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Dams are strategic tools for countries and their management of water resources. Within the Space for Climate Observatory (SCO) initiative and SWOT Downstream program, the StockWater project aims to put in place a system for monitoring water volume in dams. It is based on satellite data, and a specific processing system, thereby facilitating the work of the public authorities in this area.Water resources monitoring, including surface and groundwater, is a vital issue for governments and public institutions. Water resources are essential for society and economic activity (drinking water, irrigation, hydroelectricity, industry, flood control) and for natural and water ecosystems.Generally, reservoir stock information is collected and held by the local reservoir managers (public or private). Regional and national authorities might access this information with a certain latency, which depends on national water policies. Central authorities are then confronted with two issues: long latencies to retrieve water stock information and sparse or inexistent information about small reservoirs.The project proposes a global solution to monitor reservoir stock volumes based on frequent satellite measurements. This solution is based on reservoir water extent monitoring by imaging satellites (Sentinel 1&2) based in the Surfwater processing chain, which integrates a multitemporal approach to improve water masks. Furthermore, StockWater innovation relies on reservoir estimation of Area/Elevation/Volume relationships just from a DEM, even when acquired after the reservoir construction. Recent total volume estimations from DEM estimations have been qualified on hundreds reservoirs in France, ranging from 10 to 10000 hectares, providing errors lower than 20% on 77% of the reservoirs. About the general system assesment, Filling rates estimates yield an error lower than 8% on 75% of the measurements.New versions are evaluated on Spain, France, India and Brazil and deployed on Burkina-Faso and Tunisia over more than 100 reservoirs. Results are available here: https://www.sco-stockwater.org/ This system will also easily allow volume estimations from Elevation measurements (altimeters Jason, Sentinel3 with limited coverage or SWOT globally).StockWater project, led by CNES and developed with CS-Group and SERTIT, holds a partnership initiative with CESBIO, GET, LISAH and FUNCEME/Université Pernambuco laboratories and their local partners in Tunisia, Laos, Burkina-Faso, Brazil and India. StockWater is open to new countries willing to participate in future project expansions.

Background and Aims The persistence of a plant population under a specific local climatic regime requires phenotypic adaptation with underlying particular combinations of alleles at adaptive loci. The level of allele diversity at adaptive loci within a natural plant population conditions its potential to evolve, notably towards adaptation to a change in climate. Investigating the environmental factors that contribute to the maintenance of adaptive diversity in populations is thus worthwhile. Within-population allele diversity at adaptive loci can be partly driven by the mean climate at the population site but also by its temporal variability. Methods The effects of climate temporal mean and variability on within-population allele diversity at putatively adaptive quantitative trait loci (QTLs) were evaluated using 385 natural populations of Lolium perenne (perennial ryegrass) collected right across Europe. For seven adaptive traits related to reproductive phenology and vegetative potential growth seasonality, the average within-population allele diversity at major QTLs (HeA) was computed. Key Results Significant relationships were found between HeA of these traits and the temporal mean and variability of the local climate. These relationships were consistent with functional ecology theory. Conclusions Results indicated that temporal variability of local climate has likely led to fluctuating directional selection, which has contributed to the maintenance of allele diversity at adaptive loci and thus potential for further adaptation.

Water stock monitoring is a major issue for society on a local and global scale. Sentinel-1&2 satellites provide frequent acquisitions to track water surface dynamics, proxy variables to enable water surface volume monitoring. How do we combine such observations along time for each sensor? What advantages and disadvantages of single-date, monthly or time-windowed estimations? In this context, we analysed the impact of merging information through different types and lengths of time-windows. Satellite observations were processed separately on optical (Sentinel-2) and radar (Sentinel-1) water detectors at 10 m resolution. The analysis has been applied at two scales. First, validating with 26 large scenes (110 × 110 km) in different climatic zones in France, time-windows yielded an improvement on radar detection (F1-score improved from 0.72 to 0.8 for 30 days on average logic) while optical performances remained stable (F1-score 0.89). Second, validating reservoir area estimations with 29 instrumented reservoirs (20–1250 ha), time-windows presented in all cases an improvement on both optical and radar error for any window length (5–30 days). The mean relative absolute error in optical area detection improved from 16.9% on single measurements to 12.9% using 15 days time-windows, and from 22.15% to 15.1% in radar detection). Regarding reservoir filling rates, we identified an increased negative bias for both sensors when the reservoir is nearly full. This work helped to compare accuracies of separate optical and radar capabilities, where optical statistically outperforms radar at both local and large scale to the detriment of less frequent measurements. Furthermore, we propose a geomorphological indicator of reservoirs to predict the quality of radar area monitoring (R2 = 0.58). In conclusion, we suggest the use of time-windows on operational water mapping or reservoir monitoring systems, using 10–20 days time-windows with average logic, providing more frequent and faster information to water managers in periods of crisis (e.g., water shortage) compared to monthly estimations.

More severe seasonal stresses resulting from climate change affect the survival of perennial plant species. The growth–survival trade‐off exemplified in dormant species is a key issue to understand adaptation. As the validity of this trade‐off has yet to be tested in non‐dormant species, it was assessed by exploring the intraspecific variability of strategies to face drought and frost within perennial ryegrass. Three common gardens compared 385 European perennial ryegrass populations along a latitudinal environmental gradient over 3‐years. Persistence, productivity and physiological traits were recorded under contrasting seasonal environments. Decoupling plant responses, that is, growth under favourable summers/winters and plant survival under harsh summers/winters, showed a general trade‐off between growth potential and dehydration survival. Three groups of perennial ryegrass populations were identified according to their contrasting strategies: (a) year‐round productive but stress sensitive populations from wet areas; (b) drought‐tolerant populations with low summer growth potential from drought‐prone areas and (c) frost‐tolerant populations with low winter growth potential from frost‐prone areas. Overall, the populations surviving drought best were more resource conservative, whereas populations of the other groups were more resource acquisitive. However, such overall functional patterns were less meaningful than seasonal variations of resource acquisition potentials. The predicted potential biogeographical distribution of these groups suggests shifts of areas of suitability under climate change over the next decades in Europe. Dehydration escape and dehydration tolerance through reduction of growth potential in summer may become the strategies best adapted to an increasingly large area of Europe. The large intraspecific variability of phenological adaptations within perennial ryegrass reveals that the seasonal modulation of growth potential is crucial to plant adaptation under severe chronic abiotic stresses. The global plant economics spectrum cannot account for contrasting seasonal trade‐offs, which points out the importance of integrating phenological traits as key components of plant strategies. The identification of the trade‐off between growth potential and frost or drought stress survival in this non‐dormant species provides key knowledge to understand the future regional distribution of this major species for grassland ecosystem services. A free Plain Language Summary can be found within the Supporting Information of this article.

The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.

International audience; Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

International audience; Aim: Grasslands have been pivotal in the development of herbivore breeding since the Neolithic and still represent the most widespread agricultural land use across Europe. However, it remains unclear whether the current large‐scale genetic variation of plant species found in natural grasslands of Europe is the result of human activities or natural processes. Location: Europe. Taxon: Lolium perenne L. (perennial ryegrass). Methods: We reconstructed the phylogeographic history of L. perenne, a dominant grassland species, using 481 natural populations, including 11 populations of closely related taxa. We combined Genotyping‐by‐Sequencing (GBS) and pool‐Sequencing (pool‐Seq) to obtain high‐quality allele frequency calls of ~500 k SNP loci. We performed genetic structure analyses and demographic reconstructions based on the site frequency spectrum (SFS). We additionally used the same genotyping protocol to assess the genomic diversity of a set of 32 cultivars representative of the L. perenne cultivars widely used for forage purposes. Results: Expansion across Europe took place during the Würm glaciation (12–110 kya), a cooling period that decreased the dominance of trees in favour of grasses. Splits and admixtures in L. perenne fit historical climate changes in the Mediterranean basin. The development of agriculture in Europe (7–3.5 kya), that caused an increase in the abundance of grasslands, did not have an effect on the demographic patterns of L. perenne. We found that most modern cultivars are closely related to natural diversity from north-western Europe. Thus, modern cultivars do not represent the wide genetic variation found in natural populations. Main conclusions: Demographic events in L. perenne can be explained by the changing climatic conditions during the Pleistocene. Natural populations maintain a wide genomic variability at continental scale that has been minimally exploited by recent breeding activities. This variability constitutes valuable standing genetic variation for future adaptation of grasslands to climate change, safeguarding the agricultural services they provide.

AimGrasslands have been pivotal in the development of herbivore breeding since the Neolithic and are still nowadays the most widespread agricultural land-use across Europe. However, it remains unclear whether the current large-scale genetic variation of plant species found in natural grasslands of Europe is the result of human activities or natural processes.LocationEurope.TaxonLolium perenne L (perennial ryegrass).MethodsWe reconstructed the phylogeographic history of L. perenne, a dominant grassland species, using 481 natural populations including 11 populations from closely related taxa. We combined the Genotyping-by-Sequencing (GBS) and Pool-sequencing (Pool-seq) methods to obtain high-quality allele frequency calls of ~ 500 k SNP loci. We performed genetic structure analyses and demographic reconstructions based on the site frequency spectrum (SFS). We additionally used the same genotyping protocol to assess the genomic diversity of a set of 32 cultivars representative of the L. perenne cultivars widely used for forage purposes.ResultsExpansion across Europe took place during the Würm glaciation (12-110 kya), a cooling period that decreased the dominance of trees in favour of grasses. Splits and admixtures in L. perenne fit historical sea level changes in the Mediterranean basin. The development of agriculture in Europe (7-3.5 kya), that caused an increase in the abundance of grasslands, did not have an effect on the demographic patterns of L. perenne. We found little differentiation between modern cultivars and certain natural variants. However, modern cultivars do not represent the wide genetic variation found in natural populations.Main conclusionsDemographic events in L. perenne can be explained by the changing climatic conditions during the Pleistocene. Natural populations maintain a wide genomic variability at continental scale that has been underused by recent breeding activities. This variability constitutes valuable standing genetic variation for future adaptation of grasslands to climate change, safeguarding the agricultural services they provide.

International audience; Allele frequency fingerprinting of heterogeneous plant populations of outbreeding species can be used for variety identification, association mapping, genomic selection or characterization of genetic resources. In the FACCE-JPI GrassLandscape project, we empirically validated a pool-GBS method for Genome-Wide Allele Frequency Fingerprinting (GWAFF). As pool-GBS cannot be targeted to predefined loci such as candidate genes, we integrated it with targeted resequencing using a highly multiplexed amplicon sequencing strategy to measure allele frequencies (pool-HiPlex). A pool-HiPlex assay was designed that amplifies 185 amplicons in 41 L. perenne genes in just two parallel PCRreactions. We validated pool-GBS and pool-HiPlex using pools of 48 individuals, chosen to represent a wide range of genetic diversity in L. perenne, and addressed completeness, reproducibility and accuracy of allele frequencies with >1000 HiPlex SNPs and >150.000 GBS SNPs. We consistently found high correlations between allele frequencies obtained by genotyping individual plants and pool genotyping on leaf tissue pools and DNA extract pools. We also analyzed the error introduced at various steps of the protocol such as weighing, DNA-quantification, pooling, ligation and/or PCRamplification. Applying a minor allele frequency threshold of 5% or 3% effectively removed nonreproducible SNPs in pool-GBS and pool-HiPlex, respectively. Allele frequency spectra could be obtained for single SNPs as well as for haplotypes spanning neighboring SNPs using read-backed phasing. Application of this methodology to a set of 470 natural populations of L. perenne sampled across Europe and the fertile Crescent revealed a geographical pattern of genetic differentiation in this species.

International audience; Grasslands have been pivotal in the development of domestic herbivore breeding since the Neolithic and are nowadays the most widespread agricultural land-use over Europe. We have demonstrated that the genealogy of natural Lolium perenne (perennial ryegrass), from permanent grasslands across Europe and the Fertile Crescent, can be traced back to the pre-Holocene epoch (> 12 kya). Demographic events in this species, as reconstructed from genetic data, can be explained by the changing climatic conditions during Quaternary glaciations in Europe. Specific population splits and admixtures fit historical sea level changes across the Mediterranean basin. According to our estimations, population expansion across continental Europe took place during the Würm glaciation (12-110 kya), a cooling period that decreased the dominance of trees in favor of herbs, and notably grasses. The development of agriculture and herbivore breeding that started in the late Holocene (3.5 kya) and caused an increase in the abundance of grasses across Europe did not impact the genetic structure of Lolium perenne at continental scale. Furthermore, our results reveal little differentiation between cultivars released by contemporary plant breeding and natural strains of L. perenne, pointing to the very recent start of intensive human directional selection in herbage grasses. We expose that natural grasslands harbor wide genetic variability at continental scale that has enabled grasses to survive extreme climatic changes across millennia. This genetic variability has been underused by recent breeding activities and constitute valuable standing genetic variation for future adaptation of grasslands to Climate Change, safeguarding the agricultural services they provide.