Coral reef degradation due to environmental change, including anthropogenic disturbances, is a major concern worldwide. Detecting and assessing both temporal and spatial changes in benthic cover is a crucial requirement to inform policy makers and guide conservation measures. Here, we introduce a spatial approach based on high resolution multispectral and hyperspectral image analysis, developed in order to detect and quantify changes in benthic cover in a highly heterogeneous shallow coral reef flat in Reunion Island in the South-West Indian Ocean. We propose a new index called HCAI (Hyperspectral Coral to Algae Index), defined as the ratio of living coral cover to the sum of living coral and algal covers. Benthic cover estimates were derived from airborne hyperspectral image processing using water column correction and unmixing models implemented with the four main coral reef benthic components: corals, algae, seagrass and sand. Ground truth and LIDAR data acquired simultaneously were used to validate processing accuracy. A significant positive correlation (adjusted R-2 = 0.72, p-value < 0.001) was obtained between coral cover recorded in situ and estimated from image analysis. Moreover, 13 habitat classes based on the four main benthic component covers were mapped at a scale of an entire reef. Diachronic analyses of hyperspectral images between 2009 and 2015 revealed an overall decrease of the HCAI index and a decrease in the area of all the dominant coral classes along the reef (-28.24% for the coral class for example), while the area of habitat classes dominated by algae strongly increased during the same period. Moreover, we detected and documented the spatial and temporal evolutions of coral geomorphological features composed with coral rubble deposits called rubble tongues (RTs) using different available sensors (i.e. hyperspectral, satellite, and orthophotography). Since 2003, four detected (RTs) have spread shoreward at a mean rate of 8.4 m.y(-1) including significant loss of reef structural complexity and heterogeneity, a spreading pattern which was confirmed by 2009 and 2015 hyperspectral data. Remote sensing and more specifically airborne hyperspectral approaches open new perspectives for coral reef monitoring, at high temporal and spatial resolutions.

We have analyzed the development of "Broad-Scale Seabed Habitat Maps" (BSHM) and their potential use in a European context with regard to the EU Marine Strategy Framework Directive (MSFD) implementation, MPA designation and network assessment as well as other applications of BSHMs.The analyses are anchored in BSHMs developed by a series of interlinked EU projects (e.g.UKSeaMap, BALANCE, MESH, Mesh Atlantic, EUSeaMap 2012, and EUSeaMap 2016) and all maps are based on environmental data.Some EU Member States have used BSHMs as part of their MSFD Initial Assessments published in 2012.However, we conclude that BSHMs are a prerequisite for another key MSFD activity, i.e. mapping of potentially cumulative effects of multiple human stressors.Further, BSHMs seem to play a growing role with regard to evidence-based assessments of MPAs.With the upcoming second round of MSFD Initial Assessments due in 2018, including assessment of potentially cumulative pressures, there seems to be an increasing need for more BSHMs nationally, regionally and on a European scale.

Marine benthic ecosystems are difficult to monitor and assess, which is in contrast to modern ecosystem-based management requiring detailed information at all important ecological and anthropogenic impact levels. Ecosystem management needs to ensure a sustainable exploitation of marine resources as well as the protection of sensitive habitats, taking account of potential multiple-use conflicts and impacts over large spatial scales. The urgent need for large-scale spatial data on benthic species and communities resulted in an increasing application of distribution modelling (DM). The use of DM techniques enables to employ full spatial coverage data of environmental variables to predict benthic spatial distribution patterns. Especially, statistical DMs have opened new possibilities for ecosystem management applications, since they are straightforward and the outputs are easy to interpret and communicate. Mechanistic modelling techniques, targeting the fundamental niche of species, and Bayesian belief networks are the most promising to further improve DM performance in the marine realm. There are many actual and potential management applications of DMs in the marine benthic environment, these are (i) early warning systems for species invasion and pest control, (ii) to assess distribution probabilities of species to be protected, (iii) uses in monitoring design and spatial management frameworks (e.g. MPA designations), and (iv) establishing long-term ecosystem management measures (accounting for future climate-driven changes in the ecosystem). It is important to acknowledge also the limitations associated with DM applications in a marine management context as well as considering new areas for future DM developments. The knowledge of explanatory variables, for example, setting the basis for DM, will continue to be further developed: this includes both the abiotic (natural and anthropogenic) and the more pressing biotic (e.g. species interactions) aspects of the ecosystem. While the response variables on the other hand are often focused on species presence and some work undertaken on species abundances, it is equally important to consider, e.g. biological traits or benthic ecosystem functions in DM applications. Tools such as DMs are suitable to forecast the possible effects of climate change on benthic species distribution patterns and hence could help to steer present-day ecosystem management.

If marine management policies and actions are to achieve long-term sustainable use and management of the marine environment and its resources, they need to be informed by data giving the spatial distribution of seafloor habitats over large areas. Broad-scale seafloor habitat mapping is an approach which has the benefit of producing maps covering large extents at a reasonable cost. This approach was first investigated by Roff et al. (2003), who, acknowledging that benthic communities are strongly influenced by the physical characteristics of the seafloor, proposed overlaying mapped physical variables using a geographic information system (GIS) to produce an integrated map of the physical characteristics of the seafloor. In Europe the method was adapted to the marine section of the EUNIS (European Nature Information System) classification of habitat types under the MESH project, and was applied at an operational level in 2011 under the EUSeaMap project. The present study compiled GIS layers for fundamental physical parameters in the northeast Atlantic, including (i) bathymetry, (ii) substrate type, (iii) light penetration depth and (iv) exposure to near-seafloor currents and wave action. Based on analyses of biological occurrences, significant thresholds were fine-tuned for each of the abiotic layers and later used in multi-criteria raster algebra for the integration of the layers into a seafloor habitat map. The final result was a harmonised broad-scale seafloor habitat map with a 250mpixel size covering four extensive areas, i.e. Ireland, the Bay of Biscay, the Iberian Peninsula and the Azores. The map provided the first comprehensive perception of habitat spatial distribution for the Iberian Peninsula and the Azores, and fed into the initiative for a pan-European map initiated by the EUSeaMap project for Baltic, North, Celtic and Mediterranean seas.

The availability of light in the water column and at the seabed determines the euphotic zone and constrains the type and the vertical distribution of algae species. Light attenuation is traditionally quantified as the diffuse attenuation coefficient of the downwelling spectral irradiance at wavelength 490nm (Kd490) or the photosynthetically available radiation (KdPAR). Satellite observations provide global coverage of these parameters at high spatial and temporal resolution and several empirical and semi-analytical models are commonly used to derive Kd490 and KdPAR maps from ocean colour satellite sensors. Most of these existing empirical or semi-analytical models have been calibrated in open ocean waters and perform well in these regions, but tend to underestimate the attenuation of light in coastal waters, where the backscattering caused by the suspended matters and the absorption by the dissolved organic matters increase light attenuation in the water column.We investigate two relationships between KdPAR and Kd490 for clear and turbid waters using MERIS reflectances and the spectral diffuse attenuation coefficient Kd(λ) developed by Lee (2005). Satellite-derived fields of Kd490 and modelled KdPAR are evaluated using coincident in-situ data collected over the world in both clear and turbid waters, and by using Ecolight simulations. Temporal means at 250m resolution of KdPAR and euphotic depth were computed over the period 2005–2009 for European coastal waters. These mean data were cross-tabulated with in-situ data of kelp (Laminaria hyperborea) and seagrass (Posidonia oceanica), respectively observed at locations on Atlantic and Mediterranean shores where the light is taken as the limiting factor to the depth distribution for these species. The minima observed for P. oceanica, in percent of energy, are very close to 1% of surface irradiance, the historical threshold known as euphotic depth as defined by Ryther (1956). Real estimates of the surface irradiance (Frouin, 1989) are used in conjunction with the estimated KdPAR to calculate the residual energy at the lower limit of P. oceanica and L. hyperborea in mol·photons·m−2·day−1 as a complement to the usual fraction of the surface energy. We show that the observed values, in terms of energy, for both species were equivalent to the values reported in the literature.

We address the global deficit of data describing kelp forest distribution, relative covers and biomass by testing the ability of species distribution models to predict these attributes at locations where data are currently limited. We integrated biological ground truth data with high-resolution environmental datasets to develop generalized additive models that accurately predict the structure of Laminaria forests within the Bay of Morlaix (48°42′42″N, 3°55′40″W). Forest distribution and proportional covers were predicted using water depth, light availability, wave exposure and sediment dynamics. The biomass of individual kelp species was modeled by supplementing these same variables with measures of seafloor slope and benthic position. Biomass predictions for Laminaria digitata and Laminaria hyperborea contrast the physiological tolerances of these species to light and wave exposure gradients. As a direct management output, we produced high-resolution maps (25 m2 grids) that closely match independent field data and provide vital information for marine spatial planning.

The EUNIS (European Union Nature Information System) habitat classification system aims to provide a common European reference set of habitat types within a hierarchical classification, and to cover all terrestrial, freshwater and marine habitats of Europe. The classification facilitates reporting of habitat data in a comparable manner, for use in nature conservation (e.g. inventories, monitoring and assessments), habitat mapping and environmental management. For the marine environment the importance of a univocal habitat classification system is confirmed by the fact that many European initiatives, aimed at marine mapping, assessment and reporting, are increasingly using EUNIS habitat categories and respective codes. For this reason substantial efforts have been made to include information on marine benthic habitats from different regions, aiming to provide a comprehensive geographical coverage of European seas. However, there still remain many concerns on its applicability as only a small fraction of Europe's seas are fully mapped and increasing knowledge and application raise further issues to be resolved. This paper presents an overview of the main discussion and conclusions of a workshop, organised by the MeshAtlantic project, focusing upon the experience in using the EUNIS habitats classification across different countries and seas, together with case studies. The aims of the meeting were to: (i) bring together scientists with experience in the use of the EUNIS marine classification and representatives from the European Environment Agency (EEA); (ii) agree on enhancements to EUNIS that ensure an improved representation of the European marine habitats; and (iii) establish practices that make marine habitat maps produced by scientists more consistent with the needs of managers and decision-makers. During the workshop challenges for the future development of EUNIS were identified, which have been classified into five categories: (1) structure and hierarchy; (2) biology; (3) terminology; (4) mapping; and (5) future development. The workshop ended with a declaration from the attendees, with recommendations to the EEA and European Topic Centre on Biological Diversity, to take into account the outputs of the workshop, which identify weaknesses in the current classification and include proposals for its modification, and to devise a process to further develop the marine component of the EUNIS habitat classification.

Predictive modelling to map subtidal communities is an alternative to “traditional” methods, such as direct sampling, remote sensing and acoustic survey, which are neither time- nor cost-effective for vast expanses. The principle of this modelling is the use of a combination of environmental key parameters to produce rules to understand species distribution and hence generate predictive maps. This study focuses on subtidal kelp forests (KF) on the coast of Brittany, France. The most significant key parameters to predict KF frequency are (1) the nature of the substrate, (2) depth, (3) water transparency, (4) water surface temperature and (5) hydrodynamics associated with the flexibility of algae in a flow. All these parameters are integrated in a spatial model, built using a Geographical Information System. This model results in a KF frequency map, where sites with optimum key parameters show a deeper limit of disappearance. After validation, the model is used in the context of Climate Change to estimate the effect of environmental variation on this depth limit of KF. Thus, the effects of both an increase in water temperature and a decrease in its transparency could lead to the complete disappearance of KF.

This study has exploited aerial photographs and LiDAR digital elevation model to quantify intertidal complex landforms volume. A first volume estimation of the main sabellariid polychaete reef complex of the Bay of Mont-Saint-Michel - France is presented. The Sabellaria alveolata is an engineering species that heavily modifies its environment. This gregarious tube-building annelid forms dense and solid reefs of bioclastic coarse sand which can reach several km(2). Since 1970 a very strong decline of reefs has been observed. The authorities have curbed fishing activities without any noticeable changes in reef health status. The S. alveolata reef volume is estimated to be 132 048 m(3) (96 301 m(3) for Sainte-Anne reef and 35 747 m(3) for Champeaux reef). Further LiDAR data surveys will be needed to be able to understand and quantify the accretion/erosion processes in play in the reef dynamic. Because of the internal variability of topographic complexity of the reef, characterized by crevices, cracks, and holes rather than whole blocks, further studies are needed to calculate more accurately the volume of the reef. (C) 2010 Elsevier Ltd. All rights reserved.