Mapping whale-watching effort using AIS data in the Salish Sea

Commercial boat-based whale-watching is a very important touristic sector in the Salish Sea, taking thousands of people to view and experience up close the natural beauty and wildlife of the area. This sector provides economic benefits to local communities and opportunities for education and increase awareness for nature protection. The recent growth of whale-watching activities also can bring potential negative effects such as disturbances to wildlife. To achieve a sustainable commercial whale-watching sector, it is important to gain a good understanding of the footprint this activity has on the marine environment. For this, we assessed the spatio-temporal distribution of whale watching activities and their overlap with sensitive ecological areas. First, we developed an algorithm that classifies Automatic Identification System (AIS) vessel data from known commercial whale-watching vessels into wildlife viewing and transiting positions based on vessel speeds. Data analysed included AIS data collected in 2018, 2019, 2020 and 2021 in the Salish Sea. Wildlife viewing positions were used to estimate whale-watching effort based on the cumulative time whale-watching vessels spend wildlife viewing in a location. We then used marine protected areas and other area-based conservation measures to determine the degree of overlap between whale watching effort and ecologically sensitive areas. Results show areas consistently visited by whale-watching vessels during the study period, while other whale-watching hotspots are more dynamic and vary depending on the time of the year and targeted species. We conclude that the presented methodology applied to AIS data can provide a valuable tool to assess whale-watching activities and their potential effect to coastal environments

Quantifying marine vessel traffic from aerial surveys in the Salish Sea

There are a number of potential impacts associated with vessel traffic on marine ecosystems, including noise and oil pollution, ship-strikes, and fishing and fisheries bycatch. To assess these impacts, many studies employ marine traffic data collected using Automatic Identification Systems (AIS) onboard vessels. However, AIS only captures a fraction of the actual marine traffic because it omits many of the smaller vessels, which are not legally required to carry AIS. Without this information, the assessment of vessel-associated impacts based on AIS is inherently flawed, and underestimated. The NEMES (Noise Exposure to the Marine Environment from Ships) project is particularly interested in this unknown component of marine traffic as non-AIS vessels are likely contributing a considerable amount of noise in the Salish Sea. With the assistance of the National Aerial Surveillance Program (NASP), we have been collecting vessel traffic information for both AIS and non-AIS vessels during two years (2016, 2017) in parts of the Salish Sea. The AIS receiver and sensors onboard the NASP aircraft can collect AIS information and video with positional information of target objects such as vessels. The video also allows the characterization of the vessel type (e.g., sailboat, motorboat, fishing vessel) and vessel activity (i.e., fishing, motoring or sailing). Results indicate that non-AIS vessels contribute at least 60% of the overall vessel traffic in surveyed areas between 2016 and 2017. The majority of these non-AIS vessels are recreational vessels, particularly during the summer months and near popular touristic destinations such as the Southern Gulf Islands. Through this work, we are now able to build a more complete picture of the distribution and type of vessels using the Salish Sea, and have a better understanding of their potential impacts to the marine ecosystem

Capturing Information on Vessels and Cetaceans: developing a passive monitoring system for Boundary Pass

As marine traffic intensifies in the Salish Sea, cetaceans, and in particular, Southern Resident Killer Whales (SRKWs), are continually facing increasing amounts of exposure to noise and other disturbances from movements of vessels. While the majority of large vessel activity can be captured and assessed through the use of Automatic Identification Systems (AIS), the contribution of smaller non-AIS vessels is difficult to quantify and currently largely under assessed. Increasingly, government and industry are required to take operational and strategic mitigation measures to minimise vessel disturbances on cetaceans without reliable, comprehensive data and analysis to inform those decisions. Therefore this work focuses on filling these gaps by collecting information on both non-AIS vessels and the presence of marine mammal (including SRKW) within Boundary Pass) using three passive forms of data collection: an AIS receiver, hydrophones and a land-based camera. This talk describes an outline of the camera work being undertaken, from the design stages to installation. It will highlight some of the initial findings from the early analysis work along with some of the challenges and limitations of this type of data. Additionally, acoustic data on cetaceans in Boundary Pass will also be presented. Unlike the camera this form of passive monitoring is only able to capture the presence of cetaceans when they are vocalizing. Evidence already exists to suggest that some species reduce their rate of vocalization in the presence of vessels (and their associated noise). Therefore, integration of both acoustic and visual data will enable us to build a more complete picture of cetacean habitat use and the relationship between vessels and cetaceans in Boundary Pass. Furthermore, the information obtained through analysis of this data is also particularly important for informing models that aim to assess the level of vessel disturbance cetaceans are subjected to

Mitigation of Marine Noise through Strategic Planning, Conservation and Management Support: the effective use of knowledge exchange to aid decision making.

Concerns are being raised over the growing evidence documenting impacts of ship-source marine noise on marine species. Anthropogenic noise can affect marine organisms in a range of ways including ‘masking’ of animals own vocalisations used for communication, navigation, foraging and hazard avoidance which can lead to increased stress, disturbance, deafness and mortalities. Increasingly, calls are being made for noise mitigation strategies and management frameworks to be put in place. One of the proposed possible mechanisms by which to translate this concept of noise management has been through the use of Marine Spatial Planning (MSP) and Marine Protected Area (MPA) initiatives. However, the importance of MPAs and their effectiveness as a management tool for helping to mitigate underwater noise, in conjunction with their integration within a broader MSP approach, has as yet not been investigated, therefore further exploration and analysis is both pertinent and essential. This research considers the study areas employed by three previous MEOPAR projects (NEMES, WHaLE and 3MTSim) however for the purposes of spatial analysis work and coordinating outreach activities the focus of this project is on waters within British Columbia, and in particular the Salish Sea. This work also considers how the outputs from these projects together with end-user knowledge can be used to further inform marine management and conservation objectives. Specifically, by addressing the following questions: 1) How can MPAs and networks of MPAs be used to provide marine mammals protection from marine noise and, in particular, what degree of protection could they permit migratory species? 2) How can MSP, with integrated ‘quiet’ MPAs and ‘quiet’ MPA corridors, strategically and effectively manage ship-based noise within a broader socio-economic and environmental context? What are the most effective means of building awareness, literacy and management support related to ocean noise for planners, regulators, industry and the wider marine community

Modelling ship movements: Applications for noise exposure to the marine ecosystem

Ship-source marine noise is an emerging issue that is increasingly shown to interfere with marine mammals, fish, potentially marine birds and other animals. The exposure to ship-based noise is expected to increase in the Salish Sea as marine vessel activity increases due to planned port expansions and new marine terminal construction on Canada’s Pacific coast. Increasingly, government and industry are required to take operational and strategic mitigation measures without reliable and comprehensive data and analysis to inform those decisions, and in the absence of national guidelines. The goal of this research has been to explore and improve the utility and modelling of ship traffic, based on AIS and other data, as an indicator of noise to enable government, industry and, even individuals, make better decisions to mitigate marine noise impacts. Specifically, the research addresses the following three questions: 1) How can we build a reliable, comprehensive spatio-temporal model of vessel movement? 2) How can we confidently associate noise with marine vessels to understand cumulative noise exposure? 3) How can we integrate vessel traffic models and noise exposure models with decision making and outreach? To accomplish this goal a multidisciplinary team of researchers has been assembled to tackle these research questions for each of the projects three study areas: Sach’s Harbour in the Arctic, SGaan Kinghlas Bowie Seamount on the west coast of Haida Gwaii and the Salish Sea. Here we show the results of vessel traffic modelling for the Salish Sea, the most heavily trafficked of all three areas, and still facing further increases in shipping levels due primarily to advances on the previously planned port expansion in Vancouver

Not all maps are equal:Evaluating approaches for mapping vessel collision risk to large baleen whales

1. A growing and increasingly globalised human population, requiring the movement of goods and commodities, is placing increasing demands on the maritime industry, resulting in a concurrent increase in global shipping activities. This has consequences for the marine environment, particularly for species vulnerable to the impacts of vessel traffic. For example, vessel collisions can result in sub-lethal or fatal injuries for marine mammals, whilst vessel noise can cause acoustic masking that effectively reduces an animal's listening space, potentially impacting their communication, navigation and foraging capacity.2. While a number of parallel approaches to mapping collision risk to large whales have arisen, these methods vary in their focus, usually on either co-occurrence, collision probability, or probability of mortality. However, little attention has been given to the implications of methodological choice and data selection on subsequent risk predictions.3. To assess differences between these approaches, we used a standardised input dataset comprised of telemetry-point data from tagged bowhead whales, and satellite-based Automated Identification System (AIS) data of spatial vessel movements covering the Davis-Baffin Arctic Marine Area. We applied this data to eight different, previously published analyses for deriving areas of vessel risk.4. We found that the choice of risk mapping approach affected the location, and total area, identified as ‘high risk’, and that more computationally complex approaches did not necessarily equate to different predictions. There was considerable variation in the total area of ‘high risk’ predicted within each map (range = 20–42,246 km2).5. Synthesis and Applications. The results underscore the importance of methodological transparency, informed data selection and careful interpretation when predicting collision risk. We provide practical recommendations for enhancing transparency when predicting risk, and discuss choice of approach suitable for different situations or management applications. It is critical that managers and policy makers are aware of the implications of applying different approaches when interpreting risk evaluation outputs.</p

Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms

This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject