Harmful algae blooms (HABs) in coastal marine environments are increasing in number and duration, pressuring local resource managers to implement mitigation solutions to protect human and ecosystem health. However, insufficient spatial and temporal observations create uninformed management decisions. In order to better detect and map blooms, as well as the environmental conditions responsible for their formation, long-term, unattended observation platforms are desired. In this article, we describe a new cost-efficient, autonomous, mobile platform capable of accepting several sensors that can be used to monitor HABs in near real time. The Navocean autonomous sail-powered surface vehicle is deployable by a single person from shore, capable of waypoint navigation in shallow and deep waters, and powered completely by renewable energy. We present results from three surveys of the Florida Red Tide HAB (Karenia brevis) of 2017–2018. The vessel made significant progress toward waypoints regardless of wind conditions while underway measurements revealed patches of elevated chl. a likely attributable to the K. brevis blooms as based on ancillary measurements. Measurements of colored dissolved organic matter (CDOM) and turbidity provided an environmental context for the blooms. While the autonomous sailboat directly adds to our phytoplankton/HAB monitoring capabilities, the package may also help to ground-truth satellite measurements of HABs if careful validation measurements are performed. Finally, several other pending and future use cases for coastal and inland monitoring are discussed. To our knowledge, this is the first demonstration of a sail-driven vessel used for coastal HAB monitoring.
Tools and Data
Most cetacean species are wide-ranging and highly mobile, creating significant challenges for researchers by limiting the scope of data that can be collected and leaving large areas un-surveyed. Aerial surveys have proven an effective way to locate and study cetacean movements but are costly and limited in spatial extent. Here we present a semi-automated pipeline for whale detection from very high-resolution (sub-meter) satellite imagery that makes use of a convolutional neural network (CNN). We trained ResNet, and DenseNet CNNs using down-scaled aerial imagery and tested each model on 31 cm-resolution imagery obtained from the WorldView-3 sensor. Satellite imagery was tiled and the trained algorithms were used to classify whether or not a tile was likely to contain a whale. Our best model correctly classified 100% of tiles with whales, and 94% of tiles containing only water. All model architectures performed well, with learning rate controlling performance more than architecture. While the resolution of commercially-available satellite imagery continues to make whale identification a challenging problem, our approach provides the means to efficiently eliminate areas without whales and, in doing so, greatly accelerates ocean surveys for large cetaceans.
Fishery Improvement Projects (FIPs) are a form of private governance using seafood supply chains to reduce environmental impacts of fishing in some of the most challenged fisheries. Some FIPs are industry-led, others are championed by NGOs. They range across many different fishery types, in both high- and low-income settings. Their diversity is notable, and their proliferation remarkable. This rapid growth suggests FIPs are becoming a key feature of the fisheries governance landscape globally. Based on a global sample of 107 FIPs, we systematically examined their reported actions, the actors involved, and their achievements in terms of policy and practice outputs. The most common actions were dialogues with policy stakeholders, data collection, and educational efforts directed at fishers. Common policy outputs included development of management plans and/or a management body, and rules for limiting entry and increasing compliance. Practice related outputs were dominated by gear changes, and observer and traceability programs. Only crab and lobster FIPs engaged in sustained policy conversations as one of the most common actions. Shrimp and tuna fisheries report more engagement in testing and implementing changes to fishery practices. While supply chain actors are involved in all FIPs, retailers and 1st tier suppliers are relatively absent from FIP activities, and are primarily involved in rallying financial support or some policy engagement. Based on our analysis we discuss the opportunities and challenges FIPs will likely need to engage with to contribute to a global transition to more socially and environmentally sustainable fisheries. We outline key areas where further work is needed to understand how FIPs can improve their contribution to global fisheries governance in the future.
A high-resolution ocean circulation model for the Indian Ocean (IO) using Regional Ocean Modeling System (ROMS) is operational at Indian National Centre for Ocean Information Services (INCOIS) which provides ocean state forecasts for the Bay of Bengal (BoB) and the Arabian Sea (AS) to the Indian Ocean rim countries. To provide an improved estimate of ocean state, a variant of Ensemble Kalman Filter (EnKF), viz., the Local Ensemble Transform Kalman Filter (LETKF) has been developed and interfaced with the present basin-wide operational ROMS. This system assimilates in-situ temperature and salinity profiles and satellite track data of sea-surface temperature (SST). The ensemble members of the assimilation system are initialized with different parameters like diffusion and viscosity coefficients and are subjected to an ensemble of atmospheric fluxes. In addition, one half of the ensemble members respond to K profile parameterization mixing scheme while the other half is subjected to Mellor-Yamada mixing scheme. This strategy aids in arresting the filter divergence which has always been a challenging task. The assimilated system simulates the ocean state better than the present operational ROMS. Improvements permeate to deeper ocean depths with better correlation and reduced root-mean-squared deviation (RMSD) with respect to observations particularly in the northern Indian Ocean which is data rich in density. Analysis shows domain averaged RMSD reduction of about 0.2 - 0.4 °C in sea surface temperature and 2 - 4 cm in sea level anomaly. The assimilated system also manages to significantly improve the thickness of the temperature inversion layers and the duration of its occurrence in northern Bay of Bengal. The most profound improvements are seen in currents, with an error reduction of 15 cm/s in zonal currents of central Bay of Bengal.
Habitat suitability models are being used worldwide to help map and manage marine areas of conservation importance and scientific interest. With groundtruthing, these models may be found to successfully predict patches of occurrence, but whether all patches are part of a larger interbreeding metapopulation is much harder to assert. Here we use a North Atlantic deep-sea case study to demonstrate how dispersal models may help to complete the picture. Pheronema carpenteri is a deep-sea sponge that, in aggregation, forms a vulnerable marine ecosystem in the Atlantic Ocean. Published predictive distribution models from United Kingdom and Irish waters have now gained some support from targeted groundtruthing, but known aggregations are distantly fragmented with little predicted habitat available in-between. Dispersal models were used to provide spatial predictions of the potential connectivity between these patches. As little is known of P. carpenteri’s reproductive methods, twenty-four model set-ups with different dispersal assumptions were simulated to present a large range of potential dispersal patterns. The results suggest that up to 53.1% of the total predicted habitat may be reachable in one generation of dispersal from known populations. Yet, even in the most dispersive scenario, the known populations in the North (Hatton-Rockall Basin) and the South (Porcupine Sea Bight) are predicted to be unconnected, resulting in the relative isolation of these patches across multiple generations. This has implications for Ireland’s future conservation efforts as they may have to conserve patches from more than one metapopulation. This means that conserving one patch may not demographically support the other, requiring additional attentions to ensure that marine protected areas are ecologically coherent and sustainable. This example serves as a demonstration of a combined modeling approach where the comparison between predicted distribution and dispersal maps can highlight areas with higher conservation needs.
The Automatic Identification System (AIS) is a real-time network of transmitters and receivers that allow vessel movements to be broadcast, tracked, and recorded. Though traditionally used for real-time maritime applications related to keeping track of vessel traffic for collision avoidance, there is increasing interest in using AIS data and the AIS platform for maritime safety planning, resource management, and weather forecasting. AIS data are being made tractable for alternative non-real-time applications like determining trends and patterns in vessel traffic and helping to prioritize where modern bathymetric surveys are needed to ensure safe maritime transit. The AIS is also being used for widespread transmission of critical environmental conditions information, such as sea state and weather, to mariners, forecasters, and emergency response providers. Several pilot projects are underway that demonstrate the capacity and promise of AIS data and the AIS platform to serve multiple purposes, providing overall maritime domain awareness while maintaining its most important objective of tracking vessels to aid safe, secure, efficient and environmentally sound maritime operations.
Sea surface temperature (SST) is a fundamental physical variable for understanding, quantifying and predicting complex interactions between the ocean and the atmosphere. Such processes determine how heat from the sun is redistributed across the global oceans, directly impacting large- and small-scale weather and climate patterns. The provision of daily maps of global SST for operational systems, climate modeling and the broader scientific community is now a mature and sustained service coordinated by the Group for High Resolution Sea Surface Temperature (GHRSST) and the CEOS SST Virtual Constellation (CEOS SST-VC). Data streams are shared, indexed, processed, quality controlled, analyzed, and documented within a Regional/Global Task Sharing (R/GTS) framework, which is implemented internationally in a distributed manner. Products rely on a combination of low-Earth orbit infrared and microwave satellite imagery, geostationary orbit infrared satellite imagery, and in situ data from moored and drifting buoys, Argo floats, and a suite of independent, fully characterized and traceable in situ measurements for product validation (Fiducial Reference Measurements, FRM). Research and development continues to tackle problems such as instrument calibration, algorithm development, diurnal variability, derivation of high-quality skin and depth temperatures, and areas of specific interest such as the high latitudes and coastal areas. In this white paper, we review progress versus the challenges we set out 10 years ago in a previous paper, highlight remaining and new research and development challenges for the next 10 years (such as the need for sustained continuity of passive microwave SST using a 6.9 GHz channel), and conclude with needs to achieve an integrated global high-resolution SST observing system, with focus on satellite observations exploited in conjunction with in situSSTs. The paper directly relates to the theme of Data Information Systems and also contributes to Ocean Observing Governance and Ocean Technology and Networks within the OceanObs2019 objectives. Applications of SST contribute to all the seven societal benefits, covering Discovery; Ecosystem Health & Biodiversity; Climate Variability & Change; Water, Food, & Energy Security; Pollution & Human Health; Hazards and Maritime Safety; and the Blue Economy.
Measuring ocean physics and atmospheric conditions at the sea-surface has been taking place for decades in our world’s oceans. Enhancing R&D technologies developed in Federal and academic institutions and laboratories such as WHOI’s Vector Averaging Current Meter (VACM, 1970s) and NOAA – PMEL’s: Autonomous Temperature Line Acquisition System (ATLAS, 1980s) as example, in situ ocean measurements and real-time telemetry for data processing and dissemination from remote areas of oceans and seas are now common place. A transition of this “ocean monitoring” technology has occurred with additional support from individual and group innovative efforts in the field of ocean instrumentation. As a result, long-term monitoring of ocean processes and changes has become more accessible to the research community at large. Here; we discuss a “Hybrid” air-sea interaction deep-sea monitoring system that has been developed in the private sector to mirror ocean-climate community data streams and has been successfully deployed on three basin-scaled programs in the Indian Ocean (RAMA, First Institute of Oceanography, FIO, China), the Andaman Sea (MOMSEI, Monsoon Onset Monitoring, FIO) and the Pacific Ocean (China’s Institute of Oceanology, Academy of Sciences (IOCAS) research in the western tropical Pacific). This application is a base to build upon as new sensors are developed and increased sampling at higher resolutions is required. Surface vehicles measure the surface, with some profiling available. Water column density sampling is still a much-needed measurement within the Ocean Climate Monitoring community. The “Hybrid” is a multidisciplinary tool to integrate new biological and biogeochemical sensors for continued interaction studies of the physical processes of our oceans. This application can also be used at FLUX sites to enhance the Argo Program, telemetry applications and docking stations for autonomous vehicles such as sail-drones, gliders and wave riders for enhancement and contribution to the Global Tropical Moored Buoy Array (GTMBA), Global Ocean Observing System (GOOS), Global Climate Observing System (GCOS), and the Global Earth Observing System of Systems (GEOS).
As the process of urbanization progresses, coastal engineering are posing serious threat to the local ecosystems. The poorly designed coastal engineering will have irreversible effects on local ecosystems, such as the biodiversity declination, the connectivity destruction and the ecosystems deterioration. Therefore, it is very necessary to improve the concept of ecosystem-based coastal engineering design. In strict accordance with the notion of eco-seawall, in this research, the hydrodynamic change in 20 engineering scenarios was discussed and determined the spatial distribution of suitable habitats for aquatic species, which defined as the niche of aquatic organisms in the dimension of hydrodynamic. This research was conducted by carrying out pilot-scale experiment with an aim to enhance the traditional coastal engineering in terms of (a) measuring the intensity of hydrodynamic variations by adding artificial beach or buffer zone (b) determining the overtopping risks in varying working conditions (c) visualizing the distribution of optimal habitat areas with hydrodynamic parameters as eco-niche dimension. As revealed by the results, four working conditions pose low overtopping risk and exhibit uniform distribution of flow (No.1, No.2, No.8 and No.14). Additionally, the suitable habitats distribution have been visualized for 4 types of working condition with safety structure. A conclusion can be drawn that there are significantly fewer unsuitable habitat areas in the No.14 scenario as compared to other schemes. In general, this research is conducive to improving the development of ecosystem-based coastal engineering.
Effective marine spatial planning (MSP) requires evidence-based decision-making processes in order to achieve sustainable use of marine resources and ecosystem services. In accordance with this purpose, decision support tools (DSTs) were used as the primary assistant of planners and managers. As a further step of existing review efforts on DSTs, this research aimed to add value to current knowledge by capturing end user opinions on their applications in MSP processes. For this purpose, perceptions and experiences on tools were acquired using an inclusive questionnaire. In total, 92 MSP experts were reached from 28 countries to collect information on: (i) DST users’ profile; (ii) the contribution of tools in MSP implementation processes, (iii) user opinions and experiences; and (iv) their expectations to draw recommendations and to give insights for future developments. Results revealed that developers should keep tool-user interaction from development to application stage and focus on a publicly accepted MSP working flow. Besides, new efforts on environmental data collection are needed to enable ecosystem-based approach in MSP. Hereby, this research analysed end user perceptions and opinions on DSTs, and it concludes that users require tools providing multi-functionality, integrity and ease of use.