Can people detect the loss of water quality? A field experiment to evaluate the correlation between visual perception and water eutrophication degree

Abstract

Aim The quantity and quality of water are essential to many ecosystem services, biodiversity and human well-being. In the present paper, we used a field experiment to evaluate the visual perception of the public regarding the loss of water quality associated with eutrophication and greening of water. We hypothesized that with an increase in eutrophication (i.e. greening of water due to increased Chlorophyll-a), people can detect a loss of water quality and threats to ecosystem services. Methods We used an experimental area composed of six mesocosms (500L water tanks) with a gradient of chlorophyll-a varying from clear water (without chlorophyll-a) up to eutrophic mesocosms (very green water). A total of 100 people visited the experimental area in-situ, and 83 people visualized pictures of the mesocosms. Results Our results indicated that people were able to detect the loss of water quality associated with increased concentrations of chlorophyll-a, and recognized that these were less suitable for recreational activity and consumption. Moreover, this perception did not vary by gender, formal education, or frequency of visits to aquatic ecosystems. Conclusions The results highlight the clear potential of visual public perception to be used as a simple, rapid, early-warning strategy for monitoring programs of water quality and also an approach that strengthens the link between science and society.

La importancia de usar el biovolumen en estudios de fitoplancton y monitoreo ambiental de cianobacterias

“…Más recientemente, el uso de sensores remotos se ha extendido como herramienta de monitoreo para cuerpos de agua límnicos afectados por floraciones de cianobacterias, utilizando algoritmos para estimar la concentración de la clorofila a y la ficocianina a partir del análisis de imágenes satelitales (Mishra and Mishra 2014;Maciel et al 2022;Pamula et al 2023;Zabaleta et al 2023). Otros métodos en desarrollo incluyen aplicaciones para teléfonos inteligentes, basadas en niveles de color del agua (Mitroi et al 2020), o incluso el monitoreo visual involucrando a la población en monitoreos participativos (Bazán et al 2020;Nabout et al 2022).…”