Responses of benthic diatoms to waters affected by post-fire contamination

2021 
Abstract Wildfire effects go beyond direct impact in terrestrial ecosystems. Specifically, the periphytic communities of aquatic ecosystems standing within and downstream the burnt areas are relevant ecological receptors of post-fire runoff contamination. Nevertheless, the off-site impacts of wildfires in these communities are limitedly studied so far. The present study aimed to assess the effects of river water contaminated with ash-loaded runoff in the growth benthic diatom Navicula libonensis (Schoeman 1970). Four surface water samples were collected approximately one year after the wildfire for laboratory testing with the diatom: one was collected from a site upstream the burnt area, within the Unhais river (UU); three were collected from sites standing within the burnt area, one in the Unhais river (UB) and two in the Zezere river (Z1 and Z2), reflecting different hydrological regimes. N. libonensis was proven able to discriminate among river sites affected and unaffected by wildfire runoff, reflecting, in general, the expected trends considering the physico-chemical characterization of the water samples. The water samples from the sites standing within the burnt area inhibited the biomass yield and growth rate of the tested diatom, ranking the samples regarding toxicity as follows: Z1 > UB > Z2 > UU. However, UB rather than Z1 presented the highest contaminant burden, namely metal elements, and some were found above widely accepted safety benchmarks (polycyclic aromatic hydrocarbons were not detected). This inconsistency can be linked to unknown interactions among metals within each water sample, to differential nutrient enrichment of samples, as well as hydrological factors. Overall, our results suggest that monospecific laboratory assays with sensitive diatoms can be valuable as cost-effective screening tools to prioritize sites affected by wildfires runoff requiring in-depth monitoring of negative effects in benthic producer communities.
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