An iron cycle cascade governs the response of equatorial Pacific ecosystems to climate change.
climate change
iron
marine ecosystems
net primary production
ocean
Journal
Global change biology
ISSN: 1365-2486
Titre abrégé: Glob Chang Biol
Pays: England
ID NLM: 9888746
Informations de publication
Date de publication:
Nov 2020
Nov 2020
Historique:
received:
19
06
2020
revised:
07
08
2020
accepted:
09
08
2020
pubmed:
25
9
2020
medline:
15
4
2021
entrez:
24
9
2020
Statut:
ppublish
Résumé
Earth System Models project that global climate change will reduce ocean net primary production (NPP), upper trophic level biota biomass and potential fisheries catches in the future, especially in the eastern equatorial Pacific. However, projections from Earth System Models are undermined by poorly constrained assumptions regarding the biological cycling of iron, which is the main limiting resource for NPP over large parts of the ocean. In this study, we show that the climate change trends in NPP and the biomass of upper trophic levels are strongly affected by modifying assumptions associated with phytoplankton iron uptake. Using a suite of model experiments, we find 21st century climate change impacts on regional NPP range from -12.3% to +2.4% under a high emissions climate change scenario. This wide range arises from variations in the efficiency of iron retention in the upper ocean in the eastern equatorial Pacific across different scenarios of biological iron uptake, which affect the strength of regional iron limitation. Those scenarios where nitrogen limitation replaced iron limitation showed the largest projected NPP declines, while those where iron limitation was more resilient displayed little future change. All model scenarios have similar skill in reproducing past inter-annual variations in regional ocean NPP, largely due to limited change in the historical period. Ultimately, projections of end of century upper trophic level biomass change are altered by 50%-80% across all plausible scenarios. Overall, we find that uncertainties in the biological iron cycle cascade through open ocean pelagic ecosystems, from plankton to fish, affecting their evolution under climate change. This highlights additional challenges to developing effective conservation and fisheries management policies under climate change.
Substances chimiques
Iron
E1UOL152H7
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
6168-6179Subventions
Organisme : H2020 European Research Council
ID : 724289
Organisme : Nippon Foundation
Organisme : Region Bretagne
Organisme : Agence Nationale de la Recherche
ID : ANR-18-ERC2-0001-01
Organisme : Natural Sciences and Engineering Research Council of Canada
Informations de copyright
© 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Références
Aksnes, D. L., & Egge, J. K. (1991). A theoretical model for nutrient uptake in phytoplankton. Marine Ecology Progress Series, 70(1), 65-72. https://doi.org/10.3354/meps070065
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., & Gehlen, M. (2015). PISCES-v2: An ocean biogeochemical model for carbon and ecosystem studies. Geoscientific Model Development, 8(8), 2465-2513. https://doi.org/10.5194/gmd-8-2465-2015
Behrenfeld, M. J., & Falkowski, P. G. (1997). Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and Oceanography, 42(1), 1-20. https://doi.org/10.4319/lo.1997.42.1.0001
Bindoff, N. L., Cheung, W. W. L., Kairo, J. G., Arístegui, J., Guinder, V. A., Hallberg, R., & Williamson, P. (2019). Changing ocean, marine ecosystems, and dependent communities. In D.- C.- R.- H.-O. Pörtner, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, & N. M. Weyer (Eds.), IPCC special report on the ocean and cryosphere in a changing climate (pp. 447-587). Cambridge, UK: Cambridge University Press.
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., … Vichi, M. (2013). Multiple stressors of ocean ecosystems in the 21st century: Projections with CMIP5 models. Biogeosciences, 10(10), 6225-6245. https://doi.org/10.5194/bg-10-6225-2013
Boyce, D. G., Lotze, H. K., Tittensor, D. P., Carozza, D. A., & Worm, B. (2020). Future ocean biomass losses may widen socioeconomic equity gaps. Nature Communications, 11(1). https://doi.org/10.1038/s41467-020-15708-9
Boyd, P. W., Ellwood, M. J., Tagliabue, A., & Twining, B. S. (2017). Biotic and abiotic retention, recycling and remineralization of metals in the ocean. Nature Geoscience, 10(3), 167-173. https://doi.org/10.1038/ngeo2876
Buitenhuis, E. T., & Geider, R. J. (2010). A model of phytoplankton acclimation to iron-light colimitation. Limnology and Oceanography, 55(2), 714-724. https://doi.org/10.4319/lo.2010.55.2.0714
Caceres, C., Spatharis, S., Kaiserli, E., Smeti, E., Flowers, H., & Bonachela, J. A. (2019). Temporal phosphate gradients reveal diverse acclimation responses in phytoplankton phosphate uptake. The ISME Journal, 13(11), 2834-2845. https://doi.org/10.1038/s41396-019-0473-1
Caputi, L., Carradec, Q., Eveillard, D., Kirilovsky, A., Pelletier, E., Pierella Karlusich, J. J., … Wincker, P. (2019). Community-level responses to iron availability in open ocean plankton ecosystems. Global Biogeochemical Cycles, 33(3), 391-419. https://doi.org/10.1029/2018gb006022
Coale, T. H., Moosburner, M., Horak, A., Obornik, M., Barbeau, K. A., & Allen, A. E. (2019). Reduction-dependent siderophore assimilation in a model pennate diatom. Proceedings of the National Academy of Sciences of the United States of America, 116(47), 23609-23617. https://doi.org/10.1073/pnas.1907234116
Cohen, N. R., Mann, E., Stemple, B., Moreno, C. M., Rauschenberg, S., Jacquot, J. E., … Marchetti, A. (2018). Iron storage capacities and associated ferritin gene expression among marine diatoms. Limnology and Oceanography, 63(4), 1677-1691. https://doi.org/10.1002/lno.10800
du Pontavice, H., Gascuel, D., Reygondeau, G., Maureaud, A., & Cheung, W. W. L. (2020). Climate change undermines the global functioning of marine food webs. Global Change Biology, 26(3), 1306-1318. https://doi.org/10.1111/gcb.14944
Falkowski, P. G., Barber, R. T., & Smetacek, V. (1998). Biogeochemical controls and feedbacks on ocean primary production. Science, 281(5374), 200-206. https://doi.org/10.1126/science.281.5374.200
FAO. (2018). The State of World Fisheries and Aquaculture (SOFIA) Rome. Italy: FAO.
Frölicher, T. L., Rodgers, K. B., Stock, C. A., & Cheung, W. W. L. (2016). Sources of uncertainties in 21st century projections of potential ocean ecosystem stressors. Global Biogeochemical Cycles, 30(8), 1224-1243. https://doi.org/10.1002/2015gb005338
Gascuel, D., Guénette, S., & Pauly, D. (2011). The trophic-level-based ecosystem modelling approach: Theoretical overview and practical uses. ICES Journal of Marine Science, 68(7), 1403-1416. https://doi.org/10.1093/icesjms/fsr062
Gascuel, D., Morissette, L., Palomares, M. L. D., & Christensen, V. (2008). Trophic flow kinetics in marine ecosystems: Toward a theoretical approach to ecosystem functioning. Ecological Modelling, 217(1-2), 33-47. https://doi.org/10.1016/j.ecolmodel.2008.05.012
Guiet, J., Aumont, O., Poggiale, J.-C., & Maury, O. (2016). Effects of lower trophic level biomass and water temperature on fish communities: A modelling study. Progress in Oceanography, 146, 22-37. https://doi.org/10.1016/j.pocean.2016.04.003
Hutchins, D. A., & Boyd, P. W. (2016). Marine phytoplankton and the changing ocean iron cycle. Nature Climate Change, 6(12), 1072-1079. https://doi.org/10.1038/nclimate3147
John, S. G., Helgoe, J., Townsend, E., Weber, T., DeVries, T., Tagliabue, A., … Till, C. (2018). Biogeochemical cycling of Fe and Fe stable isotopes in the eastern tropical south pacific. Marine Chemistry, 201, 66-76. https://doi.org/10.1016/j.marchem.2017.06.003
Kooijman, S. A. L. M. (2000). Dynamic energy and mass budgets in biological systems (2nd ed.). Cambridge: Cambridge University Press.
Kwiatkowski, L., Bopp, L., Aumont, O., Ciais, P., Cox, P. M., Laufkötter, C., … Séférian, R. (2017). Emergent constraints on projections of declining primary production in the tropical oceans. Nature Climate Change, 7(5), 355-358. https://doi.org/10.1038/nclimate3265
Lampe, R. H., Mann, E. L., Cohen, N. R., Till, C. P., Thamatrakoln, K., Brzezinski, M. A., … Marchetti, A. (2018). Different iron storage strategies among bloom-forming diatoms. Proceedings of the National Academy of Sciences of the United States of America, 115(52), E12275-E12284. https://doi.org/10.1073/pnas.1805243115
Laufkötter, C., Vogt, M., Gruber, N., Aita-Noguchi, M., Aumont, O., Bopp, L., … Völker, C. (2015). Drivers and uncertainties of future global marine primary production in marine ecosystem models. Biogeosciences, 12(23), 6955-6984. https://doi.org/10.5194/bg-12-6955-2015
Longhurst, A., Sathyendranath, S., Platt, T., & Caverhill, C. (1995). An estimate of global primary production in the ocean from satellite radiometer data. Journal of Plankton Research, 17(6), 1245-1271. https://doi.org/10.1093/plankt/17.6.1245
Lotze, H. K., Tittensor, D. P., Bryndum-Buchholz, A., Eddy, T. D., Cheung, W. W. L., Galbraith, E. D., … Worm, B. (2019). Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proceedings of the National Academy of Sciences of the United States of America, 116(26), 12907-12912. https://doi.org/10.1073/pnas.1900194116
Marchetti, A., & Maldonado, M. T. (2016). Iron. In M. A. Borowitzka, J. Beardall, & J. A. Raven (Eds.), The physiology of microalgae (pp. 233-279). Cham: Springer International Publishing.
Marra, J., Ho, C., & Trees, C. C. (2003). An alternative algorithm for the calculation of primary productivity from remote sensing data. LDEO Technical Report, Lamont-Doherty Earth Observatory.
Maury, O. (2010). An overview of APECOSM, a spatialized mass balanced “Apex Predators ECOSystem Model” to study physiologically structured tuna population dynamics in their ecosystem. Progress in Oceanography, 84(1-2), 113-117. https://doi.org/10.1016/j.pocean.2009.09.013
Maury, O., & Poggiale, J. C. (2013). From individuals to populations to communities: A dynamic energy budget model of marine ecosystem size-spectrum including life history diversity. Journal of Theoretical Biology, 324, 52-71. https://doi.org/10.1016/j.jtbi.2013.01.018
McQuaid, J. B., Kustka, A. B., Oborník, M., Horák, A., McCrow, J. P., Karas, B. J., … Allen, A. E. (2018). Carbonate-sensitive phytotransferrin controls high-affinity iron uptake in diatoms. Nature, 555(7697), 534-537. https://doi.org/10.1038/nature25982
Moore, C. M., Mills, M. M., Arrigo, K. R., Berman-Frank, I., Bopp, L., Boyd, P. W., … Ulloa, O. (2013). Processes and patterns of oceanic nutrient limitation. Nature Geoscience, 6(9), 701-710. https://doi.org/10.1038/ngeo1765
Morel, F. M., & Price, N. M. (2003). The biogeochemical cycles of trace metals in the oceans. Science, 300(5621), 944-947. https://doi.org/10.1126/science.1083545
Nunn, B. L., Faux, J. F., Hippmann, A. A., Maldonado, M. T., Harvey, H. R., Goodlett, D. R., … Strzepek, R. F. (2013). Diatom proteomics reveals unique acclimation strategies to mitigate Fe limitation. PLoS One, 8(10), e75653. https://doi.org/10.1371/journal.pone.0075653
Rayner, N. A. (2003). Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research, 108(D14). https://doi.org/10.1029/2002jd002670
Richon, C., Aumont, O., & Tagliabue, A. (2020). Prey stoichiometry drives iron recycling by zooplankton in the global ocean. Frontiers in Marine Science, 7. https://doi.org/10.3389/fmars.2020.00451
Silsbe, G. M., Behrenfeld, M. J., Halsey, K. H., Milligan, A. J., & Westberry, T. K. (2016). The CAFE model: A net production model for global ocean phytoplankton. Global Biogeochemical Cycles, 30(12), 1756-1777. https://doi.org/10.1002/2016gb005521
Stock, C. A., Dunne, J. P., & John, J. G. (2014). Global-scale carbon and energy flows through the marine planktonic food web: An analysis with a coupled physical-biological model. Progress in Oceanography, 120, 1-28. https://doi.org/10.1016/j.pocean.2013.07.001
Tagliabue, A., Aumont, O., DeAth, R., Dunne, J. P., Dutkiewicz, S., Galbraith, E., … Yool, A. (2016). How well do global ocean biogeochemistry models simulate dissolved iron distributions? Global Biogeochemical Cycles, https://doi.org/10.1002/2015gb005289
Tagliabue, A., Bowie, A. R., Boyd, P. W., Buck, K. N., Johnson, K. S., & Saito, M. A. (2017). The integral role of iron in ocean biogeochemistry. Nature, 543(7643), 51-59. https://doi.org/10.1038/nature21058
Terada, M., Minobe, S., & Deutsch, C. (2020). Mechanisms of future changes in equatorial upwelling: CMIP5 intermodel analysis. Journal of Climate, 33(2), 497-510. https://doi.org/10.1175/jcli-d-19-0128.1
Twining, B. S., Baines, S. B., Bozard, J. B., Vogt, S., Walker, E. A., & Nelson, D. M. (2011). Metal quotas of plankton in the equatorial Pacific Ocean. Deep Sea Research Part II: Topical Studies in Oceanography, 58(3-4), 325-341. https://doi.org/10.1016/j.dsr2.2010.08.018
Watson, R. A. (2017). A database of global marine commercial, small-scale, illegal and unreported fisheries catch 1950-2014. Scientific Data, 4, 1950-2014. https://doi.org/10.1038/sdata.2017.39
Westberry, T., Behrenfeld, M. J., Siegel, D. A., & Boss, E. (2008). Carbon-based primary productivity modeling with vertically resolved photoacclimation. Global Biogeochemical Cycles, 22(2). https://doi.org/10.1029/2007gb003078