Comparing distribution of harbour porpoise using generalized additive models and hierarchical Bayesian models with integrated nested laplace approximation

Species Distribution Models (SDMs) are used regularly to develop management strategies, but many modelling methods ignore the spatial nature of data. To address this, we compared fine-scale spatial distribution predictions of harbour porpoise (Phocoena phocoena) using empirical aerial-video-survey data collected along the east coast of Scotland in August and September 2010 and 2014. Incorporating environmental covariates that cover habitat preferences and prey proxies, we used a traditional (and commonly implemented) Generalized Additive Model (GAM), and two Hierarchical Bayesian Modelling (HBM) approaches using Integrated Nested Laplace Approxi�mation (INLA) model-fitting methodology. One HBM-INLA modelled gridded space (similar to the GAM), and the other dealt more explicitly in continuous space using a Log-Gaussian Cox Process (LGCP). Overall, predicted distributions in the three models were similar; however, HBMs had twice the level of certainty, showed much finer-scale patterns in porpoise distribution, and identified some areas of high relative density that were not apparent in the GAM. Spatial differences were due to how the two methods accounted for autocorrelation, spatial clustering of animals, and differences between modelling in discrete vs. continuous space; consequently, methods for spatial analyses likely depend on scale at which results, and certainty, are needed. For large-scale analysis (>5–10 km resolution, e.g. initial impact assessment), there was little difference be�tween results; however, insights into fine-scale (<1 km) distribution of porpoise from the HBM model using LGCP, while more computationally costly, offered potential benefits for refining conservation management or mitigation measures within offshore developments or protected areas

Enhancing the Scientific Value of Industry Remotely Operated Vehicles (ROVs) in Our Oceans

© Copyright © 2020 McLean, Parsons, Gates, Benfield, Bond, Booth, Bunce, Fowler, Harvey, Macreadie, Pattiaratchi, Rouse, Partridge, Thomson, Todd and Jones. Remotely operated vehicles (ROVs) are used extensively by the offshore oil and gas and renewables industries for inspection, maintenance, and repair of their infrastructure. With thousands of subsea structures monitored across the world’s oceans from the shallows to depths greater than 1,000 m, there is a great and underutilized opportunity for their scientific use. Through slight modifications of ROV operations, and by augmenting industry workclass ROVs with a range of scientific equipment, industry can fuel scientific discoveries, contribute to an understanding of the impact of artificial structures in our oceans, and collect biotic and abiotic data to support our understanding of how oceans and marine life are changing. Here, we identify and describe operationally feasible methods to adjust the way in which industry ROVs are operated to enhance the scientific value of data that they collect, without significantly impacting scheduling or adding to deployment costs. These include: rapid marine life survey protocols, imaging improvements, the addition of a range of scientific sensors, and collection of biological samples. By partnering with qualified and experienced research scientists, industry can improve the quality of their ROV-derived data, allowing the data to be analyzed robustly. Small changes by industry now could provide substantial benefits to scientific research in the long-term and improve the quality of scientific data in existence once the structures require decommissioning. Such changes also have the potential to enhance industry’s environmental stewardship by improving their environmental management and facilitating more informed engagement with a range of external stakeholders, including regulators and the public

Don’t forget the porpoise: acoustic monitoring reveals fine scale temporal variation between bottlenose dolphin and harbour porpoise in Cardigan Bay SAC

Populations of bottlenose dolphin and harbour porpoise inhabit Cardigan Bay, which was designated a Special Area of Conservation (SAC), with bottlenose dolphin listed as a primary feature for its conservation status. Understanding the abundance, distribution and habitat use of species is fundamental for conservation and the implementation of management. Bottlenose dolphin and harbour porpoise usage of feeding sites within Cardigan Bay SAC was examined using passive acoustic monitoring. Acoustic detections recorded with calibrated T-PODs (acoustic data loggers) indicated harbour porpoise to be present year round and in greater relative abundance than bottlenose dolphin. Fine-scale temporal partitioning between the species occurred at three levels: (1) seasonal differences, consistent between years, with porpoise detections peaking in winter months and dolphin detections in summer months; (2) diel variation, consistent across sites, seasons and years, with porpoise detections highest at night and dolphin detections highest shortly after sunrise; and (3) tidal variation was observed with peak dolphin detections occurring during ebb at the middle of the tidal cycle and before low tide, whereas harbour porpoise detections were highest at slack water, during and after high water with a secondary peak recorded during and after low water. General Additive Models (GAMs) were applied to better understand the effects of each covariate. The reported abundance and distribution of the two species, along with the temporal variation observed, have implications for the design and management of protected areas. Currently, in the UK, no SACs have been formally designated for harbour porpoise while three exist for bottlenose dolphins. Here, we demonstrate a need for increased protection and species-specific mitigation measures for harbour porpoise

Offshore decommissioning horizon scan: Research priorities to support decision-making activities for oil and gas infrastructure

Thousands of oil and gas structures have been installed in the world's oceans over the past 70 years to meet the population's reliance on hydrocarbons. Over the last decade, there has been increased concern over how to handle decommissioning of this infrastructure when it reaches the end of its operational life. Complete or partial removal may or may not present the best option when considering potential impacts on the environment, society, technical feasibility, economy, and future asset liability. Re-purposing of offshore structures may also be a valid legal option under international maritime law where robust evidence exists to support this option. Given the complex nature of decommissioning offshore infrastructure, a global horizon scan was undertaken, eliciting input from an interdisciplinary cohort of 35 global experts to develop the top ten priority research needs to further inform decommissioning decisions and advance our understanding of their potential impacts. The highest research priorities included: (1) an assessment of impacts of contaminants and their acceptable environmental limits to reduce potential for ecological harm; (2) defining risk and acceptability thresholds in policy/governance; (3) characterising liability issues of ongoing costs and responsibility; and (4) quantification of impacts to ecosystem services. The remaining top ten priorities included: (5) quantifying ecological connectivity; (6) assessing marine life productivity; (7) determining feasibility of infrastructure re-use; (8) identification of stakeholder views and values; (9) quantification of greenhouse gas emissions; and (10) developing a transdisciplinary decommissioning decision-making process. Addressing these priorities will help inform policy development and governance frameworks to provide industry and stakeholders with a clearer path forward for offshore decommissioning. The principles and framework developed in this paper are equally applicable for informing responsible decommissioning of offshore renewable energy infrastructure, in particular wind turbines, a field that is accelerating rapidly

Influence of offshore oil and gas structures on seascape ecological connectivity.

Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure

Occupancy of bottlenose dolphins (Tursiops aduncus) in relation to vessel traffic, dredging, and environmental variables within a highly urbanised estuary

Coastal areas, and thus coastal species, are at increasing risk from human activities. Sections of the coastline of Western Australia are undergoing intense coastal development to fulfil commercial, industrial, and recreational requirements. Multiple populations of bottlenose dolphins (Tursiops aduncus) occur around this coastline; however, small community sizes and limited genetic exchange rates make them susceptible to anthropogenic pressure. This study investigated the occupancy of dolphins within the Swan–Canning Rivers, an urbanised estuary, with regard to (1) presence/absence, (2) abundance, and (3) duration in terms of time spent in the area. These response variables were related back to environmental conditions (tidal state, tidal height, salinity, temperature), vessel traffic, and dredging activities using generalised additive modelling. Theodolite tracking data revealed high levels of boat traffic at the two sites considered; however, dolphin occurrence was only negatively affected by vessel density at one of these sites. Dolphin occupancy was also significantly influenced by temperature, with possible seasonal effects. No dolphins were sighted on days when backhoe dredging was present; however, low sample sizes limited statistical interpretation. These results highlight the need to consider context in behavioural response studies, in terms of habitat type studied, explanatory variables considered, and response variables selected