Search Results
Plant genotype influence the structure of cereal seed fungal microbiome
2023, Malacrinò, Antonino, Abdelfattah, Ahmed, Belgacem, Imen, Schena, Leonardo
Plant genotype is a crucial factor for the assembly of the plant-associated microbial communities. However, we still know little about the variation of diversity and structure of plant microbiomes across host species and genotypes. Here, we used six species of cereals (Avena sativa, Hordeum vulgare, Secale cereale, Triticum aestivum, Triticum polonicum, and Triticum turgidum) to test whether the plant fungal microbiome varies across species, and whether plant species use different mechanisms for microbiome assembly focusing on the plant ears. Using ITS2 amplicon metagenomics, we found that host species influences the diversity and structure of the seed-associated fungal communities. Then, we tested whether plant genotype influences the structure of seed fungal communities across different cultivars of T. aestivum (Aristato, Bologna, Rosia, and Vernia) and T. turgidum (Capeiti, Cappelli, Mazzancoio, Trinakria, and Timilia). We found that cultivar influences the seed fungal microbiome in both species. We found that in T. aestivum the seed fungal microbiota is more influenced by stochastic processes, while in T. turgidum selection plays a major role. Collectively, our results contribute to fill the knowledge gap on the wheat seed microbiome assembly and, together with other studies, might contribute to understand how we can manipulate this process to improve agriculture sustainability.
The GGCMI Phase 2 emulators: Global gridded crop model responses to changes in CO2, temperature, water, and nitrogen (version 1.0)
2020, Franke, James A., Müller, Christoph, Elliott, Joshua, Ruane, Alex C., Jägermeyr, Jonas, Snyder, Abigail, Dury, Marie, Falloon, Pete D., Folberth, Christian, François, Louis, Hank, Tobias, Izaurralde, R. Cesar, Jacquemin, Ingrid, Jones, Curtis, Li, Michelle, Liu, Wenfeng, Olin, Stefan, Phillips, Meridel, Pugh, Thomas A. M., Reddy, Ashwan, Williams, Karina, Wang, Ziwei, Zabel, Florian, Moyer, Elisabeth J.
Statistical emulation allows combining advantageous features of statistical and process-based crop models for understanding the effects of future climate changes on crop yields. We describe here the development of emulators for nine process-based crop models and five crops using output from the Global Gridded Model Intercomparison Project (GGCMI) Phase 2. The GGCMI Phase 2 experiment is designed with the explicit goal of producing a structured training dataset for emulator development that samples across four dimensions relevant to crop yields: Atmospheric carbon dioxide (CO2) concentrations, temperature, water supply, and nitrogen inputs (CTWN). Simulations are run under two different adaptation assumptions: That growing seasons shorten in warmer climates, and that cultivar choice allows growing seasons to remain fixed. The dataset allows emulating the climatological-mean yield response of all models with a simple polynomial in mean growing-season values. Climatological-mean yields are a central metric in climate change impact analysis; we show here that they can be captured without relying on interannual variations. In general, emulation errors are negligible relative to differences across crop models or even across climate model scenarios; errors become significant only in some marginal lands where crops are not currently grown. We demonstrate that the resulting GGCMI emulators can reproduce yields under realistic future climate simulations, even though the GGCMI Phase 2 dataset is constructed with uniform CTWN offsets, suggesting that the effects of changes in temperature and precipitation distributions are small relative to those of changing means. The resulting emulators therefore capture relevant crop model responses in a lightweight, computationally tractable form, providing a tool that can facilitate model comparison, diagnosis of interacting factors affecting yields, and integrated assessment of climate impacts. © 2020 EDP Sciences. All rights reserved.
Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation
2019, Minoli, Sara, Müller, Christoph, Elliott, Joshua, Ruane, Alex C., Jägermeyr, Jonas, Zabel, Florian, Dury, Marie, Folberth, Christian, François, Louis, Hank, Tobias, Jacquemin, Ingrid, Liu, Wenfeng, Olin, Stefan, Pugh, Thomas A.M.
Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas. ©2019. The Authors.