Development of a life cycle impact assessment framework accounting for biodiversity in deep seafloor ecosystems: A case study on the Clarion Clipperton Fracture Zone.

The transformation of ecosystems is known to be a major driver of biodiversity loss. Consequently, supporting tools such as life cycle assessment methods (LCA) include this aspect in the evaluation of a product's environmental performance. Such methods consist of quantifying input and output flows to assess their specific contributions to impact categories. Therefore, land occupation and transformation are considered as inputs to assess biodiversity impacts amongst others. However, the modelling of biodiversity impact in deep seafloor ecosystems is still lacking in LCA. Most of the LCA methods focus on terrestrial biodiversity and none of them can be transposed to benthic deep sea because of knowledge gaps. This manuscript proposes a LCA framework to assess biodiversity impacts in deep seafloor ecosystems. The framework builds upon the existing methods accounting for biodiversity impacts in terrestrial and coastal habitats. A two-step approach is proposed, assessing impacts on regional and on global biodiversity. While the evaluation of regional biodiversity impacts relies only on the benthic communities' response to disturbance, the global perspective considers ecosystem vulnerability and scarcity. Those provide additional perspective for the comparison of impacts occurring in different ecosystems. The framework is operationalised to a case study for deep-sea mining in the Clarion Clipperton Fractures Zone (CCZ). Through the large variety of data sources needed to run the impact evaluation modelling, the framework shows consistency and manages the existing limitations in the understanding of deep seafloor ecosystems, although limitations for its application in the CCZ were observed mainly due to the lack of finer scaled habitat maps and data on connectivity. With growing interest for commercial activities in the deep sea and hence, increased environmental research, this work is a first attempt for the implementation of LCA methods to deep-sea products.