Home / News / Newsletters / Issue n°30 - April 2016

Issue n°30 - April 2016

Issue n°30 - April 2016
banner transition NL blank short
banner transition NL blank short
In this issue
 

Lisa Maddison

 

The IMBER IMBIZO IV that was held in Trieste, Italy last year provided the impetus for this issue of the IMBER Update. IMBIZOs are IMBER´s flagship 'gatherings'  (this is the meaning the Zulu word 'IMBIZO'). They are held every second year and bring together about 120 mutlidisciplinary scientists to discuss and synthesise the current state of knowledge about marine and human systems and their linkages, and to consider key research questions for the IMBER community to address going forward. In addition to the excellent science reporting and discussions at IMBIZO IV, we also had a lot of fun. This was particularly evident during the sometimes rather heated debate, where members of the audience were occasionally swayed to, literally, cross the floor by a novel point of view or argument!

The overall theme of IMBIZO IV was Marine and human systems: Addressing multiple scales and multiple stressors. The first article gives an overview of the meeting written by some of the IMBIZO IV organisers. The articles that follow are from participants who attended one of the four concurrent, but interacting workshops that are the essence of the IMBIZO format. The article about peoples´ perceptions of ecosystems services was presented in the Marine ecosystem-based governance workshop. The Coastal upwelling ecosystems as models for interdisciplinary studies of climate and global change workshop attracted a wide range of presentations. Here we highlight: Managing fisheries for adaptive capacity, Indicators of ocean acidification, and Eastern boundary upwelling systems and oxygen minimum zones. Workshop 3 dealt with Integrated modelling to support assessment and management of marine social-ecological systems in the face of global change, and you can read about using models for ecosystem-based management, and predicting potential fishing zones. Finally, there are three articles from the From regime shifts to novel systems – evaluating the social-ecological implications of lasting ecosystem changes for resource management workshop. These deal with Social-ecological regime shifts, Identifying driver species, and The synergistic effects of multiple species.

Where are they now? features the recently graduated Dr. Samiya Selim, who has attended both an IMBER summer school and IMBIZO IV. We wish her all the best in her new career.

I hope you enjoy reading this issue of the IMBER Update and will be inspired to apply to attend IMBIZO V next year.

banner transition NL

An overview of IMBIZO IV

Marine and Human Systems: Addressing Multiple Scales and Multiple Stressors

Eileen Hofmann1, Lisa Maddision2, Ingrid van Putten3 and Javier Arístegui4

1. Old Dominion University, Norfolk, VA, USA

2. IMBER IPO, Institute of Marine Research, Bergen, Norway

3. CSIRO, Hobart, Tasmania, Australia

4. Universidad de Las Palmas de Gran Canaria, Islas Canarias, Spain

 

The Integrated Marine Biogeochemistry and Ecosystem Research (IMBER) project is developed around four research themes, which focus on: key interactions in marine ecosystems; sensitivity to global change; feedbacks to the Earth system; and responses of society.  When IMBER started in 2005, the responses of society theme represented a new direction for global environmental change programmes because it explicitly acknowledged the role of humans as both drivers and recipients of change in marine ecosystems.  IMBER project-wide activities, regional programmes and working groups have advanced the science associated with each research theme.  However, the strength of these activities has been in the identification of theoretical and methodological overlap among the themes, facilitating integration of ideas and synthesis of research outcomes, and highlighting new research directions.

The biennial IMBIZOs are an important IMBER-wide activity for assessing current understanding of theoretical and empirical research at the local, regional and global scale, and pointing to future research needs.  IMBIZO IV, held in October 2015 in Trieste, Italy, addressed linkages between marine ecosystems and human systems (Fig. 1).  In particular, emphasis was on current systems understanding and approaches to predict the effects of multiple stressors, at multiple scales, on marine ecosystems and dependent human populations.  A novel aspect of this IMBIZO was the focus on exposing the need for human systems to respond to changes and for governance systems to adequately guide these responses.

IMBIZO-Fig 1

Figure 1. Schematic of human-ocean interactions and the four workshop topics that were the focus of IMBIZO IV.

 

IMBIZO IV was developed around four workshops (Fig. 1) that addressed i) marine ecosystem-based governance, ii) upwelling systems as models for interdisciplinary global change studies, iii) integrated modeling to support marine socio-ecological systems under global change, and iv) regime shifts and their socio-ecological implications.  Although each workshop had distinct objectives, all addressed aspects of climate, ecosystems and societies with a view towards integrating and synthesizing current understanding and highlighting approaches for developing innovative societal responses to changing marine ecosystems.  The workshops were supplemented with plenary presentations that provided overviews of the state of understanding and research needs and joint sessions and debates that allowed cross-workshop interactions (Fig. 2).   

IMBIZO-Fig 2

Figure 2. Debates held at IMBIZO IV engaged the audience to take a position on four questions that addressed the importance of natural versus social sciences to inform marine governance and control of managers and stakeholders on scientific research. Clockwise from top: Ratana Chuenpagdee and Stuart Corney debated opposing viewpoints, Eric Galbraith (debate moderator) and Einar Svendsen (debator), debate audience, and discussion group. Photo credit: V. Villanger. 

 

Within the context of each workshop, questions were addressed that considered the challenges of multiple stressors, pressures, and drivers, existing knowledge gaps, and the type of expertise needed to move forward.  Some workshops also evaluated the need for paradigm shifts to adequately address particular research questions. The overall goal of each workshop was to determine how integration of the diverse array of knowledge and different research outcomes for marine systems could be done to provide useful advice for policy and management.   

The results of the individual workshops are being summarized in a variety of ways including white papers, synthesis papers, short communications, and special issues.  However, the workshop results have common components with perhaps the clearest message being the need for continued conversations and exchange of information between scientists from different disciplinary backgrounds. To enable this dialogue to take place collaboratively and ultimately to develop workable solutions will mean that a common understanding of language will need to be developed and that jargon be avoided. Facilitating cross-disciplinary communication by domain experts will also help crucially important communication to management authorities and decision makers.

Aside from the need for good communication between scientists that straddle the physical, ecological and human domains, the different workshops considered the linkages and interactions between the driving forces (pressures-state-impacts-responses, DPSIR) and how these are understood and represented.  For most marine systems, the system state, how much of what is present and where, can be described with differing degrees of certainty depending on location and factors such as monitoring intensity and accessibility.  The connectivity and linkages between marine system components and driving forces are known from a theoretical perspective and for many systems these have been described quantitatively using different modeling approaches.  However, there is considerable empirical uncertainty about how marine systems might respond to continued and cumulative anthropogenic stresses and how in turn, this may feedback to the human domain and affect, for instance, future food security.

Marine systems may not be generalizable, sometimes cannot be simply scaled up, or may not respond linearly to anthropogenic stressors.  Regime shifts may occur that are not easily – or not at all reversible thus requiring adaptation by resource users. The governance system is crucially important in this context as it provides links to management, policy and regulatory systems that influence use of, and access to, marine resources.  Governance institutions are ultimately responsible for the sustainable management of marine resources and any necessary reduction in the pressure exerted on the resources. These governance systems in essence close the loop between the natural and human systems.  Natural, socio-economic, and governance systems need to be central to continued research efforts and inform all levels of decision making to ensure informed steps are taken.

Global environmental change is happening and will continue to affect ecosystems and alter the ecosystem services provided to humanity. The need for timely detection and attribution of these changes remains, especially where change is irreversible.  Human systems and society at large are at the same time the creators of the many stressors as well as the drivers of change to our marine ecosystems. Human systems can drive positive changes through good governance aimed at reducing vulnerability, and enhancing adaptive capacity and resilience.  It is clear that many knowledge gaps remain, in particular the way in which multiple drivers and stressors interact. Much work also remains to be done in further detailing and modeling the crucial dependencies between human and ocean systems. All these uncertainties place limitations on the predictability of governance outcomes and risk unintended consequences and maladaptation if not addressed adequately.  Outcomes from IMBIZO IV will provide guidance for these important research efforts for the next decade of IMBER research.

IMBER gratefully acknowledges the support provided by the Istituto Nazionale di Oceanografia and Geofisica Sperimentale (OGS),  Institute of Marine Research, Norway (IMR), East China Normal University (ECNU), Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO), Ocean Carbon & Biogeochemistry (OCB) Program, Seientific Committee on Oceanic Research (SCOR),  European Space Agency and European Marine Research Network (EuroMarine) for IMBIZO IV and their ongoing support of IMBER activities.

     
banner transition NL

Science Highlights from the IMBER IMBIZO IV

Public perceptions of ocean ecosystem services: indispensability, current state and readiness to act

Robert Blasiak

Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan

 

While science and policy are crucial for ensuring conservation and sustainable use of the world’s resources to promote long-term human well-being, a third essential element is the shaping of public perceptions through communication. Effective policymaking is informed by an understanding of specific socio-cultural contexts, while simultaneously building on any latent readiness for passive or direct action by the general public. Previous research demonstrated that physical proximity to natural resources encourages greater dedication to sustainable management and use. But how does this apply to ocean ecosystems? How does the public perceive the benefits it gains from them? Do these perceptions depend on age, gender, nationality? This research started in Japan, and has since expanded to the USA and other countries, and aims to contribute to the growing body of knowledge on these issues.

Initial study in Japan

Wakita et al. (2014) conducted the first study, focusing on residents of five prefectures across Japan. A survey was developed drawing on the hypothesis that perceptions of the indispensability of different types of ecosystem services are a predictor of behavioural intentions. Over 800 responses were collected. Using a structural equation model with constructed variables, Wakita et al. found that a latent “cultural” variable had the strongest correlation with stated behavioural intentions to conserve marine ecosystems. A second latent variable of “essential” services (mainly provisioning services) showed a weaker correlation. This preeminence of cultural ecosystem services may lie in the strong national attraction to traditional socio-ecological landscapes (satoyama) and seascapes (satoumi) that have dominated Japan’s history (Ichikawa and Blasiak 2012).

Large-scale survey in the USA

Building on the outcome of the Japanese survey, and to enable cross national and cultural comparisons, a USA survey was conducted in 2014 with 1,434 respondents (Blasiak 2015). The sample surveyed was demographically balanced in terms of age and gender, and also representative of the country’s spatial population distribution (determined from the respondents’ postal codes). The survey included questions about the ocean’s provisioning, regulating and cultural services, divided into sections relating to: (1) perceived indispensability of the particular ecosystem service; (2) perceived current state of the ecosystem service; (3) readiness to act to promote the conservation and sustainable use of different types of marine ecosystem services. Respondents were asked to answer the first two sections with regard to both the USA and also the whole world. (e.g. “The loss of foodstuffs provided by the ocean would have a negative effect on the diets of people in my country.” / “The loss of foodstuffs provided by the ocean would have a negative effect on the diets of people around the world”).

The data is still being analyzed, but a number of key findings presented in Blasiak et al. (2015) are outlined as follows.

Finding 1: Age-dependent aversion to top-down action (taxation)

Respondents indicated varying levels of support for five actions to support the conservation and sustainable use of marine ecosystem services: pay a tax, donate, volunteer, support environmentally-friendly businesses, purchase green products. The greatest opposition was to taxation, with a strong age dependency and weaker gender dependency across all three types of ecosystem services (Fig. 3). Around 25% of respondents in their 20s opposed taxation to promote marine ecosystem services, while this doubled to over 50% among respondents in their 60s. Although women respondents  in previous studies seemed better informed about environmental issues and more engaged than men, this study suggested a more complex situation. Women were more opposed to an environmental tax than men in their 20s. This difference became less apparent as the age of respondents increased and was reversed in the oldest age bracket. Interestingly, gender and age distinctions were not shown for other actions, namely supporting environmentally-friendly business and purchasing green products (Fig. 4).

Blasiak-Fig 1

Figure 3. Correlation between age of respondents and percentage who somewhat or strongly disagree with an environmental tax to support a marine (a) provisioning service; (b) regulating service; and (c) cultural service. Solid blue line: female respondents; dashed orange line: male respondents.  (Blasiak et al. 2015)

 
Blasiak-Fig 2

Figure 4. Correlation between age of respondents and percentage who somewhat or strongly disagree with different ways to supporting marine ecosystem services. Solid blue line: female respondents; dashed orange line: male respondents. (Blasiak et al. 2015)

 

Finding 2: Type of action more critical than type of ecosystem service

Respondents did not distinguish significantly between provisioning, regulating and cultural services, but showed strong preferences for specific types of actions (Fig. 5). Accordingly, opposition or support for each action is almost the same for all three types of ecosystem services. A strong preference for bottom-up or self-directed action was evident, with purchasing decisions (supporting green business / buying green products) meeting with the least resistance, while top-down intervention (taxation) was heavily opposed.

Blasiak-Fig 3

Figure 5. Number of respondents (out of 1,434 total) who somewhat or strongly disagree with different actions to support marine ecosystem services. (Blasiak et al. 2015)

 

Finding 3: Little or no correlation between political leanings and perceptions

The USA political system is often said to be growing increasingly polarized, with commitment to environmental issues seemingly split down party lines. From their respective zip codes, it was possible to determine in which state the respondents live. Using the non-profit Cook Partisan Voting Index, which calculates the political leanings of different states based on previous electoral results, a rough comparison was made between the respondents’ supposed political leanings and their perceptions of the indispensability of ecosystem services (Figure 6a) and readiness to pay an environmental tax (Figure 6b). In both cases, the results were surprisingly consistent across the political spectrum, suggesting that perceptions of the environment and readiness to act to protect it may transcend political polarization in the USA.

Blasiak-Fig 4

Figure 6: (a) Correlation between aggregated perceived indispensability of ecosystem services and state political leanings from the Cook Partisan Voting Index. (b) correlation between aggregate readiness to accept environmental tax and Cook Partisan Voting Index. (Blasiak et al. 2015)

 

Finding 4: Little distinction between “our” ocean and “their” ocean

Using Kendall’s tau correlation analysis, we compared a variety of constructed variables about perceived indispensability and the current state of marine ecosystem services. In this case, we found by far the strongest correlation between two USA/Global pairs: for perceived indispensability (0.793***) and current state (0.788***). This suggests that respondents see little distinction between “our” ocean and “their” ocean, and may perceive the ocean as a single system shared by all – perhaps comparable to the atmosphere. These findings are suggestive, but further qualitative research is needed to get a better understanding of public perceptions.

Next steps

Comparing the results of the first two studies in this series (Japan and USA), there is clearly diversity in how different cultures perceive the ocean and the benefits it provides. Furthermore, the USA study generated some interesting and suggestive findings related to how gender and age may affect perceptions or readiness to act to ensure sustainable management of ocean ecosystems. The initial assessment of political leanings and perceptions also points to broader consensus among the public with regard to environmental issues than political rhetoric may suggest. It would be interesting if similar surveys were conducted in other countries to enhance the comparability of results. Likewise, supplementary qualitative studies based on in-person interviews with respondents could help to determine if the results of the statistical analysis have been accurately interpreted. Any researchers interested in collaborating with this project, or learning more about the previously conducted studies are warmly welcomed to email the author at a-rb@mail.ecc.u-tokyo.ac.jp

     

References

  • Blasiak, R. et al. (2015) Marine ecosystem services: Perceptions of indispensability and pathways to engaging citizens in their sustainable use. Marine Policy 61: 155-163.
  • Ichikawa, K. and Blasiak, R. (2012) Revitalizing socio-ecological production landscapes through greening the economy in J. Puppim de Oliveira (Ed.) United Nations University Press, Tokyo, Japan.
  • Wakita, K. et al. (2014) Human utility of marine ecosystem services and behavioral intentions for marine conservation in Japan. Marine Policy 46: 53-60.
banner 2nd transition NL

Managing fisheries in upwelling ecosystems for adaptive capacity: Insights from dynamic social-ecological drivers of change in Monterey Bay, California

Stacy Aguilera

Leonard and Jayne Abess Center for Ecosystem Science and Policy, University of Miami, 1365 Memorial Drive, Ungar Building 230M, Coral Gables, FL 33124, USA

Email: s.aguilera1@umiami.edu

 

Coastal upwelling systems, particularly those found in eastern boundary currents, support highly productive and diverse ecosystems (Chavez and Messié 2009). In addition to being ecologically significant, these regions are socially significant as well. Fisheries from these regions contribute considerably to the global food supply and economy, and the abundance of marine life attracts many users, from recreational fishers to conservation organizations to the tourism industry (Ryther 1969).

At the IMBER IMBIZO IV, in Italy this past October (2015), their importance was underlined in the “Coastal upwelling ecosystems as models for interdisciplinary studies of climate and global change” workshop. Many scholars are working to address the challenges for coastal oceans in the 21st century, using coastal upwelling ecosystems as models. Participants contributed a broad range of perspectives, from oceanography to ecology, political science to biogeochemistry. The meeting focused on five primary themes regarding upwelling regions – scales of variability, drivers of variability, ecosystem pressures, ecosystem services, and human responses [mitigation/adaptation] – as well as major gaps in our understanding of upwelling systems. Here I discuss one of the papers (Aguilera et al. 2015) that was presented.

The upwelling Monterey Bay region within the California Current is one of world’s most productive marine ecosystems, with many industries and communities relying on its marine resources (Breaker and Broenkow 1994). As with all fisheries globally, the wetfish fisheries of Monterey Bay have been subject to confounding fluctuations for centuries, driven by variations such as climate, governance, technology, and markets. Such inevitable change presents both social and ecological challenges and opportunities. With climate change, many more variations and new conditions will impose stressors on these systems, and so an important question to be considered is: how should fisheries be managed in such rapidly changing social and ecological environments?

Research undertaken by the Center for Ocean Solutions Small-Scale Fishery Working Group aimed to investigate the major external drivers behind outcomes in three Monterey Bay wetfish fisheries: Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), and market squid (Loligo opalescens). These modern fisheries are remnants of the famous sardine fishery of Monterey Bay in the mid 20th century. Today, they comprise a tightly linked system where fishermen and processers participate in all three fisheries, but switch their target fishery according to current conditions. Shifting focus among fisheries is key to adaptive capacity and reduced social and ecological vulnerability. The structure of these fisheries allows the participants to adapt to changing conditions, to survive economic or environmental disturbances and to benefit when conditions are optimal.

To understand the social-ecological linkages amongst the small-scale fisheries in Monterey Bay, and how large-scale drivers contribute to short- and long-term fishery outcomes, a cluster analysis of annual landings was performed to identify time periods when one fishery accounted for a plurality of the landings. Elinor Ostrom’s social-ecological system framework was then used to identify large-scale drivers (Ostrom 2009). Ostrom developed this framework partly to describe and explain complex social-ecological systems (SESs), but also to identify subsystems particular to any common pool resource. Many researchers use it to identify key variables within each subsystem, but we used it to ensure that large-scale drivers from every aspect of the fishery common pool resource system were included. The drivers identified were markets and technology, climate dynamics, regulations and management, and community involvement. Applying these drivers to the seven identified points of switching fishery dominance mode within a 36-year time series, enabled us to identify the major drivers which were attributed to these transitions (Fig. 7).

Aguilera-Fig 1

Figure 7. Timeline of dominance modes and transition points. Identified drivers most associated with each transition are listed accordingly. (from Aguilera et al. 2015)

 

Although the system responds and fluctuates according to many drivers, market and climate factors were the most frequently attributed drivers, and El Niño events the most common driver of change (Fig. 8). Limited access regulations played a minor role, and no large change in trends or significant shift from one fishery to another was apparent because of any technological or community driven aspects.

Aguilera-Fig 2

Figure 8. Dominance mode transition points. Proportional landings bubble plots showing dominance mode transition points for three of the seven transition years identified by the cluster analysis. Circle size is scaled to relative volume of landings (Data from Table18PUB CDFW). Darkest purple circles are sardine landings, lightest purple are anchovy landings. Gray arrows represent the movement of focus shifting from one fishery to the next. PDO refers to the Pacific Decadal Oscillation. (from Aguilera et al. 2015)

 

Mangers of these fisheries rely on environmental data, especially fish abundance estimates, to regulate how much fishing is allowed (PFMC 2011). These abundance-guided governance decisions explained long-term fishing trends more than any other variable, although fishing effort metrics (i.e., CPUE and number of anchovy vessels) and climatic drivers of availability were also important.

ENSO (El Niño Southern Oscillation) was the most frequent factor attributed to changes in fishery dominance in any given year. The question then, is how fishery participants, managers and others involved in the fisheries find, understand and use the ENSO information available? This is especially pertinent considering the amount of funding and effort dedicated to forecasting ENSO events and communicating such information. To answer the question, we conducted 49 semi-structured interviews with users and managers in the Monterey Bay wetfish fisheries industry regarding how they find, trust, and communicate ENSO forecasts, and how they use the information to make decisions. Questions aligned under five main themes:

  • Role of ENSO in Monterey Bay wetfish fisheries
  • Sources and trust of climate information
  • Communication of climate information within population
  • Integration of ENSO into fisheries management
  • Behavior change, choices made according to information

Interview data were supplemented with data from ENSO observations and forecasts, social media, mainstream media, observations within the community, historical documents and participant correspondence. All data were coded using the computer assisted qualitative data analysis software NVivo 10 (Gibbs 2002). This study (Aguilera et al. in prep) aims to make ENSO research more applicable to a variety of users. In addition, improved understanding of ENSO events can be used to hypothesize about how upwelling systems may respond to climate change.

Climate change poses challenges to the fishing industry, by impacting fish accessibility [new migration and distribution patterns], fish availability [lower recruitment rates and changes in time of life history events] (Doney et al. 2012), and lower quotas [with additional stressors, possible reallocation of quotas to increase forage fish allotment to support ecosystems]. It is likely that other concerns such as food security (Godfray et al 2010) and species health (Pörtner et al. 2005) will also grow.

It is common for fishers to engage in different fisheries and to switch target fishery in response to various social and ecological drivers (Anderson et al. 2011; Badjeck et al. 2010; Schindler 2010). Yet, as livelihood diversification declines in many U.S. fisheries (Kasperski and Holland 2013, Norman and Holland 2012), climate change poses new risks and new conditions to which the system may or may not be ready to adapt to. We focused on fisheries in upwelling regions because understanding the drivers and potential ecological and social responses in these dynamic systems might elucidate how many of the world’s most important fisheries may behave in the future.

As this study shows, it is the interplay of many drivers, not just one, that changes fishery outcomes. As climate change and other factors increase uncertainty in fisheries, upholding the flexibility of a diverse fishing portfolio, with users switching target fishery according to the conditions at hand, as in the case of the Monterey Bay wetfish fisheries, contributes to more resilient ecological and social states. To maintain socially and ecologically sustainable fisheries in upwelling ecosystems in the face of climate change, human dimensions should be incorporated by understanding information, communication and usage, and by encouraging flexible management to ensure continued resilience through fluctuating conditions.

Learn more

Aguilera S.E., Cole J., Finkbeiner E.M., Le Cornu E., Ban N.C., Carr M.H., Cinner J.E., Crowder L.B., Gelcich S., Hicks C.C., Kittinger J.N., Martone R., Malone D., Pomeroy C., Starr R.M., Seram S., Zuercher R., Broad K. (2015) Managing small-scale commercial fisheries for adaptive capacity: Insights from dynamic social-ecological drivers of change in Monterey Bay. PLoS ONE 10(3): e0118992. doi:10.1371/journal.pone.0118992 

 

 

References

  • Anderson S.C., Flemming J.M., Watson R., Lotze H.K. (2011) Rapid global expansion of invertebrate fisheries: trends, drivers, and ecosystem effects. PLoS One 6: e14735.
  • Badjeck M.-C., Allison E.H., Halls A.S., Dulvy N.K. (2010) Impacts of climate variability and change on fishery-based livelihoods. Marine Policy. 34: 375-383.
  • Breaker L.C., Broenkow W.W. (1994) The circulation of Monterey Bay and related processes. Oceanography and Marine Biology: an Annual Review 32: 1-64.
  • Chavez F.P., Messié M. (2009) A comparison of eastern boundary upwelling ecosystems. Progress in Oceanography. 83: 80-96.
  • Doney S.C., Ruckelshaus M., Duffy J.E., Barry J.P., Chan F., English C.A., Galindo H.M., et al. (2011) Climate change impacts on marine ecosystems. Annual Review of Marine Science 4:11–37.
  • Gibbs G. (2002) Qualitative Data Analysis: Explorations with NVivo. London: Open University Press.
  • Godfray H.C.J., Beddington J.R., Crute I., Haddad L., Lawrence D. et al (2010). Food Security: The challenge of feeding 9 billion people. Science 327:812.
  • Kasperski S., Holland D.S. (2013) Income diversification and risk for fishermen. Proc Natl Acad Sci USA. 110: 2076-2081. 
  • Norman K.C., Holland D.S. (2012) Resilient and economically viable coastal communities. CCIEA Phase II Report: Ecosystem Components Human Dimensions. Seattle (WA): NOAA Fisheries; 2012.
  • Ostrom E. (2009) A general framework for analyzing sustainability of social-ecological systems. Science 325: 419-422.
  • Pacific Fishery Management Council (2011) Coastal Pelagic Species fishery management plan as amended through Amendment 13, 48 pp.
  • Pörtner H.O., Langenbuch M., Michaelidis B. (2005) Synergistic effects of temperature extremes, hypoxia, and increases in CO2 on marine animals: From Earth history to global change. Journal of Geophysical Research 110, C09S10.
  • Ryther J.H. (1969) Photosynthesis and fish production in the sea. Science 166: (3901), 72-76.
  • Schindler D.E., Hilborn R., Chasco B., Boatright C.P., Quinn T.P., Rogers L.A., et al. (2010) Population diversity and the portfolio effect in an exploited species. Nature. 465: 609-612.
banner 2nd transition NL

Pteropod shell dissolution as an indicator of ocean acidification across different upwelling regimes

Nina Bednaršek1,*, Ryan McCabe2 and Terrie Klinger1

1. School of Marine and Environmental Affairs, 3707 Brooklyn Ave NE, Seattle, WA, 98105, USA

2. University of Washington, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), Seattle, WA, 98105, USA

*Email: nbedna@uw.edu

 

Ocean acidification (OA) is a consequence of human activities that is threatening marine species and ecosystems around the world. The rate and scale of changes in marine chemistry is unprecedented in human history. Coastal upwelling ecosystems are particularly vulnerable to these changes because they are already naturally exposed to corrosive waters; upwelling of deep waters with high CO2 concentrations results in a lower aragonite saturation state (Ωar), which determines whether aragonite precipitates (at supersaturated conditions; Ωar>1) or dissolves (undersaturated conditions; Ωar<1). The absorption of anthropogenic CO2 in upwelling systems is causing longer, more intense and severe OA conditions that ultimately result in declining habitat suitability (Feely et al., 2004; Feely et al., 2008; Gruber et al., 2012; Hauri et al., 2013; Bednaršek et al., 2014a). This substantially impacts marine calcifiers such as pteropods, free-swimming marine planktonic snails. Because of their thin aragonite shells, which rapidly dissolve at Ωar<1, they are extremely sensitive to OA (Bednaršek et al., 2012b; 2014a,b).

Pteropods are ubiquitous across the four major upwelling systems, and are important ecological and biogeochemical players in the areas of coastal and shelf waters of the California Current Ecosystem, the Humboldt Current and the Canary Current (Fig. 9). Pteropods are extremely effective grazers and are thus, efficient at channeling energy to higher trophic levels. This makes them an important food source for a variety of other zooplankton species, including chaetognaths, heteropods, ctenophores, medusae, and siphonophores; amphipods; cephalopods; as well as pelagic and demersal fish like cod, salmon, mackerel, sablefish, clupeids, salmonids, and gadoids; and even seabirds and whales (Bednarsek et al., in review). Recent studies (Bednaršek et al., 2014a; Bednaršek and Ohman, 2015) have shown that the pteropod species Limacina helicina, one the most dominant and ecologically important pteropod species in the global ocean, is particularly vulnerable to OA.

Although the California Current Ecosystem (CCE) is one of the best studied upwelling systems, it is also one of the regions most vulnerable to OA. Currently, more than 50% of L. helicina individuals collected in the coastal region of the CCE show severe shell dissolution. Shell dissolution, in turn, has been demonstrated to correspond with ambient marine carbonate chemistry conditions (Bednaršek et al., 2014a). The threshold for shell dissolution occurs at Ωar values of ~ 1.2-1.3, approximately equivalent to pH ~7.80-7.85 and pCO2 ~ 650-700 ppm. Exposure to these conditions results in only minor types and extent of shell dissolution and shell porosity. However, with longer exposures to conditions of Ωar<1, deeper and more extensive shell dissolution prevails (Figure 2b, 2c; Bednaršek et al., 2012b). The rapidity of shell dissolution is attributed to the combination of a metastable aragonite crystal structure that is among the thinnest known for calcifying organisms (Sato-Okoshi et al., 2010), coupled with insufficient protection by an extremely thin organic layer that covers the shell (Bednaršek et al., 2014b). Shell dissolution results in thinner shells more prone to fragmentation, and coincides with impaired swimming abilities and increased susceptibility to predation and infection. From a biogeochemical point of view, shell dissolution also ultimately effects carbon export to the deep ocean, where pteropods are estimated to contribute 20-42% of global carbonate production (Bednaršek et al., 2012a).

 

The extent of shell dissolution is a robust and quantifiable metric that can be easily measured in a cost-effective manner. Because of this, pteropod shell condition may be used as an effective biological indicator of OA and has recently been ranked as a high priority indicator for the California Current Integrated Assessment project (Bednaršek et al., in prep.). In addition, due to their sensitivity to carbonate chemistry, pteropods have also been identified as one of the most promising indicators of biological impacts of OA within the OSPAR monitoring and assessment framework for the Northeast Atlantic (ICES 2014). Pteropod shell dissolution can serve as an early warning signal, adding an important element to marine and ecosystem monitoring programs. By repeatedly assessing the condition of shells collected from the natural environment, regions of highest OA vulnerability and those characterized by spatial and temporal variability in OA can be identified (Bednaršek et al., in prep.).

Predictions of shell dissolution along Ωar gradients could help to establish patterns of OA exposure across different upwelling regimes. In all upwelling systems, waters of low saturation state (Ωar<1) overlap or impinge upon waters that serve as pteropod habitat. However, the four main upwelling systems are also characterized by varying degrees in the magnitude and duration of undersaturation. To establish clear links between carbonate chemistry and biological conditions, it is critical to co-locate spatial and temporal differences in carbonate chemistry with pteropod sampling. Based on the measured shell dissolution across time and space, the impacts of OA exposure can be determined for each upwelling regime. Comparison of the dissolution patterns and the progress of dissolution in time would indicate not only regions that are most sensitive to OA but also which are changing most rapidly as a result of anthropogenic additions of CO2. The extent of shell dissolution can now be quantitatively attributed to anthropogenic CO2 impacts and thus differentiated from natural variability (Feely et al., in prep.). In this way, estimates of shell dissolution can be used as a metrics for tracking current and future CO2 trends, which can, in turn, support long-term monitoring with respect to increasing OA. 

To generalize the application of biological indicators across different regions and regimes, standard methodologies must be developed (e.g. common sampling strategies, appropriate species and metrics, should be developed (Bednaršek et al., in prep.). Currently, more data on pteropod abundance and distribution is needed, particularly in the Benguela and Canary Current systems (Fig. 9). Even if funding for more detailed field sampling is currently not available, one simple way to start is by building up a better, more complete, baseline archive of both pteropod shell condition across multiple species and ambient environmental parameters across the different upwelling systems so that they can be analyzed in the near-future. 

     
Bednarsek-Fig 1

Figure 9. Global pteropod distribution (blue dots), with pink dots and circles indicating the distribution of pteropods across the four major upwelling systems of the world including the California, Humboldt, Benguela, and Canary Current systems. The map is based on an available pteropod dataset (PANGEA database; doi.pangaea.de/10.1594/PANGAEA.777387). All four upwelling systems could benefit from additional sampling efforts, especially the Benguela and Canary Current systems. 

 
Bednarsek-Fig 2

Figure 10. Pteropod Limacina helcina response to OA: when exposed to noncorrosive conditions, pteropod shells appear intact and transparent (a); exposure to Ωar~1 produces first signs of dissolution (white ribs on the shell; b), while Ωar<1 conditions (experimental conditions projected for year 2050) increase the severity of dissolution, as well as % individuals affected by dissolution (Bednaršek et al., unpublished). The shell looks pitted, opaque and with deeper extending dissolution (c). 

 

References

  • N. Bednaršek et al. 2012a. The global distribution of pteropods and their contribution to carbonate and carbon biomass in the modern ocean. Earth System Science Data 4: 167–186.
  • N. Bednaršek et al. 2012b. Description and quantification of pteropod shell dissolution: a sensitive bioindicator of ocean acidification. Global change biology 18(7): 2378-2388.
  • N. Bednaršek et al. 2014a. Limacina helicina shell dissolution as an indicator of declining habitat suitability owing to ocean acidification in the California Current Ecosystem. Proceedings of the Royal Society B: Biological Sciences 281: 20140123.
  • N. Bednaršek et al. 2014b. 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.
  • N. Bednaršek et al. 2015. Changes in pteropod distributions and shell dissolution across a frontal system in the California Current System. Marine Ecology Progress Series 523:93-103. doi: 10.3354/meps11199 
  • R. A. Feely et al. 2004. Impact of anthropogenic CO2 on the CaCO3 system in the oceans. Science 305: 362–366..
  • R. A. Feely et al. 2008 Evidence for upwelling of corrosive "acidified" water onto the continental shelf. Science 320: 1490–1492.
  • N. Gruber et al.2012. Rapid progression of ocean acidification in the California Current System. Science 337: 220–223.
  • C. Hauri et al. 2013. Spatiotemporal variability and long-term trends of ocean acidification in the California Current System. Biogeosciences 10: 193–216.
  • ICES 2014 Final Report to OSPAR of the Joint OSPAR/ICES Ocean Acidification Study Group (SGOA). ICES CM 2014/ACOM: 67. 141 pp.
  • W. Sato-Okoshi et al. 2010. Shell structure of two polar pelagic molluscs, Arctic Limacina helicina and Antarctic Limacina helicina antarctica forma antarctica. Polar Biology 33(11): 1577-1583.
banner 2nd transition NL

Eastern boundary upwelling systems (EBUS) and oxygen minimum zones (OMZ): A natural future earth priority

Paulmier A., Dewitte B., Illig S. and V. Garçon

LEGOS, CNRS/IRD/UPS/CNES, Toulouse, FRANCE

 

The tropical and subtropical systems at eastern oceanic boundaries are characterised by upwelling-induced high primary production and export that, in combination with weak ventilation, causes oxygen depletion and the development of oxygen minimum zones (OMZs) in intermediate waters. Associated with strong physical-biogeochemical gradients, OMZs affect nearly all aspects of ecosystem structure and function in the water and on the seabed. The economies of countries neighbouring upwelling zones are largely reliant on marine resources for food and employment. There is an urgent need for increased capacity to predict changes in ecosystem structures and coastal water quality as a result of deoxygenation and acidification, to define sustainable management strategies of their marine resources. The OMZs also play critical roles in atmospheric chemistry and climate through emission of active trace gases. These regions also feature extensive stratocumulus cloud decks that play a pivotal role on the Earth’s radiation budget and thus, in the response of the climate system to greenhouse gas forcing. IPCC coupled global circulation models (CGCM) have great difficulties simulating eastern boundary regions, and exhibit severe biases in Sea Surface Temperature (SST; Richter et al., 2015) and OMZs structures (Cabré et al., 2015). Since 2009, the Surface Ocean - Lower Atmosphere Study (SOLAS) project has produced an Eastern Boundary Upwelling System (EBUS) and OMZs Strategy Initiative and has held three international workshops (Peru, November 2010 and 2012; EUR-OCEANS Conference, Toulouse, October 2011). An integrative approach for future EBUS research should join the efforts of various Future Earth core projects to combine atmosphere, ocean, continents and socio-economic dimensions. Some major scientific findings regarding EBUS are presented here.

Work is currently being undertaken to determine the cause of the warm SST bias in CGCMs (e.g.: VOCALS program, EU Preface project). Because the low-resolution global coupled models tend to underestimate the upwelled waters and are not able to simulate a well-defined upwelling cell at the coast, they have difficulties in accounting for the strong air-sea contrast in the EBUS. For instance, they usually represent more diffuse air temperature inversion zones located at lower altitudes than observed in forced atmospheric models (see Wyant et al. (2010) for the Humboldt system). This bias in particular prevents the formation of low-level clouds, which in turn significantly alters the radiative heat budget at the air-sea interface and results in SST bias ~+3°C (Richter et al., 2015). Other possible mechanisms of air-sea interaction at work in the EBUS include wind-upwelling-SST gradients, SST-low clouds, wind-SST-low clouds, wind-evaporation-SST and SST-PBL (Planetary Boundary layer) turbulence-wind. However, the temporal and space scales at which they operate have yet to be elucidated. Therefore, a better understanding of these air-sea coupled processes and their relative contribution is required, all the more so because the radiative budget in the upwelling regions may involve zonal heat transfer from the coast to the inner ocean by offshore propagating eddies. Conflicting model results on the role of eddies in the heat budget in the South Eastern Pacific (Colas et al., 2012; Zheng et al., 2010; Toniazzo et al. 2010) calls for further observational analysis (Holte et al., 2013) and for better understanding of the control of eddy activity by equatorial variability (Dewitte et al, 2012; Combes et al., 2015).

The main biogeochemical issue is to determine the net effect of the upwelled OMZ on the Earth system, as a result of the many feedback mechanisms involved (cf Law et al., 2013). Particularly important are the interactions between the remineralization processes in subsurface waters associated with chemical anomalies and bacterial activity, and primary production at the surface. In addition, EBUS and OMZ do not match exactly, suggesting a sensitivity of the oxygen budget to some aspects of the global circulation, as well as basin-scale and interhemispheric differences. According to the World Ocean Atlas (WOA) 2013 database, the lowest oxygen concentrations in the Atlantic, the most oxygenated ocean, go down to 23µM and 14µM in the Canary and Benguela EBUS, respectively, whereas in the Pacific, the least oxygenated ocean, the minimum oxygen concentrations are close to the detection limit.

Future challenges to understanding the EBUS-OMZ systems lie with identifying relevant domains and documenting relevant parameters of the appropriate space and time scales. All the EBUSs are linked to the equatorial dynamics, in particular showing an extreme sensitivity of the OMZ extension to the mean equatorial circulation (e.g. Montes et al., 2014). In terms of variability, the EBUSs are also very connected to the equatorial system through trapped coastal Kelvin waves controlling the interannual variability, particularly during El Niño and the Benguela El Niño events (Dewitte et al., 2012; Bachèlery et al., 2015). Another important domain for the EBUS-OMZ are mid-latitude anti-cyclonic gyres. These control the intra-annual variability as their sea level pressure is highly correlated to the coastal alongshore winds off both Peru and Namibia, (Dewitte et al., 2011).

Relevant space scales include sub-regional domains, and three or four sub-components (or biomes and ecosystems) of the EBUS-OMZs are usually described (Fréon et al., 2009). In particular, the intense cross-shore gradient between the shelf and the open ocean sub-systems in terms of physical forcing and the biogeochemical activity and ecosystem communities must be correctly represented. For instance, simulations from the ROMS-BIOEBUS model in the Benguela system (Gutknecht et al., 2013) indicate off-shore O2 fluxes (production and aerobic processes) twice as often as near the coast. By contrast, the highest microbiological rates appear close to the coast of Peru, with a local ammonium release fueling the nitrogen loss in the nitrogen cycle through denitrification and anammox processes. The signature of this biogeochemical activity (relative nitrite maxima and nitrogen deficit) is advected off-shore in a second stage (Kalvelage et al., 2013). EBUS-OMZs are also typically subjected to mesoscale and submesoscale variability and are populated by eddies. As evidenced from a modelling lagrangian study off Peru (Fig. 11), the paths (corridors) of mesoscale structures maintain the boundaries of the OMZ, whereas higher frequency submesoscale fluctuations ventilate the OMZ through eddy fluxes and local mixing (Bettencourt et al., 2015). This fine-scale pattern not only impacts the OMZ structure but also impacts the air-sea fluxes of greenhouse gases, illustrated for example in the extreme variability of CO2 and N2O between the coast and the open ocean, inducing complex coupled and decoupled source/sink situations (e.g. Paulmier et al., 2008; Kock et al., 2016).

 
 
Paulmier-Fig 1

Figure 11. 3D structure of the mean OMZ core off Peru, based on the 20 µM iso-surface of mean O2 concentration, and finite-size Lyapunov exponent (FSLE: l) fields (measuring the intensity of mixing) at 410 m depth from ROMS-BIOEBUS model simulations. Note the stretched vertical scale. Flat top shows the Peruvian coast. (From Bettencourt et al., 2015). 

 

In terms of relevant time scales, the EBUS-OMZ are subjected to interannual (with a thermocline and oxycline deepening during the El Niño events: e.g. Morales et al., 1999) and longer scales. The annual/seasonal cycle is also well marked (Vergara et al., 2016). In particular off Peru and Namibia, the annual O2 cycle presents a possible de-phasing between the Humboldt and Benguela systems, but also within the same system (Fig. 12; note especially the differences between 12°S off Peru and 21°S off Chile). The winds as a main physical forcing may also show seasonal latitudinal shifts off Chile (e.g. Monteiro et al., 2011). Sub-seasonal to intra-seasonal timescales have been reported from SST observations, an activity that is modulated seasonally by changes in stratification for the Peru (See Dewitte et al., 2011; Illig et al., 2014) and Benguela (Goubanova et al., 2013) systems. Data collected during recent cruises and a mooring off Peru (cf AMOP project: http://www.legos.obs-mip.fr/recherches/projets-en-cours/amop) also revealed large variability in dissolved oxygen at higher frequency, which could be partly associated with internal waves (such as a tide).

 
Paulmier-Fig 2

Figure 12. Map of O2 concentration below 40 µM from CARS database for the Humboldt (left) and Benguela (right) systems with the annual evolution of the monthly O2 concentrations off central Peru and northern Chile, and off Namibia, on the eastern Pacific and Atlantic respectively. (Courtesy of B. Dewitte).

 

Modifications in physics and biogeochemistry impact the biological processes and ecosystems (e.g. habitats), and ecosystem services and ocean-related human activities. EBUS-OMZ systems exhibit high gradients and variability, including extreme events. They are the richest ecosystems in the ocean with strong ocean-atmosphere coupling. Consequently, they can be considered as natural laboratories in terms of multiple drivers and new technology challenges. There is a pressing need to improve the predictive capacities of regional coupled models, considering the breath of interactive processes between atmosphere, ocean, biogeochemistry and land at regional scales, and the limitations of global climate models for these regions. Coordinated multi-model experiments are crucial to achieve this, as are enhanced ocean and atmosphere observations of the eastern boundary regions. Future plans and actions need to include the EBUS-OMZ systems as a Future Earth priority, supporting international initiatives like the IOC UNESCO Global Oxygen Network (GO2NE).

     

References

  • Bachèlery, M.-L., Illig, S., and Dadou, I.: Interannual variability in the South-East Atlantic Ocean, focusing on the Benguela Upwelling System: Remote versus local forcing, J. Geophys. Res. Oceans 120, doi:10.1002/2015JC011168, 2015.
  • Bettencourt, J.H., Lopez, C., Hernandez-Garcia, E., Montes, I., Sudre, J., Dewitte, B., Paulmier A., and Garcon, V.: Boundaries of the Peruvian Oxygen Minimum Zone shaped by coherent mesoscale dynamics, Nat. Geosci. 8, 937-940, doi: 10.1038/ngeo2570, 2015.
  • Cabre, A., Marinov, I., Bernardello, R., and Bianchi, D.: Oxygen minimum zones in the tropical Pacific across CMIP5 models: mean state differences and climate change trends, Biogeosciences 12, 6525-6587, doi:10.5194/bgd-12-6525-2015, 2015.
  • Colas, F., Mcwilliams, J.C, Capet, X., and Kurian, J.: Heat balance and eddies in the Peru-Chile current system, Clim. Dyn. 39 (1-2), 509–529, doi:10.1007/s00382-011-1170-6, 2012.
  • Combes, V., Hormazabal, S., and Di Lorenzo, E.: Interannual variability of the subsurface eddy field in the Southeast Pacific, Journal of Geophysical Research Oceans 120 (7), 4907-4924, 2015.
  • Dewitte, B., Illig, S.,Renault, L., Goubanova, K., Takahashi, K., Gushchina, D., Mosquera, K., and Purca, S.: Modes of covariability between sea surface temperature and wind stress intraseasonal anomalies along the coast of Peru from satellite observations (2000–2008), J.Geophys. Res., 116, C04028, doi:10.1029/2010JC006495, 2011.
  • Dewitte B., Vazquez-Cuervo, J., Goubanova, K., Illig, S., Takahashi, K., Cambon, G., Purca, S., Correa, D., Gutierrez, D., Sifeddine, A., and Ortlieb, L.: Change in El Niño flavours over 1958-2008: Implications for the long-term trend of the upwelling off Peru, Deep Sea Research II, doi:10.1016/j.dsr2.2012.04.011, 2012.
  • Fréon, P., Barange, M., and Aristegui, J.: Eastern Boundary Upwelling Ecosystems: Integrative and comparative approachesProgress in Oceanography 83 (1–4), 1-14, 2009.
  • Goubanova, K., Illig, S., Machu, E., Garçon ̧ V., and Dewitte, B.: SST subseasonal variability in the central Benguela upwelling system as inferred from satellite observations (1999–2009), J. Geophys. Res. Oceans 118, doi:10.1002/jgrc.20287, 2013.
  • Gutknecht, E., Dadou, I., Le Vu, B., Cambon, G., Sudre, J., Garcon, V., Machu, E., Rixen, T., Kock, A., Flohr, A., Paulmier, A., and Lavik, G.: Coupled physical/biogeochemical modeling including O2-dependent processes in Eastern Boundary Upwelling Systems: Application in the Benguela, Biogeosciences10, 3559–3591, doi:10.5194/bg-10-1-2013, 2013.
  • Holte, J., Straneo, F., Moffat, C., Weller, R., and Farrar, J.T.: Structure and surface properties of eddies in the southeast Pacific Ocean, J. Geophys. Res. Oceans 118, 2295–2309, doi:10.1002/jgrc.20175, 2013.
  • Illig, S., Dewitte, B., Goubanova, K., Cambon, G., Boucharel, J., Monetti, F., Romero, C., Purca, S., and Flores, R.: Forcing mechanisms of intraseasonal SST variability off central Peru in 2000–2008, J.Geophys. Res. Oceans 119, doi:10.1002/2013JC009779, 2014.
  • Kalvelage, T., Lavik, G., Lam, P., Contreras, S., Arteaga, L., Löscher, Oschlies, A., Paulmier, A., Stramma, L., and Kuypers, M.M.M.. Nitrogen cycling driven by organic matter export in the South Pacific oxygen minimum zone. NatureGeoscience 6, 228-234, DOI: 10.1038/NGEO1739, 2013.
  • Kock, A., Arévalo-Martínez, D. L., Löscher, C. R., and Bange, H. W.: Extreme N2O accumulation in the coastal oxygen minimum zone off Peru, Biogeosciences 13, 827-840, doi:10.5194/bg-13-827-2016, 2016.
  • Law, C.S., Brévière, E., De Leeuw, G., Garçon, V., Guieu, C., Kieber, D.J., Kondradowitz, S., Paulmier, A., Quinn, P.K., Saltzman, E., Stefelsk, J., and Von Glasow, R.. Evolving research directions in surface ocean–lower atmosphere (SOLAS) science. Environ. Chem. 2012, http://dx.doi.org/10.1071/EN12159.
  • Monteiro, P.M.S., Dewitte, B., Scranton, M.I., Paulmier, A., van der Pla, A. The role of open ocean boundary forcing on seasonal to decadal-scale variability and long-term change of natural shelf hypoxia. Environmental Research Letters 2011, 6, 18pp, doi:10.1088/1748-9326/6/2/025002.
  • Montes, I., Dewitte, B., Gutknecht, E., Paulmier, A., Dadou, I., Oschlies, A., and Garcon, V.: High-resolution modeling of the Eastern Tropical Pacific oxygen minimum zone: Sensitivity to the tropical oceanic circulation, J. Geophys. Res. Oceans 119, doi:10.1002/2014JC009858, 2014.
  • Morales, C. E., Hormazabal, S. E., and Blanco, J.: Interannual variability in the mesoscale distribution of the depth of the upper boundary of the oxygen minimum layer off northern Chile (18–24S): Implications for the pelagic system and biogeochemical cycling, J. Mar. Res. 57, 909–932, doi:10.1357/002224099321514097, 1999.
  • Paulmier, A., Ruiz-Pino, D., and Garcon, V.: The Oxygen Minimum Zone (OMZ) off Chile as intense source of CO2 and N2O, Contin. Shelf Res. 28, 2746–2756, 2008.
  • Richter, I.,: Climate model biases in the eastern tropical oceans: Causes, impacts and ways forward, Wiley Interdiscip.Rev. Climate Change 6, 345–358, doi:10.1002/wcc.338, 2015.
  • Toniazzo, T.: Climate variability in the south-east Pacific and its relation with ENSO: A GCM study, Climate Dyn. 34,1093–1114, doi:10.1007/s00382-009-0602-z, 2010.
  • Vergara, O., Dewitte, B., Montes, I., Garçon, V., Ramos, M., Paulmier, A., and Pizarro, O.: Seasonal Variability of the Oxygen Minimum Zone off Peru in a high-resolution regional coupled model, Biogeosciences Discuss., doi:10.5194/bg-2015-631, in review, 2016.
  • Wyant,  M.  C.,  Wood,  R.,  Bretherton,  C.  S.,  Mechoso,  C.  R.,Bacmeister, J., Balmaseda, M. A., Barrett, B., Codron, F., Earnshaw,  P.,  Fast,  J.,  Hannay,  C.,  Kaiser,  J.  W.,  Kitagawa,  H.,Klein,  S.  A.,  K ̈ohler,  M.,  Manganello,  J.,  Pan,  H.-L.,  Sun,  F.,Wang, S., and Wang, Y.:  The PreVOCA experiment:  modeling the  lower  troposphere  in  the  Southeast  Pacific,  Atmos.  Chem. Phys. 10, 4757–4774, doi:10.5194/acp-10-4757-2010 , 2010
  • Zheng, Y., Shinoda, T., Kiladis, G.N., Lin, J., Metzger, E.J., Hurlburt, H.E., and Giese, B.S.: Upper-ocean processes under the stratus cloud deck in the Southeast Pacific Ocean, J. Phys. Oceanogr. 40, 103–120, 2010.
banner 2nd transition NL

Marine ecosystem models for ecosystem-based management: has their time arrived?

Artioli, Y.1,*, Cazenave, P. 1, Ciavatta, S. 1,2, Fernandes, J.A. 1, Heard, J. 1, Kay, S. 1, Papathanasopoulou, E. 1, Saux-Picart, S.3, Torres, R. 1, Wakelin, S.4 and Allen, J.I. 1,2

1. Plymouth Marine Laboratory (UK)

2. National Centre for Earth Observation (UK)

3. Meteo France (FR)

4. National Oceanographic Centre (UK)

*Email: yuti@pml.ac.uk

 

Marine and coastal environments are exposed to increasing pressure from human activities and global change. A scientifically sound ecosystem based governance is therefore, required to maintain, and possibly increase, the benefits that marine ecosystems provide to society.

Marine ecosystem models are numerical tools that are able to simulate the dynamics of marine ecosystems under present stressers and different scenarios. They can integrate spatial and temporal gaps of monitoring programs giving the best synoptic picture of the state of the ecosystem. At the same time, models can be used to project responses of the ecosystem to global change, economic drivers and management interventions. This allows managers and policy makers to tailor their strategies to a changing ecosystem, and to test the efficacy of the planned measures before implementation. Because of these abilities,marine ecosystem models are powerful tools capable of implementing an ecosystem-based approach for marine governance. Yet, they are not widely used, for a number of reasons: a lack of confidence in model outputs, the accessibility of model products, or a mismatch between the information needed for governance and those provided by models (Hyder et al. 2015).

Drawing from a series of recent and ongoing projects, we will show how the recent advancements of marine ecosystem models allow us to positively address many of these challenges. 

Historically, assessing the performance of marine ecosystem models has been somewhat qualitative, partly due to the lack of observations, and partly due to the methodology used to validate the models (mostly limited to graphical comparisons). However, in parallel with the exponential increase in available data, techniques for model validation have improved significantly. Building on the burgeoning academic literature, the EU-FP7 OPEC (Operational Ecology: Marine Ecosystem Forecasting) project released a standardised tool that rigorously quantifies the ability of marine ecosystem models to reproduce in situ observations via a suite of statistical metrics (https://github.com/bcdev/opec-tools). This tool enables the production of synthetic diagrams that summarise model skill (Fig. 13). Many other validation methods are available, including some that are able to assess the model skill in relation to temporal and spatial scales (Saux-Picart et al. 2012).

Artioli-Fig 1

Figure 13. Taylor (upper) and Target (lower) diagrams summarising the skill of a decadal simulation of the North Western European Shelf ecosystem. A perfect simulation would sit on the yellow star (adapted from Ciavatta et al, 2016) 

 

Simulation reliability can be enhanced by data assimilation techniques, which merge observations into models to produce the best possible assessment of the ecosystem state. While these methods have been widely applied to physical variables (e.g. temperature and salinity), assimilation of biogeochemical and ecological variables is becoming more common and trustworthy (Ciavatta et al. 2011, Ciavatta et al. 2016).

2. Uncertainty

Marine ecosystem models are affected by uncertainty relating to the model assumptions, the numerical representation of the processes, to unknowns about environmental processes, and human interaction with the marine environment. Although uncertainty has been reduced by the advancements in the marine and social sciences, models will always be affected by some uncertainty (Payne et al. 2015) both for ontological reasons (being a simplification of reality, models are inherently affected by errors) as well as practical ones (e.g. computational constraints forcing the use of simplified solutions). Understanding the level of uncertainty is particularly important when models are used for governance, in order to properly value the projected environmental changes. One way to study and quantify uncertainty is to run (multi-)model ensembles, where slightly different simulations made by the same models (or similar simulations by different models) are used to explore the space of the potential state of the marine ecosystem. With such an approach, the confidence interval of model outcomes can be quantified (Fig. 14).

Artioli-Fig 2

Figure 14. Different degrees of certainty of a model simulation of oxygen deficiency in bottom waters of the North Western European shelf (Ciavatta et al., 2016). 

 

3. Resolution

Due to computational constraints, the spatial and temporal resolution of marine ecosystem models has often been too coarse to be effective in the governance of local-scale problems relevant to society (e.g. a single beach, an aquaculture farm). The exponential increase in power of High Performance Computers has enabled an astonishing increase in the spatial and temporal resolution of models, up to resolving single monopiles of a wind turbine (Cazenave et al. in revision). However, higher resolution often comes at the price of a smaller spatial coverage and shorter temporal length of the model simulations. In the ROSA project (www.rosa-marine.uk), a high resolution model system of the UK coastal seas will be able to provide environmental information to shellfish farmers of individual farms, allowing proactive management of their activity (Fig. 15).

 
Artioli-Fig 3

Figure 15. Example of the high resolution model grid for North Western Scotland (UK) used in ROSA to support the management of single shellfish farms. Elements around the farms have a maximum length of about 200m.

 

4. Communication

Lack of communication between scientific modellers and the governance community has prevented further use of models in the ecosystem based management of marine resources. Without proper guidance from regulators, modellers have built models driven mostly by purely scientific questions or by their interpretation of the regulators’ needs, leading to a mismatch between demand and what the models offer. This mismatch becomes particularly critical when the ecosystem models need to interface with the social and economic aspects of management. Although there is ample evidence to show how marine ecosystem models can be proficiently used to inform socio-economic analysis (Barange et al. 2014, Fernandes et al. 2015, Mullon et al. 2016), these rely on a strong collaboration between modellers, social scientists and managers.

At the same time, ecosystem models and their outputs are kept in the scientific domain, with only a small window of public access (if any), thus preventing wider use of these tools. Recent projects have demonstrated how both can be positively addressed with strong and early involvement of stakeholders, e.g. in ROSA, VECTORS (http://www.marine-vectors.eu/ ) or CMEMS (http://marine.copernicus.eu/) projects, and with the public release of model code (e.g. www.shelfseamodelling.org) or model outcomes ( www.meece-atlas.euhttp://www.meece.eu/kt/fs.htmlhttp://portal.marineopec.eu/ ).

In conclusion, these examples show that marine ecosystem models have reached a stage of maturity that can provide an important contribution to the real-world implementation of marine ecosystem based governance.

 
Artioli-Fig 4

Figure 16. The OPEC data portal showing simulated sea surface temperature in the North Western European Shelf (http://portal.marineopec.eu).

     

References

  • Barange M., Merino G., Blanchard J.L., Scholtens J., Harle J., Allison E.H., Allen J.I., Holt J., Jennings S.. 2014. Impacts of climate change on marine ecosystem production in societies dependent on fisheries. Nature Clim. Change 4: 211-216.
  • Cazenave P.W., Torres R., Allen J.I. in revision. Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas. Progress In Oceanography.
  • Ciavatta S., Kay S., Saux-Picart S., Butenschön M., Allen J.I. 2016. Decadal reanalysis of biogeochemical indicators and fluxes in the North West European shelf-sea ecosystem. Journal of Geophysical Research: Oceans, 121, doi:10.1002/2015JC011496.
  • Ciavatta S., Torres R., Saux-Picart S.,  Allen J.I.. 2011. Can ocean color assimilation improve biogeochemical hindcasts in shelf seas? Journal of Geophysical Research: Oceans 116: C12043. http://dx.doi.org/10.1029/2011JC007219.
  • Fernandes J.A., Kay S., Hossain M.A.R., Ahmed M., Cheung W.W.L., Lazar A.N.,  Barange M.. 2015. Projecting marine fish production and catch potential in Bangladesh in the 21st century under long-term environmental change and management scenarios. ICES Journal of Marine Science: Journal du Conseil.
  • Hyder, K., Rossberg A.G., Allen J.I., Austen M.C., Barciela R.M., Bannister H.J., Blackwell P.G.,. Blanchard J.L, Burrows M.T., Defriez E., Dorrington T., Edwards K P., Garcia-Carreras B., Heath M.R., Hembury D.J., Heymans J.J., Holt J., Houle J.E., Jennings S., Mackinson S., Malcolm S.J., McPike R., Mee L., Mills D.K., Montgomery C., Pearson D., Pinnegar J.K., Pollicino M., Popova E.E., Rae L., Rogers S.I., Speirs D., Spence M.A., Thorpe R., Turner R.K., van der Molen J., Yool A., Paterson D.M. 2015. Making modelling count - increasing the contribution of shelf-seas community and ecosystem models to policy development and management. Marine Policy 61: 291-302.
  • Mullon C., Steinmetz F., Merino G., Fernandes J.A., Cheung W.W.L., Butenschön M., Barange M. 2016. Quantitative pathways for Northeast Atlantic fisheries based on climate, ecological–economic and governance modelling scenarios. Ecological Modelling 320: 273-291.
  • Payne M.R., Barange M., Cheung W.W.L., MacKenzie B.R., Batchelder H.P., Cormon X., Eddy T.D., Fernandes J.A.,. Hollowed A.B, Jones M.C., Link J.S., Neubauer P., Ortiz I., Queirós A.M.,  Paula J.R. 2015. Uncertainties in projecting climate-change impacts in marine ecosystems. ICES Journal of Marine Science: Journal du Conseil.
  • Saux-Picart S., Butenschön M.,  Shutler J.D. 2012. Wavelet-based spatial comparison technique for analysing and evaluating two-dimensional geophysical model fields. Geosciences Model Development 5: 223-230.
banner 2nd transition NL

Operational potential fishing zone prediction for Japanese common squid in the coastal waters of southwestern Hokkaido, Japan

Xun Zhang1,*, Sei-Ichi Saitoh1, 2, Toru Hirawake3, Satoshi Nakada4, Koji Koyamada5, Toshiyuki Awaji6, Yoichi Ishikawa7 and Hiromichi Igarashi7

1. Graduate School of Fisheries Sciences, Hokkaido University, Japan 

2. Arctic Research Center, Hokkaido University, Japan 

3. Faculty of Fisheries Sciences, Hokkaido University, Japan 

4. Faculty of Maritime Sciences, Kobe University, Japan 

5. Center for the Promotion of Excellence in Higher Education, Kyoto University, Japan 

6. Board of Executive Directors, Administration Bureau, Kyoto University, Japan 

7. Japan Agency for Marine-Earth Science and Technology, Japan

*Email: xun@salmon.fish.hokudai.ac.jp

 

The Japanese common squid (Todarodes pacificus) is widely distributed throughout Japanese coastal areas and contributes up to 80% of Japan’s total annual squid landings (Ministry of Agriculture, Forestry and Fisheries, Japan, 2015). The coastal waters of southwestern Hokkaido, are the main feeding grounds of these squid, and are consequently an important fishing area. Because of the heightened sensitivity of the squid to environmental variations the habitat suitability model (HSI) can be used to predict their distribution (Sakurai et al., 2000; Kidokoro et al., 2010; Rosa et al., 2011). 

We developed a forecast system to predict daily potential fishing zones (PFZs) using model-assimilated future environmental data. The spatial resolution of the 4D-VAR dataset was approximately 1.5 km, spanning the area at 40.78°-42.67°N and 139.56°-142.69°E. Environmental parameters such as, u (eastward velocity), v (northward velocity), w (upward velocity), temperature, salinity and Eddy Kinetic Energy (EKE) were used at various depths. The prediction model was based on fishing position data derived from the night-visible images of the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) and Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB). The feasibility of using such images to obtain squid fishing locations had been shown in previous studies (Kiyofuji and Saitoh, 2004; Choi et al., 2008; Zhang et al., 2013), and by-passed the problem of accessing fishing information from local fishers. 

Our daily PFZs predictions matched well with the corresponding night-visible images, suggesting good model quality. However, because this agreement was not reflected in the fish catch information at all fishing positions, it was not possible to confirm the effectiveness of applying our PFZs to real fishing activities. We therefore carried out field surveys to validate the performance of the habitat model. Two-hour long fishing operations were conducted by the R/V Ushio-Maru at sites selected from our daily PFZs maps. When compared with past fishing attempts when the fishing site was selected based on experience, our results suggested that using the PFZs map could prevent low-catch fishing in real fishing activities, especially when these are located near highly frequented fishing zones. More detailed fishing positions were obtained using a ship-borne radar plot system, and most fishing vessels were found to be close to the areas with higher prediction values. However, there was no clear correlation between catch numbers and prediction values across days.

Autumn and winter spawning cohorts of Japanese common squid migrate between the southern spawning grounds and the northern feeding grounds (Sakurai et al., 2000; Kidokoro et al., 2010). The autumn cohort comes from the Japan Sea region and gradually moves through the Tsugaru Strait. The winter cohort arrives from the Pacific region, and then migrates anticlockwise through the Japan Sea, allowing it to grow. Mantle length measurements of catches showed good agreement with the migration patterns of the two spawning cohorts. Our monthly averaged PFZs also demonstrated the general migration patterns of the squid in this area. This consistency with the actual monthly fishing locations underpinned the robustness of our model predictions.

PFZs were frequently located in areas where coastal upwelling occurs in subsurface waters (Fig. 17). From horizontal current field maps (Fig. 18), countercurrents and eddies also showed close relationships with the location of PFZs. Coastal countercurrents can contribute to the upwelling and attract squid assemblages. The anticyclonic eddies distribute nutrients to the eddy boundaries which are closer to the coast (Yoda et al., 2014). In some regions, the water temperature below 200m was outside the range where Japanese common squid can survive, implying that they are more inclined to inhabit the upper layers.

 
 
Zhang-Fig 1

Figure 17. The upward velocity (w) in unit [cm/s] along one of potential fishing zones.

 
Zhang-Fig 2

Figure 18. Current vectors plot of the 50m water (Red circles indicate the high-frequency potential fishing zones).

 

Utilization of maps of PFZs can reduce random fishing and optimise fishing harvest. Since July 2013, four-day prediction maps have been emailed and faxed to the local fishery association and fishermen at a set time each morning, together with other useful information about the ocean environment (see Fig. 19 for an example), to facilitate the selection of fishing positions. PFZ maps can be freely accessed through our web-GIS: http://innova01.fish.hokudai.ac.jp/marinegis

This study illustrates the importance of field surveys to validate habitat suitability models for operational use. We also analyzed the fishing ground information from environmental perspectives and presented ways to promote the development of local fisheries. It is anticipated that with feedback from fishermen, our predictions and understanding of the Japanese common squid can be improved. 

Acknowledgement

This study was supported by “Hakodate Marine Bio Cluster Project” from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan and Japan Aerospace Exploration Agency (JAXA) SGLI/GCOM-C Project. It was also supported by the Sasakawa Scientific Research Grant from the Japan Science Society.

     
Zhang-Fig 3

Figure 19. Daily squid PFZs map and useful environment information sent to local fishermen.

 

References

  • Choi K., Lee C. Il, Hwang K., Kim S.W., Park J.H., Gong Y. 2008. Distribution and migration of Japanese common squid, Todarodes pacificus, in the southwestern part of the East (Japan) Sea. Fish. Res. 91: 281–290. doi:10.1016/j.fishres.2007.12.009
  • Kidokoro H., Goto T., Nagasawa T., Nishida H., Akamine T., Sakurai Y., 2010. Impact of a climate regime shift on the migration of Japanese common squid (Todarodes pacificus) in the Sea of Japan. ICES J. Mar. Sci. 67: 1314–1322. doi:10.1093/icesjms/fsq043
  • Kiyofuji H. & Saitoh S.I., 2004. Use of nighttime visible images to detect Japanese common squid Todarodes pacificus fishing areas and potential migration routes in the Sea of Japan. Mar. Ecol. Prog. Ser. 276: 173–186. doi:10.3354/meps276173
  • Ministry of Agriculture, Forestry and Fisheries, Japan 2015. Annual statistics on the fishery and culture production.
  • Rosa A.L., Yamamoto J., Sakurai Y.,2011. Effects of environmental variability on the spawning areas, catch, and recruitment of the Japanese common squid, Todarodes pacificus (Cephalopoda: Ommastrephidae), from the 1970s to the 2000s. ICES J. Mar. Sci. 68: 1114–1121. doi:10.1093/icesjms/fsr037
  • Sakurai Y., Kiyofuji H., Saitoh S.-I., Goto T., Hiyama Y., 2000. Changes in inferred spawning areas of Todarodes pacificus (Cephalopoda: Ommastrephidae) due to changing environmental conditions. ICES J. Mar. Sci. 57: 24–30. doi:10.1006/jmsc.2000.0667
  • Yoda K., Shiomi K., Sato K. 2014. Foraging spots of streaked shearwaters in relation to ocean surface currents as identified using their drift movements. Prog. Oceanogr. 122: 54–64. doi:10.1016/j.pocean.2013.12.002
  • Zhang X., Saitoh S.-I., Hirawake T., Nakada S., Koyamada K., Awaji T., Ishikawa Y., Igarashi H. 2013. An attempt of dissemination of potential fishing zones prediction map of Japanese common squid in the coastal water, southwestern Hokkaido, Japan. Proc. Asia-Pacific Adv. Netw. 36: 132. doi:10.7125/APAN.36.19
banner 2nd transition NL

Social-ecological regime shifts (SERS): A novel approach to comprehend abrupt changes in coastal-marine systems

Prateep Kumar Nayak and Derek Armitage

Environmental Change and Governance Group (ECGG), Faculty of Environment, University of Waterloo, Canada

Email: pnayak@uwaterloo.ca and derek.armitage@uwaterloo.ca

 

In this article we summarise ongoing research and preliminary insights into social-ecological regime shifts (SERS) as a novel concept to understand unexpected and significant changes in coastal-marine systems. Regime shifts (RS) are abrupt, long-term and significant changes in ecosystem structure and function (Biggs et al. 2009). Such changes are often considered irreversible, and produce complex and uncertain outcomes, with implications for the maintenance of ecosystem services and human wellbeing (MEA 2005; Allison et al. 2009; Nayak and Berkes 2010; Nayak et al. 2015). Understanding and responding to such shifts is a significant challenge for resource users and managers (Walker and Meyers 2004). Efforts to detect and assess RS currently emphasise their ecological or biophysical dimensions (Beaugrand 2004; Karunanithi et al. 2008; Scheffer 2009; Biggs et al. 2009). However, ecological regime shifts are most often catalyzed by anthropogenic or socio-economic drivers (e.g., resource exploitation, contaminant loading, climate change), and tools are urgently required to identify and assess linked social and ecological regime shifts and their outcomes. Despite advances, conceptual development in this area is incomplete (Crepin et al. 2012, Lade et al. 2013, Hughes et al. 2013). Further, understanding of linked social-ecological variables that may signal approaching thresholds and their implications for governance remains poor (Walker and Meyers 2004; Scheffer and Carpenter 2003; Béné et al. 2011). In this context, governance approaches must identify, acknowledge and navigate impending regime shifts before they are crossed, or address the often undesirable consequences of regime shifts once they occur.

Our ongoing research aims to develop and apply a social-ecological system perspective to broaden our understanding of regime shifts, and to consider the implications for management and governance in coastal-marine systems. Nayak et al. (2015) define social-ecological regime shifts (SERS) as abrupt, long-term and significant changes in linked systems of people and nature with uncertain implications for ecosystem services and human wellbeing. A social-ecological perspective emphasises the integrated concept of humans in nature and stresses that delineating between the social and the ecological is artificial and arbitrary (Berkes and Folke 1998). This perspective has important consequences for how we interpret and respond to regime shifts, and craft innovative governance arrangements to that effect. Our current focus is on three objectives: 1) To illustrate key variables of how social and ecological processes, and linkages between the two, to provide a more realistic framework to examine regime shifts; 2) To identify core attributes that require further attention if efforts to anticipate and navigate SERS are to succeed; 3) To compare and synthesise experience with governance processes across study sites undergoing rapid system changes and identify their potential to deal with uncertainty resulting from SERS.

The importance of a social-ecological perspective

Ecosystem RS are difficult to predict (Biggs et al. 2009, Karunanithi et al. 2008). Boerlijst et al. (2013) show that early warning signals in catastrophic regime shifts may be absent, despite suggestions to the contrary (Dakos et al. 2008, Biggs et al. 2009). Hughes et al. (2013) suggest that many RS emerge slowly and imperceptibly, implying that the transition between system states can be easy to miss. While ongoing development of indicators to better anticipate RS provide helpful insights (Carpenter and Brock 2006, van Nes and Scheffer 2007, Dakos et al. 2008), methods to detect RS rely primarily on models that produce quantitative representations of abrupt changes in ecosystems (May 1977, Scheffer and van Nes 2004, Gal and Anderson 2010). Improved understanding of the ecological dimensions of RS provides a foundation for better prediction, but is insufficient as a basis for analysing SERS. Strategies and associated variables are needed to address linked social and biophysical processes that may signal RS. Such strategies are less well-developed (see Béné et al. 2011; Andrachuk and Armitage 2015), and there is considerable scope to better incorporate social theory to address this challenge (Crepin et al. 2012; Lade et al. 2013; Nayak et al. 2015).

Social-ecological systems are influenced by internally and externally imposed drivers operating at multiple scales (MEA 2005). Drivers determine when and how systems become vulnerable. Geist and Lambin (2002) use proximate causes (human activities or immediate actions at local level) and underlying forces (fundamental social processes mainly impacting from national and global levels) to explain the varied nature and functional scales of drivers. A social-ecological perspective of drivers highlights that they are also socially constructed. Different individuals (government manager, resource user) bring different values and subjective interpretations of drivers of change, impacts and their causes which manifest in how SERS might be understood, anticipated and addressed. Differentiating social from ecological drivers will clarify how the drivers causing SERS often act synergistically rather than by single-factor causation (Geist and Lambin 2002).

Greater attention needs to be paid to equity and social justice concerns (i.e., winners and losers) to better anticipate and navigate SERS. Recognising environmental issues through the prism of social justice facilitates the identification of ultimate and proximate drivers of SERS, such as environmental degradation, resource depletion, poverty and marginalisation, and points to equity and justice as both cause and effect of RS (Walker and Bulkeley 2006). SERS can benefit some and adversely impact others. Social power relations expressed through institutions, the position of different actors in society, and the language used to characterize change is crucial to how we understand and respond to SERS (Nayak et al. 2015). Regarding ‘who wins and who loses from SERS’, there remains significant scope to comprehensively articulate the implications of power and politics to anticipate and navigate rapid social-ecological change (see Crepin et al. 2012; Nayak et al. 2015).

Moving from an ecological to social-ecological perspective of RS has implications for assessment and subsequent governance response. Governance is defined here as “the interrelated and increasingly integrated system of formal and informal rules [institutions], rule-making systems, and actor-networks at all levels of human society (from local to global) that are set up to steer societies towards preventing, mitigating, and adapting to global and local environmental change” (Biermann et al. 2009). Governance also reflects the importance of learning and adapting, interactions and linkages, organisational structures and institutions (see Kooiman and Bavinck 2005; Armitage et al. 2007, 2008, 2009) as essential elements in navigating SERS. Current approaches to understanding RS reflect insufficient consideration of the social conditions (poverty, power, institutions) that act as drivers of social-ecological change, and that are also crucial to navigating RS when they occur. Insights from recent methodological innovations to assess system change, e.g., “threshold dashboard” (Bene et al. 2011) and other interdisciplinary approaches (Crepin et al. 2012, Hughes et al. 2013; Andrachuk and Armitage 2015) confirm the need to link an understanding of SERS and their implications to adaptive governance processes. 

 

Attributes of social-ecological regime shifts

Our initial outcomes generated a preliminary list of six SERS attributes (Box 1) and draw attention to the integration of social and ecological dimensions and their mutual feedback in anticipating and navigating regime shifts (Berkes et al. 2003; Ostrom 2009; Crepin et al. 2012, Lade et al. 2013, Hughes et al. 2013; Nayak et al. 2015). A linked social-ecological perspective provides a number of crucial insights and helps to identify core issues that require further attention if these efforts are to succeed. These include: 1) distinguishing underlying versus proximate ecological and social drivers of RS; 2) considering appropriate levels and scales of intervention in linked social-ecological RS; 3) reflecting on social equity and the disproportionate distribution of impacts (and benefits) of SERS; 4) assessing the influence of social power in framing SERS; 5) fostering insights on appropriate units to understand SERS; and 6) critical reflection of the governance implications of SERS. We aim to build on these results to refine the SERS attributes through further synthesis and rigorous case study research in four coastal marine social-ecological systems: 1) Bay of Bengal, India, 2) South China Sea, Vietnam, 3) Gulf of Thailand, Malaysia, and 4) Java Sea, Indonesia, and to translate our findings into enhanced theorisation of SERS and identifying policy and governance implications.

 

Box 1: Six attributes of social-ecological regime shifts

  1. Differentiating drivers of regime shifts
  2. Levels and scales of intervention
  3. Equity and social justice concerns
  4. Power and politics
  5. Social-ecological units
  6. Governance to navigate regime shifts
 

Future Directions

Our research addresses several key knowledge gaps and seeks to contribute to both theory and practice. First, while there has been broad acceptance of the ecological regime shift concept (Biggs et al. 2009, Crepin et al. 2012), concepts and metrics are far less developed with regard to understanding RS in a social-ecological context. This research enhances the development of empirically generated variables and indicators to understand SERS in ways that draw on and contribute to both ecological and social theories on change and sustainability. Recognising the value of interactions among multiple variables within the SES (as opposed to ecosystem only) make it possible to comprehensively study and address RS as opposed to developing a compartmentalized understanding of social-ecological change (Nayak et al. 2015).

Second, focusing on socially and culturally relevant RS, in addition to ecologically defined RS, is a necessary innovation that will provide a novel, participatory and integrative way to understand SERS. Such an applied understanding is critical to help steer social-ecological systems towards sustainability either by avoiding critical thresholds or purposefully crossing them to navigate away from undesirable states (Carpenter 2003; Armitage and Plummer 2010).

Third, this research will enhance understanding of system thresholds and possible SERS, which is highly relevant as attempts to analyse thresholds have been hampered by a lack of empirical data (Walker and Meyers 2004). Moreover, rapid and abrupt changes in many coastal marine systems highlight the urgent need for time-sensitive data to better understand how interactions between human wellbeing and ecosystem services are related to SERS. Recognition of this important link between human development and rapid and unexpected shifts in biophysical conditions (Hicks et al., 2014) rarely features in the design and implementation of coastal marine management interventions.

Finally, this research aims to link theory to practice and public policy by developing implementation and assessment tools (e.g., best practice guidelines, methodological tools that employ visual outputs) for use by practitioners, managers and policy makers (e.g., Fisher Federations/Networks and Provincial/National Departments on Fishery/Coastal Development/Marine on fisheries management and coastal planning; UN Food and Agriculture Organisation on the implementation of 2015 Small-Scale Fisheries Guidelines). This is consistent with initiatives developing diagnostic tools for governance and sustainability of complex SES (Ostrom 2007; Pahl-Wostl 2009: Evans and Andrew 2011; Béné et al. 2011). This research will generate evidence-based lessons and best practices for governance of linked coastal-marine systems experiencing rapid change, while also increasing the literature on environmental governance to achieve patterns of development that promote human well-being while conserving the life support systems of the planet (MEA 2005; Levin and Clark 2010).

There is no governance blueprint to help societies anticipate and/or navigate regime shifts. However, framing efforts to understand and respond to regime shifts will benefit from the use of a social-ecological perspective as outlined here. Progress in responding to regime shifts can be made where there is a commitment to invest in management and governance approaches that reflect an openness to multiple types and sources of knowledge, an effort to foster multi-level linkages and networks, and strategies to build capacity for institutional adaptation and flexibility in the context of change and uncertainty. Such approaches are more likely to reflect the multi-dimensionality of social-ecological regime shifts, the invariably contested nature of understanding those shifts, and the scale-specific manner in which they must be considered. 

     

References

  • Allison E., Perry A.L., Badjeck M.C., Adger W.N., Brown K., Conway D., Halls A.S., Pilling G.M., Reynolds J.D., Andrew N.L., Dulvy N.K. 2009. Vulnerability of national economies to the impacts of climate change on fisheries. Fish and Fisheries 10(2): 173-196.
  • Andrachuk M. and Armitage D. 2015. Understanding social-ecological change and transformation through community perceptions of system identity. Ecology and Society 20(4): 26. http://dx.doi.org/10.5751/ES-07759-200426
  • Armitage D. and Plummer R., Eds. 2010. Adaptive Capacity and Environmental Governance. Springer. DOI: 10.1007/978-3-642-12194-4
  • Armitage D., Marschke M., Plummer R. 2008. Adaptive Co-Management and the Paradox of Learning. Global Environmental Change. 18(1): 86-98.
  • Armitage D., Berkes F., Doubleday N.C., Eds. 2007. Adaptive Co-Management: Collaboration, Learning and Multi-Level Governance. Vancouver: UBC Press.
  • Beaugrand G. 2004. The North Sea regime shift: Evidence, causes, mechanisms and consequences. Progress in Oceanography 60: 245-262.
  • Béné et al. 2011. Testing resilience thinking in a poverty context: Experience from the Niger River basin. Global Environmental Change 21: 1173-1184.
  • Berkes F. and Folke. C, Eds. 1998. Linking Social and Ecological Systems: Management Practices and Social Mechanisms for Building Resilience. Cambridge University Press.
  • Berkes, F., Colding J. and Folke C. (Eds.). 2003. Navigating Social-Ecological Systems: Building Resilience for Complexity and Change. Cambridge: Cambridge University Press.
  • Biggs R., Carpenter S.R., Brock W.A. 2009. Turning back from the brink: Detecting an impending regime shift in time to avert it. Proceedings of the National Academy of Science. 106: 826-831.
  • Biermann et al. 2009. Earth system governance: People, places and the planet. Science and Implementation Plan of the Earth System Governance Project, The Earth System Governance Project. SG Report No. 1.
  • Boerlijst M.C., Oudman T., de Roos A.M. 2013. Catastrophic collapse can occur without early warning: Examples of silent catastrophes in structured ecological models. PLoS ONE 8: e62033. doi:10.1371/journal.pone.0062033
  • Carpenter S.R. 2003. Regime shifts in lake ecosystems: Pattern and variation. Excellence in Ecology Series Number 15. Ecology Institute, Oldendorf/Luhe, Germany.
  • Carpenter S.R. and Brock W.A. 2006. Rising variance: A leading indicator of ecological transition. Ecological Letters 9: 311-318.
  • Crépin A.S., Biggs R., Polasky S, Troell M., Zeeuw A.D. 2012. Regime shifts and management. Ecological Economics 84: 15-22.
  • Dakos V., et al. 2008. Slowing down as an early warning signal for abrupt climate change. Proceedings of the National Academy of Science 105: 14308-14312.
  • Evans L. and Andrew N.L. 2011. Diagnosis and the management constituency of small-scale fisheries. In: N. Andrew and R. Pomeroy, (Eds.). Small-scale Fisheries Management Frameworks and Approaches for the Developing World. Wallingford: CABI Publishing.
  • Gal G. and Anderson W. 2010. A novel approach to detecting a regime shift in a lake ecosystem. Methods in Ecology and Evolution 1: 45–52.
  • Geist H.J., Lambin E.F. 2002. Proximate causes and underlying driving forces of tropical deforestation. BioScience 52: 143–150.
  • Hicks C.C., Graham N.A.J., Cinner J. 2014. Bundles and tradeoffs among managers, scientists, and fishers in their valuation of coral reef ecosystem services. Global Environmental Change. 23(6): 1444-1453.
  • Hughes T.P., Linares C., Dakos V., van de Leemput I.A., van Nes E.H. 2013. Living dangerously on borrowed time during slow, unrecognized regime shifts. Trends in Ecology and Evolution 28: 149-155.
  • Karunanithi A.T., Cabezas H., Frieden B.R., Pawlowski C.W. 2008. Detection and assessment of ecosystem regime shifts from fisher information. Ecology and Society 13: 22. [Online] URL:http://www.ecologyandsociety.org/vol13/iss1/art22/.
  • Kooiman J. and Bavinck M. 2005. The governance perspective. In: J. Kooiman, M. Bavinck, S. Jentoft and R. Pullin (eds). Fish for Life: Interactive Governance for Fisheries. Amsterdam: Amsterdam University Press, pp. 11-24.
  • Lade S.J,. Tavoni A., Levin S.A., Schlüter M. 2013. Regime shifts in a social-ecological system. Theoretical Ecology. 6: 359-372.
  • Levin S.A. and Clark W.C., Eds. 2010. Toward a Science of Sustainability: Report from Toward a Science of Sustainability Conference, Airlie Center, Warrenton, Virginia, November 29, 2009 – December 2, 2009. CID Working Paper No. 196. Center for International Development at Harvard University.
  • May R.M. 1977. Thresholds and breakpoints in ecosystems with a multiplicity of stable states. Nature 269: 471-477.
  • MEA (Millennium Ecosystem Assessment). 2005. Ecosystems and human well-being: General synthesis. In: Millennium Ecosystem Assessment. Chicago, IL, USA: Island Press. Online at: http://www.Millenniumassessment.org/en/Synthesis.aspx  
  • Nayak P.K., Armitage D. Andrachuk M. 2015. Power and politics of social–ecological regime shifts in the Chilika lagoon, India and Tam Giang lagoon, Vietnam. Regional Environmental Change Online First: DOI 10.1007/s10113-015-0775-4
  • Nayak P K. and Berkes F. 2010. Whose marginalisation? Politics around environmental injustices in India’s Chilika Lagoon. Local Environment 15 (6): 553–567
  • Ostrom E. 2009. A general framework for analyzing sustainability of social-ecological systems. Science 325: 419-422.
  • Ostrom E. 2007. A diagnostic approach for going beyond panaceas. Proceedings of the National Academy of Science 104 (39): 15181-15187.
  • Pahl-Wostl C. 2009. A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance regimes. Global Environmental Change 19(3): 354-365.
  • Scheffer M. 2009. Critical Transitions in Nature and Society. Princeton University Press.
  • Scheffer M. and Carpenter S.R. 2003. Catastrophic regime shifts in ecosystems: linking theory to observation. Trends in Ecology and Evolution 18: 648-656.
  • Scheffer M and van Nes E.H. 2004. Mechanisms for marine regime shifts: Can we use lakes as microcosms for oceans? Progress in Oceanography 60: 303-319.
  • van Nes E.H. and Scheffer M. 2007. Slow recovery from perturbations as a generic indicator of a nearby catastrophic shift. American Naturalist 169:738-747.
  • Walker G. and Bulkeley H. 2006. Geographies of environmental justice. Geoforum 37: 655-659.
  • Walker B.and Meyers J.A. 2004. Thresholds in ecological and social–ecological systems: A developing database. Ecology and Society 9: 3. [Online] URL: http://www.ecologyandsociety.org/vol9/iss2/art3/
banner 2nd transition NL

Identifying the “driver species” of an ecosystem

Fernando Cagua

Centre for Integrative Ecology – School of Biological Sciences – University of Canterbury, New Zealand

Email: fernando@cagua.co

 

Changes in the abundance of a species in an ecological community can cause changes in many other species, not only those that it interacts with directly, but also species with which it is indirectly connected. However, species are not all the same in this regard. Some are able to drive dramatic changes in their communities. For example, a reduction in the number of sea otters can precipitate reductions in kelp density because sea urchins, which graze on the kelp, are released from predation (Payne 1995; Estes 1978). Keystone species, such as the sea otter, are not just important from an ecological and evolutionary point of view: identifying them is also crucial for conservation and restoration because management actions targeted toward these species are more likely to effectively cascade the desired effects through the community.

Often, the “keystoneness” of a species is assessed using empirical observations of long term dynamics in well-studied systems or carefully planned manipulation experiments. However, this can be challenging in under-studied or highly diverse systems, or where the keystone role is shared by several species. Alternative approaches attempt to predict the role of a species by considering their position in the food web or in mass-balance models of functional groups. Unfortunately, these approaches are conceptually limited to trophic interactions and in general ignore the structural mechanisms that determine the spread of perturbations (or abundance changes) in ecosystems.

Dr. Daniel Stouffer—my PhD supervisor—and I propose to build on lessons learned from the control of complex systems to help understand and ultimately steer ecosystem dynamics. Although control theory is mostly applied in physics and engineering, it is a useful tool that copes well with the multiple feedbacks found in ecological networks. When ecosystems are considered as dynamic systems whose state is determined by the abundances of its constituent species, control theory can help identify the driver species in the community (Liu 2011), the factors that make some communities more or less difficult to manage, and ultimately indicate the way to effective, rather than hopeful, conservation and restoration interventions (Cornelius & Motter 2013).

To date, we have explored this idea using previously published plant-pollinator communities, some of which have been taken over by a dominant invasive plant (Bartomeus 2008; Fig. 20). It became apparent that we would have to design directed interventions for 60 to 80% of the species to fully control the abundances of all the species in the community. Interestingly, this proportion was independent of whether communities have been taken over by an invasive plant or not. On the surface, this result might be discouraging as such levels of management are not currently feasible from both a practical and an economic point of view. However, as the goal is often not to control the abundances of all species, but rather only a small subset, for example an invasive species or those that provide habitat or an important ecosystem service.

The next step—examining the relative importance of species as drivers—allowed us to determine the factors that make a species more or less useful for targeted interventions. We found that measures of centrality or influence, which have been previously used on complex systems to quantify the “keystoneness” of species (Jordán 2009; Estrada 2007), are actually poor predictors of their importance as ecosystem drivers. Instead, driver species tend to be those that interact with a relatively large number of species and those interacting species are collectively more dependant on the driver species than the other way around. 

 

Remarkably, invasive species were classified as drivers in every single community where they were present. This is noteworthy because it highlights the ability that invasive species have to transform the structure of ecological communities and the abundances of other species in the ecosystem. However, it is also encouraging because it suggests that, despite inconsistent outcomes, current restoration approaches that focus on direct eradication of the invasive species might not be too far off the mark.

 
Cagua-Fig 1

Figure 20. Driver species (red circle) wield a disproportionate effect on the abundances of other species. In theory, it should be possible to control the population dynamics of a whole community by managing the abundances of just this subset of species (red arrows). Applying tools developed to identify them should thus allow us to design targeted interventions to stabilise desirable ecosystems or modify undesirable ones.

 

We plan to investigate further how we can use control theory to guide the complex problems faced in conservation and restoration projects. For instance, a restoration project that aims to recover an ecosystem that has been transformed by an invasive species might be successful at eliminating the invader. However, getting rid of the invader does not guarantee that the ecosystem will return to close to its pre-disturbance state. This implies that important ecosystem services could potentially still be degraded or compromised. Our approach might be useful to identify the interventions that directly or indirectly benefit the service providers and indicate whether this includes interventions on the invasive species or not. Though our initial exploration relates to a terrestrial community, the tools and approach we are working on can be extended to marine and microbial communities.

     

References

  • Bartomeus I., Vilà M. & Santamaría L. 2008. Contrasting effects of invasive plants in plant-pollinator networks. Oecologia 155: 761–770.
  • Cornelius S.P. & Motter A.E. 2013. NECO - A scalable algorithm for NEtwork COntrol. Protoc. Exch. 1–6. doi:10.1038/protex.2013.063
  • Estes J., Smith N. & Palmisano J. 1978. Sea otter predation and community organization in the western Aleutian Islands, Alaska. Ecology 59: 822–833.
  • Estrada E. 2007. Characterization of topological keystone species. Local, global and ‘meso-scale’ centralities in food webs. Ecol. Complex. 4: 48–57.
  • Jordán F. 2009. Keystone species and food webs. Philisophical Trans. R. Soc. B 364: 1733–1741.
  • Liu, Y.-Y., Slotine, J.-J. & Barabási, A.-L. 2011. Controllability of complex networks. Nature 473: 167–173.
  • Paine R.A. 1995. Conversation on refinining the concept of keystone species. Conservation Biology 9: 962–964. 
banner 2nd transition NL

Global environmental change and implications for regime shifts: synergistic effect of multiple stressors

Beatriz E. Casareto

Graduate School of Science and Technology and Research Institute of Green Science and Technology, Shizuoka University, Japan

Email: dcbeatr@ipc.shizuoka.ac.jp, casaretobe@gmail.com

 

IMBIZO IV, held in Trieste, Italy in October 2015 dealt with the linkages between marine and human systems. Two key concepts were considered: multiple scales and multiple stressors. Four workshops ran concurrently during the IMBIZO, and I presented my research on coral reef ecosystems in the Regime shift to novel systems workshop. There were extensive discussions on the concepts of regime shifts, based on examples from different ecosystems presented by the workshop participants, including the socio-economic implications of regime shifts to newly stable states (novel ecosystems). The possibility of ecosystems that have experienced regime shifts reverting to their original states, as well as humans responding by accepting “novel ecosystems” was explored by evaluating the social-ecological consequences of different management strategies for these novel ecosystems.

Although understanding marine regime shifts is challenging for researchers, it is widely accepted that appropriate ecosystem management is essential to avoid undesirable changes in pristine ecosystems and the loss of ecosystem services available to humans. Although the prevalence of top-down trophic, or bottom-up physical drivers causing regime shifts have been investigated, until recently, the drivers, mechanisms and characteristics of abrupt changes in marine ecosystems were not well understood. Moreover, the multiple stressors acting on ecosystems and their synergistic interactions may greatly contribute to the understanding of regime shifts mechanisms (Conversi et al., 2015).

Global environmental changes are occurring more rapidly now than at any other time in the past. The combined effects of natural and anthropogenic disturbances are significantly impacting marine ecosystems, often resulting in regime shifts (open ocean systems) and face shifts (coastal ecosystems). Over the past three decades, many Caribbean coral reef ecosystems have undergone profound phase shifts in community composition from coral to macroalgal dominance (Bozeck and Munby, 2015). Most phase shifts experienced in coral reefs result from the combination of environmental changes, such as global warming, and anthropogenic pressures (Fig. 21). Other reasons cited for such phase shifts include overfishing, excessive nutrient inputs, predation by the Crown-of-thorns starfish (Acanthaster plancii), and the loss of major functional groups like fish and echinoid grazers (Work et al., 2008).

Coral bleaching is the most important process affecting coral survival. Bleaching has been reported from all around the globe, and it is understood that under stress, such as elevated temperature, light or nutrients, the corals expel the symbiotic algae (zooanthellae) living in their tissues, thus causing them to become white. However, the “coral holobiont” (the coral in symbiosis with its zooxanthellae and the microbial community that maintains the delicate balance to keep the coral healthy) is extremely complex . At IMBIZO IV, I presented a novel point of view of the bleaching mechanism based on studies performed at micro/nano size scales. These revealed that bleaching is not the result of expelling zooxanthellae to the surrounding waters, but that it results from degradation of damaged zooxanthellae inside coral tissues (Suzuki et al. 2015). Moreover, detailed examination of the composition of the pigments of the damaged zooxanthellae, showed the presence of a newly described pigment, cPPB-aE (cyclo-enol), which results from the degradation of Chl a in damage zooxanthellae. The pigment is non-fluorescent and therefore it does not promote the formation of reactive oxygen species (ROS). Since ROS are very toxic, corals under thermal stress degrade their zooxanthellae with a concomitant degradation of Chl a into cyclo-enol to fight against oxidative stress. Therefore, we concluded that bleaching is an adaptive mechanism by the coral to avoid oxidative damage under thermal stress. As cyclo-enol is only found in abnormal zooxanthellae, its presence may be useful as an indicator of thermal stress in corals that have not yet reached the stage of visible bleaching. Monitoring cyclo-enol could therefore facilitate prediction of bleaching and promote the study of coral responses to environmental changes.

 

However, bleaching is not only caused by thermal stress; it can be accelerated and exacerbated by other environmental and biological factors acting in combination or in synergy. We tested two hypotheses:

Hypothesis 1) pathogenic bacteria in the water surrounding the corals, acting in synergy with elevated sea-surface temperature (32°C vs. 27°C in our study) can accelerate bleaching;

Hypothesis 2) nutrients inputs (5 µm of nitrate vs. < 1µm in our study) in the surrounding waters will act in synergy with elevated sea-surface temperature causing bleaching and impelling coral recovery after a recovery period (cessation of the stressful conditions).

Both hypotheses were tested in laboratory incubation experiments under controlled conditions of temperature, illumination, with the addition of selected pathogenic bacteria for hypothesis 1 or high concentrations of nitrate for the hypothesis 2.

Hypothesis 1 was tested using the coral Montipora digitata and five bacterial species (Vibrio coralliilyticusV. harveyiParacoccus carotinifaciens,Pseudoalteromonas sp., and Sulfitobacter sp.) previously isolated from corals in the surrounding water (Casareto et al., in press). Bacterial challenges under high-temperature stress resulted in coral bleaching, with 70% decrease in zooxanthellae density compared to the control, 25% decrease in photosynthetic efficiency (Fv/Fm), 66% decrease in photosynthesis, and 101% reduction in calcification. Tissue necrosis was observed in the most of the compromised coral branches. Of the bacteria examined, Sulfitobacter sp. had the greatest capacity to enhance and accelerate the bleaching process under thermal stress. However, addition of bacteria at normal temperature did not promote bleaching, and high temperature stress without the addition of any bacteria) promoted partial bleaching. The combine stresses showed a synergistic effect on the corals resulting in bleaching, and in some cases tissue lyses and even death.

Hypothesis 2 was tested using four corals: Porites cylindrica and Galaxea fascicularis for thermal resistance, and Pocillopora damicornis and Acropora formosa as thermal vulnerable corals (Chumun 2014). Treatments were applied over three days, followed by three days of recovery (reverting to the normal conditions of the corals). Results showed that high levels of nitrogen alone did not have any effect on the corals; high temperature effected the two thermal sensitive corals, taking them to the bleaching threshold of a maximum quantum yield (Fv/Fm) of about 0.4. They reverted to the normalFv/Fm after the recovery period. However under a combined treatment of high temperature and high nitrate, all branches of A. formosa died within two days of treatment, and branches of P. damicornis died after the first day of the recovery period. This shows that the combined effects of these two factors can aggravate and accelerate the bleaching process. Results suggest that human impacts on shallow reefs through the introdution of high amount of nutrients by run off or sewage inputs may promotephase shifts in these environments.

Overall, these studies show that multiple stressors acting in combination can greatly affect ecosystems through their synergistic action and may promote unexpected and rapid changes such as phase shifts. The results also indicate that most of the anthropogenic disturbances that cause rapid changes in shallow coral reefs could be avoided if good management policies are implemented. Finally, to reach a greater understanding of the effects of multiple stressors, studies at different scales (from geographical to micro-nano and molecular) need to be undertaken.

     
Casereto-Fig 1

Figure 21. Effects of natural and anthropogenic multiple stressors on coral reefs resulting in face shits

 

References

  • Bozec Y.-M., Mumby P.J. 2015. Synergistic impacts of global warming on the resilience of coral reefs. Phil. Trans. R. Soc. B 370: 20130267. http://dx.doi.org/10.1098/rstb.2013.0267
  • Casareto B.E., Suzuki T., Suzuki Y. 2016. In Kayanne H (eds.): Coral reef science; Strategy for ecosystem symbiosis and coexistence with humans under multiple stresses. Chapter 2 Chemical-Biological Characteristics of Coral Reef Ecosystem at Micro/Nano Scale: Effect of Multiple and Synergistic Stresses. Springer, Japan. In press.
  • Conversi A. et al. 2015. A holistic view of marine regime shifts. Phil. Trans. R. Soc. B 370: 20130279. http://dx.doi.org/10.1098/rstb.2013.0279.
  • Chumun P.K. 2014. Response to coral symbiont complex to high nitrate levels and thermal stress. PhD thesis. Department of Environment and Energy systems, Graduate School of Science and Technology, Shizuoka University. 102 pp.
  • Suzuki T., Casareto B.E., Shioi Y., Ishikawa Y., Suzuki Y. 2015. Finding of 132, 173-cyclopheophorbide a enol as a degradation product of chlorophyll in shrunk zooxanthellae of the coral Montipora digitata. Journal of Phycology 51: 37–45 doi: 10.1111/jpy.12253.
  • Work T.M., Aeby G.S., Maragos J.E. 2008. Phase shift from a coral to a corallimorph-dominated reef associated with a shipwreck on Palmyra Atoll. PLoS ONE 3(8): e2989. doi:10.1371/journal.pone.0002989.
banner transition NL

JEAI EMACEP team: Quantitative ecology in the Peruvian upwelling system

Tam, J.1,6,*, R. Joo1,4, E. Ocaña2,5, A. Aguirre1,3, A. Alegre1,7, D. Grados10,5, D. Gutiérrez1,6 and J. Ramos1,8 and A. Bertrand9,8

1. Instituto del Mar del Perú (IMARPE), Perú.

2. Instituto de Matemáticas y Ciencias Afines (IMCA), Perú

3. Universidad Nacional Agraria La Molina (UNALM), Perú

4. Pontificia Universidad Católica del Perú (PUCP), Perú

5. Universidad Nacional de Ingeniería (UNI), Perú               

6. Universidad Peruana Cayetano Heredia (UPCH), Perú

7. Universidad Científica del Sur (UCS), Perú

8. Universidad Nacional Mayor de San Marcos (UNMSM), Perú

9. Institut de Recherche pour le Développement (IRD), France

10. IMARPE-PRODUCE-IDB Project, Perú

*Email: jtam@imarpe.gob.pe

 

The Peruvian upwelling system is highly variable in both space and time. It supports the world largest single species fishery and provides employment for both industrial and artisanal fishers. Despite intense research and monitoring by the Peruvian Marine Research Institute (IMARPE) over the past 50 years, there are still gaps in our knowledge about many ecosystem processes. This is due mainly to the limited number of scientists with quantitative ecological knowledge who are able to work on disentangling the complex processes occurring at different scales under climate change and increasing harvesting pressure. It is thus crucial to improve the training of researchers in the use of quantitative ecological tools and to establish teams capable of analysing the abundant information using complex models, in order to provide accurate and timely advice for decision makers.

The Institut de Recherche pour le Développement (IRD, France) provided support to establish a JEAI (Jeunes équipes associées à l'IRD) team, known as EMACEP (Ecología Marina Cuantitativa del Ecosistema de Afloramiento Peruano. This comprises mathematicians, statisticians and economists, as well as biologists and fisheries engineers, and aims to increase quantitative marine ecology skills in the region. The success of this JEAI is due to  the multidisciplinarity of the team, and the on-going collaboration between IMARPE and IRD since 2002. This was strengthened with the launch of the International Joint Laboratory 'Dynamics of the Humboldt Current System' (LMI DISCOH) in 2010, which has produced outstanding results (Gutierrez et al. 2011, Bertrand et al. 2014).

The research team has 15 permanent members: nine with PhDs (from the IMARPE, the Instituto de Matemática y Ciencias Afines (IMCA), Pontificia Universidad Católica del Perú (PUCP), and Universidad Nacional Agraria La Molina (UNALM)). The team is also fostering three Peruvian PhD students in France, and three Peruvian MSc students based at the Universidad Peruana Cayetano Heredia (UPCH) and the Universidad Nacional Mayor de San Marcos (UNMSM).

The JEAI EMACEP was officially launched at IMARPE on 21 April  2014 (Fig. 22). It focuses on fisheries ecology, oceanography, bioenergetics and ecosystem modelling. Activities are organised around four specific objectives (Fig. 23):

- To use mathematical and statistical tools for the spatial analysis of georeferenced data such as vessel monitoring systems, acoustics, and satellite data (Joo et al. 2013, 2014, 2015; Alegre et al., 2015; Gradoset al. 2016);

- To improve existing bioenergetics, population dynamics and stock assessment models to include environmental variables and uncertainty (Pecquerie et al. 2009, Díaz et al. 2010, Oliveros et al. 2010); 

- Application of physical, biogeochemical and biological models at different spatial scales (Tam et al. 2008; Brochier et al. 2013) to study early and adult stages of the main species (anchovy, scallop, jumbo squid, etc.);

- To develop bio-economic and socio-ecological models to support fisheries management (Ocaña et al. 2011, De Lara et al. 2012). 

 
JEAI EMACEP-Fig 1

Figure 22. Inaugural meeting of the JEAI EMACEP at the Instituto del Mar del Perú (IMARPE). From left to right: Jorge Ramos, Erick Chacón, Enrique Ramos, Abelardo Jordán, Edgar Meza, Vilma Romero, Pepe Espinoza, Eladio Ocaña, Dante Espinoza, Arnaud Bertrand, Avy Bernales, Carmela Nakazaki, Katia Aronés, Patricia Ayón, Rocío Joo, César Fernández, Jorge Tam, Federico Velazco, Cynthia Arellano, Adolfo Chamorro, Josué Díaz, Roberto Quesquén, David Castillo, David Correa, Wilbert Marín, Max Collao.

 
JEAI EMACEP-Fig 2

Figure 23. Specific objectives of JEAI EMACEP.

 

Training of the JEAI EMACEP is undertaken through a variety of courses, e.g. Dynamic energy budget (Dr. Laure Pecquerie, IRD), Methods of multivariate analyses (Dr. Sergio Camiz, Sapienza Università di Roma), Basic geostatistics and time series analysis using R (Dr. Rocío Joo and Dr. Daniel Grados, IMARPE). A “Cycle of Conferences on Quantitative Marine Ecology” was convened on 26 February 2016 at IMARPE with 76 participants. Oral presentations covered investigations of statistical analyses of El Niño, scallop larval transport, zooplankton biomass estimations, Silverside morphometric stock identification, epipelagic biodiversity, seabird foraging behaviour, artisanal fishing grounds, classification of anchovy fishery operations, classification of jack mackerel trips and proxies of anchovy biomass.

The JEAI EMACEP is an excellent opportunity for capacity building and to promote multidisciplinary quantitative marine ecological research to address this highly variable and complex upwelling ecosystem. It serves as a natural laboratory to test important hypotheses towards the sustainable development of socio-ecological fisheries communities (Fig. 24). More details about the team are available on the JEAI EMACEP website (in Spanish):
http://www.imarpe.pe/imarpe/index.php?id_seccion=I0170040302020100000000.

     
JEAI EMACEP-Fig 3

Figure 24. Activities of JEAI EMACEP (field surveys, lab analyses, trainings and discussions meetings).

 

References

  • Alegre A., Bertrand A., Espino M., Espinoza P., Dioses T., Ñiquen M., Navarro I., Simier M., Ménard F. 2015. Diet diversity of jack and chub mackerels and ecosystem changes in the northern Humboldt Current system: a long-term study. Progress in Oceanography, 137: 299–313.
  • Bertrand A., Grados D., Colas F., Bertrand S., Capet X., Chaigneau A., Vargas G., Mousseigne A., Fablet R. 2014. Broad impacts of fine-scale dynamics on seascape structure from zooplankton to seabirds. Nature Communications, 5: 5239.  
  • Brochier T., Echevin V., Tam J., Chaigneau A., Goubanova K., Bertrand A. 2013. Climate change scenarios experiments predict a future reduction in small pelagic fish recruitment in the Humboldt Current system. Global Change Biology. 19: 1841–1853.
  • De Lara M., Ocaña E., Oliveros-Ramos R., Tam J. 2012. Ecosystem Viable Yields. Environ. Model. Assess. 17:565-575.
  • Díaz, E., García C., Espinoza D., Guevara-Carrasco R., Csirke J., Ñiquen M., Vargas N., Argüelles J. 2010. Evaluación del stock norte – centro de la anchoveta peruana (Engraulis ringens Jenyns) por un modelo estadístico estructurado por edades. Bol. Inst. Mar Perú. 25(1 y 2):57-61.
  • Grados D., Bertrand A., Colas F., Echevin V., Chaigneau A., Gutiérrez D., Vargas G., Fablet R. 2016. Spatial and seasonal patterns of fine-scale to mesoscale upper ocean dynamics in an eastern Boundary Current system. Progress in Oceanography, 142: 105–116.
  • Gutiérrez, D., Bouloubassi, I., Sifeddine, A., Purca, S., Goubanova, K., Graco, M., Field, D., Méjanelle, L., Velazco, F., Lorre, A., Salvatteci, R., Quispe, D., Vargas, G., Dewitte, B. Ortlieb, L. 2011. Coastal cooling and increased productivity in the main upwelling zone off Peru since the mid-twentieth century. Geophysical Research Letters, 38:L07603.
  • Joo, R., Bertrand S., Tam J., Fablet R. 2013. Hidden Markov Models: The Best Models for Forager Movements? Plos One. 8:e71246.
  • Joo R., Bertrand A., Bouchon M., Segura M., Chaigneau A., Demarcq H., Tam J., Simier M., Gutierrez M., Gutierrez D., Fablet R., Bertrand S. 2014. Ecosystem scenarios shape fishermen spatial behavior. The case of the Peruvian anchovy fishery in the Northern Humboldt Current system. Progress in Oceanography, 128: 60-73.
  • Joo R., Salcedo O., Gutierrez M., Fablet R., Bertrand S. 2015. Defining fishing spatial strategies from VMS data: Insights from the world's largest monospecific fishery. Fisheries Research, 164: 223-230.
  • Ocaña,E., Cartigny P., Loisel P. 2009.   Singular infinite horizon calculus of variations. Applications to fisheries management. Journal of Nonlinear and Convex Analysis. 10(2): 157-176.
  • Oliveros-Ramos, R., Guevara-Carrasco R., Simmonds J., Csirke J., Gerlotto F., Castillo R., Tam J. 2010. Modelo de evaluación integrada del stock norte-centro de la anchoveta peruana Engraulis ringens Jenyns. Bol. Inst. Mar Perú, 25(1 y 2): 49-55.
  • Pecquerie, L., Petitgas P., Kooijman S.A.L.M.. 2009. Modeling fish growth and reproduction in the context of the Dynamic Energy Budget theory to predict environmental impact on anchovy spawning duration. Journal of Sea Research. 62(2-3): 93-105.
  • Tam, J., Taylor M.H., Blaskovic V., Espinoza P., Ballón R.M., Díaz E., Wosnitza-Mendo C., Argüelles J., Purca S., Ayón P., Quipuzcoa L., Gutiérrez D., Goya E., Ochoa N., Wolff M. 2008. Trophic modeling of the Northern Humboldt Current Ecosystem, Part I: Comparing trophic linkages under La Niña and El Niño conditions. Progress in Oceanogr. 79: 352-365.
banner transition NL

Interpreting COP21 outcomes: how to make it happen

Andrew Lenton, Alistair Hobday, John Church, Steve Rintoul and Peter R. Oke

CSIRO, Australia

 

The recent climate deal in Paris (COP21) challenges the world to keep warming to below 2°C with an aspirational target of 1.5°C; replacing the Kyoto Protocols when they expire in 2020. While this represents a major leap forward there still remains a great deal of work to do from all parts of society to ensure this is implemented including scientists, policy makers and wider public. In particular it raises a number of important issues and challenges around carbon sinks and sources, climate impacts, adaptation, mitigation and climate intervention.

Even a minimum 1.5°C warming will result in a significant commitment to longer-term climate change, particular in areas such as sea level rise (Figure 25; IPCC 2013) and ocean acidification. Beyond this increase in mean warming, it will be associated with an increase in variability or extremes from year to year and decade to decade. At present there is a lot of work needed, by the scientific community to inform decision and policy making, as well as underpinning research to monitor and understand the processes driving this variability, and to develop climate projections for multiyear to multidecadal timescales. Climate projections provide a means to build resilience and aid in adapting to a changing world. For example multiyear projections provide a way to quantify the likelihood of extremes such as drought and floods, and extreme hot years. Globally and regionally, climate-sensitive sectors that would benefit would include marine, fisheries, agriculture, energy, water sectors, tourism, coastal and of course sustainable development. The incorporation of forecast information into planning and adaptation in these sectors will be directed at minimising losses and maximising opportunities.

IMBER COP21-Fig 1

Figure 25. Estimates of global-average sea-level from several observational sources (purple, green, orange, light blue) and model-based projections for different emission scenarios (red, blue) with uncertainty estimates (shaded areas). Figure 13.27 from IPCC (2013).

 

Climate Intervention, within the Paris agreement is recognized as an important tool to reduce our net emissions i.e. offsetting fossil fuel emissions to directly limit warming. Examples of this include afforestation, ocean alkalinity/iron injection and bioenergy carbon capture and storage (BECCS). But deliberate manipulation of our world requires careful consideration and implementation of any large scale Climate Intervention is not without negative as well as potential positive biological and physical impacts. Clearly the ongoing assessment of the efficacy, impacts, and opportunities of Climate Intervention using well-established Earth System Modeling tools, will be critical to reaching the goals of the Paris Agreement. 

 

Reference 

  • IPCC, 2013: Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T. F., D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P. M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
banner transition NL

Where are they now?

Samiya Selim

Samiya Selim

PhD student at the University of Sheffield, UK

 
 
 

My first involvement with IMBER was attending the IMBER ClimEco3 Summer School - A View Towards Integrated Earth System Models. Human-nature Interactions in the Marine World, in Ankara, Turkey in 2012.  This was in the first year of my PhD on Shifting Baselines in Coastal Ecosystem Services. It was a great opportunity to learn about various modelling techniques, including socio-ecological models, which I was keen to use to model a long-term biological, physical and social data series of the Yorkshire coast of the North Sea. My next IMBER interaction was attending IMBIZO IV - A View Towards Integrated Earth System Models: Human-Nature Interactions in the Marine World in Trieste, Italy in October 2015. The timing could not have been more perfect! It was en route to the University of Sheffield, UK for my PhD thesis defence.  I presented my research findings at the IMBIZO, and the feedback provided by my peers and more senior scientists was very helpful and gave me increased confidence in preparation for the oral defence.

Prior to my PhD, I had done two Masters degrees at the University of Leeds – an MSc in Sustainable Development, and an MRes in Biodiversity and Conservation. My research interests lie in studying socio-ecological systems, particularly integrating the human dimensions in marine conservation.  At the moment, I am based in New Zealand but will be moving to Bangladesh in May 2016 where I plan to apply my inter-disciplinary (social sciences and marine ecology) academic and work experience to conservation and development projects. 

After ClimEco3, I was invited to participate in one of the workshops at IMBIZO III in Goa, India. The objective of the workshop was to explore the linkages and interactions between humans and marine systems to develop an understanding of the possible futures of the interrelated ecological and biogeochemical systems and the implications these could have on societies. Unfortunately, I was unable to attend. However, I remained in contact with Dr. Alida Bundy, one of the convenors of the workshop. Through this collaboration I published my first journal article as part of the workshop special issue of Regional Environmental Change on Global change, ensuing vulnerabilities, and social responses in marine environments (http://link.springer.com/journal/10113/16/2?wt_mc=alerts.TOCjournals). At IMBIZO IV, I attended the workshop titled Marine ecosystem-based governance: From rhetoric to reality. This gave me the opportunity to discuss my career options with Dr. Ratana Chuenpagdee, one of the workshop conveners, and also Dr. Annette Breckwoldt, who was assigned to be my mentor as part of the Mentoring Programme of the IMBIZO. They both provided me with contacts of scientists and academics working in marine conservation in Bangladesh. I plan to follow up on these leads for future projects and collaboration when I start working there.

The need for social and natural scientists to work together is increasingly being recognized around the world, and is beginning to be included in the principles of marine ecosystem based management and other policy drivers. This is one of the main issues that I addressed in my thesis, and I plan to apply it in my work in Bangladesh.  In my thesis, I combined path modelling with long-term datasets, collecting anecdotal stories and data from interviews with stakeholders. I demonstrated that, by employing a combination of social and natural sciences, historical marine ecology can yield better understanding of changes in socio-ecological systems. Doing so provides new insight into shifting baselines in ecosystem services and highlights long-term adaptations in socio-ecological systems at the local scale. I also showed that fishermen have good recollection of catches, but this only goes back as far as their personal experience. I provided recommendations on how these findings can aid in marine conservation and policy, particularly with regard to marine spatial planning in the Yorkshire region. There also needs to be an improvement in the methodology and standardization and spread across other coastal areas, to capture past human-nature interactions. This will and provide better understanding of trade-offs and the changing valuation of marine ecosystem services.

I am looking forward to applying the knowledge and skills I acquired during my PhD in the context of Bangladesh and getting involved in the science-policy interface. I may, for example, get involved in developing a monitoring program for the newly established marine protected areas of the coastal region, or collaborating with stakeholders on identifying which climate change adaptation and resilience policies and practices are successful and can be implemented on a regional scale. I also look forward to collaborating with all the people I have met during my three years of attending IMBER conferences, summer schools and workshops and attending future IMBER events.

banner transition NL

Announcements

IMBER future events

Special IMBER Session at the 7th World Fisheries Congress (23-27 May 2016, Busan, Korea)

Special IMBER session: How can natural science and social science research be integrated into science advice so that it is useful to policy makers and the broader society?

More info: http://www.wfc2016.or.kr/english/02_program/02_program.asp

banner 3rd transition NL

IMBER ClimEco5 Summer School (10-17 August 2016, Natal, Brazil)

Applications have closed. Applicants will be notified whether they have been accepted to attend by mid-May.
http://www.imber.info/index.php/Early-Career/IMBER-Summer-Schools/ClimEco5-August-2016-Natal-Brazil

banner transition NL

Publications

 
  • Becker M., Andersen N., Erlenkeuser H., Tanhua T., Humphreys M. P. & Körtzinger A. 2016. An Internally Consistent Dataset of δ13C-DIC Data in the North Atlantic Ocean. ORNL/CDIAC-162, NDP-096. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tennessee. doi: 10.3334/CDIAC/OTG.NAC13v1
    http://cdiac.ornl.gov/oceans/ndp_096/NAC13v1.html
  • Bermúdez J.R, Winder M., Stuhr A., Almén A.K., Engström-Öst J. & Riebesell U. In press. Effect of ocean acidification on the structure and fatty acid composition of a natural plankton community in the Baltic Sea. Biogeosciences Discussions. doi:10.5194/bg-2015-669
    http://www.biogeosciences-discuss.net/bg-2015-669/
  • Flecha S., Pérez F. F., García-Lafuente J., Sammartino S., Ríos A. I. & Huertas I. E. 2015. Trends of pH decrease in the Mediterranean Sea through high frequency observational data: indication of ocean acidification in the basin. Scientific Reports 5:16770. doi:10.1038/srep16770
    http://www.nature.com/articles/srep16770
  • Hofmann E., Bundy A., Drinkwater K., Piola A. R., Avril B., Robinson C., Murphy E., Maddison L., Svendsen E., Hall J. & Xu Y. In Press. IMBER – Research for Marine Sustainability: Synthesis and the Way Forward. Anthropocene. doi:10.1016/j.ancene.2015.12.002 
    http://dx.doi.org/10.1016/j.ancene.2015.12.002 
  • Jr. McGillicuddy D.J., Sedwick P.N., Dinniman M.S., Arrigo K.R., Bibby T.S., Greenan B.J.W., Hofmann E.E., Klinck J.M., Smith W.O. Jr., Mack S.L., Marsay C.M., Sohst B.M. & van Dijken G.L. 2015. Iron supply and demand in an Antarctic shelf ecosystem. Geophys. Res. Lett. 42: 8088­8097. doi:10.1002/2015GL065727
    http://onlinelibrary.wiley.com/doi/10.1002/2015GL065727/full 
  • Key R.M, Olsen A., van Heuven S., Lauvset S.K., Velo A., Lin X., Schirnick C., Kozyr A., Tanhua T., Hoppema M., Jutterström S., Steinfeldt R., Jeansson E., Ishii M., Perez F.F. & Suzuki T. 2015. Global Ocean Data Analysis Project, version 2 (GLODAPv2), ORNL/CDIAC-162, NDP-093, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, US. 
    http://cdiac.ornl.gov/oceans/GLODAPv2/
  • Koenigstein S., Mark F.C., Gößling-Reisemann S., Reuter H. & Pörtner H.-O. 2016. Modelling climate change impacts on marine fish populations: Process-based integration of ocean warming, acidification and other environmental drivers. Fish and Fisheries. doi: 10.1111/faf.12155
    http://onlinelibrary.wiley.com/doi/10.1111/faf.12155/abstract
  • Lauvset S.K, Key R.M., Olsen A., van Heuven S., Velo A., Lin X., Schirnick C., Kozyr A., Tanhua T., Hoppema M., Jutterström S., Steinfeldt R., Jeansson E., Ishii M., Pérez F.F., Suzuki T. & Watelet S. In review, 2016. A new global interior ocean mapped climatology: the 1°x1° GLODAP version 2. Earth System Science Data Discussions, doi:10.5194/essd-2015-43
    http://www.earth-syst-sci-data-discuss.net/essd-2015-43/
  • Montes E., Muller-Karger F.E., Lorenzoni L., Cianca A., Lomas M., Habtes S. 2016. Decadal variability in the oxygen inventory of North Atlantic Subtropical Underwater captured by sustained, long-term oceanographic time-series observations. Global Biogeochemical Cycles, DOI: 10.1002/2015GB005183. http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GB005183/full
  • Olsen A., Key R.M., van Heuven S., Lauvset S.K., Velo A., Lin X., Schirnick C., Kozyr A., Tanhua T., Hoppema M., Jutterström S., Steinfeldt R., Jeansson E., Ishii M., Pérez F.F. & Suzuki T. In review, 2016. An internally consistent data product for the world ocean: the Global Ocean Data Analysis Project, version 2 (GLODAPv2), Earth System Science Data, doi:10.5194/essd-2015-42
    http://www.earth-syst-sci-data-discuss.net/essd-2015-42/ 
  • Posner S.M., Mckenzie E. & Ricketts T.H. 2016. Policy impacts of ecosystem services knowledge. PNAS 113 (7): 1760-1765. doi: 10.1073/pnas.1502452113
    http://www.pnas.org/content/113/7/1760
  • Reum J.C.P., Alin S.R., Harvey C.J., Bednaršek N., Evans W., Feely R.A., Hales B., Lucey N., Mathis J.T., McElhany P., Newton J. & Sabine C.L. 2016. Interpretation and design of ocean acidification experiments in upwelling systems in the context of carbonate chemistry co-variation with temperature and oxygen. ICES J. Mar. Sci. 73 (3): 582-595. doi:10.1093/icesjms/fsu231
    http://icesjms.oxfordjournals.org/content/73/3/582
  • Rödenbeck C., Bakker D.C.E., Gruber N., Iida Y., Jacobson A.R., Jones S., Landschützer P., Metzl N., Nakaoka S., Olsen A., Park G.-H., Peylin P., Rodgers K.B., Sasse T.P., Schuster U., Shutler J.D., Valsala V., Wanninkhof R. & Zeng J. 2015. Data-based estimates of the ocean carbon sink variability – first results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM). Biogeosciences 12: 7251-7278. doi:10.5194/bg-12-7251-2015 
    http://www.biogeosciences.net/12/7251/2015/
  • Somero G.N., Beers J.M., Chan F., Hill T.M., Klinger T. & Litvin S.Y. 2016. What changes in the carbonate system, oxygen, and temperature portend for the Northeastern Pacific Ocean: a physiological perspective. BioScience 66(1):14-26. doi: 10.1093/biosci/biv162
    http://bioscience.oxfordjournals.org/content/66/1/14
  • van Putten I. E., Frusher S., Fulton E. A., Hobday A. J., Jennings Sarah M., Metcalf S. and Pecl G. T. 2015. Empirical evidence for differentcognitive effects in explaining the attribution of marine range shifts to climate change. ICES Journal of Marine Science. doi: 10.1093/icesjms/fsv192.
    http://icesjms.oxfordjournals.org/content/early/2016/02/09/icesjms.fsv192 
banner transition NL

Meeting Calendar

2016

2017