ORCID Profile
0000-0002-6257-0338
Current Organisation
Lunds Universitet Naturvetenskapliga fakulteten
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Ecological Impacts of Climate Change | Ecological Applications
Ecosystem Adaptation to Climate Change | Ecosystem Assessment and Management of Forest and Woodlands Environments |
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-20606
Abstract: & & A new generation of land surface models (LSMs) have been developed in the framework of the EU-funded CRESCENDO project aiming to improve understanding of the Earth system as part of the community CMIP6 effort.& & br& These new LSMs explicitly represent key processes in the carbon and nitrogen cycles, enabling more realistic vegetation-climate interactions to be simulated. For instance, vegetation phenology, the seasonality of vegetation, is explicitly represented in all these new LSMs. Intra- and inter-annual variations in vegetation phenology can substantially influence land-atmosphere exchanges of energy, moisture and carbon. Changes in phenological events also provide clear indicators of climate impacts on ecosystems.& & br& Results are presented on the evaluation of phenological variability from offline runs of this new generation of LSMs. In particular, the timing of growing season onset and offset at global scale, and the Leaf Area Index (LAI) peak timing are investigated using monthly mean outputs. Three satellite-derived LAI datasets are used as benchmark observations for this evaluation.& br& In general, LSMs exhibit high skill in reproducing the observed phenology cycle in the North hemisphere mid- and high-latitudes, while lower skill is obtained in the South hemisphere. All LSMs simulate an offset in the timing of the active vegetative season characterized by later onset and LAI peak. Offset timings are slightly better captured by the LSMs. For these reasons, further development of the representation of phenology is required in LSMs, especially in the South hemisphere, where more complex vegetation and reduced in-situ observations are available.& &
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-3712
Abstract: The importance of phosphorus (P) in plant function and ecosystem biogeochemistry has led to the addition of a P cycle to a range of vegetation models, but the predictions of these P-enabled models have rarely been evaluated with ecosystem-scale data. Here, we confronted eight state-of-the-art, P-enabled models with data from EucFACE, a P-limited& Eucalyptus& forest subject to long-term Free-Air CO2& Enrichment. We evaluated the capability of the models to capture the observed elevated CO2& responses in this ecosystem. We show that the inclusion of phosphorus-cycle is necessary to more realistically simulate ecosystem function and biogeochemistry, but this enhanced capacity did not directly translate into improved prediction accuracy. Specifically, models erged in capturing the observed CO2& responses, with simulation accuracy depending upon model assumptions about plant physiology, allocation, plant-soil interactions and soil nutrient processes. Confronting models with experimental responses observed at EucFACE represents a valuable opportunity to improve our understanding of the carbon-phosphorus interaction under rising CO2, and is an important step towards more accurate predictions of the future land carbon sink under climate change.
Publisher: American Geophysical Union (AGU)
Date: 28-08-2018
DOI: 10.1029/2018GL079195
Publisher: American Geophysical Union (AGU)
Date: 05-2014
DOI: 10.1002/2013JG002553
Publisher: Copernicus GmbH
Date: 11-02-2021
DOI: 10.5194/GMD-2020-446
Abstract: Abstract. The Earth System Model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different HPC systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behaviour and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Publisher: Copernicus GmbH
Date: 07-05-2021
Publisher: Copernicus GmbH
Date: 10-01-2020
Publisher: Copernicus GmbH
Date: 05-01-2014
Abstract: Abstract. Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown erging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100 one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C–N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.
Publisher: Copernicus GmbH
Date: 28-11-2013
DOI: 10.5194/BGD-10-18613-2013
Abstract: Abstract. The LPJ-GUESS dynamic vegetation model uniquely combines an in idual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well-reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness-of-fit for broadleaved forests. N limitation associated with low N mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N-limitation associated with low N mineralisation rates of colder soils reduces CO2-enhancement of NPP for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by c. 10% additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions not only in studies of global terrestrial C cycling, but to understand underlying mechanisms on local scales and in different regional contexts.
Publisher: Copernicus GmbH
Date: 15-06-2015
Abstract: Abstract. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C–N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.
Publisher: Copernicus GmbH
Date: 27-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-2843
Abstract: & & Future projections suggest that the Arctic will undergo extreme changes in the near future, with the largest changes occurring during the wintertime. Still, cold season processes and their impact on the annual carbon and water budgets are often understudied.& & & & We aim to assess and quantify the impact of winter warming on the arctic carbon cycle by improving the representation of cold-season processes in the LPJ-GUESS DGVM. Firstly, we developed and implemented a new, dynamic snow scheme into the model to enhance the simulation of snow-soil-vegetation interaction. These updates improved the simulation of modelled soil temperature and permafrost extent compared to observations. In our latest study, we are assessing the physical controls on non-growing season methane emissions in the model, focusing on potential burst-like methane emissions during the zero curtain period. We set out to evaluate whether enabling non-growing season methane emissions may influence the annual methane budget.& & & & So far, we found that changes in the cold season significantly affect arctic biogeochemistry. We also observed that wintertime changes affect vegetation dynamics and composition over the Arctic. Improving the model representation of wintertime processes enables to further investigate the future snow-soil-vegetation interaction. These simulations can be used to assess the impact of warming on the arctic carbon cycle and its global consequences.& &
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-7379
Abstract: Within the framework of the project IMPOSE (Emit now, mitigate later? IMPlications of temperature OverShoots for the Earth system) six idealized emission-overshoot simulations have been performed with the Earth System Model NorESM2-LM2 and used as forcing for the 2nd& generation dynamic global vegetation model LPJ-GUESS with its fire-model SIMFIRE-BLAZE to investigate the impact of different CO2& overshoots on global wildfire regimes.The simulations describe a set of scenarios with high, medium, and low accumulative CO2& emissions and each of which has a short (immediate) and a long (100 years) peak of accumulative CO2& emissions before declining towards a baseline simulation of 1500 PgC accumulatively emitted within the first 100 years.The results show that the height of the overshoot has an impact on global fire regimes while its duration does not seem to play a significant role 200 years after peak CO2. Overall, we can see that changes in vegetation composition following the temperature anomaly are the main driver for changes in global wildfire frequency. While in the low overshoot scenarios burnt area has almost converged towards the baseline simulation, the extremest scenarios show the lowest burnt area at the end of the simulation period, indicating that vegetation changes, especially in low latitudes, have been most significant and/or are still ongoing.
Publisher: Copernicus GmbH
Date: 13-11-2014
Abstract: Abstract. Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown erging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed in idual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100 one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C–N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.
Publisher: Copernicus GmbH
Date: 07-05-2021
DOI: 10.5194/BG-2021-121
Abstract: Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon-climate feedbacks under continued winter warming. The Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product. Besides soil thermodynamics, the new snow scheme resulted in increased winter respiration and an overall lower soil carbon content due to warmer soil conditions. The Dynamic scheme also influenced vegetation dynamics, resulting in an improved vegetation distribution and tundra-taiga boundary simulation. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a better understanding of the Arctic's role in the global climate system.
Publisher: Copernicus GmbH
Date: 18-06-2020
Publisher: Wiley
Date: 28-01-2014
DOI: 10.1111/NPH.12697
Abstract: We analysed the responses of 11 ecosystem models to elevated atmospheric [ CO 2 ] (e CO 2 ) at two temperate forest ecosystems ( D uke and Oak Ridge National Laboratory ( ORNL ) F ree‐ A ir CO 2 E nrichment ( FACE ) experiments) to test alternative representations of carbon ( C )–nitrogen ( N ) cycle processes. We decomposed the model responses into component processes affecting the response to e CO 2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production ( NPP ) at both sites, but none was able to simulate both the sustained 10‐yr enhancement at D uke and the declining response at ORNL : models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above‐ground–below‐ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of e CO 2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C – N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO 2 , given the complexity of factors leading to the observed erging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections.
Publisher: IOP Publishing
Date: 12-2020
Abstract: Land-use change affects both the quality and quantity of soil organic carbon (SOC) and leads to changes in ecosystem functions such as productivity and environmental regulation. Future changes in SOC are, however, highly uncertain owing to its heterogeneity and complexity. In this study, we analyzed the outputs of simulations of SOC stock by Earth system models (ESMs), most of which are participants in the Land-Use Model Intercomparison Project. Using a common protocol and the same forcing data, the ESMs simulated SOC distribution patterns and their changes during historical (1850–2014) and future (2015–2100) periods. Total SOC stock increased in many simulations over the historical period (30 ± 67 Pg C) and under future climate and land-use conditions (48 ± 32 Pg C for ssp126 and 49 ± 58 Pg C for ssp370 ). Land-use experiments indicated that changes in SOC attributable to land-use scenarios were modest at the global scale, in comparison with climatic and rising CO 2 impacts, but they were notable in several regions. Future net soil carbon sequestration rates estimated by the ESMs were roughly 0.4‰ yr −1 (0.6 Pg C yr −1 ). Although there were considerable inter-model differences, the rates are still remarkable in terms of their potential for mitigation of global warming. The disparate results among ESMs imply that key parameters that control processes such as SOC residence time need to be better constrained and that more comprehensive representation of land management impacts on soils remain critical for understanding the long-term potential of soils to sequester carbon.
Publisher: Copernicus GmbH
Date: 17-03-2022
DOI: 10.5194/GMD-2022-1
Abstract: Abstract. Land biosphere processes are of central importance to the climate system. Specifically, biological processes interact with the atmosphere through a variety of feedback loops that modulate energy, water and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land-atmosphere interactions. Dynamic Global Vegetation Models (DGVMs) attempt to capture these land surface processes, and are increasingly incorporated into Earth System Models (ESMs), which makes it possible to study the coupled dynamics of the land-biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water and CO2 between the land-ecosystem and the atmosphere. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modeled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types, but the emergent ecosystem composition and structure are consistent between the two versions. We find that the choice of stomatal conductance model has a major impact on the model's predictions. The new LSM implementation described in this work lays the foundation for using the well established LPJ-GUESS DGVM as an alternative LSM in coupled land-biosphere-climate studies, where an accurate representation of ecosystem processes is essential.
Publisher: Frontiers Media SA
Date: 14-08-2020
Publisher: American Geophysical Union (AGU)
Date: 12-2015
DOI: 10.1002/2015JG002988
Publisher: Wiley
Date: 25-03-2013
DOI: 10.1111/GCB.12164
Abstract: Predicted responses of transpiration to elevated atmospheric CO2 concentration (eCO2 ) are highly variable amongst process-based models. To better understand and constrain this variability amongst models, we conducted an intercomparison of 11 ecosystem models applied to data from two forest free-air CO2 enrichment (FACE) experiments at Duke University and Oak Ridge National Laboratory. We analysed model structures to identify the key underlying assumptions causing differences in model predictions of transpiration and canopy water use efficiency. We then compared the models against data to identify model assumptions that are incorrect or are large sources of uncertainty. We found that model-to-model and model-to-observations differences resulted from four key sets of assumptions, namely (i) the nature of the stomatal response to elevated CO2 (coupling between photosynthesis and stomata was supported by the data) (ii) the roles of the leaf and atmospheric boundary layer (models which assumed multiple conductance terms in series predicted more decoupled fluxes than observed at the broadleaf site) (iii) the treatment of canopy interception (large intermodel variability, 2-15%) and (iv) the impact of soil moisture stress (process uncertainty in how models limit carbon and water fluxes during moisture stress). Overall, model predictions of the CO2 effect on WUE were reasonable (intermodel μ = approximately 28% ± 10%) compared to the observations (μ = approximately 30% ± 13%) at the well-coupled coniferous site (Duke), but poor (intermodel μ = approximately 24% ± 6% observations μ = approximately 38% ± 7%) at the broadleaf site (Oak Ridge). The study yields a framework for analysing and interpreting model predictions of transpiration responses to eCO2 , and highlights key improvements to these types of models.
Publisher: Wiley
Date: 21-05-2014
DOI: 10.1111/NPH.12847
Abstract: Elevated atmospheric CO 2 concentration ( eCO 2 ) has the potential to increase vegetation carbon storage if increased net primary production causes increased long‐lived biomass. Model predictions of eCO 2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free‐air CO 2 enrichment ( FACE ) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO 2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO 2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions careful testing of allocation schemes and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets.
Publisher: Copernicus GmbH
Date: 26-10-2021
Abstract: Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon–climate feedbacks under continued winter warming. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product, where the overestimation of permafrost cover decreased from 10 % to 5 % using the new snow scheme. Besides soil thermodynamics, the new snow scheme resulted in a doubled winter respiration and an overall higher vegetation carbon content. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a more realistic simulation of arctic carbon–climate feedbacks.
Publisher: Springer Science and Business Media LLC
Date: 27-08-2018
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-20651
Abstract: & & Humans have dramatically increased atmospheric CO& sub& & /sub& concentration as well as biologically available nitrogen (N). Nitrogen is an essential nutrient for vegetation growth and N availability represents a limiting factor on carbon (C) sequestration by the terrestrial ecosystems. & While there is a large infrastructure for measurements to constrain the C cycle, data to constrain the N cycle are less readily available. Using a combination of remote sensing products (MODIS), canopy N concentration data (ICP forest), plant functional type and environmental variables including soil, climate (WorldClim) and elevation (EU-DEM), we generated a canopy N map across European forests using a random forest statistical method (hereafter RF canopy N map).& & & & Most current Global Vegetation Models (GVMs) have integrated C and N cycles, to account for the link between C and N for plant growth and respiration. Leaf N concentration is also important for other biomass compartments as N allocations are prescribed relative to leaf N.& The objective of this study is to compare canopy N of two GVMs, O-CN and LPJ-GUESS, and the RF canopy N map in European forests.& & & & The obtained canopy N maps show contrasting spatial patterns. The RF canopy N map shows higher canopy N values, i.e. between 1.8 and 2.2 %N, in mid-western and eastern Europe, while showing lower values, i.e. 1.2 and 1.6 %N, around the Mediterranean region and in the south of Sweden. The canopy N map obtained from the O-CN simulation shows relatively lower canopy N values, ranging from 1.0 to 1.8 %N, in central and northern Europe, while in the Mediterranean region the values are higher, between 1.8 and 2.4 %N. Similar to the RF map, the LPJ-GUESS canopy N map shows relatively higher canopy N values in mid-western Europe compared to southern and northern Europe, however, the LPJ-GUESS canopy N values show little spatial variation in the Mediterranean region.& Also, the LPJ-GUESS values are higher, with canopy N values ranging between 2.0 and 2.8 %N in mid-western Europe, and canopy N values ranging between 1.6 and 1.8 %N in the Mediterranean region.& & & & The analysis yields insight into spatial differences in RF canopy N and canopy N predicted by GVMs, with especially a mismatch in arid and warm regions.& &
Publisher: Copernicus GmbH
Date: 09-12-2016
Publisher: Copernicus GmbH
Date: 10-04-2014
Abstract: Abstract. The LPJ-GUESS dynamic vegetation model uniquely combines an in idual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C–N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10% additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C–N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.
Publisher: Copernicus GmbH
Date: 08-04-2022
Abstract: Abstract. The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Publisher: Copernicus GmbH
Date: 04-09-2020
Publisher: Copernicus GmbH
Date: 10-01-2020
DOI: 10.5194/BG-2019-513
Abstract: Abstract. The nitrogen cycle and its effect on carbon uptake in the terrestrial biosphere is a recent progression in earth system models. As with any new component of a model, it is important to understand the behaviour, strengths, and limitations of the various process representations. Here we assess and compare five models with nitrogen cycles that will be used as the terrestrial components of some of the earth system models in CMIP6. We use a historical control simulation and two perturbations to assess the models' nitrogen-related performance: a simulation with atmospheric carbon dioxide 200 ppm higher, and one with nitrogen deposition increased by 50 kg N ha−1 yr−1. We find that, despite differing nitrogen cycle representations, all models simulate recent global trends in terrestrial productivity and net carbon uptake commensurate with observations. The between-model variation is likely more influenced by other, non-nitrogen parts of the models. Globally, the productivity response to increased carbon dioxide is commensurate with observations for four of the five models, but highly spatially variable within and between models. The productivity response to increased nitrogen is significantly lower than observed in two of the five models. The global and tropical values are generally better represented than boreal, tundra, or other high latitude areas. These results are due to ergent though valid choices in the representation of key processes. They show the need for better understanding and more provision of observational constraints of nitrogen processes, especially nitrogen-use efficiency and biological nitrogen fixation.
Publisher: Wiley
Date: 16-12-2020
DOI: 10.1111/GEB.13238
Publisher: Copernicus GmbH
Date: 06-09-2022
Abstract: Abstract. Land biosphere processes are of central importance to the climate system. Specifically, ecosystems interact with the atmosphere through a variety of feedback loops that modulate energy, water, and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land–atmosphere interactions. Dynamic global vegetation models (DGVMs) attempt to capture land ecosystem processes and are increasingly incorporated into Earth system models (ESMs), which makes it possible to study the coupled dynamics of the land biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water, and CO2 between the land ecosystem and the atmosphere and thus provide surface boundary conditions to an atmospheric model over land. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modelled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types. We find that the emerging ecosystem composition and carbon fluxes are sensitive to both the choice of stomatal conductance model and the response of plant water uptake to soil moisture. The new implementation described in this work lays the foundation for using the well-established LPJ-GUESS DGVM as an alternative land surface model (LSM) in coupled land–biosphere–climate studies, where an accurate representation of ecosystem processes is essential.
Publisher: Copernicus GmbH
Date: 04-09-2020
DOI: 10.5194/BG-2020-319
Abstract: Abstract. Plant phenology plays a fundamental role in land-atmosphere interactions, and its variability and variations are an indicator of climate and environmental changes. For this reason, current land surface models include phenology parameterizations and related biophysical and biogeochemical processes. In this work, the climatology of beginning and end of the growing season, simulated by seven state-of-the-art European land surface models, is evaluated globally against satellite observations. The assessment is performed using the vegetation metric leaf area index and a recently-developed approach, named four growing season types. On average, the land surface models show a 0.6-month delay in the growing season start, while they are about 0.5 months earlier in the growing season end. Difference with observation tends to be higher in the Southern Hemisphere compared to the Northern Hemisphere. High agreement between land surface models and observations is exhibited in areas dominated by broad-leaf deciduous trees, while high variability is noted in regions dominated by broad-leaf deciduous shrubs. Generally, the timing of the growing season end is accurately simulated in about 25 % of global land grid points versus 16 % in the timing of growing season start. The refinement of phenology parameterization can lead to better representation of vegetation-related energy, water, and carbon cycles in land surface models, but plant phenology is also affected by plant physiology and soil hydrology processes. Consequently, phenology representation and, in general, vegetation modelling is a complex task, which still needs further improvement, evaluation, and multi-model comparison.
Publisher: IOP Publishing
Date: 07-2021
Abstract: Land surface models are used to provide global estimates of soil organic carbon (SOC) changes after past and future change land use change (LUC), in particular re-/deforestation. To evaluate how well the models capture decadal-scale changes in SOC after LUC, we provide the first consistent comparison of simulated time series of LUC by six land models all of which participated in the coupled model intercomparison project phase 6 (CMIP6) with soil carbon chronosequences (SCCs). For this comparison we use SOC measurements of adjacent plots at four high-quality data sites in temperate and tropical regions. We find that initial SOC stocks differ among models due to different approaches to represent SOC. Models generally meet the direction of SOC change after reforestation of cropland but the litude and rate of changes vary strongly among them. The normalized root mean square errors of the multi model mean range from 0.5 to 0.8 across sites and 0.1–0.7 when excluding outliers. Further, models simulate SOC losses after deforestation for crop or grassland too slow due to the lack of crop harvest impacts in the models or an overestimation of the SOC recovery on grassland. The representation of management, especially nitrogen levels is important to capture drops in SOC after land abandonment for forest regrowth. Crop harvest and fire management are important to match SOC dynamics but more difficult to quantify as SCC rarely report on these events. Based on our findings, we identify strengths and propose potential improvements of the applied models in simulating SOC changes after LUC.
Publisher: Copernicus GmbH
Date: 29-04-2015
Abstract: Abstract. Nitrogen (N) is a key element in terrestrial ecosystems as it influences both plant growth and plant interactions with the atmosphere. Accounting for carbon–nitrogen interactions has been found to alter future projections of the terrestrial carbon (C) cycle substantially. Dynamic vegetation models (DVMs) aim to accurately represent both natural vegetation and managed land, not only from a carbon cycle perspective but increasingly so also for a wider range of processes including crop yields. We present here the extended version of the DVM LPJ-GUESS that accounts for N limitation in crops to account for the effects of N fertilisation on yields and biogeochemical cycling. The performance of this new implementation is evaluated against observations from N fertiliser trials and CO2 enrichment experiments. LPJ-GUESS captures the observed response to both N and CO2 fertilisation on wheat biomass production, tissue C to N ratios (C : N) and phenology. To test the model's applicability for larger regions, simulations are subsequently performed that cover the wheat-dominated regions of western Europe. When compared to regional yield statistics, the inclusion of C–N dynamics in the model substantially increase the model performance compared to an earlier version of the model that does not account for these interactions. For these simulations, we also demonstrate an implementation of N fertilisation timing for areas where this information is not available. This feature is crucial when accounting for processes in managed ecosystems in large-scale models. Our results highlight the importance of accounting for C–N interactions when modelling agricultural ecosystems, and it is an important step towards accounting for the combined impacts of changes in climate, [CO2] and land use on terrestrial biogeochemical cycles.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-7001
Abstract: With climate change happening at a faster rate at high-latitudes than the global average, it is important to understand the warming-induced permafrost thaw effect on high-latitude GHG emissions. As permafrost soils contain nearly half of the global soil C pool a change to active layer depths could substantially increase GHG emissions from the soil and hence the concentrations in the atmosphere. Here we present a version of the dynamic vegetation model LPJ-GUESS updated to include a new multi-layer soil organic matter scheme that makes it possible to simulate organic matter dynamics at all soil depths. Together with improved soil physics, hydrology, and snow representation, this new version of LPJ-GUESS can closely simulate the current best estimates of Arctic soil C at depths (e.g. NCSCDv2.2) making it possible to simulate emissions of CO2, CH4, and N2O as the active layer thickens. We also present preliminary estimates of how the Arctic soil thermodynamics and biogeochemistry could change under different future scenarios, including overshoot scenarios, to see if the Arctic C balance will act as a net source or sink of greenhouse gases.
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-12561
Abstract: & & Land surface models are used to provide global estimates of soil organic carbon (SOC) changes after past and future land use change (LUC). To evaluate how well the models capture decadal scale changes in SOC after LUC, we provide the first consistent comparison of simulated time series of LUC by six land models all of which participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6) with soil carbon chronosequences (SCC). For this comparison we use SOC measurements of adjacent plots at four high-quality data sites in temperate and tropical regions. We find that initial SOC stocks differ among models due to different approaches to represent SOC. Models generally meet the direction of SOC change after reforestation of cropland but the litude and rate of changes vary strongly among them. Further, models simulate SOC losses after deforestation for crop or grassland too slow due to the lack of crop harvest impacts in the models or an overestimation of the SOC recovery on grassland. The representation of management, especially nitrogen levels is important to capture drops in SOC after land abandonment for forest regrowth. Crop harvest and fire management are important to match SOC dynamics but more difficult to quantify as SCC hardly report on these events. Based on our findings, we identify strengths and propose potential improvements of the applied models in simulating SOC changes after LUC.& &
Publisher: Copernicus GmbH
Date: 30-11-2015
Abstract: Abstract. Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response to cropland management, are scarce. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land-use-enabled dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land-use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. Our model experiments allow us to investigate trade-offs between these ecosystem services that can be provided from agricultural fields. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP (Representative Concentration Pathway) 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till management and cover crops proposed in previous studies is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C–N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles.
Publisher: Copernicus GmbH
Date: 17-08-2020
Publisher: American Geophysical Union (AGU)
Date: 28-07-2019
DOI: 10.1029/2019GL083729
Abstract: Understanding the transition of biosphere‐atmosphere carbon exchange between glacial and interglacial climates can constrain uncertainties in its future projections. Using an in idual‐based dynamic vegetation model, we simulate vegetation distribution and terrestrial carbon cycling in past cold and warm climates and elucidate the forcing effects of temperature, precipitation, atmospheric CO 2 concentration (pCO 2 ), and landmass. Results are consistent with proxy reconstructions and reveal that the vegetation extent is mainly determined by temperature anomalies, especially in a cold climate, while precipitation forcing effects on global‐scale vegetation patterns are marginal. The pCO 2 change controls the global carbon balance with the fertilization effect of higher pCO 2 linking to higher vegetation coverage, an enhanced terrestrial carbon sink, and increased terrestrial carbon storage. Our results indicate carbon transfer from ocean and permafrost eat to the biosphere and atmosphere and highlight the importance of forest expansion as a driver of terrestrial ecosystem carbon stock from cold to warm climates.
Publisher: Copernicus GmbH
Date: 23-10-2020
Abstract: Abstract. The nitrogen cycle and its effect on carbon uptake in the terrestrial biosphere is a recent progression in earth system models. As with any new component of a model, it is important to understand the behaviour, strengths, and limitations of the various process representations. Here we assess and compare five land surface models with nitrogen cycles that are used as the terrestrial components of some of the earth system models in CMIP6. The land surface models were run offline with a common spin-up and forcing protocol. We use a historical control simulation and two perturbations to assess the model nitrogen-related performances: a simulation with atmospheric carbon dioxide increased by 200 ppm and one with nitrogen deposition increased by 50 kgN ha−1 yr−1. There is generally greater variability in productivity response between models to increased nitrogen than to carbon dioxide. Across the five models the response to carbon dioxide globally was 5 % to 20 % and the response to nitrogen was 2 % to 24 %. The models are not evenly distributed within the ensemble range, with two of the models having low productivity response to nitrogen and another one with low response to elevated atmospheric carbon dioxide, compared to the other models. In all five models in idual grid cells tend to exhibit bimodality, with either a strong response to increased nitrogen or atmospheric carbon dioxide but rarely to both to an equal extent. However, this local effect does not scale to either the regional or global level. The global and tropical responses are generally more accurately modelled than boreal, tundra, or other high-latitude areas compared to observations. These results are due to ergent choices in the representation of key nitrogen cycle processes. They show the need for more observational studies to enhance understanding of nitrogen cycle processes, especially nitrogen-use efficiency and biological nitrogen fixation.
Publisher: American Geophysical Union (AGU)
Date: 10-2021
DOI: 10.1029/2020GB006933
Abstract: Anthropogenic nitrogen deposition is widely considered to increase CO 2 sequestration by land plants on a global scale. Here, we demonstrate that bedrock nitrogen weathering contributes significantly more to nitrogen‐carbon interactions than anthropogenic nitrogen deposition. This working hypothesis is based on the introduction of empirical results into a global biogeochemical simulation model over the time period of the mid‐1800s to the end of the 21st century. Our findings suggest that rock nitrogen inputs have contributed roughly 2–11 times more to plant CO 2 capture than nitrogen deposition inputs since pre‐industrial times. Climate change projections based on RCP 8.5 show that rock nitrogen inputs and biological nitrogen fixation contribute 2–5 times more to terrestrial carbon uptake than anthropogenic nitrogen deposition though year 2101. Future responses of rock N inputs on plant CO 2 capture rates are more signficant at higher latitudes and in mountainous environments, where geological and climate factors promote higher rock weathering rates. The enhancement of plant CO 2 uptake via rock nitrogen weathering partially resolves nitrogen‐carbon discrepancies in Earth system models and offers an alternative explanation for lack of progressive nitrogen limitation in the terrestrial biosphere. We conclude that natural N inputs impart major control over terrestrial CO 2 sequestration in Earth’s ecosystems.
Publisher: Copernicus GmbH
Date: 16-04-2021
Abstract: Abstract. Plant phenology plays a fundamental role in land–atmosphere interactions, and its variability and variations are an indicator of climate and environmental changes. For this reason, current land surface models include phenology parameterizations and related biophysical and biogeochemical processes. In this work, the climatology of the beginning and end of the growing season, simulated by the land component of seven state-of-the-art European Earth system models participating in the CMIP6, is evaluated globally against satellite observations. The assessment is performed using the vegetation metric leaf area index and a recently developed approach, named four growing season types. On average, the land surface models show a 0.6-month delay in the growing season start, while they are about 0.5 months earlier in the growing season end. The difference with observation tends to be higher in the Southern Hemisphere compared to the Northern Hemisphere. High agreement between land surface models and observations is exhibited in areas dominated by broadleaf deciduous trees, while high variability is noted in regions dominated by broadleaf deciduous shrubs. Generally, the timing of the growing season end is accurately simulated in about 25 % of global land grid points versus 16 % in the timing of growing season start. The refinement of phenology parameterization can lead to better representation of vegetation-related energy, water, and carbon cycles in land surface models, but plant phenology is also affected by plant physiology and soil hydrology processes. Consequently, phenology representation and, in general, vegetation modelling is a complex task, which still needs further improvement, evaluation, and multi-model comparison.
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-10409
Abstract: & & Canopy biophysical properties play an important role in understanding forest health and productivity. Among these parameters, forest leaf area index (LAI), canopy cover fraction, and canopy chlorophyll content describe the vegetation abundance, photosynthetic capacity and primary productivity of forest stands. The new generation of remote sensing satellites such as Sentinel-2 with high spatial and temporal resolutions has provided vast opportunities for monitoring these parameters and assessing their interrelationships over vast forest landscapes. In this research, temporal Sentinel-2 data between 2017-2019 in the temperate mixed forest ecosystem of the Bavarian Forest National Park, Germany, was used to retrieve forest canopy biophysical variables. INFORM radiative transfer model was used to retrieve LAI and canopy chlorophyll content while the fraction of vegetation functional types were calculated using phenological parameters and empirical approaches. A recent landcover map of the Bavarian Forest National Park was applied to retrieve considered variables pursuant to the different land cover classes. The retrieved variables were validated using in situ measurements of LAI and canopy chlorophyll content. Primary productivity was then calculated using (i) vegetation index universal pattern decomposition approach and (ii) the process-based dynamic vegetation-terrestrial ecosystem model LPJ-GUESS model. The relationships between calculated productivities and estimated biophysical variables were then studied. Our results showed that there is a good agreement between primary productivities calculated from LPG GUESS and the decomposition approach. Among studied parameters, canopy chlorophyll content, which represents pigments and vegetation abundance within the canopy, showed a strong direct relationship with both calculated primary productivities and hence may be used to explain plant functioning. Our results also revealed that remotely sensed vegetation biophysical parameters- that are becoming more and more readily available due to the availability of Earth observation data- can be used as proxies for estimation of the primary productivity calculated using either approach. Calculation of primary productivity usually needs information about canopy life-cycle and geometry, which are often not available at large scales. The results of our study support our findings in the myVARIABLE pilot of the EuroGEOSS Showcases initiative (e-shape) on developing primary productivity as a remotely sensed- essential bio ersity variable describing & #8216 Ecosystem function.& #8217 & &
Publisher: Copernicus GmbH
Date: 16-01-2015
Abstract: Abstract. Nitrogen (N) is a key element in terrestrial ecosystems as it influences both plant growth and plant interactions with the atmosphere. Accounting for carbon-nitrogen interactions has been found to alter future projections of the terrestrial carbon (C) cycle substantially. Dynamic vegetation models (DVMs) aim to accurately represent both natural vegetation and managed land, not only from a carbon cycle perspective but increasingly so also for a wider range of processes including crop yields. We present here the extended version of the DVM LPJ-GUESS that accounts for N limitation in crops to account for the effects of N fertilisation on yields and biogeochemical cycling. The performance of this new implementation is evaluated against observations from N fertiliser trials and CO2 enrichment experiments. LPJ-GUESS captures the observed response to both N and CO2 fertilization on wheat biomass production, tissue C to N ratios (C : N) and phenology. To test the model's applicability for larger regions, simulations are subsequently performed that cover the wheat-dominated regions of Western Europe. When compared to regional yield statistics, the inclusion of C–N dynamics in the model substantially increase the model performance compared to an earlier version of the model that does not account for these interactions. For these simulations, we also demonstrate an implementation of N fertilisation timing for areas where this information is not available. This feature is crucial when accounting for processes in managed ecosystems in large-scale models. Our results highlight the importance of accounting for C–N interactions when modelling agricultural ecosystems, and it is an important step towards accounting for the combined impacts of changes in climate, [CO2] and land use on terrestrial biogeochemical cycles.
Publisher: American Geophysical Union (AGU)
Date: 04-2015
DOI: 10.1002/2014GB004995
Location: Sweden
Start Date: 12-2022
End Date: 12-2026
Amount: $368,981.00
Funder: Australian Research Council
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