Articles | Volume 15, issue 13
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0
Rafael L. Bras
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
Tamara Heartsill Scalley
USDA Forest Service, International Institute of Tropical Forestry, Río Piedras, PR, United States
No articles found.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040,Short summary
Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Elias C. Massoud, A. Anthony Bloom, Marcos Longo, John T. Reager, Paul A. Levine, and John R. Worden
Hydrol. Earth Syst. Sci., 26, 1407–1423,Short summary
The water balance on river basin scales depends on a number of soil physical processes. Gaining information on these quantities using observations is a key step toward improving the skill of land surface hydrology models. In this study, we use data from the Gravity Recovery and Climate Experiment (NASA-GRACE) to inform and constrain these hydrologic processes. We show that our model is able to simulate the land hydrologic cycle for a watershed in the Amazon from January 2003 to December 2012.
Maoyi Huang, Yi Xu, Marcos Longo, Michael Keller, Ryan G. Knox, Charles D. Koven, and Rosie A. Fisher
Biogeosciences, 17, 4999–5023,Short summary
The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is enhanced to mimic the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events; determine the survivorship of cohorts in the disturbed forest; and modifying the biomass, coarse woody debris, and litter pools. This study lays the foundation to simulate land use change and forest degradation in FATES as part of an Earth system model.
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346,Short summary
Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374,Short summary
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
Marcos A. S. Scaranello, Michael Keller, Marcos Longo, Maiza N. dos-Santos, Veronika Leitold, Douglas C. Morton, Ekena R. Pinagé, and Fernando Del Bon Espírito-Santo
Biogeosciences, 16, 3457–3474,Short summary
The coarse dead wood component of the tropical forest carbon pool is rarely measured. For the first time, we developed models for predicting coarse dead wood in Amazonian forests by using airborne laser scanning data. Our models produced site-based estimates similar to independent field estimates found in the literature. Our study provides an approach for estimating coarse dead wood pools from remotely sensed data and mapping those pools over large scales in intact and degraded forests.
Matthew N. Hayek, Marcos Longo, Jin Wu, Marielle N. Smith, Natalia Restrepo-Coupe, Raphael Tapajós, Rodrigo da Silva, David R. Fitzjarrald, Plinio B. Camargo, Lucy R. Hutyra, Luciana F. Alves, Bruce Daube, J. William Munger, Kenia T. Wiedemann, Scott R. Saleska, and Steven C. Wofsy
Biogeosciences, 15, 4833–4848,Short summary
We investigated the roles that weather and forest disturbances like drought play in shaping changes in ecosystem photosynthesis and carbon exchange in an Amazon forest. We discovered that weather largely influenced differences between years, but a prior drought, which occurred 3 years before measurements started, likely hampered photosynthesis in the first year. This is the first atmospheric evidence that drought can have legacy impacts on Amazon forest photosynthesis.
Saulo R. Freitas, Jairo Panetta, Karla M. Longo, Luiz F. Rodrigues, Demerval S. Moreira, Nilton E. Rosário, Pedro L. Silva Dias, Maria A. F. Silva Dias, Enio P. Souza, Edmilson D. Freitas, Marcos Longo, Ariane Frassoni, Alvaro L. Fazenda, Cláudio M. Santos e Silva, Cláudio A. B. Pavani, Denis Eiras, Daniela A. França, Daniel Massaru, Fernanda B. Silva, Fernando C. Santos, Gabriel Pereira, Gláuber Camponogara, Gonzalo A. Ferrada, Haroldo F. Campos Velho, Isilda Menezes, Julliana L. Freire, Marcelo F. Alonso, Madeleine S. Gácita, Maurício Zarzur, Rafael M. Fonseca, Rafael S. Lima, Ricardo A. Siqueira, Rodrigo Braz, Simone Tomita, Valter Oliveira, and Leila D. Martins
Geosci. Model Dev., 10, 189–222,Short summary
We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) where different previous versions for weather, chemistry, and the carbon cycle were unified in a single harmonized software system. This version also has a new set of state-of-the-art physical parametrizations and higher computational parallel and memory usage efficiency. BRAMS has been applied for research and operational weather and air quality forecasting, largely in South America.
Douglas C. Morton, Jérémy Rubio, Bruce D. Cook, Jean-Philippe Gastellu-Etchegorry, Marcos Longo, Hyeungu Choi, Maria Hunter, and Michael Keller
Biogeosciences, 13, 2195–2206,Short summary
Seasonal dynamics of tropical forest productivity remain an important source of uncertainty in assessments of the land carbon sink. This study confirms the potential for canopy structure and illumination geometry to alter the seasonal availability of light for canopy photosynthesis without changes in canopy composition. Our results point to the need for 3-D forest structure in ecosystem models to account the impact of changing illumination geometry on tropical forest productivity.
R. G. Knox, M. Longo, A. L. S. Swann, K. Zhang, N. M. Levine, P. R. Moorcroft, and R. L. Bras
Hydrol. Earth Syst. Sci., 19, 241–273,
R. G. Knox, M. Longo, A. L. S. Swann, K. Zhang, N. M. Levine, P. R. Moorcroft, and R. L. Bras
Hydrol. Earth Syst. Sci. Discuss.,
C. Lepore, E. Arnone, L. V. Noto, G. Sivandran, and R. L. Bras
Hydrol. Earth Syst. Sci., 17, 3371–3387,
Related subject area
BiogeosciencesMEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scalesModelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazingImplementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damageThe Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamicsValidation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North AmericaGlobal agricultural ammonia emissions simulated with the ORCHIDEE land surface modelForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal modelOcean biogeochemistry in the coupled ocean-sea ice-biogeochemistry model FESOM2.1-REcoM3Global Fire Emissions Database burned-area dataset into Community Land Model version 5.0 – Biogeochemistry: Impacts on carbon and water fluxes at high latitudesFABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cyclesEvaluating 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 estimatesImplementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1Simulating 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 experimentMatrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental levelCANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescalesLow sensitivity of three terrestrial biosphere models to soil texture over the South American tropicsModeling of non-structural carbohydrate dynamics by the spatially explicitly individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC ver1.0)FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modellingImpact of changes in climate and CO2 on the carbon storage potential of vegetation under limited water availability using SEIB-DGVM version 3.02FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamicsClimate 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 carbonSurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem levelImproved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimationRepresentation 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)A validation standard for area of habitat maps for terrestrial birds and mammalsSoil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases: SCEPTER v0.9Using 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 ArcticWater Ecosystems Tool (WET) 1.0 – a new generation of flexible aquatic ecosystem modelDevelopment of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNETPredicting global terrestrial biomes with the LeNet convolutional neural networkKGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N2O emission using data from mesocosm experimentsAssessing methane emissions for northern peatlands in ORCHIDEE-PEAT revision 7020A dynamic local-scale vegetation model for lycopsids (LYCOm v1.0)Soil-related developments of the Biome-BGCMuSo v6.2 terrestrial ecosystem modelGlobal evaluation of the Ecosystem Demography model (ED v3.0)A new snow module improves predictions of the isotope-enabled MAIDENiso forest growth modelCalibrating the soil organic carbon model Yasso20 with multiple datasetsThe PFLOTRAN Reaction SandboxA new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlandsDefinitions 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
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,Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475,Short summary
We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276,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,Short summary
Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696,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,Short summary
Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081,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,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.
Özgür Gürses, Laurent Oziel, Onur Karakus, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, and Judith Hauck
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
This paper is assessing the biogeochemical model REcoM3 coupled to the ocean-sea ice model FESOM2.1. The model can be used e.g. to simulate the carbon uptake or release of the ocean on time scales of several hundred years. A detailed analysis of nutrients, ocean productivity and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well in simulating the observed mean biogeochemical state and variability, and is comparable to other ocean-biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort 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 applied 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.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108,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,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,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,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,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,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,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,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,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,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.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Non-structural carbohydrates (NSCs) are important carbon storage in plants against the climate change. We added a new NSC module into an individual-based ecosystem model: SEIB-DGVM. The amounts of simulated NSCs and the general seasonality agree well with observed NSCs on a point scale and global scale. The model has a high potential to simulate the biotic effects resulting from insufficient NSC that are otherwise difficult to measure in terrestrial ecosystems globally.
Stanley I. Nmor, Eric Viollier, Lucie Pastor, Bruno Lansard, Christophe Rabouille, and Karline Soetaert
Geosci. Model Dev., 15, 7325–7351,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,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,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,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,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,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,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,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,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.
Prabhat Raj Dahal, Maria Lumbierres, Stuart H. M. Butchart, Paul F. Donald, and Carlo Rondinini
Geosci. Model Dev., 15, 5093–5105,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,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,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,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,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,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,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,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,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,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,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.
Suman Halder, Susanne K. M. Arens, Kai Jensen, Tais W. Dahl, and Philipp Porada
Geosci. Model Dev., 15, 2325–2343,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Albani, M, Medvigy, D., Hurtt, G. C., and Moorcroft, P. R.: The contributions of land-use change, CO2 fertilization, and climate variability to the Eastern US carbon sink, Global Change Biol., 12, 2370–2390, 2006.
Baraloto, C., Timothy Paine, C. E., Poorter, L., Beauchene, J., Bonal, D., Domenach, A. M., Hérault, B., Patiño, S., Roggy, J. C., and Chave, J.: Decoupled leaf and stem economics in rain forest trees, Ecol. Lett., 13, 1338–1347, 2010.
Beven, K. and Binley, A.: The future of distribution models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, 2001.
Binley, A. M. and Beven, K. J.: Physically-based modelling of catchment hydrology: a likelihood approach to reducing predictive uncertainty, in: Computer Modelling in the Environmental Sciences, edited by: Farmer, D. G. and Rycroft, M. J., Clarendon Press, Oxford, 75–88, 1991.
Boose, E. R., Foster, D. R., and Fluet, M.: Hurricane Impacts of tropical and temperate forest landscapes, Ecol. Monogr., 64, 369–400, 1994.
Boose, E. R., Serrano, M. I., and Foster, D. R.: Landscape and regional impacts of hurricanes in Puerto Rico, Ecol. Monogr., 74, 335–352, 2004.
Brokaw, N. V. L.: Cecropia schreberiana in the Luquillo Mountains of Puerto Rico, Bot. Rev., 64, 91–120, 1998.
Chambers, J. Q., Fisher, J. I., Zeng, H., Chapman, E. L., Baker, D. B., and Hurtt, G. C.: Hurricane Katrina's carbon footprint on U.S. Gulf Coast forests, Science, 318, 1107, https://doi.org/10.1126/science.1148913, 2007.
Chen, J. and Black, T.: Foliage area and architecture of plant canopies from sunfleck size distributions, Agric. For. Meteorol., 60, 249–266, 1992.
Cole, L. E. S., Bhagwat, S. A., and Willis, K. J.: Recovery and resilience of tropical forests after disturbance, Nat. Commun., 5, 3906, https://doi.org/10.1038/ncomms4906, 2014.
Computational and Information Systems Laboratory: Cheyenne: HPE/SGI ICE XA System (University Community Computing). Boulder, CO. National Center for Atmospheric Research. https://doi.org/10.5065/D6RX99HX, 2019.
Curran, T. J., Gersbach, L. N., Edwards, W., and Krockenberger, A. K.: Wood density predicts plant damage and vegetative recovery rates caused by cyclone disturbance in tropical rainforest tree species of North Queensland, Australia, Austral Ecol., 33, 442–450, 2008.
di Porcia e Brugnera, M., Meunier, F., Longo, M., Krishna Moorthy, S. M., De Deurwaerder, H., Schnitzer, S. A., Bonal, D., Faybishenko, B., and Verbeeck, H.: Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests, Global Change Biol., 25, 3767–3780, 2019.
Everham III, M. E. and Brokaw, N. V. L.: Forest damage and recovery from catastrophic wind, Bot. Rev., 62, 113–185, 1996.
Feng, X., Uriarte, M., González, G., Reed, S., Thompson, J., Zimmerman, J. K., and Murphy, L.: Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling, Global Change Biol., 24, e213–e232, 2018.
Fisher, R. A. and Koven, C. D.: Perspectives on the future of land surface models and the challenges of representing complex terrestrial systems, J. Adv. Model. Earth Sy., 12, e2018MS001453, https://doi.org/10.1029/2018MS001453, 2020.
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C. E., Holm, J. A., Hurtt, G. C., Knox, R. G., Lawrence, P. J., Lichstein, J. W., Longo, M., Matheny, A. M., Medvigy, D., Muller-Landau, H. C., Powell, T. L., Serbin, S. P., Sato, H., Shuman, J. K., Smith, B., Trugman, A. T., Viskari, T., Verbeeck, H., Weng, E., Xu, C., Xu, X., Zhang, T., and Moorcroft, P. R.: Vegetation demographics in Earth System Models: A review of progress and priorities, Global Change Biol., 24, 35–54, 2018.
Francis, J. K. and Gillespie, A. J. R.: Relating gust speed to tree damage in hurricane Hugo, 1989, J. Arboriculture, 19, 368–373, 1993.
Freer, J., Beven, K., and Ambriose, B.: Bayesian estimation of uncertainty in runoff prediction and the value of data: An application of the GLUE approach, Water Resour. Res., 32, 2161–2173, 1996.
Gill, R. A. and Jackson, R. B.: Global patterns of root turnover for terrestrial ecosystems, New Phytologist, 147, 13–31, 2000.
González, G.: Luquillo Mountains meteorological and ceilometer data, Fort Collins, CO, Forest Service Research Data Archive [data set], https://doi.org/10.2737/RDS-2017-0023, 2017.
Gregory, A. A. and Sabat, A. M.: The effect of hurricane disturbance on the fecundity of Sierra palms (Prestoea montana), Bios, 67, 135–139, 1996.
Hall, J., Muscarella, R., Quebbeman, A., Arellano, G., Thompson, J., Zimmerman, J. K., and Uriarte, M.: Hurricane-induced rainfall is a stronger predictor of tropical forest damage in Puerto Rico than maximum wind speeds, Sci. Rep.-UK, 10, 4318, https://doi.org/10.1038/s41598-020-61164-2, 2020.
He, L., Chen, J. M., Pisek, J., Schaaf, C. B., and Strahler, A. H.: Global clumping index map derived from the MODIS BRDF product, Remote Sens. Environ., 119, 118–130, 2012.
Heartsill Scalley, T.: Insights on forest structure and composition from long-term research in the Luquillo mountains, Forests, 8, 204, https://doi.org/10.3390/f8060204, 2017.
Heartsill Scalley, T., Scatena, F. N., Lugo, A. E., Moya, S., and Estrada, C. R.: Changes in structure, composition, and nutrients during 15 years of hurricane-induced succession in a subtropical wet forest in Puerto Rico, Biotropica, 42, 455–463, 2010.
IPCC: Climate Change 2021: The physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi,O., Yu, R., and Zhou, B. , Cambridge University Press, in press, https://doi.org/10.1017/9781009157896, 2021.
Jorgensen, S. E.: Overview of the model types available for development of ecological models, Ecol. Model., 215, 3–9, 2008.
Kammesheidt, L.: Some autecological characteristics of early to late successional tree species in Venezuela, Acta Oecol., 21, 37–48, https://doi.org/10.1016/S1146-609X(00)00108-9, 2000.
Keenan, T. F. and Niinemets, U.: Global leaf trait estimates biased due to plasticity in the shade, Nature Plants, 3, 16201, https://doi.org/10.1038/nplants.2016.201, 2017.
King, D. A., Davies, S. J., Tan, S., and Noor, N. S. M.: The role of wood density and stem support costs in the growth and mortality of tropical trees, Journal of Ecology, 94, 670–680, 2006.
LeBauer, D. S., Wang, D., Richter, K. T., Davidson, C. C., and Dietze, M. C.: Facilitating feedbacks between field measurements and ecosystem models, Ecol. Monogr., 83, 133–154, 2013.
Leitold, V., Morton, D. C., Martinuzzi, S., Paynter, I., Uriarte, M., Keller, M., Ferraz, A., Cook, B. D., Corp, L. A., and González, G.: Tracking the rates and mechanisms of canopy damage and recovery following hurricane Maria using multitemporal Lidar data, Ecosystems, https://doi.org/10.1007/s10021-021-00688-8, 2021.
Lewis, R. J. and Bannar-Martin, K. H.: The impact of cyclone Fanele on a tropical dry forest in Madagascar, Biotropica, 44, 135–140, 2011.
Lloyd, J., Patiño, S., Paiva, R. Q., Nardoto, G. B., Quesada, C. A., Santos, A. J. B., Baker, T. R., Brand, W. A., Hilke, I., Gielmann, H., Raessler, M., Luizão, F. J., Martinelli, L. A., and Mercado, L. M.: Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees, Biogeosciences, 7, 1833–1859, https://doi.org/10.5194/bg-7-1833-2010, 2010.
Longo, M., Knox, R. G., Levine, N. M., Swann, A. L. S., Medvigy, D. M., Dietze, M. C., Kim, Y., Zhang, K., Bonal, D., Burban, B., Camargo, P. B., Hayek, M. N., Saleska, S. R., da Silva, R., Bras, R. L., Wofsy, S. C., and Moorcroft, P. R.: The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America, Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, 2019a.
Longo, M., Knox, R. G., Medvigy, D. M., Levine, N. M., Dietze, M. C., Kim, Y., Swann, A. L. S., Zhang, K., Rollinson, C. R., Bras, R. L., Wofsy, S. C., and Moorcroft, P. R.: The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description, Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, 2019b.
Lugo, A. E. and Rivera Batlle, C. T.: Leaf production, growth rate, and age of the palm Prestoea montana in the Luquillo Experimental Forest, Puerto Rico, J. Trop. Ecol., 3, 151–161, 1987.
Lugo, A. E., Francis, J. K., and Frangi, J. L.: Prestoea montana (R. Graham) Nichols. Sierra palm. Palmaceae. Palm family, Tech. Rep. SO-ITF-SM-82, US Department of Agriculture, Forest Service, International Institute of Tropical Forestry, Rio Piedras, Puerto Rico, https://www.fs.usda.gov/treesearch/pubs/30213 (last access: 27 June 2022), 1998.
Ma, R.-Y., Zhang, J.-L., Cavaleri, M. A., Sterck, F., Strijk, J. S., and Cao, K.-F.: Convergent evolution towards high net carbon gain efficiency contributes to the shade tolerance of palms (Arecaceae), PLoS ONE, 10, e0140384, https://doi.org/10.1371/journal.pone.0140384, 2015.
Massoud, E. C., Xu, C., Fisher, R. A., Knox, R. G., Walker, A. P., Serbin, S. P., Christoffersen, B. O., Holm, J. A., Kueppers, L. M., Ricciuto, D. M., Wei, L., Johnson, D. J., Chambers, J. Q., Koven, C. D., McDowell, N. G., and Vrugt, J. A.: Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES), Geosci. Model Dev., 12, 4133–4164, https://doi.org/10.5194/gmd-12-4133-2019, 2019.
Medlyn, B. E., Robinson, A. P., Clement, R., and McMurtrie, R. E.: On the validation of models of forest CO2 exchange using eddy covariance data: some perils and pitfalls, Tree Physiol., 25, 839–857, 2005.
Medvigy, D., Wofsy, S. C., Munger, J. W., Hollinger, D. Y., and Moorcroft, P. R.: Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2, J. Geophys. Res., 114, G01002, https://doi.org/10.1029/2008JG000812, 2009.
Medvigy, D., Clark, K. L., Skowronski, N. S., and Schafer, K. V. R.: Simulated impacts of insect defoliation on forest carbon dynamics, Environ. Res. Lett., 7, 045703, https://doi.org/10.1088/1748-9326/7/4/045703, 2012.
Meunier, F., Verbeeck, H., Cowdery, B., Schnitzer, S. A., Smith-Martin, C. M., Powers, J. S., Xu, X., Slot, M., De Deurwaerder, H. P. T., Detto, M., Bonal, D., Longo, M., Santiago, L. S., and Dietze, M.: Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis, J. Ecol., 109, 519–540, 2021.
Meunier, F., Visser, M. D., Shiklomanov, A., Dietze, M. C., Guzmán Q., J. A., Sanchez-Azofeifa, G. A., De Deurwaerder, H. P. T., Krishna Moorthy, S. M., Schnitzer, S. A., Marvin, D. C., Longo, M., Liu, C., Broadbent, E. N., Almeyda Zambrano, A. M., Muller-Landau, H. C., Detto, M., and Verbeeck, H.: Liana optical traits increase tropical forest albedo and reduce ecosystem productivity, Global Change Biol., 28, 227–244, 2022.
Miller, A. D., Dietze, M. C., DeLucia, E. H., and Anderson-Teixeira, K. J.: Alteration of forest succession and carbon cycling under elevated CO2, Global Change Biol., 22, 351–363, 2016.
Mirzaei, M., Huang, Y. F., El-Shafie, A., and Shatirah, A.: Application of the generalized likelihood uncertainty estimation (GLUE) approach for assessing uncertainty in hydrological models: A review, Stoch. Env. Res. Risk A., 29, 1265–1273, 2015.
Moorcroft, P. R., Hurtt, G. C., and Pacala, S. W.: A method for scaling vegetation dynamics: The ecosystem demography model (ED), Ecol. Monogr., 71, 557–586, 2001.
Muscarella, R., Uriarte, M., Forero-Montaña, J., Comita, L. S., Swenson, N. G., Thompson, J., Nytch, C. J., Jonckheere, I., and Zimmerman, J. K.: Life-history trade-offs during the seed-to-seedling transition in a subtropical wet forest community, J. Ecol., 101, 171–182, 2013.
Muscarella, R., Emilio, T., Phillips, O. L., et al.: The global abundance of tree palms, Global Ecol. Biogeogr., 29, 1495–1514, 2020.
Parker, G., Martínez-Yrízar, A., Álvarez-Yépiz, J. C., Maass, M., and Araiza, S.: Effects of hurricane disturbance on a tropical dry forest canopy in western Mexico, Forest Ecol. Manag., 426, 39–52, 2018.
Paz, H., Vega-Ramos, F., and Arreola-Villa, F.: Understanding hurricane resistance and resilience in tropical dry forest trees: A functional traits approach, Forest Ecol. Manag., 426, 115–122, 2018.
Royo, A. A., Heartsill Scalley T., Moya, S., and Scatena, F. N.: Non-arborescent vegetation trajectories following repeated hurricane disturbance: ephemeral versus enduring responses, Ecosphere, 27, 77, https://doi.org/10.1890/ES11-00118.1, 2011.
Rutledge, B. T., Cannon, J. B., McIntyre, R. K., Holland, A. M., and Jack, S. B.: Tree, stand, and landscape factors contributing to hurricane damage in a coastal plain forest: post-hurricane assessment in a longleaf pine landscape, Forest Ecol. Manag., 481, 118724, https://doi.org/10.1016/j.foreco.2020.118724, 2021.
Sakschewski, B., von Bloh, W., Boit, A., Poorter, L., Peña-Claros, M., Heinke, J., Joshi, J., and Thonicke, K.: Resilience of Amazon forests emerges from plant trait diversity, Nat. Clim. Change, 6, 1032–1036, 2016.
Scatena, F. N., Silver, W., Siccama, T., Johnson, A., and Sanchez, M. J.: Biomass and nutrient content of the Bisley Experimental Watersheds, Luquillo Experimental Forest, Puerto Rico, before and after hurricane Hugo, 1989, Biotropica, 25, 15–27, 1993.
Schowalter, T. D. and Ganio, L. M.: Invertebrate communities in a tropical rain forest canopy in Puerto Rico after hurricane Hugo, Ecol. Entomol., 24, 191–201, 1999.
Shiklomanov, A. N., Dietze, M. C., Fer, I., Viskari, T., and Serbin, S. P.: Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance, Geosci. Model Dev., 14, 2603–2633, https://doi.org/10.5194/gmd-14-2603-2021, 2021.
Stein, M.: Large sample properties of simulations using Latin Hypercube sampling, Technometrics, 29, 143–151, 1987.
Swenson, N. G. and Umana, M. N.: Data from: Interspecific functional convergence and divergence and intraspecific negative density dependence underlie the seed-to-seedling transition in tropical trees, Dryad [data set], https://doi.org/10.5061/dryad.j2r53. 2015.
Trugman, A. T., Fenton, N. J., Bergeron, Y., Xu, X., Welp, L. R., and Medvigy, D.: Climate, soil organic layer, and nitrogen jointly drive forest development after fire in the North American boreal zone, J. Adv. Model. Earth Sy., 8, 1180–1209, 2016.
Uriarte, M., Canham, C. D., Thompson, J., Zimmerman, J. K., and Brokaw, N. Seedling recruitment in a hurricane-driven tropical forest: light limitation, density-dependence and the spatial distribution of parent trees, J. Ecol., 93, 291–304, 2005.
Uriarte, M., Canham, C. D., Thompson, J., Zimmerman, J. K., Murphy, L., Sabat, A. M., Fetcher, N., and Haines, B. L.: Natural disturbance and human land use as determinants of tropical forest dynamics: Results from a forest simulator, Ecol. Monogr., 79, 423–443, 2009.
Uriarte, M., Clark, J. S., Zimmerman, J. K., Comita, L. S., Forero-Montana, J., and Thompson, J.: Multidimensional trade-offs in species responses to disturbance: implications for diversity in a subtropical forest, Ecology, 93, 191–205, 2012.
Uriarte, M., Thompson, J., and Zimmerman, J. K.: Hurricane Maria tripled stem breaks and doubled tree mortality relative to other major storms, Nat. Commun., 10, 1362, https://doi.org/10.1038/s41467-019-09319-2, 2019.
Walker, L. R.: Tree damage and recovery from hurricane Hugo in Luquillo Experimental Forest, Puerto Rico. Part A. special issue: ecosystem, plant, and animal responses to hurricanes in the Caribbean, Biotropica, 23, 379–385, 1991.
Walker, L. R., Voltzow, J., Ackerman, J. D., Fernandez, D. S., and Fetcher, N.: Immediate impact of hurricane Hugo on a Puerto Rico rain forest, Ecology, 73, 691–694, 1992.
Wang, D., LeBauer, D. and Dietze, M.: Predicting yields of short-rotation hybrid poplar (Populus spp.) for the United States through model-data synthesis, Ecol. Appl., 23, 944–958, 2013.
Wang, G. and Eltahir, E. A. B.: Biosphere-atmosphere interactions over West Africa. II: Multiple climate equilibria, Q. J. Roy. Meteor. Soc., 126, 1261–1280, 2000.
Xiao, Z., Liang, S., Wang, J., Xiang, Y., Zhao X., and Song, J.: Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance, IEEE T. Geosci. Remote, 54, 5301–5318, 2016.
Xiao, Z., Liang, S., and Jiang, B.: Evaluation of four long time-series global leaf area index products, Agric. For. Meteorol., 246, 218–230, 2017.
Xu, X. and Trugman, A. T.: trait-based modeling of terrestrial ecosystems: Advances and challenges under global change, Curr. Clim. Change Rep., 7, 1–13, 2021.
Xu, X., Medvigy, D., Powers, J. S., Becknell, J. M., and Guan, K.: Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests, New Phytologist, 212, 80–95, 2016.
Zhang, J., Bras, R. L., and Heartsill Scalley, T.: Tree census at Bisley Experimental Watersheds three months after hurricane Maria, Fort Collins, CO, Forest Service Research Data Archive [data set], https://doi.org/10.2737/RDS-2020-0012, 2020.
Zhang, J., Bras, R. L., Longo, M., and Heartsill Scalley, T.: ED2 model with hurricane disturbance and a new tropical palm PFT (ED2-HuDi v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.5565063, 2021.
Zhang, J., Bras, R. L., and Heartsill Scalley, T.: Tree census at Bisley Experimental Watersheds before and after Hurricane Hugo, Fort Collins, CO, Forest Service Research Data Archive [data set], https://doi.org/10.2737/RDS-2022-0025, 2022a.
Zhang, J., Heartsill Scalley, T., and Bras, R. L.: Forest structure and composition are critical to hurricane mortality, Forests, 13, 202, https://doi.org/10.3390/f13020202, 2022b.
Zhang, K., de Almeida Castanho, A. D., Galbraith, D. R., Moghim, S., Levine, N. M., Bras, R. L., Coe, M. T., Costa, M. H., Malhi, Y., Longo, M., Knox, R. G., McKnight, S., Wang, J., and Moorcroft, P. R.: The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2 and land-use, Global Change Biol., 21, 2569–2587, 2015.
Zimmerman, J, K., Everham, E. M., Waide, R. B., Lodge, D. J., Taylor, C. M., and Brokaw, N. V. L.: Responses of tree species to hurricane winds in subtropical wet forest in Puerto Rico: Implications for tropical tree life histories, J. Ecol., 82, 911–922, 1994.
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.
We implemented hurricane disturbance in a vegetation dynamics model and calibrated the model...