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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]

Highlights: [•] Stomatal optimization theories have neglected the effect of dynamic soil moisture. [•] Here soil moisture is considered to provide a closure for the optimization problem. [•] The new solutions link marginal water use efficiency to air [CO2] and soil water. [•] Previously inconsistent theoretical results and data are generalized and explained. [Copyright &y& Elsevier]

Quantification of stomatal responses to environmental variables, in particular to soil water status, is needed to model carbon and water exchange rates between plants and the atmosphere. Models based on stomatal optimality theory successfully describe leaf gas exchange under different environmental conditions, but the effects of water availability on the key optimization parameter [the marginal water use efficiency (WUE), λ = ∂ A/∂ E] has resisted complete theoretical treatment. Building on previous optimal leaf gas exchange models, we developed an analytical equation to estimate λ from gas exchange observations along gradients of soil water availability. This expression was then used in a meta-analysis of about 50 species to investigate patterns of variation in λ. Assuming that cuticular water losses are negligible λ increases under mild water stress but decreases when severe water stress limits photosynthesis. When cuticular conductance is considered, however, λ increases monotonically with increasing water stress, in agreement with previous theoretical predictions. Moreover, the shape of these response curves to soil water availability changes with plant functional type and climatic conditions. In general, λ is lower in species grown in dry climates, indicating lower marginal WUE. The proposed parameterization provides a framework to assess the responses of leaf gas exchange to changes in water availability. Moreover, the model can be extended to scale leaf-level fluxes to the canopy and ecosystem level. [ABSTRACT FROM AUTHOR]

Abstract: With vast regions already experiencing water shortages, it is becoming imperative to manage sustainably the available water resources. As agriculture is by far the most important user of freshwater and the role of irrigation is projected to increase in face of climate change and increased food requirements, it is particularly important to develop simple, widely applicable models of irrigation water needs for short- and long-term water resource management. Such models should synthetically provide the key irrigation quantities (volumes, frequencies, etc.) for different irrigation schemes as a function of the main soil, crop, and climatic features, including rainfall unpredictability. Here we consider often-employed irrigation methods (e.g., surface and sprinkler irrigation systems, as well as modern micro-irrigation techniques) and describe them under a unified conceptual and theoretical framework, which includes rainfed agriculture and stress-avoidance irrigation as extreme cases. We obtain mostly analytical solutions for the stochastic steady state of soil moisture probability density function with random rainfall timing and amount, and compute water requirements as a function of climate, crop, and soil parameters. These results provide the necessary starting point for a full assessment of irrigation strategies, with reference to sustainability, productivity, and profitability, developed in a companion paper [Vico G, Porporato A. From rainfed agriculture to stress-avoidance irrigation: II. Sustainability, crop yield, and net profit. Adv Water Resour 2011;34(2):272–81]. [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]

• On-farm ponds can sustainably provide water for irrigation, but impose trade-offs. • A minimalist model coupling soil water, crop and pond water storage is developed. • We identify the best pond size for different climates, soils and irrigation strategies. • Production maximization and low yield risk minimization require different pond sizes. • Future more extreme climates will make these goals even harder to reconcile. In many regions precipitation does not reliably meet crop water demands – a situation that climate change will likely exacerbate. Supplemental irrigation can help enhance and stabilize crop yields, but the need of water for irrigation has often led to groundwater over-exploitation. On-farm ponds can provide a more sustainable water source. Their use has often been promoted by local authorities, but, by converting a portion of cultivated area to water storage and reducing water availability downstream, on-farm ponds also imply constraints and trade-offs. For an effective exploitation of their potential benefits, they must be carefully designed and managed based on the local edaphic and climate conditions – a non trivial, task because of the cascading effects of rainfall unpredictability. Here we identify the most suitable on-farm pond size, according to two criteria: maximization of average yield (i.e., production maximization) and achievement of a minimum acceptable yield (i.e., risk minimization, accounting for the farmer's risk aversion). To this aim, we develop a minimalist model, requiring few, physically based parameters, coupling crop biomass, soil moisture, and water stored in the pond. While general, the model is here applied to a case-study in the Lower Mississippi River Basin (USA). Simulations show that yield maximization and risk minimization are goals hard to reconcile, regardless of climatic conditions, soil type and irrigation strategy, with smaller ponds allowing the maximum average yield at the cost of reducing its stability from year to year. Stress avoidance irrigation ensures higher yields than deficit irrigation, even if it implies a faster use of the stored water. Future, more extreme climates will result in lower maximum average yields and narrower ranges of pond sizes ensuring desirable minimum yields. [ABSTRACT FROM AUTHOR]

• We analyzed daily air temperature and soil moisture time series of 54 forest sites. • Moister soils supported cooler understory microclimates. • Temperature buffering was more sensitive to soil moisture in dry soils and on sunny slopes. • Forests can lose their temperature buffering function when soils become drier. Forest canopies can buffer the understory against temperature extremes, often creating cooler microclimates during warm summer days compared to temperatures outside the forest. The buffering of maximum temperatures in the understory results from a combination of canopy shading and air cooling through soil water evaporation and plant transpiration. Therefore, buffering capacity of forests depends on canopy cover and soil moisture content, which are increasingly affected by more frequent and severe canopy disturbances and soil droughts. The extent to which this buffering will be maintained in future conditions is unclear due to the lack of understanding about the relationship between soil moisture and air temperature buffering in interaction with canopy cover and topographic settings. We explored how soil moisture variability affects temperature offsets between outside and inside the forest on a daily basis, using temperature and soil moisture data from 54 sites in temperate broadleaf forests in Central Europe over four climatically different summer seasons. Daily maximum temperatures in forest understories were on average 2 °C cooler than outside temperatures. The buffering of understory temperatures was more effective when soil moisture was higher, and the offsets were more sensitive to soil moisture on sites with drier soils and on sun-exposed slopes with high topographic heat load. Based on these results, the soil–water limitation to forest temperature buffering will become more prevalent under future warmer conditions and will likely lead to changes in understory communities. Thus, our results highlight the urgent need to include soil moisture in models and predictions of forest microclimate, understory biodiversity and tree regeneration, to provide a more precise estimate of the effects of climate change. [Display omitted] [ABSTRACT FROM AUTHOR]

• Non-dimensional combinations of soil, plant, and climate variables reduce the complexity of plant water use strategies. • Plant water flux control relative to demand is the non-dimensional group that primarily influences plant water use performance. • Plant water use strategies that maximize long-term mean transpiration weighted by risks of water stress match soil moisture observations. • Combining non-dimensional groups and ecohydrological optimality offers constraints to quantify and understand plant water stress responses. Plant responses to water stress influence water and carbon cycles and can lead to feedbacks on climate yet characterizing these responses at ecosystem levels remains uncertain. Quantifying ecosystem-level water use strategies is complex due to challenges of upscaling plant traits and disentangling confounding environmental factors, ultimately limiting our ability to understand and anticipate global change in ecosystem dynamics and ecohydrological fluxes. We reduce the dimensionality of this problem and quantify plant water use strategies by combining plant traits with soil and climate variables into parameter groups that synthesize key eco-physiological tradeoffs. Using a parsimonious soil water balance framework, we explore variations in plant water uptake capacity, water stress responses, and water use performance via these non-dimensional parameter groups. The group characterizing the synchronization of plant water transport and atmospheric water demand emerges as the primary axis of variation in water use strategies and interacts with the group representing plant hydraulic risk tolerance, especially in arid conditions when plant water transport is limiting. Next, we show that specific plant water use strategies maximize plant water uptake (leading to carbon gain benefits) weighted by risks of water stress (leading to higher costs of water use). A model-data comparison demonstrates that these ecohydrologically optimal parameter groups capture observed soil moisture variability in 40 ecosystems and beyond aridity, rainfall frequency is an important environmental control for plant water use strategies. The emerging parsimonious link between ecohydrological performance and non-dimensional parameters provides a tractable representation of plant water use strategies, relevant to parameterize global models while accounting for ecological and evolutionary constraints on the water cycle. [ABSTRACT FROM AUTHOR]

When modelling forest growth, capturing the effects of climate change is needed for reliable long-term predictions and management choices. This remains a challenge because commonly used mensurational forest growth and yield models, relying on inventory data, cannot account for climate change effects. We developed hybrid physiological/mensurational basal area growth and yield models, which combine physiological response to climatic conditions and empirical relations. We included climate and site effects by replacing time with light sums of photosynthetically active radiation and modifying the latter with monthly soil water, vapour pressure deficit, temperature, and frost days. When parameterised with permanent sample plot data for Scots pine and Norway spruce across Sweden, the hybrid models could reproduce observations well, although with no increase in precision compared with time-based mensurational models. When considering different climate scenarios, a significant impact on productivity from climate change emerged. For example, a 2 °C warming enhanced Scots pine production by up to 14% in regions where temperatures were originally cooler and soil water deficit was low (i.e. northwest Sweden), but depressed it, up to 9%, elsewhere. Hence, climate-sensitive models that take local variations into account are necessary for accurate predictions and sustainable forest management. [ABSTRACT FROM AUTHOR]

Abstract: The sustainable management of unwanted vegetation in agricultural fields through integrated weed control strategies requires detailed knowledge about the maternal formation of primary seed dormancy, to support the prediction of seedling emergence dynamics. This knowledge is decisive for the timing of crop sowing and nonchemical weed control measures. Studies in controlled environments have already demonstrated that thermal conditions and, to some extent, water availability during seed set and maturation has an impact on the level of dormancy. However, it is still unclear if this applies also under field conditions, where environmental stressors and their timing are more variable. We address this question for Alopecurus myosuroides in south‐western Sweden. We quantified the effects of cumulated temperature and precipitation as well as soil water potential during the reproductive growth phase of A myosuroides on primary seed dormancy under field conditions. Empirical models differing in focal time intervals and, in case of soil water potential, focal soil depths were compared regarding their predictive power. The highest predictive power for the level of primary dormancy of A. myosuroides seeds was found for a two‐factorial linear model containing air temperature sum between 0 and 7 days before peak seed shedding as well as the number of days with soil water potential below field capacity between 7 and 35 days before peak seed shedding. For soil water potential, it was found that only the top 10 cm soil layer is of relevance, which is in line with the shallow root architecture of A. myosuroides. We conclude that for this species the level of dormancy depends on the magnitude and timing of temperature and water availability during the reproductive growth phase. Water availability appears to be more important during maternal environmental perception and temperature during zygotic environmental perception. [ABSTRACT FROM AUTHOR]