Hydrodynamic Ocean Circulation Models and Lagrangian particle tracking models are valuable tools e.g. in coastal ecology to identify the connectivity between offshore spawning and coastal nursery areas of commercially important fish, for risk assessment and more for defining or evaluating marine protected areas. Most studies are based on only one model and do not provide levels of uncertainty. Here this uncertainty was addressed by applying a suite of 11 North Sea models to test what variability can be expected concerning connectivity. Different notional test cases were calculated related to three important and well-studied North Sea fish species: herring (Clupea harengus), and the flatfishes sole (Solea solea) and plaice (Pleuronectes platessa). For sole and plaice we determined which fraction of particles released in the respective spawning areas would reach a coastal marine protected area. For herring we determined the fraction located in a wind park after a predefined time span. As temperature is more and more a focus especially in biological and global change studies, furthermore inter-model variability in temperatures experienced by the virtual particles was determined. The main focus was on the transport variability originating from the physical models and thus biological behavior was not included. Depending on the scenario, median experienced temperatures differed by 3. °C between years. The range between the different models in one year was comparable to this temperature range observed between modelled years. Connectivity between flatfish spawning areas and the coastal protected area was highly dependent on the release location and spawning time. No particles released in the English Channel in the sole scenario reached the protected area while up to 20 of the particles released in the plaice scenario did. Interannual trends in transport directions and connectivity rates were comparable between models but absolute values displayed high variations. Most models showed systematic biases during all years in comparison to the ensemble median, indicating that in general interannual variation was represented but absolute values varied. In conclusion: variability between models is generally high and management decisions or scientific analysis using absolute values from only one single model might be biased and results or conclusions drawn from such studies need to be treated with caution. We further concluded that more true validation data for particle modelling are required. © 2017 Elsevier B.V

In response to climate change, the expansion of renewable energies leads to an increasing number of offshore wind farms in the North Sea. This comes along with an increase in (artificial) hard substrates in a mainly soft-bottom dominated marine area with so far largely unknown consequences for the underlying ecosystem functioning. We used a large combined dataset (both hard- and soft-substrate data) to model the secondary production of fouling communities on turbine foundations and of soft-bottom fauna inside and outside offshore wind farms (OWF) in the southern North Sea (Belgium, the Netherlands, Germany). We demonstrate that (1) a large amount of energy is channelled through fouling fauna on turbines (i.e., secondary production of fouling communities was on average 80 times higher than of soft-substrate communities), (2) 71 % of fouling production on turbines is released to the surrounding sediment (annual release: -221 ± 825 gC m^-2 y^-1 (SD)), and that (3) local production of soft-bottom communities is elevated up to a distance of 150-250 m from turbines. Production impacted area (PIA) was determined from hard- and soft-substrate data independently: mechanistic modelling of hard-substrate production export showed a production increase of 5 % up to 150 m from the turbine and generalised additive mixed models (GAMMs) based on soft-bottom fauna data suggested an elevated production up to 250 m from turbines. Accordingly, on the scale of an OWF (distance between turbines ∼1000 m), the local production "halo" effect around turbines affects about 11 % of an OWF area (dependent on OWF configuration). The observed changes in benthic energy flow may lead to so far unknown changes at the ecosystem level from plankton communities to apex predators.

The purpose of this work was to investigate the physical and chemical dynamics of Lake Nokoué for its efficient management. For this purpose, two sampling campaigns per month from five stations (North, South, Central, East and West) were conducted for a period of one year (November 2020 to November 2021). Physic and chemical parameters (temperature, salinity, depth, water transparency, pH, dissolved oxygen and total dissolved solids) were measured and wet substrate samples were collected to study the granulometry. Data analysis revealed that Lake Nokoué is mainly affected by two regimes: flooding and low water. Flooding, which is not directly related to rainfall, did not begin until one month after the major rainy season in June. The sources that contributed to the flooding of Lake Nokoué were the freshwater tributaries coming mainly from the Ouèmé River and the flow of the Sô River from August to November. The inflow of fresh water contributed to the decrease in salinity and transparency of the lake from the east to the south. During the low water period (from December to July), Lake Nokoué is characterized by an increase in salinity and transparency from the south to the northeast due to the massive intrusion of sea water into the lake. The highest dissolved oxygen levels are observed in the south and center (5.92 ± 0.46 mg/L) while it varies greatly in the north and west (Eichhornia crassipes concentration zone) during flooding. The average annual depth of Lake Nokoué was 1.47 ± 0.66 m with an average annual pH of 6.85 ± 0.56.

Organism movement is a key process in the transfer of individuals, genes, functional traits, matter, and energy among habitat patches, at sea and across the land–sea interface. The resulting fluxes, collectively termed marine functional connectivity (MFC), underpin planetary health and an array of ecosystem services. The ecological and economic impacts of rapid environmental change, including climate change, overexploitation, habitat loss and fragmentation, and the global transport of nonindigenous species make accurate estimation and prediction of MFC patterns paramount. However, estimating MFC is challenging given the relative inaccessibility of the oceans and the small size of many of the organisms and life stages with the highest dispersal potential. Here, we provide a methodological roadmap to help researchers and stakeholders understand, use, and integrate different tools to estimate organism movement and connectivity, focusing on (1) tagging and telemetry, (2) analysis of chemical markers in body tissues and structures, (3) genetics, and (4) numerical modeling. We describe method strengths and weaknesses, and the spatiotemporal resolution and scale of resulting connectivity estimates. Ancillary and emerging methods to estimate MFC are also reviewed. We then present case studies that have successfully applied or integrated different methods, particularly to support (1) marine protected area design, (2) global change predictions, focusing on climate change and bioinvasions, and (3) fisheries management. Finally, we highlight methodological innovations and concepts that promise to transform MFC research in the future.