Reliability of Local Scale Human Pressure Modeling at the Seafloor of the Baltic Sea - Matti Sahla; Risto Kalliola (Taylor & Francis, 2022)
Efforts to understand anthropogenic stress in marine environments have introduced methods of cumulative human pressure modeling in the broad-scale mapping of large sea areas. This paper examines the usability of such modeling in the shallow seafloor and complex shoreline conditions of the Archipelago Sea in the northern Baltic Sea. We employed public spatial data sources to describe the spatial patterns of 24 different human pressures with their normalized values in a 20 m × 20 m pixel size. Public data were also used to classify the seafloor into six different environmental types. The model output was assessed against environmental data from regular seafloor monitoring. Visual examination shows general agreement between the cumulative human pressure model and the health of the benthic fauna, seabed oxygen and, to a degree, also the tributyltin. However, although none of these field parameters show high statistical correlation with the cumulative pressure status, multiple parameters assessed simultaneously could provide a sufficient reference. Local-scale disagreements between the cumulative model and the field parameters particularly occur near the largest harbor in the region where regular dredging is practiced. Model sensitivity to different input variables was further tested by comparing 36 dissimilar variants. The comparisons reveal a general stability across the inclusion, exclusion, or modification of such spatially restricted human pressure data, which only induced local-scale details. High instabilities occurred when the tested input data had a large spatial coverage. As the cumulative human impact model reduces several human pressures into one index, it should be considered as a broad scale descriptor of the likely overall health status of the sea. When implemented with accurate local-scale data it can help coastal and marine spatial planning but it should not be considered as a predictive depiction of any particular environmental characteristic. The cumulative pressure map is particularly powerful in providing unforeseen insights into the distributions of overall anthropogenic influences within the study region, and through these it can also contribute to environmental policies.