Articles | Volume 12, issue 5
Geosci. Model Dev., 12, 1765–1789, 2019
https://doi.org/10.5194/gmd-12-1765-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 12, 1765–1789, 2019
https://doi.org/10.5194/gmd-12-1765-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
06 May 2019
Development and technical paper
| 06 May 2019
Towards end-to-end (E2E) modelling in a consistent NPZD-F modelling framework (ECOSMO E2E_v1.0): application to the North Sea and Baltic Sea
Ute Daewel et al.
Related authors
Johannes Bieser, David Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-427, https://doi.org/10.5194/gmd-2021-427, 2022
Preprint under review for GMD
Short summary
Short summary
We developed a 3d model for mercury (Hg) cycling and bioaccumulation in the ocean. Hg is a major global pollutant regulated under the UN Minamata Convention. Anthropogenic Hg emission are transported globally and eventually reach the worlds Oceans. There, Hg is transformed into an even more toxic and bioaccumulative pollutant: Methylmercury (MeHg). The MERCY model is able to predict the fate of Hg in the ocean, the formation of MeHg, and its accumulation in the food web.
Philipp Heinrich, Stefan Hagemann, Ralf Weisse, Corinna Schrum, Ute Daewel, and Lidia Gaslikova
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-187, https://doi.org/10.5194/nhess-2022-187, 2022
Preprint under review for NHESS
Short summary
Short summary
High sea water levels co-occurring with high river discharges have the potential to cause destructive flooding. For the past decades, the number of such compound events was larger than expected by pure chance for most of the western facing coasts in Europe. Additionally rivers with smaller catchments showed higher numbers. In most cases, such events were associated with a large-scale weather pattern characterized by westerly winds and strong rainfall.
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.
Laurie M. Charrieau, Karl Ljung, Frederik Schenk, Ute Daewel, Emma Kritzberg, and Helena L. Filipsson
Biogeosciences, 16, 3835–3852, https://doi.org/10.5194/bg-16-3835-2019, https://doi.org/10.5194/bg-16-3835-2019, 2019
Short summary
Short summary
We reconstructed environmental changes in the Öresund during the last 200 years, using foraminifera (microfossils), sediment, and climate data. Five zones were identified, reflecting oxygen, salinity, food content, and pollution levels for each period. The largest changes occurred ~ 1950, towards stronger currents. The foraminifera responded quickly (< 10 years) to the changes. Moreover, they did not rebound when the system returned to the previous pattern, but displayed a new equilibrium state.
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265, https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
Short summary
Short summary
The Elbe estuary is subject to vigorous tidal forcing from the sea side and considerable biological inputs from the land side. Our 3D numerical coupled physical-biogeochemical integrates these forcing signals and provides highly realistic hindcasts of the associated dynamics. Model simulations show that the freshwater part of Elbe estuary is inhabited by plankton. According to simulations these organism play a key role in converting organic inputs into nitrate, the major inorganic nutrient.
Changjin Zhao, Ute Daewel, and Corinna Schrum
Earth Syst. Dynam., 10, 287–317, https://doi.org/10.5194/esd-10-287-2019, https://doi.org/10.5194/esd-10-287-2019, 2019
Short summary
Short summary
Our study highlights the importance of tides in controlling the spatial and temporal distributions North Sea primary production based on numerical experiments. We identified two different response chains acting in different regions of the North Sea. (i) In the southern shallow areas, strong tidal mixing dilutes phytoplankton concentrations and increases turbidity, thus decreasing NPP. (ii) In the frontal regions, tidal mixing infuses nutrients into the surface mixed layer, thus increasing NPP.
Ute Daewel and Corinna Schrum
Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, https://doi.org/10.5194/esd-8-801-2017, 2017
Short summary
Short summary
Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.
Johannes Bieser, David Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-427, https://doi.org/10.5194/gmd-2021-427, 2022
Preprint under review for GMD
Short summary
Short summary
We developed a 3d model for mercury (Hg) cycling and bioaccumulation in the ocean. Hg is a major global pollutant regulated under the UN Minamata Convention. Anthropogenic Hg emission are transported globally and eventually reach the worlds Oceans. There, Hg is transformed into an even more toxic and bioaccumulative pollutant: Methylmercury (MeHg). The MERCY model is able to predict the fate of Hg in the ocean, the formation of MeHg, and its accumulation in the food web.
Philipp Heinrich, Stefan Hagemann, Ralf Weisse, Corinna Schrum, Ute Daewel, and Lidia Gaslikova
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-187, https://doi.org/10.5194/nhess-2022-187, 2022
Preprint under review for NHESS
Short summary
Short summary
High sea water levels co-occurring with high river discharges have the potential to cause destructive flooding. For the past decades, the number of such compound events was larger than expected by pure chance for most of the western facing coasts in Europe. Additionally rivers with smaller catchments showed higher numbers. In most cases, such events were associated with a large-scale weather pattern characterized by westerly winds and strong rainfall.
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.
Onur Kerimoglu, Yoana G. Voynova, Fatemeh Chegini, Holger Brix, Ulrich Callies, Richard Hofmeister, Knut Klingbeil, Corinna Schrum, and Justus E. E. van Beusekom
Biogeosciences, 17, 5097–5127, https://doi.org/10.5194/bg-17-5097-2020, https://doi.org/10.5194/bg-17-5097-2020, 2020
Short summary
Short summary
In this study, using extensive field observations and a numerical model, we analyzed the physical and biogeochemical structure of a coastal system following an extreme flood event. Our results suggest that a number of anomalous observations were driven by a co-occurrence of peculiar meteorological conditions and increased riverine discharges. Our results call for attention to the combined effects of hydrological and meteorological extremes that are anticipated to increase in frequency.
Laurie M. Charrieau, Karl Ljung, Frederik Schenk, Ute Daewel, Emma Kritzberg, and Helena L. Filipsson
Biogeosciences, 16, 3835–3852, https://doi.org/10.5194/bg-16-3835-2019, https://doi.org/10.5194/bg-16-3835-2019, 2019
Short summary
Short summary
We reconstructed environmental changes in the Öresund during the last 200 years, using foraminifera (microfossils), sediment, and climate data. Five zones were identified, reflecting oxygen, salinity, food content, and pollution levels for each period. The largest changes occurred ~ 1950, towards stronger currents. The foraminifera responded quickly (< 10 years) to the changes. Moreover, they did not rebound when the system returned to the previous pattern, but displayed a new equilibrium state.
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265, https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
Short summary
Short summary
The Elbe estuary is subject to vigorous tidal forcing from the sea side and considerable biological inputs from the land side. Our 3D numerical coupled physical-biogeochemical integrates these forcing signals and provides highly realistic hindcasts of the associated dynamics. Model simulations show that the freshwater part of Elbe estuary is inhabited by plankton. According to simulations these organism play a key role in converting organic inputs into nitrate, the major inorganic nutrient.
Changjin Zhao, Ute Daewel, and Corinna Schrum
Earth Syst. Dynam., 10, 287–317, https://doi.org/10.5194/esd-10-287-2019, https://doi.org/10.5194/esd-10-287-2019, 2019
Short summary
Short summary
Our study highlights the importance of tides in controlling the spatial and temporal distributions North Sea primary production based on numerical experiments. We identified two different response chains acting in different regions of the North Sea. (i) In the southern shallow areas, strong tidal mixing dilutes phytoplankton concentrations and increases turbidity, thus decreasing NPP. (ii) In the frontal regions, tidal mixing infuses nutrients into the surface mixed layer, thus increasing NPP.
Ute Daewel and Corinna Schrum
Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, https://doi.org/10.5194/esd-8-801-2017, 2017
Short summary
Short summary
Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.
Related subject area
Biogeosciences
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)
ForamEcoGENIE 2.0: Incorporating symbiosis and spine traits into a trait-based global planktic foraminifera model
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
A dynamic local-scale vegetation model for lycopsids (LYCOm v1.0)
Soil-related developments of the Biome-BGCMuSo v6.2 terrestrial ecosystem model
Global evaluation of the Ecosystem Demography model (ED v3.0)
A new snow module improves predictions of the isotope-enabled MAIDENiso forest growth model
Calibrating the soil organic carbon model Yasso20 with multiple datasets
The PFLOTRAN Reaction Sandbox
A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands
Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2)
Locating trees to mitigate outdoor radiant load of humans in urban areas using a metaheuristic hill-climbing algorithm – introducing TreePlanter v1.0
Sensitivity of asymmetric oxygen minimum zones to mixing intensity and stoichiometry in the tropical Pacific using a basin-scale model (OGCM-DMEC V1.4)
The importance of turbulent ocean–sea ice nutrient exchanges for simulation of ice algal biomass and production with CICE6.1 and Icepack 1.2
Modeling symbiotic biological nitrogen fixation in grain legumes globally with LPJ-GUESS (v4.0, r10285)
Afforestation impact on soil temperature in regional climate model simulations over Europe
BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale
Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model
Explicit silicate cycling in the Kiel Marine Biogeochemistry Model version 3 (KMBM3) embedded in the UVic ESCM version 2.9
Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations
OMEN-SED(-RCM) (v1.1): a pseudo-reactive continuum representation of organic matter degradation dynamics for OMEN-SED
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-177, https://doi.org/10.5194/gmd-2022-177, 2022
Revised manuscript accepted for GMD
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Planktic foraminifera are marine calcifying zooplankton and their shell are widely used as to measure past temperature and productivity. Here we developed ForamECOGENIE model to simulate the four subgroups of this organism. We found the relative abundance distribution agrees with core top data and carbon flux is comparable to sediment trap observation. This model provides opportunity to study foraminifera ecology in any geological time.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Suman Halder, Susanne K. M. Arens, Kai Jensen, Tais W. Dahl, and Philipp Porada
Geosci. Model Dev., 15, 2325–2343, https://doi.org/10.5194/gmd-15-2325-2022, https://doi.org/10.5194/gmd-15-2325-2022, 2022
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A dynamic vegetation model, designed to estimate potential impacts of early vascular vegetation, namely, lycopsids, on the biogeochemical cycle at a local scale. Lycopsid Model (LYCOm) estimates the productivity and physiological properties of lycopsids across a broad climatic range along with natural selection, which is then utilized to adjudge their weathering potential. It lays the foundation for estimation of their impacts during their long evolutionary history starting from the Ordovician.
Dóra Hidy, Zoltán Barcza, Roland Hollós, Laura Dobor, Tamás Ács, Dóra Zacháry, Tibor Filep, László Pásztor, Dóra Incze, Márton Dencső, Eszter Tóth, Katarína Merganičová, Peter Thornton, Steven Running, and Nándor Fodor
Geosci. Model Dev., 15, 2157–2181, https://doi.org/10.5194/gmd-15-2157-2022, https://doi.org/10.5194/gmd-15-2157-2022, 2022
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Biogeochemical models used by the scientific community can support society in the quantification of the expected environmental impacts caused by global climate change. The Biome-BGCMuSo v6.2 biogeochemical model has been created by implementing a lot of developments related to soil hydrology as well as the soil carbon and nitrogen cycle and by integrating crop model components. Detailed descriptions of developments with case studies are presented in this paper.
Lei Ma, George Hurtt, Lesley Ott, Ritvik Sahajpal, Justin Fisk, Rachel Lamb, Hao Tang, Steve Flanagan, Louise Chini, Abhishek Chatterjee, and Joseph Sullivan
Geosci. Model Dev., 15, 1971–1994, https://doi.org/10.5194/gmd-15-1971-2022, https://doi.org/10.5194/gmd-15-1971-2022, 2022
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We present a global version of the Ecosystem Demography (ED) model which can track vegetation 3-D structure and scale up ecological processes from individual vegetation to ecosystem scale. Model evaluation against multiple benchmarking datasets demonstrated the model’s capability to simulate global vegetation dynamics across a range of temporal and spatial scales. With this version, ED has the potential to be linked with remote sensing observations to address key scientific questions.
Ignacio Hermoso de Mendoza, Etienne Boucher, Fabio Gennaretti, Aliénor Lavergne, Robert Field, and Laia Andreu-Hayles
Geosci. Model Dev., 15, 1931–1952, https://doi.org/10.5194/gmd-15-1931-2022, https://doi.org/10.5194/gmd-15-1931-2022, 2022
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We modify the numerical model of forest growth MAIDENiso by explicitly simulating snow. This allows us to use the model in boreal environments, where snow is dominant. We tested the performance of the model before and after adding snow, using it at two Canadian sites to simulate tree-ring isotopes and comparing with local observations. We found that modelling snow improves significantly the simulation of the hydrological cycle, the plausibility of the model and the simulated isotopes.
Toni Viskari, Janne Pusa, Istem Fer, Anna Repo, Julius Vira, and Jari Liski
Geosci. Model Dev., 15, 1735–1752, https://doi.org/10.5194/gmd-15-1735-2022, https://doi.org/10.5194/gmd-15-1735-2022, 2022
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We wanted to examine how the chosen measurement data and calibration process affect soil organic carbon model calibration. In our results we found that there is a benefit in using data from multiple litter-bag decomposition experiments simultaneously, even with the required assumptions. Additionally, due to the amount of noise and uncertainties in the system, more advanced calibration methods should be used to parameterize the models.
Glenn E. Hammond
Geosci. Model Dev., 15, 1659–1676, https://doi.org/10.5194/gmd-15-1659-2022, https://doi.org/10.5194/gmd-15-1659-2022, 2022
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This paper describes a simplified interface for implementing and testing new chemical reactions within the reactive transport simulator PFLOTRAN. The paper describes the interface, providing example code for the interface. The paper includes several chemical reactions implemented through the interface.
Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, https://doi.org/10.5194/gmd-15-1633-2022, 2022
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We present a new method to include peatlands in an Earth system model (ESM). Peatlands store huge amounts of carbon that accumulates very slowly but that can be rapidly destabilised, emitting greenhouse gases. Our model captures the dynamic nature of peat by simulating the change in surface height and physical properties of the soil as carbon is added or decomposed. Thus, we model, for the first time in an ESM, peat dynamics and its threshold behaviours that can lead to destabilisation.
Philippe Ciais, Ana Bastos, Frédéric Chevallier, Ronny Lauerwald, Ben Poulter, Josep G. Canadell, Gustaf Hugelius, Robert B. Jackson, Atul Jain, Matthew Jones, Masayuki Kondo, Ingrid T. Luijkx, Prabir K. Patra, Wouter Peters, Julia Pongratz, Ana Maria Roxana Petrescu, Shilong Piao, Chunjing Qiu, Celso Von Randow, Pierre Regnier, Marielle Saunois, Robert Scholes, Anatoly Shvidenko, Hanqin Tian, Hui Yang, Xuhui Wang, and Bo Zheng
Geosci. Model Dev., 15, 1289–1316, https://doi.org/10.5194/gmd-15-1289-2022, https://doi.org/10.5194/gmd-15-1289-2022, 2022
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The second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP) will provide updated quantification and process understanding of CO2, CH4, and N2O emissions and sinks for ten regions of the globe. In this paper, we give definitions, review different methods, and make recommendations for estimating different components of the total land–atmosphere carbon exchange for each region in a consistent and complete approach.
Nils Wallenberg, Fredrik Lindberg, and David Rayner
Geosci. Model Dev., 15, 1107–1128, https://doi.org/10.5194/gmd-15-1107-2022, https://doi.org/10.5194/gmd-15-1107-2022, 2022
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Exposure to solar radiation on clear and warm days can lead to heat stress and thermal discomfort. This can be alleviated by planting trees providing shade in particularly warm areas. Here, we use a model to locate trees and optimize their blocking of solar radiation. Our results show that locations can differ depending, e.g., tree size (juvenile or mature) and number of trees that are positioned simultaneously. The model is available as a tool for accessibility by researchers and others.
Kai Wang, Xiujun Wang, Raghu Murtugudde, Dongxiao Zhang, and Rong-Hua Zhang
Geosci. Model Dev., 15, 1017–1035, https://doi.org/10.5194/gmd-15-1017-2022, https://doi.org/10.5194/gmd-15-1017-2022, 2022
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We use observational data of dissolved oxygen (DO) and organic nitrogen to calibrate a basin-scale model (OGCM-DEMC V1.4) and then evaluate model capacity for simulating mid-depth DO in the tropical Pacific. Sensitivity studies show that enhanced vertical mixing combined with reduced biological consumption performs well in reproducing asymmetric oxygen minimum zones (OMZs). We find that DO is more sensitive to biological processes in the upper OMZs but to physical processes in the lower OMZs.
Pedro Duarte, Philipp Assmy, Karley Campbell, and Arild Sundfjord
Geosci. Model Dev., 15, 841–857, https://doi.org/10.5194/gmd-15-841-2022, https://doi.org/10.5194/gmd-15-841-2022, 2022
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Sea ice modeling is an important part of Earth system models (ESMs). The results of ESMs are used by the Intergovernmental Panel on Climate Change in their reports. In this study we present an improvement to calculate the exchange of nutrients between the ocean and the sea ice. This nutrient exchange is an essential process to keep the ice-associated ecosystem functioning. We found out that previous calculation methods may underestimate the primary production of the ice-associated ecosystem.
Jianyong Ma, Stefan Olin, Peter Anthoni, Sam S. Rabin, Anita D. Bayer, Sylvia S. Nyawira, and Almut Arneth
Geosci. Model Dev., 15, 815–839, https://doi.org/10.5194/gmd-15-815-2022, https://doi.org/10.5194/gmd-15-815-2022, 2022
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The implementation of the biological N fixation process in LPJ-GUESS in this study provides an opportunity to quantify N fixation rates between legumes and to better estimate grain legume production on a global scale. It also helps to predict and detect the potential contribution of N-fixing plants as
green manureto reducing or removing the use of N fertilizer in global agricultural systems, considering different climate conditions, management practices, and land-use change scenarios.
Giannis Sofiadis, Eleni Katragkou, Edouard L. Davin, Diana Rechid, Nathalie de Noblet-Ducoudre, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Lisa Jach, Ronny Meier, Priscilla A. Mooney, Pedro M. M. Soares, Susanna Strada, Merja H. Tölle, and Kirsten Warrach Sagi
Geosci. Model Dev., 15, 595–616, https://doi.org/10.5194/gmd-15-595-2022, https://doi.org/10.5194/gmd-15-595-2022, 2022
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Afforestation is currently promoted as a greenhouse gas mitigation strategy. In our study, we examine the differences in soil temperature and moisture between grounds covered either by forests or grass. The main conclusion emerged is that forest-covered grounds are cooler but drier than open lands in summer. Therefore, afforestation disrupts the seasonal cycle of soil temperature, which in turn could trigger changes in crucial chemical processes such as soil carbon sequestration.
Wei Zhi, Yuning Shi, Hang Wen, Leila Saberi, Gene-Hua Crystal Ng, Kayalvizhi Sadayappan, Devon Kerins, Bryn Stewart, and Li Li
Geosci. Model Dev., 15, 315–333, https://doi.org/10.5194/gmd-15-315-2022, https://doi.org/10.5194/gmd-15-315-2022, 2022
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Watersheds are the fundamental Earth surface functioning unit that connects the land to aquatic systems. Here we present the recently developed BioRT-Flux-PIHM v1.0, a watershed-scale biogeochemical reactive transport model, to improve our ability to understand and predict solute export and water quality. The model has been verified against the benchmark code CrunchTope and has recently been applied to understand reactive transport processes in multiple watersheds of different conditions.
Huilin Huang, Yongkang Xue, Ye Liu, Fang Li, and Gregory S. Okin
Geosci. Model Dev., 14, 7639–7657, https://doi.org/10.5194/gmd-14-7639-2021, https://doi.org/10.5194/gmd-14-7639-2021, 2021
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This study applies a fire-coupled dynamic vegetation model to quantify fire impact at monthly to annual scales. We find fire reduces grass cover by 4–8 % annually for widespread areas in south African savanna and reduces tree cover by 1 % at the periphery of tropical Congolese rainforest. The grass cover reduction peaks at the beginning of the rainy season, which quickly diminishes before the next fire season. In contrast, the reduction of tree cover is irreversible within one growing season.
Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Christopher J. Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev., 14, 7255–7285, https://doi.org/10.5194/gmd-14-7255-2021, https://doi.org/10.5194/gmd-14-7255-2021, 2021
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We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
Shannon de Roos, Gabriëlle J. M. De Lannoy, and Dirk Raes
Geosci. Model Dev., 14, 7309–7328, https://doi.org/10.5194/gmd-14-7309-2021, https://doi.org/10.5194/gmd-14-7309-2021, 2021
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A spatially distributed version of the field-scale crop model AquaCrop v6.1 was developed for applications at various spatial scales. Multi-year 1 km simulations over central Europe were evaluated against biomass and surface soil moisture products derived from optical and microwave satellite missions, as well as in situ observations of soil moisture. The regional version of the AquaCrop model provides a suitable setup for subsequent satellite-based data assimilation.
Philip Pika, Dominik Hülse, and Sandra Arndt
Geosci. Model Dev., 14, 7155–7174, https://doi.org/10.5194/gmd-14-7155-2021, https://doi.org/10.5194/gmd-14-7155-2021, 2021
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OMEN-SED is a model for early diagenesis in marine sediments simulating organic matter (OM) degradation and nutrient dynamics. We replaced the original description with a more realistic one accounting for the widely observed decrease in OM reactivity. The new model reproduces pore water profiles and sediment–water interface fluxes across different environments. This functionality extends the model’s applicability to a broad range of environments and timescales while requiring fewer parameters.
Cited articles
Anders, K. and Möller, H.: Seasonal fluctuations in macrobenthic fauna of
the Fucus belt in Kiel Fjord (western Baltic Sea), Helgoländer Meeresun.,
36, 277–283, 1983.
Andersson, A., Hajdu, S., Haecky, P., Kuparinen, J., and Wikner, J.:
Succession and growth limitation of phytoplankton in the Gulf of Bothnia
(Baltic Sea), Mar. Biol., 126, 791–801, https://doi.org/10.1007/BF00351346, 1996.
Bagge, O., Thurow, F., Steffensen, E., and Bay, J.: The Baltic cod, Dana, 10,
1–28, 1994.
Barthel, K., Daewel, U., Pushpadas, D., Schrum, C., Årthun, M., and
Wehde, H.: Resolving frontal structures: On the computational costs and
pay-off using a less diffusive but computational more expensive advection
scheme, Ocean Dynam., 62, 1457–1470, https://doi.org/10.1007/s10236-012-0578-9, 2012.
Blackford, J. C., Allen, J. I., and Gilbert, F. J.: Ecosystem dynamics at six
contrasting sites?: a generic modelling study, J. Mar. Syst., 52, 191–215,
https://doi.org/10.1016/j.jmarsys.2004.02.004, 2004.
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y.,
Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin,
G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley,
S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine
biogeochemistry and the ecosystem dynamics of the lower trophic levels,
Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016,
2016.
Callaway, R., Alsvag, J., de Boois, I., Cotter, J., Ford, A., Hinz, H.,
Jennings, S., Kröncke, I., Lancaster, J., Piet, G., Prince, P., and
Ehrich, S.: Diversity and community structure of epibenthic invertebrates and
fish in the North Sea, ICES J. Mar. Sci., 59, 1199–1214,
https://doi.org/10.1006/jmsc.2002.1288, 2002.
Casini, M., Hjelm, J., Molinero, J.-M., Lövgren, J., Cardinale, M.,
Bartolino, V., Belgrano, A., and Kornilovs, G.: Trophic cascades promote
threshold-like shifts, P. Natl. Acad. Sci. USA, 106, 197–202, 2009.
Charles, A. T.: Bio-Socio-Economic Fishery Models: Labour Dyanmics and
Multi-Objective Management, Can. J. Fish. Aquat. Sci., 46, 1313–1322, 1989.
Christensen, V. and Walters, C. J.: Ecopath with Ecosim: methods,
capabilities and limitations, Ecol. Modell., 172, 109–139,
https://doi.org/10.1016/j.ecolmodel.2003.09.003, 2004.
Clarke, A. and Johnston, N. M.: Scaling of metabolic rate with body mass and
temperature in teleost fish, J. Anim. Ecol., 68, 893–905,
https://doi.org/10.1046/j.1365-2656.1999.00337.x, 1999.
Colebrook, J. M., Environment, N., Place, P., and Hoe, T.: Continuous
plankton records: relationships between species of phytoplankton and
zooplankton in the seasonal cycle, Mar. Biol., 323, 313–323, 1984.
Coull, K., Jermyn, A., Newton, A., Henderson, G., and Hall, W.: Length/weight
Relationships for 88 Species of Fish Encountered in the North East Atlantic,
Scottish Fish. Res. Reports, 43, 82 pp., 1989.
Cury, P. and Shannon, L.: Regime shifts in upwelling ecosystems: observed
changes and possible mechanisms in the northern and southern Benguela, Prog.
Oceanogr., 60, 223–243, https://doi.org/10.1016/j.pocean.2004.02.007, 2004.
Cury, P., Shannon, L., and Shin, Y.-J.: The functioning of marine ecosystems,
in Responsible Fisheries in the Marine Ecosystem, edited by: Sinclair, M. and
Valdimarsson, G., FAO, Rome and CABI Publishing, Wallingford, 103–123, 2003.
Daan, N., Bromley, P. J., Hislop, J. R. G., and Nielson, N. A.: Ecology of
North Sea Fish, Neth. J. Sea Res., 26, 343–386, 1990.
Daewel, U. and Schrum, C.: Simulating long-term dynamics of the coupled North
Sea and Baltic Sea ecosystem with ECOSMO II: Model description and
validation, J. Mar. Syst., 119–120, 30–49,
https://doi.org/10.1016/j.jmarsys.2013.03.008, 2013.
Daewel, U., Peck, M. A., Kühn, W., St. John, M. A., Alekseeva, I., and
Schrum, C.: Coupling ecosystem and individual-based models to simulate the
influence of environmental variability on potential growth and survival of
larval sprat (Sprattus sprattus L.) in the North Sea, Fish. Oceanogr., 17,
333–351, https://doi.org/10.1111/j.1365-2419.2008.00482.x, 2008.
Daewel, U., Hjøllo, S. S., Huret, M., Ji, R., Maar, M., Niiranen, S.,
Travers-trolet, M., Peck, M. A., Wolfshaar, K. E., and van de Wolfshaar, K.
E.: Predation control of zooplankton dynamics: a review of observations and
models, ICES J. Mar. Sci., 71, 254–271, https://doi.org/10.1093/icesjms/fst125, 2014.
Daewel, U., Schrum, C., and Gupta, A. K.: The predictive potential of early
life stage individual-based models (IBMs): an example for Atlantic cod Gadus
morhua in the North Sea, Mar. Ecol. Prog. Ser., 534, 199–219,
https://doi.org/10.3354/meps11367, 2015.
Ekeroth, N., Blomqvist, S., and Hall, P. O. J.: Nutrient fluxes from reduced
Baltic Sea sediment: effects of oxygenation and macrobenthos, Mar. Ecol.
Prog. Ser., 544, 77–92, https://doi.org/10.3354/meps11592, 2016.
Elliott, M. and Hemingway, K.: Fishes in Estuaries, Fishes in Estuaries,
i–xx, https://doi.org/10.2134/jeq2003.3750, 2002.
Fennel, W.: Towards bridging biogeochemical and fish-production models, J.
Mar. Syst., 71, 171–194, https://doi.org/10.1016/j.jmarsys.2007.06.008, 2008.
Fennel, W.: Parameterizations of truncated food web models from the
perspective of an end-to-end model approach, J. Mar. Syst., 76, 171–185,
https://doi.org/10.1016/j.jmarsys.2008.05.005, 2009.
Fennel, W.: A nutrient to fish model for the example of the Baltic Sea, J.
Mar. Syst., 81, 184–195, https://doi.org/10.1016/j.jmarsys.2009.12.007, 2010.
Froese, R. and Pauly, D.: FishBase 2000: concepts, design and data sources,
ICLARM, Los Baños, Laguna, Philippines, 2000.
Froese, R., Thorson, J. T., and Reyes Jr., R. B.: A Bayesian approach for
estimating length-weight relationships in fishes, J. Appl. Ichthyol., 30,
78–85, https://doi.org/10.1111/jai.12299, 2014.
Fulton, E., Smith, A., and Punt, A.: Which ecological indicators can robustly
detect effects of fishing?, ICES J. Mar. Sci., 62, 540–551,
https://doi.org/10.1016/j.icesjms.2004.12.012, 2005.
Fulton, E. A.: Approaches to end-to-end ecosystem models, J. Mar. Syst., 81,
171–183, https://doi.org/10.1016/j.jmarsys.2009.12.012, 2010.
Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M., and Charnov, E.
L.: Effects of size and temperature on metabolic rate., Science, 293,
2248–2251, https://doi.org/10.1126/science.1061967, 2001.
Gogina, M. and Zettler, M. L.: Diversity and distribution of benthic
macrofauna in the Baltic Sea, Data inventory and its use for species
distribution modelling and prediction, J. Sea Res., 64, 313–321,
https://doi.org/10.1016/j.seares.2010.04.005, 2010.
Gogina, M., Glockzin, M., and Zettler, M. L.: Distribution of benthic
macrofaunal communities in the western Baltic Sea with regard to near-bottom
environmental parameters. 1. Causal analysis, J. Mar. Syst., 80, 57–70,
https://doi.org/10.1016/j.jmarsys.2009.10.001, 2010.
Greenstreet, S.: Seasonal variation in the consumption of food by fish in the
North Sea and implications for food web dynamics, ICES J. Mar. Sci., 54,
243–266, https://doi.org/10.1006/jmsc.1996.0183, 1997.
Greenstreet, S. P. R., Bryant, A. D., Broekhuizen, N., Hall, S. J., and
Heath, M. R.: Seasonal variation in the consumption of food by fish in the
North Sea and implications for food web dynamics, ICES J. Mar. Sci., 54,
243–266, https://doi.org/10.1006/jmsc.1996.0183, 1997.
Guerra, A. and Rocha, F.: The life history of Loligo vulgaris and Loligo
forbesi (Cephalopoda: Loliginidae) in Galician waters (NW Spain), Fish. Res.,
21, 43–69, https://doi.org/10.1016/0165-7836(94)90095-7, 1994.
Heath, M. R.: Ecosystem limits to food web fluxes and fisheries yields in the
North Sea simulated with an end-to-end food web model, Prog. Oceanogr., 102,
42–66, 2012.
Heip, C., Basford, D., Craeymeersch, J. A., Dewarumez, J. M., Dorjes, J., de
Wilde, P., Duineveld, G., Eleftheriou, A., Herman, P. M. J., Niermann, U.,
Kingston, P., Kunitzer, A., Rachor, E., Rumohr, H., Soetaert, K., and
Soltwedel, T.: Trends in biomass, density and diversity of North Sea
macrofauna, ICES J. Mar. Sci., 49, 13–22, https://doi.org/10.1093/icesjms/49.1.13, 1992.
Hinrichsen, H.-H., Lehmann, A., Petereit, C., Nissling, A., Ustups, D.,
Bergström, U., and Hüssy, K.: Spawning areas of eastern Baltic cod
revisited: Using hydrodynamic modelling to reveal spawning habitat
suitability, egg survival probability, and connectivity patterns, Prog.
Oceanogr., 143, 13–25, https://doi.org/10.1016/j.pocean.2016.02.004, 2016.
Huang, L., Wu, Y., Wan, R., and Zhang, J.: Carbon, nitrogen and phosphorus
stoichiometry in Japanese anchovy (Engraulis japonicus) from the Huanghai
Sea, China, Acta Oceanol. Sin., 31, 154–161, https://doi.org/10.1007/s13131-012-0229-5,
2012.
Hunter, E., Metcalfe, J. D., and Reynolds, J. D.: Migration route and
spawning area fidelity by North Sea plaice, Proc. Biol. Sci., 270,
2097–2103, https://doi.org/10.1098/rspb.2003.2473, 2003.
ICES: Manual for the International Bottom Trawl Surveys, Series of ICES
Survey Protocols, SISP 1-IBTS VIII, 68 pp., 2012.
ICES: Baltic Sea Ecoregion – Fisheries overview – November, 1–23,
https://doi.org/10.17895/ices.pub.4648, 2018a.
ICES: Greater North Sea Ecoregion – Fisheries overview – November, 1–31,
https://doi.org/10.17895/ices.pub.4647, 2018b.
Jennings, S., Alvsvåg, J., Cotter, A. J. R., Ehrich, S., Greenstreet, S.
P. R., Jarre-Teichmann, A., Mergardt, N., Rijnsdorp, A. D., and Smedstad, O.:
Fishing effects in northeast Atlantic shelf seas: patterns in fishing effort,
diversity and community structure, III. International trawling effort in the
North Sea: An analysis of spatial and temporal trends, Fish. Res., 40,
125–134, https://doi.org/10.1016/S0165-7836(98)00208-2, 1999.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A.,
Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.
C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Klaoudatos, D. S., Conides, A. J., Anastasopoulou, A., and Dulčić,
J.: Age, growth, mortality and sex ratio of the inshore population of the
edible crab, Cancer pagurus (Linnaeus 1758) in South Wales (UK), J. Appl.
Ichthyol., 29, 579–586, https://doi.org/10.1111/jai.12122, 2013.
Kröncke, I. and Bergfeld, C.: North sea benthos: a review, Senck. Marit.,
33, 205–268, https://doi.org/10.1007/BF03043049, 2003.
Maar, M., Friis, E., Larsen, J., Skovgaard, K., Wan, Z., She, J., Jonasson,
L., and Neumann, T.: Ecosystem modelling across a salinity gradient from the
North Sea to the Baltic Sea, Ecol. Modell., 222, 1696–1711,
https://doi.org/10.1016/j.ecolmodel.2011.03.006, 2011.
Maar, M., Rindorf, A., Møller, E. F., Christensen, A., Madsen, K. S., and
van Deurs, M.: Zooplankton mortality in 3D ecosystem modelling considering
variable spatial–temporal fish consumptions in the North Sea, Prog.
Oceanogr., 124, 78–91, https://doi.org/10.1016/j.pocean.2014.03.002, 2014.
Mackinson, S. and Daskalov, G.: An ecosystem model of the North Sea to
support an ecosystem approach to fisheries management: description and
parameterisation, Sci. Ser. Tech. Rep., 142, 196 pp., 2007.
McCully, S., Scott, F., and Ellis, J.: Lengths at maturity and conversion
factors for skate (Rajidae) around the British Isles, with an analysis of
data in the literature, ICES J. Mar. Sci., 69, 1812–1822,
https://doi.org/10.1093/icesjms/fst048, 2012.
Megrey, B. A., Rose, K. A., Klumb, R. A., Hay, D. E., Werner, F. E.,
Eslinger, D. L., and Smith, S. L.: A bioenergetics-based population dynamics
model of Pacific herring (Clupea harengus pallasi) coupled to a lower trophic
level nutrient – phytoplankton – zooplankton model?: Description,
calibration, and sensitivity analysis, Ecol. Modell., 202, 144–164,
https://doi.org/10.1016/j.ecolmodel.2006.08.020, 2007.
Michaelis, L. and Menten, M. L.: Die Kinetik der Invertinwirkung, Biochem.
Zeitschrift Beiträge zur chem. Physiol. u. Pathol., 49, 333–369,
availalbe at:
http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/17273
(last access: 22 August 2012), 1913.
Möllmann, C., Kornilovs, G., and Sidrevics, L.: Long-term dynamics of
main mesozooplankton species in the central Baltic Sea, J. Plankton Res., 22,
2015–2038, 2000.
Monod, J.: Recherches sur la croissance des cultures bacteiriennes, Hermann
& cie, Paris, available at:
http://www.worldcat.org/title/recherches-sur-la-croissance-des-cultures-bacteriennes/oclc/6126763
(last access: 22 August 2012), 1942.
Müller-Navarra, S. H. and Lange, W.: Modelling tides in the Baltic Sea –
A short note on the harmonic analysis of a one-year water level time series,
in: Proceedings of the 6th HIROMB Scientific Workshop, St. Petersburg,
Russia, 8–10 September 2003, 16–20, 2004.
Neumann, T. and Schernewski, G.: Eutrophication in the Baltic Sea and shifts
in nitrogen fixation analyzed with a 3D ecosystem model, J. Mar. Syst., 74,
592–602, https://doi.org/10.1016/j.jmarsys.2008.05.003, 2008.
Nøttestad, L., Giske, J., Holst, J. C., and Huse, G.: A length-based
hypothesis for feeding migrations in pelagic fish, Can. J. Fish. Aquat. Sci.,
56, 26–34, https://doi.org/10.1139/f99-222, 2011.
Oguz, T., Salihoglu, B., and Fach, B.: A coupled plankton–anchovy population
dynamics model assessing nonlinear controls of anchovy and gelatinous biomass
in the Black Sea, Mar. Ecol. Prog. Ser., 369, 229–256, 2008.
Omstedt, A. and Hansson, D.: The Baltic Sea ocean climate system memory and
response to changes in the water and heat balance components, Cont. Shelf
Res., 26, 236–251, https://doi.org/10.1016/j.csr.2005.11.003, 2006.
Peck, M. A., Arvanitidis, C., Butenschön, M., Canu, D. M.,
Chatzinikolaou, E., Cucco, A., Domenici, P., Fernandes, J. A., Gasche, L.,
Huebert, K. B., Hufnagl, M., Jones, M. C., Kempf, A., Keyl, F., Maar, M.,
Mahévas, S., Marchal, P., Nicolas, D., Pinnegar, J. K., Rivot, E.,
Rochette, S., Sell, A. F., Sinerchia, M., Solidoro, C., Somerfield, P. J.,
Teal, L. R., Travers-Trolet, M., and van de Wolfshaar, K. E.: Projecting
changes in the distribution and productivity of living marine resources: A
critical review of the suite of modelling approaches used in the large
European project VECTORS, Estuar. Coast. Shelf Sci., 201, 40–55,
https://doi.org/10.1016/j.ecss.2016.05.019, 2015.
Persson, L.-E.: Temporal and spatial variation in coastal macrobenthic
community structure, Hanö bay (southern Baltic), J. Exp. Mar. Biol.
Ecol., 68, 277–293, 1983.
Pierce, G. J., Boyle, P. R., Hastie, L. C., and Key, L.: The life history of
Loligo forbesi (Cephalopoda: Loliginidae) in Scottish waters, Fish. Res., 21,
17–41, https://doi.org/10.1016/0165-7836(94)90094-9, 1994.
Pinto, C., Travers-Trolet, M., Macdonald, J., Rivot, E., and Vermard, Y.:
Combining multiple data sets to unravel the spatio-temporal dynamics of a
data-limited fish stock, Can. J. Fish. Aquat. Sci.,
https://doi.org/10.1139/cjfas-2018-0149, 2018.
Politikos, D. V., Curchitser, E. N., Rose, K. A., Checkley, D. M., and
Fiechter, J.: Climate variability and sardine recruitment in the California
Current: A mechanistic analysis of an ecosystem model, Fish. Oceanogr., 27,
602–622, https://doi.org/10.1111/fog.12381, 2018.
Radtke, H., Neumann, T., and Fennel, W.: A Eulerian nutrient to fish model of
the Baltic Sea – A feasibility-study, J. Mar. Syst., 125, 61–76,
https://doi.org/10.1016/j.jmarsys.2012.07.010, 2013.
Rees, H. L., Pendle, M. a, Waldock, R., Limpenny, D. S., and Boyd, S. E.: A
comparison of benthic biodiversity in the North Sea, English Channel, and
Celtic Seas, ICES J. Mar. Sci., 56, 228–246, https://doi.org/10.1006/jmsc.1998.0438,
1999.
Rees, H. L., Eggleton, J. D., Rachor, E. and Vanden Berghe, E. (Eds.):
Structure and dynamics of the North Sea benthos, ICES Cooperative Research
Report, ISBN: 87-7482-058-3, 258 pp., 2007.
Reiss, H. and Krönke, I.: Seasonal variability of epibenthic communities
in different areas of the southern North Sea, ICES J. Mar. Sci., 61,
882–905, https://doi.org/10.1016/j.icesjms.2004.06.020, 2004.
Reiss, H. and Krönke, I.: Seasonal variability of infaunal community
structures in three areas of the North Sea under different environmental
conditions, Estuar. Coast. Shelf Sci., 65, 253–274,
https://doi.org/10.1016/j.ecss.2005.06.008, 2005.
Rodhe, J., Tett, P., and Wulff, F.: The Baltic and North Seas: A Regional
Review of some important Physical-Chemical-Biological Interaction Processes,
in: The Sea, Vol. 14 B, edited by: Robinson, A. R. and Brink, K., Harvard
University Press, 1033–1075, 2006.
Rose, K. A., Fiechter, J., Curchitser, E. N., Hedstrom, K., Bernal, M.,
Creekmore, S., Haynie, A., Ito, S., Lluch-Cota, S., Megrey, B. A., Edwards,
C. A., Checkley, D., Koslow, T., McClatchie, S., Werner, F., MacCall, A., and
Agostini, V.: Demonstration of a Fully-Coupled End-to-End Model for Small
Pelagic Fish Using Sardine and Anchovy in the California Current, Prog.
Oceanogr., 138, 348–380, https://doi.org/10.1016/j.pocean.2015.01.012, 2015.
Schlüter, M., Hinkel, J., Bots, P. W. G., and Arlinghaus, R.: Application
of the SES framework for model-based analysis of the dynamics of
social-ecological systems, Ecol. Soc., 19, https://doi.org/10.5751/ES-05782-190136, 2014.
Schrum, C. and Backhaus, J. O.: Sensitivity of atmosphere-ocean heat exchange
and heat content in the North Sea and the Baltic Sea, Tellus A, 51, 526–549,
https://doi.org/10.1034/j.1600-0870.1992.00006.x, 1999.
Schrum, C., Alekseeva, I., and St. John, M.: Development of a coupled
physical–biological ecosystem model ECOSMO, J. Mar. Syst., 61, 79–99,
https://doi.org/10.1016/j.jmarsys.2006.01.005, 2006.
Seinä, A. and Palosuo, E.: The classification of the maximum annual
extent of ice cover in the Baltic Sea 1720–1995, Meri – Report Series of
the Finnish Institute of Marine Research, 20, 79–910, 1996.
Shin, Y.-J. and Cury, P.: Using an individual-based model of fish assemblages
to study the response of size spectra to changes in fishing, Can. J. Fish.
Aquat. Sci., 61, 414–431, https://doi.org/10.1139/f03-154, 2004.
Shin, Y.-J., Travers, M., and Maury, O.: Coupling low and high trophic levels
models: Towards a pathways-orientated approach for end-to-end models, Prog.
Oceanogr., 84, 105–112, 2010.
Shin, Y. and Cury, P.: Exploring fish community dynamics through
size-dependent trophic interactions using a spatialized individual-based
model, Aquat. Living Resour., 14, 65–80, https://doi.org/10.1016/S0990-7440(01)01106-8,
2001.
Skogen, M. D., Søiland, H., and Svendsen, E.: Effects of changing nutrient
loads to the North Sea, J. Mar. Syst., 46, 23–38,
https://doi.org/10.1016/j.jmarsys.2003.11.013, 2004.
Sparholt, H.: An estimate of the total biomass of fish in the North Sea, ICES
J. Mar. Sci., 46, 200–210, https://doi.org/10.1093/icesjms/46.2.200, 1990.
Sterner, R. W. and George, N. B.: Carbon , Nitrogen , and Phosphorus
Stoichiometry of Cyprinid Fishes, Ecology, 81, 127–140, 2000.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res., 106, 7183–7192, https://doi.org/10.1029/2000JD900719, 2001.
Templeman, W.: Length-weight Relationships & Morphometric Characteristics
and Thorniness of Thorny Skate (Raja radiata) from the Northwest Atlantic, J.
Northwest Atl. Fish. Sci., 7, 89–98, 1987.
Thurow, F.: Estimation of the total fish biomass in the Baltic Sea during the
20th century, ICES J. Mar. Sci., 54, 444–461, https://doi.org/10.1006/jmsc.1996.0195,
1997.
Timmermann, K., Norkko, J., Janas, U., Norkko, A., Gustafsson, B. G., and
Bonsdorff, E.: Modelling macrofaunal biomass in relation to hypoxia and
nutrient loading, J. Mar. Syst., 105–108, 60–69,
https://doi.org/10.1016/j.jmarsys.2012.06.001, 2012.
Tomczak, M. T., Niiranen, S., Hjerne, O., and Blenckner, T.: Ecosystem flow
dynamics in the Baltic Proper – Using a multi-trophic dataset as a basis for
food–web modelling, Ecol. Modell., 230, 123–147,
https://doi.org/10.1016/j.ecolmodel.2011.12.014, 2012.
Travers, M., Shin, Y.-J., Jennings, S., and Cury, P.: Towards end-to-end
models for investigating the effects of climate and fishing in marine
ecosystems, Prog. Oceanogr., 75, 751–770, https://doi.org/10.1016/j.pocean.2007.08.001,
2007.
Utne, K. R., Hjøllo, S. S., Huse, G., and Skogen, M.: Estimating the
consumption of Calanus finmarchicus by planktivorous fish in the Norwegian
Sea using a fully coupled 3D model system, Mar. Biol. Res., 8, 527–547,
https://doi.org/10.1080/17451000.2011.642804, 2012.
Vikebø, F., Jørgensen, C., Kristiansen, T., and Fiksen, Ø.: Drift,
growth, and survival of larval Northeast Arctic cod with simple rules of
behaviour, Mar. Ecol. Prog. Ser., 347, 207–219, https://doi.org/10.3354/meps06979, 2007.
Von Storch, H. and Zwiers, F. W.: Statistical Analysis in Climate Research,
Cambridge University Press, Cambridge, UK, 1999.
Watson, J. R., Stock, C. A., and Sarmiento, J. L.: Exploring the role of
movement in determining the global distribution of marine biomass using a
coupled hydrodynamic – Size-based ecosystem model, Prog. Oceanogr., 138,
521–532, https://doi.org/10.1016/j.pocean.2014.09.001, 2014.
Short summary
Here we propose a novel modelling approach that includes an extended food web in a functional-group-type marine ecosystem model (ECOSMO E2E) by formulating new groups for macrobenthos and fish. This enables the estimation of the dynamics of the higher-trophic-level production potential and constitutes a more consistent closure term for the lower-trophic-level ecosystem. Thus, the model allows for the study of the control mechanisms for marine ecosystems at a high spatial and temporal resolution.
Here we propose a novel modelling approach that includes an extended food web in a...
