Diazotrophy as a key driver of the response of marine net primary productivity to climate change
Bopp, Laurent ; Aumont, Olivier ; Kwiatkowski, Lester ; Clerc, Corentin ; Dupont, Léonard ; Ethé, Christian ; Gorgues, Thomas ; Séférian, Roland ; Tagliabue, Alessandro
The impact of anthropogenic climate change on marine net primary production (NPP) is a reason for concern because changing NPP will have widespread consequences for marine ecosystems and their associated services. Projections by the current generation of Earth system models have suggested decreases in global NPP in response to future climate change, albeit with very large uncertainties. Here, we make use of two versions of the Institut Pierre-Simon Laplace Climate Model (IPSL-CM) that simulate divergent NPP responses to similar high-emission scenarios in the 21st century and identify nitrogen fixation as the main driver of these divergent NPP responses. Differences in the way N fixation is parameterised in the marine biogeochemical component PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies) of the IPSL-CM versions lead to N-fixation rates that are either stable or double over the course of the 21st century, resulting in decreasing or increasing global NPP, respectively. An evaluation of these two model versions does not help constrain future NPP projection uncertainties. However, the use of a more comprehensive version of PISCES, with variable nitrogen-to-phosphorus ratios as well as a revised parameterisation of the temperature sensitivity of N fixation, suggests only moderate changes in globally averaged N fixation in the 21st century. This leads to decreasing global NPP, in line with the model-mean changes of a recent multi-model intercomparison. Lastly, despite contrasting trends in NPP, all our model versions simulate similar and significant reductions in planktonic biomass. This suggests that projected plankton biomass may be a more robust indicator than NPP of the potential impact of anthropogenic climate change on marine ecosystems across models.</p>
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