The efficacy of benthic indices to evaluate the ecological quality and urbanization effects on sandy beach ecosystems.

Benthic indices have been widely used across different coastal ecosystems to assess ecological quality and detect anthropic impacts, but very few studies investigated their effectiveness on sandy beaches. Here, we evaluated and compared the efficacy of 12 assemblage-based benthic indices in assessing ecological quality in beaches, across a gradient of anthropic pressure and natural variability in 90 sandy beach sites. Overall, when sandy beaches were considered collectively, benthic indices had a poor performance in identifying decreases in ecological quality with increasing urbanization. However, when each morphodynamic type was evaluated separately, a few indices, especially those that were calibrated by reference conditions (i.e., M-AMBI, BAT, and BEQI-2), showed promising results for dissipative, and to a lesser extent, intermediate beaches. For reflective beaches, indices performed poorly, likely a reflection of the stronger natural disturbance these beaches are subjected to. Among functional indices, richness was found to be lower in urbanized beaches, but only in dissipative ones. Overall, our results show that benthic indices have the potential to be incorporated in sandy beach management and monitoring programs, especially for dissipative and intermediate beaches. For reflective beaches, given the early stage of studies with benthic indices in beaches, more research is needed to corroborate the observed patterns.

Evaluation of the effects of urbanization and environmental features on sandy beach macrobenthos highlights the importance of submerged zones.

To assess how sandy beach biodiversity is influenced by the effects of environmental features and urbanization, we sampled the macrofauna in the whole across-shore gradient of 90 beach sites in Southeast Brazil. We found that morphodynamic features were the main drivers of macrobenthos, but urbanization-related variables, such as number of beachgoers and number of constructions on the upper shore, decreased species richness and biomass. We also found that submerged zones sustained the highest number of species and biomass in the across-shore gradient, but were the most impacted by human activities. By demonstrating the ecological importance of submerged zones, our results show that beach management practices, which are mainly focused on the upper shore, are missing important components of beach biodiversity. To secure the sustainability of beach ecosystems, management initiatives should include both their social and ecological components and consider the entire Littoral Active Zone as the proper management unit.

Locally developed models improve the accuracy of remotely assessed metrics as a rapid tool to classify sandy beach morphodynamics.

Classification of beaches into morphodynamic states is a common approach in sandy beach studies, due to the influence of natural variables in ecological patterns and processes. The use of remote sensing for identifying beach type and monitoring changes has been commonly applied through multiple methods, which often involve expensive equipment and software processing of images. A previous study on the South African Coast developed a method to classify beaches using conditional tree inferences, based on beach morphological features estimated from public available satellite images, without the need for remote sensing processing, which allowed for a large-scale characterization. However, since the validation of this method has not been tested in other regions, its potential uses as a trans-scalar tool or dependence from local calibrations has not been evaluated. Here, we tested the validity of this method using a 200-km stretch of the Brazilian coast, encompassing a wide gradient of morphodynamic conditions. We also compared this locally derived model with the results that would be generated using the cut-off values established in the previous study. To this end, 87 beach sites were remotely assessed using an accessible software (i.e., Google Earth) and sampled for an in-situ environmental characterization and beach type classification. These sites were used to derive the predictive model of beach morphodynamics from the remotely assessed metrics, using conditional inference trees. An additional 77 beach sites, with a previously known morphodynamic type, were also remotely evaluated to test the model accuracy. Intertidal width and exposure degree were the only variables selected in the model to classify beach type, with an accuracy higher than 90% through different metrics of model validation. The only limitation was the inability in separating beach types in the reflective end of the morphodynamic continuum. Our results corroborated the usefulness of this method, highlighting the importance of a locally developed model, which substantially increased the accuracy. Although the use of more sophisticated remote sensing approaches should be preferred to assess coastal dynamics or detailed morphodynamic features (e.g., nearshore bars), the method used here provides an accessible and accurate approach to classify beach into major states at large spatial scales. As beach type can be used as a surrogate for biodiversity, environmental sensitivity and touristic preferences, the method may aid management in the identification of priority areas for conservation.

Nestedness patterns and the role of morphodynamics and spatial distance on sandy beach fauna: ecological hypotheses and conservation strategies.

Sandy beach fauna is hypothesized to be mainly structured by environmental variables. As such, it is expected that morphodynamic characteristics are limiting factors, and the species pool inhabiting harsher reflective beaches would be a subset of (i.e., nested in) the fauna of nearby dissipative beaches. We investigated the existence of a nestedness pattern in sandy beach assemblages, as well as the contribution of environmental and spatial variables (i.e., factors that potentially affect an assemblage regardless of environmental conditions - typically related to distance between sites and dispersal of organisms) on sandy beach macrobenthic fauna. Dissipative beaches had higher species richness than reflective beaches but we found no nestedness pattern. Furthermore, almost every beach showed exclusive species. Spatial variables exerted stronger influence on macrobenthic assemblages than local environmental variables. Our results therefore suggest that local and small-scale recruitment is the predominant process structuring macrobenthic assemblages. These results bring important implications for sandy beach conservation: given that spatial distance is an important factor structuring macrobenthic fauna and different sandy beaches harbor different pools of species, conservation programs need to focus on sandy beaches across large spatial scales and with varied morphodynamic characteristics in order to preserve coastal biodiversity.