Chapter Artificial reef along theFrench Mediterranean coastline: toward innovative integrated biodiversity management

Coastal zones are subjected to human pressure and it is necessary to protect and manage these productive and sensitive ecosystems. Artificial Reefs (AR) are relevant tools to overcome these challenges. For nearly a decade they have been used in ecological engineering in order to restore specific habitat functionalities. In the meantime, they are also employed to manage human activities. The review of the latest projects on the French Mediterranean coast shows that apart from the ecological objectives, AR are also social tools that could help to enlarge an integrated approach of an ecosystem

Seasonality in coastal macrobenthic biomass and its implications for estimating secondary production using empirical models

Macrobenthic secondary production is widely used to assess the trophic capacity, health, and functioning of marine and freshwater ecosystems. Annual production estimates are often calculated using empirical models and based on data collected during a single period of the year. Yet, many ecosystems show seasonal variations. Although ignoring seasonality may lead to biased and inaccurate estimates of annual secondary production, it has never been tested at the community level. Using time series of macrobenthic data collected seasonally at three temperate marine coastal soft-bottom sites, we assessed seasonal variations in biomass of macrobenthic invertebrates at both population and community levels. We then investigated how these seasonal variations affect the accuracy of annual benthic production when assessed using an empirical model and data from a single sampling event. Significant and consistent seasonal variations in biomass at the three study sites were highlighted. Macrobenthic biomass was significantly lower in late winter and higher in summer/early fall for 18 of the 30 populations analyzed and for all three communities studied. Seasonality led to inaccurate and often biased estimates of annual secondary production at the community level when based on data from a single sampling event. Bias varied by site and sampling period, but reached similar to 50% if biomass was sampled at its annual minimum or maximum. Since monthly sampling is rarely possible, we suggest that ecologists account for uncertainty in annual production estimates caused by seasonality.Agência financiadora EDF French Ministry of Higher Education, Research and Innovation French Ministry for the Ecological and Inclusive Transition through the Marine Strategy Framework Directive Agreement French Biodiversity Agency (Agence francaise pour la biodiversite) as part of the CAPANOUR projectinfo:eu-repo/semantics/publishedVersio

A Comparison of Two Biotic Indices, AMBI and BOPA/BO2A, for assessing the Ecological Quality Status (EcoQS) of Benthic Macro-invertebrates

1. The assessment of quality status of Transitional Aquatic Ecosystems remains a challenge for the ecologists. 2. Here, we compared the results of two common indices (AMBI - Ecological Groups and BOPA/BO2A -Taxonomic Sufficiency) from samples coming from the north-eastern Atlantic and Mediterranean Sea. Both biotic indices rely on distinct assessments of species sensitivity/tolerance. 3. Six studies provided the raw data that permitted AMBI and BOPA to be compared. A total 922 data element was available, most of them from the Seine estuary (78%). The database was later divided into three sub-sets: French Atlantic Transitional Waters, Mediterranean Coastal Waters and Mediterranean Lagoons. 4. Both indices' values demonstrated a strong correlation; however, the BOPA index had a tendency to overestimate the EcoQS compared to the values obtained from AMBI index, mainly due to discrepancies between ‘high’ and ‘good’ quality. 5. New thresholds for BOPA/BO2A index are proposed in order to reduce this overestimation

Eulerian Pressure-Velocity/ Lagrangian Vorticity-Velocity Coupling Applied to Wake and Forces Calculation of Biofouled Tidal Turbines

Marine tidal turbines are subject to the environment in which they are deployed. In the natural environment, they are gradually colonized by sessile species. These fouling organisms modify the flow around the blades and in the wake of the tidal turbine. Unfortunately, they also complicate the numerical study of such tidal turbines by preventing the use of usual methods such as the Blade Element Method or the Lifting Line Theory. In this context, we propose to use an alternative solution, which combines an Eulerian code to study the near field with a Lagrangian code for the wake. After a short presentation of each code, the coupling method is detailed, and applied to the case of a tidal turbine with its own vertical axis. First results are shown and compared to a full Eulerian simulation. Although the data transmission between both codes works well, discrepancies were found due to abnormal increase of energy in the Lagrangian area. A solution is proposed and explained

Influence of the turbulent wake downstream offshore wind turbines on larval dispersal: development of a new Lagrangian-Eulerian model

In the context of future offshore wind farms along the French coasts of the English Channel, the impacts of foundations on larval dispersal from bentho-pelagic species colonizing the hard substratum of artificial structures are studied in order to assess how the species connectivity could be modified by the farms. In particular, the effects of turbulent wake and horseshoe vortices are investigated. To this end, a new numerical approach is developed that combines the Eulerian model, OpenFoam, solving the 3D Navier-Stokes equations to compute the hydrodynamics, and the Lagrangian model, Ichthyop, based on an advection-diffusion equation to compute the larval trajectories. Firstly, some simple test cases are performed to validate the numerical coupling between OpenFoam and Ichthyop, such as the dispersion of larvae downstream a 2D cylinder in water. Secondly, the ability of OpenFoam turbulence models to simulate turbulent structures around monopile and gravity type foundations is evaluated. The RANS (Reynolds Averaged Navier-Stokes) k-omega SST turbulence model is chosen for the realistic application because it can reproduce the horseshoe vortices and turbulent wake with less computing time than the Smagorinsky LES (Large Eddy Simulation) model. Lastly, larval dispersal simulations for four benthic species and for a set of monopile and gravity foundations are performed

Turning off the DRIP (‘Data-rich, information-poor’) – rationalising monitoring with a focus on marine renewable energy developments and the benthos

Marine renewable energy developments (MREDs) are rapidly expanding in size and number as society strives to maintain electricity generation whilst simultaneously reducing climate-change linked CO2 emissions. MREDs are part of an ongoing large-scale modification of coastal waters that also includes activities such as commercial fishing, shipping, aggregate extraction, aquaculture, dredging, spoil-dumping and oil and gas exploitation. It is increasingly accepted that developments, of any kind, should only proceed if they are ecologically sustainable and will not reduce current or future delivery of ecosystem services. The benthos underpins crucial marine ecosystem services yet, in relation to MREDs, is currently poorly monitored: current monitoring programmes are extensive and costly yet provide little useful data in relation to ecosystem-scale-related changes, a situation called ‘data-rich, information-poor’ (DRIP). MRED –benthic interactions may cause changes that are of a sufficient scale to change ecosystem services provision, particularly in terms of fisheries and biodiversity and, via trophic linkages, change the distribution of fish, birds and mammals. The production of DRIPy data should be eliminated and the resources used instead to address relevant questions that are logically bounded in time and space. Efforts should target identifying metrics of change that can be linked to ecosystem function or service provision, particularly where those metrics show strongly non-linear effects in relation to the stressor. Future monitoring should also be designed to contribute towards predictive ecosystem models and be sufficiently robust and understandable to facilitate transparent, auditable and timely decision-making