Nitrate respiration and diel migration patterns of diatoms are linked in sediments underneath a microbial mat.

Diatoms are among the few eukaryotes known to store nitrate (NO3 - ) and to use it as an electron acceptor for respiration in the absence of light and O2 . Using microscopy and 15 N stable isotope incubations, we studied the relationship between dissimilatory nitrate/nitrite reduction to ammonium (DNRA) and diel vertical migration of diatoms in phototrophic microbial mats and the underlying sediment of a sinkhole in Lake Huron (USA). We found that the diatoms rapidly accumulated NO3 - at the mat-water interface in the afternoon and 40% of the population migrated deep into the sediment, where they were exposed to dark and anoxic conditions for ~75% of the day. The vertical distribution of DNRA rates and diatom abundance maxima coincided, suggesting that DNRA was the main energy generating metabolism of the diatom population. We conclude that the illuminated redox-dynamic ecosystem selects for migratory diatoms that can store nitrate for respiration in the absence of light. A major implication of this study is that the dominance of DNRA over denitrification is not explained by kinetics or thermodynamics. Rather, the dynamic conditions select for migratory diatoms that perform DNRA and can outcompete sessile denitrifiers.

A comparison of relative abundance versus class data in diatom-based quantitative reconstructions.

Relative species abundances are the most frequently applied data type used for modern or paleolimnological diatom studies. In contrast, plant ecologists save time by commonly using ordinal scale data (class data), where the abundance of a species is estimated using dominance classes, instead of relative abundance data. This study compares the performance of models based on ordinal diatom species class data (class 1: sporadic (<0-1%) up to class 6: dominant (>60%)) with similar model types based on relative abundance data for different regional training sets and sediment cores. First, relative diatom abundances were converted into ordinal classes. Species response to total phosphorous (TP) was modelled using both types of data - relative abundance and ordinal class data. Secondly, TP was reconstructed for six sediment cores from North-East Germany, Switzerland, and Denmark using WA and WA-PLS based on both types of data. Thirdly, 20 lake sediment surface samples with known relative diatom abundances and known water TP concentrations were recounted using an ordinal data scale to create an independent test set. No significant differences were found between relative abundance and class data for (1) explained species variance, (2) reconstructed TP values, and (3) inferred TP values of the 20 recounted samples. This approach demonstrates that past TP concentrations may also be reliably reconstructed using class data instead of relative diatom abundances. Thus, by using class data lake managers may not only obtain more long-term records past water quality, but this approach is also quicker and therefore more cost effective. Moreover, the findings of this study may also advance the use of automatic diatom identification with digital image recognition, as we demonstrate that not every damaged diatom valve needs to be identified.