Effects of model assumptions and data quality on spatial cumulative human impact assessments

摘要: Aim Many studies have quantified and mapped cumulative human impacts on marine ecosystems. These maps are intended to inform management planning, but uncertainty in them has not been studied depth. This paper aims to: (1) quantify the impact related spatial modelling results; (2) attribute this specific model assumptions problems with data quality; (3) identify test sound approaches such analyses. Location We used Baltic Sea Mediterranean Black Seas as example regions. The methods conclusions relevant for mapping anywhere. Methods We conducted computational experiments effects of nine quality (factors) results. factors were implemented basis a literature review. We aggregate using Monte Carlo simulations, ranked by their influence results elementary method. Both well established theoretically suitable complex models, had be modified application models. Results Some, all, robust. contradicts previous that found only minor they tested. Of tested here, eight considerable at least one result two study regions. Main conclusions Model larger than analyses. depend region describe it. Future should thus include comprehensive Computational allow us distinguish robust from less reliable prioritize improvements models data.