Abstract

River biofilm communities are the first ones to be exposed to all toxic discharges received via run off from agricultural fields. Hence, changes in river biofilm community structure and growth pattern are considered as indicator of overall health of lotic ecosystem. Toxicants have effect on biofilm biomass, photosynthetic efficiency and chlorophyll a concentrations. Mathematical models may be applied to estimate the overall vigor of riverine ecosystems considering biofilms as indicators. Herein, previous empirical data of Ricart et al. (2009) on long term effects of environmentally relevant concentrations of diuron on biofilm communities of the River Llobregat, Spain was considered as our model inputs. Our objective is to understand the influence of diuron, chlorophyll a concentrations and photosynthetic efficiency on biovolume using a statistical model. The non-linear relationships between biovolume (dependent variable) and diuron, chlorophyll a concentrations and photosynthetic efficiency (independent variables) were represented by constructing three separate basis functions based on day 8 empirical data. Biovolume, due to nonlinear influence as yielded by the basis functions were used in a multiple linear regression model to estimate the net biovolume. Model validation was done based on day 29 empirical data. The experimentally determined biovolume and our model estimated biovolume showed similar trends. Also, diuron and photosynthetic efficiency had significant (p < 0.05) influence on biovolume. Since, the predominance of diatoms as biofilms within periphytic layers is very common in lotic systems, estimation of changes in diatom biovolume will be significant to assess the effect of herbicides. Diatom biovolume of any day (for example day 22) mentioned in the experimental study may be determined by this model, without the requirement of tedious manual biovolume calculation. Our model will be useful in numerous other studies undertaken on the toxic effect of pollutants on biofilms to quickly and accurately estimate the biofilm biovolume.

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