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The inventory and variability of oceanic dissolved inorganic carbon (DIC) is driven by the interplay of physical, chemical, and biological processes. Quantifying the spatiotemporal variability of these drivers is crucial for a mechanistic understanding of the ocean carbon sink and its future trajectory. Here, we use the Estimating the Circulation and Climate of the Ocean-Darwin ocean biogeochemistry state estimate to generate a global-ocean, data-constrained DIC budget and investigate how spatial and seasonal-to-interannual variability in three-dimensional circulation, air-sea CO2 flux, and biological processes have modulated the ocean sink for 1995-2018. Our results demonstrate substantial compensation between budget terms, resulting in distinct upper-ocean carbon regimes. For example, boundary current regions have strong contributions from vertical diffusion while equatorial regions exhibit compensation between upwelling and biological processes. When integrated across the full ocean depth, the 24-year DIC mass increase of 64 Pg C (2.7 Pg C year-1) primarily tracks the anthropogenic CO2 growth rate, with biological processes providing a small contribution of 2% (1.4 Pg C). In the upper 100 m, which stores roughly 13% (8.1 Pg C) of the global increase, we find that circulation provides the largest DIC gain (6.3 Pg C year-1) and biological processes are the largest loss (8.6 Pg C year-1). Interannual variability is dominated by vertical advection in equatorial regions, with the 1997-1998 El Niño-Southern Oscillation causing the largest year-to-year change in upper-ocean DIC (2.1 Pg C). Our results provide a novel, data-constrained framework for an improved mechanistic understanding of natural and anthropogenic perturbations to the ocean sink.

While much attention has been paid to the climatic controls of species' range limits, other factors such as dispersal limitation are also important. Temperature is an important control of the distribution of coastal mangrove forests, and mangrove expansion at multiple poleward range limits has been linked to increasing temperatures. However, mangrove abundances at other poleward range limits have been surprisingly insensitive to climate change, indicating other drivers of range limitation. For example, along the west coast of North America, the poleward mangrove range limits are found on the Baja California and mainland coasts of Mexico, between 26°48ʹ and 30°18ʹN. Non‐climatic factors may play an important role in setting these range limits as 1) the abundance of range limit populations has been relatively insensitive to climate variability and 2) an introduced population of mangroves has persisted hundreds of kilometers north of the natural range limits. We combined a species distribution model with a high‐resolution oceanographic transport model to identify the roles of climate and dispersal limitation in controlling mangrove distributions. We identified estuarine habitat that is likely climatically suitable for mangroves north of the current range limits. However, propagules from current mangrove populations are unlikely to reach these suitable locations due to prevailing ocean currents and geomorphic factors that create a patchy distribution of estuarine habitat with large between‐patch distances. Thus, although climate change is driving range shifts of mangroves in multiple regions around the world, dispersal is currently limiting poleward mangrove expansion at several range limits, including the west coast of North America. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) is a greenhouse gas and stratospheric ozone‐depleting substance with large and growing anthropogenic emissions. Previous studies identified the influx of N2O‐depleted air from the stratosphere to partly cause the seasonality in tropospheric N2O (aN2O), but other contributions remain unclear. Here, we combine surface fluxes from eight land and four ocean models from phase 2 of the Nitrogen/N2O Model Intercomparison Project with tropospheric transport modeling to simulate aN2O at eight remote air sampling sites for modern and pre‐industrial periods. Models show general agreement on the seasonal phasing of zonal‐average N2O fluxes for most sites, but seasonal peak‐to‐peak amplitudes differ several‐fold across models. The modeled seasonal amplitude of surface aN2O ranges from 0.25 to 0.80 ppb (interquartile ranges 21%–52% of median) for land, 0.14–0.25 ppb (17%–68%) for ocean, and 0.28–0.77 ppb (23%–52%) for combined flux contributions. The observed seasonal amplitude ranges from 0.34 to 1.08 ppb for these sites. The stratospheric contributions to aN2O, inferred by the difference between the surface‐troposphere model and observations, show 16%–126% larger amplitudes and minima delayed by ∼1 month compared to Northern Hemisphere site observations. Land fluxes and their seasonal amplitude have increased since the pre‐industrial era and are projected to grow further under anthropogenic activities. Our results demonstrate the increasing importance of land fluxes for aN2O seasonality. Considering the large model spread, in situ aN2O observations and atmospheric transport‐chemistry models will provide opportunities for constraining terrestrial and oceanic biosphere models, critical for projecting carbon‐nitrogen cycles under ongoing global warming. Plain Language Summary: Anthropogenic N2O emissions, for example, from fertilizer use on agricultural land, fossil fuel burning, and some industrial activities, continue to increase atmospheric N2O to values unprecedented for at least the past 800,000 years. This increase causes harmful global warming and stratospheric ozone depletion. Understanding how N2O emissions from land and ocean influence atmospheric composition and climate is a research priority. Here, we address specifically how land and ocean emissions contribute to the seasonality of N2O at eight air monitoring sites. We apply surface N2O fluxes simulated by eight land biosphere and four ocean biogeochemical models with a representation of lower atmosphere transport. This study complements earlier studies that show a strong influence on N2O seasonality by the influx of N2O‐depleted air from the upper atmosphere. We demonstrate that land biosphere and ocean surface fluxes contribute substantially to the observed seasonal cycle at the different measurement sites. The surface contributions dampen the seasonal signal from the upper atmosphere and must be considered for explaining the observed N2O seasonality. However, surface fluxes differ widely across models. In future work, atmospheric N2O observations and transport modeling, considering both lower and upper atmospheric contributions, may help to better constrain biosphere models. Key Points: Model land biosphere and ocean surface fluxes are combined with tropospheric transport to simulate N2O seasonality at eight monitoring sitesSurface N2O fluxes contribute substantially to the observed seasonality of tropospheric N2O, partly offsetting stratospheric contributionLarge spread in seasonal land fluxes calls for biosphere model improvements, for example, using N2O observations and transport‐chemistry modeling [ABSTRACT FROM AUTHOR]

Ice calved from the Antarctic and Greenland Ice Sheets or tidewater glaciers ultimately melts in the ocean contributing to sea-level rise. Icebergs have also been described as biological hotspots due to their potential roles as platforms for marine mammals and birds, and as micronutrient fertilizing agents. Icebergs may be especially important in the Southern Ocean where availability of the micronutrients iron and manganese extensively limits marine primary production. Whilst icebergs have long been described as a source of iron to the ocean, their nutrient signature is poorly constrained and it is unclear if there are regional differences. Here we show that 589 ice fragments collected from floating ice in contrasting regions spanning the Antarctic Peninsula, Greenland, and smaller tidewater systems in Svalbard, Patagonia and Iceland have similar characteristic (micro)nutrient signatures with limited or no significant differences between regions. Icebergs are a minor or negligible source of macronutrients to the ocean with low concentrations of NOx (NO3 + NO2, median 0.51 µM), PO4 (median 0.04 µM), and dissolved Si (dSi, median 0.02 µM). In contrast, icebergs deliver elevated concentrations of dissolved Fe (dFe; mean 82 nM, median 12 nM) and Mn (dMn; mean 26 nM, median 2.6 nM). A tight correlation between total dissolvable Fe and Mn (R2 = 0.95) and a Mn:Fe ratio of 0.024 suggested a lithogenic origin for the majority of sediment present in ice. Total dissolvable Fe and Mn retained a strong relationship with sediment load (both R2 = 0.43, p<0.001), whereas weaker relationships were observed for dFe, dMn and dSi. Sediment load for Antarctic ice (median 9 mg L-1, n=144) was low compared to prior reported values for the Arctic. A particularly curious incidental finding was that melting samples of ice were observed to rapidly lose their sediment load, even when sediment layers were embedded within the ice and stored in the dark. Our results demonstrated that the nutrient signature of icebergs is consistent with an atmospheric source of NOx and PO4. Conversely, high Fe and Mn, and modest dSi concentrations, are associated with englacial sediment, which experiences limited biogeochemical processing prior to release into the ocean. [ABSTRACT FROM AUTHOR]

As a contribution to the Regional Carbon Cycle Assessment and Processes phase 2 (RECCAP2) project, we present synthesized estimates of Arctic Ocean sea‐air CO2 fluxes and their uncertainties from surface ocean pCO2‐observation products, ocean biogeochemical hindcast and data assimilation models, and atmospheric inversions. For the period of 1985–2018, the Arctic Ocean was a net sink of CO2 of 116 ± 4 TgC yr−1 in the pCO2 products, 92 ± 30 TgC yr−1 in the models, and 91 ± 21 TgC yr−1 in the atmospheric inversions. The CO2 uptake peaks in late summer and early autumn, and is low in winter when sea ice inhibits sea‐air fluxes. The long‐term mean CO2 uptake in the Arctic Ocean is primarily caused by steady‐state fluxes of natural carbon (70% ± 15%), and enhanced by the atmospheric CO2 increase (19% ± 5%) and climate change (11% ± 18%). The annual mean CO2 uptake increased from 1985 to 2018 at a rate of 31 ± 13 TgC yr−1 dec−1 in the pCO2 products, 10 ± 4 TgC yr−1 dec−1 in the models, and 32 ± 16 TgC yr−1 dec−1 in the atmospheric inversions. Moreover, 77% ± 38% of the trend in the net CO2 uptake over time is caused by climate change, primarily due to rapid sea ice loss in recent years. Furthermore, true uncertainties may be larger than the given ensemble standard deviations due to common structural biases across all individual estimates. Plain Language Summary: The Arctic Ocean is at present a net sink for atmospheric CO2 mainly due to the intense cooling of the inflowing waters from the Atlantic and the Pacific. Global warming is amplified in the Arctic Ocean and it experiences a rapid retreat of sea ice. Here, we present synthesized estimates of the Arctic Ocean CO2 uptake and their uncertainties from estimates obtained using different methods. Almost all estimates suggest that the Arctic Ocean was a net sink of CO2 from 1985 to 2018. The CO2 uptake is strong in late summer and early autumn and weak in winter, corresponding to the seasonal variation of sea ice. CO2 uptake has increased in recent years, especially in regions that have experienced sea ice loss. Compared to the global ocean, the Arctic Ocean is unique because climate change, in particular the change in sea ice cover, has enhanced the ocean CO2 uptake almost as much as the increase in atmospheric CO2 over the past 34 years. Moreover, this climate effect on the Arctic Ocean CO2 uptake has become more important in recent years and is the current main driver for the trend toward an increasing CO2 uptake in the Arctic Ocean. Key Points: The Arctic Ocean is estimated to be a net sink of CO2 of 116 ± 4 TgC yr−1 in pCO2 products and 92 ± 30 TgC yr−1 in ocean modelsThe Arctic Ocean CO2 uptake is explained by a steady‐state natural flux (70%) with atmospheric CO2 increase (19%) and climate change (11%)The CO2 uptake increased (31 ± 13 TgC yr−1 dec−1 in products and 10 ± 4 TgC yr−1 dec−1 in models) mostly by decreasing sea ice [ABSTRACT FROM AUTHOR]

Latitudinal range limits for mangroves on high‐energy, wave‐dominated coasts are controlled by geomorphological features and estuarine dynamics. Mangroves reach a southern global range limit along the South African coastline, but the distribution is patchy, with stands occurring in only 16% of the estuaries in the region. Yet, the persistence of forests planted >50 years ago beyond the natural distribution limit suggests that additional estuaries could support mangroves. Understanding regional drivers is necessary to inform global‐scale estimates for how this important ecosystem is predicted to respond to climate change.Here, we combine species distribution modelling (MaxEnt), Lagrangian particle tracking using an eddy‐ and tide‐resolving numerical ocean model, and connectivity matrices, to identify suitable mangrove habitats along the South African coastline at present, as well as under the IPCC RCP4.5 and RCP8.5 climate scenarios.Within the current South African distribution range (±900 km), eight more estuaries were identified to be suitable under contemporary conditions. When considering potential range extension (±110 km), an additional 14 suitable estuaries were identified. Connectivity matrices suggest limited long‐distance dispersal, stranding mostly at or near the release location, and a decreased probability of connectivity towards the range limit. Under both future climate scenarios, 30% of estuaries currently supporting mangroves are predicted to become unsuitable, while an additional six estuaries beyond the current distribution are predicted to become suitable. However, there is limited connectivity between these new sites and established forests.Synthesis. This study shows that dispersal substantially limits mangrove distribution at the southern African range limit and highlights the importance of including this process in species distribution models. Ultimately, our results provide new insight into mangrove conservation and management at range limits that are not controlled predominantly by temperature, as it has been assumed that mangroves will largely expand to higher latitudes under climate change. [ABSTRACT FROM AUTHOR]