Physical Drivers and Dominant Oceanographic Processes on the Uruguayan Margin (Southwestern Atlantic): A Review and a Conceptual Model

• Main Authors: Leticia Burone, Paula Franco-Fraguas, Alvar Carranza, Danilo Calliari, Michel Michaelovitch de Mahiques, Mónica Gómez, Yamandú Marin, Ofelia Gutiérrez, Leonardo Ortega
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Journal of Marine Science and Engineering
• Subjects: Uruguayan margin; Southwestern Atlantic; conceptual models
• Online Access: https://www.mdpi.com/2077-1312/9/3/304

The Uruguayan continental margin (UCM), located in the Southwestern Atlantic margin’s subtropical region, is positioned in a critical transitional region regarding the global ocean circulation (Río de la Plata (RdlP) outflow and Brazil-Malvinas Confluence), as also reflected in seafloor features (northernmost distribution of a large depositional contourite system and RdlP paleovalley). This complex oceanographic scenario occurring in a relatively small area highlights the advantage of considering the UCM as a natural laboratory for oceanographic research. The present work provides the first conceptual “control” model of the physical drivers (i.e., climate, geomorphology) and main oceanographic processes (i.e., hydrodynamics, sediment, and carbon dynamics) occurring along the UCM, reviewing and synthesizing available relevant information based on a functional integrated approach. Despite the conspicuous knowledge gaps on critical processes, a general picture of the system’s functioning is emerging for this complex biophysical setting. This includes conceptualizations of the actual controls, main processes, feedbacks, and interactions responsible for system dynamics. The structure adopted for developing our conceptual models allows permanent improvement by empirical testing of the working hypothesis and incorporating new information as scientific knowledge advances. These models can be used as a baseline for developing quantitative models and, as representations of relatively “pristine” conditions, for stressors models by identifying sources of stress and ecological responses of key system attributes under a transboundary approach.