Assessing anthropogenic impacts on riverine ecosystems using nested partial least squares regression

The results of three Partial Least Squares (PLS) regression models were used to gain a holistic view on the consequences of natural processes and anthropogenic pressures for water quality degradation and biodiversity decline in a multi-use watershed. The processes were soil erosion and wildfire risk; the pressures comprised land use conflicts, leachates from domestic and industrial waste, arable farming intensity and livestock density. Water quality was characterized for concentrations of nutrients (nitrate, phosphate), oxygen demands (Biochemical Oxygen Demand - BOD5, Chemical Oxygen Demand - COD) and various metals (e.g., As, Cr). Ecological integrity was assessed by the recently developed MELT (Multiple Ecological Level Index). In total, 18 variables were processed in the regression models. Two models were called nested models because they dealt with initial (pressures), intermediate (water quality) and final (MELI) environmental descriptors, used as dependent (MELI, quality) or independent (quality, pressures) variables. The third was called bypass model because it dealt solely with initial and final descriptors. Overall, the results of PLS regression linked the ineffective treatment of domestic sewage to water quality and ecological integrity declines in the studied watershed. Put another way, all models recurrently affirmed the major role of local factors, meaning of point source pollution, in determining the quality of stream water and the integrity of freshwater ecosystems. Sources of diffuse pollution were accounted for as contributing factors in the PLS regressions, but their influence was scarcely perceptible in the results. The poor treatment of domestic effluents is a public concern. In their strategic plans for mitigating this problem in the forthcoming years, administrative authorities are concentrated on management initiatives to improve the quality of provided services, instead of considering the construction of new wastewater treatment plants. (C) 2017 Elsevier B.V. All rights reserved.