Uncertainties in projecting climate-change impacts in marine ecosystems

ICES Journal of Marine Science ICES Journal of Marine Science (2016), 73(5), 1272– 1282. doi:10.1093/icesjms/fsv231 Contribution to the Symposium: ‘Effects of Climate Change on the World’s Oceans’ Review Uncertainties in projecting climate-change impacts in marine ecosystems 1 Centre for Ocean Life, National Institute of Aquatic Resources (DTU-Aqua), Technical University of Denmark, 2920 Charlottenlund, Denmark Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL13 DH, UK 3 Changing Ocean Research Unit, Institute for the Oceans and Fisheries, The University of British Columbia, AERL, 2202 Main Mall, Vancouver, BC, Canada V6T 1Z4 4 North Pacific Marine Science Organization (PICES), 9860 West Saanich Road, Sidney, BC, Canada V8L4B2 5 IFREMER, Channel and North Sea Fisheries Research Unit, 150 Quai Gambetta, BP 699, 62321 Boulogne-sur-Mer, France 6 Biology Department, Dalhousie University, 1355 Oxford Street, Halifax, Nova Scotia, Canada B3H 4J1 7 National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115, USA 8 Department of Zoology, Cambridge University, Downing Street, Cambridge CB2 3EJ, UK 9 National Oceanic and Atmospheric Administration, National Marine Fisheries Service, 166 Water St, Woods Hole, MA 02543, USA 10 Dragonfly Data Science, PO Box 27535, Wellington 6141, New Zealand 11 Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98195, USA 12 MARE—Marine and Environmental Sciences Centre, Laboratório Marı́timo da Guia—Faculdade de Ciências da Universidade de Lisboa, Av. Nossa Senhora do Cabo, 939, 2750-374 Cascais, Portugal 2 *Corresponding author: tel: +45 3588 3455; e-mail: 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, Jason S., Neubauer, P., Ortiz, I., Queirós, A. M., and Paula, J. R. Uncertainties in projecting climate-change impacts in marine ecosystems. – ICES Journal of Marine Science, 73: 1272– 1282. Received 6 July 2015; revised 9 November 2015; accepted 10 November 2015; advance access publication 17 December 2015. Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability uncertainty, (iii) parametric uncertainty, and (iv) scenario uncertainty. For each uncertainty type, we then examine the current state-of-the-art in assessing and quantifying its relative importance. We consider whether the marine scientific community has addressed these types of uncertainty sufficiently and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization uncertainty is rarely treated explicitly and reducing this type of uncertainty may deliver gains on the seasonal-to-decadal time-scale. We conclude that all parts of marine science could benefit from a greater exchange of ideas, particularly concerning such a universal problem such as the treatment of uncertainty. Finally, marine science should strive to reach the point where scenario uncertainty is the dominant uncertainty in our projections. Keywords: climate change, initialization uncertainty, parametric uncertainty, projections, scenario uncertainty, structural uncertainty, uncertainty. # International Council for the Exploration of the Sea 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Mark R. Payne 1*, Manuel Barange 2, William W. L. Cheung3, Brian R. MacKenzie 1, Harold P. Batchelder 4, Xochitl Cormon5, Tyler D. Eddy 6, Jose A. Fernandes 2, Anne B. Hollowed 7, Miranda C. Jones 3,8, Jason S. Link9, Philipp Neubauer 10, Ivonne Ortiz 11, Ana M. Queirós2, and José Ricardo Paula 12 1273 Uncertainties in projecting climate-change impacts Introduction Structural uncertainty Structural, or model, uncertainty can be characterized as the uncertainty associated with how the model is built up, i.e. how the model Figure 1. Contributions of various types of uncertainty to the total uncertainty in IPCC model ensemble projections of mean surface temperature over the British Isles. Relative (fractional) uncertainty of the total (black) and each individual component: model uncertainty (blue), scenario uncertainty (green), and internal variability (initialization uncertainty: orange). Note the change in the relative importance of the individual components. Reprinted from Hawkins and Sutton (2009). #American Meteorological Society. Used with permission. This figure is available in black and white in print and in colour at ICES Journal of Marine Science online. Climate change is expected to have major consequences for marine ecosystems, including changes in biogeochemical cycles, trophic flows, species life histories, distributions, and seasonality (IPCC, 2014; Gattuso et al., 2015). Such changes in turn impact how society depends on, and is influenced by, marine ecosystems and foodwebs. For example, there is a growing consensus that the roles of the oceans in the production of food for humans and as a sink for carbon dioxide will be altered due to climate change, and that such alterations will have socio-economic consequences (Barange et al., 2014). Climate-change projections are based on models that attempt to represent reality within the constraints of process understanding, observational data, and future conditions. However, such models may perform better at some spatial and temporal scales than others (or can only perform at one scale), even though there may be profound impacts on ecosystems and humans at other scales where model performance is less satisfactory. Moreover, the skill of a model often varies between variables; for example, global climate models typically predict surface temperatures better than precipitation. Consequently, the quality of model outputs depends on both the variable(s) being forecasted and the space-time-scale considered. In an ecosystem or fisheries management context, however, what often matters most is not necessarily (...truncated)