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AbstractExpected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed. Here we test our capacity to inform that “hindsight”, by linking a tested crop model (APSIM) with a skillful seasonal climate forecasting system, to answer “What is the value of the skill in seasonal climate forecasting, to inform crop designs?” Results showed that the GCM POAMA-2 was reliable and skillful, and that when linked with APSIM, optimum crop designs could be informed. We conclude that reliable and skillful GCMs that are easily interfaced with crop simulation models, can be used to inform optimum crop designs, increase farmers profits and reduce risks.

Establishing a direct link between climate change and fluctuations in animal populations through long-term monitoring is difficult given the paucity of baseline data. We hypothesized that social wasps are sensitive to climatic variations, and thus studied the impact of ENSO events on social wasp populations in French Guiana. We noted that during the 2000 La Niña year there was a 77.1% decrease in their nest abundance along ca. 5 km of forest edges, and that 70.5% of the species were no longer present. Two simultaneous 13-year surveys (1997-2009) confirmed the decrease in social wasps during La Niña years (2000 and 2006), while an increase occurred during the 2009 El Niño year. A 30-year weather survey showed that these phenomena corresponded to particularly high levels of rainfall, and that temperature, humidity and global solar radiation were correlated with rainfall. Using the Self-Organizing Map algorithm, we show that heavy rainfall during an entire rainy season has a negative impact on social wasps. Strong contrasts in rainfall between the dry season and the short rainy season exacerbate this effect. Social wasp populations never recovered to their pre-2000 levels. This is probably because these conditions occurred over four years; heavy rainfall during the major rainy seasons during four other years also had a detrimental effect. On the contrary, low levels of rainfall during the major rainy season in 2009 spurred an increase in social wasp populations. We conclude that recent climatic changes have likely resulted in fewer social wasp colonies because they have lowered the wasps' resistance to parasitoids and pathogens. These results imply that Neotropical social wasps can be regarded as bio-indicators because they highlight the impact of climatic changes not yet perceptible in plants and other animals.

Les changements d’affectation des sols (CAS) induits par les biocarburants et les émissions associées de gaz à effet de serre (GES) sont estimés par des modèles. Les estimations varient dans une large mesure dans les études disponibles et montrent une forte sensibilité à certaines hypothèses ainsi qu’à la valeur de paramètres clés. Elles suggèrent généralement que le biodiésel et l’éthanol, mais aussi que les biocarburants européens et américains, induisent des CAS et des émissions de GES différentes, mais il n’y a pas de consensus sur le type ni sur l’origine du biocarburant qui pourrait générer le moins d’impact sur ces critères. Nous montrons dans ce papier que l’hypothèse de modélisation Armington des échanges, couramment utilisée dans les modèles, contribue à expliquer ces différences. A partir de données observées et de l’utilisation du modèle d’équilibre partiel MATSIM-LUCA, nous montrons que les CAS découlant du développement des biocarburants sont hautement dépendant des hypothèses posées sur le commerce : l’approche dite du « marché mondial intégré », reposant sur l’hypothèse de produits homogènes, tend à gommer les différences dans les estimations de CAS induits par les biocarburants entre le biodiésel et l’éthanol et entre le biocarburant européen et américain, en comparaison à l’approche Armington qui considère que les produits sont différents selon leur origine et donc moins substituables. Available estimates of biofuel-induced land use change (LUC) and corresponding greenhouse gas (GHG) emissions vary on a wide range while estimations obtained from each model are highly sensitive to certain assumptions and key parameter values. Available studies often suggest that biodiesel and ethanol and/or EU and US biofuels would lead to different LUC and GHG emissions but they don’t agree on the type and/or the origin of the biofuel which would induce the least LUC and GHG emissions. In this paper we investigate the reasons behind this feature. We show that the Armington modeling of trade flows, which is currently used in models, contributes to this pattern. Using both observed data and the partial equilibrium model MATSIM-LUCA, we show that LUC stemming from the development of biofuels is highly dependent on assumptions made on trade: the Integrated World Market (IWM) approach, which relies on the homogenous product assumption, tends to erase differences in estimates of induced LUC from biodiesel and ethanol and from EU and US biofuels as compared to the Armington approach, that postulates that product are differentiated according to their origin and thus less substitutable.

Intensification of world trade is responsible for an increase in the number of alien species introductions. Human-mediated dispersal promotes not only introductions but also expansion of the species distribution via long-distance dispersal. Thus, understanding the role of anthropogenic pathways in the spread of invading species has become one of the most important challenges nowadays.We analysed the invasion pattern of the pinewood nematode in China based on invasion data from 1982 to 2005 and monitoring data on 7 locations over 15 years. Short distance spread mediated by long-horned beetles was estimated at 7.5 km per year. Infested sites located further away represented more than 90% of observations and the mean long distance spread was estimated at 111-339 km. Railways, river ports, and lakes had significant effects on the spread pattern. Human population density levels explained 87% of the variation in the invasion probability (P<0.05). Since 2001, the number of new records of the nematode was multiplied by a factor of 5 and the spread distance by a factor of 2. We combined a diffusion model to describe the short distance spread with a stochastic, individual based model to describe the long distance jumps. This combined model generated an error of only 13% when used to predict the presence of the nematode. Under two climate scenarios (stable climate or moderate warming), projections of the invasion probability suggest that this pest could expand its distribution 40-55% by 2025.This study provides evidence that human-induced dispersal plays a fundamental role in the spread of the pinewood nematode, and appropriate control measures should be taken to stop or slow its expansion. This model can be applied to Europe, where the nematode had been introduced later, and is currently expanding its distribution. Similar models could also be derived for other species that could be accidentally transported by humans.

By their autotrophic nature and their molecular richness, microalgae are serious assets in the context of current environmental and societal challenges. Some species produce both omega-3 long chain polyunsaturated fatty acids (PUFAs) and xanthophylls, two molecular families widely studied for their bioactivities in the fields of nutrition and cosmetics. Whereas most studies separately deal with the two families, synergies could be exploited with extracts containing both PUFAs and xanthophylls. The purpose of our work was to determine cost effective and eco-friendly parameters for their co-extraction. The effect of several parameters (solvent, solvent/biomass ratio, temperature, duration) were studied, using two microalgal species, the non-calcifying Haptophyta Tisochrysis lutea, and the diatom Phaeodactylum tricornutum, that presents a silicified frustule. Analyses of PUFAs and fucoxanthin (Fx), the main xanthophyll, allowed to compare kinetics and extraction yields between experimental protocols. Co-extraction yields achieved using 96% ethanol as solvent were 100% for Fx and docosahexaenoic acid (DHA) in one hour from T. lutea biomass, and respectively 95% and 89% for Fx and eicosapentaenoic acid (EPA) in eight hours from P. tricornutum. These conditions are compatible with industrial applications.