Environmental DNA (eDNA) can be a powerful method for assessing the presence and the distribution of aquatic species. We used this tool in order to detect and quantify eDNA from the elusive species Octopus vulgaris, using qPCRs (SybrGreen protocol). We designed species-specific primers, and set up an experimental aquarium approach to validate the new molecular tool in different controlled conditions. Field validation was conducted from sea water samples taken from 8 locations within an octopus fishery area in the Cantabrian Sea during February–March 2016. A significant positive correlation between the total biomass (g of O. vulgaris within thanks) and the amount of O. vulgaris eDNA detected (p-value = 0.01261) was found in aquarium experiments. The species was also detected by PCR in 7 of the 8 water samples taken at sea, and successfully quantified by qPCR in 5 samples. This preliminary study and innovative method opens very promising perspectives for developing quick and cheap tools for the assessment of O. vulgaris distribution and abundance in the sea. The method could help in a close future for quantifying unseen and elusive marine species, thus contributing to establish sustainable fisheries.
Tools and Data
As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances.
Increasing numbers of people are living in and using coastal areas. Combined with the presence of pervasive coastal threats, such as flooding and erosion, this is having widespread impacts on coastal populations, infrastructure and ecosystems. For the right adaptive strategies to be adopted, and planning decisions to be made, rigorous evaluation of the available options is required. This evaluation hinges on the availability and use of suitable datasets. For knowledge to be derived from coastal datasets, such data needs to be combined and analysed in an effective manner. This paper reviews a wide range of literature relating to data-driven approaches to coastal risk evaluation, revealing how limitations have been imposed on many of these methods, due to restrictions in computing power and access to data. The rapidly emerging field of ‘Big Data’ can help overcome many of these hurdles. ‘Big Data’ involves powerful computer infrastructures, enabling storage, processing and real-time analysis of large volumes and varieties of data, in a fast and reliable manner. Through consideration of examples of how ‘Big Data’ technologies are being applied to fields related to coastal risk, it becomes apparent that geospatial Big Data solutions hold clear potential to improve the process of risk based decision making on the coast. ‘Big Data’ does not provide a stand-alone solution to the issues and gaps outlined in this paper, yet these technological methods hold the potential to optimise data-driven approaches, enabling robust risk profiles to be generated for coastal regions.
Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high-resolution imaging and associated machine-learning image-scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free-to-use machine-learning software to semi-automatically generate dense and widespread abundance records of a habitat-forming algae over ~5,000 m2 of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver-based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10–20 transects (50 × 1 m) were required to obtain reliable results. This represents 2–20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine-resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi-automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.
Evidence-based decision making is an essential process for sustainable, effective, and efficient marine spatial planning (MSP). In that sense, decision support tools (DSTs) could be considered to be the primary assistant of planners. Although there are many DSTs listed in tool databases, most of them are conceptual and not used in real MSP implementation. The main objective of this review is to: (i) characterize and analyse the present use of the DSTs in existing MSP implementation processes around the world, (ii) identify weaknesses and gaps of existing tools, and (iii) propose new functionalities both to improve their feasibility and to promote their application. In total, 34 DSTs have been identified in 28 different MSP initiatives with different levels of complexity, applicability and usage purposes. Main characteristics of the tools were transferred into a DST matrix. It was observed that limited functionality, tool stability, consideration of economic and social decision problems, ease of use, and tool costs could be considered as the main gaps of existing DSTs. Future developments are needed and should be in the direction of the specific need of marine planners and stakeholders. Results revealed that DST developments should consider both spatial and temporal dynamics of the ocean, and new tools should provide multi-functionality and integrity; meanwhile they should be easy to use and freely available. Hence, this research summarised current use, gaps, and expected development trends of DSTs and it concludes that there is still a big potential of DST developments to assist operational MSP processes.
Reproducibility has long been a tenet of science but has been challenging to achieve—we learned this the hard way when our old approaches proved inadequate to efficiently reproduce our own work. Here we describe how several free software tools have fundamentally upgraded our approach to collaborative research, making our entire workflow more transparent and streamlined. By describing specific tools and how we incrementally began using them for the Ocean Health Index project, we hope to encourage others in the scientific community to do the same—so we can all produce better science in less time.
The Horizon 2020 COLUMBUS project aims to identify and transfer unexploited knowledge, generated by EU funded science and technology research, to actors with the potential to capitalise on it resulting in measurable value creation. Marine knowledge is generated, to a large extent, through analyses and application of the data and information obtained through monitoring and observation of seas and oceans. The COLUMBUS project is structured around nine areas of competency, or nodes. The Monitoring and Observation node has been focusing on identifying some of the bottlenecks and challenges to greater uptake and application of marine data and information by users, in particular by industry. Building on the knowledge of the partners involved, significant work has been carried out to engage with actors from the private sector, establishing their general and specific needs and to what extent observatories and marine data-sharing initiatives can or should adapt to meet them. This document is based on desk-top research resulting in COLUMBUS Deliverable D4.1, attendance at trade fairs and workshops, one-on-one meetings with representatives from the private sector, a COLUMBUS brokerage event in the context of SeaTech Week (2016) and contributions from partners’ own experience.
A multinational oceanographic and acoustic sea experiment was carried out in the summer of 2014 off the western coast of the island of Sardinia, Mediterranean Sea. During this experiment, an underwater glider fitted with two hydrophones was evaluated as a potential tool for marine mammal population density estimation studies. An acoustic recording system was also tested, comprising an inexpensive, off-the-shelf digital recorder installed inside the glider. Detection and classification of sounds produced by whales and dolphins, and sometimes tracking and localization, are inherent components of population density estimation from passive acoustics recordings. In this work we discuss the equipment used as well as analysis of the data obtained, including detection and estimation of bearing angles. A human analyst identified the presence of sperm whale (Physeter macrocephalus) regular clicks as well as dolphin clicks and whistles. Cross-correlating clicks recorded on both data channels allowed for the estimation of the direction (bearing) of clicks, and realization of animal tracks. Insights from this bearing tracking analysis can aid in population density estimation studies by providing further information (bearings), which can improve estimates.
1. In the Gulf of Aqaba (GoA), coral reefs are considered the dominating ecosystem, while seagrass meadows, recognized worldwide as important ecosystems, have received little attention. Absence of comprehensive seagrass maps limits awareness, evaluations of associated ecosystem services, and implementation of conservation and management tools.
2. Presented here are the first detailed maps of seagrass meadows along the Israeli coast of the northern GoA. Mapping was performed by snorkelling along transects perpendicular to the shore above meadows growing at 15–25 m. Measurements along these transects included position, meadow depth and visual estimations of seagrass cover. Shallow boundaries of meadows, parallel to shore, were recorded by GPS tracking. Supplementary work included drop-camera boat surveys to determine the position of the deeper edge of meadows. In addition, GIS layers were created that indicated shoreline infrastructures, near-shore human activities and potential pollution threats. Ecosystem services of seagrass meadows mapped were valuated using a benefit transfer approach.
3. In total, 9.7 km of the 11 km shoreline were surveyed and 2830 data points collected. Seagrasses were growing along 7.5 km of the shoreline, with shallow (15–25 m) meadows found to cover an area of 707 000 m2 and valued at more than US$ 2 000 000 yr-1 in associated ecosystem services. Pilot drop-camera surveys (additional 283 data points) indicated that meadows can extend down to 50 m in some places. Coastal uses and threats varied in character and location. A municipality runoff point and drainage canal located close to the largest meadow were identified as the main threats to local seagrasses.
4. These low-cost methods enhance our understanding of seagrass distribution in the northern GoA. They demonstrate a GIS-based tool for assessing how environmental changes might affect the cover and state of seagrasses, improving efforts to conserve seagrass, and have particular relevance to seagrass mapping in developing countries and/or island nations.
Fisheries provide nutrition and livelihoods for coastal populations, but many fisheries are fully or over-exploited and we lack an approach for analysing which factors affect management tool performance. We conducted a literature review of 390 studies to assess how fisheries characteristics affected management tool performance across both small-scale and large-scale fisheries. We defined success as increased or maintained abundance or biomass, reductions in fishing mortality or improvements in population status. Because the literature only covered a narrow set of biological factors, we also conducted an expert elicitation to create a typology of broader fishery characteristics, enabling conditions and design considerations that affect performance. The literature suggested that the most commonly used management tool in a region was often the most successful, although the scale of success varied. Management tools were more often deemed successful when used in combination, particularly pairings of tools that controlled fishing mortality or effort with spatial management. Examples of successful combinations were the use of catch limits with quotas and limited entry, and marine protected areas with effort restrictions. The most common factors associated with inadequate biological performance were ‘structural’ issues, including poor design or implementation. The expert-derived typologies revealed strong local leadership, high community involvement and governance capacity as common factors of success across management tool categories (i.e. input, output and technical measures), but the degree of importance varied. Our results are designed to inform selection of appropriate management tools based on empirical data and experience to increase the likelihood of successful fisheries management.