Beschreibung: Cold-water corals, such as Lophelia pertusa, are key habitat-forming organisms found throughout the world's oceans to 3000 m deep. The complex three-dimensional framework made by these vulnerable marine ecosystems support high biodiversity and commercially important species. Given their importance, a key question is how both the living and the dead framework will fare under projected climate change. Here, we demonstrate that over 12 months L. pertusa can physiologically acclimate to increased CO2, showing sustained net calcification. However, their new skeletal structure changes and exhibits decreased crystallographic and molecular-scale bonding organization. Although physiological acclimatization was evident, we also demonstrate that there is a negative correlation between increasing CO2 levels and breaking strength of exposed framework (approx. 20-30% weaker after 12 months), meaning the exposed bases of reefs will be less effective 'load-bearers', and will become more susceptible to bioerosion and mechanical damage by 2100.

Beschreibung: We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to forecast changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean (from 18°N to 76°N and 36°E to 98°W). The VME indicator taxa included Lophelia pertusa , Madrepora oculata, Desmophyllum dianthus, Acanela arbuscula, Acanthogorgia armata, and Paragorgia arborea. The six deep-sea fish species selected were: Coryphaenoides rupestris, Gadus morhua, blackbelly Helicolenus dactylopterus, Hippoglossoides platessoides, Reinhardtius hippoglossoides, and Sebastes mentella. We used an ensemble modelling approach employing three widely-used modelling methods: the Maxent maximum entropy model, Generalized Additive Models, and Random Forest. This dataset contains: 1) Predicted habitat suitability index under present-day (1951-2000) and future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean, using an ensemble modelling approach.  2) Climate-induced changes in the suitable habitat of twelve deep-sea species in the North Atlantic Ocean, as determined by binary maps built with an ensemble modelling approach and the 10-percentile training presence logistic (10th percentile) threshold. 3) Forecasted present-day suitable habitat loss (value=-1), gain (value=1), and acting as climate refugia (value=2) areas under future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modelling approach and two thresholds: 10-percentile training presence logistic threshold (10th percentile) and maximum sensitivity and specificity (MSS). Refugia areas are those areas predicted as suitable both under present-day and future conditions. All predictions were projected with the Albers equal-area conical projection centred in the middle of the study area. The grid cell resolution is of 3x3 km.