Application of Bipartite Networks to the Study of Water Quality

Jair J. Pineda-Pineda, C. T. Martínez-Martínez, J. A. Méndez-Bermúdez, Jesús Muñoz-Rojas and José M. Sigarreta
Additional contact information
Jair J. Pineda-Pineda: Ecology and Survival of Microorganisms Research Group (ESMRG), Laboratorio de Ecología Molecular Microbiana (LEMM), Centro de Investigaciones en Ciencias Microbiológicas (CICM), Instituto de Ciencias (IC), Benemérita Universidad Autónoma de Puebla (BUAP), Puebla 72570, Mexico
C. T. Martínez-Martínez: Instituto de Física, Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico
J. A. Méndez-Bermúdez: Instituto de Física, Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico
Jesús Muñoz-Rojas: Ecology and Survival of Microorganisms Research Group (ESMRG), Laboratorio de Ecología Molecular Microbiana (LEMM), Centro de Investigaciones en Ciencias Microbiológicas (CICM), Instituto de Ciencias (IC), Benemérita Universidad Autónoma de Puebla (BUAP), Puebla 72570, Mexico
José M. Sigarreta: Facultad de Matemáticas, Universidad Autónoma de Guerrero, Acapulco 39650, Mexico

Sustainability, 2020, vol. 12, issue 12, 1-19

Abstract: Water is a basic natural resource for life and the sustainable development of society. Methods to assess water quality in freshwater ecosystems based on environmental quality bioindicators have proven to be low cost, reliable, and can be adapted to ecosystems with well-defined structures. The objective of this paper is to propose an interdisciplinary approach for the assessment of water quality in freshwater ecosystems through bioindicators. From the presence/absence of bioindicator organisms and their sensitivity/tolerance to environmental stress, we constructed a bipartite network, G . In this direction, we propose a new method that combines two research approaches, Graph Theory and Random Matrix Theory (RMT). Through the topological properties of the graph G , we introduce a topological index, called J P ( G ) , to evaluate the water quality, and we study its properties and relationships with known indices, such as Biological Monitoring Working Party ( B M W P ) and Shannon diversity ( H ′ ). Furthermore, we perform a scaling analysis of random bipartite networks with already specialized parameters for our case study. We validate our proposal for its application in the reservoir of Guájaro, Colombia. The results obtained allow us to infer that the proposed techniques are useful for the study of water quality, since they detect significant changes in the ecosystem.

Keywords: water quality; biotic index; topological index; bipartite network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/12/5143/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/12/5143/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:12:p:5143-:d:375632

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().