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The functional trait framework provides a powerful corpus of integrated concepts and theories to assess how environmental factors influence ecosystem functioning through community assembly. While common in plant ecology, this approach is under-used in microbial ecology. After an introduction of this framework in the context of microbial ecology and enzymology, we propose an approach 1) to elucidate new links between soil microbial community composition and microbial traits; and 2) to disentangle mechanisms underlying “total” potential enzyme activity in soil (sum of 7 hydrolase potential activities). We address these objectives using a terrestrial grassland ecosystem model experiment with intact soil monoliths from three European countries (Switzerland, France and Portugal) and two management types (Conventional-intensive and Ecological-intensive), subjected to 4 rain regimes (Dry, Wet, Intermittent and Normal) under controlled conditions in a common climate chamber. We found tight associations between proxies of microbial ecoenzymatic community-weighted mean traits (enzymatic stoichiometry and biomass-specific activity) and community composition, bringing new information on resource acquisition strategy associated with fungi, Gram positive and Gram negative bacteria. We demonstrate that microbial biomass explained most of the total enzyme activity before altered rain regimes, whereas adjustments in biomass-specific activity (enzyme activity per unit of microbial biomass) explained most variation under altered rain regime scenarios. Furthermore, structural equation models revealed that the variation of community composition was the main driver of the variation in biomass-specific enzyme activity prior to rain perturbation, whereas physiological acclimation or evolutionary adaptation became an important driver only under altered rain regimes. This study presents a promising trait-based approach to investigate soil microbial community response to environmental changes and potential consequences for ecosystem functioning. We argue that the functional trait framework should be further implemented in microbial ecology to guide experimental and analytical design.

Significance Bioethanol produced from waste biomass from crops has the potential to provide a sustainable alternative to petroleum-based transportation fuel that does not compete with human food supply. The main obstacle to this approach is the resistance of this biomass to digestion. Thus, expensive energetic pretreatment and high enzyme inputs are needed to increase digestion. In this study, we screened a population of randomly mutated plants for digestibility with the aim of identifying novel factors that impact on this trait. We found a number of mutants with high digestibility and no impairments in growth or fitness. These mutants show a range of alterations in cell-wall composition, and we have mapped and characterized the mutant with the highest increase in digestibility.

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

Acid–base disturbances caused by environmental factors and physiological events including feeding have been well documented in several fish species, but little is known about the impact of dietary electrolyte balance (dEB). In the present study, we investigated the effect of feeding diets differing in dEB ( − 100, 200, 500 or 800 mEq/kg diet) on the growth, nutrient digestibility and energy balance of Nile tilapia. After 5 weeks on the test diet, the growth of the fish was linearly affected by the dEB levels (P< 0·001), with the lowest growth being observed in the fish fed the 800 dEB diet. The apparent digestibility coefficient (ADC) of fat was unaffected by dEB, whereas the ADC of DM and protein were curvilinearly related to the dEB levels, being lowest and highest in the 200 and 800 dEB diets, respectively. Stomach chyme pH at 3 h after feeding was linearly related to the dEB levels (P< 0·05). At the same time, blood pH of the heart (P< 0·05) and caudal vein (P< 0·01) was curvilinearly related to the dEB levels, suggesting the influence of dEB on postprandial metabolic alkalosis. Consequently, maintenance energy expenditure (MEm) was curvilinearly related to the dEB levels (P< 0·001), being 54 % higher in the 800 dEB group (88 kJ/kg0·8per d) than in the 200 dEB group (57 kJ/kg0·8per d). These results suggest that varying dEB levels in a diet have both positive and negative effects on fish. On the one hand, they improve nutrient digestibility; on the other hand, they challenge the acid–base homeostasis (pH) of fish, causing an increase in MEm, and thereby reduce the energy required for growth.