Modeling of the boreal vegetation and its dynamics in the ORCHIDEE continental land surface scheme

L’évolution du climat sur les prochaines dizaines voire centaines d’années pose de nombreuses interrogations, du fait de l’impact de l’homme. Les émissions de gaz à effet de serre depuis le début de l’ère industrielle entrainent une augmentation des températures. Celle-ci est susceptible d’affecter les écosystèmes terrestres, notamment dans les régions boréales où les augmentations de température observées et projetées sont plus importantes. Une évolution de ces écosystèmes peut entrainer des rétroactions sur le climat. Ainsi le phénomène actuel observé de verdissement des régions boréales (ou « Arctic greening ») peut augmenter ce réchauffement via une diminution de l’albédo. Afin de répondre à ces interrogations, des modèles climatiques ont été développés, intégrant des modèles de surface continentale représentant les flux de matière et d’énergie. Le travail effectué dans cette thèse a été mené à partir de l’un d’eux, le modèle de surface continentale ORCHIDEE, qui comprend une description succincte de la végétation boréale. L’objectif de cette thèse était donc l’implémentation puis la modélisation de la végétation boréale.Afin de décrire la végétation présente au niveau des hautes latitudes, i.e. les toundras et les steppes, de nouveaux types de végétation (PFTs) ont été intégrés au modèle à partir des PFTs déjà présents. Tout d’abord, les plantes non vasculaires (NVPs) ont été introduites pour représenter les lichens et les bryophytes, ensuite les buissons pour représenter une strate intermédiaire entre les arbres et les herbacées, et enfin des herbacées C3 boréales pour distinguer la végétation considérée dans les steppes boréales et les prairies tempérées. La description de cette végétation boréale s’est accompagnée de l’intégration de nouveaux processus caractéristiques, allant de l’implémentation d’interactions nouvelles telles que la protection des buissons par la neige en hiver, au simple choix de nouveaux paramètres du PFT, en passant par la modification de processus déjà présents dans le modèle comme la conductance stomatique des NVPs. D’autres processus en lien avec la végétation ont également été mis à jour ou corrigés. Enfin, pour modéliser la dynamique de la végétation boréale, les nouveaux PFTs ont été intégrés à la description initialement présente dans le modèle.Ces modifications ont permis de modéliser la végétation boréale et ses impacts sur les autres variables du système (flux de matière ou d’énergie), soit avec une végétation prescrite (simulations de la période récente), soit avec une végétation dynamique (simulations présentes et futures, à partir des scénarios RCPs 4.5 et 8.5). Les simulations effectuées avec la végétation prescrite montrent que l’on représente mieux le comportement de la végétation avec les nouveaux PFTs. Avec les PFTs originaux la productivité et la biomasse étaient surestimées dans les régions boréales et entrainaient une sous-estimation de l’albédo et une surestimation de la transpiration. Les simulations avec une végétation dynamique ont démontré la capacité du modèle à représenter avec la nouvelle végétation boréale les biomes actuels ainsi que l’« Arctic greening ». Par contre, l’embuissonement observé dans plusieurs études n’a pas été reproduit. Globalement l’introduction des PFTs boréaux s’est traduite par une meilleure description des écosystèmes arctiques et des échanges d’énergie et de matière avec l’atmosphère. Par contre, la protection du pergélisol par les NVPs n’a pas été aussi importante qu’attendu et a été compensée par une augmentation de l’humidité du sol.L’introduction de la nouvelle végétation boréale dans le modèle ORCHIDEE semble donc pertinente et met en évidence l’importance de la représentation de ces écosystèmes. Ce travail ouvre donc des perspectives pour améliorer les simulations climatiques, tant futures que passées. Comme la modélisation de la végétation depuis l’Holocène afin de simuler la quantité de carbone contenu aujourd’hui dans le pergélisol.Climate evolution over the next ten to hundred years involves many questions, linked to the impact of man. Indeed, greenhouse gases emissions since the beginning of the industrial era lead to an increase in temperature. The latter can affect terrestrial ecosystems, particularly in boreal regions where observed and projected temperature increase is larger than in mid-latitudes. Evolution of these ecosystems can trigger climate feedbacks. For example, the currently observed « Arctic greening » phenomenon could enhance the warming via a decrease in albedo due to the increase in vegetation cover. In order to address these questions, climate models were developped, including continental surface models taking into account the fluxes of mass and energy. In this thesis, such a model was used, the continental surface scheme ORCHIDEE, which includes a succinct description of boreal vegetation. The aim of this work was thus the implementation and the modeling of boreal vegetation.In order to describe high-latitude vegetation, i.e. toundras and steppes, new plant functional types (PFTs) were integrated into the model based on existing PFTs. First, non-vascular plants (NVPs) were integrated to represent lichens and bryophytes found in desert toundras and peatlands, then shrubs to represent an intermediate stratum between trees and grasses in toundras, and finally boreal C3 grasses to distinguish vegetation found in boreal steppes and temperate grasslands. The description of this boreal vegetation was accompanied by the integration of new charachteristic processes, from the implementation of new interactions such as the protection of shrubs by snow in winter, to the simple choice of new PFT parameters such as the lower photosynthetic capacity of boreal C3 grasses compared to temperate C3 grasses, through the modification of existing processes such as the stomatal conductance of NVPs. Other processes linked to vegetation were also updated or corrected. Finally, to model the dynamics of boreal vegetation, new PFTs were integrated into the initial description in the model.Those changes enabled the modeling of boreal vegetation and its impact on other variables (mass or energy fluxes), either using a prescribed vegetation (simulations on the recent period), or using a dynamical vegetation (recent and future simulations using RCPs 4.5 and 8.5). Simulations using the prescribed vegetation indicated that vegetation behaviour is better represented with the new PFTs. With original PFTs, productivity and biomass were overestimated in boreal regions, and lead to an underestimation of albedo and an overestimation of transpiration. Simulations using a dynamical vegetation demonstrated the ability of the model, using the new boreal vegetation, to represent current-day biomes as well as « Arctic greening ». However, the shrubification observed in several studies was not reproduced. Similarly, the impact of new PFTs on other model outputs is important, with for example a decrease in productivity or albedo in winter compared to the original vegetation. Thus, the introduction of boreal PFTs generally resulted in a better description of Arctic ecosystems and of the exchanges of energy and mass with the atmosphere. On the other hand, the protection of permafrost by NVPs was not as substantial as expected and was compensated by an increase in soil humidity (due to shrubs and boreal grasses).The introduction of the new boreal vegetation in the ORCHIDEE model thus seems relevant, and highlights the importance of representing these ecosystems. This work opens up new perspectives to improve future and past climate simulations. The next step consists in modeling vegetation since the Holocene into the future in order to simulate the current amounts of carbone in the permafrost, and to project the outcome of these stocks in the context of climate change and permafrost melt

Modélisation de la végétation boréale et de sa dynamique dans le modèle de surface continentale ORCHIDEE

Climate evolution over the next ten to hundred years involves many questions, linked to the impact of man. Indeed, greenhouse gases emissions since the beginning of the industrial era lead to an increase in temperature. The latter can affect terrestrial ecosystems, particularly in boreal regions where observed and projected temperature increase is larger than in mid-latitudes. Evolution of these ecosystems can trigger climate feedbacks. For example, the currently observed « Arctic greening » phenomenon could enhance the warming via a decrease in albedo due to the increase in vegetation cover. In order to address these questions, climate models were developped, including continental surface models taking into account the fluxes of mass and energy. In this thesis, such a model was used, the continental surface scheme ORCHIDEE, which includes a succinct description of boreal vegetation. The aim of this work was thus the implementation and the modeling of boreal vegetation.In order to describe high-latitude vegetation, i.e. toundras and steppes, new plant functional types (PFTs) were integrated into the model based on existing PFTs. First, non-vascular plants (NVPs) were integrated to represent lichens and bryophytes found in desert toundras and peatlands, then shrubs to represent an intermediate stratum between trees and grasses in toundras, and finally boreal C3 grasses to distinguish vegetation found in boreal steppes and temperate grasslands. The description of this boreal vegetation was accompanied by the integration of new charachteristic processes, from the implementation of new interactions such as the protection of shrubs by snow in winter, to the simple choice of new PFT parameters such as the lower photosynthetic capacity of boreal C3 grasses compared to temperate C3 grasses, through the modification of existing processes such as the stomatal conductance of NVPs. Other processes linked to vegetation were also updated or corrected. Finally, to model the dynamics of boreal vegetation, new PFTs were integrated into the initial description in the model.Those changes enabled the modeling of boreal vegetation and its impact on other variables (mass or energy fluxes), either using a prescribed vegetation (simulations on the recent period), or using a dynamical vegetation (recent and future simulations using RCPs 4.5 and 8.5). Simulations using the prescribed vegetation indicated that vegetation behaviour is better represented with the new PFTs. With original PFTs, productivity and biomass were overestimated in boreal regions, and lead to an underestimation of albedo and an overestimation of transpiration. Simulations using a dynamical vegetation demonstrated the ability of the model, using the new boreal vegetation, to represent current-day biomes as well as « Arctic greening ». However, the shrubification observed in several studies was not reproduced. Similarly, the impact of new PFTs on other model outputs is important, with for example a decrease in productivity or albedo in winter compared to the original vegetation. Thus, the introduction of boreal PFTs generally resulted in a better description of Arctic ecosystems and of the exchanges of energy and mass with the atmosphere. On the other hand, the protection of permafrost by NVPs was not as substantial as expected and was compensated by an increase in soil humidity (due to shrubs and boreal grasses).The introduction of the new boreal vegetation in the ORCHIDEE model thus seems relevant, and highlights the importance of representing these ecosystems. This work opens up new perspectives to improve future and past climate simulations. The next step consists in modeling vegetation since the Holocene into the future in order to simulate the current amounts of carbone in the permafrost, and to project the outcome of these stocks in the context of climate change and permafrost melt.L’évolution du climat sur les prochaines dizaines voire centaines d’années pose de nombreuses interrogations, du fait de l’impact de l’homme. Les émissions de gaz à effet de serre depuis le début de l’ère industrielle entrainent une augmentation des températures. Celle-ci est susceptible d’affecter les écosystèmes terrestres, notamment dans les régions boréales où les augmentations de température observées et projetées sont plus importantes. Une évolution de ces écosystèmes peut entrainer des rétroactions sur le climat. Ainsi le phénomène actuel observé de verdissement des régions boréales (ou « Arctic greening ») peut augmenter ce réchauffement via une diminution de l’albédo. Afin de répondre à ces interrogations, des modèles climatiques ont été développés, intégrant des modèles de surface continentale représentant les flux de matière et d’énergie. Le travail effectué dans cette thèse a été mené à partir de l’un d’eux, le modèle de surface continentale ORCHIDEE, qui comprend une description succincte de la végétation boréale. L’objectif de cette thèse était donc l’implémentation puis la modélisation de la végétation boréale.Afin de décrire la végétation présente au niveau des hautes latitudes, i.e. les toundras et les steppes, de nouveaux types de végétation (PFTs) ont été intégrés au modèle à partir des PFTs déjà présents. Tout d’abord, les plantes non vasculaires (NVPs) ont été introduites pour représenter les lichens et les bryophytes, ensuite les buissons pour représenter une strate intermédiaire entre les arbres et les herbacées, et enfin des herbacées C3 boréales pour distinguer la végétation considérée dans les steppes boréales et les prairies tempérées. La description de cette végétation boréale s’est accompagnée de l’intégration de nouveaux processus caractéristiques, allant de l’implémentation d’interactions nouvelles telles que la protection des buissons par la neige en hiver, au simple choix de nouveaux paramètres du PFT, en passant par la modification de processus déjà présents dans le modèle comme la conductance stomatique des NVPs. D’autres processus en lien avec la végétation ont également été mis à jour ou corrigés. Enfin, pour modéliser la dynamique de la végétation boréale, les nouveaux PFTs ont été intégrés à la description initialement présente dans le modèle.Ces modifications ont permis de modéliser la végétation boréale et ses impacts sur les autres variables du système (flux de matière ou d’énergie), soit avec une végétation prescrite (simulations de la période récente), soit avec une végétation dynamique (simulations présentes et futures, à partir des scénarios RCPs 4.5 et 8.5). Les simulations effectuées avec la végétation prescrite montrent que l’on représente mieux le comportement de la végétation avec les nouveaux PFTs. Avec les PFTs originaux la productivité et la biomasse étaient surestimées dans les régions boréales et entrainaient une sous-estimation de l’albédo et une surestimation de la transpiration. Les simulations avec une végétation dynamique ont démontré la capacité du modèle à représenter avec la nouvelle végétation boréale les biomes actuels ainsi que l’« Arctic greening ». Par contre, l’embuissonement observé dans plusieurs études n’a pas été reproduit. Globalement l’introduction des PFTs boréaux s’est traduite par une meilleure description des écosystèmes arctiques et des échanges d’énergie et de matière avec l’atmosphère. Par contre, la protection du pergélisol par les NVPs n’a pas été aussi importante qu’attendu et a été compensée par une augmentation de l’humidité du sol.L’introduction de la nouvelle végétation boréale dans le modèle ORCHIDEE semble donc pertinente et met en évidence l’importance de la représentation de ces écosystèmes. Ce travail ouvre donc des perspectives pour améliorer les simulations climatiques, tant futures que passées. Comme la modélisation de la végétation depuis l’Holocène afin de simuler la quantité de carbone contenu aujourd’hui dans le pergélisol

Modeling the vegetation dynamics of northern shrubs and mosses in the ORCHIDEE land surface model

International audienceParameterizations of plant competition processes involving shrubs, mosses, grasses, and trees were introduced with the recently implemented shrubs and mosses plant functional types in the ORCHIDEE dynamic global vegetation model in order to improve the representation of high latitude vegetation dynamics. Competition is based on light capture for growth, net primary productivity, and survival to cold-induced mortality during winter. Trees are assumed to outcompete shrubs and grasses for light, and shrubs outcompete grasses. Shrubs are modeled to have a higher survival than trees to extremely cold winters because of thermic protection by snow. The fractional coverage of each plant type is based on their respective net primary productivity and winter mortality of trees and shrubs. Gridded simulations were carried out for the historical period and the 21st century following the RCP4.5 and 8.5 scenarios. We evaluate the simulated present-day vegetation with an observation-based distribution map and literature data of boreal shrubs. The simulation produces a realistic present-day boreal vegetation distribution, with shrubs, mosses north of trees and grasses. Nevertheless, the model underestimated local shrub expansion compared to observations from selected sites in the Arctic during the last 30 years suggesting missing processes (nutrients and microscale effects). The RCP4.5 and RCP8.5 projections show a substantial decrease of bare soil, an increase in tree and moss cover and an increase of shrub net primary productivity. Finally, the impact of new vegetation types and associated processes is discussed in the context of climate feedbacks. Plain Language Summary Changes in the northern vegetation exert feedbacks on climate through surface energy and greenhouse gas fluxes. For example, increased vegetation cover can lead to warming due to stronger absorption of shortwave radiation (through decreased albedo). In this study we developed a new version of the ORCHIDEE dynamic vegetation model, allowing us to simulate the dynamical cover of mosses and shrubs, two important types of northern vegetation, alongside with grasses and trees. The prevalence of the different forms of vegetation is ruled by light capture during the growing season, mortality during the cold conditions, and competition for space. The new model is tested for present-day land cover and used for future climate projections. We simulated a realistic vegetation map for historical simulations and a substantial decrease of bare soil with shifts of vegetation in future simulations. However, the model underestimated local shrub expansion compared to observations

Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1

International audienceAbstract. With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited with respect to the impact of agriculture on land surface variables. This is particularly true for agro-hydrological processes related to a strong human control on freshwater. While many LSMs consider natural processes only, the development of human-related processes, e.g. crop phenology and irrigation in LSMs, is key. In this study, we present the implementation of a new crop phenology and irrigation scheme in the ISBA (interactions between soil–biosphere–atmosphere) LSM. This highly flexible scheme is designed to account for various configurations and can be applied at different spatial scales. For each vegetation type within a model grid cell, three irrigation systems can be used at the same time. A limited number of parameters are used to control (1) the amount of water used for irrigation, (2) irrigation triggering (based on the soil moisture stress), and (3) crop seasonality (emergence and harvesting). A case study is presented over Nebraska (USA). This region is chosen for its high irrigation density and because independent observations of irrigation practices can be used to verify the simulated irrigation amounts. The ISBA simulations with and without the new crop phenology and irrigation scheme are compared to different satellite-based observations. The comparison shows that the irrigation scheme improves the simulated vegetation variables such as leaf area index, gross primary productivity, and land surface temperature. In addition to a better representation of land surface processes, the results point to potential applications of this new version of the ISBA model for water resource monitoring and climate change impact studies

Mineral element recycling in topsoil following permafrost degradation and a vegetation shift in sub-Arctic tundra

Climate change affects the Arctic and sub-Arctic regions by exposing previously frozen permafrost to thaw, unlocking soil nutrients, changing hydrological processes, and boosting plant growth. As a result, sub-Arctic tundra is subject to a shrub expansion, called “shrubification”, at the expense of sedge species. Depending on the intrinsic foliar properties of these plant species, changes in foliar mineral element fluxes with shrubification in the context of permafrost degradation may influence topsoil mineral element composition. Despite the potential implications of changes in topsoil mineral element concentrations for the fate of organic carbon, this remains poorly quantified. Here, we investigate vegetation foliar and topsoil mineral element composition (Si, K, Ca, P, Mn, Zn, Cu, Mo, V) across a natural gradient of permafrost degradation at a typical sub-Arctic tundra at Eight Mile Lake (Alaska, USA). Results show that foliar mineral element concentrations are higher (up to 9 times; Si, K, Mo for all species, and for some species Zn) or lower (up to 2 times; Ca, P, Mn, Cu, V for all species, and for some species Zn) in sedge than in shrub species. As a result, a vegetation shift over ~40 years has resulted in lower topsoil concentrations in Si, K, Zn, and Mo (respectively of 52, 24, 20, and 51%) in highly degraded permafrost sites compared to poorly degraded permafrost sites due to lower foliar fluxes of these elements. For other elements (Ca, P, Mn, Cu, and V), the vegetation shift has not induced a marked change in topsoil concentrations at this current stage of permafrost degradation. A modeled amplified shrubification associated with a further permafrost degradation is expected to increase foliar Ca, P, Mn, Cu, and V fluxes, which will likely change these element concentrations in topsoil. These data can serve as a first estimate to assess the influence of other shifts in vegetation in Arctic and sub-Arctic tundra such as sedge expansion under wetter soil conditions

Does vegetation shift in Arctic tundra upon permafrost degradation influence mineral element recycling in the topsoil?

Climate change affects the Arctic and Subarctic regions by exposing previously frozen permafrost to thaw, unlocking nutrients, changing hydrological processes, and boosting plant growth. As a result, Arctic tundra is subject to a shrub expansion, called “shrubification” at the expense of sedge species. Depending on intrinsic foliar properties of these plant species, changes in foliar fluxes with shrubification in the context of permafrost degradation may influence topsoil mineral element composition. Despite the potential implications for the fate of organic carbon in the topsoil, this remains poorly quantified. Here, we investigate vegetation foliar and topsoil mineral element composition (mineral elements that influence organic carbon decomposition: Si, K, Ca, P, Mn, Zn, Cu, Mo and V) from a typical Arctic tundra at Eight Mile Lake (Alaska, USA) across a natural gradient of permafrost degradation. Results show that foliar element concentrations are higher (up to 9 times; Si, K, Mo, and for some species Zn) or lower (up to 2 times; Ca, P, Mn, Cu, V, and for some species Zn) in sedge than in shrub species. This induces different foliar flux with permafrost degradation and shrubification. As a result, a vegetation shift over ~40 years from sedges to shrubs has resulted in lower topsoil concentrations in Si, K, Zn and Mo (respectively of 52, 24, 20 and 51%) in poorly degraded permafrost sites compared to highly degraded permafrost sites. For other mineral elements (Ca, P, Mn, Cu and V), the vegetation shift has not induced a marked changed in topsoil concentrations at this stage of permafrost degradation. This observed change in topsoil composition involving beneficial or toxic elements for decomposers is likely to influence organic carbon decomposition. These data can serve as a first estimate to assess the influence of other shifts in vegetation in Arctic tundra such as sedge expansion with wildfires

Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0)

International audienceSimulation of vegetation-climate feedbacks in high latitudes in the ORCHIDEE land surface model was improved by the addition of three new circumpolar plant functional types (PFTs), namely non-vascular plants representing bryophytes and lichens, Arctic shrubs and Arctic C 3 grasses. Non-vascular plants are assigned no stomatal con-ductance, very shallow roots, and can desiccate during dry episodes and become active again during wet periods, which gives them a larger phenological plasticity (i.e. adaptability and resilience to severe climatic constraints) compared to grasses and shrubs. Shrubs have a specific carbon allocation scheme, and differ from trees by their larger survival rates in winter, due to protection by snow. Arctic C 3 grasses have the same equations as in the original ORCHIDEE version , but different parameter values, optimised from in situ observations of biomass and net primary productivity (NPP) in Siberia. In situ observations of living biomass and productivity from Siberia were used to calibrate the parameters of the new PFTs using a Bayesian optimisation procedure. With the new PFTs, we obtain a lower NPP by 31 % (from 55 • N), as well as a lower roughness length (−41 %), transpi-ration (−33 %) and a higher winter albedo (by +3.6 %) due to increased snow cover. A simulation of the water balance and runoff and drainage in the high northern latitudes using the new PFTs results in an increase of fresh water discharge in the Arctic ocean by 11 % (+140 km 3 yr −1), owing to less evapotranspiration. Future developments should focus on the competition between these three PFTs and boreal tree PFTs, in order to simulate their area changes in response to climate change, and the effect of carbon-nitrogen interactions

Spatio-temporal variations and uncertainty in land surface modelling for high latitudes: univariate response analysis

International audienceA range of applications analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, make use of land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from that account for land processes in different ways and this may introduce predictive uncertainty when LSM outputs are used as inputs to inform a given application. For useful predictions for a specific application , one must therefore understand the inherent uncertainties in the LSMs and the variations between them, as well as uncertainties arising from variation in the climate data driving the LSMs. This requires methods to analyse multivariate spatio-temporal variations and differences. A methodology is proposed based on multiway data analysis, which extends singular value decomposition (SVD) to multidimensional tables and provides spatio-temporal descriptions of agreements and disagreements between LSMs for both historical simulations and future predictions. The application underlying this paper is prediction of how climate change will affect the spread of CSIs in the Fennoscandian and northwest Russian regions, and the approach is explored by comparing net primary production (NPP) estimates over the period 1998-2013 from versions of leading LSMs (JULES, CLM5 and two versions of ORCHIDEE) that are adapted to high-latitude processes , as well as variations in JULES up to 2100 when driven by 34 global circulation models (GCMs). A single optimal spatio-temporal pattern, with slightly different weights for the four LSMs (up to 14 % maximum difference), provides a good approximation to all their estimates of NPP, capturing between 87 % and 93 % of the variability in the individual models, as well as around 90 % of the variability in the combined LSM dataset. The next best adjustment to this pattern, capturing an extra 4 % of the overall variability , is essentially a spatial correction applied to ORCHIDEE-HLveg that significantly improves the fit to this LSM, with only small improvements for the other LSMs. Subsequent correction terms gradually improve the overall and individual LSM fits but capture at most 1.7 % of the overall variability. Analysis of differences between LSMs provides information on the times and places where the LSMs differ and by how much, but in this case no single spatio-temporal pattern strongly dominates the variability. Hence interpretation of the analysis requires the summation of several such patterns. Nonetheless, the three best principal tensors capture around 76 % of the variability in the LSM differences and to a first approximation successively indicate the times and places where ORCHIDEE-HLveg, CLM5 and ORCHIDEE-MICT differ from the other LSMs. Differences between the climate forcing GCMs had a marginal effect up to 6 % on NPP predictions out to 2100 without specific spatio-temporal GCM interaction