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Abstract - The study of natural ecosystems and experiments using mixtures of plant species demonstrates that both species and genetic diversity generally promote ecosystem functioning. Therefore, mixing crop varieties is a promising alternative practice to transform modern high-input agriculture that is associated with a drastic reduction of within-field crop genetic diversity and is widely recognized as unsustainable. Here, we review the effects of mixtures of varieties on ecosystem functioning, and their underlying ecological mechanisms, as studied in ecology and agronomy, and outline how this knowledge can help designing more efficient mixtures. We recommend the development of two complementary strategies to optimize variety mixtures by fostering the ecological mechanisms leading to a positive relationship between biodiversity and ecosystem functioning and its stability through time, i.e., sampling and complementarity effects. (1) In the “trait-blind” approach, the design of high-performance mixtures is based on estimations of the mixing abilities of varieties. While this approach is operational because it does not require detailed trait knowledge, it relies on heavy experimental designs to evaluate mixing ability. (2) The trait-based approach is particularly efficient to design mixtures of varieties to provide particular baskets of services but requires building databases of traits for crop varieties and documenting the relations between traits and services. The performance of mixtures requires eventually to be evaluated in real economic, social, and agronomic contexts. We conclude that the need of a multifunctional low-input agriculture strongly increases the attractiveness of mixtures but that new breeding approaches are required to create varieties with higher mixing abilities, to foster complementarity and selection effects through an increase in the variance of relevant traits and to explore new combinations of trait values. International audience

Knowledge on insecticide resistance in Anopheles species is a basic requirement to guide malaria vector control programs. In Lao PDR, vector control relies on insecticide residual spraying (IRS) and impregnated bed-nets (ITNs) with the use of pyrethroids. Here, the susceptibility of Anopheles species, including several malaria vectors (An. maculatus and An. minimus), to various insecticides was investigated in ten provinces of Lao PDR through a north-south transect. Bioassays were performed on field caught female mosquitoes using the standard WHO susceptibility tests with DDT (4%), deltamethrin (0.05%) and permethrin (0.75%). In addition, the DIIS6 region of the para-type sodium channel gene was amplified and sequenced to identify knockdown resistance mutations (kdr). Resistance to DDT and permethrin was detected in suspected malaria vectors, such as An. nivipes and An. philippi-nensis in Lao PDR. Resistance to the formerly used DDT was found in a population of An. maculatus s.l. from Luang Prabang province. No resistance to pyrethroids was found in primary vectors, indicating that these insecticides are still adequate for malaria vector control. However, high resistance levels to pyrethroids was found in-vector species and reduced susceptibility to permethrin in An. minimus and An. maculatus was reported in specific localities which raises concerns for pyrethroid-based control in the future. No kdr mutation was found in any of the resistant populations tested hence suggesting a probable role detoxifica-tion enzymes in resistance. This study highlights the necessity to continue the monitoring of insecticide susceptibility to early detect potential occurrence and/or migration of insecticide resistance in malaria vectors in Lao PDR. International audience

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able– for the first time – to identify and measure the crown dimensions of individual trees from airborne imagery. Yet tomake full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric toolswhich have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 treesfor which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measureaboveground biomass. Using this database, we develop general allometric models for estimating both the diameterand aboveground biomass of trees from attributes which can be remotely sensed – specifically height and crowndiameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual treesand find that a single equation predicts stem diameter from these two variables across the world’s forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoringprogrammes and will be of key importance for parameterizing the next generation of dynamic vegetation models. International audience

High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at these scales are rare. There is increasing recognition of the role played by small scale ocean processes in ocean-atmosphere coupling, upper-ocean mixing and ocean vertical transports, with advanced numerical models and in situ observations highlighting fundamental changes in dynamics when scales reach 1 km. Numerous scientific publications highlight the global impact of small oceanic scales on marine ecosystems, operational forecasts and long-term climate projections through strong ageostrophic circulations, large vertical ocean velocities and mixed layer re-stratification. Small-scale processes particularly dominate in coastal, shelf and polar seas where they mediate important exchanges between land, ocean, atmosphere and the cryosphere, e.g., freshwater, pollutants. As numerical models continue to evolve toward finer spatial resolution and increasingly complex coupled atmosphere-wave-ice-ocean systems, modern observing capability lags behind, unable to deliver the high-resolution synoptic measurements of total currents, wind vectors and waves needed to advance understanding, develop better parameterizations and improve model validations, forecasts and projections. SEASTAR is a satellite mission concept that proposes to directly address this critical observational gap with synoptic two-dimensional imaging of total ocean surface current vectors and wind vectors at 1 km resolution and coincident directional wave spectra. Based on major recent advances in squinted along-track Synthetic Aperture Radar interferometry, SEASTAR is an innovative, mature concept with unique demonstrated capabilities, seeking to proceed toward spaceborne implementation within Europe and beyond CG and AM received funding from the United Kingdom Centre for Earth Observation Instrumentation SEASTAR+ project (Contract No. RP10G0435A02). PVL was supported by the European Research Council (ERC) CUNDA project 694509 under the European Union Horizon 2020 Research and Innovation Program 7 pages, 2 figures Peer Reviewed

Plastics and other artificial materials pose new risks to the health of the ocean. Anthropogenic debris travels across large distances and is ubiquitous in the water and on shorelines, yet, observations of its sources, composition, pathways, and distributions in the ocean are very sparse and inaccurate. Total amounts of plastics and other man-made debris in the ocean and on the shore, temporal trends in these amounts under exponentially increasing production, as well as degradation processes, vertical fluxes, and time scales are largely unknown. Present ocean circulation models are not able to accurately simulate drift of debris because of its complex hydrodynamics. In this paper we discuss the structure of the future integrated marine debris observing system (IMDOS) that is required to provide long-term monitoring of the state of this anthropogenic pollution and support operational activities to mitigate impacts on the ecosystem and on the safety of maritime activity. The proposed observing system integrates remote sensing and in situ observations. Also, models are used to optimize the design of the system and, in turn, they will be gradually improved using the products of the system. Remote sensing technologies will provide spatially coherent coverage and consistent surveying time series at local to global scale. Optical sensors, including high-resolution imaging, multi- and hyperspectral, fluorescence, and Raman technologies, as well as SAR will be used to measure different types of debris. They will be implemented in a variety of platforms, from hand-held tools to ship-, buoy-, aircraft-, and satellite-based sensors. A network of in situ observations, including reports from volunteers, citizen scientists and ships of opportunity, will be developed to provide data for calibration/validation of remote sensors and to monitor the spread of plastic pollution and other marine debris. IMDOS will interact with other observing systems monitoring physical, chemical, and biological processes in the ocean and on shorelines as well as the state of the ecosystem, maritime activities and safety, drift of sea ice, etc. The synthesized data will support innovative multi-disciplinary research and serve a diverse community of users.