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Purpose: Perennial crops have been suggested as a more sustainable alternative to the currently most common cropping systems. Compared with annual plants, perennial plants produce more biomass and have deeper roots, and are expected to lead to higher soil organic carbon (SOC). This hypothesis, however, has not been well tested for grain crops. Methods: Using perennial intermediate wheatgrass (IWG, Thinopyrum intermedium) and annual winter wheat (Triticum aestivum) as focal species, and native grassland as reference, we quantified the SOC accumulation via a process-based model, describing water and heat exchanges and carbon-nitrogen cycling in the canopy and soil to a depth of 2 m. The model includes C fixation via photosynthesis, plant biomass growth and litter production, physical protection of SOC, depolymerisation, C mineralisation, nitrification, denitrification, microbial growth, and necromass turnover in the soil. While of general applicability, we considered a sandy loam under warm-summer humid continental climate. Results: Following a conversion from native grassland, IWG reduced SOC losses by at least 38%, especially in the particulate organic carbon (POC) pool, within the top 2 m of soil, compared with annual wheat. Soil microbial biomass and soil respiration were higher in IWG than annual wheat. Shifting from annual wheat to high photosynthetic capacity IWG increased SOC by about 33 g C m−2 y−1 (averaged over a 4-year continuous IWG cropping), with a large fraction of SOC gain stemming from restoring POC. Conclusion: Compared with annual grains, perennial grains can increase soil carbon sequestration and maintain SOC at levels nearer to that of native grasslands. [ABSTRACT FROM AUTHOR]

Miscalculating the volumes of water withdrawn for irrigation, the largest consumer of freshwater in the world, jeopardizes sustainable water management. Hydrological models quantify water withdrawals, but their estimates are unduly precise. Model imperfections need to be appreciated to avoid policy misjudgements. [ABSTRACT FROM AUTHOR]

In Northern Europe, poplars (Populus) can provide biomass for energy and material use, but most available clones were developed for lower latitudes and are unlikely to be well adapted to higher latitudes, even under warmer climates. We thus need to understand how clones respond to climatic conditions and photoperiod, and how these responses can be predicted. We answer these questions exploiting leaf phenological data of Populus clones, grown in six sites across the Baltic region, in Northern Europe, for 2 years with contrasting climatic conditions. Regarding the effects of climatic conditions and photoperiod, within each site, higher temperatures advanced the timing and enhanced the speed of spring and autumn phenology, but reduced the effective growing season length. Across sites, latitude affected the timing of spring and autumn phenology, the speed of spring phenology, and the effective growing season length; clone affected only the timing of phenology. Regarding the predictability of clone response to growing conditions, the growing degree day (GDD) model could not predict spring phenology, because the growing degree day threshold for a specific phenological stage was not only clone-, but also latitude- and year-specific. Yet, this GDD threshold allowed a robust ranking of clones across sites and years, thus providing a tool to determine the relative differences across clones, independently of latitude and temperature. A similar, but not as strong, pattern was observed in the timing of spring and autumn phenological stages. Hence, while prediction of spring phenology remains elusive, the ranking of clones based on observations of their phenology in a single location can provide useful indications on the clones' relative performance under different latitudes and climates. [ABSTRACT FROM AUTHOR]

Irrigation represents one of the main strategies to enhance and stabilize agricultural productivity, by mitigating the effects of rainfall vagaries. In the face of the projected growth in population and in biofuel demands, as well as shifts in climate and dietary habits, a more sustainable management of water resources in agroecosystems is needed. The field of ecohydrology, traditionally focusing on natural ecosystems, has the potential to offer the necessary quantitative tools to assess and compare agricultural enterprises across climates, soil types, crops, and irrigation strategies, accounting for the unpredictability of the hydro-climatic forcing. Here, agricultural sustainability and productivity are assessed with reference to water productivity (defined as the ratio between yield and total supplied water), yields, water requirements, and their variability-a crucial element for food security and resource allocation planning. These synthetic indicators are quantified by means of a probabilistic description of the soil water balance and crop development. The model results allow the interpretation of patterns of water productivity observed in Zea mays (maize) and Triticum aestivum (wheat), grown under a variety of soils, climates, and irrigation strategies. Employing the same modeling framework, the impact of rainfall pattern and irrigation strategy on yield and water requirements is further explored. The obtained standard deviations of yield and water requirements suggest the existence of a nonlinear tradeoff between yield stabilization and variability of water requirements, which in turn is strongly impacted by irrigation strategy. Moreover, intermediate rainfall amounts are associated to the highest variability in yields and irrigation requirements, although allowing the maximum water productivity. The existence of these tradeoffs between productivity, reliability, and sustainability poses a problem for water management, in particular in mesic climates. [ABSTRACT FROM AUTHOR]

Background and Aims: Due to their high water use efficiency, Crassulacean acid metabolism (CAM) plants are of environmental and economic importance in the arid and semiarid regions of the world. Moreover, many CAM plants (e.g., Agave tequilana) have attractive qualities for biofuel production such as a relatively low lignin content and high amount of soluble carbohydrates. However, the current estimates of CAM productivity are based on empirical stress indices that create large uncertainties. As a first step towards a more accurate quantification of CAM productivity, this paper introduces a new model that couples both soil and atmosphere conditions to CAM photosynthesis. Methods: The new CAM model is based upon well established C photosynthesis models coupled to a nonlinear circadian rhythm oscillator for the control of the photosynthesis carbon fluxes. The leaf-level dynamics are coupled to a simple, yet realistic description of the soil-plant-atmosphere continuum, including a plant water capacitance module. Results: The resulting model reproduces the four phases of CAM photosynthes is and the evolution of their dynamics during a soil moisture drydown, as a function of soil type, plant features, and climatic conditions. Conclusion: The results help quantify the impact of soil water availability on CAM carbon assimilation and transpiration flux. [ABSTRACT FROM AUTHOR]

Despite the observed impact of water stress on photosynthesis, some of the most used models of CO2 assimilation in C3 and C4 functional types do not directly account for it. We discuss an extension of these models, which explicitly includes the metabolic and diffusive limitations due to water stress on photosynthesis. Functional relationships describing the photosynthetic processes and CO2 diffusion inside leaves are modified to account for leaf water status on the basis of experimental results available in the literature. Extensive comparison with data shows that the model is suitable to describe the reduction in CO2 assimilation rate with decreasing leaf water potentials in various species. A simultaneous analysis of photosynthesis, transpiration and soil moisture dynamics is then carried out to explore the actual impact of drought on different photosynthesis processes and on the overall plant activity. The model well reproduces measured CO2 assimilation rate as a function of soil moisture and could be useful to formulate hypotheses for detailed experiments as well as to simulate in detail transpiration and photosynthesis dynamics under water stress. [ABSTRACT FROM AUTHOR]