Epinephelus itajara is one of the marine fish species most threatened for extinction and it is considered to be "critically endangered" by the IUCN. The present study evaluated the genetic diversity of the species and the genetic/evolutionary relationships of its populations along the Atlantic coast of South America. The results indicate relatively reduced genetic variation, re-emphasizing the low adaptive potential of the species. One of the populations presented relatively high degrees of genetic diversity and it is evolutionary isolated from the all other populations. The evidences indicate the existence of two Evolutionarily Significant Units comprising E. itajara in the Atlantic coast of South America and the conservation prospects for the species must take these evidences into account. Highlights ► A low genetic diversity was confirmed in Epinephelus itajara. ► The species is divided into two genetic/evolutionary lineages. ► A possible ESU of E. itajara occurs at the Babitonga bay (Southern Brazil). ► Physical oceanography explains the isolation at the Babitonga bay (Southern Brazil). ► Also a panmictic population occurs in the rest of the Atlantic coast of South America.
Through alteration of wave-generating atmospheric systems, global climate changes play a fundamental role in regional wave climate. However, long-term wave-climate cycles and their associated forcing mechanisms remain poorly constrained, in part due to a relative dearth of highly resolved archives. Here we use the morphology of former shorelines preserved in beach-foredune ridges (BFR) within a protected embayment to reconstruct changes in predominant wave directions in the Subtropical South Atlantic during the last ~ 3000 years. These analyses reveal multi-centennial cycles of oscillation in predominant wave direction in accordance with stronger (weaker) South Atlantic mid- to high-latitudes mean sea-level pressure gradient and zonal westerly winds, favouring wave generation zones in higher (lower) latitudes and consequent southerly (easterly) wave components. We identify the Southern Annular Mode as the primary climate driver responsible for these changes. Long-term variations in interhemispheric surface temperature anomalies coexist with oscillations in wave direction, which indicates the influence of temperature-driven atmospheric teleconnections on wave-generation cycles. These results provide a novel geomorphic proxy for paleoenvironmental reconstructions and present new insights into the role of global multi-decadal to multi-centennial climate variability in controlling coastal-ocean wave climate.
A hybrid method is applied to generate a high‐resolution regional downscaling of atmospheric conditions to the southern coast of Brazil. The method consists of applying a principal component analysis to daily fields of the sea level pressure (SLP) data from the NCEP‐CFSR reanalysis. A cluster analysis (K‐means) is then applied to the 87 principal components that explained 95% of the variance of the time series. Daily atmospheric conditions were clustered into 36 weather types which represent the most predominant conditions observed in the study area. The estimated weather types were able to represent the major atmospheric systems affecting local climate, including the cyclones and anticyclones that are usually present in this region. Then, we applied the numerical Ocean‐Land‐Atmosphere Model (OLAM) to dynamically downscale the atmospheric condition that is closest to the centroid of each cluster. The model was set with a global grid and a refining approach with 6 km grid spacing over the coastal region of south Brazil. This approach allowed us to represent simultaneously the planetary waves and the local mesoscale systems, and their mutual interactions. The results provided new high‐resolution atmospheric fields for the coastal region and showed that the model was capable of resolving the major local mesoscale features. The main advantage of applying such a method is in reducing the number of numerical simulations (lower computational cost) at the same time it represents the totality of the atmospheric conditions observed in the study area. The final results consist in detailed information of the local climate that can be related to injuries to the coastal area and thus is useful to support decision‐makers.
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