Aquatic macroinvertebrate assemblages in rivers influenced by mining activities

Abstract

Mining is one of the major pollution sources worldwide, causing huge disturbances to the environment. Industrial and artisanal mining activities are widespread in Mexico, a major global producer of various metals. This study aimed to assess the ecological impairments resulting from mining activities using aquatic macroinvertebrates assemblages (MA). A multiple co-inertia analysis was applied to determine the relationships between environmental factors, habitat quality, heavy metals, and aquatic macroinvertebrates in 15 study sites in two different seasons (dry and wet) along two rivers running across the Central Plateau of Mexico. The results revealed three contrasting environmental conditions associated with different MAs. High concentrations of heavy metals, nutrients, and salinity limit the presence of several families of seemingly sensitive macroinvertebrates. These factors were found to influence structural changes in MAs, showing that not only mining activities, but also agriculture and presence of villages in the basin, exert adverse effects on macroinvertebrate assemblages. Diversity indices showed that the lowest diversity matched both the most polluted and the most saline rivers. The rivers studied displayed high alkalinity and hardness levels, which can reduce the availability of metals and cause adverse effects on periphyton by inhibiting photosynthesis and damaging MAs. Aquatic biomonitoring in rivers, impacted by mining and other human activities, is critical for detecting the effect of metals and other pollutants to improve management and conservation strategies. This study supports the design of cost-effective and accurate water quality biomonitoring protocols in developing countries.

Figure 1

Heatmap of diversity indices for the study sites in the SGBR: (a) taxa richness, (b) Shannon exponential index, (c) Inverse Gini-Simpson index, (d) Shannon index. The regional map was generated using the vectorial layers freely available from National Institute of Statistics, Geography and Informatics (https://www.inegi.org.mx/temas/mapadigital) and National Commission of Protected Natural Areas (http://sig.conanp.gob.mx/website/pagsig/info_shape.htm. All layers were processed with the open source software geographic information system QGIS 3.18 (QGIS is open source software available under the terms of the General Public License (GNU) meaning that source codes can be downloaded through tarballs or the git repository). Study site points were downloaded from a hand-held GPS (Monterra^®|Garmin) before being digitized and uploaded as shapefiles. Sampling points and legend layouts were edited using open source software available at: https://inkscape.org. The sampling points show diversity calculated from iNEXT package (; Hsieh, T.C., Ma, K. H. & Chao, A. (2016) iNEXT: An R package for interpolation and extrapolation of species diversity) and processed using R Core Team version 3.1.0. (A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; https://www.R-project.org/).

Figure 2

Scheme showing the streams and rivers of the Sierra Gorda Biosphere Reserve, (a) location of the 15 study sites, (b) mines located in the study area, and (c) zoom of the shaded area. The core zones of the reserve are areas under strict protection where any anthropogenic land use is forbidden. Acronyms identify the various sites as follows: PB  Peña Blanca, EP  El Paraíso, RQ Rancho Quemado, BC Bucareli, ES Escanela, EN  Escanelilla, AH Ahuacatlán, PI Pizquintla, JL Jalpan, PA Purísima de Arista, VC Vegas Cuatas, CN Concá, AY Ayutla, SM Santa María, AT Autopista 190. The map was generated using the vectorial layers freely available from National Institute of Statistics, Geography and Informatics (https://www.inegi.org.mx/temas/mapadigital), National Commission of Protected Natural Areas (http://sig.conanp.gob.mx/website/pagsig/info_shape.htm), and Mexican Geological Survey GEOINFOMEX (https://www.sgm.gob.mx/GeoInfoMexGobMx/). To build the map, all layers were processed with the open source software geographic information system QGIS 3.18 (QGIS is open source software available under the terms of the General Public License (GNU) meaning that its source code can be downloaded through tarballs or the git repository). Study sites points were downloaded from a hand-held GPS (Monterra®|Garmin) before being digitalized and uploaded as a shapefile.

Figure 3

Results of the MCOA: (a) environmental factors resulting from the correlation analysis. Vectors indicate the magnitude of each factor over each taxa block; (b) ordered study sites; (c–j) blocks of contribution (vectors) of aquatic macroinvertebrate taxa (for easier visualization, separate biplots are shown for each taxonomic order). See Appendix for taxa codes. The blocks and MCOA analysis were generated using the ADE4 package (https://cran.r-project.org/web/packages/ade4/index.html; Dray, S. & Dufour, A.-B. 2007. The ade4 Package: Implementing the Duality Diagram for Ecologists) and vegan package (http://cran.r-project.org/;Oksanen, J., Kindt, R., Pierre, L., O’Hara, B., Simpson, G. L., Solymos, P., … Wagner, H. 2016. Vegan: Community Ecology Package, R package version 2.4–0). Images were edited using Inkscape, an open source software available at: https://inkscape.org.