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.
Highlights
One of the Sustainable Development Goals of the 2030 Agenda for Sustainable Development is to ensure the availability and sustainable management of water and sanitation for all and to preserve water quality by reducing pollution [1,2]
In 1978, Hellawell proposed values of tolerance/sensitivity to organic pollution associated with certain families of aquatic macroinvertebrates. He established that water quality is related to the presence or absence of those families through the sum of their tolerance values, without taking into account the abundance of each taxon; the final score is the so-called and usually applied Biological Monitoring Working Party (BMWP) index [12,13,14]
The geometric representation of a phenomenon associated with an ecological system allowed the study of a topological index to assess water quality
Summary
One of the Sustainable Development Goals of the 2030 Agenda for Sustainable Development is to ensure the availability and sustainable management of water and sanitation for all and to preserve water quality by reducing pollution [1,2]. In 1978, Hellawell proposed values of tolerance/sensitivity to organic pollution associated with certain families of aquatic macroinvertebrates He established that water quality is related to the presence or absence of those families through the sum of their tolerance values, without taking into account the abundance of each taxon; the final score is the so-called and usually applied Biological Monitoring Working Party (BMWP) index [12,13,14]. The fundamental structures of plant or animal communities can be described mathematically [39] In this direction and in order to assess water quality, in [40], the mathematical structure, which is a bipartite network G, was associated with the presence or absence of aquatic macroinvertebrate families and their tolerance value to pollution by means of the topological index. We show that by properly defining a universal curve for the average Shannon entropy of the eigenvectors of the adjacency matrices of the bipartite network G, it is possible to define water quality classes equivalent to those obtained from the topological study of Section 2
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
