Winter is coming: food web structure and seasonality in a subtropical freshwater coastal-lake

Indexación: Web of Science; Scopus.Food web studies provide a useful tool to assess the organization and complexity of natural communities. Nevertheless, the seasonal dynamics of food web properties, their environmental correlates, and potential association with community diversity and stability remain poorly studied. Here, we condensed an incomplete 6-year community dataset of a subtropical coastal lake to examine how monthly variation in diversity impacts food web structure over an idealized time series for an averaged year. Phytoplankton, zooplankton, macroinvertebrates, and fish were mostly resolved to species level (n = 120 trophospecies). Our results showed that the seasonal organization of the food web could be aggregated into two clusters of months grouped here as ‘summer’ and ‘winter’. During ‘winter’, the food web decreases in size and complexity, with the number of trophospecies dropping from 106 to 82 (a 22.6% decrease in the number of nodes) and the trophic interactions from 1,049 to 637 between month extremes (a 39.3% drop in the number of links). The observed simplification in food web structure during ‘winter’ suggests that community stability is more vulnerable to the impact of any change during this period.http://onlinelibrary.wiley.com/doi/10.1002/ece3.3031/epd

The riverine bioreactor: an integrative perspective on biological decomposition of organic matter across riverine habitats

Riverine ecosystems can be conceptualized as ‘bioreactors’ (the riverine bioreactor) which retain and decompose a wide range of organic substrates. The metabolic performance of the riverine bioreactor is linked to their community structure, the efficiency of energy transfer along food chains, and complex interactions among biotic and abiotic environmental factors. However, our understanding of the mechanistic functioning and capacity of the riverine bioreactor remains limited. We review the state of knowledge and outline major gaps in the understanding of biotic drivers of organic matter decomposition processes that occur in riverine ecosystems, across habitats, temporal dimensions, and latitudes influenced by climate change. We propose a novel, integrative analytical perspective to assess and predict decomposition processes in riverine ecosystems. We then use this model to analyse data to demonstrate that the size-spectra of a community can be used to predict decomposition rates by analysing an illustrative dataset. This modelling methodology allows comparison of the riverine bioreactor's performance across habitats and at a global scale. Our integrative analytical approach can be applied to advance understanding of the functioning and efficiency of the riverine bioreactor as hotspots of metabolic activity. Application of insights gained from such analyses could inform the development of strategies that promote the functioning of the riverine bioreactor across global ecosystems