Detecting Mediterranean White Sharks with Environmental DNA

The white shark (Carcharodon carcharias) is a globally distributed, ecologically important top predator whose biology and population dynamics are challenging to study. Basic biological parameters remain virtually unknown in the Mediterranean Sea due to its historically low population density, dwindling population size, and lack of substantial sightings. White sharks are considered Critically Endangered in the Mediterranean Sea, and recent analyses suggest that the population has declined by 52% to 96% from historical levels in different Mediterranean sectors (Moro et al., 2020). Thus, white shark sightings dating back to 1860 are being used to estimate population trajectories throughout the entire region. Though the population size is unknown, remaining individuals are thought to be primarily restricted to a handful of hotspots deemed important for their reproduction and foraging. One of these hypothesized hotspots is the Sicilian Channel, which accounts for 19% of total historical sightings

Modeling aquaculture suitability in a climate change future

Aquaculture has become the primary supplier of fish for human consumption, with production increasing every year since 1990 (FAO, 2020). At the same time, up to 89% of the world’s capture fisheries are fully exploited, overexploited, or collapsed. While some fisheries may have increased yields due to climate change in the short term, global fisheries catch is projected to fall by 10% by 2050 (Barange et al., 2014; Ramos Martins et al., 2021). However, the security of aquaculture production will depend on how future climate change affects productive regions as species’ optimal climatic conditions shift poleward (Chaudhary et al., 2021). This makes the forecasting of climate impacts on key aquaculture species a top priority in order to facilitate adaptation of this industry.info:eu-repo/semantics/publishedVersio

Tide Gauges: From single hazard to multi-hazard warning systems

As the name suggests, tide gauges were originally devised for the singular purpose of monitoring tidal fluctuations in sea level in order to aid safe navigation and port operations. Early tide gauges, such as that used by the famous dockmaster William Hutchinson at Liverpool in the late eighteenth century, consisted of little more than graduated markers on sea walls or posts, against which the sea surface could be measured by eye (Figure 1). These were used to record and then forecast the times and heights of high and low water each day; printed in local tide tables, they provided rudimentary information on variations in the tide

Porcupine Abyssal Plain Sustained observatory monitors the atmosphere to the seafloor on multidecadal timescales

Through international collaborations and advances in technology, ocean observatories are increasingly capable of monitoring over long time periods. The Porcupine Abyssal Plain Sustained Observatory (PAP–SO), located at 4,850 m depth in the Northeast Atlantic, is one of a small number of oceanic sites that has achieved monitoring to full ocean depths over several decades. It has monitored seafloor ecology since 1985, water column particle flux since 1992, and surface ocean and atmosphere parameters since 2003. The observatory is serviced annually, providing the opportunity to carry out conventional ship-based observations, sensor comparison, and sampling

Probabilistic approaches to coastal risk decision-making under future sea level projections

Coastal communities are increasingly threatened by flooding from climate change-induced sea level rise and potential increases in storminess. Informed decisions on risk and resilience related to flood risk need to be made, but the assessment process is complex. It is difficult to bring all of the climate science and sea level rise projections to decision-making, and as a result, decisions are made without a real understanding of the uncertainties involved, a problem magnified the further projections go into the future (Figure 1)

The Global Ocean Observing System: One perspective

This document presents a possible organization for a Global Ocean Observing System (GOOS) within the Intergovernmental Oceanographic Commission and the joint ocean programs with the World Meteorological Organization. The document and the organization presented here is not intended to be definitive, complete or the best possible organization for such an observation program. It is presented at this time to demonstrate three points. The first point to be made is that an international program office for GOOS along the lines of the WOCE and TOGA IPOs is essential. The second point is that national programs will have to continue to collect data at the scale of WOCE plus TOGA and more. The third point is that there are many existing groups and committees within the IOC and joint IOC/WMO ocean programs that can contribute essential experience to and form part of the basis of a Global Ocean Observing System. It is particularly important to learn from what has worked and what has not worked in the past if a successful ocean observing system is to result

Applying OGC sensor web enablement to ocean observing systems

The complexity of marine installations for ocean observing systems has grown significantly in recent years. In a network consisting of tens, hundreds or thousands of marine instruments, manual configuration and integration becomes very challenging. Simplifying the integration process in existing or newly established observing systems would benefit system operators and is important for the broader application of different sensors. This article presents an approach for the automatic configuration and integration of sensors into an interoperable Sensor Web infrastructure. First, the sensor communication model, based on OGC's SensorML standard, is utilized. It serves as a generic driver mechanism since it enables the declarative and detailed description of a sensor's protocol. Finally, we present a data acquisition architecture based on the OGC PUCK protocol that enables storage and retrieval of the SensorML document from the sensor itself, and automatic integration of sensors into an interoperable Sensor Web infrastructure. Our approach adopts Efficient XML Interchange (EXI) as alternative serialization form of XML or JSON. It solves the bandwidth problem of XML and JSON.Peer ReviewedPostprint (author's final draft