosci..

[35]  David Brusi,et al.  Nitrate pollution of groundwater; all right…, but nothing else? , 2016, The Science of the total environment.

[36]  A. Khandoker,et al.  Cardiac rehabilitation outcomes following a 6-week program of PCI and CABG Patients , 2013, Front. Physiol..

[37]  John G. Holden,et al.  The Self-Organization of a Spoken Word , 2012, Front. Psychology.

[38]  C. Allègre,et al.  Scaling laws and geochemical distributions , 1995 .

[39]  G. Mateu-Figueras,et al.  Isometric Logratio Transformations for Compositional Data Analysis , 2003 .

[40]  B. Raco,et al.  Towards the Concept of Background/baseline Compositions: A Practicable Path? , 2015 .

[41]  F. Chayes On correlation between variables of constant sum , 1960 .

[42]  V. Pawlowsky-Glahn,et al.  Geometric approach to statistical analysis on the simplex , 2001 .