Editing IPCC:AR6/SROCC/Chapter-5 (section)

==== 5.2.2.6 Changing Ocean Primary and Export Production ====

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Ocean primary productivity is a key process in the ocean carbon cycle (see Section 5.2.2.3), as well as for supporting pelagic ocean ecosystems (see Section 5.2.3). NPP is the product of phytoplankton growth rate and standing stock. Phytoplankton growth is controlled by the combination of temperature, light and nutrients, while the phytoplankton standing stock is modified by both gains from growth and losses due to grazing by zooplankton (Figure 5.12). Export production is here defined as the sinking flux of particulate organic carbon (produced by NPP) across a specified depth horizon. Otherwise known as the biological pump, export production is also a key component of the global carbon cycle (see Section 5.2.2.3) and an essential food supply to benthic organisms (see Section 5.2.3.2). Export production is regulated by the level of primary production and the transfer efficiency with depth, itself controlled by the type of sinking organic carbon, which is affected by the upper ocean food web structure (Boyd et al., 2019 <sup>[[#fn:r317|317]]</sup> ).

Satellite datasets that use mathematical algorithms to convert ocean colour, often alongside other remotely sensed information, into chlorophyll or other indexes of phytoplankton biomass and NPP provide the potential to deliver a global meta-analysis of changes in NPP. Since AR5, a variety of studies have reported relatively insignificant changes in overall open ocean chlorophyll levels of &lt;±1% yr –1 for individual time periods (Boyce et al., 2014 <sup>[[#fn:r318|318]]</sup> ; Gregg and Rousseaux, 2014 <sup>[[#fn:r319|319]]</sup> ; Boyce and Worm, 2015 <sup>[[#fn:r320|320]]</sup> ; Hammond et al., 2017 <sup>[[#fn:r321|321]]</sup> ). Regionally, trends of ±4% between 2002–2015 for different regions are found when different satellite products are merged, with increases at high latitudes and moderate decreases at low latitudes (Mélin et al., 2017 <sup>[[#fn:r322|322]]</sup> . While some studies report good comparability of merged products (Mélin et al., 2017 <sup>[[#fn:r323|323]]</sup> ), others highlight significant mismatches regarding absolute values and decadal trends in NPP between NPP algorithms (Gómez-Letona et al., 2017 <sup>[[#fn:r324|324]]</sup> ). Satellite derived NPP shows significant mismatches when compared to ''in situ'' data and reducing uncertainties in derived NPP is a high priority for the community (Lee et al., 2015 <sup>[[#fn:r325|325]]</sup> ), although there is a reasonable correlation in higher biomass coastal regions (Kahru et al., 2009 <sup>[[#fn:r326|326]]</sup> ). Importantly, satellite records are not yet long enough to unambiguously isolate long term climate related trends from natural variability (Beaulieu et al., 2013 <sup>[[#fn:r327|327]]</sup> ). Overall, there is ''low confidence'' in satellite-based trends in global ocean NPP due to the time series length and lack of corroborating ''in situ'' measurements or other validation time series. This is especially true at regional scales where distinct sets of poorly understood processes dominate.

Future changes in NPP will result from the changing influence from temperature, light, nutrients and grazing (Figure 5.12). Across CMIP models, NPP is predicted to broadly decline or remain constant by 2081–2100, with mean changes by 2100 of –3.8 to –10.6% and –1.1–0.8% across 90% confidence intervals for the RCP85 and RCP26 scenario, respectively (all relative to 2006–2015), with a strong degree of regional symmetry (Figure 5.8k). As seen for nitrate, changes are most marked in low-latitude upwelling regions, which are projected to show the largest absolute declines. As for nitrate, projected NPP changes are lower for the RCP26 scenario (Figure 5.8j), but the overall uncertainty is dominated by internal and inter-model variability in 2100 (Figure 5.8l) which results in no clear separation of NPP trends between the RCP85 and RCP26 (Figure 5.8j). Tropical ocean NPP is projected to show a large decline, but is underpinned by substantial intermodal uncertainty, with mean changes of 11 ± 24% across the suite of CMIP5 models by 2100, relative to 2000 under RCP8.5 (Laufkötter et al., 2015 <sup>[[#fn:r328|328]]</sup> ). However, if emergent constraints from the historical record that link the variability of tropical productivity to temperature anomalies then a four-fold decline in inter-model uncertainty results. This leads to a projected tropical ocean decline of 11 ± 6%, or from 6.8–16.2% across 90% confidence limits, depending on which historical constraint is used (Kwiatkowski et al., 2017 <sup>[[#fn:r329|329]]</sup> ). NPP is projected to increases for higher latitude regions, such as the Arctic and Southern Oceans.

Detailed analyses of the interplay between different drivers of NPP, including temperature, light, nutrient levels and grazing from a subset of CMIP5 models, reveals a complex interplay with a strong latitudinal dependence (Laufkötter et al., 2015 <sup>[[#fn:r330|330]]</sup> ) summarised in Figure 5.12. Warming acts to enhance growth, most notably at lower latitudes, while light conditions are also predicted to improve, mostly at the poles. Nutrient limitation shows a much more complex response across models, but tends to increase in the tropics and northern high latitudes, with little change in the Southern Ocean. Taken together there is a tendency for reduced growth rates across the entire ocean, but there is a large amount of inter-model variability. The changes in growth are allied to a consistent increase in the grazing loss of biomass to upper trophic levels. Since AR5, we have an increasing body of literature concerning role of biological feedbacks, especially due to interactions between organisms, specific physiological responses and from upper trophic levels on nutrient concentrations, linked to variable food quality (Kwiatkowski et al., 2018 <sup>[[#fn:r331|331]]</sup> ), resource recycling (Boyd et al., 2015a <sup>[[#fn:r332|332]]</sup> ; Tagliabue et al., 2017 <sup>[[#fn:r333|333]]</sup> ) and interactions between organisms (Lima-Mendez et al., 2015 <sup>[[#fn:r334|334]]</sup> ), but their role in shaping the response of NPP to climate change remains a major unknown. Lastly, modelling work suggests that the increasing deposition of anthropogenic aerosols (supplying N and Fe) stimulates biological activity (Wang et al., 2015b <sup>[[#fn:r335|335]]</sup> ) and may compensate for warming driven reductions in primary productivity (Wang et al., 2015b <sup>[[#fn:r336|336]]</sup> ), but these effects do not form part of the CMIP5 projections assessed here.

CMIP5 models show a strong negative relationship between changes in stratification that reduces net nutrient supply and integrated export production (Fu et al., 2016 <sup>[[#fn:r337|337]]</sup> ). Export production is projected to decline by 8.9–15.8% or 1.6–4.9% (across 90% confidence intervals) by 2100, relative to 2000 for the RCP8.5 or RCP2.6 scenario, respectively (Bopp et al., 2013 <sup>[[#fn:r338|338]]</sup> ; Fu et al., 2016 <sup>[[#fn:r339|339]]</sup> ; Laufkötter et al., 2016 <sup>[[#fn:r340|340]]</sup> ). The projected changes in export production can be larger than global primary production because they are affected by both the NPP changes, but also how shifts in food web structure modulates the ‘transfer efficiency’ of particulate organic material (Guidi et al., 2016 <sup>[[#fn:r341|341]]</sup> ; Tréguer et al., 2018 <sup>[[#fn:r342|342]]</sup> ), which then affects the sinking speed and lability of exported particles through the ocean interior to the sea floor (Bopp et al., 2013 <sup>[[#fn:r343|343]]</sup> ; Fu et al., 2016 <sup>[[#fn:r344|344]]</sup> ; Laufkötter et al., 2016 <sup>[[#fn:r345|345]]</sup> ). Declines in export production over much of the ocean mean that the flux arriving at the sea floor is also predicted to decline, while increases in export production are projected in the polar regions that see enhanced NPP (Sweetman et al., 2017 <sup>[[#fn:r346|346]]</sup> ).

The realism in model projections can be appraised via their ability to accurately simulate the limiting nutrient in specific ocean regions (Figure 5.11), with high model skill in reproducing surface distributions of nitrate and phosphate (Laufkötter et al., 2015 <sup>[[#fn:r347|347]]</sup> ), raising confidence in projections in nitrogen and phosphorus limited systems, but poor skill in reproducing iron distributions (Tagliabue et al., 2016 <sup>[[#fn:r348|348]]</sup> ) lowering confidence in iron limited regions (Figure 5.11). In addition to concentrations of specific nutrients, the response of NPP to environmental change is strongly controlled by accurate representation of the ratio of resources (Moreno et al., 2017 <sup>[[#fn:r349|349]]</sup> ). Overall CMIP5 models skill in reproducing patterns of NPP and export production from limited satellite derived estimates range from poor to average (correlation coefficients of 0.1–0.6 across different models (Laufkötter et al., 2016; Moreno et al., 2017 <sup>[[#fn:r350|350]]</sup> )), but it should be noted that complete comprehensive observational datasets do not exist for these metrics with very few ''in situ'' observations. As export production is a much better understood net integral of changing net nutrient supply (Sarmiento and Gruber, 2002 <sup>[[#fn:r351|351]]</sup> ) and can be constrained by interior ocean nutrient and oxygen levels, there is ''medium confidence'' in these projections for global changes. Improving the ability of models to reproduce historical NPP is crucial for more accurate projections as model biases in simulating contemporary ocean biogeochemistry play a key role in driving future projections (Fu et al., 2016 <sup>[[#fn:r352|352]]</sup> ).

Overall, these assessments balance the range of projections across models alongside the strength of different kinds of observational constraints available, as well as our theoretical or experimental understanding of the impact of a warmer, more stratified ocean on NPP and export production. As for AR5, net primary productivity is ''very likely'' to decline by 4–11% by 2081–2100, relative to 1850–1900, across CMIP5 models for RCP8.5, but there is ''low confidence'' for this estimate due to the ''medium agreement'' among models and the ''limited evidence'' from observations. It is ''very likely'' that tropical NPP will decline by 7–16% by 2100 for RCP8.5with ''medium confidence'' , as there are improved constraints from historical variability in this region. Globally, the increased stratification in the future is ''very likely'' to reduce export production by 9–16% in response to reduced nutrient supply, especially in tropical regions ( ''medium confidence'' ).

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'''Figure 5.12'''

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'''Figure 5.12 | A schematic diagram to illustrate how net primary production (NPP) is a combination of microbial growth and biomass. In this context, growth is controlled by three limiting factors (nutrients, light and temperature), while biomass is affected by grazing. The grey lines in the plots represent results from different Coupled Model Intercomparison Project […]'''
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Figure 5.12 | A schematic diagram to illustrate how net primary production (NPP) is a combination of microbial growth and biomass. In this context, growth is controlled by three limiting factors (nutrients, light and temperature), while biomass is affected by grazing. The grey lines in the plots represent results from different Coupled Model Intercomparison Project Phase 5 (CMIP5) models as reported by Laufkötter et al. (2015) <sup>[[#fn:r353|353]]</sup> . Poorly understood feedbacks from upper trophic levels on autotroph biomass and nutrients are represented by dashed arrows.

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