Agent Based Modelling (ABM) of eelgrass ( Zostera marina ) seedbank dynamics in a shallow Danish estuary

A network analysis of connected biophysical pathways to advice eelgrass (Zostera marina) restoration

The North Sea and the Baltic Sea, including Danish coastal waters, have experienced a drastic decline in eelgrass Zostera marina coverage during the past century. Around 1900, eelgrass meadows covered about 6700 km² of Danish coastal waters while the current potential distribution area is only about one third of this. In some areas, the potential distribution area is far from realized, and restoration efforts are needed to assist recovery. Such efforts are challenging, and resource-demanding and careful site selection is, therefore, important. In the present study, we aim to identify the connectivity of eelgrass populations as a basis for guiding site selection for restoration. We developed a coupled biophysical model to study eelgrass dispersal in the Kattegat. Partly submerged particles simulated the dispersal of reproductive eelgrass shoots containing seeds during the flowering season July-September. We then used network analysis to identify the potential connectivity between populations. We evaluated connectivity based on In-strength, Betweenness and Eigenvector centrality metrics and identified key areas in the Kattegat such as the central part of Aalborg Bay, to be considered to restore the network of Z. marina patches. The study proves the potentials of combining hydrodynamic models and network analysis to support marine conservation and planning, and highlights the importance of collaboration between ecologists, oceanographers, and practitioners in this endeavour.

Adaptive intertidal seed-based seagrass restoration in the Dutch Wadden Sea

Seagrasses form the foundation of many coastal ecosystems but are rapidly declining on a global scale. The Dutch Wadden Sea once supported extensive subtidal seagrass meadows that have all disappeared. Here, we report on the setbacks and successes of intertidal seed-based restoration experiments in the Dutch Wadden Sea between 2014-2017. Our main goals were to 1) optimize plant densities, and 2) reduce seed losses. To achieve our goals, we conducted research-based, adaptive seagrass (Zostera marina) restoration, adjusting methods yearly based on previous results. We applied various seeding methods in three subsequent years-from Buoy Deployed Seeding (BuDS), and 'BuDS-in-frame' in fall, to a newly developed 'Dispenser Injection Seeding' (DIS) method. Our adaptive experimental approach revealed high seed losses between seeding and seedling establishment of the BuDS methods (>99.9%), which we mitigated by controlled harvest and storage of seeds throughout fall and winter, followed by DIS-seeding in spring. These iterative innovations resulted in 83 times higher plant densities in the field (0.012 to 1.00 plants m-2) and a small reduction in seed loss (99.94 to 99.75%) between 2015-2017. Although these developments have not yet resulted in self-sustaining seagrass populations, we are one step closer towards upscaling seagrass restoration in the Dutch Wadden Sea. Our outcomes suggest that an iterative, research-based restoration approach that focuses on technological advancement of precision-seeding may result in advancing knowledge and improved seed-based seagrass restoration successes.

Water quality prospective in Twenty First Century: Status of water quality in major river basins, contemporary strategies and impediments: A review

Water quality improvement is one of the top priorities in the global agenda endorsed by United Nation. In this review manuscript, a holistic view of water quality degradation such as concerned pollutants, source of pollution, and its consequences in major river basins around the globe (at least 1 from each continent and a total of 16 basins) is presented. Additionally, nine contemporary techniques such as field scale evaluation, watershed scale evaluation, strategies to identify critical source areas, optimization strategies for placement of best management practices (BMPs), social component in watershed modeling, machine learning algorithms to address water quality problems in complex natural systems concomitant with spatial heterogeneity, establishing a total maximum daily loads (TMDLs), remote sensing in monitoring water quality, and developing water quality index are discussed. Next, the existing barriers to improve water quality are classified into primary and secondary impediments. A detail discussion of three primary impediments (climate change, urbanization and industrial activities, and agriculture) and ten secondary impediments (availability of water quality data, complexity of system, lack of skilled person, environmental legislation, fragmented mandate, limitation in resources, environmental awareness, resistance to change, alteration of nutrient ratio by river damming, and emerging pollutants) are illustrated. Finally, considering all the existing knowledge gaps pertaining to contemporary strategies, a future direction of water quality research is outlined to significantly improve the water quality around the globe.

Integrating genetics, biophysical, and demographic insights identifies critical sites for seagrass conservation

The eelgrass Zostera marina is an important foundation species of coastal areas in the Northern Hemisphere, but is continuing to decline, despite management actions. The development of new management tools is therefore urgent in order to prioritize limited resources for protecting meadows most vulnerable to local extinctions and identifying most valuable present and historic meadows to protect and restore, respectively. We assessed 377 eelgrass meadows along the complex coastlines of two fjord regions on the Swedish west coast-one is currently healthy and the other is substantially degraded. Shoot dispersal for all meadows was assessed with Lagrangian biophysical modeling (scale: 100-1,000 m) and used for barrier analysis and clustering; a subset (n = 22) was also assessed with population genetic methods (20 microsatellites) including diversity, structure, and network connectivity. Both approaches were in very good agreement, resulting in seven subpopulation groupings or management units (MUs). The MUs correspond to a spatial scale appropriate for coastal management of "waterbodies" used in the European Water Framework Directive. Adding demographic modeling based on the genetic and biophysical data as a third approach, we are able to assess past, present, and future metapopulation dynamics to identify especially vulnerable and valuable meadows. In a further application, we show how the biophysical approach, using eigenvalue perturbation theory (EPT) and distribution records from the 1980s, can be used to identify lost meadows where restoration would best benefit the present metapopulation. The combination of methods, presented here as a toolbox, allows the assessment of different temporal and spatial scales at the same time, as well as ranking of specific meadows according to key genetic, demographic and ecological metrics. It could be applied to any species or region, and we exemplify its versatility as a management guide for eelgrass along the Swedish west coast.

Bioremediation potential of waste biomaterials originating from coastal Zostera marina L. meadows for polluted aqueous media with industrial effluents

The studies on novel and efficient biosorbent materials for the promotion of environmental and economic sustainability have been become an up-to-date attempt by scientists for the removal of synthetic dyes from industrial effluents. The biosorbents prepared from biomass based resources are emerging as an alternative promising material for the environmental clean-up because of their low-cost, renewability, eco-friendly, easy availability and so forth characteristics. Hence, for the first time, the biosorption performance of abundantly available natural biowastes originating from coastal Zostera marina L. meadows was explored for the biotreatment of colored industrial effluents in the present study. The biosorption properties of biosorbent for methylene blue as a representative synthetic industrial dye were investigated by means of the operational parameters optimization, kinetic, isotherm, thermodynamic and characterization studies. The operating conditions significantly affected the biosorption process and the optimal values were determined as pH of 8, biosorbent dosage of 10 mg, dye concentration of 15 mg L^-1 and contact time of 120 min. Elovich and Freundlich models provided the best fit to the kinetic and isotherm data compared with other applied models, respectively. The negative change in free energy (-10.682 to -8.466 kJ mol^-1) indicated a thermodynamically feasible and spontaneous process. The characterization analysis showed that the biosorbent has appropriate chemical and physical properties for the dye biosorption. Thus, the present study displayed that the waste materials originating from coastal Z. marina L. meadows can be applied as a highly efficient as well as cost-effective green generation biosorbent for the clean-up of colored aquatic media.