References of "Minet, Julien"
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See detailCrowdsourcing for agricultural applications: A review of uses and opportunities for a farmsourcing approach
Minet, Julien ULiege; Curnel, Yannick; Gobin, Anne et al

in Computers & Electronics in Agriculture (2017), 142, Part A

Abstract Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper ... [more ▼]

Abstract Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper, we reviewed crowdsourcing initiatives in agricultural science and farming activities and further discussed the particular characteristics of this approach in the field of agriculture. On-going crowdsourcing initiatives in agriculture were analysed and categorised according to their crowdsourcing component. We identified eight types of agricultural data and information that can be generated from crowdsourcing initiatives. Subsequently we described existing methods of quality control of the crowdsourced data. We analysed the profiles of potential contributors in crowdsourcing initiatives in agriculture, suggested ways for increasing farmers’ participation, and discussed the on-going initiatives in the light of their target beneficiaries. While crowdsourcing is reported to be an efficient way of collecting observations relevant to environmental monitoring and contributing to science in general, we pointed out that crowdsourcing applications in agriculture may be hampered by privacy issues and other barriers to participation. Close connections with the farming sector, including extension services and farm advisory companies, could leverage the potential of crowdsourcing for both agricultural research and farming applications. This paper coins the term of farmsourcing as a professional crowdsourcing strategy in farming activities and provides a source of recommendations and inspirations for future collaborative actions in agricultural crowdsourcing. [less ▲]

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See detailOpen Geodata
Minet, Julien ULiege

Scientific conference (2017, October 10)

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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 (2017)

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 detailAdaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment
Ruiz-Ramos, M.; Ferrise, R.; Rodríguez, A. et al

in Agricultural Systems (2017)

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See detailMulti-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance
Sándor, R.; Barcza, Z.; Acutis, M. et al

in European Journal of Agronomy (2016)

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See detailModeling heat stress under different environmental conditions
Carabano, Maria-Jesus; Logar, Betka; Bormann, Jeanne et al

in Journal of Dairy Science (2016), 99(5), 37983814

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at ... [more ▼]

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across three European regions differing in climate and production systems to detect differences and similarities that can be used to optimize heat stress (HS) effect modeling. Milk, fat and protein test day data from official milk recording for years 1999 to 2010 in four Holstein populations located in the Walloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO) and Southern Spain (SPA) were merged with temperature and humidity data provided by the state meteorological agencies. After merging, the number of test day records/cows per trait ranged from 686,726/49,655 in SLO to 1,982,047/136,746 in BEL. Values for the daily average and maximum temperature and humidity index (THIavg and THImax) ranges for THIavg/THImax were largest in SLO (22-74/28-84) in SLO and shortest in SPA (39-76/46-83). Change point techniques were used to determine comfort thresholds, which differed across traits and climatic regions. Milk yield showed an inverted U shaped pattern of response across the THI scale with a HS threshold around 73 THImax units. For fat and protein, thresholds were lower than for milk yield and were shifted around 6 THI units towards larger values in SPA compared with the other countries. Fat showed lower HS thresholds than protein traits in all countries. The traditional broken line model was compared to quadratic and cubic fits of the pattern of response in production to increasing heat loads. A cubic polynomial model allowing for individual variation in patterns of response and THIavg as heat load measure showed the best statistical features. Higher/lower producing animals showed less/more persistent production (quantity and quality) across the THI scale. The estimated correlations between comfort and THIavg values of 70 (which represents the upper end of the THIavg scale in BEL-LUX) were lower for BEL-LUX (0.70 - 0.80) than for SPA (0.83 - 0.85). Overall, animals producing in the more temperate climates and semi-extensive grazing systems of BEL and LUX showed HS at lower heat loads and more re-ranking across the THI scale than animals producing in the warmer climate and intensive indoor system of SPA. [less ▲]

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See detailModeling heat stress under different environmental conditions
Carabano, Maria-Jesus; Logar, Betka; Bormann, Jeanne et al

in Journal of Dairy Science (2016), 99(5), 37983814

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at ... [more ▼]

Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across three European regions differing in climate and production systems to detect differences and similarities that can be used to optimize heat stress (HS) effect modeling. Milk, fat and protein test day data from official milk recording for years 1999 to 2010 in four Holstein populations located in the Walloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO) and Southern Spain (SPA) were merged with temperature and humidity data provided by the state meteorological agencies. After merging, the number of test day records/cows per trait ranged from 686,726/49,655 in SLO to 1,982,047/136,746 in BEL. Values for the daily average and maximum temperature and humidity index (THIavg and THImax) ranges for THIavg/THImax were largest in SLO (22-74/28-84) in SLO and shortest in SPA (39-76/46-83). Change point techniques were used to determine comfort thresholds, which differed across traits and climatic regions. Milk yield showed an inverted U shaped pattern of response across the THI scale with a HS threshold around 73 THImax units. For fat and protein, thresholds were lower than for milk yield and were shifted around 6 THI units towards larger values in SPA compared with the other countries. Fat showed lower HS thresholds than protein traits in all countries. The traditional broken line model was compared to quadratic and cubic fits of the pattern of response in production to increasing heat loads. A cubic polynomial model allowing for individual variation in patterns of response and THIavg as heat load measure showed the best statistical features. Higher/lower producing animals showed less/more persistent production (quantity and quality) across the THI scale. The estimated correlations between comfort and THIavg values of 70 (which represents the upper end of the THIavg scale in BEL-LUX) were lower for BEL-LUX (0.70 - 0.80) than for SPA (0.83 - 0.85). Overall, animals producing in the more temperate climates and semi-extensive grazing systems of BEL and LUX showed HS at lower heat loads and more re-ranking across the THI scale than animals producing in the warmer climate and intensive indoor system of SPA. [less ▲]

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See detailHigh-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections
Jacquemin, Ingrid ULiege; Henrot, Alexandra-Jane ULiege; Beckers, Veronique et al

Poster (2016, April 21)

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric ... [more ▼]

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM. [less ▲]

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See detailClassifying simulated wheat yield responses to changes in temperature and precipitation across a european transect
Fronzek, S.; Pirttioja, N.; Carter, T. R. et al

Conference (2016, March)

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See detailAn ensemble of projections of wheat adaptation to climate change in europe analyzed with impact response surfaces
Ruiz-Ramos, M.; Ferrise, R.; Rodríguez, A. et al

Conference (2016, March)

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See detailKey challenges and priorities for modelling European grasslands under climate change
Kipling, Richard P.; Virkajärvi, Perttu; Breitsameter, Laura et al

in Science of the Total Environment (2016), 566–567

Abstract Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range ... [more ▼]

Abstract Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change. [less ▲]

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See detailL'agriculture devra s'adapter aux changements climatiques
Minet, Julien ULiege

Article for general public (2015)

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See detailThe potential of OpenStreetMap for land use/land cover mapping
Minet, Julien ULiege; Robert, Brieuc; Tychon, Bernard ULiege

Conference (2015, October 29)

Land use and land cover (LULC) maps are important tools for the management of the environment, in particular for the modelling of biogeochemical cycles and climate. LULC maps are typically produced using ... [more ▼]

Land use and land cover (LULC) maps are important tools for the management of the environment, in particular for the modelling of biogeochemical cycles and climate. LULC maps are typically produced using supervised classification of satellite images supported by expert knowledge. Nowadays, the advance of the crowdsourced project OpenStreetMap (OSM) offers an alternative to official LULC maps. In OSM, LULC is usually mapped by manual digitalisation of satellite imagery and/or by the import of existing databases. We explored the potential of OSM to contribute to the improvement of an existing LULC map, Corine Land Cover (CLC), by comparing forest cover in Southern Belgium and Luxembourg. We focused on three forest types that were common to the two databases: coniferous, deciduous and mixed forest. Confusion matrices showed that the two databases differed in terms of classes over about one quarter of the forest area. Moreover, 9.9% and 8.0% of the forest area in OSM and CLC, respectively, were unmapped as forest area compared to the other database. Compared to CLC data, small patches of forest areas are mapped in OSM data. This study is a first attempt to show the potential of a crowdsourced project, i.e., OSM, to contribute to an official geodatabase. While current drawbacks of OSM such as the lack of completeness may limit its application in some operational applications, we claim that its large accessibility and its potentially high reactiveness makes OSM a serious alternative to existing geodatabase. [less ▲]

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See detailMilk production, milking frequency and rumination time of grazing dairy cows milked by a mobile milking robot.
Lessire, Françoise ULiege; Hornick, Jean-Luc ULiege; Minet, Julien ULiege et al

in Conington, J; Klopcic, M; Lauridsen, C (Eds.) et al Book of abstracts of the 66th Annual meeting of the European Federation of animal science (2015, September 28)

In Europe, analysis of meteorological data shows that the average temperature has increased by ~1°C over the past hundred years (IPCC, 2013). Heat stress periods are thus expected to be more frequent even ... [more ▼]

In Europe, analysis of meteorological data shows that the average temperature has increased by ~1°C over the past hundred years (IPCC, 2013). Heat stress periods are thus expected to be more frequent even in temperate areas. The use of an automatic milking system (AMS) implies the need to stimulate cows’ traffic to the robot, especially with grazing cows. Describing how heat stress influenced cows’ traffic to the robot is the aim of this study. Grazing dairy cows milked by an automatic system (AMS) experienced heat stress (HS) periods, twice during the summer 2013 in July (J) and August (A). The daily temperature humidity index (THI) during these periods were higher than 75. Each HS period was compared with a “normal period”(N), presenting the same number of cows, similar lactation number, days in milk, distance to come back to the robot and an equal access to water. The first HS period of 5 days with a mean THI of 78.4 was chosen in J, and a second that lasted for 6 days in A with a THI value of 77.3. Heat stress periods were cut off with the same duration of days with no stress (N) and mean THI <70. Milk production, milkings and refusals to the robot during HS were compared with N periods. Milkings and refusals were significantly more numerous in HS periods in July (HS: 2.54 ± 0.11 vs N: 2.19 ± 0.08, 1.87 ± 0.20 vs 0.72 ± 0.16) but milk production dropped from 21.8 ±0.6 kg per cow and per day during N periods to 18.9 ± 0.8 kg in HS. In August, MY increased slightly during HS. This could be explained by less high ambient temperatures and decreased distance to walk inducing less energy expenditure. The increase in milkings and refusals to the robot during HS could be linked to water availability nearby the robot and confirmed previous findings (Lessire et al., 2014). [less ▲]

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See detailMonitoring surface water content using visible and short-wave infrared SPOT-5 data of wheat plots in irrigated semi-arid regions
Benabdelouahab, Tarik ULiege; Balaghi, Riad; Hadria, Rachid et al

in International Journal of Remote Sensing (2015), 36(15), 4018-4036

Irrigated agriculture is an important strategic sector in arid and semi-arid regions. Given the large spatial coverage of irrigated areas, operational tools based on satellite remote sensing can ... [more ▼]

Irrigated agriculture is an important strategic sector in arid and semi-arid regions. Given the large spatial coverage of irrigated areas, operational tools based on satellite remote sensing can contribute to their optimal management. The aim of this study was to evaluate the potential of two spectral indices, calculated from SPOT-5 high-resolution visible (HRV) data, to retrieve the surface water content values (from bare soil to completely covered soil) over wheat fields and detect irrigation supplies in an irrigated area. These indices are the normalized difference water index (NDWI) and the moisture stress index (MSI), covering the main growth stages of wheat. These indices were compared to corresponding in situ measurements of soil moisture and vegetation water content in 30 wheat fields in an irrigated area of Morocco, during the 2012–2013 and 2013–2014 cropping seasons. NDWI and MSI were highly correlated with in situ measurements at both the beginning of the growing season (sowing) and at full vegetation cover (grain filling). From sowing to grain filling, the best correlation (R2 = 0.86; p < 0.01) was found for the relationship between NDWI values and observed soil moisture values. These results were validated using a k-fold cross-validation methodology; they indicated that NDWI can be used to estimate and map surface water content changes at the main crop growth stages (from sowing to grain filling). NDWI is an operative index for monitoring irrigation, such as detecting irrigation supplies and mitigating wheat water stress at field and regional levels in semi-arid areas. [less ▲]

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See detailZonage phénoclimatique et caractérisation des parcours naturels du Sénégal avec les données de télédétection satellitaire
Diouf, Abdoul Aziz ULiege; Faye, G.; Minet, Julien ULiege et al

in XXVIIIème Colloque de l’Association Internationale de Climatologie, Liège 1-5 juillet 2015 (2015, July 02)

Les métriques phénologiques qui expriment certains événements du cycle de vie des plantes, tels que l'émergence, la croissance et la sénescence, principalement liées aux conditions météorologiques et au ... [more ▼]

Les métriques phénologiques qui expriment certains événements du cycle de vie des plantes, tels que l'émergence, la croissance et la sénescence, principalement liées aux conditions météorologiques et au climat, ont été utilisées afin : (i) de déterminer, à travers les parcours naturels du Sénégal, des entités "phénoclimatiques" homogènes ou phénorégions par classification non-supervisée des images de la série temporelle (1999-2013); (ii) d’analyser l’homogénéité des phénorégions en comparant l’évolution interannuelle de l’indice et des quantités de précipitation et (iii) de donner leurs principales caractéristiques biophysiques. Les résultats obtenus montrent que le domaine pastoral sénégalais peut être subdivisé en trois phénorégions à partir de la grande intégrale du NDVIS10 qui donne les entités spatiales les plus homogènes dans lesquelles les paramètres biophysiques comportent une variation latitudinale caractéristique du Sahel [less ▲]

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See detailLe réseau scientifique wallon Agriculture - changement climatique
Minet, Julien ULiege

Scientific conference (2015, May 20)

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See detailModelling carbon fluxes of forest and grassland ecosystems in Western Europe using the CARAIB dynamic vegetation model: evaluation against eddy covariance data.
Henrot, Alexandra-Jane ULiege; François, Louis ULiege; Dury, Marie ULiege et al

Poster (2015, April)

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface ... [more ▼]

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface and vegetation models at regional and global scale. In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), vegetation dynamics and carbon fluxes of forest and grassland ecosystems simulated by the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) are evaluated and validated by comparison of the model predictions with eddy covariance data. Here carbon fluxes (e.g. net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO)) and evapotranspiration (ET) simulated with the CARAIB model are compared with the fluxes measured at several eddy covariance flux tower sites in Belgium and Western Europe, chosen from the FLUXNET global network (http://fluxnet.ornl.gov/). CARAIB is forced either with surface atmospheric variables derived from the global CRU climatology, or with in situ meteorological data. Several tree (e.g. Pinus sylvestris, Fagus sylvatica, Picea abies) and grass species (e.g. Poaceae, Asteraceae) are simulated, depending on the species encountered on the studied sites. The aim of our work is to assess the model ability to reproduce the daily, seasonal and interannual variablility of carbon fluxes and the carbon dynamics of forest and grassland ecosystems in Belgium and Western Europe. [less ▲]

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