The PGR Networks in France: Collaboration of users and the genetic resources centre on small grain cereals

Plant genetic resources (PGR) have been used in breeding programs for many decades to produce modern varieties by introducing genes of interest, in particular, resistance genes. Nevertheless, these resources remain underestimated if we focus on abiotic stress tolerance or new agricultural techniques, which consider productivity with regard to the environment. In recent years, new users, such as scientists and farmers, have discovered diverse sources of interest for screening and exploiting natural diversity conserved in PGR collections.In the case of the French cereals PGR Network, a share of the responsibility, based on the knowledge and ability of network members, has been decided in order to better promote the use of PGR. The main species of Triticum (wheat), Hordeum (barley), Secale (rye), ×Triticosecale (triticale), Avena (oat) genera and their wild relatives are held in the collection. By combining phenotypic and genotypic data, the whole genetic resource collection has been structured into smaller functional groups of accessions, in order to facilitate the access and meet the increasing number of different requirements for the distribution of adapted samples of accessions.New panels are being processed to give breeders and scientists new useful tools to study, for instance, stress resistance or to develop association studies. All these data obtained from the French small grain cereal Network will be progressively available through the INRA Genetic Resource Website (http://urgi.versailles.inra.fr/siregal/siregal/welcome.do)

Carbon Stocks and Fluxes in Kenyan Forests and Wooded Grasslands Derived from Earth Observation and Model-Data Fusion

The characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. Here we present the most detailed and rigorous national-scale assessment of aboveground woody biomass carbon stocks and dynamics for Kenya to date. A non-parametric random forest algorithm was trained to retrieve aboveground woody biomass carbon (AGBC) for the year 2014 ± 1 and forest disturbances for the 2014–2017 period using in situ forest inventory plot data and satellite Earth Observation (EO) data. The ecosystem carbon cycling of Kenya’s forests and wooded grassland were assessed using a model-data fusion framework, CARDAMOM, constrained by the woody biomass datasets from this study as well as time series information on leaf area, fire events and soil organic carbon. Our EO-derived AGBC stocks were estimated as 140 Mt C for forests and 199 Mt C for wooded grasslands. The total AGBC loss during the study period was estimated as 1.89 Mt C with a dispersion below 1%. The CARDAMOM analysis estimated woody productivity to be three times larger in forests (mean = 1.9 t C ha−1 yr−1) than wooded grasslands (0.6 t C ha−1 yr−1), and the mean residence time of woody C in forests (16 years) to be greater than in wooded grasslands (10 years). This study stresses the importance of carbon sequestration by forests in the international climate mitigation efforts under the Paris Agreement, but emphasizes the need to include non-forest ecosystems such as wooded grasslands in international greenhouse gas accounting frameworks

The decadal state of the terrestrial carbon cycle: global retrievals of terrestrial carbon allocation, pools and residence times

The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64–0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types

Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system

There is a significant knowledge gap in the current state of the terrestrial carbon (C) budget. Recent studies have highlighted a poor understanding particularly of C pool transit times and of whether productivity or biomass dominate these biases. The Arctic, accounting for approximately 50% of the global soil organic C stocks, has an important role in the global C cycle. Here, we use the CARbon DAta MOdel (CARDAMOM) data-assimilation system to produce pan-Arctic terrestrial C cycle analyses for 2000-2015. This approach avoids using traditional plant functional type or steady-state assumptions. We integrate a range of data (soil organic C, leaf area index, biomass, and climate) to determine the most likely state of the high-latitude C cycle at a 11 resolution and also to provide general guidance about the controlling biases in transit times. On average, CARDAMOM estimates regional mean rates of photosynthesis of 565 gCm2 yr1 (90% confidence interval between the 5th and 95th percentiles: 428, 741), autotrophic respiration of 270 g Cm2 yr1 (182, 397) and heterotrophic respiration of 219 g Cm2 yr1 (31, 1458), suggesting a pan-Arctic sink of 67 (287, 1160) gCm2 yr1, weaker in tundra and stronger in taiga. However, our confidence intervals remain large (and so the region could be a source of C), reflecting uncertainty assigned to the regional data products. We show a clear spatial and temporal agreement between CARDAMOM analyses and different sources of assimilated and independent data at both pan-Arctic and local scales but also identify consistent biases between CARDAMOM and validation data. The assimilation process requires clearer error quantification for leaf area index (LAI) and biomass products to resolve these biases. Mapping of vegetation C stocks and change over time and soil C ages linked to soil C stocks is required for better analytical constraint. Comparing CARDAMOM analyses to global vegetation models (GVMs) for the same period, we conclude that transit times of vegetation C are inconsistently simulated in GVMs due to a combination of uncertainties from productivity and biomass calculations. Our findings highlight that GVMs need to focus on constraining both current vegetation C stocks and net primary production to improve a process-based understanding of C cycledynamics in the Arctic

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission

Analysis of diversity and linkage disequilibrium along chromosome 3B of bread wheat (Triticum aestivum L.)

A highly polymorphic core collection of bread wheat and a more narrow-based breeding material, gathered from pedigrees of seven modern cultivars, was analysed in order to compare genetic diversity indices and linkage disequilibrium (LD) patterns along the chromosome 3B with microsatellite (SSR) and Diversity Arrays Technology markers. Five ancestral gene pools could be identified within the core collection, indicating a strong geographical structure (Northwest Europe, Southeast Europe, CIMMYT-ICARDA group, Asia, Nepal). The breeding material showed a temporal structure, corresponding to different periods of breeding programmes [old varieties (from old landraces to 1919), semi-modern varieties (1920-1959), modern varieties (1960-2006)]. Basic statistics showed a higher genetic diversity in the core collection than in the breeding material, indicating a stronger selection pressure in this latter material. More generally, the chromosome 3B had a lower diversity than the whole B-genome. LD was weak in all studied materials. Amongst geographical groups, the CIMMYT-ICARDA pool presented the longest ranged LD in contrast to Asian accessions. In the breeding material, LD increased from old cultivars to modern varieties. Genitors of seven modern cultivars were found to be different; most marker pairs in significant LD were observed amongst genitors of Alexandre and Koreli varieties, indicating an important inbreeding effect. At low genetic distances (0-5 cM), the breeding material had higher LD than the core collection, but globally the two materials had similar values in all classes. Marker pairs in significant LD are generally observed around the centromere in both arms and at distal position on the short arm of the chromosome 3B