Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate amounts of water.
Also, the trade-off in the filter spacing remains unexplored, despite its simple formulation: A filter too coarse will allow suitably sized prey to pass unintercepted, whereas a filter too fine will cause strong flow resistance.
We quantify the feeding flow of the filter-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates.
Both approaches underestimate observed filtration rates by more than an order of magnitude; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox.
Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), something notoriously difficult to visualize but sporadically observed in the related choanocytes (sponges).
A CFD model with a flagellar vane correctly predicts the filtration rate of D. grandis, and using a simple model we can account for the filtration rates of other microbial filter feeders.
We finally predict how optimum filter mesh size increases with cell size in microbial filter feeders, a prediction that accords very well with observations. We expect our results to be of significance for small-scale biophysics and trait-based ecological modeling.
Development of a microbial test suite and data integration method for assessing microbial health of contaminated soil.
There is no standard methodology or guideline for assessing soil microbial health for the purposes of contaminant risk assessments. Here we propose a laboratory-based test suite and novel data integration method for evaluating soil microbial health using site-specific contaminated and reference soil.
The test suite encompasses experiments for evaluating microbial biomass, activity, and diversity. The results from the tests are then integrated so that a Soil Microbial Health Score (SMHS) may be assigned.
This test suite and data integration method was tested on soils from 3 different contaminated sites in Canada. The soil microbial health of a petroleum hydrocarbon (PHC) contaminated site was found to be ‘Mildly Impacted’ and ‘Moderately Impacted’ for two soil horizons at a boreal forest site.
The soil microbial health of the mixed metal/PHC and mixed metal sites were both found to be ‘Not Impacted’. Continued use of this test suite and data integration method will help create guidelines for assessing soil microbial health in ecological risk assessments.