During the last fifty years, there has been a dramatic increase in the development of anthropogenic activities, and this is particularly threatening to marine coastal ecosystems.

This study developed a statistical and modelling approach to study the complex relationship between human multiple activities and ecosystem status. The authors used Random Forest modelling to explain the degradation status of the Mediterranean seagrass Posidonia oceanica as a function of depth and 10 anthropogenic pressures along the French Mediterranean coast.

The obtained results show as the best global predictors: human-made coastline, depth, coastal population, urbanization, and agriculture; while aquaculture was the least important predictor, although its local individual influence was among the highest.

The authors state that the obtained model showed excellent performance to predict the degradation status of this important marine ecosystem. It is underlined that the study provides useful tools for stakeholders and managers, which could be used to facilitate decision making concerning impact assessment and conservation actions, and highlight the potential applicability of the method to other marine ecosystems.

https://www.sciencedirect.com/science/article/pii/S0006320717307115

Holon F et al. (2018) A predictive model based on multiple coastal anthropogenic pressures explains the degradation status of a marine ecosystem: Implications for management and conservation. Biological Conservation 222:125-135.