• Energy Research

Physical damage caused by the mechanical impact of bottom fishing gears on epibenthic community can reduce the biomass and coverage of habitat-forming species as well as the richness and diversity of the rest of the associated community. A practical development of a methodology for spatially assessing the potential degree of disturbance that benthic habitats suffered as a consequence of trawling and long-lining was carried out using a seamount located within a marine Natura 2000 site in the western Mediterranean as a case of study. By jointly assessing the extent of the impact and mapping the sensitivity of all the habitats to these fishing activities, vulnerability and disturbance per benthic habitat and pressure type was evaluated. Habitat sensitivity and fishing effort were combined using a disturbance matrix which categorize grid cells in 9 different levels of disturbance. Additionally, different thresholds of probability of presence of the different habitats obtained from distribution models were used to identify priority conservation and potential recovery. Around 50% of the area was disturbed by fishing and all habitats, both biogenic and non-biogenic, were subjected to fishing. Most of the trawling effort was carried out on soft bathyal substrates while the percentage of longlining effort carried out on hard bottoms was relatively higher than for trawling. Biogenic habitats showed significantly greater sensitivity to both trawling and longlining than non-biogenic habitats. Disturbed, priority conservation and potential recovery areas were identified and mapped in order to inform marine spatial planning. 1,865

Under current levels of global warming most demersal species in the Northeast Atlantic are experiencing tropicalization, meridionalization or borealization of their distributions, leading to profound changes in demersal communities. We explore these changes using the Community Weighted Mean Temperature (CWMT), an index to link the thermal preference of demersal fish communities and temperature. The CWMT is calculated as the summation of the mean temperature of each fish species distribution weighted by its relative abundance in the community. The relative abundance is based on the community composition data obtained by the International Bottom Trawl Surveys (IBTS) in the Southern Bay of Biscay between 1983 and 2015. Our analyses show that the CWMT responds to the actual temperature of the water column reproducing its space–time trends in the study area: (i) an increase from SW to NE, towards the inner Bay of Biscay, (ii) a decrease with depth, except in the SW area characterized by an intense upwelling, (iii) a general increase along the time series. Applying a k-means classification to the CWMT data we identified warm-, temperate- and cold-communities over the shelf and slope and their spatial changes in the last decades. The area occupied by warm communities has expanded 268.4 km2/ yr since the 80 s, while the cold communities have retracted at a speed of − 155.4 km2/yr. The CWMT was able to capture the community dynamics in relation to environmental temperature at different temporal and spatial scales, highlighting the potential of this index to explore and anticipate the effects of climate change in demersal communities under different scenarios of global warming. 2,695

Abstract Regional differences in climate vulnerability are particularly important in many countries with socio-ecological gradients or geographical and environmental spatial segregation. Many studies are regularly performed at the national level, but regional assessments can provide more detailed information and important insights into intra-national vulnerabilities. They require detailed information of many socio-ecological components that are often neglected at the regional scale but are meaningful and operational at national and international levels. In this work, we developed a climate vulnerability assessment (CVA) to investigate the vulnerability of demersal fisheries based on 19 indicators covering exposure, fisheries sensitivity, species sensitivity (SS) and adaptive capacity (AC) for nine coastal regions of Spain, contrasting the Mediterranean to Atlantic areas. Exposure was consistently larger in the Mediterranean than Atlantic regions, while AC showed the opposite trend. While fisheries and SS did not display a clear Atlantic-Mediterranean pattern, they were critical for capturing regional differences that have an impact on fisheries vulnerability. Our results highlight the generally higher vulnerability of Mediterranean demersal fisheries, mainly due to the lower AC and higher exposure of Mediterranean regions, while providing key regional elements for guiding national and international actions for adaptation. This study demonstrates that the spatial scale considered in the development of CVAs must recognise the spatial heterogeneity in the socio-ecological system within its unit of analysis in order to be a relevant tool for management and policy makers.

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). This dataset contains a set of terrain (static in time) and environmental (dynamic in time) variables were used as candidate predictors of present-day (1951-2000) distribution and to forecast future (2081-2100) changes. All predictor variables were projected with the Albers equal-area conical projection centred in the middle of the study area. The terrain variable depth was extracted from a bathymetry grid built from two data sources: the EMODnet Digital Terrain Model (EMODnet, 2018) and the General Bathymetric Chart of the Oceans (GEBCO 2014; Weatherall et al., 2015). Slope (in degrees) was derived from the final bathymetry grid using the Raster package in R (Hijmans, 2016) and the Bathymetric Position Index (BPI) was computed using the Benthic Terrain Model 3.0 tool in ArcGIS 10.1 with an inner radius of 3 and an outer radius of 25 grid cells. In order to avoid extreme values, BPI was standardized using the scale function from the Raster package. Environmental variables of present-day and future conditions, including particulate organic carbon (POC) flux at 100-m depth (epc100, mg C m-2 d-1), bottom water dissolved oxygen concentration (µmol kg-1), pH, and potential temperature (°K) were downloaded from the Earth System Grid Federation (ESGF) Peer-to-Peer (P2P) enterprise system. The epc100 was converted to export POC flux at the seafloor using the Martin curve (Martin, Knauer, Karl, & Broenkow, 1987) following the equation: epc = epc100*(water depth/export depth)-0.858, and setting the export depth to 100 m. Near seafloor aragonite (Ωar) and calcite (Ωcal) saturation were also used as candidate predictors for habitat suitability of cold-water coral species. These saturation states were computed by dividing the bottom water carbonate ion concentration (mol m-3) by the bottom water carbonate ion concentration (mol m-3) for seawater in equilibrium with pure aragonite and calcite. Yearly means of these parameters were calculated for the periods 1951-2000 (historical simulation) and 2081-2100 (RCP8.5 or business-as-usual scenario) using the average values obtained from the Geophysical Fluid Dynamics Laboratory's ESM 2G model (GFDL-ESM-2G; Dunne et al., 2012), the Institut Pierre Simon Laplace's CM6-MR model (IPSL-CM5A-MR; Dufresne et al., 2013) and Max Planck Institute's ESM-MR model (MPI-ESM-MR; Giorgetta et al., 2013) within the Coupled Models Intercomparison Project Phase 5 (CMIP5) for each grid cell of the present study area.

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.

AbstractThe deep sea plays a critical role in global climate regulation through uptake and storage of heat and carbon dioxide. However, this regulating service causes warming, acidification and deoxygenation of deep waters, leading to decreased food availability at the seafloor. These changes and their projections are likely to affect productivity, biodiversity and distributions of deep‐sea fauna, thereby compromising key ecosystem services. Understanding how climate change can lead to shifts in deep‐sea species distributions is critically important in developing management measures. 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 project changes under severe, high emissions future (2081–2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean. Our models projected a decrease of 28%–100% in suitable habitat for cold‐water corals and a shift in suitable habitat for deep‐sea fishes of 2.0°–9.9° towards higher latitudes. The largest reductions in suitable habitat were projected for the scleractinian coral Lophelia pertusa and the octocoral Paragorgia arborea, with declines of at least 79% and 99% respectively. We projected the expansion of suitable habitat by 2100 only for the fishes Helicolenus dactylopterus and Sebastes mentella (20%–30%), mostly through northern latitudinal range expansion. Our results projected limited climate refugia locations in the North Atlantic by 2100 for scleractinian corals (30%–42% of present‐day suitable habitat), even smaller refugia locations for the octocorals Acanella arbuscula and Acanthogorgia armata (6%–14%), and almost no refugia for P. arborea. Our results emphasize the need to understand how anticipated climate change will affect the distribution of deep‐sea species including commercially important fishes and foundation species, and highlight the importance of identifying and preserving climate refugia for a range of area‐based planning and management tools.