Climate change projections to the year 2100 may miss physical-biogeochemical feedbacks that emerge later from the cumulative effects of climate warming. In a coupled climate simulation to the year ...2300, the westerly winds strengthen and shift poleward, surface waters warm, and sea ice disappears, leading to intense nutrient trapping in the Southern Ocean. The trapping drives a global-scale nutrient redistribution, with net transfer to the deep ocean. Ensuing surface nutrient reductions north of 30°S drive steady declines in primary production and carbon export (decreases of 24 and 41%, respectively, by 2300). Potential fishery yields, constrained by lower-trophic-level productivity, decrease by more than 20% globally and by nearly 60% in the North Atlantic. Continued high levels of greenhouse gas emissions could suppress marine biological productivity for a millennium.
Ocean carbon uptake and storage simulated by the Community Earth System Model, version 1–Biogeochemistry CESM1(BGC), is described and compared to observations. Fully coupled and ocean-ice ...configurations are examined; both capture many aspects of the spatial structure and seasonality of surface carbon fields. Nearly ubiquitous negative biases in surface alkalinity result from the prescribed carbonate dissolution profile. The modeled sea–air CO₂ fluxes match observationally based estimates over much of the ocean; significant deviations appear in the Southern Ocean. Surface oceanpCO₂ is biased high in the subantarctic and low in the sea ice zone. Formation of the water masses dominating anthropogenic CO₂ (Cant) uptake in the Southern Hemisphere is weak in the model, leading to significant negative biases in Cantand chlorofluorocarbon (CFC) storage at intermediate depths. Column inventories of Cantappear too high, by contrast, in the North Atlantic. In spite of the positive bias, this marks an improvement over prior versions of the model, which underestimated North Atlantic uptake. The change in behavior is attributable to a new parameterization of density-driven overflows. CESM1(BGC) provides a relatively robust representation of the ocean–carbon cycle response to climate variability. Statistical metrics of modeled interannual variability in sea–air CO₂ fluxes compare reasonably well to observationally based estimates. The carbon cycle response to key modes of climate variability is basically similar in the coupled and forced ocean-ice models; however, the two differ in regional detail and in the strength of teleconnections.
We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework ...of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2–16 % and EP by 7–18 %. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positive biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface–ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. Community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.
Nutrient supply regulates the activity of phytoplankton, but the global biogeography of nutrient limitation and co-limitation is poorly understood.
adapt to local environments by gene gains and ...losses, and we used genomic changes as an indicator of adaptation to nutrient stress. We collected metagenomes from all major ocean regions as part of the Global Ocean Ship-based Hydrographic Investigations Program (Bio-GO-SHIP) and quantified shifts in genes involved in nitrogen, phosphorus, and iron assimilation. We found regional transitions in stress type and severity as well as widespread co-stress.
stress genes, bottle experiments, and Earth system model predictions were correlated. We propose that the biogeography of multinutrient stress is stoichiometrically linked by controls on nitrogen fixation. Our omics-based description of phytoplankton resource use provides a nuanced and highly resolved description of nutrient stress in the global ocean.
Selective removal of nitrogen (N) and phosphorus (P) from the marine dissolved organic matter (DOM) pool has been reported in several regional studies. Because DOM is an important advective/mixing ...pathway of carbon (C) export from the ocean surface layer and its non‐Redfieldian stoichiometry would affect estimates of marine export production per unit N and P, we investigated the stoichiometry of marine DOM and its remineralization globally using a compiled DOM data set. Marine DOM is enriched in C and N compared to Redfield stoichiometry, averaging 317:39:1 and 810:48:1 for C:N:P within the degradable and total bulk pools, respectively. Dissolved organic phosphorus (DOP) is found to be preferentially remineralized about twice as rapidly with respect to the enriched C:N stoichiometry of marine DOM. Biogeochemical simulations with the Biogeochemical Elemental Cycling model using Redfield and variable DOM stoichiometry corroborate the need for non‐Redfield dynamics to match the observed DOM stoichiometry. From our model simulations, preferential DOP remineralization is found to increase the strength of the biological pump by ~9% versus the case of Redfield DOM cycling. Global net primary productivity increases ~10% including an increase in marine nitrogen fixation of ~26% when preferential DOP remineralization and direct utilization of DOP by phytoplankton are included. The largest increases in marine nitrogen fixation, net primary productivity, and carbon export are observed within the western subtropical gyres, suggesting the lateral transfer of P in the form of DOP from the productive eastern and poleward gyre margins may be important for sustaining these processes downstream in the subtropical gyres.
Key Points
Marine DOM and its remineralization exhibit non‐Redfield C:N:P stoichiometry
Preferential remineralization of DOP increases marine N2‐fixation by 26%
Marine DOC export increases global export production by 24%
Metal dissolution from atmospheric aerosol deposition to the oceans is important in enhancing and inhibiting phytoplankton growth rates and modifying plankton community structure, thus impacting ...marine biogeochemistry. Here we review the current state of knowledge on the causes and effects of the leaching of multiple trace metals from natural and anthropogenic aerosols. Aerosol deposition is considered both on short timescales over which phytoplankton respond directly to aerosol metal inputs, as well as longer timescales over which biogeochemical cycles are affected by aerosols.
The authors compare Community Earth System Model results to marine observations for the 1990s and examine climate change impacts on biogeochemistry at the end of the twenty-first century under two ...future scenarios (Representative Concentration Pathways RCP4.5 and RCP8.5). Late-twentieth-century seasonally varying mixed layer depths are generally within 10 m of observations, with a Southern Ocean shallow bias. Surface nutrient and chlorophyll concentrations exhibit positive biases at low latitudes and negative biases at high latitudes. The volume of the oxygen minimum zones is overestimated.
The impacts of climate change on biogeochemistry have similar spatial patterns under RCP4.5 and RCP8.5, but perturbation magnitudes are larger under RCP8.5. Increasing stratification leads to weaker nutrient entrainment and decreased primary and export production (>30% over large areas). The global-scale decreases in primary and export production scale linearly with the increases in mean sea surface temperature. There are production increases in the high nitrate, low chlorophyll (HNLC) regions, driven by lateral iron inputs from adjacent areas. The increased HNLC export partially compensates for the reductions in non-HNLC waters (∼25% offset). Stabilizing greenhouse gas emissions and climate by the end of this century (as in RCP4.5) will minimize the changes to nutrient cycling and primary production in the oceans. In contrast, continued increasing emission of CO₂ (as in RCP8.5) will lead to reduced productivity and significant modifications to ocean circulation and biogeochemistry by the end of this century, with more drastic changes beyond the year 2100 as the climate continues to rapidly warm.
Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in ...climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from 13 global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES program, we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron fertilization experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.
Key Points
First intercomparison of 13 global iron models highlights key challenges in reproducing iron data
Wide uncertainty in iron input fluxes, which results in poorly constrained residence times
Reducing uncertainty in scavenging and biological cycling is a priority
A large database of field estimates of phytoplankton community growth rates in natural populations was compiled and analyzed to determine the apparent temperature effect on phytoplankton community ...growth rate. We conducted an ordinary least squares regression to optimize the parameters in two commonly used growth‐temperature relations (Arrhenius and Q10 models). Both equations fit the observational data equally with the optimized parameter values. The optimum apparent Q10 value was 1.47 ± 0.08 (95% confidence interval, CI). Microzooplankton grazing rates closely matched the temperature trends for phytoplankton growth. This likely reflects a dynamic adjustment of biomass and grazing rates by the microzooplankton to match their available food source, illustrating tight coupling of phytoplankton growth and microzooplankton grazing rates. The field‐measured temperature effect and growth rates were compared with estimates from the satellite Carbon‐based Productivity Model (CbPM) and three Earth System Models (ESMs), with model output extracted at the same month and sampling locations as the observations. The optimized, apparent Q10 value calculated for the CbPM was 1.51, with overestimation of growth rates. The apparent Q10 value in the Community Earth System Model (V1.0) was 1.65, with modest underestimation of growth rates. The GFDL‐ESM2M and GFDL‐ESM2G models produced apparent Q10 values of 1.52 and 1.39, respectively. Models with an apparent Q10 that is significantly greater than ~1.5 will overestimate the phytoplankton community growth response to the ongoing climate warming and will have spatial biases in estimated growth rates for the current era.
Key Points
Estimations of Q10 and Arrhenius equation parameters were made using field‐measured phytoplankton community growth rates
The Arrhenius and Q10 equations do an equally good job of estimating the temperature dependence of phytoplankton community growth rates
The optimal apparent Q10 value is 1.5. Models should capture a community growth‐temperature response equal to this value to avoid bias
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