Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-5865-2023
© Author(s) 2023. 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-16-5865-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
20 Oct 2023
Model description paper |
| 20 Oct 2023
| 20 Oct 2023
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
Institute of Geochemistry and Petrology, Department of Earth Sciences, ETH Zürich, 8092 Zürich, Switzerland
Related subject area
Biogeosciences
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)
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water and nitrogen perturbations
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
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
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 PFTs to model peatland vegetation, CH4 and CO2 emissions
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
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)
A Novel Eulerian Reaction-Transport Model to Simulate Age and Reactivity Continua Interacting with Mixing Processes
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics
FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modelling
Impact of changes in climate and CO2 on the carbon storage potential of vegetation under limited water availability using SEIB-DGVM version 3.02
FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamics
Climate and parameter sensitivity and induced uncertainties in carbon stock projections for European forests (using LPJ-GUESS 4.0)
Use of genetic algorithms for ocean model parameter optimisation: a case study using PISCES-v2_RC for North Atlantic particulate organic carbon
SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level
Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation
Representation of the phosphorus cycle in the Joint UK Land Environment Simulator (vn5.5_JULES-CNP)
CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5)
The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0
A validation standard for area of habitat maps for terrestrial birds and mammals
Soil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases: SCEPTER v0.9
Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)
A map of global peatland extent created using machine learning (Peat-ML)
Implementation and evaluation of the unified stomatal optimization approach in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES)
ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic
Water Ecosystems Tool (WET) 1.0 – a new generation of flexible aquatic ecosystem model
Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET
Predicting global terrestrial biomes with the LeNet convolutional neural network
KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N2O emission using data from mesocosm experiments
Assessing methane emissions for northern peatlands in ORCHIDEE-PEAT revision 7020
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.
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.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-74, https://doi.org/10.5194/gmd-2023-74, 2023
Revised manuscript accepted for GMD
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 lightweight way.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, and Yanxu Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-89, https://doi.org/10.5194/gmd-2023-89, 2023
Revised manuscript accepted for GMD
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.
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.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-66, https://doi.org/10.5194/gmd-2023-66, 2023
Revised manuscript accepted for GMD
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.
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.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-25, https://doi.org/10.5194/gmd-2023-25, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We present a framework that links biogeochemical-Argo data to models. We utilize Argo dataset to identify sources of model errors, improve and validate model configurations. We imitate the observed physical conditions along the biogeochemical-Argo tracks and focus on the biogeochemical model formulations and parameterizations. We showcase the framework for the Nordic Seas and focus on improvements towards model chlorophyll-a and production dynamics.
Tanya J. R. Lippmann, Monique M. P. D. Heijmans, Ype van der Velde, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-48, https://doi.org/10.5194/gmd-2023-48, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Peatlands store approximately one third of the planet’s terrestrial carbon and have the ability to bother further sequester or release the stored carbon. Process based model are useful tools to understand how peatlands change with changing environmental conditions. Vegetation is a critical component to the exchange of carbon 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.
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-278, https://doi.org/10.5194/egusphere-2023-278, 2023
Short summary
Short summary
This paper introduces a plant hydrodynamic model for the DOE-sponsored dynamic vegetation model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We have identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
EGUsphere, https://doi.org/10.5194/egusphere-2023-46, https://doi.org/10.5194/egusphere-2023-46, 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, bottom trawling, etc. We derive equations for simulating the effect of mixing on central moments that describe the distributions. Then, we demonstrate applications in which these equations are used to model continua in disturbed natural environments.
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).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
Short summary
Short summary
Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
Short summary
Short summary
In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Short summary
There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
Short summary
Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
Short summary
Short summary
Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
Short summary
Short summary
Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
Short summary
Short summary
We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
Short summary
Short summary
To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
Short summary
Short summary
Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
Short summary
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.
Félicien Meunier, Wim Verbruggen, Hans Verbeeck, and Marc Peaucelle
Geosci. Model Dev., 15, 7573–7591, https://doi.org/10.5194/gmd-15-7573-2022, https://doi.org/10.5194/gmd-15-7573-2022, 2022
Short summary
Short summary
Drought stress occurs in plants when water supply (i.e. root water uptake) is lower than the water demand (i.e. atmospheric demand). It is strongly related to soil properties and expected to increase in intensity and frequency in the tropics due to climate change. In this study, we show that contrary to the expectations, state-of-the-art terrestrial biosphere models are mostly insensitive to soil texture and hence probably inadequate to reproduce in silico the plant water status in drying soils.
Stanley I. Nmor, Eric Viollier, Lucie Pastor, Bruno Lansard, Christophe Rabouille, and Karline Soetaert
Geosci. Model Dev., 15, 7325–7351, https://doi.org/10.5194/gmd-15-7325-2022, https://doi.org/10.5194/gmd-15-7325-2022, 2022
Short summary
Short summary
The coastal marine environment serves as a transition zone in the land–ocean continuum and is susceptible to episodic phenomena such as flash floods, which cause massive organic matter deposition. Here, we present a model of sediment early diagenesis that explicitly describes this type of deposition while also incorporating unique flood deposit characteristics. This model can be used to investigate the temporal evolution of marine sediments following abrupt changes in environmental conditions.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Jing Fang, Herman H. Shugart, Feng Liu, Xiaodong Yan, Yunkun Song, and Fucheng Lv
Geosci. Model Dev., 15, 6863–6872, https://doi.org/10.5194/gmd-15-6863-2022, https://doi.org/10.5194/gmd-15-6863-2022, 2022
Short summary
Short summary
Our study provided a detailed description and a package of an individual tree-based carbon model, FORCCHN2. This model used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. The model could reproduce daily carbon fluxes across Northern Hemisphere forests. Given the potential importance of the application of this model, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimation.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
Short summary
Short summary
Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Marcus Falls, Raffaele Bernardello, Miguel Castrillo, Mario Acosta, Joan Llort, and Martí Galí
Geosci. Model Dev., 15, 5713–5737, https://doi.org/10.5194/gmd-15-5713-2022, https://doi.org/10.5194/gmd-15-5713-2022, 2022
Short summary
Short summary
This paper describes and tests a method which uses a genetic algorithm (GA), a type of optimisation algorithm, on an ocean biogeochemical model. The aim is to produce a set of numerical parameters that best reflect the observed data of particulate organic carbon in a specific region of the ocean. We show that the GA can provide optimised model parameters in a robust and efficient manner and can also help detect model limitations, ultimately leading to a reduction in the model uncertainties.
Julien Ruffault, François Pimont, Hervé Cochard, Jean-Luc Dupuy, and Nicolas Martin-StPaul
Geosci. Model Dev., 15, 5593–5626, https://doi.org/10.5194/gmd-15-5593-2022, https://doi.org/10.5194/gmd-15-5593-2022, 2022
Short summary
Short summary
A widespread increase in tree mortality has been observed around the globe, and this trend is likely to continue because of ongoing climate change. Here we present SurEau-Ecos, a trait-based plant hydraulic model to predict tree desiccation and mortality. SurEau-Ecos can help determine the areas and ecosystems that are most vulnerable to drying conditions.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
Short summary
Short summary
We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Mahdi André Nakhavali, Lina M. Mercado, Iain P. Hartley, Stephen Sitch, Fernanda V. Cunha, Raffaello di Ponzio, Laynara F. Lugli, Carlos A. Quesada, Kelly M. Andersen, Sarah E. Chadburn, Andy J. Wiltshire, Douglas B. Clark, Gyovanni Ribeiro, Lara Siebert, Anna C. M. Moraes, Jéssica Schmeisk Rosa, Rafael Assis, and José L. Camargo
Geosci. Model Dev., 15, 5241–5269, https://doi.org/10.5194/gmd-15-5241-2022, https://doi.org/10.5194/gmd-15-5241-2022, 2022
Short summary
Short summary
In tropical ecosystems, the availability of rock-derived elements such as P can be very low. Thus, without a representation of P cycling, tropical forest responses to rising atmospheric CO2 conditions in areas such as Amazonia remain highly uncertain. We introduced P dynamics and its interactions with the N and P cycles into the JULES model. Our results highlight the potential for high P limitation and therefore lower CO2 fertilization capacity in the Amazon forest with low-fertility soils.
Olga Dombrowski, Cosimo Brogi, Harrie-Jan Hendricks Franssen, Damiano Zanotelli, and Heye Bogena
Geosci. Model Dev., 15, 5167–5193, https://doi.org/10.5194/gmd-15-5167-2022, https://doi.org/10.5194/gmd-15-5167-2022, 2022
Short summary
Short summary
Soil carbon storage and food production of fruit orchards will be influenced by climate change. However, they lack representation in models that study such processes. We developed and tested a new sub-model, CLM5-FruitTree, that describes growth, biomass distribution, and management practices in orchards. The model satisfactorily predicted yield and exchange of carbon, energy, and water in an apple orchard and can be used to study land surface processes in fruit orchards at different scales.
Jiaying Zhang, Rafael L. Bras, Marcos Longo, and Tamara Heartsill Scalley
Geosci. Model Dev., 15, 5107–5126, https://doi.org/10.5194/gmd-15-5107-2022, https://doi.org/10.5194/gmd-15-5107-2022, 2022
Short summary
Short summary
We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model with observations of a tropical forest. We used the model to study forest recovery from hurricane disturbance and found that a single hurricane disturbance enhances AGB and BA in the long term compared with a no-hurricane situation. The model developed and results presented in this study can be utilized to understand the impact of hurricane disturbances on forest recovery under the changing climate.
Prabhat Raj Dahal, Maria Lumbierres, Stuart H. M. Butchart, Paul F. Donald, and Carlo Rondinini
Geosci. Model Dev., 15, 5093–5105, https://doi.org/10.5194/gmd-15-5093-2022, https://doi.org/10.5194/gmd-15-5093-2022, 2022
Short summary
Short summary
This paper describes the validation of area of habitat (AOH) maps produced for terrestrial birds and mammals. The main objective was to assess the accuracy of the maps based on independent data. We used open access data from repositories, such as ebird and gbif to check if our maps were a better reflection of species' distribution than random. When points were not available we used logistic models to validate the AOH maps. The majority of AOH maps were found to have a high accuracy.
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.
Félicien Meunier, Sruthi M. Krishna Moorthy, Marc Peaucelle, Kim Calders, Louise Terryn, Wim Verbruggen, Chang Liu, Ninni Saarinen, Niall Origo, Joanne Nightingale, Mathias Disney, Yadvinder Malhi, and Hans Verbeeck
Geosci. Model Dev., 15, 4783–4803, https://doi.org/10.5194/gmd-15-4783-2022, https://doi.org/10.5194/gmd-15-4783-2022, 2022
Short summary
Short summary
We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
Short summary
Short summary
Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Qianyu Li, Shawn P. Serbin, Julien Lamour, Kenneth J. Davidson, Kim S. Ely, and Alistair Rogers
Geosci. Model Dev., 15, 4313–4329, https://doi.org/10.5194/gmd-15-4313-2022, https://doi.org/10.5194/gmd-15-4313-2022, 2022
Short summary
Short summary
Stomatal conductance is the rate of water release from leaves’ pores. We implemented an optimal stomatal conductance model in a vegetation model. We then tested and compared it with the existing empirical model in terms of model responses to key environmental variables. We also evaluated the model with measurements at a tropical forest site. Our study suggests that the parameterization of conductance models and current model response to drought are the critical areas for improving models.
Veli Çağlar Yumruktepe, Annette Samuelsen, and Ute Daewel
Geosci. Model Dev., 15, 3901–3921, https://doi.org/10.5194/gmd-15-3901-2022, https://doi.org/10.5194/gmd-15-3901-2022, 2022
Short summary
Short summary
We describe the coupled bio-physical model ECOSMO II(CHL), which is used for regional configurations for the North Atlantic and the Arctic hind-casting and operational purposes. The model is consistent with the large-scale climatological nutrient settings and is capable of representing regional and seasonal changes, and model primary production agrees with previous measurements. For the users of this model, this paper provides the underlying science, model evaluation and its development.
Nicolas Azaña Schnedler-Meyer, Tobias Kuhlmann Andersen, Fenjuan Rose Schmidt Hu, Karsten Bolding, Anders Nielsen, and Dennis Trolle
Geosci. Model Dev., 15, 3861–3878, https://doi.org/10.5194/gmd-15-3861-2022, https://doi.org/10.5194/gmd-15-3861-2022, 2022
Short summary
Short summary
We present the Water Ecosystems Tool (WET) – a new modular aquatic ecosystem model configurable to a wide array of physical setups, ecosystems and research questions based on the popular FABM–PCLake model. We aim for the model to become a community staple, thus helping to consolidate the state of the art under a few flexible models, with the aim of improving comparability across studies and preventing the
re-inventions of the wheelthat are common to our scientific modeling community.
Hamze Dokoohaki, Bailey D. Morrison, Ann Raiho, Shawn P. Serbin, Katie Zarada, Luke Dramko, and Michael Dietze
Geosci. Model Dev., 15, 3233–3252, https://doi.org/10.5194/gmd-15-3233-2022, https://doi.org/10.5194/gmd-15-3233-2022, 2022
Short summary
Short summary
We present a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon
reanalysisproduct that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. Here, we build on a decade of work on uncertainty propagation to generate the most complete and robust uncertainty accounting available to date.
Hisashi Sato and Takeshi Ise
Geosci. Model Dev., 15, 3121–3132, https://doi.org/10.5194/gmd-15-3121-2022, https://doi.org/10.5194/gmd-15-3121-2022, 2022
Short summary
Short summary
Accurately predicting global coverage of terrestrial biome is one of the earliest ecological concerns, and many empirical schemes have been proposed to characterize their relationship. Here, we demonstrate an accurate and practical method to construct empirical models for operational biome mapping via a convolutional neural network (CNN) approach.
Licheng Liu, Shaoming Xu, Jinyun Tang, Kaiyu Guan, Timothy J. Griffis, Matthew D. Erickson, Alexander L. Frie, Xiaowei Jia, Taegon Kim, Lee T. Miller, Bin Peng, Shaowei Wu, Yufeng Yang, Wang Zhou, Vipin Kumar, and Zhenong Jin
Geosci. Model Dev., 15, 2839–2858, https://doi.org/10.5194/gmd-15-2839-2022, https://doi.org/10.5194/gmd-15-2839-2022, 2022
Short summary
Short summary
By incorporating the domain knowledge into a machine learning model, KGML-ag overcomes the well-known limitations of process-based models due to insufficient representations and constraints, and unlocks the “black box” of machine learning models. Therefore, KGML-ag can outperform existing approaches on capturing the hot moment and complex dynamics of N2O flux. This study will be a critical reference for the new generation of modeling paradigm for biogeochemistry and other geoscience processes.
Elodie Salmon, Fabrice Jégou, Bertrand Guenet, Line Jourdain, Chunjing Qiu, Vladislav Bastrikov, Christophe Guimbaud, Dan Zhu, Philippe Ciais, Philippe Peylin, Sébastien Gogo, Fatima Laggoun-Défarge, Mika Aurela, M. Syndonia Bret-Harte, Jiquan Chen, Bogdan H. Chojnicki, Housen Chu, Colin W. Edgar, Eugenie S. Euskirchen, Lawrence B. Flanagan, Krzysztof Fortuniak, David Holl, Janina Klatt, Olaf Kolle, Natalia Kowalska, Lars Kutzbach, Annalea Lohila, Lutz Merbold, Włodzimierz Pawlak, Torsten Sachs, and Klaudia Ziemblińska
Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
Short summary
Short summary
A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Cited articles
Abbott, A. N., Haley, B. A., and McManus, J.: Bottoms up: Sedimentary control of the deep North Pacific Ocean's ϵNd signature, Geology, 43, 1035–1035, https://doi.org/10.1130/G37114.1, 2015a.
Abbott, A. N., Haley, B. A., McManus, J., and Reimers, C. E.: The sedimentary flux of dissolved rare earth elements to the ocean, Geochim. Cosmochim. Ac., 154, 186–200, https://doi.org/10.1016/j.gca.2015.01.010, 2015b.
Abbott, A. N., Haley, B. A., and McManus, J.: The impact of sedimentary coatings on the diagenetic Nd flux, Earth Planet. Sc. Lett., 449, 217–227, https://doi.org/10.1016/j.epsl.2016.06.001, 2016.
Anbar, A. D. and Rouxel, O.: Metal Stable Isotopes in Paleoceanography, Annu. Rev. Earth Planet. Sci., 35, 717–746, https://doi.org/10.1146/annurev.earth.34.031405.125029, 2007.
Anderson, R. F.: GEOTRACES: Accelerating Research on the Marine Biogeochemical Cycles of Trace Elements and Their Isotopes, Annu. Rev. Mar. Sci., 12, 49–85, https://doi.org/10.1146/annurev-marine-010318-095123, 2020.
Archer, C. and Vance, D.: The isotopic signature of the global riverine molybdenum flux and anoxia in the ancient oceans, Nat. Geosci., 1, 597–600, https://doi.org/10.1038/ngeo282, 2008.
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, 17-1–17-21, https://doi.org/10.1029/2000GB001288, 2002.
Balay, S., Abhyankar, S., Adams, M. F., Benson, S., Brown, J., Brune, P., Buschelman, K., Constantinescu, E., Dalcin, L., Dener, A., Eijkhout, V., Faibussowitsch, J., Gropp, W. D., Hapla, V., Isaac, T., Jolivet, P., Karpeev, D., Kaushik, D., Knepley, M. G., Kong, F., Kruger, S., May, D. A., McInnes, L. C., Mills, R. T., Mitchell, L., Munson, T., Roman, J. E., Rupp, K., Sanan, P., Sarich, J., Smith, B. F., Zampini, S., Zhang, H., Zhang, H., and Zhang, J.: PETSc/TAO Users Manual, technical report, Argonne National Laboratory, https://doi.org/10.2172/1968587, 2022.
Berner, R. A.: Early Diagenesis: A Theoretical Approach, Princeton University Press, 260 pp., ISBN 9780691082608, 1980.
Bezanson, J., Edelman, A., Karpinski, S., and Shah, V.: Julia: A Fresh Approach to Numerical Computing, SIAM Rev., 59, 65–98, https://doi.org/10.1137/141000671, 2017.
Boudreau, B. P.: Modelling the sulfide-oxygen reaction and associated pH gradients in porewaters, Geochim. Cosmochim. Ac., 55, 145–159, https://doi.org/10.1016/0016-7037(91)90407-V, 1991.
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.
Boudreau, B. P.: Diagenetic models and their implementation: modelling transport and reactions in aquatic sediments, Springer, Berlin, New York, ISBN 3-540-61125-8, 1997.
Boudreau, B. P. and Canfield, D. E.: A provisional diagenetic model for pH in anoxic porewaters: Application to the FOAM Site, J. Marine Res., 46, 429–455, https://doi.org/10.1357/002224088785113603, 1988.
Boudreau, B. P. and Canfield, D. E.: A comparison of closed- and open-system models for porewater pH and calcite-saturation state, Geochim. Cosmochim. Ac., 57, 317–334, https://doi.org/10.1016/0016-7037(93)90434-X, 1993.
Boudreau, B. P., Arnosti, C., Jørgensen, B. B., and Canfield, D. E.: Comment on “Physical Model for the Decay and Preservation of Marine Organic Carbon”, Science, 319, 1616, https://doi.org/10.1126/science.1148589, 2008.
Burdige, D. J.: The biogeochemistry of manganese and iron reduction in marine sediments, Earth-Sci. Rev., 35, 249–284, https://doi.org/10.1016/0012-8252(93)90040-E, 1993.
Burdige, D. J.: Geochemistry of Marine Sediments, Princeton University Press, 646 pp., ISBN 9780691095066, 2006.
Cameron, V. and Vance, D.: Heavy nickel isotope compositions in rivers and the oceans, Geochim. Cosmochim. Ac., 128, 195–211, https://doi.org/10.1016/j.gca.2013.12.007, 2014.
Ciscato, E. R., Bontognali, T. R. R., and Vance, D.: Nickel and its isotopes in organic-rich sediments: implications for oceanic budgets and a potential record of ancient seawater, Earth Planet. Sc. Lett., 494, 239–250, https://doi.org/10.1016/j.epsl.2018.04.061, 2018.
Covalt, M.: ILUZero.jl, GitHub [code], https://github.com/mcovalt/ILUZero.jl (last access: 26 July 2023), 2022.
Crusius, J. and Thomson, J.: Comparative behavior of authigenic Re, U, and Mo during reoxidation and subsequent long-term burial in marine sediments, Geochim. Cosmochim. Ac., 64, 2233–2242, https://doi.org/10.1016/S0016-7037(99)00433-0, 2000.
Dale, A. W., Nickelsen, L., Scholz, F., Hensen, C., Oschlies, A., and Wallmann, K.: A revised global estimate of dissolved iron fluxes from marine sediments, Global Biogeochem. Cycles, 29, 691–707, https://doi.org/10.1002/2014GB005017, 2015.
Dickson, A. G., Sabine, C. L., and Christian, J. R. (Eds.): Guide to best practices for ocean CO2 measurements, PICES Special Publication 3, 191 pp., https://doi.org/10.25607/OBP-1342, 2007.
Du, J.: SedTrace.jl: a Julia package for generating and running reactive-transport models of marine sediment diagenesis, Zenodo [code], https://doi.org/10.5281/zenodo.7225861, 2022.
Du, J., Haley, B. A., and Mix, A. C.: Neodymium isotopes in authigenic phases, bottom waters and detrital sediments in the Gulf of Alaska and their implications for paleo-circulation reconstruction, Geochim. Cosmochim. Ac., 193, 14–35, https://doi.org/10.1016/j.gca.2016.08.005, 2016.
Du, J., Haley, B. A., Mix, A. C., Walczak, M. H., and Praetorius, S. K.: Flushing of the deep Pacific Ocean and the deglacial rise of atmospheric CO2 concentrations, Nat. Geosci., 11, 749–755, https://doi.org/10.1038/s41561-018-0205-6, 2018.
Du, J., Haley, B. A., and Mix, A. C.: Evolution of the Global Overturning Circulation since the Last Glacial Maximum based on marine authigenic neodymium isotopes, Quaternary Sci. Rev., 241, 106396, https://doi.org/10.1016/j.quascirev.2020.106396, 2020.
Du, J., Haley, B. A., Mix, A. C., Abbott, A. N., McManus, J., and Vance, D.: Reactive-transport modeling of neodymium and its radiogenic isotope in deep-sea sediments: The roles of authigenesis, marine silicate weathering and reverse weathering, Earth Planet. Sc. Lett., 596, 117792, https://doi.org/10.1016/j.epsl.2022.117792, 2022.
Dunning, I., Huchette, J., and Lubin, M.: JuMP: A Modeling Language for Mathematical Optimization, SIAM Rev., 59, 295–320, https://doi.org/10.1137/15M1020575, 2017.
Elderfield, H. and Greaves, M. J.: The rare earth elements in seawater, Nature, 296, 214–219, https://doi.org/10.1038/296214a0, 1982.
Elrod, V. A., Berelson, W. M., Coale, K. H., and Johnson, K. S.: The flux of iron from continental shelf sediments: A missing source for global budgets, Geophys. Res. Lett., 31, L12307, https://doi.org/10.1029/2004GL020216, 2004.
Erickson, B. E. and Helz, G. R.: Molybdenum(VI) speciation in sulfidic waters:: Stability and lability of thiomolybdates, Geochim. Cosmochim. Ac., 64, 1149–1158, https://doi.org/10.1016/S0016-7037(99)00423-8, 2000.
Fiadeiro, M. E. and Veronis, G.: On weighted-mean schemes for the finite-difference approximation to the advection-diffusion equation, Tellus, 29, 512–522, https://doi.org/10.3402/tellusa.v29i6.11385, 1977.
Frank, M.: Radiogenic isotopes: Tracers of past ocean circulation and erosional input, Rev. Geophys., 40, 1001, https://doi.org/10.1029/2000RG000094, 2002.
Freitas, F. S., Pika, P. A., Kasten, S., Jørgensen, B. B., Rassmann, J., Rabouille, C., Thomas, S., Sass, H., Pancost, R. D., and Arndt, S.: New insights into large-scale trends of apparent organic matter reactivity in marine sediments and patterns of benthic carbon transformation, Biogeosciences, 18, 4651–4679, https://doi.org/10.5194/bg-18-4651-2021, 2021.
Gardner, D. J., Reynolds, D. R., Woodward, C. S., and Balos, C. J.: Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 48, 31:1–31:24, https://doi.org/10.1145/3539801, 2022.
Gattuso, J.-P., Orr, J., Epitalon, J.-M., Baldry, K., Hoshijima, U., and Abulos: seacarb: seawater carbonate chemistry. R package version 3.3.0., Zenodo [code], https://doi.org/10.5281/zenodo.4600014, 2021.
Gebremedhin, A. H., Manne, F., and Pothen, A.: What Color Is Your Jacobian? Graph Coloring for Computing Derivatives, SIAM Rev., 47, 629–705, https://doi.org/10.1137/S0036144504444711, 2005.
Goldstein, S. L. and Hemming, S. R.: Long-lived Isotopic Tracers in Oceanography, Paleoceanography, and Ice-sheet Dynamics, in: Treatise on Geochemistry, edited by: Holland, H. D. and Turekian, K. K., Pergamon, Oxford, 453–489, https://doi.org/10.1016/B978-0-08-095975-7.00617-3, 2003.
Gowda, S., Ma, Y., Churavy, V., Edelman, A., and Rackauckas, C.: Sparsity Programming: Automated Sparsity-Aware Optimizations in Differentiable Programming, Program Transformations for ML Workshop at NeurIPS 2019, 2022.
Haley, B. A., Du, J., Abbott, A. N., and McManus, J.: The Impact of Benthic Processes on Rare Earth Element and Neodymium Isotope Distributions in the Oceans, Front. Marine Sci., 4, 426, https://doi.org/10.3389/fmars.2017.00426, 2017.
Hindmarsh, A. C., Brown, P. N., Grant, K. E., Lee, S. L., Serban, R., Shumaker, D. E., and Woodward, C. S.: SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers, ACM Trans. Math. Softw., 31, 363–396, https://doi.org/10.1145/1089014.1089020, 2005.
Hoffmann, K. A. and Chiang, S. T.: Computational Fluid Dynamics, Engineering Education System, 502 pp., ISBN 0-9623731-0-9, 2000.
Hofmann, A. F., Meysman, F. J. R., Soetaert, K., and Middelburg, J. J.: A step-by-step procedure for pH model construction in aquatic systems, Biogeosciences, 5, 227–251, https://doi.org/10.5194/bg-5-227-2008, 2008.
Hofmann, A. F., Middelburg, J. J., Soetaert, K., and Meysman, F. J. R.: pH modelling in aquatic systems with time-variable acid-base dissociation constants applied to the turbid, tidal Scheldt estuary, Biogeosciences, 6, 1539–1561, https://doi.org/10.5194/bg-6-1539-2009, 2009.
Hofmann, A. F., Middelburg, J. J., Soetaert, K., A.Wolf-Gladrow, D., and Meysman, F. J. R.: Proton cycling, buffering, and reaction stoichiometry in natural waters, Marine Chem., 121, 246–255, https://doi.org/10.1016/j.marchem.2010.05.004, 2010.
Homoky, W. B., Weber, T., Berelson, W. M., Conway, T. M., Henderson, G. M., Hulten, M. van, Jeandel, C., Severmann, S., and Tagliabue, A.: Quantifying trace element and isotope fluxes at the ocean–sediment boundary: a review, Phil. T. Roy. Soc. A, 374, 20160246, https://doi.org/10.1098/rsta.2016.0246, 2016.
Horner, T. J., Little, S. H., Conway, T. M., Farmer, J. R., Hertzberg, J. E., Janssen, D. J., Lough, A. J. M., McKay, J. L., Tessin, A., Galer, S. J. G., Jaccard, S. L., Lacan, F., Paytan, A., Wuttig, K., and Members, G.-P. B. P. W. G.: Bioactive Trace Metals and Their Isotopes as Paleoproductivity Proxies: An Assessment Using GEOTRACES-Era Data, Global Biogeochem. Cycles, 35, e2020GB006814, https://doi.org/10.1029/2020GB006814, 2021.
Hülse, D., Arndt, S., Daines, S., Regnier, P., and Ridgwell, A.: OMEN-SED 1.0: a novel, numerically efficient organic matter sediment diagenesis module for coupling to Earth system models, Geosci. Model Dev., 11, 2649–2689, https://doi.org/10.5194/gmd-11-2649-2018, 2018.
Humphreys, M. P., Waters, J. F., Turner, D. R., Dickson, A. G., and Clegg, S. L.: Chemical speciation models based upon the Pitzer activity coefficient equations, including the propagation of uncertainties: Artificial seawater from 0 to 45 ∘C, Marine Chem., 244, 104095, https://doi.org/10.1016/j.marchem.2022.104095, 2022.
Jahnke, R. A.: The synthesis and solubility of carbonate fluorapatite, Am. J. Sci., 284, 58–78, https://doi.org/10.2475/ajs.284.1.58, 1984.
Jeandel, C.: Overview of the mechanisms that could explain the “Boundary Exchange” at the land–ocean contact, Phil. Trans. R. Soc. A, 374, 20150287, https://doi.org/10.1098/rsta.2015.0287, 2016.
Jørgensen, B. B. and Revsbech, N. P.: Colorless Sulfur Bacteria, Beggiatoa spp. and Thiovulum spp., in O2 and H2S Microgradients, Appl. Environ. Microbiol., 45, 1261–1270, https://doi.org/10.1128/aem.45.4.1261-1270.1983, 1983.
Jourabchi, P., Cappellen, P. V., and Regnier, P.: Quantitative interpretation of pH distributions in aquatic sediments: A reaction-transport modeling approach, Am. J. Sci., 305, 919–956, https://doi.org/10.2475/ajs.305.9.919, 2005.
Jourabchi, P., Meile, C., Pasion, L. R., and Van Cappellen, P.: Quantitative interpretation of pore water O2 and pH distributions in deep-sea sediments, Geochim. Cosmochim. Ac., 72, 1350–1364, https://doi.org/10.1016/j.gca.2007.12.012, 2008.
Katsev, S., Sundby, B., and Mucci, A.: Modeling vertical excursions of the redox boundary in sediments: Application to deep basins of the Arctic Ocean, Limnol. Oceanogr., 51, 1581–1593, https://doi.org/10.4319/lo.2006.51.4.1581, 2006.
Kendall, B., Dahl, T. W., and Anbar, A. D.: Good Golly, Why Moly? THE STABLE ISOTOPE GEOCHEMISTRY OF MOLYBDENUM, in: Non-Traditional Stable Isotopes, edited by: Teng, F.-Z., Watkins, J., and Dauphas, N., De Gruyter, 683–732, https://doi.org/10.1515/9783110545630-017, 2017.
Knoll, D. A. and Keyes, D. E.: Jacobian-free Newton–Krylov methods: a survey of approaches and applications, J. Comput. Phys., 193, 357–397, https://doi.org/10.1016/j.jcp.2003.08.010, 2004.
Lacan, F. and Jeandel, C.: Neodymium isotopes as a new tool for quantifying exchange fluxes at the continent–ocean interface, Earth Planet. Sc. Lett., 232, 245–257, https://doi.org/10.1016/j.epsl.2005.01.004, 2005.
Lam, P. J. and Anderson, R. F.: GEOTRACES: The Marine Biogeochemical Cycle of Trace Elements and Their Isotopes, Elements, 14, 377–378, https://doi.org/10.2138/gselements.14.6.377, 2018.
Lau, K. V., Lyons, T. W., and Maher, K.: Uranium reduction and isotopic fractionation in reducing sediments: Insights from reactive transport modeling, Geochim. Cosmochim. Ac., 287, 65–92, https://doi.org/10.1016/j.gca.2020.01.021, 2020.
Lemaitre, N., Du, J., de Souza, G. F., Archer, C., and Vance, D.: The essential bioactive role of nickel in the oceans: Evidence from nickel isotopes, Earth Planet. Sc. Lett., 584, 117513, https://doi.org/10.1016/j.epsl.2022.117513, 2022.
Li, Y.-H. and Gregory, S.: Diffusion of ions in sea water and in deep-sea sediments, Geochim. Cosmochim. Ac., 38, 703–714, https://doi.org/10.1016/0016-7037(74)90145-8, 1974.
Little, S. H., Vance, D., Walker-Brown, C., and Landing, W. M.: The oceanic mass balance of copper and zinc isotopes, investigated by analysis of their inputs, and outputs to ferromanganese oxide sediments, Geochim. Cosmochim. Ac., 125, 673–693, https://doi.org/10.1016/j.gca.2013.07.046, 2014.
Little, S. H., Archer, C., McManus, J., Najorka, J., Wegorzewski, A. V., and Vance, D.: Towards balancing the oceanic Ni budget, Earth Planet. Sc. Lett., 547, 116461, https://doi.org/10.1016/j.epsl.2020.116461, 2020.
Llorente, V. J., ten Thije Boonkkamp, J. H. M., Pascau, A., and Anthonissen, M. J. H.: Similarities and differences of two exponential schemes for convection-diffusion problems: The FV-CF and ENATE schemes, Appl. Math. Comput., 365, 124700, https://doi.org/10.1016/j.amc.2019.124700, 2020.
Luff, R., Haeckel, M., and Wallmann, K.: Robust and fast FORTRAN and MATLAB® libraries to calculate pH distributions in marine systems, Comput. Geosci., 27, 157–169, https://doi.org/10.1016/S0098-3004(00)00097-2, 2001.
Lyons, T. W., Anbar, A. D., Severmann, S., Scott, C., and Gill, B. C.: Tracking Euxinia in the Ancient Ocean: A Multiproxy Perspective and Proterozoic Case Study, Annu. Rev. Earth Planet. Sci., 37, 507–534, https://doi.org/10.1146/annurev.earth.36.031207.124233, 2009.
Maher, K., Steefel, C. I., DePaolo, D. J., and Viani, B. E.: The mineral dissolution rate conundrum: Insights from reactive transport modeling of U isotopes and pore fluid chemistry in marine sediments, Geochim. Cosmochim. Ac., 70, 337–363, https://doi.org/10.1016/j.gca.2005.09.001, 2006.
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.
Meile, C. and Van Cappellen, P.: Particle age distributions and O2 exposure times: Timescales in bioturbated sediments, Global Biogeochem. Cycles, 19, GB3013, https://doi.org/10.1029/2004GB002371, 2005.
Meile, C., Berg, P., Van Cappellen, P., and Tuncay, K.: Solute-specific pore water irrigation: Implications for chemical cycling in early diagenesis, J. Mar. Res., 63, 601–621, https://doi.org/10.1357/0022240054307885, 2005.
Meurer, A., Smith, C. P., Paprocki, M., Èertík, O., Kirpichev, S. B., Rocklin, M., Kumar, Am., Ivanov, S., Moore, J. K., Singh, S., Rathnayake, T., Vig, S., Granger, B. E., Muller, R. P., Bonazzi, F., Gupta, H., Vats, S., Johansson, F., Pedregosa, F., Curry, M. J., Terrel, A. R., Rouèka, Š., Saboo, A., Fernando, I., Kulal, S., Cimrman, R., and Scopatz, A.: SymPy: symbolic computing in Python, PeerJ Comput. Sci., 3, e103, https://doi.org/10.7717/peerj-cs.103, 2017.
Meysman, F. J. R., Middelburg, J. J., Herman, P. M. J., and Heip, C. H. R.: Reactive transport in surface sediments. II. Media: an object-oriented problem-solving environment for early diagenesis, Comput. Geosci., 29, 301–318, https://doi.org/10.1016/S0098-3004(03)00007-4, 2003.
Millero, F. J. and Schreiber, D. R.: Use of the ion pairing model to estimate activity coefficients of the ionic components of natural waters, Am. J. Sci., 282, 1508–1540, https://doi.org/10.2475/ajs.282.9.1508, 1982.
Morel, F. M. M., Lam, P. J., and Saito, M. A.: Trace Metal Substitution in Marine Phytoplankton, Annu. Rev. Earth Planet. Sci., 48, 491–517, https://doi.org/10.1146/annurev-earth-053018-060108, 2020.
Palmer, M. R. and Elderfield, H.: Sr isotope composition of sea water over the past 75 Myr, Nature, 314, 526–528, https://doi.org/10.1038/314526a0, 1985.
Paraska, D. W., Hipsey, M. R., and Salmon, S. U.: Sediment diagenesis models: Review of approaches, challenges and opportunities, Environ. Model. Softw., 61, 297–325, https://doi.org/10.1016/j.envsoft.2014.05.011, 2014.
Pasquier, B., Primeau, F. W., and John, S. G.: AIBECS.jl: A tool for exploring global marine biogeochemical cycles, J. Open Source Softw., 7, 3814, https://doi.org/10.21105/joss.03814, 2022.
Piepgras, D. J., Wasserburg, G. J., and Dasch, E. J.: The isotopic composition of Nd in different ocean masses, Earth Planet. Sc. Lett., 45, 223–236, https://doi.org/10.1016/0012-821X(79)90125-0, 1979.
Pierrot, D. and Millero, F. J.: The Speciation of Metals in Natural Waters, Aquat. Geochem., 23, 1–20, https://doi.org/10.1007/s10498-016-9292-4, 2017.
Rackauckas, C. and Nie, Q.: DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia, J. Open Res. Softw., 5, 15, https://doi.org/10.5334/jors.151, 2017.
Reimers, C. E., Ruttenberg, K. C., Canfield, D. E., Christiansen, M. B., and Martin, J. B.: Porewater pH and authigenic phases formed in the uppermost sediments of the Santa Barbara Basin, Geochim. Cosmochim. Ac., 60, 4037–4057, https://doi.org/10.1016/S0016-7037(96)00231-1, 1996.
Revels, J., Lubin, M., and Papamarkou, T.: Forward-Mode Automatic Differentiation in Julia, arXiv [preprint], https://doi.org/10.48550/arXiv.1607.07892, 26 July 2016.
SCOR Working Group: GEOTRACES – An international study of the global marine biogeochemical cycles of trace elements and their isotopes, Geochemistry, 67, 85–131, https://doi.org/10.1016/j.chemer.2007.02.001, 2007.
Soetaert, K. and Meysman, F.: Reactive transport in aquatic ecosystems: Rapid model prototyping in the open source software R, Environ. Model. Softw., 32, 49–60, https://doi.org/10.1016/j.envsoft.2011.08.011, 2012.
Soetaert, K., Herman, P. M. J., and Middelburg, J. J.: A model of early diagenetic processes from the shelf to abyssal depths, Geochim. Cosmochim. Ac., 60, 1019–1040, https://doi.org/10.1016/0016-7037(96)00013-0, 1996.
Sridhar, A., Tissaoui, Y., Marras, S., Shen, Z., Kawczynski, C., Byrne, S., Pamnany, K., Waruszewski, M., Gibson, T. H., Kozdon, J. E., Churavy, V., Wilcox, L. C., Giraldo, F. X., and Schneider, T.: Large-eddy simulations with ClimateMachine v0.2.0: a new open-source code for atmospheric simulations on GPUs and CPUs, Geosci. Model Dev., 15, 6259–6284, https://doi.org/10.5194/gmd-15-6259-2022, 2022.
Stoppels, H.: ILU for SparseMatrixCSC, GitHub [code], https://github.com/haampie/IncompleteLU.jl (last access: 26 July 2023), 2022.
Sulpis, O., Humphreys, M. P., Wilhelmus, M. M., Carroll, D., Berelson, W. M., Menemenlis, D., Middelburg, J. J., and Adkins, J. F.: RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave, Geosci. Model Dev., 15, 2105–2131, https://doi.org/10.5194/gmd-15-2105-2022, 2022.
Tagliabue, A., Bowie, A. R., Boyd, P. W., Buck, K. N., Johnson, K. S., and Saito, M. A.: The integral role of iron in ocean biogeochemistry, Nature, 543, 51–59, https://doi.org/10.1038/nature21058, 2017.
ten Thije Boonkkamp, J. H. M. and Anthonissen, M. J. H.: Extension of the Complete Flux Scheme to Time-Dependent Conservation Laws, in: Numerical Mathematics and Advanced Applications 2009, Berlin, Heidelberg, 865–873, https://doi.org/10.1007/978-3-642-11795-4_93, 2010.
ten Thije Boonkkamp, J. H. M. and Anthonissen, M. J. H.: The Finite Volume-Complete Flux Scheme for Advection-Diffusion-Reaction Equations, J. Sci. Comput., 46, 47–70, https://doi.org/10.1007/s10915-010-9388-8, 2011.
Tossell, J. A.: Calculating the partitioning of the isotopes of Mo between oxidic and sulfidic species in aqueous solution, Geochim. Cosmochim. Ac., 69, 2981–2993, https://doi.org/10.1016/j.gca.2005.01.016, 2005.
Vance, D., Archer, C., Little, S. H., Köbberich, M., and de Souza, G. F.: The oceanic cycles of the transition metals and their isotopes, Ac. Geochim., 36, 359–362, https://doi.org/10.1007/s11631-017-0162-6, 2017.
Wang, Y. and Van Cappellen, P.: A multicomponent reactive transport model of early diagenesis: Application to redox cycling in coastal marine sediments, Geochim. Cosmochim. Ac., 60, 2993–3014, https://doi.org/10.1016/0016-7037(96)00140-8, 1996.
Werder, M.: Parameters.jl, GitHub [code], https://github.com/mauro3/Parameters.jl (last access: 26 July 2023), 2022a.
Werder, M.: UnPack.jl, GitHub [code], https://github.com/mauro3/UnPack.jl (last access: 26 July 2023), 2022b.
Zeebe, R. E. and Wolf-Gladrow, D. A.: CO2 in Seawater: Equilibrium, Kinetics, Isotopes, Elsevier, Amsterdam, 346 pp., ISBN 9780444509468, 2001.
Zheng, Y., Anderson, R. F., van Geen, A., and Kuwabara, J.: Authigenic molybdenum formation in marine sediments: a link to pore water sulfide in the Santa Barbara Basin, Geochim. Cosmochim. Ac., 64, 4165–4178, https://doi.org/10.1016/S0016-7037(00)00495-6, 2000.
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.
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean...
