Bounded version vectors

Version vectors play a central role in update tracking under optimistic distributed systems, allowing the detection of obsolete or inconsistent versions of replicated data. Version vectors do not have a bounded representation; they are based on integer counters that grow indefinitely as updates occur. Existing approaches to this problem are scarce; the mechanisms proposed are either unbounded or operate only under specific settings. This paper examines version vectors as a mechanism for data causality tracking and clarifies their role with respect to vector clocks. Then, it introduces bounded stamps and proves them to be a correct alternative to integer counters in version vectors. The resulting mechanism, bounded version vectors, represents the first bounded solution to data causality tracking between replicas subject to local updates and pairwise symmetrical synchronization.FCT project POSI/ICHS/44304/2002, FCT under grant BSAB/390/2003

Sensitivity of simulated soil water content, evapotranspiration, gross primary production and biomass to climate change factors in Euro-Mediterranean grasslands

Grassland models often yield more uncertain outputs than arable crop models due to more complex interactions and the largely undocumented sensitivity of grassland models to environmental factors. The aim of the present study was to assess the impact of single-factor changes in temperature, precipitation, and atmospheric [CO2] on simulated soil water content (SWC), actual evapotranspiration (ET), gross primary production (GPP) and yield biomass, and also to link the sensitivity analysis with experimental results. We employed an unprecedented multi-model framework consisting of seven grassland models at nine sites with different environmental characteristics in Europe and Israel, with two management options at three sites. For warming/cooling and wetting/drying, models showed general consistency in the direction of SWC and ET changes, but less agreement regarding GPP and biomass changes. The simulated responses consistently revealed an overall positive effect of CO2 enrichment on GPP and biomass, while the direction of change differed for SWC and ET. Comparing with single-factor experimental manipulations, SWC simulations slightly underestimated the observed effect of warming, while the overall mean model sensitivity for biomass (+7.5%) closely matched the mean response observed with 1–2 °C warming (+6.6%). The models exhibited lower sensitivity of SWC to wetting or drying compared to the experiments. The overall mean sensitivity of biomass to drying was -4.3%, contrasting with the mean experimental effect size of -9.6%, which proved to be more realistic than the mean wetting effect (+3.2%, against +38.9% in the field trials). The simulated sensitivity of SWC to CO2 enrichment was markedly underestimated, while the biomass response (+12.0%) closely matched the observations (+17.5%). Although the multi-model averaging did not manifestly improve the realism of the simulations, it ensured a realistic response in the direction of change to varying conditions. The results suggest a paradigm shift in grassland modelling meaning that the usual practice of model optimisation/validation needs to be complemented by a sensitivity analysis following the approach presented. The results also highlight the importance of model improvements, especially in terms of soil hydrology representation, a key environmental driver of grassland functioning

Parameter identification of the STICS crop model, using an accelerated formal MCMC approach

This study presents a Bayesian approach for the parameters’ identification of the STICS crop model based on the recently developed Differential Evolution Adaptive Metropolis (DREAM) algorithm. The posterior distributions of nine specific crop parameters of the STICS model were sampled with the aim to improve the growth simulations of a winter wheat (Triticum aestivum L.) culture. The results obtained with the DREAM algorithm were initially compared to those obtained with a Nelder-Mead Simplex algorithm embedded within the OptimiSTICS package. Then, three types of likelihood functions implemented within the DREAM algorithm were compared, namely the standard least square, the weighted least square, and a transformed likelihood function that makes explicit use of the coefficient of variation (CV). The results showed that the proposed CV likelihood function allowed taking into account both noise on measurements and heteroscedasticity which are regularly encountered in crop modellingPeer reviewe

An ensemble of projections of wheat adaptation to climate change in europe analyzed with impact response surfaces

IRS2 TEAM:Alfredo Rodríguez(1), Ignacio J. Lorite(3), Fulu Tao(4), Nina Pirttioja(5), Stefan Fronzek(5), Taru Palosuo(4), Timothy R. Carter(5), Marco Bindi(2), Jukka G Höhn(4), Kurt Christian Kersebaum(6), Miroslav Trnka(7,8),Holger Hoffmann(9), Piotr Baranowski(10), Samuel Buis(11), Davide Cammarano(12), Yi Chen(13,4), Paola Deligios(14), Petr Hlavinka(7,8), Frantisek Jurecka(7,8), Jaromir Krzyszczak(10), Marcos Lana(6), Julien Minet(15), Manuel Montesino(16), Claas Nendel(6), John Porter(16), Jaime Recio(1), Françoise Ruget(11), Alberto Sanz(1), Zacharias Steinmetz(17,18), Pierre Stratonovitch(19), Iwan Supit(20), Domenico Ventrella(21), Allard de Wit(20) and Reimund P. Rötter(4).An ensemble of projections of wheat adaptation to climate change in europe analyzed with impact response surfaces . International Crop Modelling Symposiu

Probabilistic assessment of adaptation options from an ensemble of crop models: a case study in the Mediterranean

Effective adaptation of agricultural systems to climate change has to: Consider local specificities; provide sound and practical information and deal with the uncertainty We present a methodology for assessing different aspects of adaptation. Our study case is adaptation of winter wheat in the Mediterranean

Applying adaptation response surfaces for managing wheat under perturbed climate and elevated CO2 in a Mediterranean environment

This study developed Adaptation Response Surfaces and applied them to a study case in North East Spain on winter crops adaptation, using rainfed winter wheat as reference crop.  Crop responses to perturbed temperature, precipitation and CO2 were simulated by an ensemble of crop models. A set of combined changes on cultivars (on vernalisation requirements and phenology) and management (on sowing date and irrigation) were considered as adaptation options and simulated by the crop model ensemble. The discussion focused on two main issues: 1) the recommended adaptation options for different soil types and perturbation levels, and 2) the need of applying our current knowledge (AOCK) when building a crop model ensemble. The study has been published Agricultural Systems (Available online 25 January 2017, https://doi.org/10.1016/j.agsy.2017.01.009), and the  text below consists on extracts from that paper

Relations entre matière sèche à la floraison et rendement en grains chez le maïs : importance du rayonnement disponible par plante

International audienc

Présentation d'une méthode simple d'estimation de la contribution des réserves pour le remplissage des grains chez le maïs

L'intervention de réserves dans le remplissage des grains, quoique connue, est généralement mise en évidence à partir de méthodes lourdes, qui conduisent à diminuer la fréquence des observations ou le nombre de traitements. Or, la datation et la quantification des interventions de réserves, indispensables pour une bonne modélisation de la gestion des réserves, nécessitent des mesures nombreuses. Le présent travail propose une estimation des réserves utilisées pendant le remplissage des grains, à partir de la différence entre croissance des grains et croissance de la plante entière. Cette dernière est estimée grâce au rayonnement intercepté par la culture. L'exemple traité ici est celui du maïs, mais pourrait s'adapter à toute autre culture où un organe (grains ou tubercules) est rempli de façon régulière, avec appel aux réserves temporaires en cas d'insuffisance des fournitures directes d'assimilats.An easy method to quantify reserve use in corn grain filling. The use of storage carbohydrates for grain filling has been known for a long time. However, its quantification by carbohydrate concentration prevents frequent measurements from being made. Use of reserves is measured from the difference between grain growth and whole plant growth. As respiratory losses are very small compared to dry matter decrease, they are not taken into account. Figure 1 shows the evolution of whole plant and grain dry matter during grain filling. For each observation period, reserve use between 2 measurement dates is negatively correlated with whole plant growth (fig 2). Reserve use increases with time for all genotypes (fig 3). We propose an easy method to estimate reserve use based on the difference between actual grain growth and maximal dry matter production (estimated from crop light interception). The results are in good agreement with the measurements except for points corresponding to early stages of grain filling (fig 4). These points correspond to high conversion efficiency (fig 5) at the beginning of grain filling (as has already been reported in the literature). This method allows the frequent quantification of reserve use from grain growth, leaf area index and global radiation measurements. It can be used for maize or other plants for which the storage organ (grain or tuber) is the only one to grow towards the end of the life cycle