Articles | Volume 15, issue 20
https://doi.org/10.5194/gmd-15-7593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-7593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
20 Oct 2022
Model description paper |
| 20 Oct 2022
| 20 Oct 2022
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Department of Earth and Planetary Sciences, Tokyo Institute of
Technology, Tokyo 152-8551, Japan
Nexus for Exoplanet System Science (NExSS), National Aeronautics and
Space Administration, Washington, D.C. 20546, USA
Alternative Earths Team, Interdisciplinary Consortia for Astrobiology
Research, National Aeronautics and Space Administration, Riverside, CA
92521, USA
Devon B. Cole
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA 30332, USA
Christopher T. Reinhard
Nexus for Exoplanet System Science (NExSS), National Aeronautics and
Space Administration, Washington, D.C. 20546, USA
Alternative Earths Team, Interdisciplinary Consortia for Astrobiology
Research, National Aeronautics and Space Administration, Riverside, CA
92521, USA
School of Earth and Atmospheric Sciences, Georgia Institute of
Technology, Atlanta, GA 30332, USA
Eiichi Tajika
Department of Earth and Planetary Science, The University of Tokyo,
Tokyo 113-0033, Japan
Related authors
No articles found.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
Yoshiki Kanzaki, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 15, 4959–4990, https://doi.org/10.5194/gmd-15-4959-2022, https://doi.org/10.5194/gmd-15-4959-2022, 2022
Short summary
Short summary
Increasing carbon dioxide in the atmosphere is an urgent issue in the coming century. Enhanced rock weathering in soils can be one of the most efficient C capture strategies. On the basis as a weathering simulator, the newly developed SCEPTER model implements bio-mixing by fauna/humans and enables organic matter and crushed rocks/minerals at the soil surface with an option to track their particle size distributions. Those features can be useful for evaluating the carbon capture efficiency.
Sebastiaan J. van de Velde, Dominik Hülse, Christopher T. Reinhard, and Andy Ridgwell
Geosci. Model Dev., 14, 2713–2745, https://doi.org/10.5194/gmd-14-2713-2021, https://doi.org/10.5194/gmd-14-2713-2021, 2021
Short summary
Short summary
Biogeochemical interactions between iron and sulfur are central to the long-term biogeochemical evolution of Earth’s oceans. Here, we introduce an iron–sulphur cycle in a model of Earth's oceans. Our analyses show that the results of the model are robust towards parameter choices and that simulated concentrations and reactions are comparable to those observed in ancient ocean analogues (anoxic lakes). Our model represents an important step forward in the study of iron–sulfur cycling.
Christopher T. Reinhard, Stephanie L. Olson, Sandra Kirtland Turner, Cecily Pälike, Yoshiki Kanzaki, and Andy Ridgwell
Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, https://doi.org/10.5194/gmd-13-5687-2020, 2020
Short summary
Short summary
We provide documentation and testing of new developments for the oceanic and atmospheric methane cycles in the cGENIE Earth system model. The model is designed to explore Earth's methane cycle across a wide range of timescales and scenarios, in particular assessing the mean climate state and climate perturbations in Earth's deep past. We further document the impact of atmospheric oxygen levels and ocean chemistry on fluxes of methane to the atmosphere from the ocean biosphere.
Related subject area
Biogeosciences
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of carbon cycle in Central European beech forests
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
Impacts of land-use change on biospheric carbon: an oriented benchmark using ORCHIDEE land surface model
DeepPhenoMem V1.0: Deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
Simulating Bark Beetle Outbreak Dynamics and their Influence on Carbon Balance Estimates with ORCHIDEE r7791
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošeľa, Doroteja Bitunjac, Masa Zorana Ostrogovic Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-45, https://doi.org/10.5194/gmd-2024-45, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values, aiming to strike a balance between their local precision and broad applicability. Using Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-42, https://doi.org/10.5194/gmd-2024-42, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM), ORCHIDEE, in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2024-464, https://doi.org/10.5194/egusphere-2024-464, 2024
Short summary
Short summary
Our study employs Long Short-Term Memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlocking the secrets of vegetation phenology responses to climate change with deep learning techniques.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, and Christoph Müller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2946, https://doi.org/10.5194/egusphere-2023-2946, 2024
Short summary
Short summary
We present a new approach to model biological nitrogen fixation (BNF) in the Lund Potsdam Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, the nitrogen (N) deficit and carbon (C) costs. The new approach improved global sums and spatial patterns of BNF compared to the scientific literature and the models’ ability to project future C and N cycle dynamics.
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
Short summary
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne-Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
EGUsphere, https://doi.org/10.5194/egusphere-2023-1216, https://doi.org/10.5194/egusphere-2023-1216, 2023
Short summary
Short summary
This research looks at how climate change influences forests, particularly how altered wind and insect activities could make forests emit, instead of absorb, carbon. We've updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, like insect outbreaks, can dramatically affect carbon storage, offering crucial insights for tackling climate change.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
Short summary
Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
Short summary
Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
Short summary
Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
Short summary
Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
Short summary
Short summary
Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Cited articles
Alcott, L. J., Mills, B. J. W., and Poulton, S. W.: Stepwise Earth
oxygenation is an inherent property of global biogeochemical cycling,
Science, 366, 1333–1337, https://doi.org/10.1126/science.aax6459, 2019.
Algeo, T. J. and Ingall, E.: Sedimentary Corg:P ratios, paleocean
ventilation, and Phanerozoic atmospheric pO2, Palaeogeogr.
Palaeocl., 256, 130–155, https://doi.org/10.1016/j.palaeo.2007.02.029, 2007.
Anderson, L. D., Delaney, M. L., and Faul, K. L.: Carbon to phosphorus
ratios in sediments: Implications for nutrient cycling, Global Biogeochem.
Cycles, 15, 65–79, https://doi.org/10.1029/2000GB001270, 2001.
Archer, D., Kheshgi, H., and Maier-Reimer, E.: Dynamics of fossil fuel
CO2 neutralization by marine CaCO3, Global Biogeochem. Cycles, 12,
259–276, https://doi.org/10.1029/98GB00744, 1998.
Archer, D. E., Eshel, G., Winguth, A., Broecker, W., Pierrehumbert, R.,
Tobis, M., and Jacob, R.: Atmospheric pCO2 sensitivity to the biological
pump in the ocean, Global Biogeochem. Cycles, 14, 1219–1230, https://doi.org/10.1029/1999GB001216, 2000.
Archer, D. E., Morford, J. L., and Emerson, S. R.: A model of suboxic
sedimentary diagenesis suitable for automatic tuning and gridded global
domains, Global Biogeochem. Cycles, 16, 17-11–17-21, https://doi.org/10.1029/2000gb001288,
2002.
Armstrong, R. A., Lee, C., Hedges, J. I., Honjo, S., and Wakeham, S. G.: A
new, mechanistic model for organic carbon fluxes in the ocean based on the
quantitative association of POC with ballast minerals, Deep-Sea Res.
Pt. II, 49, 219–236, https://doi.org/10.1016/S0967-0645(01)00101-1, 2001.
Arndt, S., Regnier, P., Goddéris, Y., and Donnadieu, Y.: GEOCLIM reloaded (v 1.0): a new coupled earth system model for past climate change, Geosci. Model Dev., 4, 451–481, https://doi.org/10.5194/gmd-4-451-2011, 2011.
Baturin, G. N.: Issue of the relationship between primary productivity of
organic carbon in ocean and phosphate accumulation (Holocene-Late Jurassic),
Lithol. Min. Resour., 42, 318–348, https://doi.org/10.1134/s0024490207040025,
2007.
Beal, E. J., Claire, M. W., and House, C. H.: High rates of anaerobic
methanotrophy at low sulfate concentrations with implications for past and
present methane levels, Geobiology, 9, 131–139,
https://doi.org/10.1111/j.1472-4669.2010.00267.x, 2011.
Belcher, C. M. and McElwain, J. C.: Limits for combustion in low O2
redefine paleoatmospheric predictions for the Mesozoic, Science, 321,
1197–1200, https://doi.org/10.1126/science.1160978, 2008.
Bellefroid, E. J., Hood, A. v. S., Hoffman, P. F., Thomas, M. D., Reinhard,
C. T., and Planavsky, N. J.: Constraints on Paleoproterozoic atmospheric
oxygen levels, P. Natl Acad. Sci. USA, 115, 8104–8109,
https://doi.org/10.1073/pnas.1806216115, 2018.
Benitez-Nelson, C. R.: The biogeochemical cycling of phosphorus in marine
systems, Earth-Sci. Rev., 51, 109–135, https://doi.org/10.1016/S0012-8252(00)00018-0, 2000.
Berelson, W. M.: Particle settling rates increase with depth in the ocean,
Deep-Sea Res. Pt. II, 49, 237–251,
https://doi.org/10.1016/S0967-0645(01)00102-3, 2001a.
Berelson, W. M.: The Flux of Particulate Organic Carbon Into the Ocean
Interior: A Comparison of Four U.S. JGOFS Regional Studies, Oceanography,
14, 59–67, 2001b.
Berelson, W. M., Balch, W. M., Najjar, R., Feely, R. A., Sabine, C., and
Lee, K.: Relating estimates of CaCO3 production, export, and
dissolution in the water column to measurements of CaCO3 rain into
sediment traps and dissolution on the sea floor: A revised global carbonate
budget, Global Biogeochem. Cycles, 21, GB1024, https://doi.org/10.1029/2006GB002803, 2007.
Bergman, N. M., Lenton, T. M., and Watson, A. J.: COPSE: A new model of
biogeochemical cycling over Phanerozoic time, Am. J. Sci., 304, 397–437,
https://doi.org/10.2475/ajs.304.5.397, 2004.
Berner, R. A.: Early diagenesis: A theoretical
approach, Princeton University Press, Princeton, 256 pp., ISBN 0-691-08258-8, 1980.
Berner, R. A.: Burial of organic carbon and pyrite sulfur in the modern
ocean; its geochemical and environmental significance, Am. J. Sci., 282,
451–473, https://doi.org/10.2475/ajs.282.4.451, 1982.
Berner, R. A.: Biogeochemical cycles of carbon and sulfur and their effect
on atmospheric oxygen over phanerozoic time, Palaeogeogr. Palaeocl., 75, 97–122, https://doi.org/10.1016/0031-0182(89)90186-7, 1989.
Berner, R. A.: The Phanerozoic Carbon Cycle: CO2 and O2, Oxford
University Press, ISBN 0-19-517333-3, 2004a.
Berner, R. A.: A model for calcium, magnesium and sulfate in seawater over
Phanerozoic time, Am. J. Sci., 304, 438–453, https://doi.org/10.2475/ajs.304.5.438, 2004b.
Berner, R. A.: GEOCARBSULF: A combined model for Phanerozoic atmospheric
O2 and CO2, Geochim. Cosmochim. Ac., 70, 5653–5664, https://doi.org/10.1016/j.gca.2005.11.032, 2006.
Berner, R. A.: Phanerozoic atmospheric oxygen: New results using the
GEOCARBSULF model, Am. J. Sci., 309, 603–606, https://doi.org/10.2475/07.2009.03, 2009.
Berner, R. A. and Canfield, D. E.: A new model for atmospheric oxygen over
Phanerozoic time, Am. J. Sci., 289, 333–361, https://doi.org/10.2475/ajs.289.4.333, 1989.
Berner, R. A. and Westrich, J. T.: Bioturbation and the early diagenesis of
carbon and sulfur, Am. J. Sci., 285, 193–206, https://doi.org/10.2475/ajs.285.3.193, 1985.
Betts, J. N. and Holland, H. D.: The oxygen content of ocean bottom waters,
the burial efficiency of organic carbon, and the regulation of atmospheric
oxygen, Palaeogeogr. Palaeocl., 97, 5–18, https://doi.org/10.1016/0031-0182(91)90178-T, 1991.
Bohlen, L., Dale, A. W., and Wallmann, K.: Simple transfer functions for
calculating benthic fixed nitrogen losses and
Bolton, E. W., Berner, R. A., and Petsch, S. T.: The Weathering of
Sedimentary Organic Matter as a Control on Atmospheric O2: II.
Theoretical Modeling, Am. J. Sci., 306, 575–615, https://doi.org/10.2475/08.2006.01, 2006.
Bottrell, S. H. and Newton, R. J.: Reconstruction of changes in global
sulfur cycling from marine sulfate isotopes, Earth-Sci. Rev., 75,
59–83, https://doi.org/10.1016/j.earscirev.2005.10.004, 2006.
Boudreau, B. P.: A method-of-lines code for carbon and nutrient diagenesis
in aquatic sediments, Comput. Geosci., 22, 479–496, https://doi.org/10.1016/0098-3004(95)00115-8, 1996.
Bowles, M. W., Mogollón, J. M., Kasten, S., Zabel, M., and Hinrichs,
K.-U.: Global rates of marine sulfate reduction and implications for
sub–sea-floor metabolic activities, Science, 344, 889–891,
https://doi.org/10.1126/science.1249213, 2014.
Bradley, J. A., Arndt, S., Amend, J. P., Burwicz, E., Dale, A. W., Egger,
M., and LaRowe, D. E.: Widespread energy limitation to life in global
subseafloor sediments, Sci. Adv., 6, eaba0697,
https://doi.org/10.1126/sciadv.aba0697, 2020.
Brandes, J. A. and Devol, A. H.: A global marine-fixed nitrogen isotopic
budget: Implications for Holocene nitrogen cycling, Global Biogeochem.
Cycles, 16, GB001856, https://doi.org/10.1029/2001gb001856, 2002.
Broecker, W. S. and Peng, T.-H.: Tracers in the sea, Eldigio Pr, New
York,
690 pp., ISBN 9993186724, 1982.
Burdige, D. J.: Burial of terrestrial organic matter in marine sediments: A
re-assessment, Global Biogeochem. Cycles, 19, GB4011, https://doi.org/10.1029/2004gb002368, 2005.
Burdige, D. J.: Preservation of Organic Matter in Marine Sediments:
Controls, Mechanisms, and an Imbalance in Sediment Organic Carbon Budgets?,
Chem. Rev., 107, 467–485, https://doi.org/10.1021/cr050347q, 2007.
Canfield, D. E.: Sulfate reduction and oxic respiration in marine sediments:
implications for organic carbon preservation in euxinic environments, Deep-Sea Res. Pt. A., 36, 121–138, https://doi.org/10.1016/0198-0149(89)90022-8, 1989.
Canfield, D. E.: Sulfate reduction in deep-sea sediments, Am. J. Sci., 291,
177–188, https://doi.org/10.2475/ajs.291.2.177, 1991.
Canfield, D. E.: Organic Matter Oxidation in Marine Sediments, in:
Interactions of C, N, P and S Biogeochemical Cycles and Global Change,
edited by: Wollast, R., Mackenzie, F. T., and Chou, L., Springer Berlin
Heidelberg, Berlin, 333–363, ISBN 978-3-642-76066-2, 1993.
Canfield, D. E.: The evolution of the Earth surface sulfur reservoir, Am. J.
Sci., 304, 839–861, https://doi.org/10.2475/ajs.304.10.839, 2004.
Canfield, D. E. and Farquhar, J.: Animal evolution, bioturbation, and the
sulfate concentration of the oceans, P. Natl Acad. Sci. USA, 106,
8123–8127, https://doi.org/10.1073/pnas.0902037106, 2009.
Canfield, D. E., Zhang, S., Frank, A. B., Wang, X., Wang, H., Su, J., Ye,
Y., and Frei, R.: Highly fractionated chromium isotopes in
Mesoproterozoic-aged shales and atmospheric oxygen, Nat. Commun., 9, 2871,
https://doi.org/10.1038/s41467-018-05263-9, 2018.
Carr, M.-E., Friedrichs, M. A. M., Schmeltz, M., Noguchi Aita, M., Antoine,
D., Arrigo, K. R., Asanuma, I., Aumont, O., Barber, R., Behrenfeld, M.,
Bidigare, R., Buitenhuis, E. T., Campbell, J., Ciotti, A., Dierssen, H.,
Dowell, M., Dunne, J., Esaias, W., Gentili, B., Gregg, W., Groom, S.,
Hoepffner, N., Ishizaka, J., Kameda, T., Le Quéré, C., Lohrenz, S.,
Marra, J., Mélin, F., Moore, K., Morel, A., Reddy, T. E., Ryan, J.,
Scardi, M., Smyth, T., Turpie, K., Tilstone, G., Waters, K., and Yamanaka,
Y.: A comparison of global estimates of marine primary production from ocean
color, Deep-Sea Res. Pt. II, 53,
741–770, https://doi.org/10.1016/j.dsr2.2006.01.028, 2006.
Catling, D. C. and Kasting, J. F.: Atmospheric Evolution on Inhabited and
Lifeless Worlds, Cambridge University Press, ISBN 978-0-521-84412-3, 2017.
Catling, D. C. and Zahnle, K. J.: The Archean atmosphere, Sci. Adv.,
6, eaax1420, https://doi.org/10.1126/sciadv.aax1420, 2020.
Cha, H. J., Lee, C. B., Kim, B. S., Choi, M. S., and Ruttenberg, K. C.:
Early diagenetic redistribution and burial of phosphorus in the sediments of
the southwestern East Sea (Japan Sea), Marine Geol., 216, 127–143,
https://doi.org/10.1016/j.margeo.2005.02.001, 2005.
Claire, M. W., Catling, D. C., and Zahnle, K. J.: Biogeochemical modelling
of the rise in atmospheric oxygen, Geobiology, 4, 239–269,
https://doi.org/10.1111/j.1472-4669.2006.00084.x, 2006.
Cole, D. B., Reinhard, C. T., Wang, X., Gueguen, B., Halverson, G. P.,
Gibson, T., Hodgskiss, M. S. W., McKenzie, N. R., Lyons, T. W., and
Planavsky, N. J.: A shale-hosted Cr isotope record of low atmospheric oxygen
during the Proterozoic, Geology, 44, 555–558, https://doi.org/10.1130/g37787.1, 2016.
Cole, D. B., Ozaki, K., and Reinhard, C. T.: Atmospheric Oxygen Abundance,
Marine Nutrient Availability, and Organic Carbon Fluxes to the Seafloor,
Global Biogeochem. Cycles, 36, e2021GB007052, https://doi.org/10.1029/2021GB007052, 2022.
Colman, A. S. and Holland, H. D.: The global diagenetic flux of phosphorus
from marine sediments to the oceans: redox sensitivity and the control of
atmosphreic oxygen levels, in: Marine authigenesis: from global to
microbial, edited by: Glenn, C. R., Prevot-Lucas, L., and Lucas, J., SEPM
(Society for Sedimentary Geology), 53–75,
ISBN 1-56576-064-6, 2000.
Compton, J., Mallinson, D., Glenn, C. R., Filippelli, G., Follmi, K.,
Shields, G. A., and Zanin, Y.: Variations in the global phosphorus cycle,
in: Marine authigenesis: from global to microbial, edited by: Glenn, C. R.,
Prevot-Lucas, L., and Lucas, J., SEPM (Society for Sedimentary Geology),
21–33, 2000.
Crichton, K. A., Wilson, J. D., Ridgwell, A., and Pearson, P. N.: Calibration of temperature-dependent ocean microbial processes in the cGENIE.muffin (v0.9.13) Earth system model, Geosci. Model Dev., 14, 125–149, https://doi.org/10.5194/gmd-14-125-2021, 2021.
Crockford, P. W., Hayles, J. A., Bao, H., Planavsky, N. J., Bekker, A.,
Fralick, P. W., Halverson, G. P., Bui, T. H., Peng, Y., and Wing, B. A.:
Triple oxygen isotope evidence for limited mid-Proterozoic primary
productivity, Nature, 559, 613–616, https://doi.org/10.1038/s41586-018-0349-y, 2018.
Daines, S. J., Mills, B. J. W., and Lenton, T. M.: Atmospheric oxygen
regulation at low Proterozoic levels by incomplete oxidative weathering of
sedimentary organic carbon, Nat. Commun., 8, 14379, https://doi.org/10.1038/ncomms14379,
2017.
Dale, A. W., Meyers, S. R., Aguilera, D. R., Arndt, S., and Wallmann, K.:
Controls on organic carbon and molybdenum accumulation in Cretaceous marine
sediments from the Cenomanian–Turonian interval including Oceanic Anoxic
Event 2, Chem. Geol., 324–325, 28–45, https://doi.org/10.1016/j.chemgeo.2011.10.004, 2012.
Delaney, M. L.: Phosphorus accumulation in marine sediments and the oceanic
phosphorus cycle, Global Biogeochem. Cycles, 12, 563–572, https://doi.org/10.1029/98gb02263,
1998.
Dellwig, O., Leipe, T., März, C., Glockzin, M., Pollehne, F., Schnetger,
B., Yakushev, E. V., Böttcher, M. E., and Brumsack, H.-J.: A new
particulate Mn–Fe–P-shuttle at the redoxcline of anoxic basins, Geochim.
Cosmochim. Ac., 74, 7100–7115, https://doi.org/10.1016/j.gca.2010.09.017, 2010.
Derry, L. A.: Causes and consequences of mid-Proterozoic anoxia, Geophys.
Res. Lett., 42, 2015GL065333, https://doi.org/10.1002/2015gl065333, 2015.
Des Marais, D. J., Harwit, M. O., Jucks, K. W., Kasting, J. F., Lin, D. N.,
Lunine, J. I., Schneider, J., Seager, S., Traub, W. A., and Woolf, N. J.:
Remote Sensing of Planetary Properties and Biosignatures on Extrasolar
Terrestrial Planets, Astrobiology, 2, 153–181, https://doi.org/10.1089/15311070260192246,
2002.
Deutsch, C., Sarmiento, J. L., Sigman, D. M., Gruber, N., and Dunne, J. P.:
Spatial coupling of nitrogen inputs and losses in the ocean, Nature, 445,
163, https://doi.org/10.1038/nature05392,
2007.
Devol, A. and Christensen, J. P.: Benthic fluxes and nitrogen cycling in
sediments of the continental margin of the eastern North Pacific, J.
Marine Res., 51, 345–372, 1993.
Devol, A. H.: Denitrification, Anammox, and N2 Production in Marine
Sediments, Ann. Rev. Mar. Sci., 7, 403–423,
https://doi.org/10.1146/annurev-marine-010213-135040, 2015.
DeVries, T., Deutsch, C., Primeau, F., Chang, B., and Devol, A.: Global
rates of water-column denitrification derived from nitrogen gas
measurements, Nat. Geosci., 5, 547, https://doi.org/10.1038/ngeo1515,
2012.
DeVries, T., Deutsch, C., Rafter, P. A., and Primeau, F.: Marine denitrification rates determined from a global 3-D inverse model, Biogeosciences, 10, 2481–2496, https://doi.org/10.5194/bg-10-2481-2013, 2013.
Doney, S. C., Lindsay, K., Caldeira, K., Campin, J. M., Drange, H., Dutay,
J. C., Follows, M., Gao, Y., Gnanadesikan, A., Gruber, N., Ishida, A., Joos,
F., Madec, G., Maier-Reimer, E., Marshall, J. C., Matear, R. J., Monfray,
P., Mouchet, A., Najjar, R., Orr, J. C., Plattner, G. K., Sarmiento, J.,
Schlitzer, R., Slater, R., Totterdell, I. J., Weirig, M. F., Yamanaka, Y.,
and Yool, A.: Evaluating global ocean carbon models: The importance of
realistic physics, Global Biogeochem. Cycles, 18, GB3017,
https://doi.org/10.1029/2003gb002150, 2004.
Donis, D., McGinnis, D. F., Holtappels, M., Felden, J., and Wenzhofer, F.:
Assessing benthic oxygen fluxes in oligotrophic deep sea sediments
(HAUSGARTEN observatory), Deep-Sea Res. Pt. I, 111, 1–10, https://doi.org/10.1016/j.dsr.2015.11.007, 2016.
Duce, R. A., LaRoche, J., Altieri, K., Arrigo, K. R., Baker, A. R., Capone,
D. G., Cornell, S., Dentener, F., Galloway, J., Ganeshram, R. S., Geider, R.
J., Jickells, T., Kuypers, M. M., Langlois, R., Liss, P. S., Liu, S. M.,
Middelburg, J. J., Moore, C. M., Nickovic, S., Oschlies, A., Pedersen, T.,
Prospero, J., Schlitzer, R., Seitzinger, S., Sorensen, L. L., Uematsu, M.,
Ulloa, O., Voss, M., Ward, B., and Zamora, L.: Impacts of Atmospheric
Anthropogenic Nitrogen on the Open Ocean, Science, 320, 893–897,
https://doi.org/10.1126/science.1150369, 2008.
Dunne, J. P., Sarmiento, J. L., and Gnanadesikan, A.: A synthesis of global
particle export from the surface ocean and cycling through the ocean
interior and on the seafloor, Global Biogeochem. Cycles, 21, GB4006,
https://doi.org/10.1029/2006gb002907, 2007.
Eguchi, J., Seales, J., and Dasgupta, R.: Great Oxidation and Lomagundi
events linked by deep cycling and enhanced degassing of carbon, Nat.
Geosci., 13, 71–76, https://doi.org/10.1038/s41561-019-0492-6, 2020.
Etheridge, D. M., Steele, L. P., Francey, R. J., and Langenfelds, R. L.:
Atmospheric methane between 1000 A.D. and present: Evidence of anthropogenic
emissions and climatic variability, J. Geophys. Res., 103, 15979–15993,
https://doi.org/10.1029/98JD00923, 1998.
Eugster, O. and Gruber, N.: A probabilistic estimate of global marine
N-fixation and denitrification, Global Biogeochem. Cycles, 26, GB4013,
https://doi.org/10.1029/2012gb004300, 2012.
Fakhraee, M., Planavsky, N. J., and Reinhard, C. T.: The role of
environmental factors in the long-term evolution of the marine biological
pump, Nat. Geosci., 13, 812–816, https://doi.org/10.1038/s41561-020-00660-6, 2020.
Fiebig, J., Woodland, A. B., D'Alessandro, W., and Püttmann, W.: Excess
methane in continental hydrothermal emissions is abiogenic, Geology, 37,
495–498, https://doi.org/10.1130/g25598a.1, 2009.
Filippelli, G. M.: Carbon and phosphorus cycling in anoxic sediments of the
Saanich Inlet, British Columbia, Marine Geol., 174, 307–321, https://doi.org/10.1016/S0025-3227(00)00157-2, 2001.
Föllmi, K. B.: The phosphorus cycle, phosphogenesis and marine
phosphate-rich deposits, Earth-Sci. Rev., 40, 55–124, https://doi.org/10.1016/0012-8252(95)00049-6, 1996.
Fowler, D., Coyle, M., Skiba, U., Sutton, M. A., Cape, J. N., Reis, S.,
Sheppard, L. J., Jenkins, A., Grizzetti, B., Galloway, J. N., Vitousek, P.,
Leach, A., Bouwman, A. F., Butterbach-Bahl, K., Dentener, F., Stevenson, D.,
Amann, M., and Voss, M.: The global nitrogen cycle in the twenty-first
century, Phil. Trans. R. Soc. B, 368, 20130164, https://doi.org/10.1098/rstb.2013.0164, 2013.
Francois, R., Honjo, S., Krishfield, R., and Manganini, S.: Factors
controlling the flux of organic carbon to the bathypelagic zone of the
ocean, Global Biogeochem. Cycles, 16, 1087, https://doi.org/10.1029/2001gb001722, 2002.
Froelich, P. N., Klinkhammer, G. P., Bender, M. L., Luedtke, N. A., Heath,
G. R., Cullen, D., Dauphin, P., Hammond, D., Hartman, B., and Maynard, V.:
Early oxidation of organic matter in pelagic sediments of the eastern
equatorial Atlantic: suboxic diagenesis, Geochim. Cosmochim. Ac., 43,
1075–1090, https://doi.org/10.1016/0016-7037(79)90095-4,
1979.
Galbraith, E. D. and Martiny, A. C.: A simple nutrient-dependence mechanism
for predicting the stoichiometry of marine ecosystems, P. Natl Acad. Sci.
USA, 112, 8199–8204, https://doi.org/10.1073/pnas.1423917112, 2015.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R.
W., Seitzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A.,
Holland, E. A., Karl, D. M., Michaels, A. F., Porter, J. H., Townsend, A.
R., and Vöosmarty, C. J.: Nitrogen Cycles: Past, Present, and Future,
Biogeochemistry, 70, 153–226, https://doi.org/10.1007/s10533-004-0370-0, 2004.
Garcia, H. E. and Gordon, L. I.: Oxygen solubility in seawater: Better
fitting equations, Limnol. Oceanogr., 37, 1307–1312,
https://doi.org/10.4319/lo.1992.37.6.1307, 1992.
Garrels, R. M. and Lerman, A.: Phanerozoic cycles of sedimentary carbon and
sulfur, P. Natl Acad. Sci. USA, 78, 4652–4656, 1981.
Garrels, R. M. and Perry, J. E. A.: Cycling of carbon, sulfur, and oxygen
through geologic time, The Sea, Wiley-Interscience, New York, edited by: Goldberg, E. D.,
303–336,
ISBN 067401734X, 1974.
Goldblatt, C., Lenton, T. M., and Watson, A. J.: Bistability of atmospheric
oxygen and the Great Oxidation, Nature, 443, 683–686, 2006.
Graham, W. F. and Duce, R. A.: Atmospheric pathways of the phosphorus cycle,
Geochim. Cosmochim. Ac., 43, 1195–1208, https://doi.org/10.1016/0016-7037(79)90112-1, 1979.
Großkopf, T., Mohr, W., Baustian, T., Schunck, H., Gill, D., Kuypers, M.
M. M., Lavik, G., Schmitz, R. A., Wallace, D. W. R., and LaRoche, J.:
Doubling of marine dinitrogen-fixation rates based on direct measurements,
Nature, 488, 361, https://doi.org/10.1038/nature11338,
2012.
Gruber, N.: Chapter 1 – The Marine Nitrogen Cycle: Overview and Challenges,
in: Nitrogen in the Marine Environment, 2nd edn., Academic Press, San
Diego, 1–50, https://doi.org/10.1016/B978-0-12-372522-6.00001-3, 2008.
Gruber, N. and Sarmiento, J. L.: Global patterns of marine nitrogen fixation
and denitrification, Global Biogeochem. Cycles, 11, 235–266,
https://doi.org/10.1029/97gb00077, 1997.
Gruber, N. and Sarmiento, J. L.: Biogeochemical/physical interactions in
elemental cycles, in: THE SEA: Biological-Physical Interactions in the
Oceans, edited by: Robinson, A. R., McCarthy, J. J., and Rothschild, B. J.,
John Wiley and Sons, New York, 337–399, 2002.
Guidry, M. W., Mackenzie, F. T., and Arvidson, R. S.: Role of tectonics in
phosphorus distribution and cycling, in: Marine Authigenesis: From Global to
Microbial, edited by: Glenn, C. R., Prevot-Lucas, L., and Lucas, J., SEPM,
35–51, 2000.
Gundersen, J. K. and Jorgensen, B. B.: Microstructure of diffusive boundary
layers and the oxygen uptake of the sea floor, Nature, 345, 604,
https://doi.org/10.1038/345604a0, 1990.
Halevy, I., Peters, S. E., and Fischer, W. W.: Sulfate Burial Constraints on
the Phanerozoic Sulfur Cycle, Science, 337, 331–334,
https://doi.org/10.1126/science.1220224, 2012.
Handoh, I. C. and Lenton, T. M.: Periodic mid-Cretaceous oceanic anoxic
events linked by oscillations of the phosphorus and oxygen biogeochemical
cycles, Global Biogeochem. Cycles, 17, 1092, https://doi.org/10.1029/2003gb002039, 2003.
Hartnett, H. E. and Devol, A. H.: Role of a strong oxygen-deficient zone in
the preservation and degradation of organic matter: a carbon budget for the
continental margins of northwest Mexico and Washington State, Geochim.
Cosmochim. Ac., 67, 247–264, https://doi.org/10.1016/S0016-7037(02)01076-1, 2003.
Hartnett, H. E., Keil, R. G., Hedges, J. I., and Devol, A. H.: Influence of
oxygen exposure time on organic carbon preservation in continental margin
sediments, Nature, 391, 572–575, 1998.
Hayes, C. T., Costa, K. M., Anderson, R. F., Calvo, E., Chase, Z., Demina,
L. L., Dutay, J.-C., German, C. R., Heimbürger-Boavida, L.-E., Jaccard,
S. L., Jacobel, A., Kohfeld, K. E., Kravchishina, M. D., Lippold, J., Mekik,
F., Missiaen, L., Pavia, F. J., Paytan, A., Pedrosa-Pamies, R., Petrova, M.
V., Rahman, S., Robinson, L. F., Roy-Barman, M., Sanchez-Vidal, A., Shiller,
A., Tagliabue, A., Tessin, A. C., van Hulten, M., and Zhang, J.: Global
Ocean Sediment Composition and Burial Flux in the Deep Sea, Global
Biogeochem. Cycles, 35, e2020GB006769, https://doi.org/10.1029/2020GB006769, 2021.
Hayes, J. M. and Waldbauer, J. R.: The carbon cycle and associated redox
processes through time, Phil. Trans. R. Soc. B, 361, 931–950,
https://doi.org/10.1098/rstb.2006.1840, 2006.
Hedges, J. I., Hu, F. S., Devol, A. H., Hartnett, H. E., Tsamakis, E., and
Keil, R. G.: Sedimentary organic matter preservation; a test for selective
degradation under oxic conditions, Am. J. Sci., 299, 529–555,
https://doi.org/10.2475/ajs.299.7-9.529, 1999.
Heinze, C., Kriest, I., and Maier-Reimer, E.: Age offsets among different
biogenic and lithogenic components of sediment cores revealed by numerical
modeling, Paleoceanography, 24, PA4214, https://doi.org/10.1029/2008pa001662, 2009.
Henrichs, S. M. and Reeburgh, W. S.: Anaerobic mineralization of marine
sediment organic matter: Rates and the role of anaerobic processes in the
oceanic carbon economy, Geomicrobiol. J., 5, 191–237,
https://doi.org/10.1080/01490458709385971, 1987.
Hensen, C., Landenberger, H., Zabel, M., and Schulz, H. D.: Quantification
of diffusive benthic fluxes of nitrate, phosphate, and silicate in the
southern Atlantic Ocean, Global Biogeochem. Cycles, 12, 193–210,
https://doi.org/10.1029/97gb02731, 1998.
Hitchcock, D. R. and Lovelock, J. E.: Life detection by atmospheric
analysis, Icarus, 7, 149–159, https://doi.org/10.1016/0019-1035(67)90059-0, 1967.
Holland, H. D.: The Chemistry of the Atmosphere and Oceans, John Wiley &
Sons, New York, ISBN 0471035092, 1978.
Holser, W. T., Maynard, J. B., and Cruikshank, K. M.: Modelling the natural
cycle of sulphur through Phanerozoic time, in: Evolution of the Global
Biogeochemical Sulphur Cycle, edited by: Brimblecombe, P., and Lein, A. Y.,
John Wiley & Sons Ltd, New York, 21–56, 1989.
Honjo, S.: Material fluxes and modes of sedimentation in the mesopelagic and
bathypelagic zones, J. Marine Res., 38, 53–97, 1980.
Honjo, S. and Manganini, S. J.: Annual biogenic particle fluxes to the
interior of the North Atlantic Ocean; studied at 34∘ N
21∘ W and 48∘ N 21∘ W, Deep-Sea Res. Pt.
II, 40, 587–607, https://doi.org/10.1016/0967-0645(93)90034-K, 1993.
Hotinski, R. M., Kump, L. R., and Najjar, R. G.: Opening Pandora's Box: The
impact of open system modeling on interpretations of anoxia,
Paleoceanography, 15, 267–279, https://doi.org/10.1029/1999pa000408, 2000.
Hyacinthe, C., Anschutz, P., Carbonel, P., Jouanneau, J. M., and Jorissen,
F. J.: Early diagenetic processes in the muddy sediments of the Bay of
Biscay, Marine Geol., 177, 111–128, https://doi.org/10.1016/S0025-3227(01)00127-X, 2001.
Ingall, E. and Jahnke, R.: Evidence for enhanced phosphorus regeneration
from marine sediments overlain by oxygen depleted waters, Geochim.
Cosmochim. Ac., 58, 2571–2575, https://doi.org/10.1016/0016-7037(94)90033-7, 1994.
Ingall, E. and Jahnke, R.: Influence of water-column anoxia on the elemental
fractionation of carbon and phosphorus during sediment diagenesis, Marine
Geol., 139, 219–229, https://doi.org/10.1016/S0025-3227(96)00112-0, 1997.
Ingall, E. D. and Cappellen, P. V.: Relation between sedimentation rate and
burial of organic phosphorus and organic carbon in marine sediments,
Geochim. Cosmochim. Ac., 54, 373–386, https://doi.org/10.1016/0016-7037(90)90326-G, 1990.
Ingall, E. D., Bustin, R. M., and Van Cappellen, P.: Influence of water
column anoxia on the burial and preservation of carbon and phosphorus in
marine shales, Geochim. Cosmochim. Ac., 57, 303–316, https://doi.org/10.1016/0016-7037(93)90433-W, 1993.
Ittekkot, V.: The abiotically driven biological pump in the ocean and
short-term fluctuations in atmospheric CO2 contents, Global
Planet. Change, 8, 17–25, https://doi.org/10.1016/0921-8181(93)90060-2, 1993.
Jahnke, R. A.: The global ocean flux of particulate organic carbon: Areal
distribution and magnitude, Global Biogeochem. Cycles, 10, 71–88, https://doi.org/10.1029/95GB03525, 1996.
Joos, F., Sarmiento, J. L., and Siegenthaler, U.: Estimates of the effect of
Southern Ocean iron fertilization on atmospheric CO2 concentrations,
Nature, 349, 772–775, https://doi.org/10.1038/349772a0, 1991.
Jørgensen, B. B.: Mineralization of organic matter in the sea bed—the
role of sulphate reduction, Nature, 296, 643, https://doi.org/10.1038/296643a0, 1982.
Jørgensen, B. B. and Kasten, S.: Sulfur cycling and methane oxidation,
in: Marine Geochemistry, edited by: Schulz, H. D. and Zabel, M., Springer Berlin Heidelberg, 271–309, https://doi.org/10.1007/3-540-32144-6_8, 2006.
Kagoshima, T., Sano, Y., Takahata, N., Maruoka, T., Fischer, T. P., and
Hattori, K.: Sulphur geodynamic cycle, Sci. Rep.-UK, 5, 8330, https://doi.org/10.1038/srep08330,
2015.
Karl, D., Michaels, A., Bergman, B., Capone, D., Carpenter, E., Letelier,
R., Lipschultz, F., Paerl, H., Sigman, D., and Stal, L.: Dinitrogen fixation
in the world's oceans, in: The Nitrogen Cycle at Regional to Global Scales,
edited by: Boyer, E. W., and Howarth, R. W., Springer Netherlands,
Dordrecht, 47–98, https://doi.org/10.1007/978-94-017-3405-9_2, 2002.
Karl, D. M., Beversdorf, L., Björkman, K. M., Church, M. J., Martinez,
A., and Delong, E. F.: Aerobic production of methane in the sea, Nat.
Geosci., 1, 473–478, https://doi.org/10.1038/ngeo234, 2008.
Karthäuser, C., Ahmerkamp, S., Marchant, H. K., Bristow, L. A., Hauss,
H., Iversen, M. H., Kiko, R., Maerz, J., Lavik, G., and Kuypers, M. M. M.:
Small sinking particles control anammox rates in the Peruvian oxygen minimum
zone, Nat. Commun., 12, 3235, https://doi.org/10.1038/s41467-021-23340-4, 2021.
Kashiyama, Y., Ozaki, K., and Tajika, E.: Impact of the Evolution of
Carbonate Ballasts on Marine Biogeochemistry in the Mesozoic and Associated
Changes in Energy Delivery to Subsurface Waters, Paleontol. Res.,
15, 89–99, https://doi.org/10.2517/1342-8144-15.2.089, 2011.
Katsev, S. and Crowe, S. A.: Organic carbon burial efficiencies in
sediments: The power law of mineralization revisited, Geology, 43, 607–610,
https://doi.org/10.1130/g36626.1, 2015.
Key, R. M., Olsen, A., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X.,
Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S.,
Steinfeldt, R., Jeansson, E., Ishii, M., Perez, F. F., and Suzuki, T.:
Global Ocean Data Analysis Project, Version 2 (GLODAPv2),
https://doi.org/10.3334/CDIAC/OTG. NDP093_GLODAPv2, 2015.
Kharecha, P., Kasting, J., and Siefert, J.: A coupled atmosphere–ecosystem
model of the early Archean Earth, Geobiology, 3, 53–76,
https://doi.org/10.1111/j.1472-4669.2005.00049.x, 2005.
Klaas, C. and Archer, D. E.: Association of sinking organic matter with
various types of mineral ballast in the deep sea: Implications for the rain
ratio, Global Biogeochem. Cycles, 16, 63-61–63-14, https://doi.org/10.1029/2001gb001765,
2002.
Knox, F. and McElroy, M. B.: Changes in atmospheric CO2: Influence of
the marine biota at high latitude, J. Geophys. Res., 89, 4629–4637,
https://doi.org/10.1029/JD089iD03p04629, 1984.
Krissansen-Totton, J., Garland, R., Irwin, P., and Catling, D. C.:
Detectability of Biosignatures in Anoxic Atmospheres with the James Webb
Space Telescope: A TRAPPIST-1e Case Study, The Astronom. J., 156,
114, https://doi.org/10.3847/1538-3881/aad564, 2018.
Kump, L. R.: Chemical stability of the atmosphere and ocean, Palaeogeogr.
Palaeocl., 75, 123–136, https://doi.org/10.1016/0031-0182(89)90187-9, 1989.
Kump, L. R.: The rise of atmospheric oxygen, Nature, 451, 277–278, https://doi.org/10.1038/nature06587, 2008.
Kuypers, M. M. M., Lavik, G., Woebken, D., Schmid, M., Fuchs, B. M., Amann,
R., Jørgensen, B. B., and Jetten, M. S. M.: Massive nitrogen loss from
the Benguela upwelling system through anaerobic ammonium oxidation, P.
Natl. Acad. Sci. USA, 102, 6478–6483, https://doi.org/10.1073/pnas.0502088102, 2005.
Kuznetsov, I., Neumann, T., and Burchard, H.: Model study on the ecosystem
impact of a variable
Laakso, T. A. and Schrag, D. P.: Regulation of atmospheric oxygen during the
Proterozoic, Earth Planet. Sc. Lett., 388, 81–91, https://doi.org/10.1016/j.epsl.2013.11.049, 2014.
Larsson, U., Hajdu, S., Walve, J., and Elmgren, R.: Baltic Sea nitrogen
fixation estimated from the summer increase in upper mixed layer total
nitrogen, Limnol. Oceanogr., 46, 811–820, https://doi.org/10.4319/lo.2001.46.4.0811, 2001.
Lasaga, A. C.: A new approach to isotopic modeling of the variation of
atmospheric oxygen through the Phanerozoic, Am. J. Sci., 289, 411–435,
https://doi.org/10.2475/ajs.289.4.411, 1989.
Lasaga, A. C. and Ohmoto, H.: The oxygen geochemical cycle: dynamics and
stability, Geochim. Cosmochim. Ac., 66, 361–381, https://doi.org/10.1016/S0016-7037(01)00685-8, 2002.
Laws, E. A., Falkowski, P. G., Smith, W. O., Ducklow, H., and McCarthy, J.
J.: Temperature effects on export production in the open ocean, Global
Biogeochem. Cycles, 14, 1231–1246, https://doi.org/10.1029/1999gb001229, 2000.
Ledwell, J. R., Watson, A. J., and Law, C. S.: Mixing of a tracer in the
pycnocline, J. Geophys. Res., 103, 21499–21529, https://doi.org/10.1029/98JC01738, 1998.
Lenton, T. M.: Fire Feedbacks on Atmospheric Oxygen, in: Fire Phenomena and
the Earth System, edited by: Belcher, C. M., 289–308, https://doi.org/10.1002/9781118529539.ch15, 2013.
Lenton, T. M.: On the use of models in understanding the rise of complex
life, Interface Focus, 10, 20200018, https://doi.org/10.1098/rsfs.2020.0018, 2020.
Lenton, T. M. and Watson, A. J.: Redfield revisited: 1. Regulation of
nitrate, phosphate, and oxygen in the ocean, Global Biogeochem. Cycles, 14,
225–248, https://doi.org/10.1029/1999gb900065, 2000a.
Lenton, T. M. and Watson, A. J.: Redfield revisited: 2. What regulates the
oxygen content of the atmosphere?, Global Biogeochem. Cycles, 14, 249–268,
https://doi.org/10.1029/1999gb900076, 2000b.
Lenton, T. M., Daines, S. J., and Mills, B. J. W.: COPSE reloaded: An
improved model of biogeochemical cycling over Phanerozoic time,
Earth-Sci. Rev., 178, 1–28, https://doi.org/10.1016/j.earscirev.2017.12.004, 2018.
Lenton, T. M., Dahl, T. W., Daines, S. J., Mills, B. J. W., Ozaki, K.,
Saltzman, M. R., and Porada, P.: Earliest land plants created modern levels
of atmospheric oxygen, P. Natl Acad. Sci. USA, 113, 9704–9709,
https://doi.org/10.1073/pnas.1604787113, 2016.
Lin, S. and Morse, J. W.: Sulfate reduction and iron sulfide mineral
formation in Gulf of Mexico anoxic sediments, Am. J. Sci., 291, 55–89,
https://doi.org/10.2475/ajs.291.1.55, 1991.
Liss, P. S. and Slater, P. G.: Flux of Gases across the Air-Sea Interface,
Nature, 247, 181–184, 1974.
Lord, N. S., Ridgwell, A., Thorne, M. C., and Lunt, D. J.: An impulse
response function for the “long tail” of excess atmospheric CO2 in an
Earth system model, Global Biogeochem. Cycles, 30, 2–17, https://doi.org/10.1002/2014GB005074, 2016.
Lovelock, J. E.: A Physical Basis for Life Detection Experiments, Nature,
207, 568–570, https://doi.org/10.1038/207568a0, 1965.
Lovelock, J. E.: Gaia as seen through the atmosphere, Atmos.
Environ., 6, 579–580, https://doi.org/10.1016/0004-6981(72)90076-5, 1972.
Lovelock, J. E.: Thermodynamics and the recognition of alien biospheres,
P. Roy. Soc. Lond. B,
189, 167–181, https://doi.org/10.1098/rspb.1975.0051, 1975.
Lumpkin, R. and Speer, K.: Global Ocean Meridional Overturning, J.
Phys. Oceanogr., 37, 2550–2562, https://doi.org/10.1175/jpo3130.1, 2007.
Luo, Y.-W., Doney, S. C., Anderson, L. A., Benavides, M., Berman-Frank, I., Bode, A., Bonnet, S., Boström, K. H., Böttjer, D., Capone, D. G., Carpenter, E. J., Chen, Y. L., Church, M. J., Dore, J. E., Falcón, L. I., Fernández, A., Foster, R. A., Furuya, K., Gómez, F., Gundersen, K., Hynes, A. M., Karl, D. M., Kitajima, S., Langlois, R. J., LaRoche, J., Letelier, R. M., Marañón, E., McGillicuddy Jr., D. J., Moisander, P. H., Moore, C. M., Mouriño-Carballido, B., Mulholland, M. R., Needoba, J. A., Orcutt, K. M., Poulton, A. J., Rahav, E., Raimbault, P., Rees, A. P., Riemann, L., Shiozaki, T., Subramaniam, A., Tyrrell, T., Turk-Kubo, K. A., Varela, M., Villareal, T. A., Webb, E. A., White, A. E., Wu, J., and Zehr, J. P.: Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates, Earth Syst. Sci. Data, 4, 47–73, https://doi.org/10.5194/essd-4-47-2012, 2012.
Lutz, M., Dunbar, R., and Caldeira, K.: Regional variability in the vertical
flux of particulate organic carbon in the ocean interior, Global Biogeochem.
Cycles, 16, 11-11–11-18, https://doi.org/10.1029/2000gb001383, 2002.
Lyons, T. W. and Gill, B. C.: Ancient Sulfur Cycling and Oxygenation of the
Early Biosphere, Elements, 6, 93–99, https://doi.org/10.2113/gselements.6.2.93, 2010.
Lyons, T. W., Reinhard, C. T., and Planavsky, N. J.: The rise of oxygen in
Earth's early ocean and atmosphere, Nature, 506, 307–315,
https://doi.org/10.1038/nature13068, 2014.
Mackenzie, F. T., Ver, L. M., Sabine, C., Lane, M., and Lerman, A.: C, N, P,
S Global Biogeochemical Cycles and Modeling of Global Change, in:
Interactions of C, N, P and S Biogeochemical Cycles and Global Change,
edited by: Wollast, R., Mackenzie, F. T., and Chou, L., Springer Berlin
Heidelberg, Berlin, Heidelberg, 1–61, 1993.
Maier-Reimer, E.: Geochemical cycles in an ocean general circulation model.
Preindustrial tracer distributions, Global Biogeochem. Cycles, 7, 645–677,
https://doi.org/10.1029/93gb01355, 1993.
Markovic, S., Paytan, A., and Wortmann, U. G.: Pleistocene sediment offloading and the global sulfur cycle, Biogeosciences, 12, 3043–3060, https://doi.org/10.5194/bg-12-3043-2015, 2015.
Martin, J. H., Knauer, G. A., Karl, D. M., and Broenkow, W. W.: VERTEX:
carbon cycling in the northeast Pacific, Deep-Sea Res. Pt. A, 34, 267–285, https://doi.org/10.1016/0198-0149(87)90086-0, 1987.
Martin, W. R. and Sayles, F. L.: The Recycling of Biogenic Material at the
Sea Floor, in: Treatise on Geochemistry (Second Edition), edited by:
Turekian, K. K., Elsevier, Oxford, 33–59, https://doi.org/10.1016/B978-0-08-095975-7.00702-6, 2014.
Mayor, M. and Queloz, D.: A Jupiter-mass companion to a solar-type star,
Nature, 378, 355–359, https://doi.org/10.1038/378355a0, 1995.
McManus, J., Berelson, W. M., Coale, K. H., Johnson, K. S., and Kilgore, T.
E.: Phosphorus regeneration in continental margin sediments, Geochim.
Cosmochim. Ac., 61, 2891–2907, https://doi.org/10.1016/S0016-7037(97)00138-5, 1997.
McManus, J., Berelson, W. M., Klinkhammer, G. P., Hammond, D. E., and Holm,
C.: Authigenic uranium: Relationship to oxygen penetration depth and organic
carbon rain, Geochim. Cosmochim. Ac., 69, 95–108, https://doi.org/10.1016/j.gca.2004.06.023, 2005.
Meadows, V. S.: Reflections on O2 as a Biosignature in Exoplanetary
Atmospheres, Astrobiology, 17, 1022–1052, https://doi.org/10.1089/ast.2016.1578, 2017.
Meadows, V. S., Reinhard, C. T., Arney, G. N., Parenteau, M. N.,
Schwieterman, E. W., Domagal-Goldman, S. D., Lincowski, A. P., Stapelfeldt,
K. R., Rauer, H., DasSarma, S., Hegde, S., Narita, N., Deitrick, R.,
Lustig-Yaeger, J., Lyons, T. W., Siegler, N., and Grenfell, J. L.: Exoplanet
Biosignatures: Understanding Oxygen as a Biosignature in the Context of Its
Environment, Astrobiology, 18, 630–662, https://doi.org/10.1089/ast.2017.1727, 2018.
Middelburg, J. J., Soetaert, K., Herman, P. M. J., and Heip, C. H. R.:
Denitrification in marine sediments: A model study, Global Biogeochem.
Cycles, 10, 661–673, https://doi.org/10.1029/96gb02562, 1996.
Middelburg, J. J., Soetaert, K., and Herman, P. M. J.: Empirical
relationships for use in global diagenetic models, Deep-Sea Res. Pt. I, 44, 327–344, https://doi.org/10.1016/S0967-0637(96)00101-X, 1997.
Millero, F. J.: The oxidation of H2S in Black Sea waters, Deep-Sea Res. Pt. A, 38, S1139–S1150, https://doi.org/10.1016/S0198-0149(10)80028-7, 1991.
Millero, F. J.: Chemical Oceanography, 3rd edn., Taylor & Francis Group
CRC Press, Boca Raton, 496 pp., 2006.
Millero, F. J., Plese, T., and Fernandez, M.: The dissociation of
hydrogen-sulfide in seawater, Limnol. Oceanogr., 33, 269–274, 1988.
Morford, J. L. and Emerson, S.: The geochemistry of redox sensitive trace
metals in sediments, Geochim. Cosmochim. Ac., 63, 1735–1750, https://doi.org/10.1016/S0016-7037(99)00126-X, 1999.
Muller-Karger, F. E., Varela, R., Thunell, R., Luerssen, R., Hu, C., and
Walsh, J. J.: The importance of continental margins in the global carbon
cycle, Geophys. Res. Lett., 32, L01602, https://doi.org/10.1029/2004gl021346, 2005.
National Academies of Sciences, E. and Medicine: An Astrobiology Strategy
for the Search for Life in the Universe, The National Academies Press,
Washington, D.C., 188 pp., https://doi.org/10.17226/25252, 2019.
Nierop, K. G. J., Reichart, G.-J., Veld, H., and Sinninghe Damsté, J.
S.: The influence of oxygen exposure time on the composition of
macromolecular organic matter as revealed by surface sediments on the Murray
Ridge (Arabian Sea), Geochim. Cosmochim. Ac., 206, 40–56,
https://doi.org/10.1016/j.gca.2017.02.032, 2017.
Oguz, T., Ducklow, H. W., and Malanotte-Rizzoli, P.: Modeling distinct
vertical biogeochemical structure of the Black Sea: Dynamical coupling of
the oxic, suboxic, and anoxic layers, Global Biogeochem. Cycles, 14,
1331–1352, https://doi.org/10.1029/1999GB001253, 2000.
Oguz, T., Murray, J. W., and Callahan, A. E.: Modeling redox cycling across
the suboxic–anoxic interface zone in the Black Sea, Deep-Sea Res. Pt.
I, 48, 761–787, https://doi.org/10.1016/S0967-0637(00)00054-6, 2001.
Olsen, A., Key, R. M., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Pérez, F. F., and Suzuki, T.: The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean, Earth Syst. Sci. Data, 8, 297–323, https://doi.org/10.5194/essd-8-297-2016, 2016.
Olsen, A., Lange, N., Key, R. M., Tanhua, T., Álvarez, M., Becker, S., Bittig, H. C., Carter, B. R., Cotrim da Cunha, L., Feely, R. A., van Heuven, S. M. A. C., Hoppema, M., Ishii, M., Jeansson, E., Jones, S. D., Jutterström, S., Karlsen, M. K., Kozyr, A., Lauvset, S. K., Lo Monaco, C., Murata, A., Pérez, F. F., Pfeil, B., Schirnick, C., Steinfeldt, R., Suzuki, T., Telszewski, M., Tilbrook, B., Velo, A., and Wanninkhof, R.: Global Ocean Data Analysis Project version 2.2019 (GLODAPv2.2019) (NCEI Accession 0186803), version 2.2019, NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/xnme-wr20, 2019.
Olson, S. L., Reinhard, C. T., and Lyons, T. W.: Limited role for methane in
the mid-Proterozoic greenhouse, P. Natl Acad. Sci. USA, 113, 11447–11452,
https://doi.org/10.1073/pnas.1608549113, 2016.
Oschlies, A., Schulz, K. G., Riebesell, U., and Schmittner, A.: Simulated
21st century's increase in oceanic suboxia by CO2-enhanced biotic
carbon export, Global Biogeochem. Cycles, 22, GB4008, https://doi.org/10.1029/2007gb003147,
2008.
Ozaki, K.: kazumi-ozaki/CANOPS-GRBv1: CANOPS-GRBv1 (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.5893804, 2022.
Ozaki, K. and Reinhard, C. T.: The future lifespan of Earth's oxygenated
atmosphere, Nat. Geosci., 14, 138–142, https://doi.org/10.1038/s41561-021-00693-5, 2021.
Ozaki, K. and Tajika, E.: Biogeochemical effects of atmospheric oxygen
concentration, phosphorus weathering, and sea-level stand on oceanic redox
chemistry: Implications for greenhouse climates, Earth Planet. Sc. Lett.,
373, 129–139, https://doi.org/10.1016/j.epsl.2013.04.029,
2013.
Ozaki, K., Tajima, S., and Tajika, E.: Conditions required for oceanic
anoxia/euxinia: Constraints from a one-dimensional ocean biogeochemical
cycle model, Earth Planet. Sc. Lett., 304, 270–279, https://doi.org/10.1016/j.epsl.2011.02.011, 2011.
Ozaki, K., Tajika, E., Hong, P. K., Nakagawa, Y., and Reinhard, C. T.:
Effects of primitive photosynthesis on Earth's early climate system, Nat.
Geosci., 11, 55–59, https://doi.org/10.1038/s41561-017-0031-2, 2018.
Ozaki, K., Reinhard, C. T., and Tajika, E.: A sluggish mid-Proterozoic
biosphere and its effect on Earth's redox balance, Geobiology, 17, 3–11,
https://doi.org/10.1111/gbi.12317, 2019a.
Ozaki, K., Thompson, K. J., Simister, R. L., Crowe, S. A., and Reinhard, C.
T.: Anoxygenic photosynthesis and the delayed oxygenation of Earth's
atmosphere, Nat. Commun., 10, 3026, https://doi.org/10.1038/s41467-019-10872-z, 2019b.
Pallud, C. and Van Cappellen, P.: Kinetics of microbial sulfate reduction in
estuarine sediments, Geochim. Cosmochim. Ac., 70, 1148–1162, https://doi.org/10.1016/j.gca.2005.11.002, 2006.
Papadomanolaki, N. M., Lenstra, W. K., Wolthers, M., and Slomp, C. P.:
Enhanced phosphorus recycling during past oceanic anoxia amplified by low
rates of apatite authigenesis, Sci, Adv,, 8, eabn2370,
https://doi.org/10.1126/sciadv.abn2370, 2022.
Petsch, S. T. and Berner, R. A.: Coupling the geochemical cycles of C, P,
Fe, and S; the effect on atmospheric O2 and the isotopic records of
carbon and sulfur, Am. J. Sci., 298, 246–262, https://doi.org/10.2475/ajs.298.3.246, 1998.
Petsch, S. T., Eglinton, T. I., and Edwards, K. J.: 14C-Dead Living
Biomass: Evidence for Microbial Assimilation of Ancient Organic Carbon
During Shale Weathering, Science, 292, 1127–1131,
https://doi.org/10.1126/science.1058332, 2001.
Pfeifer, K., Hensen, C., Adler, M., Wenzhfer, F., Weber, B., and Schulz, H.
D.: Modeling of subsurface calcite dissolution, including the respiration
and reoxidation processes of marine sediments in the region of equatorial
upwelling off Gabon, Geochim. Cosmochim. Ac., 66, 4247–4259, https://doi.org/10.1016/S0016-7037(02)01073-6, 2002.
Planavsky, N. J., Cole, D. B., Reinhard, C. T., Diamond, C., Love, G. D.,
Luo, G., Zhang, S., Konhauser, K. O., and Lyons, T. W.: No evidence for high
atmospheric oxygen levels 1,400 million years ago, P. Natl Acad. Sci.
USA, 113, E2550–E2551, https://doi.org/10.1073/pnas.1601925113, 2016.
Planavsky, N. J., Cole, D. B., Isson, T. T., Reinhard, C. T., Crockford, P.
W., Sheldon, N. D., and Lyons, T. W.: A case for low atmospheric oxygen
levels during Earth's middle history, Emerging Topics in Life Sciences, 2,
149–159, https://doi.org/10.1042/etls20170161, 2018.
Prentice, I. C., Farquhar, G. D., Fasham, M. J. R., Goulden, M. L., Heimann,
M., Jaramillo, V. J., Kheshgi, H. S., Le Quere, C., Scholes, R. J., and
Wallace, D. W. R.: The carbon cycle and atmospheric carbon dioxide, in:
Climate Change 2001: the Scientific Basis, edited by: Houghton, J. T., Ding,
Y., Griggs, D. J., Noguer, N., van der Linden, P. J., Xiaosu, D., Maskell,
K., and Johnson, C. A., Cambridge University Press, New York, 2001.
Quigg, A., Finkel, Z. V., Irwin, A. J., Rosenthal, Y., Ho, T.-Y.,
Reinfelder, J. R., Schofield, O., Morel, F. M. M., and Falkowski, P. G.: The
evolutionary inheritance of elemental stoichiometry in marine phytoplankton,
Nature, 425, 291–294, https://doi.org/10.1038/nature01953, 2003.
Raiswell, R. and Canfield, D. E.: The Iron Biogeochemical Cycle Past and
Present, Geochemical Perspectives, 1, 1–2, 2012.
Raynaud, D., Jouzel, J., Barnola, J. M., Chappellaz, J., Delmas, R. J., and
Lorius, C.: The Ice Record of Greenhouse Gases, Science, 259, 926–934,
https://doi.org/10.1126/science.259.5097.926, 1993.
Redfield, A. C., Ketchum, B. H., and Richards, F. A.: The influence of
organisms on the composition of sea-water, in: The Sea, edited by: Hill, M.
N., Interscience Publishers, New York, 26–77, 1963.
Reimers, C. E., Jahnke, R. A., and McCorkle, D. C.: Carbon fluxes and burial
rates over the continental slope and rise off central California with
implications for the global carbon cycle, Global Biogeochem. Cycles, 6,
199–224, https://doi.org/10.1029/92gb00105, 1992.
Reinhard, C. T., Olson, S. L., Schwieterman, E. W., and Lyons, T. W.: False
Negatives for Remote Life Detection on Ocean-Bearing Planets: Lessons from
the Early Earth, Astrobiology, 17, 287–297, https://doi.org/10.1089/ast.2016.1598, 2017a.
Reinhard, C. T., Planavsky, N. J., Gill, B. C., Ozaki, K., Robbins, L. J.,
Lyons, T. W., Fischer, W. W., Wang, C., Cole, D. B., and Konhauser, K. O.:
Evolution of the global phosphorus cycle, Nature, 541, 386–389,
https://doi.org/10.1038/nature20772,
2017b.
Reinhard, C. T., Olson, S. L., Kirtland Turner, S., Pälike, C., Kanzaki, Y., and Ridgwell, A.: Oceanic and atmospheric methane cycling in the cGENIE Earth system model – release v0.9.14, Geosci. Model Dev., 13, 5687–5706, https://doi.org/10.5194/gmd-13-5687-2020, 2020.
Ridgwell, A. and Hargreaves, J. C.: Regulation of atmospheric CO2 by
deep-sea sediments in an Earth system model, Global Biogeochem. Cycles, 21,
GB2008, https://doi.org/10.1029/2006gb002764, 2007.
Romaniello, S. J. and Derry, L. A.: An intermediate-complexity model for
simulating marine biogeochemistry in deep time: Validation against the
modern global ocean, Geochem. Geophys. Geosyst., 11, Q08001,
https://doi.org/10.1029/2009gc002711, 2010.
Rowe, G. T., Morse, J., Nunnally, C., and Boland, G. S.: Sediment community
oxygen consumption in the deep Gulf of Mexico, Deep-Sea Res. Pt. II, 55, 2686–2691, https://doi.org/10.1016/j.dsr2.2008.07.018, 2008.
Ruttenberg, K. C.: Reassessment of the oceanic residence time of phosphorus,
Chem. Geol., 107, 405–409, https://doi.org/10.1016/0009-2541(93)90220-D, 1993.
Ruttenberg, K. C.: The Global Phosphorus Cycle, in: Treatise on
Geochemistry, edited by: Turekian, K. K., Pergamon, Oxford, 585–643,
https://doi.org/10.1016/B0-08-043751-6/08153-6, 2003.
Sachs, O., Sauter, E. J., Schlüter, M., Rutgers van der Loeff, M. M.,
Jerosch, K., and Holby, O.: Benthic organic carbon flux and oxygen
penetration reflect different plankton provinces in the Southern Ocean, Deep-Sea Res. Pt. I, 56, 1319–1335,
https://doi.org/10.1016/j.dsr.2009.02.003, 2009.
Sagan, C., Thompson, W. R., Carlson, R., Gurnett, D., and Hord, C.: A search
for life on Earth from the Galileo spacecraft, Nature, 365, 715–721, 1993.
Sarmiento, J. L. and Gruber, N.: Ocean biogeochemical dynamics, Princeton
University Press, ISBN 0-691-01707-7, 2006.
Sarmiento, J. L. and Toggweiler, J. R.: A new model for the role of the
oceans in determining atmospheric
Schenau, S. J. and De Lange, G. J.: Phosphorus regeneration vs. burial in
sediments of the Arabian Sea, Marine Chem., 75, 201–217, https://doi.org/10.1016/S0304-4203(01)00037-8, 2001.
Schlesinger, W. H. and Bernhardt, E. S.: The Global Cycles of Sulfur and
Mercury, in: Biogeochemistry, 3rd edn., Academic Press, Boston,
469–486, https://doi.org/10.1016/B978-0-12-385874-0.00013-3,
2013.
Schwieterman, E. W., Kiang, N. Y., Parenteau, M. N., Harman, C. E.,
DasSarma, S., Fischer, T. M., Arney, G. N., Hartnett, H. E., Reinhard, C.
T., Olson, S. L., Meadows, V. S., Cockell, C. S., Walker, S. I., Grenfell,
J. L., Hegde, S., Rugheimer, S., Hu, R., and Lyons, T. W.: Exoplanet
Biosignatures: A Review of Remotely Detectable Signs of Life, Astrobiology,
18, 663–708, https://doi.org/10.1089/ast.2017.1729, 2018.
Shaffer, G.: Phosphate pumps and shuttles in the Black Sea, Nature, 321,
515–517, https://doi.org/10.1038/321515a0, 1986.
Shaffer, G. and Sarmiento, J. L.: Biogeochemical cycling in the global
ocean: 1. A new, analytical model with continuous vertical resolution and
high-latitude dynamics, J. Geophys. Res., 100, 2659–2672, https://doi.org/10.1029/94JC01167, 1995.
Shaffer, G., Malskær Olsen, S., and Pepke Pedersen, J. O.: Presentation, calibration and validation of the low-order, DCESS Earth System Model (Version 1), Geosci. Model Dev., 1, 17–51, https://doi.org/10.5194/gmd-1-17-2008, 2008.
Sharoni, S. and Halevy, I.: Geologic controls on phytoplankton elemental
composition, P. Natl Acad. Sci. USA, 119, e2113263118,
https://doi.org/10.1073/pnas.2113263118, 2022.
Siegenthaler, U. and Wenk, T.: Rapid atmospheric CO2 variations and
ocean circulation, Nature, 308, 624–626, https://doi.org/10.1038/308624a0, 1984.
Sleep, N. H.: Dioxygen over geological time, in: Metal ions in biological
systems, edited by: Sigel, A., Sigel, H., and Sigel, R. K. O., Taylor &
Francis Group, Boca Raton, 49–73, 2005.
Slomp, C. P. and Van Cappellen, P.: The global marine phosphorus cycle: sensitivity to oceanic circulation, Biogeosciences, 4, 155–171, https://doi.org/10.5194/bg-4-155-2007, 2007.
Slomp, C. P., Thomson, J., and de Lange, G. J.: Enhanced regeneration of
phosphorus during formation of the most recent eastern Mediterranean
sapropel (S1), Geochim. Cosmochim. Ac., 66, 1171–1184, https://doi.org/10.1016/S0016-7037(01)00848-1, 2002.
Sloyan, B. M.: Spatial variability of mixing in the Southern Ocean, Geophys.
Res. Lett., 32, L18603, https://doi.org/10.1029/2005gl023568, 2005.
Soulet, G., Hilton, R. G., Garnett, M. H., Roylands, T., Klotz, S.,
Croissant, T., Dellinger, M., and Le Bouteiller, C.: Temperature control on
CO2 emissions from the weathering of sedimentary rocks, Nat. Geosci.,
14, 665–671, https://doi.org/10.1038/s41561-021-00805-1, 2021.
Southam, J. R., Peterson, W. H., and Brass, G. W.: Dynamics of anoxia,
Palaeogeogr. Palaeocl., 40, 183–198, https://doi.org/10.1016/0031-0182(82)90089-X, 1982.
Steefel, C. I. and MacQuarrie, K. T. B.: Approaches to modeling of reactive
transport in porous media, Rev. Miner. Geochem., 34,
85–129, 1996.
Suess, E.: Particulate organic carbon flux in the oceans – surface
productivity and oxygen utilization, Nature, 288, 260–263, https://doi.org/10.1038/288260a0,
1980.
Tang, D., Shi, X., Wang, X., and Jiang, G.: Extremely low oxygen
concentration in mid-Proterozoic shallow seawaters, Precambrian Res., 276,
145–157, https://doi.org/10.1016/j.precamres.2016.02.005,
2016.
Tarhan, L. G., Droser, M. L., Planavsky, N. J., and Johnston, D. T.:
Protracted development of bioturbation through the early Palaeozoic Era,
Nat. Geosci., 8, 865, https://doi.org/10.1038/ngeo2537,
2015.
Tarpgaard, I. H., Røy, H., and Jørgensen, B. B.: Concurrent low- and
high-affinity sulfate reduction kinetics in marine sediment, Geochim.
Cosmochim. Ac., 75, 2997–3010, https://doi.org/10.1016/j.gca.2011.03.028, 2011.
The LUVOIR Team: Mission Concept Study Final Report, in: arXiv e-prints, https://doi.org/10.48550/arXiv.1912.06219,
2019.
Tostevin, R., Turchyn, A. V., Farquhar, J., Johnston, D. T., Eldridge, D.
L., Bishop, J. K. B., and McIlvin, M.: Multiple sulfur isotope constraints
on the modern sulfur cycle, Earth Planet. Sc. Lett., 396, 14–21, https://doi.org/10.1016/j.epsl.2014.03.057, 2014.
Tromp, T. K., Van Cappellen, P., and Key, R. M.: A global model for the
early diagenesis of organic carbon and organic phosphorus in marine
sediments, Geochim. Cosmochim. Ac., 59, 1259–1284, https://doi.org/10.1016/0016-7037(95)00042-X, 1995.
Tsunogai, S. and Noriki, S.: Particulate fluxes of carbonate and organic
carbon in the ocean. Is the marine biological activity working as a sink of
the atmospheric carbon?, Tellus B, 43,
265–266, https://doi.org/10.3402/tellusb.v43i2.15272, 1991.
Turchyn, A. V. and Schrag, D. P.: Oxygen Isotope Constraints on the Sulfur
Cycle over the Past 10 Million Years, Science, 303, 2004–2007,
https://doi.org/10.1126/science.1092296, 2004.
Turchyn, A. V. and Schrag, D. P.: Cenozoic evolution of the sulfur cycle:
Insight from oxygen isotopes in marine sulfate, Earth Planet. Sc. Lett.,
241, 763–779, https://doi.org/10.1016/j.epsl.2005.11.007, 2006.
Turnewitsch, R. and Pohl, C.: An estimate of the efficiency of the iron- and
manganese-driven dissolved inorganic phosphorus trap at an oxic/euxinic
water column redoxcline, Global Biogeochem. Cycles, 24, GB4025,
https://doi.org/10.1029/2010gb003820, 2010.
Tyrrell, T.: The relative influences of nitrogen and phosphorus on oceanic
primary production, Nature, 400, 525–531, https://doi.org/10.1038/22941, 1999.
Van Cappellen, P. and Ingall, E. D.: Benthic phosphorus regeneration, net
primary production, and ocean anoxia: A model of the coupled marine
biogeochemical cycles of carbon and phosphorus, Paleoceanography, 9,
677–692, https://doi.org/10.1029/94PA01455, 1994.
Van Cappellen, P. and Ingall, E. D.: Redox Stabilization of the Atmosphere
and Oceans by Phosphorus-Limited Marine Productivity, Science, 271, 493–496,
https://doi.org/10.1126/science.271.5248.493, 1996.
Van Cappellen, P. and Wang, Y.: Cycling of iron and manganese in surface
sediments; a general theory for the coupled transport and reaction of
carbon, oxygen, nitrogen, sulfur, iron, and manganese, Am. J. Sci., 296,
197–243, https://doi.org/10.2475/ajs.296.3.197, 1996.
van de Velde, S. J., Hülse, D., Reinhard, C. T., and Ridgwell, A.: Iron and sulfur cycling in the cGENIE.muffin Earth system model (v0.9.21), Geosci. Model Dev., 14, 2713–2745, https://doi.org/10.5194/gmd-14-2713-2021, 2021.
Volk, T. and Hoffert, M. I.: Ocean carbon pumps: Analysis of relative
strengths and efficiencies in ocean-driven atmospheric CO2 changes, in:
The Carbon Cycle and Atmospheric CO2: Natural Variations Archean to
Present, edited by: Sundquist, E. T. and Broecker, W. S.,
99–110, https://doi.org/10.1029/GM032p0099, 1985.
Walker, J. C. G.: Evolution of the atmosphere, Macmillan, New York, 318
pp., ISBN 0-02-854390-4, 1977.
Walker, J. C. G. and Brimblecombe, P.: Iron and sulfur in the pre-biologic
ocean, Precambrian Res., 28, 205–222, https://doi.org/10.1016/0301-9268(85)90031-2, 1985.
Wallmann, K.: Feedbacks between oceanic redox states and marine
productivity: A model perspective focused on benthic phosphorus cycling,
Global Biogeochem. Cycles, 17, 1084, https://doi.org/10.1029/2002gb001968, 2003.
Wallmann, K.: Phosphorus imbalance in the global ocean?, Global Biogeochem.
Cycles, 24, GB4030, https://doi.org/10.1029/2009gb003643, 2010.
Wang, W.-L., Moore, J. K., Martiny, A. C., and Primeau, F. W.: Convergent
estimates of marine nitrogen fixation, Nature, 566, 205–211,
https://doi.org/10.1038/s41586-019-0911-2, 2019.
WebBook, N. C.: NIST Chemistry WebBook, https://doi.org/10.18434/T4D303, 2022.
Westrich, J. T. and Berner, R. A.: The role of sedimentary organic matter in
bacterial sulfate reduction: The G model tested, Limnol. Oceanogr.,
29, 236–249, https://doi.org/10.4319/lo.1984.29.2.0236, 1984.
Wheat, C. G., Feely, R. A., and Mottl, M. J.: Phosphate removal by oceanic
hydrothermal processes: An update of the phosphorus budget in the oceans,
Geochim. Cosmochim. Ac., 60, 3593–3608, https://doi.org/10.1016/0016-7037(96)00189-5, 1996.
Wheat, C. G., McManus, J., Mottl, M. J., and Giambalvo, E.: Oceanic
phosphorus imbalance: Magnitude of the mid-ocean ridge flank hydrothermal
sink, Geophys. Res. Lett., 30, 1895, https://doi.org/10.1029/2003GL017318, 2003.
Woodward, F. I.: Global primary production, Current Biology, 17, R269–R273,
https://doi.org/10.1016/j.cub.2007.01.054, 2007.
Wortmann, U. G. and Paytan, A.: Rapid Variability of Seawater Chemistry Over
the Past 130 Million Years, Science, 337, 334–336, https://doi.org/10.1126/science.1220656,
2012.
Yakushev, E. V. and Neretin, L. N.: One-dimensional modeling of nitrogen and
sulfur cycles in the aphotic zones of the Black and Arabian Seas, Global
Biogeochem. Cycles, 11, 401–414, https://doi.org/10.1029/97GB00782, 1997.
Yakushev, E. V., Pollehne, F., Jost, G., Kuznetsov, I., Schneider, B., and
Umlauf, L.: Analysis of the water column oxic/anoxic interface in the Black
and Baltic seas with a numerical model, Marine Chem., 107, 388–410,
https://doi.org/10.1016/j.marchem.2007.06.003, 2007.
Yamanaka, Y. and Tajika, E.: The role of the vertical fluxes of particulate
organic matter and calcite in the oceanic carbon cycle: Studies using an
ocean biogeochemical general circulation model, Global Biogeochem. Cycles,
10, 361–382, https://doi.org/10.1029/96gb00634, 1996.
Yao, W. and Millero, F.: The chemistry of the anoxic waters in the Framvaren
Fjord, Norway, Aquatic Geochemistry, 1, 53–88, https://doi.org/10.1007/bf01025231, 1995.
Yaroshevsky, A. A.: Abundances of chemical elements in the Earth's crust,
Geochem. Int., 44, 48–55, https://doi.org/10.1134/s001670290601006x, 2006.
Zabel, M., Dahmke, A., and Schulz, H. D.: Regional distribution of diffusive
phosphate and silicate fluxes through the sediment–water interface: the
eastern South Atlantic, Deep-Sea Res. Pt. I, 45, 277–300, https://doi.org/10.1016/S0967-0637(97)00073-3, 1998.
Zhang, S., Wang, X., Wang, H., Bjerrum, C. J., Hammarlund, E. U., Dahl, T.
W., and Canfield, D. E.: Reply to Planavsky et al.: Strong evidence for high
atmospheric oxygen levels 1,400 million years ago, P. Natl Acad. Sci.
USA, 113, E2552–E2553, https://doi.org/10.1073/pnas.1603982113, 2016.
Zhao, M., Zhang, S., Tarhan, L. G., Reinhard, C. T., and Planavsky, N.: The
role of calcium in regulating marine phosphorus burial and atmospheric
oxygenation, Nat. Commun., 11, 2232, https://doi.org/10.1038/s41467-020-15673-3, 2020.
Short summary
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of...
