RESUMO
Many indicators have been developed to assess the state of benthic communities and identify seabed habitats most at risk from bottom trawling disturbance. However, the large variety of indicators and their development and application under specific geographic areas and management contexts has made it difficult to evaluate their wider utility. We compared the complementarity/uniqueness, sensitivity, and selectivity of 18 benthic indicators to pressure of bottom trawling. Seventeen common datasets with broad regional representation covering a range of pressure gradients from bottom trawling disturbance (n = 14), eutrophication (n = 1), marine pollution (n = 1), and oxygen depletion (n = 1) were used for the comparison. The outcomes of most indicators were correlated to a certain extent with response to bottom trawling disturbance, and two complementary groups of indicators were identified: diversity-based and biological trait-based indicators. Trait-based indicators that quantify the changes in relative abundance of sensitive taxa were most effective in identifying benthic community change in response to bottom trawling disturbance. None of the indicators responded to the trawling pressure gradient in all datasets, and some showed a response that were opposed to the theoretical expectation for some gradients. Indicators that showed clear responses to bottom trawling disturbance also showed clear responses in at least one other pressure gradient, suggesting those indicators are not pressure specific. These results emphasize the importance of selecting several indicators, at least one from each group (diversity and trait-based), to capture the broader signals of change in benthic communities due to bottom trawling activities. Our systematic approach offers the basis from which scientific advisors and/or managers can select suitable combinations of indicators to arrive at a sensitive and comprehensive benthic status assessment.
RESUMO
The 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.
RESUMO
The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME) from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO) produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE) to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify "significant concentrations" of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores), and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here and elsewhere.