Publications of Ingrid Jacquemin
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See detailSimulating and analysing climate change impacts on crop yields in Morocco using the CARAIB dynamic vegetation model driven by Med- CORDEX projections
Loudiyi, Iliass ULiege; Jacquemin, Ingrid ULiege; Tychon, Bernard ULiege et al

Conference (2020, May 08)

Morocco, by its geographical position and its climate, is strongly affected by climate change and presents an ever-increasing vulnerability. In fact, the country's economy, being very dependent on ... [more ▼]

Morocco, by its geographical position and its climate, is strongly affected by climate change and presents an ever-increasing vulnerability. In fact, the country's economy, being very dependent on agriculture, would be greatly affected. It is therefore necessary to further develop knowledge about climate change and strengthen forcasting systems for predicting the impacts of climate change. The agriculture in Morocco is largely dominated by rainfed crops and therefore dependent on pluviometry. According to the Global Yield Gap Atlas, about 43% of arable land is devoted to cereals, 7% to plantation crops (olives, almonds, citrus, grapes, dates), 3% to pulses, 2% to forage, 2% to vegetables, 2% to industrial crops (sugar beets, sugar cane, cotton) and oilseeds, and 42% is fallow. In this project we are going to focus on cereals, olives, potatoes and sugar beets. Regarding the climate, Morocco is characterized by a wide variety of topographies ranging from mountains to plains, oasis and Saharan dunes. For this reason, the country experiences diverse climatic conditions with large spatial and intra- and inter-annual variability of precipitation. Morocco faces irregular rain patterns, cold spells and heat waves increasingly resulting in droughts, which significantly affects agriculture. Our research, funded by a bilateral project of Wallonie-Bruxelles International, aims to study the response of Moroccan agriculture to climate change, using the dynamic vegetation model CARAIB (CARbon Assimilation In the Biosphere) developed within the Unit for Modelling of Climate and Biogeochemical Cycles (UMCCB) of the University of Liège. This spatial model includes crops and natural vegetation and may react dynamically to land use changes. Originally constructed to study vegetation dynamics and carbon cycle, it includes coupled hydrological, biogeochemical, biogeographical and fire modules. These modules respectively describe the exchange of water between the atmosphere, the soil and the vegetation, the photosynthetic production and the evolution of carbon stocks and fluxes in this vegetation-soil system. The biogeographical module describes, for natural vegetation, the establishment, growth, competition, mortality, and regeneration of plant species, as well as the occurrence and propagation of fires. For crops, a specific module describes basic management (sowing, harvest, rotation) and phenological phases. Model simulations are performed across north-west Morocco, where the crops activities are important, by using different input data. The timeline of simulations is divided in two periods: past (from 1901 to 2018[LF1] ) and future (from 2019 to 2100). For the past period, we are using high resolution (30 arc sec) gridded climate data derived from WorldClim (climatology) and interpolated anomalies from Climate Research Unit CRU (trend and variability). For the future period, we use interpolated and bias-corrected fields from a regional climate model (ALADIN-Climate) from the Med-CORDEX initiative run at a spatial resolution of 12 km and for three different Representative Concentration Pathway scenarios (RCP2.6, RCP4.5 and RCP8.5). [less ▲]

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See detailAnalysis of carbon sequestration sensitivity to recent changes in land use patterns over Belgium using a combination of models and remote sensing techniques
Verma, Arpita ULiege; Jacquemin, Ingrid ULiege; Francois, Louis et al

Conference (2020, May 07)

Changes in land use/land cover (LU/LC) practices are critical to determine and this is one of the crucial driving forces of terrestrial ecosystem productivity and carbon sink variability. However ... [more ▼]

Changes in land use/land cover (LU/LC) practices are critical to determine and this is one of the crucial driving forces of terrestrial ecosystem productivity and carbon sink variability. However, relatively few studies have quantified the impact of LU/LC change on the terrestrial carbon cycle. In the present study, we developed a workflow for quantifying and assessing changes in terrestrial carbon stocks due to land use change using a dynamic vegetation model. The main objectives are to assess status and variation in carbon stocks across land covers, towards the quantification of spatial distribution and dynamic variation of terrestrial carbon sinks in response to LU/LCchange. Here, with the CARAIB dynamic vegetation model, we perform simulations using several sets of LU/LC data to analyse the sensitivity of the carbon sink. Here we propose a new method of using satellite – and machine learning-based observation to reconstruct historical LU/LC change and compare it with static data from the cadastral map and dynamic data from an agent-based model coupled with CARAIB. It will quantify the spatial and temporal variability of land use during the 2000-2019 period over Belgium at high resolution. This study will give the space to analyse past information and hence calibrate the dynamic vegetation model to minimize uncertainty in the future projection (until 2035). Overall, this study allows us to understand the effect of changing land use pattern and identify the input dataset, which minimizes the uncertainty in model estimation. [less ▲]

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See detailThe GGCMI Phase 2 experiment: Global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
Franke, J. A.; Müller, C.; Elliott, J. et al

in Geoscientific Model Development (2020), 13(5), 2315-2336

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes ... [more ▼]

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen ("CTWN") for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future. © Author(s) 2020. [less ▲]

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See detailGlobal response patterns of major rainfed crops to adaptation by maintaining current growing periods and irrigation
Minoli, Sara; Müller, Christoph; Elliott, Joshua et al

in Earth's Future (2019), 7(12), 1464-1480

Increasing temperature trends are expected to impact yields of major field crops by affectingvarious plant processes, such as phenology, growth, and evapotranspiration. However, future ... [more ▼]

Increasing temperature trends are expected to impact yields of major field crops by affectingvarious plant processes, such as phenology, growth, and evapotranspiration. However, future projectionstypically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble ofseven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops underincreasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, thedominant effect of temperature increase is to shorten the growing period and to reduce grain yields andproduction. We then test the potential of two agronomic measures to combat warming-induced yieldreduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and(ii) conversion of rainfed systems to irrigated ones inorder to alleviate the negative temperature effects thatare mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate globalproduction losses up to2Koftemperature increase, with larger potentials in continental and temperateregions. Irrigation could also compensate production losses, but its potential is highest in arid regions,where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation isnot a true adaptation measure but rather an intensification strategy, as it equally increases productionunder any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation,crop production declines already at moderate warming, making adaptation particularly challenging inthese areas. (c) The Authors [less ▲]

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See detailUtilisation du modèle dynamique de végétation CARAIB pour simuler les rendements en Belgique : validation et projections à l'horizon 2035
Jacquemin, Ingrid ULiege; Berckmans, Julie; Henrot, Alexandra-Jane ULiege et al

Poster (2019, September)

Le modèle CARAIB (CARbon Assimilation In the Biosphere) est un modèle dynamique de végétation initialement développé pour étudier le comportement de la végétation naturelle, tant son rôle dans le cycle ... [more ▼]

Le modèle CARAIB (CARbon Assimilation In the Biosphere) est un modèle dynamique de végétation initialement développé pour étudier le comportement de la végétation naturelle, tant son rôle dans le cycle global du carbone que sa réponse aux changements de climat et de sol. Afin de pouvoir répondre à de nouveaux challenges (comme l’étude des rétroactions climat-végétation ou encore de l’évaluation des services écosystémiques), le modèle a été doté d’un nouveau module lui permettant de couvrir l’ensemble de la végétation, naturelle et celle dite « managée » comme les cultures. Par conséquent, CARAIB devient un outil intéressant pour l’analyse du risque encouru par la végétation, et tout particulièrement pour les cultures agricoles, dans un contexte de changement climatique. Mais avant toute chose, il convient de procéder à la validation du module culture. Afin d’évaluer la variation temporelle, nous avons confronté les sorties du modèle avec des données de terrain venant des sites de mesure des flux d’eddy-covariance du réseau Fluxnet. Nous avons notamment comparé les flux de carbone (la GPP pour « Gross Primary Production » et la NEE pour « Net Ecosystem Exchange ») et l’évapotranspiration simulés par le modèle, avec les observations venant de plusieurs sites, dont celui de Lonzée en Belgique et de Grignon en France. A eux seuls, ces deux sites permettent de couvrir les 6 cultures proposées par CARAIB, à savoir le froment et l’orge d’hiver, le maïs, les pommes de terre, les betteraves sucrières et le colza. Pour l’évaluation de la variabilité spatiale, nous avons procédé à des simulations sur l’ensemble de la Belgique, où le modèle a été forcé par les sorties du modèle régional ALARO de l’Institut Royal Météorologique pour le passé récent, à 4km de résolution. Finalement, nous avons forcé le modèle CARAIB, toujours avec les sorties du modèle ALARO à 4km, mais cette fois pour les scénarios futurs RCP4.5 et 8.5, pour l’horizon 2035. Au-delà de l’effet fertilisant du CO2 atmosphérique croissant qui impacte positivement les rendements, nous pouvons d’ores et déjà mettre en évidence une variabilité interannuelle plus importante pour l’ensemble des cultures à l’exception du maïs. [less ▲]

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See detailEstimation of present and future soil water balance and its impacts on wheat yields in African regions north of the equator using a dynamic vegetation model
Dury, Marie ULiege; Jacquemin, Ingrid ULiege; Henrot, Alexandra-Jane ULiege et al

in Geo-Eco-Trop: Revue Internationale de Géologie, de Géographie et d'Écologie Tropicales (2019), 43(3), 317-326

Climate warming and growing population are hot topics for agriculture and food security in Africa. In this context, the CARAIB dynamic vegetation model is run over Africa north of the equator to project ... [more ▼]

Climate warming and growing population are hot topics for agriculture and food security in Africa. In this context, the CARAIB dynamic vegetation model is run over Africa north of the equator to project future soil water balance and its impact on yields of wheat (a culture whose distribution is projected to increase rapidly given the huge demand on the continent). Forced with different climate and CO2 concentration scenarios, the uncertainties in yield projections are large. Assuming CO2 effects, model results indicate a potential stimulation of wheat growth overcoming negative climate change impacts with yield gains around 20 % in sub-Saharan regions above the equator (up to 40 % in Eastern Africa). Without CO2 fertilization, negative yield anomalies are projected under future climate trends (warming and drying). Since the agronomic adaptation of African agriculture is an important source of uncertainties, the yield-increasing effect of irrigation is also analysed. [less ▲]

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See detailISIMIP2a Simulation Data from Biomes Sector (V. 1.1)
Reyer, Christopher; Asrar, Gassem; Betts, Richard et al

Textual, factual or bibliographical database (2019)

This database collects the results from the ISIMIP2a simulation experiments carried out with from 8 global vegetation models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to ... [more ▼]

This database collects the results from the ISIMIP2a simulation experiments carried out with from 8 global vegetation models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). [less ▲]

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See detailTree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale
Bugmann, H.; Seidl, R.; Hartig, F. et al

in Ecosphere (2019), 10(2),

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration ... [more ▼]

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics. © 2019 The Authors. [less ▲]

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See detailClassifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R. et al

in Agricultural Systems (2018), 159

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models ... [more ▼]

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities. [less ▲]

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See detailLes changements climatiques et leurs impacts sur l'agriculture en Belgique : apport de la modélisation
Jacquemin, Ingrid ULiege

Conference given outside the academic context (2017)

Detailed reference viewed: 31 (4 ULiège)
See detailHigh-resolution simulations of natural and agricultural ecosystems over Belgium with the CARAIB Dynamic Vegetation Model
Jacquemin, Ingrid ULiege; Dury, Marie ULiege; Henrot, Alexandra-Jane ULiege et al

Conference (2017, November 17)

CARAIB (for CARbon Assimilation In the Biosphere) is a state-of-the-art dynamic vegetation model (DVM), initially designed to study the role of the vegetation in the global carbon cycle and the vegetation ... [more ▼]

CARAIB (for CARbon Assimilation In the Biosphere) is a state-of-the-art dynamic vegetation model (DVM), initially designed to study the role of the vegetation in the global carbon cycle and the vegetation behavior as a function of climate and soil. Motivated by the requirements of ecosystem management and land use planning studies, CARAIB was recently improved so as to deal with both natural and agricultural ecosystems and at a high resolution of 1km over Belgium. A new module, for crops and meadows, was added in the model, which deals with the specific processes (phenology) and management (sowing, harvesting,…) of these ecosystems. The spatial and temporal validation was carried out with different data sources : agricultural statistics, eddy-covariance site, field measurements,… The addition of the crop module has led to the improvement of the surface scheme, from now on including dynamic land use and land cover information. As well as describes the evolution of physical and biological processes, CARAIB has become an interesting tool to assess the sustainability under climate change of the ecological systems, in particular by the approach of the ecosystem goods and services. Indeed, if some model outputs can be directly read as quantitative indicators of ecosystem services (e.g. carbon sequestration), we have translated some of them to get, e.g., the crop yield (from net primary productivity) or an estimation of the soil erosion for simulation at the parcel level (from runoff and parcels characteristics). But whether an ecosystem services or land use planning studies, the crucial point for CARAIB is the landscape dynamics, which is not considered by the model, in the absence of anthropogenic, economic and societal factors in the system. In order to overcome this lack, CARAIB is now coupled with an agent-based model (ABM), to compose a land surface dynamics (LSD) module. The productivity and growth of natural and managed vegetation is given by the DVM to the ABM, which determines the shifts in land use and land cover. The LSD module is able to represent the mutual interactions between ecological and socio-economic systems and thus, to assess the sustainability of the different climate and socio-economic scenarios tested. [less ▲]

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See detailHow do individual species and Plant Functional Type responses to environmental change differ in Dynamic Vegetation Models? - A forest stand analysis
Dury, Marie ULiege; Henrot, Alexandra-Jane ULiege; Jacquemin, Ingrid ULiege et al

Poster (2017, October 09)

Originally dedicated to simulate vegetation at the global scale, dynamic (global) vegetation models (D(G)VMs) classify vegetation into Plant Functional Types (PFTs) to represent the largest set of plant ... [more ▼]

Originally dedicated to simulate vegetation at the global scale, dynamic (global) vegetation models (D(G)VMs) classify vegetation into Plant Functional Types (PFTs) to represent the largest set of plant species. PFTs are clusters of species that share common morphological and physiological traits. However, PFT classification becomes surely too coarse to reflect the large diversity in plant species responses to climate and environmental changes, a critical point for biodiversity questions. Thus, some efforts focus now on applying DVMs at the species level refining the definition of morphophysiological parameters from initial PFT traits to specific traits collected or found in trait databases. What are the effects of using species-specific parameters? Do dynamic vegetation models better reproduce historical forest growth and mortality observed in monitored stands? How will individual species respond to future climate compared to PFTs? To study these questions, we used two process-based dynamic vegetation models CARAIB (Dury et al., 2011) as well as LPJ-GUESS (Smith et al., 2001), and compared their outputs. CARAIB has been previously adapted to model a set of 40 European tree species, differentiated by their specific traits, proper climatic requirements and tolerances. LPJ-GUESS features a detailed representation of climate sensitive tree species dynamics, resource competition and canopy structure (Hickler et al., 2012). The respective tree species are distinguished by taking differences in phenology, allometry and bioclimatic limits into account. Model simulations were performed in accordance with the experimental protocol of the COST Action PROFOUND (“Towards robust projections of European forests under climate change”) for several European forest stands selected in the project. We particularly focused on Fagus sylvatica stand in Sorø (Denmark), Picea abies stand in Solling (Germany) and Pinus sylvestris (and Picea abies) stands in Hyytiala (Finland). The experiments include site-specific soil characteristics, management practices (planting, thinning and harvest) and climate conditions. For the historical period (from planting year to 2014), besides local observations, simulations were also run with the original (0.5-degree spatial resolution) and locally bias-corrected (LBC) ISIMIP2B outputs of global climate models for testing the reliance of DVM results to the spatial resolution of climatic inputs. For the future period (2005-2100), vegetation models were driven by the ISIMIP2B climates under different Representative Concentration Pathways. The simulations at the PFT level were performed following the same protocol replacing the locally present species by their representative PFTs. The carbon and water fluxes obtained from the different experiments carried out with the two DVMs were compared with eddy-covariance data from each site. [less ▲]

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See detailLand surface interactions modeling (Agent-Based-Model - Dynamic Vegetation Model) over Belgium: current state and crop yield assessment for future (at the Belgian and European scales)
Jacquemin, Ingrid ULiege; Beckers, Veronique; Henrot, Alexandra-Jane ULiege et al

Poster (2017, May 23)

Agriculture in Europe is under substantial pressure. Farmers need to adapt to an ever-increasing global market, resulting in increasing competition and a high dependency on global food prices. Furthermore ... [more ▼]

Agriculture in Europe is under substantial pressure. Farmers need to adapt to an ever-increasing global market, resulting in increasing competition and a high dependency on global food prices. Furthermore, they have to deal with an increasing urbanization pressure and to comply with increasingly strict environmental rules and policies, sometimes requiring heavy investments. Combined to potential impacts of climate changes on ecosystems functions and structures, these factors could lead to a change in land use structure. In the framework of the MASC project ("Modelling and Assessing Surface Change impacts on Belgium and Western European climate"), we aim at providing a better understanding of these factors, with the final objective of improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models. We propose to combine an agent-base model (ABM) and a dynamic vegetation model (DVM), CARAIB (“CARbon Assimilation In the Biosphere”). The ABM models the farmers as individual agents using a certain number of parcels. They decide on what to plant based on market prices, subsidies, crop rotations, personal preferences and the expected yield, which will be given by CARAIB. CARAIB will be forced over Belgium with the outputs of the regional climate model ALARO (4 km resolution) for the recent past and for the most common crops. As a first attempt to assess the impact of the climate change on crops yields over Europe, CARAIB will be driven with the outputs of several regional climate models (RCMs), from EURO-CORDEX, nested in CMIP5 general circulation model projections: ALADIN53 (Météo-France/CNRM), RACMO22E (KNMI), RCA4 (SMHI) and REMO2009 (MPI-CSC) RCMs (0.11-degree, ≈12 km) [less ▲]

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See detailEstimation des bilans hydriques présent et futur ainsi que de leur impact sur les rendements agricoles en Afrique du Nord et de l'Ouest à l'aide d'un modèle de végétation dynamique
Dury, Marie ULiege; Jacquemin, Ingrid ULiege; Henrot, Alexandra-Jane ULiege et al

Conference (2017, March 29)

Climate change is affecting agriculture all over the world with dramatic consequences in developing countries already affected by limited water resources. Unfortunately, the lack of a consistent coverage ... [more ▼]

Climate change is affecting agriculture all over the world with dramatic consequences in developing countries already affected by limited water resources. Unfortunately, the lack of a consistent coverage of hydrological data (precipitation, soil water content, etc.), especially in those regions, makes difficult a good knowledge of the current conditions and, thus, prevents any planning for the future. Therefore, ecosystem process-based models are interesting tools to represent the water balance of terrestrial ecosystems and provide an overview of the current and future hydrological conditions. Here, we use the CARAIB (CARbon Assimilation In the Biosphere; Dury et al., 2011) dynamic vegetation model (DVM) to evaluate current and future soil water availability and assess potential impacts of its reduction on crop yields. CARAIB is a state-of-the-art DVM with various modules dealing with (i) soil hydrology, (ii) photosynthesis/stomatal regulation, (iii) carbon allocation and biomass growth, (iv) litter/soil carbon dynamics, (v) vegetation cover dynamics, (vi) seed dispersal, and (vii) vegetation fires. Climate and atmospheric CO2 are the primary inputs. Within the VOTES project (Fontaine et al., 2014) and the GGCMI intercomparison (Global Gridded Crop Model Intercomparison), the model has been improved to include crops and meadows (Minet et al., 2015), and some modules have been written to translate model outputs into quantitative indicators of ecosystem services (e.g., to evaluate crop yield from net primary productivity, to calculate soil erosion from runoff and slope or to apply irrigation water). In this contribution, we focus on four crop species (maize, rice, soy and spring wheat) over North and West Africa. We use historical climate and future projections from the ISI-MIP2 model intercomparison (Inter-Sectoral Impact Model Intercomparison Project). Historical climate is PGMFD v.2.1 (NCEP/NCAR Reanalysis 1) 1901-2012 time series. Future change in temperature and precipitation are produced over the 21st century by CMIP5 general circulation model simulations that were bias-corrected in the framework of the ISI-MIP2 project. Simulations of the vegetation model are performed at 0.5° spatial resolution under two water scenarios: a water-limited (precipitation only) and a full irrigation (water supplied to reach field capacity). In the model, the soil water available for plant (ASW) is expressed as the fraction between the actual soil water and the water available for plant growth at field capacity (FC): ASW = (SW-WP)/(FC-WP) with SW being the actual soil water and WP the wilting point. Under the first scenario, the soil water deficit and its impacts on crop production are evaluated. The second scenario allows an evaluation of the amount of irrigation water necessary to fulfill crop requirements. This kind of study can help in the identification of agricultural areas currently vulnerable or which might be exposed in the future. It can also be useful to optimise water resource management in African countries. [less ▲]

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See detailPhotosynthetic productivity and its efficiencies in ISIMIP2a biome models: benchmarking for impact assessment studies
Ito, Akihiko; Nishina, Kazuya; Reyer, Christopher P. O. et al

in Environmental Research Letters (2017), 12(8), 085001

Simulating vegetation photosynthetic productivity (or gross primary production, GPP) is a critical feature of the biome models used for impact assessments of climate change. We conducted a benchmarking of ... [more ▼]

Simulating vegetation photosynthetic productivity (or gross primary production, GPP) is a critical feature of the biome models used for impact assessments of climate change. We conducted a benchmarking of global GPP simulated by eight biome models participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a) with four meteorological forcing datasets (30 simulations), using independent GPP estimates and recent satellite data of solar-induced chlorophyll fluorescence as a proxy of GPP. The simulated global terrestrial GPP ranged from 98 to 141 Pg C yr −1 (1981–2000 mean); considerable inter-model and inter-data differences were found. Major features of spatial distribution and seasonal change of GPP were captured by each model, showing good agreement with the benchmarking data. All simulations showed incremental trends of annual GPP, seasonal-cycle amplitude, radiation-use efficiency, and water-use efficiency, mainly caused by the CO 2 fertilization effect. The incremental slopes were higher than those obtained by remote sensing studies, but comparable with those by recent atmospheric observation. Apparent differences were found in the relationship between GPP and incoming solar radiation, for which forcing data differed considerably. The simulated GPP trends co-varied with a vegetation structural parameter, leaf area index, at model-dependent strengths, implying the importance of constraining canopy properties. In terms of extreme events, GPP anomalies associated with a historical El Niño event and large volcanic eruption were not consistently simulated in the model experiments due to deficiencies in both forcing data and parameterized environmental responsiveness. Although the benchmarking demonstrated the overall advancement of contemporary biome models, further refinements are required, for example, for solar radiation data and vegetation canopy schemes. [less ▲]

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See detailISIMIP2a Simulation Data from Biomes Sector
Reyer, Christopher; Asrar, Gassem; Betts, Richard et al

Textual, factual or bibliographical database (2017)

This database gathers the results from the ISIMIP2a simulation experiments carried out with from 8 global vegetation models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to ... [more ▼]

This database gathers the results from the ISIMIP2a simulation experiments carried out with from 8 global vegetation models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). [less ▲]

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See detailUsing a dynamic vegetation model for future projections of crop yields: simulations from the plot scale to the Belgian and European scales
Jacquemin, Ingrid ULiege; Dury, Marie ULiege; Henrot, Alexandra-Jane ULiege et al

Conference (2016, September 29)

Dynamic vegetation models (DVM), such as CARAIB (“CARbon Assimilation In the Biosphere”) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil with the ... [more ▼]

Dynamic vegetation models (DVM), such as CARAIB (“CARbon Assimilation In the Biosphere”) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil with the aim of studying the role of vegetation in the carbon cycle. But their characteristics allow numerous other applications and improvements, such as the development of a crop module. This module can be validated at the plot scale, with the use of eddy-covariance data from agricultural sites in the FLUXNET network. The carbon fluxes (e.g., net ecosystem exchange (NEE), gross primary productivity (GPP)) and the evapotranspiration (ET) simulated with the CARAIB model are compared with the fluxes measured at several sites, in order to cover a maximum number of crop types (winter wheat/barley, sugar beets, potatoes, rapeseed,…) and to evaluate the model for different European regions (Belgium, France, Germany,…). The aim of this validation is to assess the model ability to reproduce the seasonal and inter-annual variability of carbon fluxes. In order to assess the spatial variability of the model, CARAIB will be applied over Belgium and forced with the outputs the regional climate model ALARO (4 km resolution), for the recent past and the decennial projections. To reach the larger scale, we also aim to assess crops yields over Europe and to quantify the uncertainties in the climatic projections. CARAIB will be driven with the outputs of different regional climatic models (RCMs), nested in CMIP5 GCM projections for the EURO-CORDEX project: ALADIN53 (Météo-France/CNRM), RACMO22E (KNMI), RCA4 (SMHI) and REMO2009 (MPI-CSC) RCMs. These climatic projections are at a high spatial resolution (0.11-degree, ≈12 km). The model will be set up for the most common crops in Europe and for simulations tests with marginal and/or new crops. Finally, this simulation ensemble will be used to highlight potential changes in the most productive areas of Europe. [less ▲]

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See detailAssessing the impact of climate change on terrestrial plants in Europe using a Dynamic Vegetation Model driven by EURO-CORDEX projections
Dury, Marie ULiege; Hambuckers, Alain ULiege; Henrot, Alexandra-Jane ULiege et al

Poster (2016, September 26)

While the combination of warmer and drier mean climatic conditions can have severe impacts on ecosystems, extreme events like droughts or heat waves that break the gradual climate change can have more ... [more ▼]

While the combination of warmer and drier mean climatic conditions can have severe impacts on ecosystems, extreme events like droughts or heat waves that break the gradual climate change can have more long-term consequences on ecosystem composition, functioning and carbon storage. Hence, it is essential to assess the changes in climate variability and the changes in frequency of extreme events projected for the future. Here, the process-based dynamic vegetation model CARAIB DVM was used to evaluate and analyse how future climate and extreme events will affect European terrestrial plants. To quantify the uncertainties in climatic projections and their potential impacts on ecosystems, the vegetation model was driven with the outputs of different regional climatic models, nested in CMIP5 GCM projections for the EURO-CORDEX project: ALADIN53 (Météo-France/CNRM), RACMO22E (KNMI), RCA4 (SMHI) and REMO2009 (MPI-CSC) RCMs. These daily climatic scenarios are at a high spatial resolution (0.11°, ≈ 12 km). CARAIB simulations were performed across Europe over the historical period 1971-2005 and the future period 2006-2100 under RCP4.5 and RCP8.5 emission scenarios. We simulated a set of 99 individual species (47 herbs, 12 shrubs and 40 trees) representing the major European ecosystem flora. First, we analysed the climatic variability simulated by the climatic models over the historical period and compared it with the observed climatic variability. Then, we evaluated change in climatic variability and extreme events projected by the climatic models for the end of the century. Finally, we assessed the change in species productivity and abundance. We evaluated the severity of projected productivity change for the period 2070-2099 relative to their current productivity variability (period 1970-1999). Mean changes were considered severe if they exceed observed variability. The projections of potential shifts in species distributions are directly dedicated to current forest management. [less ▲]

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See detailSensitivity of the regional climate model ALARO-0 to land surface changes
Berckmans, Julie; Henrot, Alexandra-Jane ULiege; Jacquemin, Ingrid ULiege et al

Poster (2016, September)

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See detailResponse to droughts and heat waves of the productivity of natural and agricultural ecosystems in Europe within ISI-MIP2 historical simulations
François, Louis ULiege; Henrot, Alexandra-Jane ULiege; Dury, Marie ULiege et al

Conference (2016, June 23)

According to the projections of climate models, extreme events such as droughts and heat waves are expected to become more frequent and more severe in the future. Such events are known to severely impact ... [more ▼]

According to the projections of climate models, extreme events such as droughts and heat waves are expected to become more frequent and more severe in the future. Such events are known to severely impact the productivity of both natural and agricultural ecosystems, and hence to affect ecosystem services such as crop yield and ecosystem carbon sequestration potential. Dynamic vegetation models are conventional tools to evaluate the productivity and carbon sequestration of ecosystems and their response to climate change. However, how far are these models able to correctly represent the sensitivity of ecosystems to droughts and heat waves? How do the responses of natural and agricultural ecosystems compare to each other, in terms of drought-induced changes in productivity and carbon sequestration? In this contribution, we use ISI-MIP2 model historical simulations from the biome sector. Eight dynamic vegetation models have participated in the biome sector intercomparison of ISI-MIP2: CARAIB, DLEM, JULES, LPJ-GUESS, LPJml, ORCHIDEE, VEGAS and VISIT. We focus the analysis on well-marked droughts or heat waves that occured in Europe after 1970, such as the 1976, 2003 and 2010 events. For most recent studied events, the model results are compared to the response observed at several eddy covariance sites in Europe, and, at a lager scale, to the drops in crop productivities reported in national statistics or to the drought impacts retrieved from satellite data (Terra MODIS instrument). [less ▲]

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