Written by Nereus Program Manager/Research Associate Vicky Lam,
A recently published United Nations (UN) Global Assessment report conducted by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) with more than 450 experts from around the world marks the milestones for safeguarding our healthy planet. The report highlights that the rate of species extinction is surging at an alarming rate and it is time for transformative changes across economic, social, political and technological aspects to protect our nature. In addition, many international societal and environmental goals, such as the Aichi Biodiversity Targets and the 2030 Agenda for Sustainable Development, will not be achieved. The major direct drivers for these changes are changes in land and sea use, direct exploitation of organisms, climate change, pollution and invasive alien species. In the ocean, direct exploitation of organisms is the dominant key driver for the negative impact on the marine ecosystem, followed by land and sea use change. About 66% of the ocean were experiencing increasing cumulative impacts from these drivers in 2014 (Diaz et al., 2019). Also, about 33% of the marine fish stocks were being harvested at an unstainable level in 2015. These negative impacts on biodiversity and marine ecosystem functions and services adversely affect human well-being and their quality of life. To reduce the rate of the massive loss, policy actions and societal initiatives are crucial for promoting the awareness of the impacts of our consumption on nature, protecting habitats, promoting sustainable local economies and restoring degraded areas. Implementing ecosystem-based approaches to fisheries management, spatial planning, reducing other anthropogenic stressors to the ocean and working closely with producers and consumers are put forth as plausible options and practices for managing and protecting our marine ecosystems in this report.
Given the urgency of these challenges, modeling approach and scenario analysis plays a very important role for exploring and identifying the possible actions, policies and approaches for achieving the long-term ecological, economic and social sustainable ways of utilizing the marine resources. Modeling approach has long been widely adopted in projecting the future changes of environmental variables under climate change, distribution and abundance of marine species under global change, change in maximum catch potential and the subsequent impacts on the economics and human who depend on marine resources for food and livelihood. Climate models have been evolving from simple model to the complicated Earth System Models (ESMs) in the recent decades (Morgenstern et al. 2017). These models capture interactions between physical, chemical and biological aspects including simulating air quality, tropospheric chemistry, stratospheric ozone and global climate of the Earth system (Morgenstern et al. 2017; Bonan and Doney 2018). In the context of the marine ecosystem, there is a range of biophysical models, among others, to include Dynamic Bioclimate Envelope Model (DBEM), which links projection of habitat suitability to the spatial and temporal population dynamics and ecophysiology (Cheung et al. 2011; Cheung et al., 2016), and models that capture the dynamics and interactions of marine food webs including a coupled model that combined physical-biogeochemical model with dynamic, size-based ecosystem model developed by Blanchard et al. (2012), Princeton Ocean Ecosystem Model (POEM) (Watson et al. 2015) and the composite (hybrid) model such as Madingley (Harfoot et al. 2014a). The results of these models have further been used to explore the impacts of climate change on the society, economics, jobs, food and nutrition impacts on the society. However, most of the feedback actions from the societal actions have not been considered.
From here, we can see the importance of having the Integrated Assessment Models (IAMs) to link various parts of the system together and project the future changes in the natural system and the society from the effects of human development and climate change.
Although modeling approach can help us to explore plausible futures, the results are still filled with uncertainties associated with changes in the environmental and socio-economic systems and the interactions across different sectors. To address these uncertainties, different possible alternative narratives of the future development of the world are developed using scenario analysis. For examining the future pathways and solutions for the challenges, scenarios are usually developed to explore different plausible future scenarios of social, economic and environmental development impacts on the human society. One component of these scenarios is the shared socioeconomic pathway (SSPs) developed by Intergovernmental Panel on Climate Change (IPCC) (Ebi et al., 2014; Kriegler et al., 2014; O’Neill et al.; 2014, van Vuuren et al., 2014). SSP narratives are a set of scenarios describing alternative futures of societal developments including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. In parallel with the SSPs, the IPCC Fifth Assessment Report (IPCC Working Group II 2014; Tayler et al. 2012) also developed climate change scenarios which are known as Representative Concentration Pathways (RCPs), which describe four different 21st century pathways of greenhouse gas (GHG) emissions and atmospheric concentrations, air pollutant emissions and land-use based on a set of anthropogenic drivers. Hence, to have a comprehensive understanding of possible futures, a framework for combining both climate change scenarios and the socioeconomic dimension of the scenario framework in a Scenario Matrix Architecture is necessary (Riahi et al. 2017).
The crucial next step for the research community is to combine the RCPs and SSPs with the IAMs, which are designed for projecting the future state of the natural biosphere, to quantitatively assess the impacts of both climate change and other global challenges on the biodiversity and the subsequent socioeconomic aspects. In the context of marine fisheries, IAM combines representation of the change in biogeochemical conditions in the ocean under climate change, population dynamics of fish stocks, fishing effort, fish demand, trade of seafood and fish market dynamics to make projections about the future of marine fisheries and the impacts on human-wellbeing. Thus, both IAM and scenario analysis have been already identified as core elements within the work of the IPBES assessing future states of biodiversity (Harfoot et al. 2014b). Also, intercomparison studies of different models are necessary for identifying within and among model uncertainties, assessing model fits to historical data and providing ensemble projections of future change under particular scenarios (Tittensor et al. 2018).
Recently, a high-level international workshop co-organized by the Nereus Program and IPBES involving about 40 stakeholders and experts from all over the world was held to discuss gaps and issues for the development of narratives, scenarios and models to address feedbacks of direct (e.g., habitat loss or conversion, invasive species, pollution, climate change) and indirect (e.g., socio-political, economic and technological) drivers affecting the Earth’s ecosystems, including terrestrial environments (urbanization and land), freshwater (land-water) and oceans (marine interaction), as well as the identification of indicators. The outcomes of the workshop are in line with the recent Global Assessment report and the recent work of Nereus Program on future scenario development with a target to develop narrative and pathways affecting the ocean and fishing sector under various SSPs and climate change scenarios.
 Summary for policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (2019). Link
BLANCHARD, J. L., JENNINGS, S., HOLMES, R., HARLE, J., MERINO, G., ALLEN, J. I., HOLT, J., DULVY, N. K. & BARANGE, M. 2012. Potential consequences of climate change for primary production and fish production in large marine ecosystems. Phil. Trans. R. Soc. B, 367, 2979-2989.
Bonan, G.B. and Doney, S.C., 2018. Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models. Science, 359(6375), p.eaam8328.
CHEUNG, W. W., DUNNE, J., SARMIENTO, J. L. & PAULY, D. 2011. Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J Mar Sci.
CHEUNG, W. W. L., JONES, M. C., REYGONDEAU, G., STOCK, C. A., LAM, V. W. Y. & FROLICHER, T. L. 2016. Structural uncertainty in projecting global fisheries catches under climate change. Ecol. Model., 325, 57 – 66.
Diaz, S., Settele, J., Brondizio, E., et al. 2019. Summary of policymakers of the global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (Advance unedited version). Link
Ebi, K.L., Hallegatte, S., Kram, T., Arnell, N.W., Carter, T.R., Edmonds, J., Kriegler, E., Mathur, R., O’Neill, B.C., Riahi, K. and Winkler, H., 2014. A new scenario framework for climate change research: background, process, and future directions. Climatic Change, 122(3), pp.363-372.
HARFOOT, M. B., NEWBOLD, T., TITTENSOR, D. P., EMMOTT, S., HUTTON, J., LYUTSAREV, V., SMITH, M. J., SCHARLEMANN, J. P. & PURVES, D. W. 2014a. Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model. PLoS biology, 12, e1001841.
Harfoot, M., Tittensor, D.P., Newbold, T., McInerny, G., Smith, M.J. and Scharlemann, J.P., 2014b. Integrated assessment models for ecologists: the present and the future. Global Ecology and Biogeography, 23(2), pp.124-143.
IPCC Working Group II, 2014. Climate Change 2014-Impacts, Adaptation, and Vulnerability: Summary for Policymakers. Intergovernmental Panel on Climate Change.Morgenstern, O., Hegglin, M.I., Rozanov, E., O’Connor, F.M., Abraham, N.L., Akiyoshi, H., Archibald, A.T., Bekki, S., Butchart, N., Chipperfield, M.P. and Deushi, M., 2017. Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI).
Kriegler, E., Edmonds, J., Hallegatte, S., Ebi, K.L., Kram, T., Riahi, K., Winkler, H. and Van Vuuren, D.P., 2014. A new scenario framework for climate change research: the concept of shared climate policy assumptions. Climatic Change, 122(3), pp.401-414.
Morgenstern, O., Hegglin, M.I., Rozanov, E., O’Connor, F.M., Abraham, N.L., Akiyoshi, H., Archibald, A.T., Bekki, S., Butchart, N., Chipperfield, M.P. and Deushi, M., 2017. Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI).
O’Neill, B.C., Kriegler, E., Riahi, K., Ebi, K.L., Hallegatte, S., Carter, T.R., Mathur, R. and van Vuuren, D.P., 2014. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic change, 122(3), pp.387-400.
Riahi, K., Van Vuuren, D.P., Kriegler, E., Edmonds, J., O’neill, B.C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O. and Lutz, W., 2017. The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Global Environmental Change, 42, pp.153-168.
Taylor, K.E., Stouffer, R.J. and Meehl, G.A., 2012. An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4), pp.485-498.
Tittensor, D.P., Eddy, T.D., Lotze, H.K., Galbraith, E.D., Cheung, W., Barange, M., Blanchard, J.L., Bopp, L., Bryndum-Buchholz, A., Büchner, M. and Bulman, C., 2018. A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1. 0. Geoscientific Model Development, 11(4), pp.1421-1442.
Van Vuuren, D.P., Kriegler, E., O’Neill, B.C., Ebi, K.L., Riahi, K., Carter, T.R., Edmonds, J., Hallegatte, S., Kram, T., Mathur, R. and Winkler, H., 2014. A new scenario framework for climate change research: scenario matrix architecture. Climatic Change, 122(3), pp.373-386.
WATSON, J. R., STOCK, C. A. & SARMIENTO, J. L. 2015. Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic–size-based ecosystem model. Progress in Oceanography, 138, 521-532.