Resilience and high compositional variability reflect the complex response of river waters to global drivers: The Eastern Siberian River Chemistry database.

Climate change Computation methods Environmental geochemistry Permafrost degradation Simplex geometry Variance

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
15 Jan 2024
Historique:
received: 30 08 2023
revised: 20 10 2023
accepted: 23 10 2023
medline: 3 11 2023
pubmed: 3 11 2023
entrez: 2 11 2023
Statut: ppublish

Résumé

The chemical composition of river waters represents an important matter of investigation to understand environment modifications in response to climate changes and global warming. Prolonged dry periods, heavy flood events, degradation of the lands and ice thawing, modify the chemical composition of river waters influencing the drivers governing the complex dynamics of river catchments where everything comes together. In this framework, Compositional Data Analysis (CoDA) offers methods in which the complex structure of the river water composition and the interrelationships among the various components are put into the proper context for their statistical analysis. In this research, we propose a new CoDA approach combining the robust Mahalanobis distance (D) calculus of ilr-transformed chemical variables and the perturbation difference, both with respect to a pristine compositional benchmark. The aim was to trace the change in the chemical composition of the Eastern Siberian River Chemistry Database where degradation of the permafrost for global warming produces important effects on natural waters. The findings indicate complex multiplicative laws and feedback mechanisms governing solutes in Eastern Siberian rivers, with high values of D found where permafrost is more discontinuous. Perturbations clearly discriminate chemical components more resilient to stresses induced by global changes (Ca

Identifiants

pubmed: 37918739
pii: S0048-9697(23)06747-5
doi: 10.1016/j.scitotenv.2023.168120
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

168120

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Caterina Gozzi (C)

University of Florence, Dept. of Earth Sciences, Via G. La Pira 4, 50121 Firenze, Italy; NBFC, National Biodiversity Future Center, Palermo 90133, Italy. Electronic address: caterina.gozzi@unifi.it.

Antonella Buccianti (A)

University of Florence, Dept. of Earth Sciences, Via G. La Pira 4, 50121 Firenze, Italy; NBFC, National Biodiversity Future Center, Palermo 90133, Italy; National Centre for HPC, Big Data and Quantum Computing, PNRR, Italy.

Classifications MeSH