The effect of short-term meteorological disturbances on the submerged aquatic vegetation and associated fauna in the Patos Lagoon estuary, southern Brazil

a dataset




Benthic Fauna, Seagrass, Sandflat, Occluded Front, Sedimentary organic matter


Occluded fronts are naturally cyclogenic areas that have been intensified by global warming. Studies evaluating the effects of occluded fronts in the submerged aquatic vegetation (SAV) and its associated fauna in shallow estuarine areas may provide insights on the impacts of climate change-induced extreme weather events on coastal ecosystems functioning. The present dataset describes data on benthic fauna and flora in the Patos Lagoon Estuary (PLE), in southern Brazil, seasonally obtained during intense occluded fronts. Using a hierarchical sample design, based on Beyond BACI protocols (Before/After and Control/Impact), fauna and flora were sampled before and after four occluded fronts passage throughout 2019.Three habitats were sampled: SAV Meadow, SAV Edge and adjacent Sandflat. A total of 432 macrozoobenthic samples (216 samples for stratum); 216 samples for bellow and aboveground biomass, vegetation coverage, canopy height and marine macrophytes morphology; 144 samples by sedimentology and organic matter; 72 water column depth measurements; and 8 temperature and salinity measurements were collected during the study period. The data is available at the Global Biodiversity Information Facility (GBIF), in Darwin Core standard format (DwC), organized according to the OBIS-ENV-DATA model, with CC-BY-NC-4-0 license for use. The present dataset adds to the comprehension of the temporal variability of estuarine benthic communities in subtropical systems, and how short-term meteorological process can affect zoo and fitobenthic communities in the context of climate changes.


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How to Cite

MISTURINI, D.; LANARI, M.; LEMOS, V.; COLLING, L. A. The effect of short-term meteorological disturbances on the submerged aquatic vegetation and associated fauna in the Patos Lagoon estuary, southern Brazil: a dataset. Latin American Data in Science, [S. l.], v. 1, n. 2, p. 63–71, 2021. DOI: 10.53805/lads.v1i2.26. Disponível em: Acesso em: 1 mar. 2024.