Climate-carbon Cycle Research Articles

Evaluation of NPP using three models compared with MODIS-NPP data over China.

Estimating net primary productivity (NPP) is significant in global climate change research and carbon cycle. However, there are many uncertainties in different NPP modeling results and the process of NPP is challenging to model on the absence of data. In this study, we used meteorological data as input to simulate vegetation NPP through climate-based model, synthetic model and CASA model. Then, the results from three models were compared with MODIS NPP and observed data over China from 2000 to 2015. The statistics evaluation metrics (Relative Bias (RB), Pearson linear Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE)) between simulated NPP and MODIS NPP were calculated. The results implied that the CASA-model performed better than the other two models in terms of RB, RMSE, NSE and CC whether on the national or the regional scale. It has a higher CC with 0.51 and a smaller RMSE with 111.96 g C·m-2·yr-1 in the whole country. The synthetic model and CASA-model has the same advantages at some regions, and there are lower RMSE in Southern China (86.35 g C·m-2·yr-1), Xinjiang (85.53 g C·m-2·yr-1) and Qinghai-Tibet Plateau (93.22 g C·m-2·yr-1). The climate-based model has widespread overestimation and large systematic errors, along with worse performances (NSEmax = 0.45) and other metric indexes unsatisfactory, especially Qinghai-Tibet Plateau with relatively lower accuracy because of the unavailable observation data. Overall, the CASA-model is much more ideal for estimating NPP all over China in the absence of data. This study provides a comprehensive intercomparison of different NPP-simulated models and can provide powerful help for researchers to select the appropriate NPP evaluation model.

Molecular chemodiversity of water-soluble organic matter in atmospheric particulate matter and their associations with atmospheric conditions

Water-soluble organic matter (WSOM) is a complex mixture of organic compounds affecting global climate change and carbon cycle. Herein, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used for identification of WSOM molecular compositions in annual atmospheric particulate matter with diameters ≤10 μm (PM10). Totally 6538 unambiguous monoisotopic molecular formulas were assigned to WSOM with m/z values concentrating in 150–600 Da. The CHO compounds with high unsaturation degrees contributed most (51.7–52.1%) to WSOM in spring and summer. However, the S-containing compounds (CHOS and CHNOS) with higher O/C and H/C ratios accounted for 56.8–63.2% of WSOM in autumn and winter. Temperature (r = 0.82) and O3 (r = 0.89) showed higher correlation with CHO compounds, which were mainly aliphatics and highly unsaturated structures with high oxygen compounds (80.7–90.8%). The concentrations of SO42− (r = 0.33) and NO3− (r = 0.46) in PM10 both showed a positive correlation with the abundances of the S-containing compounds due to their direct participation in atmospheric reactions. Among them, 96–100% and 78–96% of the CHOS and CHNOS compounds were confirmed to be organosulfates (OSs) and nitrooxy-organosulfates (NOSs) by MS/MS analysis, respectively. These findings illustrate the strong association of atmospheric conditions with molecular chemodiversity of WSOM.

A model for marine sedimentary carbonate diagenesis and paleoclimate proxy signal tracking: IMP v1.0

Abstract. The preservation of calcium carbonate in marine sediments is central to controlling the alkalinity balance of the ocean and, hence, the ocean–atmosphere partitioning of CO2. To successfully address carbon cycle–climate dynamics on geologic (≫1 kyr) timescales, Earth system models then require an appropriate representation of the primary controls on CaCO3 preservation. At the same time, marine sedimentary carbonates represent a major archive of Earth history, as they have the potential to preserve how seawater chemistry, isotopic composition, and even properties of planktic and benthic ecosystems, change with time. However, changes in preservation and even chemical erosion of previously deposited CaCO3, along with the biogenic reworking of upper portions of sediments, whereby sediment particles are translocated both locally and nonlocally between different depths in the sediments, all act to distort the recorded signal. Numerical models can aid in recovering what the “true” environmental changes might have been, but only if they appropriately account for these processes. Building on a classical 1-D reaction-transport framework, we present a new diagenetic model – IMP (Implicit model of Multiple Particles (and diagenesis)) – that simulates biogeochemical transformations in carbonate-hosted proxy signals by allowing for populations of solid carbonate particles to possess different physicochemical characteristics such as isotopic value, solubility and particle size. The model also utilizes a variable transition matrix to implement different styles of bioturbation. We illustrate the utility of the model for deciphering past environmental changes using several hypothesized transitions of seawater proxies obscured by sediment mixing and chemical erosion. To facilitate the use of IMP, we provide the model in Fortran, MATLAB and Python versions. We described IMP with integration into Earth system models in mind, and we present the description of this coupling of IMP with the “cGENIE.muffin” model in a subsequent paper.

In Support of a Renewable Energy and Materials Economy: A Global Green New Deal That Includes Arctic Sea Ice Triage and Carbon Cycle Restoration

A Global Green New Deal (GGND)—that includes Arctic sea ice climate triage and carbon cycle climate restoration, and that, following Eisenberger (2020), would move us toward a renewable energy and materials economy (REME)—is necessary to turn our current civilization and species-threatening climate crises into an opportunity to stabilize our planet’s climate and advance to a new, more equitable and prosperous stage of human development. Imminent, potentially catastrophic, global climate impacts of Arctic sea ice loss, the first global climate “tipping point,” are reviewed, and practical and efficient potential climate triage methods for avoiding this are summarized. Longer-term carbon dioxide removal (CDR) and carbon capture, sequestration, and use (CCSU) methods, that would move us toward long-term carbon cycle climate restoration, are presented. A general reframing of climate policy and specific GGND policy proposals—that include Arctic sea ice climate triage and carbon cycle climate restoration that would rapidly move us toward a REME and avoid increasingly catastrophic climate impacts—are proposed. JEL Classification: Q53, Q54, Q55, Q56, Q58

Implications of temperature overshoot dynamics for climate and carbon dioxide removal policies in the DICE model

Assessing climate policies that involve temporary overshoot of temperature targets requires an accurate representation of carbon cycle and climate dynamics. Here, we compare temperature overshoot climate policies obtained with the dynamic integrated climate–economy (DICE) integrated assessment model using two different climate-carbon cycle sub-models: first, the original DICE implementation, and second an implementation of the finite amplitude impulse response (FaIR) simple climate model. We analyze in a cost-effectiveness framework the minimum abatement and carbon dioxide removal costs for compliance against a (future) ceiling on temperatures. In our setup, the magnitude of the overshoot is not limited by temperature impacts, but simply by the temperature dynamics such that from a certain compliance date onwards a temperature ceiling cannot be exceeded anymore. We show that the rather sluggish temperature response and underestimation of carbon sinks in the most recent version of DICE implies that the additional future temperature change after a cessation of a given CO2 emission scenario is significantly overestimated compared to the zero emission commitments obtained with FaIR and complex earth system models. However, investigating climate policies which allow for a temporary temperature overshoot, this inertia translates into more than twice as high optimal carbon prices compared to FaIR and consequently in rather strict climate policies. For compliance with the 1.5 °C target from 2100 onward and non-CO2-warming of 0.2 °C, the mean optimal carbon prices in the year 2030 are 173USD/tCO2 and 56USD/tCO2 for DICE and FaIR, respectively. Still, the dynamics towards the target suggest that improved understanding of and accounting for (limited) reversibility of vulnerable Earth system components is required to derive appropriate overshoot climate policies.

Earth System Model Analysis of How Astronomical Forcing Is Imprinted Onto the Marine Geological Record: The Role of the Inorganic (Carbonate) Carbon Cycle and Feedbacks.

Astronomical cycles are strongly expressed in marine geological records, providing important insights into Earth system dynamics and an invaluable means of constructing age models. However, how various astronomical periods are filtered by the Earth system and the mechanisms by which carbon reservoirs and climate components respond, particularly in absence of dynamic ice sheets, is unclear. Using an Earth system model that includes feedbacks between climate, ocean circulation, and inorganic (carbonate) carbon cycling relevant to geological timescales, we systematically explore the impact of astronomically modulated insolation forcing and its expression in model variables most comparable to key paleoceanographic proxies (temperature, the δ13C of inorganic carbon, and sedimentary carbonate content). Temperature predominately responds to short and long eccentricity and is little influenced by the modeled carbon cycle feedbacks. In contrast, the cycling of nutrients and carbon in the ocean generates significant precession power in atmospheric CO2, benthic ocean δ13C, and sedimentary wt% CaCO3, while inclusion of marine sedimentary and weathering processes shifts power to the long eccentricity period. Our simulations produce reduced pCO2 and dissolved inorganic carbon (DIC) δ13C at long eccentricity maxima and, contrary to early Cenozoic marine records, CaCO3 preservation in the model is enhanced during eccentricity‐modulated warmth. Additionally, the magnitude of δ13C variability simulated in our model underestimates marine proxy records. These model‐data discrepancies hint at the possibility that the Paleogene silicate weathering feedback was weaker than modeled here and that additional organic carbon cycle feedbacks are necessary to explain the full response of the Earth system to astronomical forcing.

Asymmetry of extreme Cenozoic climate-carbon cycle events.

The history of Earth's climate and carbon cycle is preserved in deep-sea foraminiferal carbon and oxygen isotope records. Here, we show that the sub-million-year fluctuations in both records have exhibited negatively skewed non-Gaussian tails throughout much of the Cenozoic era (66 Ma to present), suggesting an intrinsic asymmetry that favors "hyperthermal-like" extreme events of abrupt global warming and oxidation of organic carbon. We show that this asymmetry is quantitatively consistent with a general mechanism of self-amplification that can be modeled using stochastic multiplicative noise. A numerical climate-carbon cycle model in which the amplitude of random biogeochemical fluctuations increases at higher temperatures reproduces the data well and can further explain the apparent pacing of past extreme warming events by changes in orbital parameters. Our results also suggest that, as anthropogenic warming continues, Earth's climate may become more susceptible to extreme warming events on time scales of tens of thousands of years.

Empirical evidence that manganese enrichment accelerates decomposition

Our understanding of the controls regulating the rate of litter decomposition is important for improving confidence in the parameterization of carbon cycle–climate feedbacks. Traditional conceptual models rely primarily on climate and lignin/N ratios as the main regulators of decomposition. Here we studied the effects of manganese (Mn) addition on long-term decomposition across 18 substrates in a laboratory incubation. Mn addition remarkably promoted later stage of decomposition, resulting into a smaller fraction of slowly decomposing litter. This dynamic is closely associated with the changes of activities of manganese peroxidase, an important enzyme with greater capacity for lignin degradation. Our findings suggest the necessity of incorporating the interaction of Mn and decomposition into biogeochemical models.

Asymmetry in the climate–carbon cycle response to positive and negative CO2 emissions

Asymmetry in the climate–carbon cycle response to positive and negative CO2 emissions

Temporally variable parameters simulate asymmetrical interannual variation of aboveground and belowground carbon pools in an alpine meadow

Exploring interannual variation (IAV) of terrestrial carbon cycle is crucial for understanding the climate-carbon cycle feedback. However, model simulations of IAV in carbon pools are highly sensitive to parameterization. Although researches indicate that parameters vary as environment changes, most terrestrial carbon cycle models apply time-invariant parameters, leading to uncertainty in reproducing IAV. We compared the IAV simulation accuracy of carbon pools between constant and temporally variable parameters, generated by a piecewise model-data fusion framework based on long-term multi-observations in an alpine meadow over the Tibetan Plateau. Piecewise assimilation showed that key parameters involved in photosynthesis and allocation processes exhibited significant temporal variation under warming and nitrogen deposition. Specifically, day length threshold for leaf senescence was postponed, while allocation to autotrophic respiration, allocation to root, leaf nitrogen content, and nitrogen use efficiency increased. Compared with constant parameters, temporally variable parameters captured the observed asymmetrical response of aboveground and belowground carbon pools to climate fluctuations, improved modeled magnitude of IAV in carbon pools by 34% on average, and advanced carbon sink estimation accuracy by 43.15%. Therefore, fitting parameter dynamics to climatic conditions can provide a benchmark for future simulation in the Tibetan Plateau. Our research suggests that IAV in different carbon pools is crucial in determining carbon sinks. Temporal variations of parameters present how ecosystems adapt to a changing environment and should be incorporated to terrestrial carbon cycle models to reduce uncertainty in model prediction.

A small climate-amplifying effect of climate-carbon cycle feedback

The climate-carbon cycle feedback is one of the most important climate-amplifying feedbacks of the Earth system, and is quantified as a function of carbon-concentration feedback parameter (β) and carbon-climate feedback parameter (γ). However, the global climate-amplifying effect from this feedback loop (determined by the gain factor, g) has not been quantified from observations. Here we apply a Fourier analysis-based carbon cycle feedback framework to the reconstructed records from 1850 to 2017 and 1000 to 1850 to estimate β and γ. We show that the β-feedback varies by less than 10% with an average of 3.22 ± 0.32 GtC ppm−1 for 1880–2017, whereas the γ-feedback increases from −33 ± 14 GtC K−1 on a decadal scale to −122 ± 60 GtC K−1 on a centennial scale for 1000–1850. Feedback analysis further reveals that the current amplification effect from the carbon cycle feedback is small (g is 0.01 ± 0.05), which is much lower than the estimates by the advanced Earth system models (g is 0.09 ± 0.04 for the historical period and is 0.15 ± 0.08 for the RCP8.5 scenario), implying that the future allowable CO2 emissions could be 9 ± 7% more. Therefore, our findings provide new insights about the strength of climate-carbon cycle feedback and about observational constraints on models for projecting future climate.

Five years of variability in the global carbon cycle: comparing an estimate from the Orbiting Carbon Observatory-2 and process-based models

Year-to-year variability in CO2 fluxes can yield insight into climate-carbon cycle relationships, a fundamental yet uncertain aspect of the terrestrial carbon cycle. In this study, we use global observations from NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite for years 2015–2019 and a geostatistical inverse model to evaluate 5 years of interannual variability (IAV) in CO2 fluxes and its relationships with environmental drivers. OCO-2 launched in late 2014, and we specifically evaluate IAV during the time period when OCO-2 observations are available. We then compare inferences from OCO-2 with state-of-the-art process-based models (terrestrial biosphere model, TBMs). Results from OCO-2 suggest that the tropical grasslands biome (including grasslands, savanna, and agricultural lands within the tropics) makes contributions to global IAV during the 5 year study period that are comparable to tropical forests, a result that differs from a majority of TBMs. Furthermore, existing studies disagree on the environmental variables that drive IAV during this time period, and the analysis using OCO-2 suggests that both temperature and precipitation make comparable contributions. TBMs, by contrast, tend to estimate larger IAV during this time and usually estimate larger relative contributions from the extra-tropics. With that said, TBMs show little consensus on both the magnitude and the contributions of different regions to IAV. We further find that TBMs show a wide range of responses on the relationships of CO2 fluxes with annual anomalies in temperature and precipitation, and these relationships across most of the TBMs have a larger magnitude than inferred from OCO-2. Overall, the findings of this study highlight large uncertainties in process-based estimates of IAV during recent years and provide an avenue for evaluating these processes against inferences from OCO-2.

Historical and future global burned area with changing climate and human demography

Summary Wildfires influence terrestrial carbon cycling and represent a safety risk, and yet a process-based understanding of their frequency and spatial distributions remains elusive. We combine satellite-based observations with an enhanced dynamic global vegetation model to make regionally resolved global assessments of burned area (BA) responses to changing climate, derived from 34 Earth system models and human demographics for 1860–2100. Limited by climate and socioeconomics, recent BA has decreased, especially in central South America and mesic African savannas. However, future simulations predict increasing BA due to changing climate, rapid population density growth, and urbanization. BA increases are especially notable at high latitudes, due to accelerated warming, and over the tropics and subtropics, due to drying and human ignitions. Conversely, rapid urbanization also limits BA via enhanced fire suppression in the immediate vicinity of settlements, offsetting the potential for dramatic future increases, depending on warming extent. Our analysis provides further insight into regional and global BA trends, highlighting the importance of including human demographic change in models for wildfire under changing climate.

Microbial community shifts reflect losses of native soil carbon with pyrogenic and fresh organic matter additions and are greatest in low-carbon soils.

Soil organic carbon (SOC) plays an important role in regulating global climate change, carbon and nutrient cycling in soils, and soil moisture. Organic matter (OM) additions to soils can affect the rate at which SOC is mineralized by microbes, with potentially important effects on SOC stocks. Understanding how pyrogenic organic matter (PyOM) affects the cycling of native SOC (nSOC) and the soil microbes responsible for these effects is important for fire-affected ecosystems as well as for biochar-amended systems. We used an incubation trial with five different soils from National Ecological Observatory Network sites across the US and 13C-labelled 350°C corn stover PyOM and fresh corn stover OM to trace nSOC-derived CO2 emissions with and without PyOM and OM amendments. We used high-throughput sequencing of rRNA genes to characterize bacterial, archaeal, and fungal communities and their response to PyOM and OM in soils that were previously stored at -80°C. We found that the effects of amendments on nSOC-derived CO2 reflected the unamended soil C status, where relative increases in C mineralization were greatest in low-C soils. OM additions produced much greater effects on nSOC-CO2 emissions than PyOM additions. Furthermore, the magnitude of microbial community composition change mirrored the magnitude of increases in nSOC-CO2, indicating a specific subset of microbes were likely responsible for the observed changes in nSOC mineralization. However, PyOM responders differed across soils and did not necessarily reflect a common "charosphere". Overall, this study suggests that soils that already have low SOC may be particularly vulnerable to short-term increases in SOC loss with OM or PyOM additions.Importance Soil organic matter (SOM) has an important role in global climate change, carbon and nutrient cycling in soils, and soil moisture dynamics. Understanding the processes that affect SOM stocks is important for managing these functions. Recently, understanding how fire-affected organic matter (or "pyrogenic" organic matter (PyOM)) affects existing SOM stocks has become increasingly important, both due to changing fire regimes, and to interest in "biochar" - pyrogenic organic matter that is produced intentionally for carbon management or as an agricultural soil amendment. We found that soils with less SOM were more prone to increased losses with PyOM (and fresh organic matter) additions, and that soil microbial communities changed more in soils that also had greater SOM losses with PyOM additions. This suggests that soils that already have low SOM content may be particularly vulnerable to short-term increases in SOM loss, and that a subset of the soil microbial community is likely responsible for these effects.

A small climate-amplifying effect of climate-carbon cycle feedback

A small climate-amplifying effect of climate-carbon cycle feedback

On the modeling paradigm of plant root nutrient acquisition

Plant root nutrient acquisition, and to a lesser extent foliar nutrient uptake, maintain plant metabolism and strongly regulate terrestrial biogeochemistry and carbon-climate feedbacks. However, terrestrial biogeochemical models differ in their representations of plant root nutrient acquisition, leading to significantly different, and uncertain, carbon cycle and future climate projections. Here we first review biogeochemical principles and observations relevant to three essential plant root nutrient acquisition mechanisms: activity of nutrient acquiring proteins, maintenance of nutrient stoichiometry, and energy expenditure for these processes. We next examine how these mechanisms are considered in three existing modeling paradigms, and conclude by recommending the capacity-based approach, the need for observations, and necessary modeling developments of plant root nutrient acquisition to improve carbon-climate feedback projections.

Millennial-age glycerol dialkyl glycerol tetraethers (GDGTs) in forested mineral soils: <sup>14</sup>C-based evidence for stabilization of microbial necromass

Abstract. Understanding controls on the persistence of soil organic matter (SOM) is essential to constrain its role in the carbon cycle and inform climate–carbon cycle model predictions. Emerging concepts regarding the formation and turnover of SOM imply that it is mainly comprised of mineral-stabilized microbial products and residues; however, direct evidence in support of this concept remains limited. Here, we introduce and test a method for the isolation of isoprenoid and branched glycerol dialkyl glycerol tetraethers (GDGTs) – diagnostic membrane lipids of archaea and bacteria, respectively – for subsequent natural abundance radiocarbon analysis. The method is applied to depth profiles from two Swiss pre-Alpine forested soils. We find that the Δ14C values of these microbial markers markedly decrease with increasing soil depth, indicating turnover times of millennia in mineral subsoils. The contrasting metabolisms of the GDGT-producing microorganisms indicates it is unlikely that the low Δ14C values of these membrane lipids reflect heterotrophic acquisition of 14C-depleted carbon. We therefore attribute the 14C-depleted signatures of GDGTs to their physical protection through association with mineral surfaces. These findings thus provide strong evidence for the presence of stabilized microbial necromass in forested mineral soils.

Reducing intensification by shifting cultivation through sustainable climate-smart practices in tropical forests: A review in the context of UN Decade on Ecosystem Restoration

The tropical forests provide important ecosystem services at local and global scales (i.e. climate regulation, carbon cycling, and food resources). Shifting cultivation (SC) is the most common traditional farm system in tropical forest landscapes, which along with hunting and gathering from forests, have been the main food sources and livelihoods. This traditional SC was probably sustainable for nomadic indigenous populations for centuries. However, the non-traditional shifting cultivation is a consequence of cultural changes of indigenous communities influenced by western culture that induce land-use changes using new technologies, promoting the high local-scale expansion and intensification, and overhunting. The intensification occurs due to the short-term farm system, low crop diversity or monocultures, and larger slash and burn forest patches inducing agricultural expansion due to higher commercial crop demand. This expansion and intensification determine the loss of biodiversity and ecosystem services, forest degradation and fragmentation, higher greenhouse gas emissions, defaunation and local extinction. Thus, degraded forest rehabilitation with different sustainable food systems (i.e. Agroforestry) can reduce the expansion and intensification of SC. Restored forest, agroforestry, and second-growth forests can be restored as reservoirs for valuable biodiversity and a host of different ecosystem services. Tropical forests are central to climate change mitigation efforts and should prioritize the UN Decade on Ecosystem Restoration. In this context, we provide a review on the effects of shifting cultivation intensification on tropical forest landscapes as a base to apply sustainable climate-smart practices in the context of UN Decade on Ecosystem Restoration.

Apparent ecosystem carbon turnover time: uncertainties and robust features

Abstract. The turnover time of terrestrial ecosystem carbon is an emergent ecosystem property that quantifies the strength of land surface on the global carbon cycle–climate feedback. However, observation- and modeling-based estimates of carbon turnover and its response to climate are still characterized by large uncertainties. In this study, by assessing the apparent whole ecosystem carbon turnover times (τ) as the ratio between carbon stocks and fluxes, we provide an update of this ecosystem level diagnostic and its associated uncertainties in high spatial resolution (0.083∘) using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble of data, we estimated the global median τ to be 43-7+7 yr (median-difference to percentile 25+difference to percentile 75) when the full soil is considered, in contrast to limiting it to 1 m depth. Only considering the top 1 m of soil carbon in circumpolar regions (assuming maximum active layer depth is up to 1 m) yields a global median τ of 37-6+3 yr, which is longer than the previous estimates of 23-4+7 yr (Carvalhais et al., 2014). We show that the difference is mostly attributed to changes in global Csoil estimates. Csoil accounts for approximately 84 % of the total uncertainty in global τ estimates; GPP also contributes significantly (15 %), whereas Cveg contributes only marginally (less than 1 %) to the total uncertainty. The high uncertainty in Csoil is reflected in the large range across state-of-the-art data products, in which full-depth Csoil spans between 3362 and 4792 PgC. The uncertainty is especially high in circumpolar regions with an uncertainty of 50 % and a low spatial correlation between the different datasets (0.2<r<0.5) when compared to other regions (0.6<r<0.8). These uncertainties cast a shadow on current global estimates of τ in circumpolar regions, for which further geographical representativeness and clarification on variations in Csoil with soil depth are needed. Different GPP estimates contribute significantly to the uncertainties of τ mainly in semiarid and arid regions, whereas Cveg causes the uncertainties of τ in the subtropics and tropics. In spite of the large uncertainties, our findings reveal that the latitudinal gradients of τ are consistent across different datasets and soil depths. The current results show a strong ensemble agreement on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30–60∘ N) than in the subtropical and tropical zones (30∘ S–30∘ N). Additionally, while the strength of the τ–precipitation correlation was dependent on the Csoil data source, the latitudinal gradients also agree among different ensemble members. Overall, and despite the large variation in τ, we identified robust features in the spatial patterns of τ that emerge beyond the differences stemming from the data-driven estimates of Csoil, Cveg and GPP. These robust patterns, and associated uncertainties, can be used to infer τ–climate relationships and for constraining contemporaneous behavior of Earth system models (ESMs), which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback. The dataset of τ is openly available at https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).

High-latitude biomes and rock weathering mediate climate\u2013carbon cycle feedbacks on eccentricity timescales

The International Ocean Discovery Programme (IODP) and its predecessors generated a treasure trove of Cenozoic climate and carbon cycle dynamics. Yet, it remains unclear how climate and carbon cycle interacted under changing geologic boundary conditions. Here, we present the carbon isotope (δ13C) megasplice, documenting deep-ocean δ13C evolution since 35 million years ago (Ma). We juxtapose the δ13C megasplice with its δ18O counterpart and determine their phase-difference on ~100-kyr eccentricity timescales. This analysis reveals that 2.4-Myr eccentricity cycles modulate the δ13C-δ18O phase relationship throughout the Oligo-Miocene (34-6 Ma), potentially through changes in continental weathering. At 6 Ma, a striking switch from in-phase to anti-phase behaviour occurs, signalling a reorganization of the climate-carbon cycle system. We hypothesize that this transition is consistent with Arctic cooling: Prior to 6 Ma, low-latitude continental carbon reservoirs expanded during astronomically-forced cool spells. After 6 Ma, however, continental carbon reservoirs contract rather than expand during cold periods due to competing effects between Arctic biomes (ice, tundra, taiga). We conclude that, on geologic timescales, System Earth experienced state-dependent modes of climate–carbon cycle interaction.