Worldwide, it is acknowledged that changes of land use influence water quality; however, in tropical forests, the relationship between land use and water quality is still poorly understood. This study assessed spatial and seasonal variations in water quality, and the relationship between water quality and changes of land use in the Bobos-Nautla River, whose upper course runs across a patch of a tropical cloud forest. Spatial and seasonal variations in water quality and land use were assessed with multivariate tools. A cluster analysis, as well as a Principal Component Analysis (PCA-3D), identified three groups of sites: (1) an upper portion, which showed the best water quality and the broadest natural vegetation coverage; (2) a middle course, with high nitrogen and phosphorus concentrations associated with extensive agricultural uses; and (3) a lower course, characterized by the highest levels of total and fecal coliforms, as well as ammonia nitrogen, associated with the highest percentage of urbanization and human settlements. Our findings demonstrate the impact of changes of land use on water quality of rivers running through cloud forests in tropical zones, which are currently endangered ecosystems.

The Lake of Texcoco is a closed basin with soils that confer salinity, conductivity, and alkalinity to it. It has undergone a reduction in size, incorporation of wastewater, and short-term desiccation, and includes temporary wetlands interconnected during the rainy season, some of which receive treated wastewater. Sediments contain metals, thus affecting water quality. Five artificial lakes were studied, and 12 metals (As, Ba, Cd, Cu, Cr, Fe, Mg, Mn, Hg, Ni, Pb, and Zn) were monitored bimonthly in water and sediments from June 2015 to March 2018. The Metal Pollution Index (MPI) and the Distribution Coefficient (Kd) were computed. Fe and Cd were the most and least stable metals in sediments, respectively (mean Log(Kd) = 4.24 and 2.079). Based on Log(K d ), metals were ranked as Fe > Mn > Zn > Cu > Mg > Cr > Ni > Ba > Pb > Hg > As > Cd. Log(K d ) values < 3 and > 5 indicate that metals occur mainly in water and sediments, respectively. The Mean Distribution Coefficient Log(K d MPI ) is a novel index proposed to assess ecological risk from metals in a water body. This index allows determining the phase (liquid or solid) where metals predominate, negatively affecting either free-swimming or benthic organisms. Log(K d MPI ) values indicated that metals occur primarily in the liquid phase in all lakes studied.Water 2020, 12, 29 2 of 20 of metals derived from anthropogenic sources such as urban, agricultural, and industrial areas are discharged into aquatic environments [5], then transported through the water column and accumulated in sediments, thus posing an ecological risk to benthic organisms, fish, and other aquatic organisms, and ultimately affecting humans [8,12].Lakes are among the most vulnerable and fragile aquatic ecosystems, because they function as sinks for a wide range of dissolved and particulate substances [13]. Sediments are essential components of lakes, providing food for benthic organisms and accumulating multiple pollutants such as pesticides; additionally, sediments are the most important reservoirs of metals in aquatic systems [1,10,14]. Over the past three decades, metals in water and sediments of freshwater ecosystems have been the focus of interest of several researchers [15][16][17]. Therefore, the development of evaluation methods to monitor metal pollution is essential.

The Tehuacán-Cuicatlán Biosphere Reserve (TCBR), the southernmost semi-arid zone of North America, includes two dryland streams, the Río Salado (RS) and Río Grande (RG); it is surrounded by high vegetation diversity, a cacti diversification center, and the densest columnar cacti forest worldwide. However, no scientific knowledge is currently available on these dryland streams. We evaluated water quality, its relationship with the local geological characteristics, land uses, and the composition of aquatic macroinvertebrates (AM), analyzing their bioindicator potential. These results were discussed in relation to climate change predictions. The RS showed higher mineralization, salinity, hardness, water and air temperature, and low water quality index (WQI), relative to the RG. A discriminant analysis showed spatial (mineralization, salinity, and hardness in the RS) and temporal patterns (higher nitrogen compounds and temperature in the rainy season). The RS showed a lower AM diversity (40 taxa) compared to the RG (73 taxa); Ephemeroptera-Plecoptera-Trichoptera reached higher values in the RG. A co-inertia analysis identified five groups of sites with different AM assemblages and water quality characteristics. Climate change predictions for the TCBR suggest increased aridity, higher temperature, and lower rainfall, leading to reduced river flow and increased salinity and mineralization. These could alter habitat features and connectivity, with loss of AM diversity, highlighting the vulnerability of these unique ecosystems to climate change.