ABSTRACT
Several theoretical models have been proposed as the underlying mechanisms behind occupancy frequency distribution (OFD) patterns. For instance, the metapopulation dynamic model predicts bimodal OFD pattern indicating the dominance of dispersal processes in structuring the assemblages, while the niche-based model predicts unimodal right-skewed OFD pattern, and thus assemblages are driven mostly by niche processes. However, it is well known that the observed OFD pattern reflects the interplay of several other factors (e.g. habitat heterogeneity, species specificity and sampling protocol parameters). It follows that the individual contribution of each factor to the OFD pattern is rather complicated to explore. Our main objective was to examine the role of the spatial extent of the sampling and the dispersal strategies of species in shaping OFD pattern. For this, we collected samples of stream insect assemblages inhabiting near-natural streams in the Pannon Ecoregion. We formed groups of species representing contrasting dispersal strategies (referred to as dispersal groups). Applying a computer program algorithm, we produced samples with different spatial extent. We found that with increasing spatial extent, the OFD pattern changed from bimodal to unimodal for active dispersers. Insect groups with different dispersal strategies differed in the strength of support for OFD patterns within all spatial extent. Furthermore, the strength of support for OFD patterns varied across dispersal groups differently as the spatial extent increased. Our results reflected underlying changes in mechanisms structuring assemblages along an increasing spatial extent. We also assumed that the stream insect dispersal strategy influences the relative role of dispersal and niche processes particularly as spatial extent increases from stream reaches to the extent of adjacent valleys. We could define spatial extents and dispersal strategies within which unique metacommunity processes could underlie the organisation of assemblages.
ABSTRACT
Combined partial nitritation-anammox (PN/A) systems are increasingly being employed for sustainable removal of nitrogen from wastewater, but process instabilities present ongoing challenges for practitioners. The goal of this study was to elucidate differences in process stability between PN/A process variations employing two distinct aggregate types: biofilm [in moving bed biofilm reactors (MBBRs)] and suspended growth biomass. Triplicate reactors for each process variation were studied under baseline conditions and in response to a series of transient perturbations. MBBRs displayed elevated NH4+ removal rates relative to those of suspended growth counterparts over six months of unperturbed baseline operation but also exhibited significantly greater variability in performance. Transient perturbations led to strikingly divergent yet reproducible behavior in biofilm versus suspended growth systems. A temperature perturbation prompted a sharp reduction in NH4+ removal rates with no accumulation of NO2- and rapid recovery in MBBRs, compared to a similar reduction in NH4+ removal rates but a high level of accumulation of NO2- in suspended growth reactors. Pulse additions of a nitrification inhibitor (allylthiourea) prompted only moderate declines in performance in suspended growth reactors compared to sharp decreases in NH4+ removal rates in MBBRs. Quantitative fluorescence in situ hybridization demonstrated a significant enrichment of anammox in MBBRs compared to suspended growth reactors, and conversely a proportionally higher AOB abundance in suspended growth reactors. Overall, MBBRs displayed significantly increased susceptibility to transient perturbations employed in this study compared to that of suspended growth counterparts (stability parameter), including significantly longer recovery times (resilience). No significant difference in the maximal impact of perturbations (resistance) was apparent. Taken together, our results suggest that aggregate architecture (biofilm vs suspended growth) in PN/A processes exerts an unexpectedly strong influence on process stability.
