Abstract Commercial fisheries and oil and gas extraction are both spatially extensive industries in the North Sea (NS), and inevitably there is physical interaction where the two activities coincide. Regular contact between fishing gear and pipelines may risk pipeline integrity and could lead to gear snagging. It is also known, anecdotally, that some vessels target pipelines, potentially benefiting from local artificial reef effects. The impacts of pipeline decommissioning options (removal vs. in situ) on commercial fisheries must be evaluated as part of the consenting process, but the degree of interaction between the two is presently unknown in the NS. Vessel Monitoring System (VMS) data for the Scottish demersal fleet were analysed with spatial data on pipelines. Approximately one-third (36.1%) of trips fished within 200 m of a pipeline over a 5-year period, suggesting that pipelines are subjected to regular interaction with fishing gear. The fishing effort (in hours) associated with pipelines was 2.52% of the total effort, compared to 1.33% in an equivalent area of seabed 1 km away, implying modest aggregation of fishing around pipelines. Only a small percentage (0.93%) of fishing trips actively targeted pipelines as fishing grounds. The highest level of fishing around pipelines occurred in the northeast NS. Pipeline sections with >100 h of fishing were typically larger diameter pipelines. The results suggest that pipeline decommissioning may have both negative (displacement of aggregated effort) and positive (reduced snagging potential) outcomes for commercial fisheries. It is recommended that where there is little or no fishing activity associated with pipelines, receptors other than fishing should be prioritized when selecting decommissioning strategies. Additionally, the intensity of fishing around pipelines should be used to inform the frequency of post-decommissioning integrity monitoring for any pipelines left in situ. Introduction To enable exploitation of North Sea (NS) oil and gas (O&G), more than 45 000 km of pipelines, umbilicals and cables have been installed in the region since the 1960s (Oil and Gas UK, 2013). The pipelines range in diameter, construction material and configuration on the seabed (Oil and Gas UK, 2013). Large diameter pipelines are typically installed resting on the seabed (surface laid), while smaller pipelines, or those in close proximity to platforms, tend to be trenched and buried (Oil and Gas UK, 2013). Less than 2% of NS pipelines have been decommissioned, and to date research has focussed on the consequences of decommissioning platforms to other marine industries and the environment, rather than pipelines (Osmundsen and Tveteras, 2003; Oil and Gas UK, 2013). The maturing NS hydrocarbon basin means that it is increasingly necessary to consider the strategic options for decommissioning infrastructure and the likely impacts of various scenarios. Unlike O&G platforms, pipelines are not covered by the OSPAR 98/3 decision to ban the disposal of offshore installations at sea (DECC, 2011), and individual states are able to set their own national policies. In the United Kingdom and Norway, pipeline decommissioning is considered on a case-by-case basis, and a strategy is selected by undertaking a comparative assessment (CA) process of the different options. Each decommissioning option (e.g. removal, leave in situ with or without intervention) is rated in terms of the perceived impacts to the marine environment and to the fishing industry, as well as safety, cost, and technology implications (DECC, 2011). Operators must demonstrate that any proposed decommissioning strategy meets international obligations to ensure the safety of navigation and fishing, and protection of the marine environment (Oil and Gas UK, 2013). In the NS, fishing is an ecologically and economically important activity, with an estimated 2.3 million tons of fish caught per year (OSPAR, 2010). The catch is composed of pelagic, demersal, and crustacean species, from trawling, seine nets, static gear, dredging, and line fishing (Rogers and Stocks, 2001, Thorpe et al., 2016). Scottish vessels dominate the UK demersal fleet and represent a significant proportion of the total trawling activity that takes place within the NS (Royal Society of Edinburgh, 2004). Since 2005, all European vessels larger than 15 m have been required to use the Vessel Monitoring System (VMS). The VMS transmits a vessel’s location, speed and heading at regular intervals to the relevant competent authority (EC, 2002). The reporting interval required for VMS pings is at least every 2 h (EC, 2003); however; the actual transmission rate can vary above or below this (Mills et al., 2007; Lee et al., 2010). VMS data can be analysed to provide information on real-time spatial fishing trends (Mills et al., 2007; Vermard et al., 2010; Witt et al., 2012). Indeed, analysis of northeast Atlantic fishing patterns has highlighted the concentration of fishing effort around depth contours (Sharples et al., 2013) and certain seabed types (Campbell et al., 2014). Furthermore, VMS data can be coupled with a vessel’s logbook to provide higher-resolution spatial information on the landings and the value of the fish caught throughout European waters (Bastardie et al., 2010; Holmes et al., 2011; Martín et al., 2014). Due to the proximity of the O&G, and fishing industries in the NS, there is inevitably physical interaction between the two activities. Whilst vessels are banned from fishing within the 500 m exclusion zone around O&G platforms (Petroleum Act, 1987), no such restrictions apply to pipelines. In fact, it is known that some vessels actively target pipelines as fishing grounds (Scottish Fishermen’s Federation, pers. comm.), potentially benefiting from the local artificial reef effects created by the pipeline and any protective material surrounding it (Osmundsen and Tveteras, 2003; Rogers and Stocks, 2001; Feary et al., 2011). It would also be expected that many vessels cross pipelines coincidently while fishing due to their spatial extent. Operational and in situ decommissioned pipelines that are subjected to regular interaction with fishing gear may be prone to damage (de Groot, 1982) and may pose a snagging risk to vessels while gear is deployed (Cicin-Sain and Tiddens, 1989). The decommissioning strategy that is selected for pipelines in the NS is likely to influence fishing activity, with potentially both negative (loss of reef effect) and positive (reduced snagging potential) outcomes. The aim of this study was to understand the extent of fishing activity associated with NS pipelines, which is the first stage in managing the decommissioning of pipelines with respect to fisheries. The following objectives were established to meet the study aim: (i) quantify fishing activity associated with NS pipelines using VMS data for the Scottish demersal fleet and (ii) identify which pipelines, and sections of pipelines, are subjected to the greatest (and least) interaction with fishing. Material and methods Study area The NS was defined according to the OSPAR Region 2 definition (Figure 1). It extends west from the English Channel into the Baltic Sea and opens into the Atlantic Ocean in the north. Figure 1. View largeDownload slide (a) The OSPAR Greater NS Region (shaded area); VMS fishing pings from the UK demersal fleet from 2009 to 2013 (grey points) and O&G pipelines (black lines). (b) Fishing associated with specific pipelines. Solid black lines represent pipelines with the highest number (>75) of tracks per km. Light grey pipelines have no associated fishing. (c) 1 km sections of pipeline associated with more than 100 h of fishing are shown in black, mid-grey sections are associated with <100 h and light grey sections have zero fishing associated with them. The 200 m contour line of the Norwegian trench is shown as a solid line. Figure 1. View largeDownload slide (a) The OSPAR Greater NS Region (shaded area); VMS fishing pings from the UK demersal fleet from 2009 to 2013 (grey points) and O&G pipelines (black lines). (b) Fishing associated with specific pipelines. Solid black lines represent pipelines with the highest number (>75) of tracks per km. Light grey pipelines have no associated fishing. (c) 1 km sections of pipeline associated with more than 100 h of fishing are shown in black, mid-grey sections are associated with <100 h and light grey sections have zero fishing associated with them. The 200 m contour line of the Norwegian trench is shown as a solid line. Data sources VMS data were obtained from the Scottish Government’s fisheries information network database for all Scottish commercial fishing vessels (≥15 m length) for the years 2009–2013. Since data were not available for other EU vessels, all figures will represent an underestimate of the total fishing activity in the NS and may show a bias towards waters close to Scotland (this is also where the majority of UK oil infrastructure is located). The Scottish VMS data were cleaned to remove pings with any of the following attributes: within 5 km of a port, latitude or longitude outside the range of possible values or a derived speed of >20 knots (Hintzen et al., 2010). Data were then filtered to include only those points with an associated speed of <5 knots, which is considered to be indicative of fishing activity (Lee et al., 2010). A unique fishing trip ID was assigned to all pings between a vessel leaving and returning to port. VMS points were interpolated into fishing tracks to obtain a greater spatial resolution of fishing activity (Lambert et al., 2012, O’Neill and Ivanović, 2015). The interpolation followed the methods of Hintzen et al. (2010) using a cubic Hermite spline, which accounts for the heading and speed of the vessel. VMS ping data without heading or speed information were available for the remaining 18% of the UK demersal fleet, which are not Scottish registered vessels. These datasets could not be interpolated into tracks due to the missing information, but were used to provide context to the Scottish vessel data. Visualization of the non-Scottish UK fleet data was used to determine whether the approximate distribution of fishing around pipelines for Scottish vessels is likely to reflect that of the remaining UK fleet. The location and properties of pipelines in the NS were obtained from Oil and Gas UK and the Norwegian Petroleum Directorate (Norwegian Petroleum Directorate, 2016). The pipeline dataset consists of trunklines, flexible and rigid flowlines, umbilicals, and cables. Data included the diameter, exposure, trenching, and fluid medium inside each pipeline. Analysis Analyses were confined to vessels operating bottom gear (beam trawls, otter trawls, and pair trawls), since these proved to be the most significant group interacting with pipelines, and are most likely to benefit from any artificial reef effects (Picken et al., 2000). To quantify the overall interaction between NS fishing and pipelines, the percentages of total fishing trips and total fishing hours that occurred within 200 m either side of a pipeline were calculated. A buffer area of 200 m was chosen following consultation with representatives from the fishing industry about pipeline use (Scottish Fishermen’s Federation, pers. comm.). To determine the distribution of fishing effort around pipelines, effort (total hours) was also calculated for 200 m bins (up to 1000 m) away from the pipeline. A time threshold was used to distinguish between vessels that actively fished along pipelines from those that were considered to have coincidentally interacted with pipelines. The threshold was defined by calculating, for each trip, the percentage of fishing time spent within 200 m of a pipeline, and examining the frequency distribution of these percentages. To understand whether the fishing effort associated with pipelines merely reflected background fishing activity in that area, individual pipelines were also shifted on a random bearing by 1000 m. The 200 m buffers and associated fishing hours were recalculated for the shifted pipes. This was repeated 100 times to give a probability distribution of obtaining different values for the percentage of trips classified as ‘actively targeting’. The average number of trips in the ‘actively targeting’ category was calculated for the 100 shifted pipelines and compared to the true value. By shifting the pipes 1000 m, the true buffer zone and shifted buffer would not overlap. Furthermore, moving the pipeline by only 1000 m meant that the shifted pipelines were more likely to be on a similar substrate to the true pipelines, than if the shifted pipelines were randomly distributed throughout the entire NS basin. To identify which pipelines were most (and least) exposed to fishing, the total fishing time and number of tracks within 200 m (either side) was calculated for each pipeline. This number was divided by the length of the pipeline to give the number of fishing hours and tracks per km. Sections of pipeline that had the highest levels of fishing activity were identified by dividing each pipeline into 1 km by 400 m sections and calculating the total fishing time per 0.4 km2 section. All analyses were implemented using the R-package ‘sp’ (Pebesma and Bivand, 2005; R Development Core Team, 2008) with final maps produced in ArcMap 10.1 (ESRI, 2014). Results Between 2009 and 2013, the Scottish demersal fleet contained 274 vessels. The mean number of demersal trips per year was 9329 across all vessels. Of all demersal fishing trips that took place over the 5 years, 36.1% fished within 200 m either side of a pipeline. The total hours of fishing within 200 m of a pipeline were 68 613 which represented 2.52% of total demersal fishing hours. The majority (64.6%) of demersal vessels fished within 200 m of pipelines on at least one fishing trip over the 5 years. A summary of interpolated fishing tracks in the northern NS is shown in Figure 2a. Routes that were routinely fished were visible as densely clustered tracks, and a number of areas that have little or no fishing tracks were also observed. The majority of tracks occurred in areas where there are no pipelines present, but several of the routinely fished routes corresponded to pipeline locations (Figure 2b). The distribution of fishing effort (hours) with distance from pipelines up to 1000 m is shown in Figure 2c. The largest proportion of fishing hours was concentrated within 200 m of pipelines. Figure 2. View largeDownload slide Demersal fishing associated with pipelines. Routes that are repeatedly fished are represented by densely clustered tracks (a). A number of routinely fished routes correspond to the location of O&G pipelines (black lines in b). Fishing effort (hours) diminishes with distance from pipelines (c). Values on the x axis represent the mid-point of the distance bins. Figure 2. View largeDownload slide Demersal fishing associated with pipelines. Routes that are repeatedly fished are represented by densely clustered tracks (a). A number of routinely fished routes correspond to the location of O&G pipelines (black lines in b). Fishing effort (hours) diminishes with distance from pipelines (c). Values on the x axis represent the mid-point of the distance bins. The majority of trips spent less than 10% of the total fishing time within 200 m of a pipeline. Fewer trips spent 10–20, 20–30, 30–40, and 40–50% of total time fishing within 200 m of a pipeline (Figure 3). The number of trips then increased beyond 50% of total fishing time within 200 m of a pipeline. It was therefore decided to split fishing trips into three groups based on the percentage of total fishing time spent within 200 m (Table 1). These thresholds were used to distinguish trips that actively targeted pipelines from those that had coincidental interaction. From 2009 to 2013, 0.93% of all demersal trips spent 50% or more of their time fishing within 200 m of a pipeline (actively fishing). Table 1. Fishing trip groups defined by the percentage of total time fishing within 200 m of a pipeline. % of time fishing within 200 m No interaction 0 Coincidental interaction 0–50% Actively fishing >50% % of time fishing within 200 m No interaction 0 Coincidental interaction 0–50% Actively fishing >50% Figure 3. View largeDownload slide The percentage of total fishing time spent, per trip, within 200 m either side of a pipeline and the number of trips in each 5% bin for years 2009–2013. (a) The majority of trips fished within 200 m of a pipeline for <10% of the total fishing time. Trips that spent no time within the pipeline buffer zone are not shown. (b) Zoomed section of (a) showing only trips that spend >30% of time with 200 m of a pipeline. The dotted lines show the defined threshold between ‘actively fishing trips’ and ‘coincidental interaction’. Figure 3. View largeDownload slide The percentage of total fishing time spent, per trip, within 200 m either side of a pipeline and the number of trips in each 5% bin for years 2009–2013. (a) The majority of trips fished within 200 m of a pipeline for <10% of the total fishing time. Trips that spent no time within the pipeline buffer zone are not shown. (b) Zoomed section of (a) showing only trips that spend >30% of time with 200 m of a pipeline. The dotted lines show the defined threshold between ‘actively fishing trips’ and ‘coincidental interaction’. For the randomly shifted pipelines, the average percentage of demersal trips in the ‘actively fishing’ category was 0.14%, compared with the true figure of 0.93%. The probability of obtaining a value of 0.93% or greater when pipelines were randomly distributed was <0.01. The percentage of total fishing hours within the 200 m of a pipeline was also lower (2.52 vs. 1.12%) when pipelines were offset. The distribution of VMS points from non-Scottish UK demersal vessels (Figure 1a) shows that the fishing effort of the entire UK fleet was also concentrated in the northern NS over the 5 years. Pipeline properties The total area of pipelines with a 200 m buffer zone in the NS was 9900 km2, which constitutes 1.32% of the OSPAR Greater NS region (750 000 km2). The pipelines that were associated with the highest numbers of fishing tracks per km were short pipelines (<7 km) located in the vicinity of the Scott platform in the outer Moray Firth (Figure 1b). There were 749 pipelines in the NS that had no demersal fishing tracks within 200 m; however, these were typically short sections of connector pipelines, umbilicals or cables. The average length of pipelines with no fishing tracks was 9.74 km and the average diameter was 6.62 inches. The number of fishing hours per 0.4 km2 pipeline section ranged from 0 to 223 h. The pipeline sections associated with more than 100 h of fishing were typically larger pipelines, with a median diameter of 21 inches (range in diameter: 2–40 inches) and were all located in the northern NS and to the east of Shetland (Figure 1c). The hours of fishing associated with pipe sections beyond the 200 m contour of the Norwegian trench and in the southern NS were generally low or zero (Figure 1c). Discussion Analysis of the Scottish demersal fishing fleet showed that NS pipelines are regularly exposed to interaction with fishing gear. Over one-third of demersal trips fished in the vicinity of a pipeline, although the percentage of total fishing hours associated with pipelines was small (2.52%). The percentage of fishing hours represented approximately double the proportion of the NS area occupied by pipelines (1.32%) and double the proportion of fishing hours (1.33%) that occurred in an equivalent area of seabed located 1 km away from pipes. This information suggests that there was some degree of fishing aggregation around pipelines. Given the spatial extent of fishing across the NS, it is understandable that any modest aggregation around pipelines still only represents a small proportion of total fishing effort. The identification of vessels that followed pipelines for the majority of a trip provides further evidence that pipelines are actively targeted as fishing grounds. The proportion of total NS fishing trips that did actively targeted pipelines was; however, very small (<1% of trips), and in some circumstances may be considered negligible. The highest intensity of fishing activity around sections of pipelines was concentrated on larger diameter trunklines. This may be a result of larger pipelines being placed in favourable fishing areas or, potentially, the enhanced artificial reef effects (aggregation or enhanced production) of larger pipelines, which are most likely to be surface laid (Oil and Gas UK, 2013). Little research has specifically focused on the reef effects of pipelines, but Love and York (2005) showed that fish density was higher within 10 m of pipelines than on the surrounding seafloor. Additionally, Russell et al. (2014) showed that foraging behaviour of certain NS seals was associated with pipelines, and suggested that this behaviour, observed within 100 m of pipelines, was a result of increased fish densities. On other artificial structures there was evidence that fish biomass is related to structure size (Bohnsack et al., 1994; Campbell et al., 2011), and it would be expected that this is the case for pipelines. Despite the potential for more fish to associate with bigger pipelines, not all large diameter pipelines (>16 inches), nor all sections of large diameter pipelines, were associated with fishing. Specifically, pipelines off the east coast of England, in the southern NS, had little fishing activity surrounding them. It is possible that this is a geographical artefact, resulting from the analysis being restricted to the Scottish demersal fleet, but the scarcity of VMS points from other UK (mainly English) vessels in the southern NS suggests that it is not an artefact. Alternatively, the patterns may reflect differences in the ground type and fish stocks between the two areas of the NS. For instance, in the central and southern NS, fishing largely targets flatfish (Rogers and Stocks, 2001) which tend to associate with soft bottom habitats (Munroe, 2005) and are therefore less likely to benefit from the presence of hard substrata than the demersal species targeted in northern NS fisheries. Similarly, beam trawls used to catch flatfish might underperform on uneven ground such as over a pipeline. The target species, seabed type, depth and the distance from port of the pipeline are all likely to be important factors driving fishing behaviour around pipelines. Combining the present results with landings information could help to elucidate whether fishing along pipelines yields differences in landings and/or revenue. Considerations for decommissioning The choice of decommissioning strategy for any pipeline is selected following an assessment of the potential impacts to the fishing industry, and the potential snagging risk posed by in situ decommissioning (as part of the wider CA processes). At present, this assessment is made using low resolution fishing intensity data based on the scale adopted under the available ICES rectangles. These intensity datasets often do not reflect fine-scale spatial fishing patterns (Lee et al., 2010) and may misrepresent the interaction between fishing vessels and pipelines. The high resolution fishing data generated in this study will enable operators and regulators to improve estimates of the intensity and type of fishing around specific pipelines. For the sections of pipeline that have been identified as having little or no fisheries interaction (Figure 1c), the impacts of decommissioning to the fishing industry may be considered minor. If these pipeline sections were to be left in situ, it would be expected that the future snagging risk would also be low. Other considerations, such as impacts to the marine environment, seabed disturbance or the cost/safety implications of the decommissioning options, should therefore take precedence for these pipeline sections. In contrast, for the sections of pipelines that are associated with a high intensity of fishing (e.g. the pipelines east of Shetland), the impacts to the fishing industry and potential snagging hazards should be important considerations to regulators and operators. Inputs from fisheries organizations during the CA would be necessary to understand the potential consequences of different decommissioning strategies. Based on the present analysis, it is not yet possible to speculate exactly how the removal of pipelines would influence the spatial distribution of fishing, and if the fishing effort that is currently aggregated around certain pipelines would be displaced. In areas where there is a high intensity of fishing activity associated with pipelines, decommissioning could occur by pipeline removal, pipeline trenching or the addition of protective material to reduce the risk (of snagging and of pipeline integrity being compromised) posed by fisheries interaction. The addition of protective material, such as rock dump or concrete mattresses, may alter the artificial reef ecosystem around the pipeline and/or the ability to tow fishing gear over the pipeline. The available data used in this study, lacked detail on vessel interactions according to pipeline exposure or the presence of existing protective material. The effects of these protective measures as part of a decommissioning programme are, therefore, unknown at present. Access to data held by the O&G industry on NS infrastructure (such as the location of the 35 000–40 000 concrete mattresses) would allow for greater insights into the likely impacts of different decommissioning strategies based on an improved understanding of the current interactions. For any pipelines that are decommissioned in situ, a monitoring programme must be initiated to monitor the continued integrity of the pipelines and development of new snagging hazards as the pipelines degrade. The pipelines identified in this study as being associated with little or no fishing activity are likely to maintain their integrity for longer and as such could be subjected to a less frequent monitoring regime than those sections of pipelines that are regularly fished over. The adoption of such a risk-based approach to monitoring, informed by the fishing intensity data presented here, could represent a significant cost-saving to the industry and regulators. Limitations of data The figures presented here may underestimate the fishing activity associated with pipelines in the NS as a result of some of the limitations associated with the data availability in this study. VMS information for other EU vessels were excluded, despite the likelihood that a large number also interact with NS pipelines while fishing. Furthermore, track interpolations are subjected to an inherent error and may not represent the true fishing track. Access to high-resolution plotter data would enable more accurate descriptions of spatial patterns of fishing activities, and centralized initiatives (e.g. the UK Crown Estate Fisherman’s mapping project) are currently underway to facilitate access to these datasets. Similarly, it is possible that for a small minority of trips, fishing effort has been overestimated. The method used to differentiate between fishing and non-fishing relies on speed as a proxy, yet there are several factors, including weather, vessel turning, hauling of gear, and travelling near hazards/port when the speed of the vessel may fall below five knots. The threshold used to distinguish trips that actively fished along pipelines from those that coincidentally interacted may exclude some trips that actively targeted pipelines. It is apparent from visualizing fishing trips that several vessels spent a proportion of their time following pipelines very closely and a period fishing elsewhere. If such trips spent more than the threshold of time (e.g. 50%) outside of pipeline buffer then they were excluded from the actively targeting category. Observing the fishing paths, however, it seems highly likely that, for at least some of the trip, the vessels were targeting pipelines. Beyond visualizing each fishing trip and deciding whether the pattern follows pipelines, it would be hard to find a method to capture this use. There is some potential for using trajectory similarity analysis to compare the route of fishing tracks and pipelines, but defining the similarity between two paths is a challenging task and there are a range of trajectories that can be considered similar e.g. same shape and direction but far apart; overlap but different directions; similar direction but different shape/length (Liu and Schneider, 2012). Conclusions This study provides novel data on the intensity of fishing associated with pipelines in the NS. It offers insight into the spatial variations in the overlap between the commercial fishing and O&G industries. The results demonstrate that at some point, the majority of Scottish demersal vessels fished within 200 m of a pipeline, but only approximately one third of all fishing trips interacted with a pipeline. The interactions included vessels that were coincidentally fishing in the vicinity of pipelines and a small, but clear subset of vessels that specifically targeted pipelines as fishing grounds. Several sections of pipelines were identified as having little or no fisheries interaction and it is recommended that receptors other than fishing should be prioritized when selecting decommissioning strategies for these pipeline sections. Additionally, the frequency of post-decommissioning monitoring of pipelines left in situ should be informed by the intensity of fishing associated with pipelines, with higher frequency monitoring on those pipelines that are regularly exposed to interaction with fishing gear. The study has also demonstrated the methods that can be applied to VMS and other spatial datasets to understand the response of the fishing industry to man-made structures. The approach employed in this study also has merit to be adapted to other activities (e.g. marine renewables and installation of power cables) where fishing interactions need to be assessed. Acknowledgements Marine Scotland Science in Aberdeen hosted this study and provided all the datasets required. The authors would like to thank Valerie West for FIN extractions, Gareth Jones for pipeline degradation literature and Oban fisheries office for computer access. Funding This work was undertaken as part of the MASTS internship programme and was funded by the MASTS Marine Energy Forum, UHI T&C fund and The Scottish Association for Marine Science Bursary. References Bastardie F., Nielsen J. R., Ulrich C., Egekvist J., Degel H. 2010. Detailed mapping of fishing effort and landings by coupling fishing logbooks with satellite-recorded vessel geo-location. Fisheries Research , 106: 41– 53. Google Scholar CrossRef Search ADS Bohnsack J. A., Harper D. E., Mcclellan D. B., Hulsbeck M. 1994. Effects of reef size on colonization and assemblage structure of fishes at artificial reefs off southeastern Florida, U.S.A. Bulletin of Marine Science , 55: 796– 823. Campbell M. D., Rose K., Boswell K., Cowan J. 2011. Individual-based modeling of an artificial reef fish community: effects of habitat quantity and degree of refuge. Ecological Modelling , 222: 3895– 3909. Google Scholar CrossRef Search ADS Campbell M. S., Stehfest K. M., Votier S. C., Hall-Spencer J. M. 2014. Mapping fisheries for marine spatial planning: Gear-specific vessel monitoring system (VMS), marine conservation and offshore renewable energy. Marine Policy , 45: 293– 300. Google Scholar CrossRef Search ADS Cicin-Sain B., Tiddens A. 1989. Private and public approaches to solving oil/fishing conflicts offshore California. Ocean and Shoreline Management , 12: 233– 251. Google Scholar CrossRef Search ADS DECC. 2011. Decommissioning of offshore oil and gas installations and pipelines under the Petroleum Act 1998, Guidance notes. Aberdeen, Department of Energy and Climate Change. 134 pp. EC. 2002. Council regulation 2371/2002 of 20 December 2002 on the consesrvation and sustainable exploitation of fisheries resources under the Common Fisheries Policy. Official Journal of the European Communities, L358/59. EC. 2003. Commission regulation 2244/2003 of 18 December 2003 laaying down detailed provision regarding satellite-based vessel monitoring systems. Official Journal of the European Communities, L33/17. ESRI. 2014. ArcGIS Desktop . Environmental Systems Research Institute, Redlands, California. Feary D. A., Burt J. A., Bartholomew A. 2011. Artificial marine habitats in the Arabian Gulf: Review of current use, benefits and management implications. Ocean and Coastal Management , 54: 742– 749. Google Scholar CrossRef Search ADS de Groot S. J. 1982. The impact of laying and maintenance of offshore pipelines on the marine environment and North Sea fisheries. Ocean Management , 8: 1– 27. Google Scholar CrossRef Search ADS Hintzen N. T., Pier G.J., Brunel T. 2010. Improved estimation of trawling tracks usng cubic Hermite spline interpolation of position registration data. Fisheries Research , 101: 108– 115. Google Scholar CrossRef Search ADS Holmes S., Bailey N., Campbell N., Catarino R., Barratt K., Gibb A., Fernandes P. 2011. Using fishery-dependent data to inform the development and operation of a co-management initiative to reduce cod mortality and cut discards. ICES Journal of Marine Science: Journal du Conseil , 68: 1679– 1688. Google Scholar CrossRef Search ADS Lambert G. I., Jennings S., Hiddink J. G., Hintzen N. T., Hinz H., Kaiser M. J., Murray L. G. 2012. Implications of using alternative methods of vessel monitoring system (VMS) data analysis to describe fishing activities and impacts. ICES Journal of Marine Science, 69: 682–693 . Lee J., South A. B., Jennings S. 2010. Developing reliable, repeatable, and accessible methods to provide high-resolution estimates of fishing-effort distribution from vessel monitoring system (VMS) data. Ices Journal of Marine Science , 67: 1260– 1271. Google Scholar CrossRef Search ADS Liu H., Schneider M. 2012. Similarity measurement of moving object trajectories. IWGS ‘12 Proceedings of the third ACM SIGSPATIAL International Workshop on Geostreaming, 19–22, Redondo Beach, California. Love M. S., York A. 2005. A comparison of the Fish assemblages associated with an oil/gas pipeline and adjacent seafloor in the Santa Barbara Channel, Southern California Bight. Bulletin of Marine Science , 77: 101– 118. Martín P., Muntadas A., De Juan S., Sánchez P., Demestre M. 2014. Performance of a northwestern Mediterranean bottom trawl fleet: How the integration of landings and VMS data can contribute to the implementation of ecosystem-based fisheries management. Marine Policy , 43: 112– 121. Google Scholar CrossRef Search ADS Mills C. M., Townsend S. E., Jennings S., Eastwood P. D., Houghton C. A. 2007. Estimating high resolution trawl fishing effort from satellite-based vessel monitoring system data. ICES Journal of Marine Science: Journal du Conseil 64: 248– 255. Google Scholar CrossRef Search ADS Munroe T. A. 2005. Distribution and Biogeograhpy. In Gibson R. N. (ed.) Flatfishes: Biology and Exploitation . Oxford, UK: Blackwell Science. Norwegian Petroleum Directorate. 2016. FactMaps [Online]. http://www.npd.no/en/Maps/Fact-maps/ (last accessed 1 February 2016). O’Neill F. G., Ivanović A. 2015. The physical impact of towed demersal fishing gears on soft sediments. ICES Journal of Marine Science, 73: i5 . Oil and Gas UK. 2013. Decommissioning of pipelines in the North Sea region, Aberdeen, Oil and Gas UK. 48 pp. Osmundsen P., Tveteras R. 2003. Decommissioning of petroleum installations-major policy issues. Energy Policy , 31: 1579– 1588. Google Scholar CrossRef Search ADS OSPAR. 2010. Quality Status Report. London, OSPAR Commission. 176 pp. Pebesma E. J., Bivand R. S. 2005. Classes and methods for spatial data in R. http://cran.r-project.org/doc/Rnews/, R News 5(2). Petroleum Act. 1987. Chapter 12 . The Stationery Office, London. Picken G., Baine M., Heaps L., Side J. 2000. Rigs to Reefs in the North Sea. In: Jensen A. C., Collins K. J., Lockwood A. P. M. (eds.) Artificial Reefs in European Seas . Springer, Netherlands. R Development Core Team. 2008. R: A language and environment for statistical computing. R foundation for Statistical Computing, Vienna, Austria. Rogers S., Stocks R. 2001. North Sea Fish and Fisheries. Technical Report Productice for Strategic Environmental Assessment. Royal Society of Edinburgh. 2004. Inquiry in the Future of the Scottish Fishing Industry, 96 pp. Russell D. J. F., Brasseur S. M. J. M., Thompson D., Hastie G. D., Janik V. M., Aarts G., McClintock B. T., et al. 2014. Marine mammals trace anthropogenic structures at sea. Current Biology , 24: R638– R639. Google Scholar CrossRef Search ADS PubMed Sharples J., Ellis J. R., Nolan G., Scott B. E. 2013. Fishing and the oceanography of a stratified shelf sea. Progress in Oceanography , 117: 130– 139. Google Scholar CrossRef Search ADS Thorpe R. B., Dolder P. J., Reeves S., Robinson P., Jennings S. 2016. Assessing fishery and ecological consequences of alternate management options for multispecies fisheries. ICES Journal of Marine Science, 73: 1503–1512. Vermard Y., Rivot E., Mahévas S., Marchal P., Gascuel D. 2010. Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models. Ecological Modelling , 221: 1757– 1769. Google Scholar CrossRef Search ADS Witt M. J., Sheehan E. V., Bearhop S., Broderick A. C., Conley D. C., Cotterell S. P., Crow E., et al. 2012. Assessing wave energy effects on biodiversity: the Wave Hub experience. Philosophical Transactions of the Royal Society A-Mathematical Physical and Engineering Sciences , 370: 502– 529. Google Scholar CrossRef Search ADS © International Council for the Exploration of the Sea 2017. All rights reserved. For Permissions, please email: email@example.com
ICES Journal of Marine Science – Oxford University Press
Published: Jan 1, 2018
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