Tools and Data

Granger-causality analysis of integrated-model outputs, a tool to assess external drivers in fishery

Rincón M, Corti R, Elvarsson B, Ramos F, Ruiz J. Granger-causality analysis of integrated-model outputs, a tool to assess external drivers in fishery. [Internet]. 2019 . Available from: https://marxiv.org/zn63y/
Freely available?: 
Yes
Summary available?: 
No
Type: Manuscript

Integrated models are able to combine several sources of data into a single analysis using joint likelihood functions, fostering the consistency of assumptions among analyses and the ability to diagnose goodness of fit and model-misspecification. Owing to their capacity to consistently combine diverse information, integrated models could detect the variability induced by external drivers, such as various environmental drivers, on key components of the stock dynamics (e.g. recruitment) in cases where these external drivers are relevant but not yet identified or incorporated into the modelling exercise. This diagnosing power could then be used to explore causality between fishery dynamics, as estimated by the integrated model, and external drivers. To achieve this aim, a correlation analysis is neither necessary nor sufficient to prove causation. An alternative statistical concept, Granger-causality, provides a framework that uses predictability, rather than correlation, to give more evidence of causation between time-series variables.

A two-step procedure to investigate external forcings in stock dynamics is proposed. First, an integrated model is implemented to detect anomalies that cannot be explained by the internal dynamics of the stock. Then, in a second step, Granger-causality is used to detect the external origin of these anomalies. This two-step procedure is explored using the European anchovy in the Gulf of Cádiz as an example population where the external (environmental) drivers are well documented. The fishery dynamics is first estimated through an age-length model (Gadget). Then Granger-causality is used to assess the predictive power of different environmental drivers on recruitment. The results indicate that this is a powerful procedure, although also with important limitations, to determine predictability and that it can be implemented in a wide variety of stocks and external drivers. Moreover, once Granger-causality has been identified, it is shown that it can be used to forecast by making few modifications of the integrated model used for diagnosis.

Ocean data portals: Performing a new infrastructure for ocean governance

Boucquey N, Martin KSt., Fairbanks L, Campbell LM, Wise S. Ocean data portals: Performing a new infrastructure for ocean governance. Environment and Planning D: Society and Space [Internet]. 2019 :026377581882282. Available from: https://journals.sagepub.com/doi/abs/10.1177/0263775818822829
Freely available?: 
No
Summary available?: 
No
Approximate cost to purchase or rent this item from the publisher: 
US $36.00
Type: Journal Article

We are currently in what might be termed a “third phase” of ocean enclosures around the world. This phase has involved an unprecedented intensity of map-making that supports an emerging regime of ocean governance where resources are geocoded, multiple and disparate marine uses are weighed against each other, spatial tradeoffs are made, and exclusive rights to spaces and resources are established. The discourse and practice of marine spatial planning inform the contours of this emerging regime. This paper examines the infrastructure of marine spatial planning via two ocean data portals recently created to support marine spatial planning on the East Coast of the United States. Applying theories of ontological politics, critical cartography, and a critical conceptualization of “care,” we examine portal performances in order to link their organization and imaging practices with the ideological and ontological work these infrastructures do, particularly in relation to environmental and human community actors. We further examine how ocean ontologies may be made durable through portal use and repetition, but also how such performances can “slip,” thereby creating openings for enacting marine spatial planning differently. Our analysis reveals how portal infrastructures assemble, edit, and visualize data, and how it matters to the success of particular performances of marine spatial planning.

From research to end-users, tracing the path of ocean observations in Australia

Lara-Lopez A, Hodgson-Johnston I, Cahill M, Mancini S, Blain P, Moltmann T. From research to end-users, tracing the path of ocean observations in Australia. Marine and Freshwater Research [Internet]. 2019 . Available from: http://www.publish.csiro.au/MF/MF18066
Freely available?: 
No
Summary available?: 
No
Approximate cost to purchase or rent this item from the publisher: 
US $25.00
Type: Journal Article

The mission of Australia’s Integrated Marine Observing System (IMOS), established under the Federal Government’s national collaborative research infrastructure program, is to deliver ocean observations to the marine and climate science community. However, the observations have many uses, ranging from real-time operational forecasting to understanding of processes and policy decision making. Observations need to be provided in a format that fits the purpose of the intended application. Turning observations into usable data, time series, gridded products and analyses broadens the use of such observations. Value adding by developing products that are relevant to end-user needs and easily accessible to non-scientists is also required as a strategic response to new and emerging socioeconomic, legal and policy priorities. This paper describes some of the pathways on which IMOS observations are being delivered and used in Australia, demonstrating the value that ocean observations have for society.

Zooglider: An autonomous vehicle for optical and acoustic sensing of zooplankton

Ohman MD, Davis RE, Sherman JT, Grindley KR, Whitmore BM, Nickels CF, Ellen JS. Zooglider: An autonomous vehicle for optical and acoustic sensing of zooplankton. Limnology and Oceanography: Methods [Internet]. 2018 . Available from: https://aslopubs.onlinelibrary.wiley.com/doi/full/10.1002/lom3.10301
Freely available?: 
Yes
Summary available?: 
No
Type: Journal Article

We present the design and preliminary results from ocean deployments of Zooglider, a new autonomous zooplankton‐sensing glider. Zooglider is a modified Spray glider that includes a low‐power camera (Zoocam) with telecentric lens and a custom dual frequency Zonar (200 and 1000 kHz). The Zoocam quantifies zooplankton and marine snow as they flow through a defined volume inside a sampling tunnel. Images are acquired on average every 5 cm from a maximum operating depth of ~ 400 m to the sea surface. Biofouling is mitigated using a dual approach: an ultraviolet light‐emitting diode and a mechanical wiper. The Zonar permits differentiation of large and small acoustic backscatterers in larger volumes than can be sampled optically. Other sensors include a pumped conductivity, temperature, and depth unit and chlorophyll a fluorometer. Zoogliderenables fully autonomous in situ measurements of mesozooplankton distributions, together with the three‐dimensional orientation of organisms and marine snow in relation to other biotic and physical properties of the ocean water column. It is well suited to resolve thin layers and microscale ocean patchiness. Battery capacity supports 50 d of operations. Zooglider includes two‐way communications via Iridium, permitting near‐real–time transmission of data from each dive profile, as well as interactive instrument control from remote locations for adaptive sampling.

A novel GIS-based tool for predicting coastal litter accumulation and optimising coastal cleanup actions

Haarr MLarsen, Westerveld L, Fabres J, Iversen KRokkan, Busch KEline Tøn. A novel GIS-based tool for predicting coastal litter accumulation and optimising coastal cleanup actions. Marine Pollution Bulletin [Internet]. 2019 ;139:117 - 126. Available from: https://www.sciencedirect.com/science/article/pii/S0025326X18308762
Freely available?: 
No
Summary available?: 
No
Approximate cost to purchase or rent this item from the publisher: 
US $39.95
Type: Journal Article

Effective site selection is a key component of maximising debris removal during coastal cleanup actions. We tested a GIS-based predictive model to identify marine litter hotspots in Lofoten, Norway based on shoreline gradient and shape. Litter density was recorded at 27 randomly selected locations with 5 transects sampled in each. Shoreline gradient was a limiting factor to litter accumulation when >35%. The curvature of the coastline correlated differently with litter density at different spatial scales. The greatest litter concentrations were in small coves located on larger headlands. A parsimonious model scoring sites on a scale of 1–5 based on shoreline slope and shape had the highest validation success. Sites unlikely to have high litter concentrations were successfully identified and could be avoided. The accuracy of hotspot identifications was more variable, and presumably more parameters influencing litter deposition, such as shoreline aspect relative to prevailing winds, should be incorporated.

Geovisualization tools to inform the management of vessel noise in support of species' conservation

Cominelli S, Leahy M, Devillers R, Hall BG. Geovisualization tools to inform the management of vessel noise in support of species' conservation. Ocean & Coastal Management [Internet]. 2019 ;169:113 - 128. Available from: https://www.sciencedirect.com/science/article/pii/S0964569118302643
Freely available?: 
No
Summary available?: 
No
Approximate cost to purchase or rent this item from the publisher: 
US $35.95
Type: Journal Article

The growth of global ocean noise recorded over the past decades is increasingly affecting marine species and requires assessment on the part of marine managers. We present a framework for the analysis of species' exposure to noise from shipping. Integrated into a set of geovisualization tools, our approach focuses on exposure hotspot mapping, on the computation of probabilistic levels of exposure, and on the identification of shipping routes that minimize exposure levels for Cetacean species. The framework was applied to estimate noise exposure for the Southern Resident Killer Whale (SRKW) population, and for the exploration of possible ship traffic displacement scenarios in the Salish Sea, British Columbia. Four noise exposure hotspots were identified within the SRKW's core habitat. Exposure over these areas was mainly produced by six vessel classes, namely Ferries, Tugboats, Recreational Vessels, Vehicle Carriers, Containers, and Bulkers. Exposure levels showed variability across hotspots suggesting that a fine-scale spatial dimension should be included in the design of noise pollution mitigation strategies for the Salish Sea. The scenarios suggest that small changes in the current shipping lanes (3.4% increase in traveled distance) can lead to a 56% reduction of the overlap between vessel traffic and sensitive areas for SRKW.

A supporting marine information system for maritime spatial planning: The European Atlas of the Seas

Barale V. A supporting marine information system for maritime spatial planning: The European Atlas of the Seas. Ocean & Coastal Management [Internet]. 2018 ;166:2 - 8. Available from: https://www.sciencedirect.com/science/article/pii/S0964569118301911
Freely available?: 
Yes
Summary available?: 
No
Type: Journal Article

The European Atlas of the Seas is a web-based coastal and marine information system, originally aimed at the general public, but capable also of supporting non-specialist professionals in addressing environmental matters, human activities and management policies related to the sea. It is based on a combination of data (and metadata), which present a snapshot of both natural and socio-economic elements of coastal and marine regions in the European Union and its Outermost Regions. The first idea of a European Atlas of the Seas was set forward in 2007 with the launch of the Integrated Maritime Policy for the European Union. Early work on the Atlas was conducted by the Directorate General for Maritime Affairs of the European Commission, while further development of system architecture, data collection, map services and descriptive text was assigned in 2013 to the Joint Research Centre, with the aim to offer new services and features, as well as the interaction with other available information tools. The present European Atlas of the Seas consists of background data layers designed to be displayed as map backdrop, as well as a number of thematic data layers, classified under 8 main categories: geography, nature, tourism, security and safety, people and employment, transport and energy, governance and European policies, fisheries and aquaculture. These can be used to compose customized maps, as user-defined ad hoc indicators, and to probe them with tools such as product-to-product correlations, or time series visualisation. Non-specialist professional users can use such analysis and interpretation capabilities to couple data into ecological and socio-economic indicators for a wide range of applications. The thematic map collection provided a common baseline that can be used by Member States of the European Union in getting started with the Maritime Spatial Planning Directive requirements. As this is seen as a pre-requisite for Blue Growth, the European Atlas of the Seas will help the sustainable use of marine ecosystem services and resources.

Shaping sustainability of seafood from capture fisheries integrating the perspectives of supply chain stakeholders through combining systems analysis tools

Hornborg S, Hobday AJ, Ziegler F, Smith ADM, Green BS. Shaping sustainability of seafood from capture fisheries integrating the perspectives of supply chain stakeholders through combining systems analysis tools. ICES Journal of Marine Science [Internet]. 2018 . Available from: https://academic.oup.com/icesjms/article/75/6/1965/5056868
Freely available?: 
Yes
Summary available?: 
No
Type: Journal Article

Seafood from capture fisheries can be assessed in many ways and for different purposes, with sometimes divergent views on what characterizes “sustainable use”. Here we use two systems analysis tools—Ecological Risk Assessment for Effects of Fishing (ERAEF) and Life Cycle Assessment (LCA)—over the historical development of the Australian Patagonian toothfish fishery at Heard and McDonald Islands since the start in 1997. We find that ecological risks have been systematically identified in the management process using ERAEF, and with time have been mitigated, resulting in a lower risk fishery from an ecological impact perspective. LCA inventory data from the industry shows that fuel use per kilo has increased over the history of the fishery. Our results suggest that LCA and ERAEF may provide contrasting and complementary perspectives on sustainability and reveal trade-offs when used in combination. Incorporation of LCA perspectives in assessing impacts of fishing may facilitate refinement of ecosystem-based fisheries management, such as improved integration of the different perspectives of supply chain stakeholders.

MAIA—A machine learning assisted image annotation method for environmental monitoring and exploration

Zurowietz M, Langenkämper D, Hosking B, Ruhl HA, Nattkemper TW. MAIA—A machine learning assisted image annotation method for environmental monitoring and exploration Sarder P. PLOS ONE [Internet]. 2018 ;13(11):e0207498. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0207498
Freely available?: 
Yes
Summary available?: 
No
Type: Journal Article

Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mobile platforms such as autonomous underwater vehicles (AUVs) are now equipped with high-resolution cameras to capture huge collections of images from the seabed. However, the timely evaluation of all these images presents a bottleneck problem as tens of thousands or more images can be collected during a single dive. This makes computational support for marine image analysis essential. Computer-aided analysis of environmental images (and marine images in particular) with machine learning algorithms is promising, but challenging and different to other imaging domains because training data and class labels cannot be collected as efficiently and comprehensively as in other areas. In this paper, we present Machine learning Assisted Image Annotation (MAIA), a new image annotation method for environmental monitoring and exploration that overcomes the obstacle of missing training data. The method uses a combination of autoencoder networks and Mask Region-based Convolutional Neural Network (Mask R-CNN), which allows human observers to annotate large image collections much faster than before. We evaluated the method with three marine image datasets featuring different types of background, imaging equipment and object classes. Using MAIA, we were able to annotate objects of interest with an average recall of 84.1% more than twice as fast as compared to “traditional” annotation methods, which are purely based on software-supported direct visual inspection and manual annotation. The speed gain increases proportionally with the size of a dataset. The MAIA approach represents a substantial improvement on the path to greater efficiency in the annotation of large benthic image collections.

Knowledge integration in Marine Spatial Planning: A practitioners' view on decision support tools with special focus on Marxan

Janßen H, Göke C, Luttmann A. Knowledge integration in Marine Spatial Planning: A practitioners' view on decision support tools with special focus on Marxan. Ocean & Coastal Management [Internet]. 2019 ;168:130 - 138. Available from: https://www.sciencedirect.com/science/article/pii/S0964569118304277
Freely available?: 
Yes
Summary available?: 
No
Type: Journal Article

Modern ecosystem-based forms of marine management such as Marine Spatial Planning(MSP) deal with various complex systems and often with huge amounts of data. Software-based simulative and analytical tools are therefore frequently mentioned in the scientific literature on marine management approaches. But in addition to the evolution of management approaches, the requirements for more integrated tools are also progressing. MSP, for instance, comes with different spatial resolutions, an increased need to consider multiple interdepencies, and increased requirements for validity than most of the previous marine management questions. We reviewed seven well-known Decision Support Tools (DSTs) by asking 59 MSP practitioners from at least 25 countries worldwide about their experience with these tools. The results revealed that, while respondents were mostly positive about the use of DSTs in MSP processes, DSTs are still mainly used in the academic realm and have not yet found their way into everyday MSP practice. There is a broad range of reasons for not using DSTs, including the complexity of these tools, the resources required to operate them, low stakeholder confidence in DST outcomes, and the lack of additional value in using DSTs.

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