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Issue n°28 - June 2015

Issue n°28 - June 2015
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In this issue

Lisa Maddison

As IMBER is located in Norway, and is becoming more involved locally, and with projects and organisations located in northern regions, this issue of the IMBER Update focuses on IMBER-relevant research in the north. We also introduce some of the people who recently took on an official role in guiding IMBER - the International Project Office (IPO) and the Regional Project Office (RPO) both got new leaders. Einar Svendsen now has the overall responsibility for the project and Yi Xu is in charge of the RPO in Shanghai, China. And three new members joined the Scientific Steering Committee.

Paul Suprenand has provided the first of what we hope will become a regular feature in the IMBER Update, where students and early-career researchers who have attended IMBER activities or events describe how they have helped to direct their careers. From Paul’s article, it seems that the IMBER ClimEco summer schools are doing something right! Watch out for an announcement soon for ClimEco5 that will be held next year!

The section on IMBER-related research includes interesting articles dealing with a variety topics, including autonomously observing change in the surface ocean carbon inventory, and a somewhat controversial review that indicates fish stock assessments rarely consider ecosystem drivers of stock production in fisheries management. Happy reading and if you would like to comment or contribute to the next IMBER Update, please contact me.

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IMBER in the North

Why IMBER IPO at IMR

Einar Svendsen

IMBER IPO, Institute of Marine Research, Bergen, Norway

 

Three years ago, on the initiative of Ken Drinkwater (co-Chair of the ESSAS regional programme), from the Institute of Marine Research (IMR) in Bergen, Norway, IMR (http://www.imr.no/en) agreed to host the IMBER International Project Office (IPO) with support from the Norwegian Research Council (NRC)). At that stage, IMR was in the process of developing a new science strategy for 2013-2017. Its vision was: To provideknowledge and advice for productive and clean ocean and coastal areas, and its aim was: To do research, monitor and give advice on marine ecosystems and aquaculture related to the basic (governmentally approved) societal mission of IMR: To develop the scientific basis for sustainable management of the living marine resources, aqua culture and the environment of the marine ecosystems. This leads to three strategic goals:

  1. Deliver the knowledge base for management of ocean and coastal areas
  2. Deliver and further develop advice for sustainable management of the marine ecosystems, their resources and aqua culture
  3. To be the national manager of marine data

IMR has about 750 employees, five research vessels and two aquaculture research stations. Although it focuses mainly on the north Atlantic, the Arctic, the Norwegian coast and the southern and western Africa, there are clear similarities with IMBER’s new science plan that is currently being developed. The proposed new vision is: Sustainable global oceans under global change for the benefit of society, and the main research goals for the next decade is to: Understand, quantify and compare historic, present and future structure and functioning of marine ecosystems, predict and project changes including developing future scenarios and options for securing or transitioning towards marine sustainability, and integrate these with ocean-human systems.

It is important to recognize that the usefulness of scientific research for society (such as providing management advice) is often linked to predictions/projections to create scenarios -looking into the future where observations do not exist. This is why mathematical models (and laboratory process studies) are so important (as seen in weather forecasting and e.g. IPCC climate predictions). However, most ecosystem models demonstrate low predictability or even ability to realistically quantify the observed ecosystem dynamics. As it is critical for organisms to continuously obtain food for survival, especially during the early life stages, it is my vision to be able to continuously (in time and space) quantify the marine ecosystem dynamics and thus, the overlap in space and time between prey and predators. By using a combination of observations and models this may be the clue to understanding recruitment variability, a puzzle put forward by Hjort 100 years ago that has still not been solved.

IMR focuses on being relevant to society by giving science-based management advice (particularly on fisheries), while IMBER aims to link natural and social sciences, a requirement that is gaining strength from European funding agencies. This approach has not been adopted by IMR, mainly because of not wanting to jeopardise the neutrality of providing assessments and advice on ecosystem status and productivity related to human pressures (fishing, aquaculture, pollution, eutrophication) and climate variability and change. It will therefore, be very interesting to see how IMBER’s ocean-human integration will influence the future science and advisory processes at IMR, both in Norway and globally.

 

IMR is a national institute with departments and research stations throughout Norway. The headquarters are in Bergen, where several other collaborating marine research institutions are also based. These include the University of Bergen (UiB), the Nansen Environmental and Remote Sensing Centre (NERSC) and UniResearch, that together make Bergen an extremely important marine science hub. In addition to the Bjerknes Centre for Climate Research (BCCR), these institutions have also formed the Hjort Centre for Ecosystem Dynamics (http://www.hjortcentre.no/en/projects/hjort-centre), that is co-located with the IMBER IPO at IMR. The vision of the Hjort Centre is to: Conduct cross-disciplinary research of natural and human-induced changes in marine ecosystems with the aim of increasing the sustainable harvest of living resources, also very related to IMBER and another good reason for IMR to host the IMBER IPO.

In a recent paper by Kjesbu et al., 2014, they state that currently many exploited fish populations, including several of the Atlantic cod stocks, are at historically low levels and question whether contemporary management is capable of facilitating population recovery. By contrast, the spawning stock biomass of Barents Sea cod is at an historic high, demonstrating that successful management actions interacting synergistically with the prevailing climate has resulted in this increase. Warming of water masses in the Barents Sea over the last decade positively reinforced management actions while the stock adjusted to suitable new feeding areas with the northernmost distribution (in 2012) ever seen. This adjustment is linked closely to community dynamics and increased stock productivity. During the same period, the mackerel stock also reached record highs and has drastically extended its feeding area into the northern Norwegian Sea.

The question has been raised at IMR regarding what will happen if the climate gets colder and marine production is reduced. Will there be enough food to feed the large fish stocks, particularly at the polar extremes of their distribution? But why would it become colder when climate predictions generally suggest warming, particularly at high latitudes?  Some of the world’s longest vertical profile (0-250/300m) time-series observations of temperature and salinity, recorded along the coast of Norway since 1935, show cooling trends after 2006-7 of about 0.03-0.05  C/year (Svendsen et al. in prep.). Several other climate monitoring data in northern waters show similar trends (see the ICES IROC report). Arctic ice cover (http://arctic-roos.org/observations/satellite-data/sea-ice/total-icearea-from-1978-2007) was not reduced during the same period, and long term Russian data from the Barents Sea indicate that warming has stopped. The Russian and Norwegian data also indicate a multi-decadal variability, which may be part of the Atlantic Multidecadal Oscillation demonstrated by the AMO-index (see figure), a temperature index with a period roughly between 60-80 years.

If this multi-decadal signal continues, it could balance, or even override, the greenhouse effect in the northeast Atlantic and Arctic over the next three decades. Observations indicate that this is already happening. Temperatures have been reducing for less than 10 years, and it may perhaps a bit premature predicting a colder (or not warmer) marine climate for the next 20-30 years. After about 2050, when the AMO is expected to turn positive again, thus adding to the greenhouse effect, temperatures could increase far beyond those previously experienced. It is difficult to predict the impacts of this on the functioning of our ecosystems, and also of the added impact of ocean acidification.

     
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Figure 1. The Atlantic Multidecadal Oscillation Index developed for 157 years, expressed as de-trended, standardized anomalies, i.e. excluding the anthropogenic signal.

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A new collaborator for IMBER – the Hjort Centre

Annette Samuelsen1,2 and Olav Sigurd Kjesbu2*

1Nansen Environmental and Remote Sensing center, Bergen, Norway

2Hjort Centre for Ecosystem Dynamics, Bergen, Norway

* corresponding author, e-mail: olav.kjesbu@imr.no

 
HJORT Centre

The Hjort Centre was officially opened in Bergen, Norway, on 18 February 2014. It is named after Dr. Johan Hjort (1869-1948) who is considered a founding father of marine sciences. The Centre represents a cluster of marine research institutions in Bergen, comprising the Institute of Marine Research (IMR), the University of Bergen (UiB), Uni Research and the Nansen Environmental and Remote Sensing Center (NERSC). It is organized as a formalised research program with extensive collaboration involving about 90 scientists. The Director, Dr. Olav Sigurd Kjesbu, administrative staff and five ‘science motivators’ coordinate the Centre. Financial support is provided by the participating institutions, as well as the research project portfolios of the individual members. The Centre has thus far, employed four Postdocs and one senior researcher full-time. The ‘Scientific Council’ consisting of leading senior researchers from the member institutions provides scientific guidance. During the first year, four workshops were arranged to enable the members to develop the Science Plan for the Centre. This was finalized at the beginning of this year. In 2014, the Hjort Centre members reported 44 peer review publications on marine ecosystem processes.

The research questions on fish recruitment and stock variability addressed by Johan Hjort 100 year ago are still of ecological and economic relevance. While most of our food currently originates from land-based farming, approximately half of the global biological production takes place in the oceans. Along with a growing human population comes an increasing need to utilize the marine living resources, but this must occur in a sustainable manner. This is one of the major issues that the Hjort Centre for Marine Ecosystem Dynamics will address. This requires better understanding of all parts of the marine ecosystem, from the physical environment and planktonic communities, to fish and the impact of human activities. It is also necessary to understand how climate change can alter the marine ecosystems.

The Centre’s research is focused around six central themes that contribute to its scientific vision and also plays to the complementary strengths of the members of the Hjort Centre. In the Science Plan each theme is associated with key research questions and a plan on how the Centre will specifically address these. The first four themes are: 1) ‘Dynamics of ocean primary productivity’, 2) ‘Dynamics of trophic pathways’, 3) ‘Dynamics of harvestable resources’, and 4) ‘Dynamics of marine ecosystems under past, present and future climate’. The first three focus on different trophic levels and processes in the marine ecosystem, while Theme 4 focuses on how the marine ecosystems have and will respond to climate variability and change.  The remaining two themes are: 5) ‘Observation methodology’ and 6) ‘Integrative modelling’. These are overarching themes that address methodological developments that will benefit all the themes.

 

The research objectives will be achieved by exploring innovative and new experimental designs, both in the laboratory and in the field. This will be combined with the use of extensive data series in advanced programs for new model developments. Laboratory, mesocosm and field studies will be used to depict and understand central biological and oceanographic processes. The Centre will also take advantage of recent developments in genetic tools and in acoustics (e.g. submerged echo-sounders). Remote-sensing satellite technology can provide a global view of the surface oceans, and currently an increasing number of autonomous sensors provide information from the ocean interior. Numerical ocean models provide tools to understand and interpret key processes across spatial and temporal scales and across trophic levels. However, there is still a great need for technological improvements to properly address key questions in ecosystem processes and dynamics studies. The Hjort Centre will advance marine research by continuously exploring and adopting new technologies and methodologies for monitoring, analyzing and predicting current and future states of marine ecosystems.

The proposed research requires collaboration between different disciplines, both within the Centre and beyond. The Hjort Centre is therefore, organized to encourage creative and productive discussions amongst researchers and students with different scientific backgrounds. In the first year several seminars and workshops involving all the participating institutions were arranged. Scholarships for visiting researchers are awarded annually. There is currently a ‘Hjort Scholar’ visiting Bergen and another will follow later in the year. The education and recruitment of students and postdocs are also important, and in early September the Hjort Centre will hold its first Summer School titled ‘Fishing and physics as drivers of marine ecosystem dynamics’ at UiB’s Espegrend field station, near Bergen.

The oceans are global and fish and other marine organisms follow the currents and migrate between different countries’ economic zones. No single discipline, research community or nation can fully explain the changes that are currently occurring in the oceans, nor can they predict future changes and consequences. The Hjort Centre has established an extensive international network of collaborators to compare different marine ecosystems and seeks to find global solutions.  IMBER, with the International Project Office conveniently located down the hall from the Hjort Centre, will be a key partner in developing the global aspects of the research. The FAO-supported Nansen Program that focuses on sustainable fisheries in developing countries is also central to the Hjort Centre. Hence, in collaboration with the international research community, the Centre will examine various marine ecosystems in different geographical regions to be able to undertake thorough comparative studies on productivity and other characteristics of marine ecosystems under different biological and physical conditions.

Please visit our web-site www.hjortcentre.no for further information.

     
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New ESSAS Arctic Project

Ken Drinkwater1, Franz Mueter2 and Sei-Ichi Saitoh3

1Institute of Marine Research, Bergen, Norway

2University of Alaska Fairbanks, Fairbanks, Alaska, USA

3Arctic Research Center, Sapporo, and Graduate School of Fisheries Sciences, Hakodate, Hokkaido University, Japan

 

The international RACArctic (Resilience and Adaptive Capacity of ARCTIC marine systems under a changing climate) Project developed by the Ecosystem Studies of Sub-Arctic Seas (ESSAS) regional programme of IMBER was recently awarded funding for a synthesis activity under the Belmont Forum call on Arctic Observing and Research for Sustainability. The project, which is funded for three years and begins in July 2015, is a joint undertaking by Japan, the USA, and Norway to synthesize information from completed and ongoing regional studies on how climate variability and change in the Subarctic to Arctic transition zones may affect future marine ecosystems of the Pacific and Atlantic Arctic (see Fig. 1 for geographic areas of focus). In particular, it will examine how fish populations and their prey are able to adapt or respond to natural and anthropogenic changes in the Arctic and how these are expected to affect existing and future fisheries, subsistence harvests, and the socio-economic systems that depend upon them. The project also will incorporate input from user groups who directly or indirectly depend on living marine resources and assess the strengths and weaknesses of current management institutions in Japan, the USA and Norway in terms of their capacity to successfully meet the anticipated challenges associated with global warming and ocean acidification.

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Figure 2. Physical geography of the Arctic highlighting the Subarctic-to-Arctic transition zones in the Pacific and Atlantic Arctic that are the principal areas of investigation within RACArctic. The red line denotes the location of the 10˚C July isotherm for air temperatures.

 

The project is headed by the three ESSAS co-chairs, with Dr. Sei-Ichi Saitoh taking the overall lead while Dr. Franz Mueter heads the US team and Dr. Ken Drinkwater the Norwegian team. During its initial years, ESSAS focused almost exclusively on the Subarctic regions. More recently its work has extended into Arctic-Subarctic interactions, in particular the physical and biological consequences of exchanges between the Subarctic and Arctic. This put ESSAS in a good position to put together a strong proposal in response to the Belmont Forum call. In selecting national team members for RACArctic, an attempt has been made to achieve a balance between natural scientists, economists, social scientists, and representatives of user groups, while also drawing on past and current international collaborations, where possible. 

Because direct experiments on large ecosystems are not practical, an alternative method to study ecosystems is through a comparative approach. Contrasting different systems can provide insights into what are fundamental ecosystem processes and what might be unique to a particular ecosystem (Murawski et al., 2010). Thus, the emphasis in RACArctic is on a comparative synthesis. This approach  has been used by ESSAS since its inception in 2005, to highlight the importance of climate variability in driving tropho-dynamic interactions in these systems and to determine the dominant processes by which climate influences ecological communities (see e.g. Mueter et al., 2009; Link et al., 2012, Hunt et al., 2013). The RACArctic Project will build upon and extend these ESSAS studies, as well as incorporate other recent research.

 

Future reductions in sea ice due to anthropogenic forcing and the associated changes in productivity are expected to affect marine fish, marine mammals and seabirds in the Subarctic and Arctic. Anticipated changes include fish movements from the Subarctic towards the Arctic, with changes in local productivity and abundance. While the nature and magnitude of such effects will vary in different ecosystems, they are of interest because existing fisheries will be affected and potentially new fisheries will develop in areas where currently none exist. Also, fish are prey to marine mammals and seabirds that provide a livelihood for many Arctic inhabitants, especially indigenous peoples. Marine mammals, such as walrus and some seals that use sea ice for hauling out or birthing could lose their habitat. Much of the variability in the Subarctic to Arctic transition zones is tied to advection of warmer waters into the Arctic. This transport is highly variable and its effect on the ecology is poorly understood. With warming, there is uncertainty about whether the primary productivity of the Arctic will increase or decrease. On the seasonally ice-covered Arctic shelves, primary production is expected to increase due to a longer growing season, but to what extent this added production would become available to fish is not known. In addition to warming, ocean acidification is also particularly pronounced in high-latitude regions as the decline in sea-ice coverage allows more CO2 to enter oceanic waters and cold water more readily absorbs CO2. Continued sea-ice loss is likely to result in aragonite undersaturation that will directly impact calcifying organisms as waters become corrosive to their shells, several species of which are prey for commercial fish populations.  These are just a few of the issues that RACArctic will attempt to address as part of the syntheses.

The syntheses will be achieved principally through a series of three workshops, one in each of the sponsoring nations, coupled with inter-session work. The first workshop will be held in Japan in the spring of 2016, where each nation will review the main processes whereby climate influences their particular ecosystems. A plan will be established at this meeting for the development of the comparative syntheses. The second meeting will be held in early 2017 in Alaska where the emphasis will be on user input. This will largely be from Alaskan indigenous peoples as well as local fishing companies, fishers and other fishing communities. Users from Japan and Norway will also be invited to provide their perspectives. The final workshop will be held in late 2017 in Norway and will include scientific investigators and other stakeholders from the three countries. The syntheses will be completed here and plans for writing scientific papers and reports based on the results from the project, will be made. These will include stakeholder summaries that evaluate the potential sustainability of Arctic marine ecosystems under climate change and provide recommendations for both the fishing industry and northern communities to prepare for potential problems they might encounter. They will be written by a team consisting of both scientists and user groups. Recommendations on future internationally coordinated research and monitoring activities will also be made.

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Figure 3. With the reduction of sea-ice area in the Arctic and Subarctic, some marine mammals such as these walrus, will lose habitat for hauling out and resting.

To our knowledge, this is the first international project that draws on similar and complimentary research programmes across the Pacific and Atlantic Arctic to assess the resilience and adaptive capacity of Arctic marine systems to climate variability and change, with an emphasis on fish and fisheries and including socio-economic subsystems. ESSAS looks forward to this exciting challenge!

References

  • Hunt G.L. Jr., Blanchard, A.L., Boveng, P., Dalpadado, P., Drinkwater, K., Eisner, L., Hopcroft, R., Kovacs, K.M., Norcross, B.L., Renaud, P., Reigstad, M., Renner, M., Sjkoldal, H.R., Whitehouse, G.A., Woodgate, R. 2013. The Barents and Chukchi Seas: Comparison of two Arctic shelf ecosystems. J. Mar. Sys. 109-110: 43-68.
  • Link, J.S., Gaichas, S., Miller, T.J.,  Essington, T., Bundy, A., Boldt, J., Drinkwater, K.F., Moksness, E. 2012.  Synthesizing lessons learned from comparing fisheries production in 13 Northern Hemisphere ecosystems: Emergent fundamental features. Mar. Ecol. Prog. Ser. 459: 293-302.
  • Mueter F.J., Broms J., Drinkwater K.F, Friedland K.D., Hare J. A., Hunt G.L, Jr., Melle W., Taylor M. 2009. Ecosystem response to recent oceanographic variability in high-latitude Northern Hemisphere ecosystems. Prog. Oceanogr. 81: 93-110.
  • Murawski S.A., Steele J.H, Taylor P., Fogarty, M.J., Sissenwine, M.P., Ford, M., Suchman, C.   2010. Why compare marine ecosystems? ICES J. Mar. Sci. 67: 1-9.
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Canadian Research in the North

Kumiko Azetsu-Scott

Oceanography and Climate Section, Ocean and Ecosystem Sciences Division, Department of Fisheries and Oceans, Bedford Institute of Oceanography, Canada

 
Canada has by far the longest coast line in the world and diverse research activities are ongoing and planned in the near future, both nearshore and offshore. Although most marine research in Canada falls in the category of “Research in the North”, Canadian research in the Arctic, a geographic region defined by the Arctic Monitoring Assessment Programme (AMAP, http://www.amap.no/about/geographical-coverage) as the area north of 51.1º N, including the Hudson Bay system and the Labrador Sea, will be summarized. Ongoing and planned activities in the Arctic include long term monitoring programs and process studies of limited duration.  The former is mainly maintained by government organizations, such as Fisheries and Oceans, Canada (DFO), and the latter is conducted by scientists at universities in collaboration with scientists from government laboratories and industries.  Table 1 provides an overview of the programs being undertaken and Figure 1 depicts the regions where they are carried out.
 
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Figure 4.  Research regions.  The numbers correspond to the projects in Table 1.

 
 
Table 1. Research Programs in the Canadian Arctic
  Program names Region Lead PI(s)
Time series studies
1

JOIS-BGOS

http://www.whoi.edu/beaufortgyre/expeditions

Beaufort Sea Bill Williams (IOS) and Andrey Proshutinsky (WHOI)
2

Davis Strait

Http://iop.apl.washington.edu/projects/ds/html/overview.html

Davis Strait, S. Baffin Bay, N. Labrador Sea Craig Lee (UW) and Kumiko Azetsu-Scott (BIO)
3

AZOMP

http://www.bio.gc.ca/science/monitoring-monitorage/azomp-pmzao/labrador/labrador-eng.php

the Labrador Sea Igor Yashayaev, Kumiko Azetsu-Scott and Erica Head (BIO)
4

DFO's Arctic Real Time Ocean Observatory

http://www.bio.gc.ca/science/newtech-technouvelles/observatory-observatoire-eng.php

Barrow Strait, CAA Jim Hamilton (BIO)
process studies
5

ArcticNet

http://www.arcticnet.ulaval.ca

S. Beaufort, CAA, Baffin Bay Louis Fortier (Univ. Laval)
6

GEOTRACE

http://www.geotraces.org

Baffin Bay, CAA, Canada Basin Roger Francois (UBC)
7

GREENEDGE

http://www.greenedgeproject.info

Baffin Bay Marcel Babin (Univ. Laval)
8

VITALS

http://knossos.eas.ualberta.ca/vitals

the Labtador Sea Paul Myers (Univ of Alberta)
9

BaySYS

http://umanitoba.ca/faculties/environment/departments/ceos/research/1187.html

Hudson Bay David Barber (University of Manitoba)
10

SERF

http://home.cc.umanitoba.ca/~wangf/serf

Winnipeg, MB Fei Wang (University of Manitoba)
11

Arctic Scinece Partnership

http://www.asp-net.org

Baffin Bay, CAA and Greenland coastal area Søren Rysgaard (Univ of Manitoba, Greenland Climate Research Institute and U. of Aarhus)
Research Station
12

CHARS

http://www.science.gc.ca/default.asp?lang=En&n=6B43B3E0-1

Cambridge Bay Aboriginal Affairs and Northern Development Canada
 
 

The major circulation around Canada’s north is a flow from the Pacific to the North Atlantic through the Canadian Arctic Archipelago (CAA).  This Pacific Water, which flows into the Arctic through the Bering Strait, is modified by sea ice formation/melting and freshwater input from rivers and glacial meltwater before flowing out to the northwest Atlantic.  The Atlantic Water from the south circulates cyclonically in Baffin Bay and the Labrador Sea.  The outflow from the Hudson Bay system travels south along Canada’s east coast together with the Arctic outflow.  The on-going and planned studies in the next few years are summarized from west to east, i.e., the upstream to the downstream.  The list of programs discussed below is not exhaustive, since many regional scale projects in coastal regions and modelling projects are not included.

In the Beaufort Sea and Canada Basin, the Joint Ocean Ice Study (JOIS), in collaboration with the Beaufort Gyre Observing System (BGOS) and Japanese collaborators, has been investigating basin-scale mechanisms that regulate freshwater content in the Arctic Ocean and particularly in the Beaufort Gyre since 2003, using the Canadian icebreaker, CCGS Louis St. Laurent.  The “Canadian-Arctic-GEOTRACE” will start its field season in 2015 to the Beaufort Sea and Canada Basin through Baffin Bay and CAA to identify processes and quantify fluxes that control the distribution of trace elements and isotopes.  Fishes and beluga whales are monitored in the Beaufort Sea by scientists from the Freshwater Institute, DFO. 

In the CAA, DFO’s Arctic Real Time Ocean Observatory is located in the Barrow Strait in the eastern Northwest Passage, near the long-time monitoring site of the Bedford Institute of Oceanography (BIO), started in 1998, to explore the relationships between ocean properties, ice and biota to better understand climate change impacts on the Arctic ecosystem.  The Canadian High Arctic Research Station (CHARS) is newly built and expected to provide a world-class hub for science and technology research in Cambridge Bay, Nunavut.

Many research programs will focus on Baffin Bay/Davis Strait in the coming years. The ArcticNet is one of the largest Arctic research consortiums in Canada that brings together scientists and managers in the natural, human health and social sciences with their partners from Inuit organizations, northern communities, federal and provincial agencies and the private sector to study the impacts of climate change in the coastal Canadian Arctic spanning from Baffin Bay to Beaufort Sea. The GreenEdge project investigates spring bloom at the ice edge using multiple platforms including ship-based ice camp based experiments, Argo floats, gliders and remote sensing in Baffin Bay.  As a part of Arctic Science Partnership among University of Manitoba, Greenland Climate Research Institute and University of Aarhus, Denmark, research on ice-ocean-atmosphere and land-ocean interaction in Baffin Bay, CAA and seas around Greenland has been conducted since 2011 and will continue for the next few years.  Multi-species offshore fisheries are monitored in Baffin Bay, Davis Strait and Hudson Strait as well as inshore fisheries and marine mammals in the Baffin Island coastal area by DFO in partnership with the Ocean Tracking Network (http://oceantrackingnetwork.org/ ). Four-year studies in Hudson Bay coastal regions start in 2015 to understand the influence of hydro-regulation and variability in regional discharge of major rivers entering the Bay. A unique 

 

Sea Ice Experimental Research Facility (SERF) in Winnipeg enables scientists at the University of Manitoba to conduct mesocosm experiments on ocean-ice-air interactions.  Davis Strait, the northern Labrador Sea and southern Baffin Bay have been monitored since 2004 as a collaborative project between University of Washington and BIO. The purpose of this monitoring project is to quantify the variability of fluxes (heat, freshwater, carbon and nutrients) between the Arctic and sub-polar oceans, to understand the role played by the Arctic and sub-Arctic in steering decadal scale climate variability and to establish a pan-Arctic integrated observing network.  This monitoring project is composed of year round measurements using an extensive mooring array, gliders and annual (2004-2013) and bi-annual (2015- ) hydrographic surveys.

Deep convection in the Labrador Sea in late winter varies from 200 m to over 2000 m, and produces a homogeneous, cold and low salinity water mass, Labrador Seawater (LSW). North East Atlantic Deep Water (NEADW) and Denmark Strait Overflow Water (DSOW), which are produced by winter convection in the Nordic Seas, flow into and occupy the depths of the Labrador Sea. The LSW, NEADW and DSOW comprise and drive the deep part of the meridional overturning circulation. Therefore, observations in the Labrador Sea offer early detection of changes occurring in the deep water in the North Atlantic. The Atlantic Zone Off-Shelf Monitoring Program (AZOMP) in the Labrador Sea, generally referred to as the AR7W line, started in the early 1990’s to monitor variability in the ocean climate, with scientists from BIO measuring physical, chemical and biological parameters every spring. A new program, “VITALS – Ventilation, Interactions and Transport Across the Labrador Sea) is a pan-Canadian initiative, involving scientists from universities and government laboratories, industrial and foreign partners, to study gas and heat exchange processes between the deep ocean and the atmosphere using state of the art technologies including fixed (SeaCycler) and mobile platforms (gliders, Argo floats) and modelling.

Arctic research is costly due to its logistics, so national and international collaboration is essential. Most of the Canadian research in the North are interdisciplinary and conducted in collaboration with scientists in different sectors and countries. Northern research in Canada is important not only for addressing the large scale climate issues, but also for sustainability of the local communities. Both monitoring and process studies need to be continued to understand the role of the polar oceans in global climate and to mitigate and adapt to the rapidly changing marine environment for the people who live in the North.

 
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IMBER-related research and activities

A generic concept for the vertical distribution of fish eggs in the world oceans

Svein Sundby and Trond Kristiansen

Institute of Marine Research and Hjort Centre for Marine Ecosystem Dynamics, Bergen, Norway

 

Unlike phytoplankton and zooplankton, vertebrate fish plankton have the physical-biological attributes to keep the salinity of their internal body fluids constant, independent of the ambient salinity (Smith 1930; Riis-Vestergaard 2002), through active osmoregulation. Consequently, the body fluids of fish have a salinity of about 11-12, which is not particularly dissimilar to that of humans. Moreover, the buoyancy of marine fish eggs relative to the ambient seawater remains practically unchanged under varying ambient temperature and pressure (Sundnes et al. 1965; Coombs et al. 1985), indicating that these (ectothermic) eggs have similar thermal-and pressure-dependent expansion properties as the ambient seawater. Although in principle this is not actually correct, it appears to be for all practical purposes (Sundby and Kristiansen submitted). This implies that the specific gravity of marine fish eggs can be measured by reference to salinity alone. Coombs (1981) introduced a salinity gradient to measure the specific gravity of marine fish eggs with high precision. This made it possible to simulate vertical distributions of the eggs based on the 1) vertical salinity profile, 2) vertical turbulent mixing in the water column, and 3) measures of the eggs’ specific gravity (Sundby 1983; Sundby 1991). 

The large majority of fish spawn in coastal regions and above the continental shelves where salinity increases with depth (red regions in Fig. 5).  Here, fish eggs are distributed pelagically, mesopelagically or as bottom eggs, depending on their neutral buoyancy in relation to the salinity profile (Fig. 6). However, in the large parts of the oceanic regions, i.e. mainly in the subtropical gyres, the Gulf of Mexico, and in the eastern boundary upwelling ecosystems, except the California Current, salinity decreases with depth (blue regions in Fig. 5). Here, only pelagic fish eggs can occur in steady-state vertical distributions (shown in Fig. 6). Typical examples of pelagic distributions in these regions are eggs from sardines and anchovies. These species spawn in the high salinity upper layer and their eggs are positively buoyant. Mesopelagic eggs, in the red regions of Fig. 5, are neutrally buoyant and float at the halocline. But such eggs cannot exist in the blue regions. Therefore, there are specific limitations to the depth layers at which these deep-spawning fish can successful reproduce. Deeply distributed eggs in the blue regions do not have an equilibrium distribution where buoyancy balances turbulent mixing. They must rise or sink until they hatch, at which time larval behaviour can take control of their vertical distribution. Only eggs spawned above the depth level of their neutral buoyancy will be able to ascend to the pelagic level (Fig. 7) where the larvae are able to feed successfully. Spawning below the level of neutral buoyancy would cause the eggs to sink out of the water column and be lost for recruitment. Hence, a critical spawning layer exists in the blue regions of the world’s oceans (Fig. 7). Spawning must take place above this layer in order to transport the offspring up into the planktonic layer where the hatched larvae would be able to feed and survive. An example of such adaptive behaviour is the spawning of Cape Hake (Merluccius capensis) in the Northern Benguela (Sundby et al. 2001). Hake spawn “at the edge” at between 150 and 350 m depth. The eggs are slightly buoyant so that they rise fast enough to avoid the suboxic and anoxic layers above the seabed, but slow enough to avoid hatching in the offshore-directed Ekman layer where the larvae would be swept offshore and lost for recruitment.

This is a summary of manuscript submitted to the primary literature in March 2015.

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Figure 5. Difference between salinity at the surface and at 500 m depth in the world’s oceans. Regions with increasing salinity with depth (red regions) include the most of the coastal regions and the Arctic and the Antarctic. Regions with decreasing salinity with depth (blue regions) include the subtropical gyres, the eastern boundary upwelling ecosystems (except the California Current), the Somali Current, the eastern Mediterranean and the oceanic part of the Northeast Atlantic. (After Sundby and Kristiansen, submitted).

 
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Figure 6. a) The three major types of marine fish eggs based on buoyancy distributions with salinity as reference in coastal regions (red regions in Figure 5). b) Salinity structure in the red regions. c) Resulting vertical distributions of pelagic, mesopelagic and bottom eggs.

Pelagic eggs have a lower specific gravity than the upper mixed layer in b). Mesopelagic eggs have specific gravity overlapping with that of the halocline. Bottom eggs are heavier than the bottom layer. These three main buoyancy distributions are vertically distributed as in c). The figure is a synthesis from Sundby (1983; 1991).

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Figure 7. Left panel: Vertical salinity profile in the Northern Benguela upwelling ecosystem off Namibia where the Cape Hake (Merluccius capensis) spawn offshore at about 150-350 m depth. The average neutral buoyancy of the eggs (with salinity as reference) is 34.6. The eggs rise slowly towards the surface and hatch subsurface after about 4-5 days, before they reach the Ekman layer. If eggs are spawned below the critical spawning layer, they will sink out of the water column and would be lost for recruitment.

     

References

  • Coombs SH. 1981. A density-gradient column for determining the specific gravity of fish eggs, with particular reference to eggs of the mackerel Scomber scombrus. Mar. Biol. 63: 101–106.
  • Coombs S, Fosh C, Keen M. 1985. The buoyancy and vertical distribution of eggs of sprat (Sprattus sprattus) and pilchard (Sardina pilchardus). J. Mar. Biol. Assoc. UK. 65: 461–474.
  • Riis-Vestergaard J. 2002. Energy density of marine pelagic fish eggs. J. Fish. Biol. 60: 1511–1528.
  • Smith H.W. 1930. The absorption and excretion of water and salts by marine teleosts. Am. J. Physiol. 93: 480-505.
  • Sundby S. 1983. A one-dimensional model for the vertical distribution of pelagic fish eggs in the mixed layer. Deep-Sea Res. Part A. 30: 645–661.
  • Sundby S. 1991. Factors affecting the vertical distribution of eggs. ICES Mar. Sci. Symp. 192:33–38.
  • Sundby S., Boyd A., Hutchings L., O’Toole M., Thorisson K., Thorsen A. 2001. Interaction between Cape hake spawning and the circulation in the Northern Benguela upwelling ecosystem. S. Afr. J. Mar. Sci. 23: 317-336.
  • Sundby S. and Kristiansen T. 2015. The principles of buoyancy in marine fish eggs and their vertical distributions across the world oceans. Submitted. 
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Observing changes in the surface ocean carbon inventory, autonomously

Andrea J. Fassbender and Christopher L. Sabine

NOAA Pacific Marine Environmental Laboratory, Seattle, WA, USA

 

The ocean exerts significant influence on global climate through carbon cycle feedback mechanisms that affect the air-sea exchange of carbon dioxide (CO2) gas (Passow and Carlson, 2012; Ciais et al., 2013). Many of these feedback mechanisms are influenced by biological processes for which preindustrial baseline information does not exist. Thus, in a climate now transitioning away from preindustrial equilibrium, biogeochemical feedbacks may be even more challenging to discern and quantify.

In recognition of this issue, an immense effort has gone into the quantitative characterization of marine carbon cycling and biological carbon export from the surface ocean over the past few decades (e.g., Emerson, 2014). In particular, numerous investigators have worked to advance the technology available for autonomous carbon cycle studies (Johnson et al., 2009; Schuster et al., 2009) to learn more about the interplay of thermodynamic and biogeochemical controls on the observed global air-sea CO2 exchange. The marine inorganic carbon system is often described by four primary parameters: dissolved inorganic carbon (DIC), total alkalinity (TA), CO2, and pH. DIC is the sum of dissolved molecular species derived from CO2. TA is a measure of the seawater charge balance. Measurement of any two of these four parameters, in addition to salinity and temperature, can be used to calculate all of the other carbonate system parameters (Millero, 2007) and to quantitatively evaluate the drivers of marine carbon cycling.

In the past 10 years, autonomous CO2 and pH sensors have become commercially available for moorings enabling the collection of high-frequency (<daily) time series observations of the carbonate system (Sutton et al., 2014). Unfortunately, CO2 and pH are the least ideal pair to constrain the carbonate system due to their strong covariance. Uncoupling of the CO2 and pH uncertainties leads to large errors in the calculations of DIC and TA (>100 µmol kg-1(Dickson and Riley, 1978; Cullison Gray et al., 2011). Recognizing the challenges associated with further improving autonomous CO2 and pH sensor measurement accuracies (~1 µatm and ~0.003, respectively), we set out to develop an autonomous surface ocean DIC sensor for moored application.

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Figure 8. Diagram of the MADIC system. The equilibrator and electronics tubes house the primary instrument components and are shown here without their deployment housings. Three additional tubes house the battery pack, calibration gas, and satellite antenna. Details of the equilibrator tube are shown in the upper left. Figure reproduced from Fassbender et al., 2015.

 

The Moored Autonomous DIC (MADIC) sensor was modified from the Pacific Marine Environmental Laboratory MAPCO2 system design (Fig. 8, Sutton et al., 2014). A 10-port valve with fixed-volume tubing loops is used to collect calibrated volumes of seawater (~1 mL) from ~1m depth, and of acid (~200 µL) from an acid reservoir within the equilibrator tube. The acid and seawater mix inside an equilibration chamber as initially CO2-free air is bubbled through the acidic sample in a closed loop until equilibrium is reached. Most of the DIC in the acidic solution is transferred to the gas phase, and at equilibrium, CO2 in the gas phase is measured with an infrared detector. The DIC concentration of the seawater is determined from the CO2 content, pressure and temperature of the gas phase at equilibrium, measurements of sea water salinity and temperature from an external CTD at the time of sample injection, the Ideal Gas Law, and Henry’s Law (Fassbender et al., 2015). Each measurement takes ~12 minutes to complete, including satellite transmission of the data after every two samples. The laboratory determined accuracy was found to be ±5 µmol kg-1.

After rigorous testing in the laboratory and at the Seattle Aquarium, the MADIC sensor was deployed near Honolulu, Hawaii for a fully autonomous field test from November 2013 to May 2014. The sensor was mounted on a moored buoy with a Seabird Electronics CTD and SAMI2 pH sensor affixed to the bridle and was positioned ~400m from shore and ~25m from another buoy carrying a MAPCO2sensor. Fifty two discrete samples were collected throughout the deployment and analyzed for DIC via coulometry at the University of Hawaii SOEST Laboratory. Results indicate that the MADIC sensor measurements were ~90% more accurate than DIC values calculated from in situ measurements of pH and CO2, based on the 52 high-quality discrete DIC samples that were collected (Fig. 2, Fassbender et al., 2015).

The MADIC system is a first step toward autonomous and continuous monitoring of the surface ocean carbon inventory. Near real-time data transmission and remote control of the sensor through two-way satellite communication makes it possible to increase the sample frequency (up to 4 samples per hour) during interesting or intermittent environmental events. In addition, the sample injection volume can be altered so that a wider range of DIC concentrations than those observed in the surface ocean can be measured. The utility of the MADIC analyzer for long-term observing is particularly apparent in nearshore and high-latitude regions where fresh water input can lead to environmental conditions outside of the charge balance assumptions used to define ocean pH and TA (Dickson, 1981, 1984). In these environments, the direct measurement of DIC may be essential for robust constraint of the carbonate system until charge balance definitions are expanded.

The next phase in advancing autonomous marine carbon cycle observing capabilities will be the combination of two carbonate system sensors in one package, such that one platform can house multiple sensors and over constrain the carbonate system. The development of dual carbonate system sensors is well underway (Wang et al., 2015) and sensors for a variety of monitoring platforms and applications have proliferated over the past 5 years (for example: Martz et al., 2010; Easley et al., 2013; Li et al., 2013; Liu et al., 2013; Spaulding et al., 2014). Commercialization of these sensors coupled with continued technology advancement in the coming years will provide a wealth of new research opportunities for the broader carbon research community.

This research has been published in the Journal of Environmental Science & Technology (doi: 10.1021/es5047183) in collaboration with the coauthors listed therein and was presented in 2014 at the IMBER Open Science Conference in Bergen, Norway thanks to generous travel support provided by the conference organizers. The article is PMEL contribution number 4332.

     
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Figure 9. DIC concentrations measured by the DIC sensor (MADIC), calculated from in situ measurements of xCO2 and pH (Calc), and determined via coulometry (Bottle). 

     

References

  • Ciais, P. et al. 2013. Carbon and Other Biogeochemical Cycles, in Climate Change 2013: The Physical Science Basis, edited by V. B. and P. M. M. (eds. . Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
  • Cullison Gray, S. E., M. D. DeGrandpre, T. S. Moore, T. R. Martz, G. Friederich, and K. S. Johnson. 2011.  Applications of in situ pH measurements for inorganic carbon calculations, Mar. Chem., 125, 82–90, doi:10.1016/j.marchem.2011.02.005.
  • Dickson, a. G. 1981. An exact definition of total alkalinity and a procedure for the estimation of alkalinity and total inorganic carbon from titration data, Deep Sea Res. Part A. Oceanogr. Res. Pap., 28(6), 609–623, doi:10.1016/0198-0149(81)90121-7.
  • Dickson, A. G. 1984. pH scales and proton-transfer reactions in saline media such as sea water, Geochim. Cosmochim. Acta, 48(11), 2299–2308, doi:10.1016/0016-7037(84)90225-4.
  • Dickson, A. G., and J. Riley. 1978. The effect of analytical error on the evaluation of the components of the aquatic carbon-dioxide system, Mar. Chem., 6, 77–85, doi:10.1016/0304-4203(78)90008-7.
  • Easley, R. a, M. C. Patsavas, R. H. R. H. Byrne, X. Liu, R. R. A. R. a Feely, and J. T. Mathis. 2013. Spectrophotometric measurement of calcium carbonate saturation states in seawater., Environ. Sci. Technol., 47(3), 1468–77, doi:10.1021/es303631g.
  • Emerson, S. R. 2014. Annual net community production and the biological carbon flux in the ocean, Global Biogeochem. Cycles, 14–28, doi:10.1002/2013GB004680.Received.
  • Fassbender, A. J., C. L. Sabine, N. Lawrence-Slavas, E. H. De Carlo, C. Meinig, and S. Maenner Jones. 2015. Robust Sensor for Extended Autonomous Measurements of Surface Ocean Dissolved Inorganic Carbon, Environ. Sci. Technol., doi:10.1021/es5047183.
  • Johnson, K. S., W. M. Berelson, E. S. Boss, Z. Chase, H. Claustre, S. R. Emerson, N. Gruber, A. Kortzinger, M. J. Perry, and S. C. Riser. 2009. Observing biogeochemical cycles at global scales with profiling floats and gliders: Prospects for a global array, Oceanography, 22, 216–225.
  • Li, Q., F. Wang, Z. A. Wang, D. Yuan, M. Dai, J. Chen, J. Dai, and K. A. Hoering. 2013. Automated spectrophotometric analyzer for rapid single-point titration of seawater total alkalinity., Environ. Sci. Technol., 47(19), 11139–46, doi:10.1021/es402421a.
  • Liu, X., R. H. Byrne, L. Adornato, K. K. Yates, E. Kaltenbacher, X. Ding, and B. Yang. 2013. In situ spectrophotometric measurement of dissolved inorganic carbon in seawater., Environ. Sci. Technol., 47, 11106–11114, doi:10.1021/es4014807.
  • Martz, T. R., J. G. Connery, and K. S. Johnson. 2010. Testing the Honeywell Durafet for seawater pH applications, Limnol. Oceanogr. Methods, 8, 172–184, doi:10.4319/lom.2010.8.172.
  • Millero, F. J. 2007. The marine inorganic carbon cycle., Chem. Rev., 107, 308–341, doi:10.1021/cr0503557.
  • Passow, U., and C. A. Carlson. 2012. The biological pump in a high CO2 world, Mar. Ecol. Prog. Ser., 470(2), 249–271, doi:10.3354/meps09985.
  • Schuster, U., A. Hannides, L. Mintrop, and A. Körtzinger. 2009. Sensors and instruments for oceanic dissolved carbon measurements, Ocean Sci. Discuss., 5(1), 491–524, doi:10.5194/osd-6-491-2009.
  • Spaulding, R. S., M. D. DeGrandpre, J. C. Beck, R. D. Hart, B. Peterson, E. H. De Carlo, P. S. Drupp, and T. R. Hammar. 2014. Autonomous in situ measurements of seawater alkalinity., Environ. Sci. Technol., 48(16), 9573–81, doi:10.1021/es501615x.
  • Sutton, A. J. et al. 2014. A high-frequency atmospheric and seawater pCO2 data set from 14 open ocean sites using a moored autonomous system, Earth Syst. Sci. Data Discuss., 7, 385–418, doi:10.5194/essdd-7-385-2014.
  • Wang, Z. A., F. N. Sonnichsen, A. M. Bradley, K. a. Hoering, T. M. Lanagan, S. N. Chu, T. R. Hammar, and R. Camilli. 2015. An In-situ Sensor Technology for Simultaneous Spectrophotometric Measurements of Seawater Total Dissolved Inorganic Carbon and pH, Environ. Sci. Technol., 150226220706007, doi:10.1021/es504893n.
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World-wide evaluation of the use of ecosystem drivers of stock production in tactical fisheries management – a review

Geir Ottersen1, 2 and Mette Skern-Mauritzen1   

1Institute of Marine Research and Hjort Centre for Marine Ecosystem Dynamics, P.O. Box 1870 Nordnes, NO-5817 Bergen, Norway

2Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, PO Box 1066 Blindern, N-0316 Oslo, Norway

 

An extensive review in Fish and Fisheries by Skern-Mauritzen et al. (2015) that considered assessment reports for 1200 fish stocks worldwide found that ecosystem drivers of stock production are rarely implemented in tactical fisheries management. This is despite the fact that incorporating effects of ecosystem processes on stock production is one of the foundations in international conventions on the Ecosystem Approach to Fisheries (EAF).

Introduction

Fish stock productivity, and hence sensitivity to harvesting, depends on physical (e.g., ocean climate) and biological (e.g., prey availability, competition and predation) processes in the ecosystem. It could therefore be argued that management systems should adapt to changing ecosystems to enhance responsiveness and precision relative to changes in stock production (King and McFarlane 2006, Brown et al. 2012). While traditional fisheries management focuses on harvest rates and stock biomass, incorporating the impacts of such ecosystem processes is one of the main pillars of the ecosystem approach to fisheries management (EAF). The EAF management framework has been formally adopted by many governments and international organizations and agreements since the 1990s. Despite this, little is known of the extent that ecosystem drivers of fish stock productivity are explicitly implemented in fisheries management.

Ecosystem drivers of fish stock production in fisheries management

To examine this we conducted an evaluation of the extent to which ecosystem information has been included in tactical fisheries management practices (Skern-Mauritzen et al. 2015). Based on a worldwide review of more than 1200 marine fish stocks, we found that ecosystem drivers were included in the tactical management of only 24 stocks (not an accurate number, but a ballpark figure). This is rather surprising, both from an ecological point of view and considering that the EAF framework has been formally adopted by many governments and international organizations and agreements since the 1990s. Despite this, Pitcher et al. (2009) found that very few countries are actually moving towards EAF, and Vert-pre et al. (2013) stated that fisheries management is still predominantly based on a ‘single-species equilibrium’ paradigm. This assumes that fluctuations in vital rates (growth, mortality and recruitment) and the resulting stock productivity are centred on a stationary mean at a given harvest rate, and that stock production is predominantly linked to stock abundance per se, which may be controlled through regulating the harvest rate. Thus, if management targets, such as maximum sustainable yield, are based on a high-productivity regime, a shift to a low-productivity regime will result in increased risk of overfishing. Conversely, management targets based on a low-productivity regime will result in overly cautious harvesting during high productivity regimes (Vert-pre et al. 2013).

Although it is fairly comprehensive, Skern-Mauritzen et al. (2015) emphasize that their review should not be considered as a complete coverage of all stocks managed by these management bodies. Nevertheless, except for some geographic bias, the general conclusions are considered to be valid. The 24 cases included both typically data-rich stocks with high scientific support that enabled estimates of population structure, vital rates and total abundance to be incorporated in quantitative stock assessments, and data-poor stocks managed by relative abundance indices, such as catch per unit effort and simpler production models, assuming rather than estimating, the population-dynamic processes involved. Most of the cases identified by Skern-Mauritzen et al. (2015) were in the North Atlantic and North-east Pacific, where scientific support is strong (Fig. 10). However, the diversity of ecosystem drivers implemented, and the approaches taken, suggest that implementation is largely a bottom-up process driven by a few dedicated experts.

 
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Figure 10. Geographic distribution of tactical fisheries management frameworks incorporating ecosystem drivers of stock production, and regional scientific support according to Skern-Mauritzen et al. (2015). The extent of the scientific support was assessed using the number of publications in the ISI Web of Knowledge containing the terms ‘fish’ (blue bars, numbers in 1000s) and ‘ecosystem approach or ecosystem based and fish’ (green bars, numbers in 100s) for different geographic regions. Red bars indicate the number of stocks with ecosystem drivers implemented in stock assessment and management advice identified in the review.

The results demonstrate that tactical fisheries management is still predominantly single-species oriented. It may be argued that traditional single species management implicitly covers variability in the biotic and abiotic environment as this is reflected in, e.g., growth rates.  However, by not explicitly taking account of fish stock production generally being dependent on the physical and biological conditions of the ecosystem, the underlying ecosystem processes remain, by and large, a black box. Thus, while the ecosystem approach is highlighted in policy, key aspects of it tend not yet to be implemented in actual fisheries management.

The use of management strategy evaluations

While direct implementation of ecosystem drivers is rare, general descriptions of ecosystem impact on stock productivity were more frequent, and used as ‘contextual’ assessments. The importance of explicit implementation of ecosystem drivers in the management framework was highlighted in many assessment reports.  However, the identified cases clearly demonstrated that such approaches are challenged by non-stationary relationships between drivers and stock production, level of process understanding and precision. Skern-Mauritzen et al. (2015) therefore, advise that when a stock is known or expected to respond to changes in the ecosystem, alternative management strategies should be tested in formal Management Strategy Evaluations (MSE, Butterworth and Punt 1999) before implementation. In MSE, simulations of each step in the management cycle are run, including the responses of fish stocks to ecosystem change scenarios, to test the robustness and precision of alternative management frameworks. A roadmap for such an MSE process is outlined in Figure 11.

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Figure 11. Geographic distribution of tactical fisheries management frameworks incorporating ecosystem drivers of stock production, and regional scientific support according to Skern-Mauritzen et al. (2015). The extent of the scientific support was assessed using the number of publications in the ISI Web of Knowledge containing the terms ‘fish’ (blue bars, numbers in 1000s) and ‘ecosystem approach or ecosystem based and fish’ (green bars, numbers in 100s) for different geographic regions. Red bars indicate the number of stocks with ecosystem drivers implemented in stock assessment and management advice identified in the review.

     

References

  • Skern-Mauritzen, M., Ottersen, G., Handegard, N., Huse, G., Dingsør, G., Stenseth, N.C., & Kjesbu, O. (2015). Ecosystem processes are rarely included in tactical fisheries management. Fish and Fisheries DOI: 10.1111/faf.12111. Open access - download at: http://onlinelibrary.wiley.com/doi/10.1111/faf.12111/abstract
  • Brown, C., Fulton, E., Possingham, H., & Richardson, A. (2012). How long can fisheries management delay action in response to ecosystem and climate change? Ecological Applications, 22 (1), 298-310 DOI: 10.1890/11-0419.1
  • Butterworth, D. & Punt, A.E. (1999). Experiences in the evaluation and implementation of management procedures. ICES Journal of Marine Science, 56 (6), 985-998 DOI: 10.1006/jmsc.1999.0532
  • King, J., & McFarlane, G. (2006). A framework for incorporating climate regime shifts into the management of marine resources. Fisheries Management and Ecology, 13 (2), 93-102 DOI: 10.1111/j.1365-2400.2006.00480.x
  • Pitcher, T., Kalikoski, D., Short, K., Varkey, D., & Pramod, G. (2009). An evaluation of progress in implementing ecosystem-based management of fisheries in 33 countries. Marine Policy, 33 (2), 223-232 DOI: 10.1016/j.marpol.2008.06.002
  • Vert-pre, K., Amoroso, R., Jensen, O., & Hilborn, R. (2013). Frequency and intensity of productivity regime shifts in marine fish stocks Proceedings of the National Academy of Sciences, 110 (5), 1779-1784 DOI: 10.1073/pnas.1214879110
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Where are they now?

 

The 2012 Integrated Marine Biogeochemistry and Ecosystem Research (IMBER) ClimEco3 Summer School in Ankara, Turkey, was an extremely important and well-timed opportunity at the beginning of my career in marine science. I had spent the two years prior to ClimEco3 working on topics pertaining to western Antarctic Peninsula zooplankton ecology and physiology, and found myself asking: 1) how my research might inform the larger ecological picture in a region being affected by climate change, and 2) what do I do once I complete my Ph.D. The summer school aimed to teach early career scientists and students different methods of ecological modelling, and it enabled me integrate different science disciplines and ideas into new and exciting research. It was quickly evident that a career in ecological modelling was the answer to both of my questions, and I thank the Ocean Carbon & Biogeochemistry program and IMBER for the financial support that enabled me to attend ClimEco3 and launch my career.

On my return to the University of South Florida’s College of Marine Science after ClimEco3, I introduced myself to Dr. Cameron Ainsworth and asked him to consider doing an ecological modelling project with me, and that project would form the final chapter of my Ph.D. dissertation. Knowing nothing about me other than my excitement to apply my newly found skills in ecological modelling, he agreed to work with me, and within a few months my dissertation’s final chapter was complete. It centered on an ecological model that was used to explore consequences of Southern Ocean warming, ocean acidification, and changing trophodynamics. I completed my Ph.D. in the spring of 2013 and took a postdoctoral position with Dr. Ainsworth to assess 14 fishery independent monitoring (FIM) programs in the Gulf of Mexico.  In this position we used a temporal and spatial ecological model to determine which habitats, gear-types and months provided the most informative and accurate fishery management indices for 35 managed species or groups of species. Once again I was able to use the ecological modelling skills introduced at ClimEco3, and published a paper on our findings. This resulted in a second ecological modelling postdoctoral position, this time at the University of Florida.

 
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Paul Suprenand

Postdoc Research Fellow,
Mote Marine Laboratory,
Sarasota, FL, USA

At the University of Florida I focused on integrating indices of clam physiology, environmental data, and predictive mathematical modelling to develop a decision-support tool to warn Florida clam farmers of impending stressful seawater conditions. At the beginning of the clam modelling project, I was also given three excellent opportunities to further develop my marine science skills and knowledge. The first opportunity was to attend the 2014 IMBER ClimEco4 Summer School in Shanghai, China to learn how to develop ecological indices in ecological modelling projects - the perfect topic for my clam project! The second was to lead a National Science Foundation-funded oceanographic expedition as Chief Scientist on a University-National Oceanographic Laboratory’s Chief Scientist training cruise, and the third was being selected as one of the first International Arctic Science Committee (IASC) Fellows. The latter enabled me to begin planning using ecological modelling to address environmental change issues in Alaska’s North Slope Arctic marine ecosystem, and to attend meetings in Finland and Sweden as an IASC working group participant, where I learned of potential international Arctic science collaborations.  

At the end of the clam project, I was offered a postdoctoral research fellowship with Mote Marine Laboratory, and with their support, I have begun work on the Alaskan North Slope ecological modelling project. In this two-year project, we are currently developing an ecological model of the Beaufort Sea Arctic marine ecosystem that considers predator-prey relationships, seasonal/environmental changes, as well as the North Slope indigenous community (Inupiat) artisanal hunting and fishing efforts.  We aim to build the ecological model through communications with, and learning from, the Inupiat communities and leaders, in order to set cooperative research goals and develop a practical, well-informed ecological model. The model will be used to simulate inshore and offshore oil spills, based on existing and potential oil extraction locations, to identify those marine species and habitats most at risk to oil exposure, as well as indigenous communities who might be most affected by oil spill consequences to the coastal marine ecosystem. In this project I continue to work with Dr. Cameron Ainsworth at the University of South Florida, and have begun working with Drs. Dana Wetzel and John Reynolds at Mote Marine Laboratory, as well as Dr. Carie Hoover from the Division of Fisheries in Canada. Dr. Hoover and I met at the ClimEco4 Summer School, thus adding even more benefit to having attended ClimEco4!

As my ecological modelling career progresses I plan to work more closely with the United States members of the IASC working groups, as well as Dr. Peter Sköld at Arcum (Arctic Research Centre at Umea University, Sweden) to help lead cross-cutting science initiatives in Arctic science in the years to come. In these future plans I want to remain involved in IMBER, and IMBER-related conferences and workshops…It is my hope to participate in ClimEco5 next year in Brazil!

     
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The comings and goings of IMBER

Meet IMBER's new Executive Officer

     
Einar Svendsen
 

Einar Svendsen is a physical oceanographer who has spent more than 33 years doing  physical oceanography, remote sensing and marine ecology research in Arctic and sub-Arctic regions. The first eight years (1979-1987) after graduation were spent working with what was then a small group that formed the Nansen Centre for Environment and Remote Sensing (NERSC). They had close links with the NASA Goddard Space Flight Centre that deals with satellite remote sensing. Einar’s most important contribution from this time is the NORSEX-algorithm that is used to estimate sea ice concentration and ice types from passive microwave measurements. It was developed from detailed field studies of ice and snow structure and their related radiation properties and is still in use today. Applying the NORSEX algorithm (and others) to satellite data made it possible to continuously measure the changing sea ice distribution. This has been an important contribution to the climate change issue (http://arctic-roos.org/observations/satellite-data/sea-ice/total-icearea-from-1978-2007 ).

In 1987 he changed direction somewhat and took up position as a principle scientist at the Institute of Marine Research (IMR). IMR is a large marine research institute with a strong focus on fish. Salmon aquaculture along the Norwegian coast is also of importance, as is providing governmental fisheries management advice. 

Because varying physics/climate is one of the main drivers of the ecosystem dynamics 4-dimentional (space and time) numerical ecosystem models are needed. The first numerical modellers were also appointed at IMR in 1987, and Einar took the lead in building a numerical modelling team that now consists of about 10 highly skilled modellers who developed the NORWegian ECOlogical Model system (NORWECOM). In cooperation with the University of Bergen, NERSC and the Norwegian Meteorological Institute (MET.no), NORWECOM was the first (in 1994) operational model system operated with realistic forcings on a large ecosystem (the North Sea), that provided routine (5-day) forecasts of the physics, nutrients, phytoplankton and oxygen. It is also used for fish recruitment predictions based on multi-decadal hindcast simulations. Later, NORWECOM was expanded to include individual based modules for zooplankton, fish larvae and, so far, three adult planktivorous fish species that occur in the Norwegian and Barents seas. Plans are also underway to implement a fishers module that will include human behaviour.

Through IMR, Einar became involved with the century-old International Council for the Exploration of the Seas (ICES. http://ices.dk/Pages/default.aspx). He was leader of the Shelf Seas Working Group and later, the Oceanography Committee, and initiated the ICES Working Group on Operational Oceanography for Fisheries and Ecosystems (WGOOFE,http://groupsites.ices.dk/sites/wgoofe/operationalOcenography/Pages/Temperature.aspx). He was also the leader of the Oceanography Research Group at IMR, and was involved in the large European operational oceanography initiative. He recently completed a 6-year term as Research Director at IMR, during which he represented Norway on the ICES Science Committee (SCICOM). Einar has published about 50 scientific peer-review articles and took part in 17 large expeditions (several as chief scientist) to the Arctic, Antarctic and the Northern Seas. In February 2015, IMBER was delighted that he agreed to lead the IMBER International Project Office at IMR and to increase IMBER’s prominence both in Bergen and the rest of Norway.

A New DEO at the RPO

     
Yi Xu
  Yi Xu was appointed as the Deputy Executive Officer of the IMBER Regional Project Office (RPO) in Shanghai, China in December 2014. She came to IMBER directly from the State University of North Carolina, USA where she had been a Postdoc Research Associate, working on coastal circulation and marine ecosystem dynamics in the northwest Atlantic Ocean. She obtained a PhD in Oceanography from Rutgers, the state University of New Jersey, USA and focused on satellite data analysis, numerical simulation, and bio-physical interactions. After completing her PhD at the end of 2012, she stayed on in the lab for an additional year, working for the Middle Atlantic Regional Coastal Ocean Observing System (MARCOOS) project as a Postdoc Researcher. She has published several articles based on her PhD and postdoc work. In addition to her research interests, she was the Vice President of the Oceanography Graduate Students Association at Institute of Marine and Coastal Sciences, Rutgers. She also has experience of teaching undergraduate students and was a student volunteer at several international science meetings, such as American Geophysical Union (AGU) Ocean Science Conferences.
Yi was productive during her PhD, not only with her research, but also raising two lovely children. She and her family moved back to Shanghai at the end of last year for her to take up this position, and they are enjoying their new life in China with the extended family and friends there.

New Scientific Steering Committee (SSC) Members

IMBER is pleased to introduce the three new members who joined the IMBER Scientific Steering Committee this year.

     
RUBEN ESCRIBANO
  Ruben is an expert in zooplankton population and community ecology. His PhD thesis focused on ecophysiology and molecular biology of pelagic copepods from the north Atlantic. This interest continued during his time as Associate Professor at the Oceanological Institute of University of Antofagasta in Chile where he spent 10 years working on the dynamics of copepods in the coastal upwelling system off northern Chile. From there he moved to the Center of Oceanographic Research in the eastern South Pacific (COPAS), and then to the University of Concepción, where he is currently Director of the PhD Program of Oceanography, and Deputy Director of the new Millennium Institute of Oceanography, funded by the Chilean Government. International collaboration and networking are key for regional visibility and involvement, and Ruben has been part of several joint research initiatives and programmes. He was actively involved in the Census of Marine (CoML), and served as President of the South American Committee of CoML in 2003, during which time he launched a Regional Node of OBIS (Ocean Biogeographic Information System) for the eastern South Pacific. He was a member of the Global Ocean Ecosystem Dynamics (GLOBEC) Steering Committee. Regionally, he maintains strong and continuous collaboration for research and higher education with partners in other South American countries.
Ruben has published extensively in international journals and books, and was Guest Editor for two volumes of Progress in Oceanography that focused on the COPAS Oceanographic Time Series study off Concepción that he coordinated. His research interests now extend beyond zooplankton ecology and he conducts integrated research with multidisciplinary teams of researchers involved working on the dynamics of the Chilean coastal upwelling system. In the framework of the research plan of the Millennium Institute of Oceanography (IMO), he is involved in uncovering and understanding the structure and ecology of deep sea pelagic communities in the unexplored South Pacific Ocean, providing expertise in taxonomy, and population/community biology of zooplankton.
 
Masao Ishii
 

Masao Ishii is a senior researcher at Meteorological Research Institute, Japan Meteorological Agency (JMA), in Tsukuba, Japan, and leads an ocean biogeochemistry research group in the Department of Oceanography and Geochemistry. He also serves as a Science Steering Group member of the International Ocean Carbon Coordination Project (IOCCP), is an Executive Group member of the Global Ocean Ship-Based Hydrographic Investigations Program (GO-SHIP), and a member of the Carbon and Climate section of the North Pacific Marine Science Organization (PICES).

Masao has a PhD in chemistry. His interest in ocean science and environmental issues pushed him to become a sea-going chemist and an expert in measuring CO2 system variables in the ocean. His research group is working to quantify the ocean’s role as a sink of CO2, document trends of ocean acidification and deoxygenation, and understand the physical and biogeochemical processes underlying these trends. The results of their research are leading to the firm recognition that excess CO2 produced by fossil fuel burning and other industrial activities is causing pronounced perturbations to the CO2 chemistry in the surface and interior of the oceans including the vast western North Pacific tropical and subtropical zones where many coral reef habitats with rich biodiversity are distributed.

     
Svein-SUNDBY
  Svein Sundby is a research scientist in Physical Oceanography and Marine Ecology at Institute of Marine Research in Bergen, Norway. His main research interests include physical-biological ocean processes, ocean climate and fisheries oceanography. Like Ruben, he also served on the GLOBEC SSC and so is no stranger to international marine projects. When asked what  his favourite sea creatures were, Svein responded – cod, cod and cod, both to research and to eat!

Farewell to Bernard Avril at the IMBER Project Office

     
Bernard Avril
  Bernard was appointed as the Executive Officer of the IMBER International Project Office when it relocated from France to Norway in 2011. We are very grateful for all his efforts during this time and wish him well in his future endeavours. 
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Publications

  • Ayers J.M., Strutton P.G. , Coles V.J., Hood R.R. & Matear R.J. 2014. Indonesian throughflow nutrient fluxes and their potential impact on Indian Ocean productivity. Geophys. Res. Lett. 41(14): 5060-5067. DOI: 10.1002/2014GL060593. Article
  • Basso L., Hendriks I. E. & Duarte C. M., in press. Juvenile pen shells (Pinna nobilis) tolerate acidification but are vulnerable to warming. Estuaries and Coasts. doi:10.1007/s12237-015-9948-0 Article
  • Bednaršek N., Tarling G. A., Bakker D. C. E., Fielding S. & Feely R. A. 2014. Dissolution dominating calcification process in polar pteropods close to the point of aragonite undersaturation. PLoS ONE 9(10): e109183. doi: 10.1371/journal.pone.0109183. Article
  • Bednaršek N. & Ohman M.D. 2015. Changes in pteropod distributions and shell dissolution across a frontal system in the California Current System. Marine Ecology Progress Series 523: 93-103. Article 
  • Blenckner T., Kannen A., Barausse A., Fischer C., Heymans J., Luisetti T., Todorova V., Valman M. & Mee L. 2015. Past and future challenges in managing European seas. Ecology and Society 20(1): 40 Article
  • Blenckner T., Llope M., Mollmann C., Voss R., Quaas M., Casini M., Lindegren M., Folke C. & Stenseth Chr. 2015. Climate and fishing steer ecosystem regeneration to uncertain economic futures. Proceedings of the Royal Society B: 282. doi:10.1098/rspb.2014.2809 Article
  • Borja A., Prins T. C., Simboura N., Andersen J. H., Berg T., Marques J.-C., Neto J. M., Papadopoulou N., Reker J., Teixeira H. & Uusitalo L. 2014. Tales from a thousand and one ways to integrate marine ecosystem components when assessing the environmental status. Front. Mar. Sci. 1:72. doi: 10.3389/fmars.2014.00072. Article  
  • Boyd P. & Brown C. 2015. Modes of interactions between environmental drivers and marine biota. Front. Mar. Sci. 2: 9. doi:10.3389/fmars.2015.00009 Article
  • Caihong F., Large S., Knight B., Richardson A.J., Bundy A., Reygondeau G., Boldt J., van der Meeren G.I., Torres M.A., Sobrino I., Auber A., Travers-Trolet M., Piroddi C., Diallo I., Jouffre D., Mendes H., Borges M.F., Lynam C.P., Coll M., Shannon L. J. & Shin Y-J. 2015. Relationships among fisheries exploitation, environmental conditions, and ecological indicators across a series of marine ecosystems. Journal of Marine Systems 148: 101-111. DOI:10.1016/j.jmarsys.2015.01.004. Article
  • Carman V., Machain N. & Campagna C. In press. Legal and institutional tools to mitigate plastic pollution affecting marine species: Argentina as a case study. Marine Pollution Bulletin. doi: 10.1016/j.marpolbul.2014.12.047 Article
  • Chust G., Allen I., Bopp L., Schrum C., Holt J., Tsiaras K., Zavatarelli M., Chifflet M., Cannaby H., Dadou I., Daewel U., Wakelin S.L., Machu E., Pushpadas D., Butenschon M., Artioli Y., Petihakis G., Smith C., Garçon V., Goubanova K., Le Vu B., Fach B.A., Salihoglu B., Clementi E. & Irigoien X. 2014. Biomass changes and trophic amplification of plankton in a warmer ocean. Global Change Biology 20: 2124-2139. doi:10.1111/gcb.12562 Article
  • Clark D. R., Flynn K. J. & Fabian H. 2014. Variation in elemental stoichiometry of the marine diatom Thalassiosira weissflogii (Bacillariophyceae) in response to combined nutrient stress and changes in carbonate chemistry. Journal of Phycology 50(4): 640–651. doi:10.1111/jpy.12208 Article
  • Cooper C. A., Regan M. D., Brauner C. J., De Bastos E. S. R. & Wilson R. W., 2014. Osmoregulatory bicarbonate secretion exploits H+-sensitive haemoglobins to autoregulate intestinal O2 delivery in euryhaline teleosts. Journal of Comparative Physiology B 184(7):865-876. DOI: 10.1007/s00360-014-0844-x Article 
  • Dore J. E., Church M. J., Karl D. M., Sadler D. W. & Letelier R. M. 2014. Paired windward and leeward biogeochemical time series reveal consistent surface ocean CO2trends across the Hawaiian Ridge. Geophysical Research Letters 41(18): 6459–6467. doi:10.1002/2014GL060725 Article
  • Duarte C.M., Fulweiler R.W., Lovelock C.E., Martinetto P., Saunders M.I., Pandolfi J.M., Gelcich S. & Nixon S.W. 2014. Reconsidering Ocean Calamities. BioScience XX: 1-10. doi:10.1093/biosci/biu198 Article
  • Flynn K.J., Clark D.R., Mitra A., Fabian H., Hansen P.J., Glibert P.M., Wheeler G.L., Stoecker D.K., Blackford J.C. & Brownlee C. 2015. Ocean acidification with (de)eutrophication will alter future phytoplankton growth and succession. Proc. R. Soc. B: 2015 282 20142604. doi:10.1098/rspb.2014.2604 Article 
  • Frisch L. C. , Mathis J. T. , Kettle N. P. & Trainor S. F., 2015. Gauging perceptions of ocean acidification in Alaska. Marine Policy 53:101-110. DOI: 10.1016/j.marpol.2014.11.022. Article
  • Forrest R. E., Savina M., Fulton E. A. & Pitcher T. J. 2015. Do marine ecosystem models give consistent policy evaluations? A comparison of Atlantis and Ecosim.Fisheries Research 167: 293 - 312 Article
  • Fulton E., Boschetti F., Sporcic M., Jones T., Little R., Dambacher J., Gray R., Scott R. & Gorton R. 2015. A multi-model approach to engaging stakeholder and modellers in complex environmental problems. Environmental Science & Policy 48: 44-56. doi:10.1016/j.envsci.2014.12.006 Article 
  • Gattuso J.-P., Brewer P., Hoegh-Guldberg O., Kleypas J. A., Pörtner H.-O. & Schmidt D., 2014. Ocean acidification. In: Field C. B., Barros V. R., Dokken D. J., Mach K. J., Mastrandrea M. D., Bilir T. E., Chatterjee M., Ebi K. L., Estrada Y. O., Genova R. C., Girma B., Kissel E. S., Levy A. N., MacCracken S., Mastrandrea P. R. & White L. L. (Eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, pp. 129-131. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press. Report chapter.
  • Garilli V., Rodolfo-Metalpa R., Scuderi D., Brusca L., Parrinello D., Rastrick S. P. S., Foggo A., Twitchett R. J., Hall-Spencer J. M. & Milazzo M., in press. Physiological advantages of dwarfing in surviving extinctions in high-CO2 oceans. Nature Climate ChangeArticle
  • Guenette S., Araújo J.N. & Bundy A. 2014. Exploring the potential effects of climate change on the Western Scotian Shelf ecosystem, Canada. Journal of Marine Systems 134: 89-100. DOI: 10.1016/j.jmarsys.2014.03.001 Article
  • Gaylord B., Kristy J. Kroeker K. J., Sunday J. M., Anderson K. M., Barry J. P., Brown N. E., Connell S. D., Dupont S., Fabricius K. E., Hall-Spencer J. M., Klinger T., Milazzo M., Munday P. L., Russell B. D., Sanford E., Schreiber S. J., Thiyagarajan V., Vaughan M. L. H. , Widdicombe S. & Harley C. D. G.  In press. Ocean acidification through the lens of ecological theory. Ecology. doi: 10.1890/14-0802.1. Article 
  • Gattuso J.-P., Epitalon J.-M. & Lavigne H., 2015. seacarb: Seawater Carbonate Chemistry. R package version 3.0.6. Package 
  • Guallart E.F., Fajar N.M., Padín X.A., Vázquez-Rodríguez M., Calvo E., Ríos A.F., Hernández-Guerra A., Pelejero C. & Pérez F.F. In press. Ocean acidification along the 24.5°N section in the subtropical North Atlantic. Geophysical Research Letters. doi:10.1002/2014GL062971 Article
  • Hoegh-Guldberg O., Cai R., Brewer P., Fabry V., Hilmi K., Jung S., Poloczanska E. & Sundby S., 2014. The ocean. In: Field C. B., Barros V. R., Dokken D. J., Mach K. J., Mastrandrea M. D., Bilir T. E., Chatterjee M., Ebi K. L., Estrada Y. O., Genova R. C., Girma B., Kissel E. S., Levy A. N., MacCracken S., Mastrandrea P. R. & White L. L. (Eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, pp. 1655-1731. Cambridge, United Kingdom and New York, NY, USA, Cambridge: Cambridge University Press. Report chapter 
  • Heenan A., Pomeroy R., Bell J., Munday P. L., Cheung W., Logan C., Brainard R., Amri A. Y., Aliño P., Armada N., David L., Rivera-Guieb R., Green S., Jompam J., Leonardo T., Mamauag S., Parkero B., Shackeroff J. & Yasin Z., 2015. A climate-informed, ecosystem approach to fisheries management. Marine Policy 57: 182-192. DOI: 10.1016/j.marpol.2015.03.018. Article
  • Hagens M., Slomp C. P., MeysmanF. J. R., Seitaj D., Harlay J., Borges A. V. & Middelburg J. J. 2014. Biogeochemical processes and buffering capacity concurrently affect acidification in a seasonally hypoxic coastal marine basin. Biogeosciences Discussions 11:15827-15887. Article 
  • Holtz L.-M., Wolf-Gladrow D. & Thoms S., in press. Simulating the effects of light intensity and carbonate system composition on particulate organic and inorganic carbon production in Emiliania huxleyiJournal of Theoretical Biology. doi:10.1016/j.jtbi.2015.02.024 Article 
  • Hollowed A.B. & Sundby S. 2014. Change is coming to the northern oceans. Science 344: 1084-1085. doi:10.1126/science.1251166 Article
  • Holt J., Allen I, Anderson T., Brewin R., Butenschön M., Harle J., Huse G., Lehodey P., Lindemann C., Memery L., Salihoglu B., Senina I. & Yool A. 2014. Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to fish and coasts to ocean. Progress in Oceanography 129: 285 - 313. doi:10.1016/j.pocean.2014.04.024 Article 
  • Holt J., Schrum C., Cannaby H., Daewel U., Allen I., Artioli Y., Bopp L., Butenschon M., Fach B.A., Harle J., Pushpadas D., Salihoglu B. & Wakelin S. 2014. Physical processes mediating climate change impacts on regional sea ecosystems. Biogeosciences Discussions 11: 1909-1975. doi:10.5194/bgd-11-1909-2014 Article 
  • Howes E. L., Joos F., Eakin M. & Gattuso J.-P. 2015. The Oceans 2015 Initiative, Part I: An updated synthesis of the observed and projected impacts of climate change on physical and biological processes in the oceans. Studies N°02/2015, IDDRI, Paris, France, 52 p. Article
  • Hood R.R., McPhaden M.J. & Urban E. 2014 New Indian Ocean program builds on a scientific legacy. Eos. Vol. 95, No. 39:349-350 Article 
  • Hagens M., Slomp C. P., Meysman F. J. R., Seitaj D., Harlay J., Borges A. V. & Middelburg J. J. 2015. Biogeochemical processes and buffering capacity concurrently affect acidification in a seasonally hypoxic coastal marine basin. Biogeosciences 12: 1561-1583. doi:10.5194/bg-12-1561-2015 Article
  • Hunt G.L. Jr., Blanchard A. L., Boveng P., Dalpadado P., Drinkwater K.F., Eisner L., Hopcroft R. R., Kovacs K. M., Borcross B. L., Renaud P., Reigstad M., Renner M., Skjoldal H.R., Whitehouse A. & Woodgate R.A. 2013. The Barents and Chukchi Seas: Comparison of two Arctic shelf ecosystems. Journal of Marine Systems 109-110: 43-68. Doi: doi:10.1016/j.jmarsys.2012.08.003. Article
  • Jones M. C. & Cheung W.W.L. 2015. Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES Journal of Marine Science 72(3) 741 - 752. doi:10.1093/icesjms/fsu172 Article
  • Kaczmarek K., Langer G., Nehrke G., Horn I., Misra S., Janse M. & Bijma J. 2014. Boron incorporation in the foraminifer Amphistegina lessonii under a decoupled carbonate chemistry. Biogeosciences Discussions 11:16743-16771. Article 
  • Krause-Jensen D., Duarte C. M., Hendriks I. E., Meire L., Blicher M. E., Marbà N. & Sejr M. K. 2015. Macroalgae contribute to nested mosaics of pH variability in a sub-Arctic fjord. Biogeosciences Discussions 12: 4907-4945 Article
  • Keul N., Langer G., de Nooijer L., Nehrke G., Reichart G.-J., Bijma J. & Schneider R. 2015. New carbonate system proxies: foram culturing and pteropod potentials. Nova Acta Leopoldina NF 121, 408:305 -309. Article
  • Lauvset S. K., Gruber N., Landschützer P., Olsen A. & Tjiputra, J. 2014. Trends and drivers in global surface ocean pH over the past three decades. Biogeosciences Discuss. 11: 15549-15584. doi:10.5194/bgd-11-15549-2014. Article
  • Lauvset S. K., Gruber N., Landschützer P., Olsen A. & Tjiputra J. 2015. Trends and drivers in global surface ocean pH over the past 3 decades. Biogeosciences 12: 1285-1298. doi:10.5194/bg-12-1285-2015 Article
  • Large S.I., Fay G., Friedland K.D. & Link J.S. 2015. Quantifying Patterns of Change in Marine Ecosystem Response to Multiple Pressures. PLoS ONE 10(3): e0119922. doi:10.1371/journal.pone.0119922 Article
  • Llopiz J.K. & Hobday A.J. 2015. A global comparative analysis of the feeding dynamics and environmental conditions of larval tunas, mackerels, and billfishes. Deep Sea Research Part II: Topical Studies in Oceanography 113: 113-124 Article
  • Llopiz J.K., Cowen R.K., Hauff M.J., Ji R., Munday P.L., Muhling B.A., Peck M.A., Richardson D.E., Sogard S. & Sponaugle S. 2014. Early life history and fisheries oceanography: New questions in a changing world.  Oceanography 27(4): 26-41 Article
  • Levin P.S. & Möllmann C. 2015. Marine ecosystem regime shifts: challenges and opportunities for ecosystem-based management. Philosophical Transactions of the Royal Society B: Biological Sciences 370. DOI: 10.1098/rstb.2013.0275. Article
  • Manríquez P.H., Jara M.E., Torres R., Loreto Mardones M., Lagos N.A., Lardies M A., Vargas C.A., Duarte C. & Navarro J.M. 2014. Effects of ocean acidification on larval development and early post-hatching traits in Concholepas concholepas (loco). Marine Ecology Progress Series 514: 87-103. Article 
  • Maugendre L., Gattuso J.-P., Poulton A. J., Dellisanti W., Gaubert M., Guieu C. & Gazeau F. in press. No detectable effect of ocean acidification on plankton metabolism in the NW oligotrophic Mediterranean Sea: results from two mesocosm studies. Estuarine, Coastal and Shelf ScienceArticle
  • Meyer J. & Riebesell U. 2015. Reviews and syntheses: Responses of coccolithophores to ocean acidification: a meta-analysis. Biogeosciences 12: 1671-1682 Article
  • Meier K. J. S., Beaufort L., Heussner S. & Ziveri P. 2014. The role of ocean acidification in Emiliania huxleyi coccolith thinning in the Mediterranean Sea. Biogeosciences11: 2857-2869. doi:10.5194/bg-11-2857-2014. Article
  • Meyer J. & Riebesell U. 2014. Responses of coccolithophores to ocean acidification: a meta-analysis. Biogeosciences Discussions 11: 14857-14887. doi:10.5194/bgd-11-14857-2014 Article 
  • Mitra A., Flynn K.J., Burkholder J.M., Berge T., Calbet A., Raven J.A., Granéli E., Glibert P.M., Hansen P.J., Stoecker D.K., Thingstad F.,Tillmann U., Våge S., Wilken S. & Zubkov M.V. 2014. The role of mixotrophic protists in the biological carbon pump. Biogeosciences 11: 995-1005. doi:10.5194/bg-11-995-2014 Article 
  • Moya A., Huisman L., Forêt S., Gattuso J.-P., Hayward D. C., Ball E. E. & Miller D. J. in press. Rapid acclimation of juvenile corals to CO2-mediated acidification by up-regulation of HSP and Bcl-2 genes. Molecular Ecology. doi: 10.1111/mec.13021. Article 
  • Möllmann C., Folke C., Edwards M. & Conversi A. 2015. Marine regime shifts around the globe: theory, drivers and impacts. Philosophical Transactions of the Royal Society B: Biological Sciences 370. DOI:10.1098/rstb.2013.0260. Article 
  • O'Connor M. I., Holding J. M., Kappel C. V., Duarte C. M., Brander K., Brown C. J., Bruno J. F., Buckley L., Burrows M. T., Halpern B. S., Kiessling W., Moore P., Pandolfi J. M., Parmesan C., Poloczanska E. S., Schoeman D. S., Sydeman W. J. & Richardson A. J., 2015. Strengthening confidence in climate change impact science. Global Ecology and Biogeography 24(1):64-76. DOI: 10.1111/geb.12218 Article
  • Orr J. C. & Epitalon J.-M. 2015. Improved routines to model the ocean carbonate system: mocsy 2.0. Geoscientific Model Development 8: 485-499. doi:10.5194/gmd-8-485-2015 Article
  • Oyanedel R., Marín A., Castilla J. Carlos & Gelcich S. 2015. Establishing marine protected areas through bottom-up processes: insights from two contrasting initiatives in Chile. Aquatic Conservation: Marine and Freshwater Ecosystems. doi:10.1002/aqc.2546 Article
  • Qiu Y. 2015. Iron fertilisation by Asian dust influences North Pacific sardine regime shifts. Progress in Oceanography 134: 370-378. Article
  • Patrick W.S. & Link J.S. 2015. Myths that continue to impede progress in ecosystem-based fisheries management. Fisheries 40: 155-160. DOI: 10.1080/03632415.2015.1024308. Article
  • Planque B., Lindstrøm U. & Subbey S. 2014. Non-Deterministic Modelling of Food-Web Dynamics. PLoS ONE 9(10): e108243. doi:10.1371/journal.pone.0108243.Article
  • Planque B., Primicerio R., Michalsen K., Aschan M., Certain G., Dalpadado P., Gjøsæter H., Hansen C., Johannesen E., Jørgensen L.L., Kolsum I., Kortsch S., Leclerc L.-M., Omli L., Skern-Mauritzen M. & Wiedmann M. 2014. Who eats whom in the Barents Sea: a food web topology from plankton to whales. Ecology 95: 1430-1430. doi:10.1890/13-1062.1 Article 
  • Pörtner H.-O., Karl D., Boyd P., Cheung W., Lluch-Cota S. E., Nojiri Y., Schmidt D. & Zavialov P., 2014. Ocean systems. In: Field C. B., Barros V. R., Dokken D. J., Mach K. J., Mastrandrea M. D., Bilir T. E., Chatterjee M., Ebi K. L., Estrada Y. O., Genova R. C., Girma B., Kissel E. S., Levy A. N., MacCracken S., Mastrandrea P. R. & White L. L. (Eds.), Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, pp. 411-484. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press. Report chapter 
  • Rose K.A., Sable S., DeAngelis D.L., Yurek S., Trexler J.C., Graf W. & Reed D.J. 2014. Proposed best modeling practices for assessing the effects of ecosystem restoration on fish. Ecological Modelling 300: 12-29. doi:10.1016/j.ecolmodel.2014.12.020 Article
  • Rocha J., Yletyinen J., Biggs R., Blenckner T. & Peterson G. 2015 Marine regime shifts: drivers and impacts on ecosystems services. Philosophical Transactions of the Royal Society B: 2015 370 20130273. doi:10.1098/rstb.2013.0273 Article
  • Réveillac E., Lacoue-Labarthe T., Oberhänsli F., Teyssié J.-L., Jeffree R., Gattuso J.-P. & Martin S. 2015. Ocean acidification reshapes the otolith-body allometry of growth in juvenile sea bream. Journal of Experimental Marine Biology and Ecology 463:87-94. Article 
  • Reum J. C. P., AlinS. R., Harvey C. J., Bednaršek N., Evans W., Feely R. A., Hales B., Lucey N., Mathis J. T., McElhany P., Newton L. & Sabine C. L., in press. Interpretation and design of ocean acidification experiments in upwelling systems in the context of carbonate chemistry co-variation with temperature and oxygen. ICES Journal of Marine ScienceArticle
  • Subbey S, Devine J.A., Schaarschmidt U. & Nash R.D.M. 2014. Modelling and forecasting stock-recruitment: current and future perspectives. ICES Journal of Marine Science 71(8): 2307-2322. doi: 10.1093/icesjms/fsu148. Article
  • Saraswat R., Kouthanker M., Kurtarkar S. R., Nigam R., Naqvi S. W. A. & Linshy V. N. 2015. Effect of salinity induced pH/alkalinity changes on benthic foraminifera: A laboratory culture experiment. Estuarine, Coastal and Shelf Science 153: 96-107. doi:10.1016/j.ecss.2014.12.005 Article
  • Skern-Mauritzen M., Ottersen G., Handegard N. O., Huse G., Dingsør G. E., Stenseth N. C. & Kjesbu O. S. 2015. Ecosystem processes are rarely included in tactical fisheries management. Fish and Fisheries. doi: 10.1111/faf.12111 Article
  • Sasse T.P., McNeil B.I., Matear R.J. & Lenton A. 2015. Quantifying the influence of CO2 seasonality on future ocean acidification. Biogeosciences Discussions 12: 5907-5940. DOI: 10.5194/bgd-12-5907-2015. Article
  • Shannon L., Coll M., Bundy A., Gascuel D., Heymans J.J., Kleisner K., Lynam C., Piroddi C., Tam J., Travers M. & Shin Y-J. 2014. Trophic level-based indicators to track fishing impacts across marine ecosystems. Marine Ecology Progress Series 512: 115-140 Article
  • Suprenand P.M., Drexler M., Jones D.L., Ainsworth C.H. 2015 Strategic assessment of fisheries independent monitoring programs in the Gulf of Mexico. PLoS ONE 10(4): e0120929. doi:10.1371/journal.pone.0120929
  • Thingstad T.F., Våge S., Storesund J.E., Sandaa R.-A. & Giske J. 2014. A theoretical analysis of how strain-specific viruses can control microbial species diversity.Proceedings of the National Academy of Sciences 111: 7813-7818. doi:10.1073/pnas.1400909111 Article 
  • Taucher J., Jones J., James A., Brzezinski M. A., Carlson C. A., Riebesell U. & Passow U. in press. Combined effects of CO2 and temperature on carbon uptake and partitioning by the marine diatoms Thalassiosira weissflogii and Dactyliosolen fragilissimusLimnology and Oceanography. doi: 10.1002/lno.10063 Article
  • Tanhua T., Orr J. R., Lorenzoni L. & Hansson L. 2015. Monitoring ocean carbon and ocean acidification. WMO Bulletin 64(1). Article
  • Uthicke S., Furnas M. & Lønborg C. 2014. Coral reefs on the edge? Carbon chemistry on inshore Great Barrier Reef reefs. PloS One9. doi:10.1371/journal.pone.0109092 Article
  • Vargas C. A., Aguilera V. M., San Martín V., Manríquez P. H., Navarro J. M., Duarte C., Torres R., Lardies M. A. & Lagos N. A. In press. CO2-driven ocean acidification disrupts the filter feeding behavior in Chilean gastropod and bivalve species from different geographic localities. Estuaries and Coasts. doi: 10.1007/s12237-014-9873-7. Article 
  • Våge S., Storesund J.E., Giske J. & Thingstad T.F. 2014. Optimal defense strategies in an idealized microbial food web under trade-off between competition and defense. PLoS ONE 9(7): e0101415. doi:10.1371/journal.pone.0101415 Article 
  • Voss R., Quaas M. F., Schmidt J. O. & Kapaun U. 2015. Ocean acidification may aggravate social-ecological trade-offs in coastal fisheries. PLoS One 10(3): e0120376. doi: 10.1371/journal.pone.0120376 Article
  • Wang G., Jing W., Wang S., Xu Y., Wang Z., Zhang Z., Li Q. & Dai M., 2014. Coastal acidification induced by tidal-driven submarine groundwater discharge in a coastal coral reef system. Environmenta Science & Technology 48 (22):13069-13075. DOI: 10.1021/es5026867 Article 
  • Weeber A., Swart S. & Monteiro P.  2015. Seasonality of sea ice controls interannual variability of summertime ΩA at the ice shelf in the Eastern Weddell Sea – an ocean acidification sensitivity study. Biogeosciences Discussions 12:1653-1687. doi:10.5194/bgd-12-1653-2015 Article
  • Weatherdon L., Rogers A., Sumaila R., Magnan A. & Cheung W.W.L. 2015. The Oceans 2015 Initiative, Part II: An updated understanding of the observed and projected impacts of ocean warming and acidification on marine and coastal socioeconomic activities/sectors. Studies N°03/2015, IDDRI, Paris, France, 46 p. Article
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