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16 pages, 7 figures, 1 table The model of Paillard and Parrenin (Earth Planet Sci Lett 227(3-4):263-271, 2004) has been recently optimized for the last eight glacial cycles, leading to two different relaxation models with model-data correlations between 0.8 and 0.9 (García-Olivares and Herrero (Clim Dyn 1-25, 2012b)). These two models are here used to predict the effect of an anthropogenic CO2 pulse on the evolution of atmospheric CO2, global ice volume and Antarctic ice cover during the next 300 kyr. The initial atmospheric CO2 condition is obtained after a critical data analysis that sets 1300 Gt as the most realistic carbon Ultimate Recoverable Resources (URR), with the help of a global compartmental model to determine the carbon transfer function to the atmosphere. The next 20 kyr will have an abnormally high greenhouse effect which, according to the CO2 values, will lengthen the present interglacial by some 25 to 33 kyr. This is because the perturbation of the current interglacial will lead to a delay in the future advance of the ice sheet on the Antarctic shelf, causing that the relative maximum of boreal insolation found 65 kyr after present (AP) will not affect the developing glaciation. Instead, it will be the following insolation peak, about 110 kyr AP, which will find an appropriate climatic state to trigger the next deglaciation. © 2013 Springer Science+Business Media Dordrecht This study has been carried out in the framework of project TIC-MOC (CTM2011-28867), funded by the 2008-2011 Spanish R+D Plan. C. Herrero acknowledges a CSIC JAE-Predoc scholarship co-financed by the European Social Fund (FSE) Peer Reviewed

Asseng, S. et al. Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time. We thank the Agricultural Model Intercomparison and Improvement Project and its leaders C. Rosenzweig from NASA Goddard Institute for Space Studies and Columbia University (USA), J. Jones from University of Florida (USA), J. Hatfield from United States Department of Agriculture (USA) and J. Antle from Oregon State University (USA) for support. We also thank M. Lopez from CIMMYT (Turkey), M. Usman Bashir from University of Agriculture, Faisalabad (Pakistan), S. Soufizadeh from Shahid Beheshti University (Iran), and J. Lorgeou and J-C. Deswarte from ARVALIS—Institut du Végétal (France) for assistance with selecting key locations and quantifying regional crop cultivars, anthesis and maturity dates and R. Raymundo for assistance with GIS. S.A. and D.C. received financial support from the International Food Policy Research Institute (IFPRI). C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Science Foundation (project EW 119/5-1). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM—Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and P.D.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O’L. was funded through the Australian Grains Research and Development Corporation and the Department of Environment and Primary Industries Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. E.W. and Z.Z. were funded by CSIRO and the Chinese Academy of Sciences (CAS) through the research project ‘Advancing crop yield while reducing the use of water and nitrogen’ and by the CSIRO-MoE PhD Research Program. Peer reviewed

Seawater warming and increased incidence of marine heatwaves (MHW) are threatening the integrity of coastal marine habitats including seagrasses, which are particularly vulnerable to climate changes. Novel stress tolerance-enhancing strategies, including thermo-priming, have been extensively applied in terrestrial plants for enhancing resilience capacity under the re-occurrence of a stress event. We applied, for the first time in seedlings of the Mediterranean seagrass Posidonia oceanica, a thermo-priming treatment through the exposure to a simulated warming event. We analyzed the photo-physiological and growth performance of primed and non-primed seedlings, and the gene expression responses of selected genes (i.e. stress-, photosynthesis- and epigenetic-related genes). Results revealed that during the re-occurring stress event, primed seedlings performed better than unprimed showing unaltered photo-physiology supported by high expression levels of genes related to stress response, photosynthesis, and epigenetic modifications. These findings offer new opportunities to improve conservation and restoration efforts in a future scenario of environmental changes.

AbstractMarine biota is redistributing at a rapid pace in response to climate change and shifting seascapes. While changes in fish populations and community structure threaten the sustainability of fisheries, our capacity to adapt by tracking and projecting marine species remains a challenge due to data discontinuities in biological observations, lack of data availability, and mismatch between data and real species distributions. To assess the extent of this challenge, we review the global status and accessibility of ongoing scientific bottom trawl surveys. In total, we gathered metadata for 283,925 samples from 95 surveys conducted regularly from 2001 to 2019. 59% of the metadata collected are not publicly available, highlighting that the availability of data is the most important challenge to assess species redistributions under global climate change. We further found that single surveys do not cover the full range of the main commercial demersal fish species and that an average of 18 surveys is needed to cover at least 50% of species ranges, demonstrating the importance of combining multiple surveys to evaluate species range shifts. We assess the potential for combining surveys to track transboundary species redistributions and show that differences in sampling schemes and inconsistency in sampling can be overcome with vector autoregressive spatio-temporal modeling to follow species density redistributions. In light of our global assessment, we establish a framework for improving the management and conservation of transboundary and migrating marine demersal species. We provide directions to improve data availability and encourage countries to share survey data, to assess species vulnerabilities, and to support management adaptation in a time of climate-driven ocean changes.