Landscape maps based on multivariate cluster analyses provide an objective and comprehensive view on the (marine) environment. They can hence support decision making regarding sustainable ocean resource handling and protection schemes. Across a large number of scales, input parameters and classification methods, numerous studies categorize the ocean into seascapes, hydro-morphological provinces or clusters. Many of them are regional, however, while only a few are on a basin scale. This study presents an automated cluster analysis of the entire Atlantic seafloor environment, based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities. As a result, we obtained nine seabed areas (SBAs) that portray the Atlantic seafloor. Some SBAs have a clear geological and geomorphological nature, while others are defined by a mixture of terrain and water body characteristics. The majority of the SBAs, especially those covering the deep ocean areas, are coherent and show little seasonal and hydrographic variation, whereas other, nearshore SBAs, are smaller sized and dominated by high seasonal changes. To demonstrate the potential use of the marine landscape map for marine spatial planning purposes, we mapped out local SBA diversity using the patch richness index developed in landscape ecology. It identifies areas of high landscape diversity, and is a practical way of defining potential areas of interest, e.g. for designation as protected areas, or for further research. Clustering probabilities are highest (100%) in the center of SBA patches and decrease towards the edges (< 98%). On the SBA point cloud which was reduced for probabilities <98%, we ran a diversity analysis to identify and highlight regions that have a high number of different SBAs per area, indicating the use of such analyses to automatically find potentially delicate areas. We found that some of the highlights are already within existing EBSAs, but the majority is yet unexplored.
The large, habitat-forming bubblegum coral, Paragorgia arborea, is a vulnerable marine ecosystem indicator with an antitropical distribution. Dense aggregations of the species have been protected from bottom-contact fishing in the Scotian Shelf bioregion off Nova Scotia, Canada in the northwest Atlantic Ocean. Recently, basin-scale habitat suitability ensemble modeling has projected an alarming loss of 99% of suitable habitat for this species across the North Atlantic by 2100. Here, a regional reassessment of the predicted distribution of this species in the bioregion, using both machine learning (random forest) and generalized additive model (GAM) frameworks, including projection to 2046−2065, was undertaken. Extrapolation diagnostics were applied to determine the degree to which the models projected into novel covariate space (i.e., extrapolation) in order to avoid erroneous inferences. The best predictors of the species’ distribution were a suite of temporally-invariant terrain variables that identified suitable habitat along the upper continental slope. Additional predictors, projected to vary with future ocean climatologies, identified areas of the upper slope in the eastern portion of the study area that will remain within suitable ranges for P. arborea at least through to the mid-century. Additionally, 3-D Lagrangian particle tracking simulations indicated potential for both connectivity among known occurrence sites and existing protected areas, and for colonization of unsurveyed areas predicted to have suitable habitat, from locations of known occurrence. These results showed that extirpation of this iconic species from the Scotian Shelf bioregion is unlikely over the next decades. Potential climate refugia were identified and results presented in the context of protected area network design properties of representativity, connectivity, adequacy, viability and resilience.
This study used a novel approach combining biological, environmental, and ecosystem function data of the Logachev cold-water coral carbonate mound province to predictively map coral framework (bio)mass. A more accurate representation and quantification of cold-water coral reef ecosystem functions such as Carbon and Nitrogen stock and turnover were given by accounting for the spatial heterogeneity. Our results indicate that 45% is covered by dead and only 3% by live coral framework. The remaining 51%, is covered by fine sediments. It is estimated that 75,034–93,534 tons (T) of live coral framework is present in the area, of which ∼10% (7,747–9,316 T) consists of Cinorg and ∼1% (411–1,061 T) of Corg. A much larger amount of 3,485,828–4,357,435 T (60:1 dead:live ratio) dead coral framework contained ∼11% (418,299–522,892 T) Cinorg and <1% (0–16 T) Corg. The nutrient turnover by dead coral framework is the largest, contributing 45–51% (2,596–3,626 T) C year–1 and 30–62% (290–1,989 T) N year–1 to the total turnover in the area. Live coral framework turns over 1,656–2,828 T C year–1 and 53–286 T N year–1. Sediments contribute between 1,216–1,512 T C year–1 and 629–919 T N year–1 to the area’s benthic organic matter mineralization. However, this amount is likely higher as sediments baffled by coral framework might play a much more critical role in reefs CN cycling than previously assumed. Our calculations showed that the area overturns 1–3.4 times the C compared to a soft-sediment area at a similar depth. With only 5–9% of the primary productivity reaching the corals via natural deposition, this study indicated that the supply of food largely depends on local hydrodynamical food supply mechanisms and the reefs ability to retain and recycle nutrients. Climate-induced changes in primary production, local hydrodynamical food supply and the dissolution of particle-baffling coral framework could have severe implications for the survival and functioning of cold-water coral reefs.