Sinking particles of organic matter transfer 5–10 Pg C per year from the upper ocean to the ocean interior as part of a process known as the biological pump. As these particles sink, they are remineralized through bacterial- and zooplankton-related activity, releasing the carbon and nutrients back into solution at depth. Vertical fluxes of particulate organic carbon (POC) in the water column have historically been described by the Martin curve, a power-law function that describes the rapid decrease in flux (Fz) from a maximum value at depth z0, nominally the base of the mixed layer, to a small asymptotic value in deep waters Fig. ; Eq. ;: 1Fz=Fz0zz0-b.

The dimensionless exponent in the power law (b) describes whether organic matter is remineralized predominantly at shallower depths (larger values of b; e.g. b=1.6) or deeper in the water column (smaller values of b; e.g. b=0.4) (Fig. ). The exponent itself parameterizes the rate at which POC sinks through the water column (units of m d-1) and the rate at which it is remineralized (units of d-1; ). In this paper we use the term “remineralization depth”, defined as a depth at which a defined % of POC has been remineralized. Previously, this has been defined as an e folding depth: the depth at which ∼63 % of POC has been remineralized (; although note that the Martin curve is not exponential).

Ocean biogeochemical models predict that the concentration of CO2 in the atmosphere is sensitive to changes in a globally uniform remineralization depth. showed that a deepening of the remineralization depth globally of 24 m (from b=1.0 to 0.9) redistributed dissolved inorganic carbon (DIC) from the intermediate waters to the deep ocean, leading to a reduction in atmospheric CO2 of between 10 and 27 ppm. The drawdown was also associated with a decrease in the global mean concentration of preformed nutrients in the ocean interior nutrients that are not utilised by biology in the surface ocean and enter the ocean interior via circulation;. found that an increase in respired carbon in the deep ocean was balanced by a reduction in preformed nutrients exported in the North Atlantic. Deepening of the POC remineralization depth could also drive dissolution of calcium carbonate (CaCO3) in ocean sediments, ultimately drawing down more CO2 over millennial timescales . The potential impact of remineralization depth changes on atmospheric CO2 is therefore a highly relevant component of the marine carbon cycle for both past and current changes in climate .

Analyses of global sediment trap observations suggest there is a spatially heterogeneous pattern of remineralization depths in the modern ocean that varies particularly with latitude. A synthesis of observations from deep sediment traps >1500–2000 m; suggests that POC fluxes in high latitudes attenuate faster with depth (shallower remineralization depth: b=1.6) than in low latitudes, where a greater proportion of POC is transported to depth (deeper remineralization depth: b=0.4); see Fig. ). However, POC fluxes measured using neutrally buoyant sediment traps at shallower depths (<1000 m) suggest the inverse of this latitudinal pattern ; see also . A recent compilation of sediment trap data and profiles of particle size distributions observed in the water column highlight additional intra-basin variability in b (e.g. shallower remineralization in the eastern equatorial Pacific than in the western equatorial Pacific) and inter-basin variability (e.g. deeper remineralization in the Atlantic and Indian basins compared to the Pacific) . The uncertainty in the spatial variability of remineralization depths presents a challenge for determining which mechanisms may be responsible for changes in remineralization depths and how these might drive future or past changes in remineralization e.g.. Additionally, this also presents a challenge for biogeochemical models, which are beginning to resolve the mechanisms that are potentially responsible for these spatial patterns, such as particle-size-dependent sinking rates , temperature-dependent remineralization , and oxygen dependence .

A key question in light of the observed spatial variability in remineralization depths and the associated uncertainty in spatial patterns is what the sensitivity of atmospheric CO2 concentrations to spatial variability in remineralization depths is. further quantified the sensitivity of atmospheric CO2 to basin-scale changes in remineralization depths by perturbing them in each basin individually, finding that the Pacific, Southern Ocean (defined as >40∘ S), Atlantic, and Indian oceans contributed 38 %, 22 %, 21 %, and 19 % of the total CO2 drawdown, respectively . The variability in CO2 sensitivity between basins matched the variability in the magnitude of export production integrated over the basins and basin area, suggesting that no one region was more significant when varying the globally uniform remineralization depth . However, this basin-scale analysis does not resolve the sensitivity of atmospheric CO2 occurring at the resolution suggested by observations, i.e. a latitudinal and within-basin scale, or at the resolution of ecological and biogeochemical variability . Additionally, the analysis does not allow for the identification of potential interactions and feedbacks between regions when remineralization depths are changing simultaneously.

Here we aim to address these issues by performing a global sensitivity analysis of regionally varying remineralization depths. To this end, we use a transport matrix (a steady-state, computationally efficient representation of ocean transport) derived from the MIT global circulation model (MITgcm) with a model of phosphorus and carbon cycling where the ocean is divided into 15 regions in which remineralization depths can change independently. Remineralization depths are perturbed simultaneously using Latin hypercube sampling and sensitivity quantified using regression analysis,.

Sediment trap observations reveal significant spatial variability in remineralization depths. Here we have quantified the sensitivity of atmospheric CO2 to regional changes in remineralization depths and show that CO2 is most sensitive to changes in the subantarctic regions. Much of the observed spatial variability varies across latitudes . Additionally, the mechanisms potentially driving these patterns are also likely to vary on a latitudinal basis, with changes in related environmental properties in response to anthropogenic CO2 emissions affecting the high latitudes in particular: temperature changes affecting temperature-dependent remineralization rates, a reduction in carbonate saturation state with ocean acidification affecting ballasting and changes in plankton community composition, and cell size affecting aggregation dynamics and particle sinking velocities. Additionally, this is a consideration for changes in remineralization depths occurring in past climates . This suggests that the spatial patterns in CO2 sensitivity could be significant when considering the impact of remineralization depth changes.

Changes in the air–sea balance of carbon are commonly related to changes in preformed nutrients. Because of the inefficient utilization of upwelled nutrients in the Southern Ocean, this region has been identified as key to setting the efficiency of the biological pump . Our results show that this is also key for the sensitivity of CO2 to regional variability in remineralization depths because of upwelling in subantarctic regions (Fig. ). This relationship has implications when invoking changes in the efficiency of the biological pump in past climates such as the Last Glacial Maximum (LGM). Processes that increase the utilization of nutrients in the Southern Ocean, such as iron fertilization, and processes that reduce the delivery of nutrients to the Southern Ocean, such as increased stratification, have been implicated in the drawdown of atmospheric CO2 during the LGM . Any changes in stratification will also impact the sensitivity of CO2 to any additional changes in remineralization depths, such as from changes in ballasting minerals and/or temperature-dependent remineralization . In comparison, processes such as iron fertilization will not impact on this sensitivity. Because the spatial patterns of CO2 sensitivity to regional changes in remineralization are predominantly constrained by ocean circulation pathways, this also suggests that the sensitivity may change with a reorganization of ocean circulation as suggested for the LGM .

The Martin curve is a commonly used parameterization of the remineralization of particulate organic matter with depth in marine biogeochemical models and is commonly applied with a globally uniform exponent (b) . However, the Martin curve used in this way has potential limitations: it is an empirical and static parameterization that does not represent the mechanisms affecting remineralization and sinking rates and it does not capture spatial variability in remineralization observed in sediment trap data . In our sensitivity analysis, we have shown that CO2 has a similar sensitivity to the global mean change in b, as compared to a globally uniform change in b with an uncertainty of ±5–15 ppm, equivalent to a change in b of ∼0.2 (Fig. ). suggest a decrease of 0.3 from the modern remineralization depth is sufficient to explain the increase in deep ocean nutrient concentrations during the Last Glacial Maximum. For the 21st century, predict a decrease in POC export at 500 m by 2100 under RCP8.5 in response to temperature- and oxygen-dependent remineralization, equivalent to a decrease in b of ∼0.25. As such, the global mean change in potential future and past changes in remineralization depth may be larger than the uncertainty associated with spatial variability. This has potentially useful implications for modelling the remineralization of particulate organic matter fluxes. Models resolving the various processes that affect remineralization rates and sinking velocities have recently been developed ; however, the requirements to model processes such as particle aggregation can be computationally expensive, limiting their application to 1-D models or to offline models . A globally uniform change in b informed by these models could then be used to calculate the impact on atmospheric CO2 if the change in b is greater than 0.2. However, we note that the modern global mean b is subject to uncertainty associated with under-sampled spatial variability.

Our results are dependent on the use of transport matrices derived from one global circulation model. Whilst this model has been widely applied to study biogeochemistry previously, it is subject to a number of caveats. The ocean model predicts significantly larger outcrops of dense water in the Southern Ocean compared to observations see Fig. S3 in Supplement, also, leading to deep-water formation occurring at latitudes around 50∘ S (Fig. S4 in Supplement). The volumetric fraction of water in the ocean interior derived from the subantarctic is also higher (26 %) compared to data-constrained estimates 18 %, Table S1:. As such, the sensitivity estimates for the subantarctic may be overestimated. This is also consistent with the higher sensitivity compared to the basin-scale analysis of , who found that the Southern Ocean (>40∘ S) contributed 22 % of the global CO2 sensitivity, compared with 36 % in this study (>38∘ S, see Table ). However, our results have key similarities, including absolute and relative magnitudes of regional preformed PO4 export, to other studies using alternative steady-state circulation states . As such, our results should be broadly reproducible with other models. A disadvantage to using a steady-state circulation is that we cannot quantify impact of the CO2–climate feedback on ocean circulation and atmospheric CO2. Studies exploring the simultaneous effects of warming temperatures on circulation and biology in response to anthropogenic CO2 emissions show that changes in circulation could be as important as biological changes (; ). Quantifying the regional sensitivity with a dynamic ocean is therefore an important focus for future work. Ratios of CaCO3 to POC vary latitudinally, and could also therefore modify our sensitivity results. found important feedbacks involving interactions between calcifiers and silicifiers in an marine ecosystem model when exploring temperature-dependent remineralization rates in the 21st century. Future model experiments including a representation of plankton ecosystems would therefore help explore the impact of CaCO3 export on regional sensitivity patterns.

We have presented a sensitivity analysis that quantifies the sensitivity of atmospheric CO2 to regional variability in particulate organic carbon remineralization depths. CO2 is most sensitive to changes in remineralization depths occurring in the subantarctic regions, particularly in the Indian Ocean sector. As a whole, the subantarctic regions have a sensitivity similar to that of the Pacific basin despite the smaller area and levels of production. Sensitivity patterns are in part a function of the magnitude of export production in each region and the physical circulation pathways specific to each region. Whilst the overall magnitude of CO2 sensitivity to regional changes is dependent on the magnitude and response of export production to changes in nutrients, the relative spatial patterns in sensitivity are predominantly constrained by ocean circulation pathways. We also find that the regional variability adds ±5–15 ppm uncertainty to global mean changes in remineralization depths. The regional patterns in sensitivity could be significant if a number of processes that potentially drive changes in remineralization depths, including temperature-dependent remineralization rates and plankton community structure, vary predominantly in the high latitudes. However, this uncertainty is similar to the change in CO2 for a globally uniform change in b of ∼0.2, meaning that larger changes in b could be reliably approximated by a globally uniform b as commonly used in biogeochemical models.