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  • 1.
    Bergström, Lena
    et al.
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU, Aquatic Resources.
    Lagenfelt, Ingvar
    Swedish Agency for Marine and Water Management.
    Sundqvist, Frida
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU, Aquatic Resources.
    Andersson, Ingemar
    Swedish Agency for Marine and Water Management.
    Andersson, Mathias H.
    Perfomers of environmental monitoring, Universities, Stockholm University, SU, Department of Zoology. Perfomers of environmental monitoring, Institutes, Swedish Defence Research Agency, FOI.
    Sigray, Peter
    Perfomers of environmental monitoring, Institutes, Swedish Defence Research Agency, FOI.
    Fiskundersökningar vid Lillgrund vindkraftpark: Slutredovisning av kontrollprogram för fisk och fiske 2002–20102013Report (Other academic)
    Abstract [en]

    In 2001, the Government authorised the construction of an offshore wind farm at Lillgrund (48 wind turbines with 2.3 MW generators). The Lillgrund wind farm is located in the Öresund Strait in the southwest Sweden and it connects the brackish Baltic Sea with the Kattegat and North Sea area. In 2002, the Environmental Court defined the final terms and conditions for the wind farm development and the extent of the monitoring programme required. Lillgrund wind farm has been operating since 2008 and is currently the largest investment in offshore wind power that is in operation in Sweden. The National Board of Fisheries conducted a monitoring programme in the area in the years before (2002–2005) and after (2008–2010) the construction of the wind farm; a base line study and a study when the wind farm was operational, respectively. The aim was to investigate the impact of the wind farm, when operating, on the benthic (bottom-living) and pelagic (open-water living) fish as well as on fish migration. These studies have partly been integrated into work conducted as a part of the research project Vindval, funded by the Energy Agency. Throughout the project period, regular contact has been maintained between the National Board of Fisheries and Vattenfall (which owns and operates the wind farm), as well as with the regulatory authority (County Administrative Board of Skåne). The main results can be summarised in a number of points below: 

    Acoustics (sound) 

    • The overall sound energy from the wind farm under water, is mainly generated by vibration from the gearbox.

    • An analysis of the sound pressure level for the wind farm area, showed a correlation between noise level and the number of turbines in the wind farm (the so called park effect), where each individual turbine helps to increase the overall noise level in the area.

    • Sound measurements from Lillgrund wind farm showed that noise levels within a distance of 100 metres from a turbine at high wind speeds are high enough to be a risk for some species of fish to be negatively affected, e.g. in the form of escape behaviour, or masking of vocal communication between individuals.

    • Stress reactions can also occur at distances of more than 100 metres from a turbine. This is due to the fact that the noise from the turbines is continuous and louder than the ambient noise levels within some frequencies.

    Benthic (bottom-living) fish

    • The development of the fish community in Lillgrund was similar to that observed in the reference areas during the study period. For the wind farm as a whole, no effect was observed on the species richness, species composition or quantity of fish.

    • Several species of bottom-living fish showed an increase in abundance close to the individual wind turbines compared with further away, especially eel (yellow eel) (Anguilla anguilla), cod (Gadus morhua), goldsinny wrasse (Ctenolabrus rupestris) and shorthorn sculpin (Myoxocephalus scorpius). The results more likely reflect a redistribution of fish within the wind farm, rather than a change in productivity or migration from surrounding areas. The increase in abundance is probably due to the wind turbine foundations providing an opportunity for protection and improved foraging.

    • The distance within which an increased abundance could be observed was estimated for different species to be between 50–160 metres from a wind turbine.

    Pelagic (open-water living) fish

    • There was a dramatic increase in commercial fishing for herring (Clupea harengus) north of the Öresund bridge, in contrast to the south of this line, where it practically completely stopped during the first years of operation of the wind farm. This change may imply that the Rügen herring migration was affected by the Lillgrund wind farm. Due to the fact that there were other factors in addition to the wind farm contributing to the herring movements, it proved difficult to identify any correlation.  Fish migration

    • According to the study, the wind farm at Lillgrund is not a definitive barrier for the migration of silver eels (Anguilla anguilla) that migrate through and close to the wind farm area. The same proportion of the tagged and released silver eels (approximately one-third), passed the transect line with receivers, both before the wind farm was constructed (the baseline period) and after it was in operation.

    • There was no statistical difference indicating any alterations in the migration period for silver eel, but there was a tendency towards the migration taking longer at higher productivity (>20% of maximum effect) which could indicate that some eels were affected by the wind farm. There was a tendency towards the eels being recorded on fewer occasions than expected within the wind farm when functioning at low productivity (<20 %) and on more occasions than expected when functioning at higher productivity (>20 %), which may indicate that some individuals are less able to navigate past the wind farm at higher production rates.   

    Conclusions

    The study at Lillgrund has resulted in an increase in knowledge of how offshore wind farms can affect fish, which is very valuable. Even within an international perspective, there are very few studies of offshore wind farms in operation.  Three years of monitoring the effects of the wind farm on fish and fisheries is only a relatively short period. Some of the most significant results however, include the fact that some bottom-dwelling fish were attracted to the fundaments of the wind farm and the associated rocky protection layer (reef effect). In addition, an increasing noise level in the Öresund environment was observed and the results of the eel tracking may indicate that the migration pattern of some eels was, to some extent, affected by the wind farm. There is a need for caution however, when applying the results in other marine areas and on a larger scale. Lillgrund wind farm is one of the first large-scale wind farms and is located in an area with frequent and noisy shipping traffic as well as frequent and large fluctuations in external parameters such as salinity and currents. A key gap in our knowledge, despite these studies, is the lack of long term monitoring, to evaluate the long term ecological impacts of the reef effects observed. It would be ideal to re-visit the wind farm after a number of years to see how the fish populations have developed over the longer term, and see whether the observed accumulation of certain fish species near the structures continues, and if quantitative effects on the whole area are also are evident. Studies looking at whether noise as a physiological stress, can affect the fish species that live or pass through the wind farm environment are also required. In addition it would be useful to implement further studies, especially in the Baltic Sea, with regard to the cumulative impacts on migratory fish such as silver eels. The full report is available as a PDF in English.

  • 2.
    Bergström, Lena
    et al.
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU, Aquatic Resources.
    Lagenfelt, Ingvar
    Swedish Agency for Marine and Water Management.
    Sundqvist, Frida
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU, Aquatic Resources.
    Andersson, Ingemar
    Swedish Agency for Marine and Water Management.
    Andersson, Mathias H.
    Perfomers of environmental monitoring, Universities, Stockholm University, SU, Department of Zoology. Perfomers of environmental monitoring, Institutes, Swedish Defence Research Agency, FOI.
    Sigray, Peter
    Perfomers of environmental monitoring, Institutes, Swedish Defence Research Agency, FOI.
    Study of the Fish Communities at Lillgrund Wind Farm: Final Report from the Monitoring Programme for Fish and Fisheries 2002–20102013Report (Other academic)
    Abstract [en]

    In 2001, the Swedish Government authorised the construction of an offshore wind farm at Lillgrund in the Öresund Strait between Denmark and Sweden. In 2002, the Environmental Court defined the final terms and conditions for the wind farm development and the extent of the monitoring programme required.  Lillgrund wind farm came into full operation in 2008, and is currently the largest offshore wind farm in operation in Sweden.  The Swedish National Board of Fisheries conducted a monitoring programme, in the area, in the years before (2002–2005) and after (2008– 2010) the construction of the wind farm; a base line study and a study when the wind farm was operational, respectively. No investigation was conducted during the construction phase. The aim was to investigate the impact of the wind farm during the operational phase on the benthic and pelagic fish as well as on fish migration. These studies have partly been integrated into work conducted as a part of the Vindval Research Programme, funded by the Swedish Energy Agency.

    Acoustics (sound) 

    • The overall sound energy from the wind farm under water is mainly generated by vibration from the gearbox.

    • An analysis of the sound pressure level for the wind farm area, showed a correlation between noise level and the number of turbines in the wind farm (the so called park effect), where each individual turbine helps to increase the overall noise level in the area. 

    • Sound measurements from Lillgrund wind farm showed that noise levels within a distance of 100 metres from a turbine at high wind speeds are high enough to be a risk for some species of fish to be negatively affected, e.g. in the form of direct escape behaviour, or masking of vocal communication between individuals. 

    • Stress reactions can also occur at distances of more than 100 metres from a turbine. This is due to the fact that the noise from the turbines is continuous and louder than the ambient noise levels within some frequencies.   

    Measurements of the underwater noise levels were carried out at varying distances from individual turbines, from longer distances away from the entire wind farm as well as within a reference site (Sjollen) 10 km north of the wind farm. The results show that the wind farm produces a broadband noise below 1 kHz as well as one or two tones where the 127 Hz tone is the most powerful (vibrations from the first stage in the gear box). The majority of the overall underwater sound energy from the wind farm lies around the tone of 127 Hz.  The maximum noise levels, generated by the wind turbine, working at full production (12 m/s), at 1 m were 136 dB re 1µPa(RMS) for the dominant tone of the turbine which was 127 Hz (integrated across 123–132 Hz) and 138 dB re 1µPa(RMS) at the full spectrum (integrated across 52–343 Hz). At a distance of 100 m from the turbine, the noise levels are reduced to 104–106 dB re 1µPa(RMS) across the full spectrum, which is close to the locally measured ambient noise in the Öresund Strait, but the noise level was still around 23 dB above the background level for the 127 Hz tone.

    An analysis of the sound pressure level for the wind farm area showed a correlation between noise level and the number of turbines in the wind farm (called the park effect). Close to the wind farm (<80 m), the noise environment was dominated by the individual wind turbine with a calculated sound propagation loss of 17•log (distance). At greater distances (80 m to 7000 m) the sound propagation loss was non-linear and less than 17•log (distance). This is explained by the fact that the other turbines in the wind farm contributed to the total noise level. At even greater distances (>7 km) the entire wind farm functioned as a point source and the sound propagation loss was once again measured as 17•log (distance). The noise levels equivalent to those recorded and calculated from Lillgrund wind farm have not been shown to cause any physical injury to fish according to the current published scientific literature. It was only within some 100 metres from a turbine at high wind speeds that the noise levels were high enough to result in the risk of negative effects on some species of fish in the form of direct escape behaviour or possible masking of communication. The response depends upon the individual species’ sensitivity to sound. Fish have been shown to become stressed when they find themselves in a consistently noisy environment, which in turn can result in for example, lower growth rates or can have an impact on reproduction. Stress in general can also, in combination with other negative factors, make them more susceptible to disease etc., due to an impaired immune system. Animals can choose however, to remain in an area despite the disturbance, if the area is sufficiently important for their survival or reproduction.  Based on the calculated sound propagation around the wind farm, salmon and eel could theoretically detect the 127 Hz tone at 250 m and 1 km distances respectively at a productivity rate of 60 and 100 %, which is equivalent to a wind speed of approximately 6 and 12 m/s. The calculated distances would be limited by the hearing ability of both fish species and not the background noise levels in the Öresund Strait. For herring and cod, the theoretical detection distance was calculated to be between 13 and 16 km respectively for a production rate of 60 and 100 %. This distance should have been greater, but is limited for these species due to the ambient noise levels in the area. These calculations indicate that fish can potentially detect sound from the wind farm at relatively long distances. Local variations with regard to depth and physical barriers such as peninsulas, e.g. Falsterbonäset in the southern end of the Öresund Strait, can however, have a large impact on the actual sound propagation. 

    Benthic Fish

    • The temporal development of the fish community in Lillgrund was similar to that observed in the reference areas during the study period. For the wind farm as a whole, no effect was observed on species richness, species composition or on the abundance of fish. 

    • Several species of fish however, showed an increase in abundance close to the wind turbines compared with further away, especially eel (yellow eel) (Anguilla anguilla), cod (Gadus morhua), goldsinny wrasse (Ctenolabrus rupestris) and shorthorn sculpin (Myoxocephalus scorpius). The results reflect a redistribution of fish within the wind farm, rather than a change in productivity or migration from surrounding areas. The increase in abundance is probably due to the wind turbine foundations providing an opportunity for protection and improved foraging. The distance within which an increased abundance could be observed was estimated, for different species, to be between 50– 160 metres from a wind turbine. 

    • Fish distribution may to some extent have been influenced by the local acoustic environment, as a lower degree of aggregation close to the wind turbines at higher noise levels. The effect was most obvious for eelpout and eel (yellow eel). No response was seen for cod in relation to sound levels.   

    Changes in the species composition of the fish communities over time were studied in comparison with two reference areas. Of these, the northerly reference area (Sjollen) had a larger marine component than the southern reference area (Bredgrund). The species composition at Lillgrund had similarities with both of the reference areas.  The results from fish sampling with fyke nets and gill net series indicate that there have been no significant changes in the number of species, the species composition or the fish abundance after the wind farm was built, looking at the wind farm as a whole. Some changes have however been noted in relation to individual species. An increased catch of shore crab and eel (yellow eel) was observed during the first two years of production, but not in the third year. The catch of eelpout increased in all areas during the period studied, but to a slightly lesser extent at Lillgrund when compared to the reference areas. For the other species, the changes observed at Lillgrund were similar to at least one of the reference areas. These results suggest that the fish communities within the wind farm were primarily affected by the same general environmental conditions as the fish communities within the reference areas, rather than by the effects of the wind farm.  An analysis of the distribution patterns of fish close to the turbines showed an increased abundance in the immediate vicinity of the wind turbines in four of the eight species of fish studied: specifically shorthorn sculpin, goldsinny wrasse, cod and eel (yellow eel). The effects were seen already after the first year and were similar over all three years studied. An effect was also identified for eelpout, but only in 2010. The aggregation effect was seen within a distance of 50–160 metres from the wind turbines, different for the different species.  A comparison of the relative effect of different factors, based on the data from an extended survey in 2010, showed that the observed distribution pattern could be explained to a larger extent by the presence of the turbines rather than the underwater topography of the area. The analysis also indicated weak effects of the local acoustic environment on fish distribution patterns, with a reduced presence of fish at higher noise levels. The response was strongest for eelpout and eel. No response in relation to noise level was seen for cod. For shorthorn scuplin and common shore crab a response was seen only 11 Swedish Agency for Marine and Water Management Report 2013:19  during the autumn. The magnitude of the effect of noise was, however, lower than the aggregation effect. Hence, fish aggregated close to the wind turbines in all conditions, but the effect was weaker when the noise levels were higher. It is recommended that the the wind farm area is reinvestigated after a number of years to follow the long-term development of the fish populations, and to see if the aggregation effect observed continues and potentially also increases over time. A prerequisite for a long term positive development of fish abundance is that the removal of fish, such as from fishing or predation by marine mammals and fish-eating birds, does not increase in the area. 

    Pelagic Fish

    • There was a dramatic increase in commercial fishing for herring north of the Öresund Link (close to the north of the wind farm) in the first years of operation of the wind farm, in contrast to south of the bridge that forms a part of the Öresund Link, where it virtually completely stopped. This change may imply that the Rügen herring migration was affected by the Lillgrund Wind Farm. Due to the fact that there were other factors in addition to the wind farm contributing to the herring movements, it proved difficult to identify any correlation.   

    The evaluation was based on catch statistics from the commercial fisheries in the Öresund Strait (ICEs subdivision SD 23) and fisheries independent statistics from ICES for adult herring (Rügen herring) (ICES subdivision SD 21–23, western Baltic Sea and southern Kattegatt) and density of juvenile fish (ICES subdivision SD 24). There was a dramatic increase in commercial fishing for herring north of the Öresund Link in the first years of operation of the wind farm, in contrast to south of the bridge where it virtually completely stopped. The reason may be largely explained by the regulations banning drift-net fishing and a favourable market for herring, but potentially also because of the Öresund Link which was completed in 2000.The potential impacts of the wind farm are therefore difficult to distinguish from the impacts of these other factors because detailed resolution in the catch statistics are missing from the years before 1995 prior to the start of the building work on the Öresund Link. The statistics independent of commercial fishing from ICES showed no significant correlation between the density of herring juveniles in the western Baltic Sea and the number of adult herring (3 years old or more) in the following years in the Öresund Strait (ICES SD 21–24). There was however a weak tendency towards a negative development of the fish population over the period 1993 – 2010. The presence of Rügen herring and their migration through the Öresund Strait is likely strongly influenced by the fact that the population shows large fluctuations between the years. In addition, there is a possible overlapping effect on the soundscape from the wind farm and the Öresund Link, which has been in use since 2000.  Overall, the variety of factors together mean that it is difficult to identify any clear results with regard to if the migration of Rűgen herring is influenced by Lillgrund wind farm.

    Fish Migration 

    • According to the results from this work, the wind farm at Lillgrund is not a barrier for the migration of the eels that come into contact with it. An equally large proportion of the tagged and released silver eels (approximately one third) passed the transect line with receivers, at Lillgrund both before the wind farm was constructed (baseline study) and after it was in operation. 

    • There was no statistically significant difference indicating any alteration in the migration speed of eels, but there were occasional longer migration times when the wind farm was working at higher levels of production (>20 % of maximum) which may indicate that some eels are affected by the wind farm. The fact that the eels also showed a tendency towards being noted on fewer occasions than expected within the wind farm at low productivity (<20 %) and on slightly more occasions than expected at higher productivity (>20 %), could indicate that they have greater difficulty in navigating past the wind farm at higher levels of productivity than lower. 

    The impact of the wind farm on migration was studied via tagging of migrating silver eels. In total, 300 acoustically individually tagged eels were included in the study and of these, 100 contributed with useable information. The baseline study period started on a small scale in 2001 and ended in 2005. The majority of the eels were tagged and monitored during the production period (2008– 2010). All tagged silver eels were released south of the wind farm. 

    The results showed that an equally large proportion of the tagged and released silver eels; approximately one third, passed a transect with receivers at Lillgrund wind farm, both during the baseline period 2001–2005, and when it was in production 2008–2009. The greatest proportion of eels passed through the deeper part of the transect by the navigation channel Flintrännan close to the Danish border at Drogden during the production phase (31 %) and baseline period (43 %). A somewhat larger proportion of the eels were registered passing the most easterly part of the transect, close to Klagshamn, during the production phase (14 %) compared with the baseline period (5 %). A behaviour which occurred during the production phase, was that some individuals moved back to the release site, after being in the vicinity of wind farm. The most commonly observed behaviour during the study in 2010 was that an eel was registered moving south of the wind farm in a more or less northerly direction, but without being registered to the north of the wind farm.  The range in the time taken for the movement of the eels from the release site to the transect running through the wind farm was very great, from four to more than 1000 hours. There was no statistically significant difference in the time taken to travel, between periods with low production (<20 % of maximum) and periods with high production (>20 %) or for individuals which passed through or outside of the wind farm.  Even if the eels did not show any statistically significant behaviour, changes in movement patterns may occur for some individuals. The fact that there was a tendency towards longer periods of time taken for movement at higher production levels (not statistically significant) (>20 %) could indicate that some individual eels are influenced by the wind farm. The proportion of eels that took more than a week (168 hours) to make the journey was 48 % during the period with higher production (>20 %) compared with 28 % at lower production. No significant difference in the proportion of passes within or outside of the wind farm respectively could be shown. The eels showed however, – a tendency of being recorded on fewer occasions than expected inside the wind farm at low production levels (<20 %) and on more occasions than expected at higher production levels (>20 %). The irregularities in the proportions, compared with the expected result, could indicate that individual eels stayed longer in the wind farm when it was functioning at higher productivity. If the eels discover the wind turbine only when they are very close and do not change course, then other factors such as the speed of the current across the shallow marine areas become significant and can mean that the time spent in the area is shorter and records fewer. At high productivity, the eels may hesitate and/or divert their course and be recorded from close to or within the area, to then be recorded on the transect outside of the wind farm.  The mechanisms that lie behind the possible impact from the electromagnetic field or the noise pattern are difficult to distinguish, as both can have an impact on the same areas. Travelling speed showed no linear relationship with the level of production in the wind farm. 

    Conclusions

    The study at Lillgrund has resulted in an increase in the understanding of how offshore wind farms can affect fish, which is very valuable. Even within an international context, there are currently very few experience-based studies of offshore wind farms in operation.  The results from three years of monitoring during the operational phase show that the effects of the wind farm on fish populations and fishing were limited. One of the clearest results showed that some benthic fish species were attracted to the foundations of the wind turbines with their associated scour protection (reef effect). In addition, the effect on the local noise environment in the form of increased noise in the Öresund Strait was documented. The results of the eel tracking study may indicate that some eels are influenced by the wind farm on their migration. Some care should be taken however, when applying the results of these studies in other offshore environments and on a larger scale. The monitoring has only been carried out for three years and thus reflects only a short-term perspective. Lillgrund wind farm is also one of the first large-scale wind farms and is situated in an area with regular and noisy shipping traffic and both frequent and large variations in environmental factors such as salinity and currents.  A key knowledge gap that remains after the completion of this work is the lack of studies over a longer period of time, to help identify the long term ecological effects of, for example, the reef effect. Ideally, the wind farm should be re-visited after a number of years to see how the fish populations have developed over the longer term, and see if the observed aggregation of certain fish species close to the wind turbines continues, and to possibly see if any quantitative effects have taken place. Studies are also required in relation to how stress may affect fish species/individuals which choose the reef-like foundations and their noisier environment. Additional studies, primarily for the Baltic Sea, are also required to establish if there are any cumulative effects on migratory fish such as silver eels.

  • 3.
    Gullström, Martin
    et al.
    Perfomers of environmental monitoring, Universities, Stockholm University, SU, Department of Ecology, Environment and Plant Sciences.
    Sundblad, Göran
    Perfomers of environmental monitoring, Companies, Aquabiota Water Research AB.
    Mörk, Erik
    Svensk Ekologikonsult.
    Lilliesköld Sjöö, Gustaf
    Svensk Ekologikonsult.
    Naeslund, Mona
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU, Swedish Species Information Centre.
    Halling, Christina
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU, Swedish Species Information Centre.
    Lindegarth, Mats
    Institutionen för marina vetenskaper, Göteborgs universitet och Havsmiljöinstitutets enhet vid Göteborgs universitet.
    Utvärdering av videoteknik som visuell undervattensmetod för uppföljning av marina naturtyper och typiska arter: Metodsäkerhet, precision och kostnader2017Report (Other academic)
    Abstract [en]

    Nature conservation in Sweden is today strongly linked to nature conservation in the EU and is to a significant part regulated by various directives. The EU Habitat Directive is an important directive and focuses on conservation of biodiversity. This report presents a national study where the primary objective was to assess underwater video as a visual method for monitoring of marine habitats and typical species defined in the EU Habitat Directive. The overall goal is to develop a well-functioning and harmonized environmental monitoring program designated to protect and monitor our coasts and oceans. 

    The project is conducted within the framework of a joint project between the Swedish Agency for Marine and Water Management, the Swedish Environmental Protection Agency and the Swedish Species Information Centre, and the findings are the basis for the manual Visual underwater methods for monitoring of marine habitats and typical species (Havs- och vattenmyndigheten manus) and contribute to the project Biogeographic monitoring (contract 2574-13). The study was conducted during the summer of 2012 with the main objective to compare and evaluate data collected using four different photographic methods, two video analyzing methods and two still image analyses, among themselves and against data collected using SCUBA diving. Variables tested included taxonomic resolution, the ability to estimate various organisms’ coverage with good precision and the cost efficiency of the different methods. To get a general picture of the Swedish coast, five geographically dispersed areas were selected (from the Gulf of Bothnia in the northern Baltic Sea to the Koster archipelago near the Norwegian border). Within each area investigations were carried out on hard- and soft bottoms and included five replicates per bottom type. 

    The results show that SCUBA gives a higher taxonomic resolution than photographic methods, while video techniques where the whole film was analysed turned out to be better than image photography methods where a number of still images from the videos were analysed. Interesting from a monitoring perspective is that video analyses from the whole film showed equivalent precision and repeatability as SCUBA. Regarding costs, the findings showed that the photographic methods are clearly advantageous in comparison with SCUBA diving technique. To create a harmonized environmental monitoring instrument and to monitor marine habitats and typical species under the EU Habitat Directive underwater video can be regarded as an interesting and good option, as also other recent studies (e.g. Sundblad et al. 2013a, b, c) have indicated.

  • 4.
    Ledesma, Matias
    et al.
    Perfomers of environmental monitoring, Universities, Stockholm University, SU, Department of Environmental Science and Analytical Chemistry, ACES.
    Sundelin, Brita
    Perfomers of environmental monitoring, Universities, Stockholm University, SU, Department of Environmental Science and Analytical Chemistry, ACES.
    Vitmärlans reproduktion i Hanöbukten2018Report (Other academic)
    Abstract [sv]

    Havs- och vattenmyndigheten har fått i uppdrag från regeringen att utreda bakgrunden och orsakerna till problematiken i Hanöbukten. Denna rapport är en del i HaV:s arbete med regeringsuppdraget.

    Under de senaste åren har rapporter om problem hos kustfisk, sjöfågel samt förekomsten av brunt illaluktande vatten uppmärksammats i Hanöbukten och en utredning kring denna problematik startades därför 2011.

    Havs- och vattenmyndigheten, HaV, hade under 2013 ett regeringsuppdrag att utreda bakgrunden och orsakerna till problematiken, Havs- vattenmyndigheten 2013. De utredningar som HaV och Länsstyrelsen i Skåne tidigare genomfört har inte kunnat fastställa deras orsaker.

    Januari 2013 fick Havs- och vattenmyndigheten som regeringsuppdrag att vidare utreda bakgrunden och orsakerna till problematiken i Hanöbukten. Denna rapport är en del i HaV:s arbete med regeringsuppdraget.

    Anledningen till att vitmärlan inkluderades i studierna var att vi 2012 studerat reproduktionen hos vitmärlan på en station i norra delen av Hanöbukten inom det nationella miljöövervakningsprogrammet ”Missbildade embryon hos vitmärla”. Metoden är en rekommenderad metod inom ICES för att detektera effekter av miljögifter i sediment och är en ”precore indicator” inom HELCOM.

  • 5.
    Nilsson, Jessica (Editor)
    Swedish Agency for Marine and Water Management.
    Snoeijs-Leijonmalm, Pauline (Editor)
    Perfomers of environmental monitoring, Universities, Stockholm University, SU.
    Havenhand, Jon (Editor)
    Perfomers of environmental monitoring, Universities, University of Gothenburg, GU.
    Nilsson, Per (Editor)
    Perfomers of environmental monitoring, Universities, University of Gothenburg, GU.
    Scientific considerations of  how Arctic Marine Protected Area (MPA) networks may reduce  negative effects of climate change and ocean acidification: Report from the Third Expert Workshop on Marine Protected Area networks in  the Arctic, organised by Sweden and Finland under the auspices of the PAME  working group of the Arctic Council in Helsinki, Finland, 21-22 September 20172017Report (Other academic)
    Abstract [en]

    Rapid environmental changes in the Arctic

    During the last two decades, the Arctic region has become an area of international strategic importance for states, businesses, NGOs and other stakeholders. The rapid environmental changes in the Arctic create new opportunities for different actors that may impact negatively on ecological and social values. Global climate change and ocean acidification change the habitats of the cold-adapted organisms living in the Arctic, with the risk of exterminating unique biodiversity. Human-induced emissions of greenhouse gases (primarily carbon dioxide, methane and nitrous oxide) affect the balance between energy entering and leaving the Earth’s system resulting in global warming, melting of sea-ice (which increases heat absorption by the Arctic Ocean), and associated climate change. Approximately 27 % of the carbon dioxide released to the atmosphere every year is absorbed by the oceans. This keeps the atmosphere from warming as much as it otherwise would, but creates ocean acidification. In the Arctic region climate change and ocean acidification take place 10-100 times faster than at any time in the last 65 million years.

    Intention of the workshop

    This third expert workshop on Marine Protected Area (MPA) networks in the Arctic, organised by Sweden and Finland, was held in Helsinki (Finland) and its outcome is a contribution to the ‘‘PAME MPA-network toolbox’’ project. An MPA, as defined by PAME, is ‘‘a clearly defined geographical space recognized, dedicated, and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values’. An MPA network is a collection of individual MPAs or reserves operating cooperatively and synergistically, at various spatial scales, and with a range of protection levels that are designed to meet objectives that a single reserve cannot achieve. During this third expert workshop the scientific basis of how MPA networks may reduce negative effects of climate change and ocean acidification in the Arctic region was discussed. Workshop participants were mainly scientists with expertise on Arctic marine ecosystems, climate change, ocean acidification and/or MPAs. The intention of the workshop was not to reach consensus and provide a fixed list of recommendations, but rather to summarize: (1) the best available knowledge that can already be applied to the planning of a pan-Arctic MPA network, and (2) the primary uncertainties and, hence, what necessary scientific knowledge is still lacking. As such, the six main outcomes from the workshop below contribute to the scientific basis for the potential of MPAs as a tool to meet the threats posed by climate change and ocean acidification to Arctic ecosystems and livelihoods.

    A paradigm shift for establishing MPAs is necessary

    Given the rapid environmental changes and unprecedented rate of loss of Arctic sea ice there is an urgency to protect habitats that are essential for ecosystem functioning and to link MPAs in an international network. Humanity has now the opportunity of a pro-active and precautionary approach vis-à-vis the largely intact, highly sensitive and unique cold-adapted Arctic marine ecosystems. The current paradigm for the creation of MPAs seems to be that a direct regional or local threat needs to be proven before an MPA can be designated. However, climate change and ocean acidification are global processes that operate across the whole Arctic, and therefore this paradigm should be shifted towards one that establishes MPA networks to protect what is valued and cherished before it is harmed. This calls for applying the precautionary principle and creating Arctic MPA networks that will support resilience of biodiversity and ecosystem services to climate change and ocean acidification. Scientists are aware that not all desired knowledge for planning such networks is available at this time. This includes uncertainty associated with projecting the consequences of climate change across the physical (e.g. climate models), ecological (e.g. species diversity, ecosystem processes) to the human domain (e.g. ecosystem services, human well-being). Uncertainty about the effects of climate change and ocean acidification grows when moving from physical processes to ecology and finally to human well-being. Nonetheless, general ecological principles and additional experience from other regions (e.g. Antarctica, Baltic Sea) provide sufficient basic understanding to start designing a robust pan-Arctic MPA network already now and to develop and implement the necessary connected management measures.

    Existing MPA criteria need to be adapted to Arctic conditions

    Creating an MPA network for the Arctic will require adaptation of established criteria to the unique, and rapidly changing, character of the region. For example, optimal MPA locations for some MPAs in the Arctic Ocean may not be stationary in space and time; e.g. high-biodiversity marginal ice zone (MIZ) ecosystems will become more dynamic in time and space, contracting in winter and expanding in summer, with climate change. In order to account for the migration of species with moving physico-chemical conditions (so-called ‘climate tracking’) creating dynamic MPAs along oceanographic and climatic gradients may be a feasible and effective approach. Such focus on ocean features, the integration of other effective area-based measures next to MPAs, as well as the systematic integration of traditional and local knowledge (TLK), will be essential in the process of designating MPA networks. In so doing, the vulnerability and status of Arctic ecosystems to cumulative drivers and pressures from not only regional and local scales (fishing, tourism, pollution, etc.) but also global scales (climate change and ocean acidification) should be monitored and reviewed on a regular basis.

    Arctic MPAs should be located in areas that are expected to become refugia

    Climate change and ocean acidificationdo not operate in isolation but combine with regional and local environmental stressors to affect Arctic species, habitats, and ecosystems. It is possible to lessen the total stress burden and increase the resilience of biodiversity to the impacts of climate change and ocean acidification by mitigating stresses from direct anthropogenic pressures, such as habitat destruction, fishing, shipping, discharges of hazardous substances, etc., through establishing MPA networks. This will not ‘solve’ the underlying problems of climate change and ocean acidification, which can only be done by reducing atmospheric greenhouse gas emissions, but it will ‘buy time’ during which the underlying problems are addressed globally.

    Additional stresses should be targeted

    A key aspect is how to identify the location of prospective MPAs within a network. Since the effects of climate change and ocean acidification are unevenly distributed across the Arctic Ocean, it would be recommended to protect habitats that will act as refugia for Arctic biodiversity. For example, protecting the areas north of Greenland, where summer sea ice is projected to be most long-lasting, or parts of the Arctic Ocean where the supply of organic matter through permafrost melt, glacier melt, higher precipitation and higher river runoff (with increasing coastal CO2 concentrations through microbial activity) will be lowest. The 18 Arctic large marine ecosystems (LMEs) reflect the marine ecosystem variability in the region, and should be used to draft plans for MPA networks to more effectively consider representativeness.

    The scientific knowledge basis must be improved

    The workshop highlighted the need for a dedicated group to compile relevant geophysical and biological data for the purpose of MPA network planning. These data should include the changing environment, ‘spatial adaptation planning’, biochemical gradients, and identification of areas of high and low impact of climate change and ocean acidification. There is a wealth of information available (both reviews and analyses of knowledge gaps from CAFF, AMAP and others), that can be used for MPA planning but this information is highly scattered and needs to be collated and made spatially explicit, when possible. While the planning for MPA networks can start already now, there remains a large need for monitoring and relevant scientific research. This would require not only improved scientific cooperation between countries but also truly integrated international monitoring and research to decrease fragmentation and duplication of research.

    Identification of research priorities

    Gaps in knowledge identified by the workshop participants mainly concern the winter season, the vulnerability and resilience of the Arctic marine ecosystems and the need to support sustainable development. With respect to climate change much more is known about species higher up in the food web (seabirds, marine mammals, some fish) than about species lower in food web. For ocean acidification, most of the experimental work has been done on lower trophic levels. Much uncertainty surrounds the fate of Arctic ecosystems in a future world and how to deal with uncertainties is an issue that should be addressed in scientific studies. For example, the disappearance of strongly ice-associated species in many places will likely lead to a state-change in the associated ecosystem, yet the timing and nature of that change is currently unpredictable. While the basic drivers of the Arctic shelf-sea ecosystems are quite well understood, there is a massive lack of information at all trophic levels for the Central Arctic Ocean  LME, i.e. the deep central basin, and key species are difficult to identify. Presently, this high-latitude ecosystem is ice-bound, but climate projections indicate that it will become ice-free during summer within decades; the projected spatial and temporal variability is however very large and is likely not predictable. It is not known if native species will be able to adapt to the very rapid rates of change. It is also not known if more southern species that may migrate into the new ice-free areas will be able to adapt to certain local conditions that are not likely to change, e.g. the low nutrient availability in the Central Arctic Ocean . While many coastal areas may become more productive as melting terrestrial ice and snow transports nutrients to the sea, the Central Arctic Ocean is expected to remain nutrient-poor since no new nutrients are projected to reach this remote area with climate change. Clear is that the ecosystems of the Arctic Ocean, and especially the Central Arctic Ocean, face critical changes, which will be large and unprecedented, and that there is an urgent need for food-web studies and ecosystem modelling to inform the establishment of marine protection regimes in the Arctic.

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