Figure 1

Schematic of framework for calculating cumulative impact and accounting for ‘knowledge-based uncertainty’. Experts were asked to give ‘effect scores’ (between 0–8) for each combination of threat (in this example it is prawn trawl fishing) and ecosystem (here subtidal soft sediment), and for three uncertainty scenarios:’best-case’, ‘most-likely’ and ‘worst-case’. These effect scores were then used in a calculation of impact that accounts for the spatial intensity of each threat and the locations of overlap between a threat and an ecosystem. This process was repeated for each threat that occurs to each ecosystem and the resulting impact layers were summed to generate ecosystem-specific cumulative impact maps. This entire process was carried out for all eight ecosystems, and was repeated three times, once for each uncertainty scenario, to account for the experts’ ‘knowledge-based uncertainty’ around the cumulative impact scores. Maps were produced using R statistical software (version 3.3.1; https://www.r-project.org) and the packages raster³⁶, rgdal³⁷, sp³⁵ and rasterVis³⁸.