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Large variability in N2O emissions from managed grasslands may occur because most emissions originate in surface litter or near-surface soil where variability in soil water content (θ) and temperature (Ts) is greatest. To determine whether temporal variability in θ and Ts of surface litter and near-surface soil could explain this in N2O emissions, a simulation experiment was conducted with ecosys, a comprehensive mathematical model of terrestrial ecosystems in which processes governing N2O emissions were represented at high temporal and spatial resolution. Model performance was verified by comparing N2O emissions, CO2 and energy exchange, and θ and Ts modelled by ecosys with those measured by automated chambers, eddy covariance (EC) and soil sensors on an hourly timescale during several emission events from 2004 to 2009 in an intensively managed pasture at Oensingen, Switzerland. Both modelled and measured events were induced by precipitation following harvesting and subsequent fertilizing or manuring. These events were brief (2-5 days) with maximum N2O effluxes that varied from < 1 mgNm-2h-1 in early spring and autumn to > 3 mgNm-2h-1 in summer. Only very small emissions were modelled or measured outside these events. In the model, emissions were generated almost entirely in surface litter or near-surface (0-2 cm) soil, at rates driven by N availability with fertilization vs. N uptake with grassland regrowth and by O2 supply controlled by litter and soil wetting relative to O2 demand from microbial respiration. In the model, NOx availability relative to O2 limitation governed both the reduction of more oxidized electron acceptors to N2O and the reduction of N2O to N2, so that the magnitude of N2O emissions was not simply related to surface and near-surface θ and Ts. Modelled N2O emissions were found to be sensitive to defoliation intensity and timing which controlled plant N uptake and soil θ and Ts prior to and during emission events. Reducing leaf area index (LAI) remaining after defoliation to half that under current practice and delaying harvesting by 5 days raised modelled N2O emissions by as much as 80% during subsequent events and by an average of 43% annually. Modelled N2O emissions were also found to be sensitive to surface soil properties. Increasing near-surface bulk density by 10% raised N2O emissions by as much as 100% during emission events and by an average of 23% annually. Relatively small spatial variation in management practices and soil surface properties could therefore cause the large spatial variation in N2O emissions commonly found in field studies. The global warming potential from annual N2O emissions in this intensively managed grassland largely offset those from net C uptake in both modelled and field experiments. However, model results indicated that this offset could be adversely affected by suboptimal land management and soil properties. [ABSTRACT FROM AUTHOR]

Besides its primary role in producing food and fiber, agriculture also has relevant effects on several other functions, such as management of renewable natural resources. Climate change (CC) may lead to new trade-offs between agricultural functions or aggravate existing ones, but suitable agricultural management may maintain or even improve the ability of agroecosystems to supply these functions. Hence, it is necessary to identify relevant drivers (e.g., cropping practices, local conditions) and their interactions, and how they affect agricultural functions in a changing climate. The goal of this study was to use a modeling framework to analyze the sensitivity of indicators of three important agricultural functions, namely crop yield (food and fiber production function), soil erosion (soil conservation function), and nutrient leaching (clean water provision function), to a wide range of agricultural practices for current and future climate conditions. In a two-step approach, cropping practices that explain high proportions of variance of the different indicators were first identified by an analysis of variance-based sensitivity analysis. Then, most suitable combinations of practices to achieve best performance with respect to each indicator were extracted, and trade-offs were analyzed. The procedure was applied to a region in western Switzerland, considering two different soil types to test the importance of local environmental constraints. Results show that the sensitivity of crop yield and soil erosion due to management is high, while nutrient leaching mostly depends on soil type. We found that the influence of most agricultural practices does not change significantly with CC; only irrigation becomes more relevant as a consequence of decreasing summer rainfall. Trade-offs were identified when focusing on best performances of each indicator separately, and these were amplified under CC. For adaptation to CC in the selected study region, conservation soil management and the use of cropped grasslands appear to be the most suitable options to avoid trade-offs. [ABSTRACT FROM AUTHOR]

In this paper, we assess climate change impacts on an intensively managed grassland system at the Swiss Plateau using the process-based grassland model PROGRASS. Taking the CO fertilization into account, we find increasing yield levels (in the range of 10-24%) and sharp increases in production risks for an illustrative climate change scenario that suggests a marked increase in temperature and decrease in summer rainfall. Climate change-induced increases in the coefficients of variation of grassland yields are in the range of 21 and 50%. This finding underpins that additional risk management strategies are needed to cope with climate-change impacts on grassland production. The outputs from the grassland model are evaluated economically using certainty equivalents, i.e., accounting for mean quasi rents and production risks. To identify potential risk management strategies under current and future climatic conditions, we consider adjustments of production intensity and farm-level yield insurance. The impact of climate change on production intensities is found to be ambiguous: farmers' will increase intensity under unconstrained production conditions, but will decrease production intensity in the presence of a cross-compliance scheme. Our results also show that the considered insurance scheme is a powerful tool to manage climate risks in grassland production under current and future conditions because it can reduce the coefficients of variation of quasi rents by up to 50%. However, we find that direct payments tend to reduce farmers' incentives to use such insurance scheme. [ABSTRACT FROM AUTHOR]

Mechanisms controlling transient responses to elevated CO2 concentration and climate change in an unfertilized grassland on the Swiss Plateau were examined in light of simulations with PROGRASS, a process-based model of grass-clover interactions. Daily weather for a series of transient climate scenarios spanning the 21st century were developed for the study site with the help of the LARS-WG weather generator. Changes in the length of dry and wet spells, temperature, precipitation and solar radiation defining the scenarios were obtained from regional climate simulations carried out in the framework of the PRUDENCE project. Compared to 1961-1990, the latter indicated that for 2071-2100 there would be a noticeable increase in temperature (roughly 3°C in winter and 5°C in summer), a significant drop in summer precipitation (of the order of -30%) and a nearly 2-told increase in the length of dry spells. Assuming that clover is less drought-tolerant than grass, we examined whether clover abundance would decrease as a consequence of increasing heat and water stress, or be promoted on account of CO2 stimulation. Results indicated that: (1) at our site, climate change alone did not curtail biological N2 fixation to the point as to alter the composition of the sward but nevertheless entailed a decrease in grassland productivity; (2) increasing CO2 clearly promoted clover growth (via feedbacks on nitrogen acquisition) and grassland productivity; and (3) even with CO2 stimulation, the additional N input from symbiotic N2 fixation was not sufficient to substantially improve the mineral N status of the system and promote grass competitiveness. [ABSTRACT FROM AUTHOR]

We improved a process-oriented biogeochemical model of carbon and nitrogen cycling in grasslands and tested it against in situ measurements of biomass and CO2 and CH4 fluxes at five European grassland sites. The new version of the model (PASIM) calculates the growth and senescence of aboveground vegetation biomass accounting for sporadic removals when the grassland is cut and for continuous removals when it is grazed. Limitations induced by high leaf area index (LAI), soil water deficits and aging of leaves are also included. We added to this a simple empirical formulation to account for the detrimental impact on vegetation of trampling and excreta by grazing animals. Finally, a more realistic methane emission module than is currently used was introduced on the basis of the quality of the animals' diet. Evaluation of this improved version of PASIM is performed at (1) Laqueuille, France, on grassland continuously grazed by cattle with two plots of intensive and extensive grazing intensities, (2) Oensingen, Switzerland, on cut grassland with two fertilized and nonfertilized plots, and (3) Carlow, Ireland, on grassland that is both cut and grazed by cattle during the growing season. In addition, we compared the modeled animal CH4 emissions with in situ measurements on cattle for two grazing intensities at the grazed grassland site of Laqueuille. Altogether, when all improvements to the PASIM model are included, we found that the new parameterizations resulted into a better fit to the observed seasonal cycle of biomass and of measured CO2 and CH4 fluxes. However, the large uncertainties in measurements of biomass and LAI make simulation of biomass dynamics difficult to make. Also simulations for cut grassland are better than for grazed swards. This work paves the way for simulating greenhouse gas fluxes over grasslands in a spatially explicit manner, in order to quantify and understand the past, present and future role of grasslands in the greenhouse gas budget of the European continent. [ABSTRACT FROM AUTHOR]

The Ozone DEposition Model (ODEM) was developed for national scale modeling of total and fractional ozone fluxes to grasslands and wheat using high-resolution gridded input data. The aim of this study was to improve the preliminary version 1.1 to enable season-long simulations by introducing a new parameterization of leaf area index (LAI), and the effect of soil moisture on soil surface resistance, and by refining the descriptions of friction velocity, u&ast;, stability correction function, and all resistances depending on these parameters. Version 1.2 was tested by comparing simulation results with field measurements over grassland at Braunschweig, Germany, and wheat at Comun Nuovo, Lombardy, Italy. These comparisons showed that the simulation of ozone flux and u* for grassland was greatly improved by the modifications, yielding a root mean square error for model vs. simulation of 0.056 ppb m s−1, as compared to 0.106 ppb m s−1 obtained with the original model. Atmospheric, boundary layer, and in-canopy resistances, which all depend on u*, increased as a result of the combined modifications. For wheat, the agreement between simulated and measured ozone flux was good under wet conditions, but less during a phase characterized by drying soils. It is suggested that in-canopy processes, which are uncertain in the model, become more important under these conditions. The application of the model using 6-year ozone and meteorological data from a site in southern Switzerland (Cadenazzo) revealed that the monthly cumulative stomatal ozone flux for grassland remained more stable across the growing season than for wheat because of less variation in green LAI. Highest stomatal ozone uptake in wheat occurred during anthesis and declined later due to decreasing green LAI. In both grassland and wheat, cumulative seasonal ozone uptake was less variable between years than was the AOT40 index. The results demonstrate the improvements in ODEM 1.2, and they underline the importance of species-specific parameterizations of plant development. But it is also concluded that for high-resolution modeling of ozone fluxes the overall quality of model outputs may critically depend on the quality of an extensive set of site-specific biological, climatic, and edaphic input data. [Copyright &y& Elsevier]

The reduction of N fertilization in agriculture as part of the Farm to Fork (F2F) strategy plays a central role in the integrated nutrient management action plan of the European Commission. However, the implications of this strategy for mitigating N losses and possible side-effects on grassland yields under global change are largely unknow. We examined how a 20% reduction in N fertilization according to the F2F strategy is likely to impact yields, N 2 O emissions and N leaching of four intensively managed temperate grasslands in the Alpine region, two of them located in Switzerland, the other two in Germany. Following automatic data-driven calibration supported by inverse modeling and a cross-validation step, the process-based model DayCent was used for conducting the analysis. Global change scenarios under the representative concentration pathways (RCPs) 4.5 and 8.5 and a baseline scenario (current climate) were created for the time frame 2041–2060 with the help of the stochastic weather generator LARS-WG. Our results indicated that, under current conditions of climate and CO 2 levels (400 ppm), a 20% decrease in N fertilization would lead to a 5% drop in yields, but also in a 15% decline in N 2 O emissions and a 21% decline in N leaching (largely as NO 3 −). Under global change conditions (i.e. , climate change and higher atmospheric CO 2 levels), we found that increased yields, mainly induced by higher CO 2 levels, are likely to compensate for yield losses resulting from the reduction in N fertilization. In addition, we found that the effectiveness of the F2F strategy to mitigate N losses is likely to be preserved under global change, still with stronger effect on N leaching. The F2F-induced decline in N losses was stronger when the latter were expressed per unit of harvested dry matter, i.e. , up to 17% for N 2 O and up to 42% for N leaching. Although significant, these abatements in N losses are still below the 50% reduction level envisaged by the F2F strategy. Actions related to other axes of the strategy (e.g. , sustainable food consumption) will be necessary to further reduce N fertilization and, therefore, to reach this ambitious goal. Our results highlight the usefulness of models in accounting for interacting effects of global change and mitigation practices on multiple ecosystem services of grasslands. They allow quantification of the impact of new policies. [Display omitted] • Reducing N fertilization and losses plays a central role in the EU's Farm to Fork (F2F) strategy. • Possible side effects on yields of Alpine grasslands were quantified using a mechanistic model. • Yield losses due to reduced N fertilization are offset by positive effects of rising CO 2 levels. • Yield-scaled N losses as N 2 O and leaching tend to decrease in future scenarios with global change and the F2F strategy. • The impact of integrating all aspects of the F2F strategy should be further investigated. [ABSTRACT FROM AUTHOR]

Abstract: In order to analyze impacts of climate change on managed grassland systems and to project potential changes in farmers’ management practices in response to altered climatic conditions, we develop a modeling approach that integrates a process-based grassland model into an economic model. This economic model describes farmers’ decision making with respect to input use and accounts for production levels, production risks, fodder quality as determined by the grassland composition, and environmental protection. We apply the bio-economic model to an intensively managed grassland system with a geographic focus on the Swiss Plateau. Our results show an increase of future production risks in grassland production due to climate change. Projected changes in yield levels, grassland composition and optimal responses of risk-averse farmers are dependent on the assumptions concerning cross-compliance obligations, forage quality and particularly on the assumed effect of elevated CO2 concentrations: Grasslands yields will increase under future climatic conditions only if the benefits of rising atmospheric CO2 concentrations are taken into account. Without this potential benefit, climate change will lead to less intensive input use and lower grassland yields. [ABSTRACT FROM AUTHOR]

• Earlier onset of pre-alpine cut grassland growing season entails shifts to earlier cutting dates and more cuts per year. • Dynamic simulation of cutting dates can tackle these shifts if temperature and soil moisture are considered. • Climate change increase pre-alpine grassland yields only if growth is not limited by soil moisture and nitrogen. The productivity of permanent temperate cut grasslands is mainly driven by weather, soil characteristics, botanical composition and management. To adapt management to climate change, adjusting the cutting dates to reflect earlier onset of growth and expansion of the vegetation period is particularly important. Simulations of cut grassland productivity under climate change scenarios demands management settings to be dynamically derived from actual plant development rather than using static values derived from current management operations. This is even more important in the alpine region, where the predicted temperature increase is twice as high as compared to the global or Northern Hemispheric average. For this purpose, we developed a dynamic management module that provides timing of cutting and manuring events when running the biogeochemical model LandscapeDNDC. We derived the dynamic management rules from long-term harvest measurements and monitoring data collected at pre-alpine grassland sites located in S-Germany and belonging to the TERENO monitoring network. We applied the management module for simulations of two grassland sites covering the period 2011–2100 and driven by scenarios that reflect the two representative concentration pathways (RCP) 4.5 and 8.5 and evaluated yield developments of different management regimes. The management module was able to represent timing of current management operations in high agreement with several years of field observations (r² > 0.88). Even more, the shift of the first cutting dates scaled to a +1 °C temperature increase simulated with the climate change scenarios (−9.1 to −17.1 days) compared well to the shift recorded by the German Weather Service (DWD) in the study area from 1991−2016 (−9.4 to −14.0 days). In total, the shift in cutting dates and expansion of the growing season resulted in 1−2 additional cuts per year until 2100. Thereby, climate change increased yields of up to 6 % and 15 % in the RCP 4.5 and 8.5 scenarios with highest increases mainly found for dynamically adapted grassland management going along with increasing fertilization rates. In contrast, no or only minor yield increases were associated with simulations restricted to fertilization rates of 170 kg N ha−1 yr−1 as required by national legislations. Our study also shows that yields significantly decreased in drought years, when soil moisture is limiting plant growth but due to comparable high precipitation and water holding capacity of soils, this was observed mainly in the RCP 8.5 scenario in the last decades of the century. [ABSTRACT FROM AUTHOR]

• A model of the community dynamics of semi-natural grasslands is presented in detail. • The model was parameterized for species often observed in the Jura Mountains. • Management is a key driver of the simulated composition of the multi-species sward. • Initial community structure has a low impact at long-term on functional composition. Permanent grasslands host a high plant diversity, which sustains many ecosystem services. Thus, understanding how composition of the plant community responds to different management practices under given soil and climatic conditions is crucial for making best use of grasslands. modeling approaches may be used to explain the manifold interactions involved to sustain this diversity. We developed the dynamic, process-based ecological model DynaGraM to simulate the seasonal aboveground vegetation dynamics of semi-natural grasslands. The model allows specifying plant community by any number of species. The predictive power of the model was assessed by simulating the dynamics of a virtual mountain grassland in response to four typical management scenarios under constant climatic conditions over several decades. In our experiments, we modelled an assemblage of seven species representing contrasted plant functional types. We compared model outputs to compositions inferred from floristic records conducted in the French Jura Mountains. Irrespective of initial conditions, the simulated community converged to four distinct compositions that primarily reflected management. Overall, the results matched the functional composition inferred for each of the scenarios from the botanical records. Convergence in functional composition was reached in less than 15 years under grazing scenarios, but not less than 50 years under mowing scenarios. At quasi-equilibrium, the highest vegetation diversity was obtained for extensive grazing and the lowest for extensive mowing. Overall, this study introduces a novel and relatively simple approach to model competition and adaptation processes in plant community dynamics, thus providing a response to the key challenge of modeling multi-species grasslands. [ABSTRACT FROM AUTHOR]

Pre-alpine grasslands provide important economic value via fodder used for milk and meat production. Grassland soils also support environmental key functions such as carbon and nitrogen storage, water retention, erosion control and biodiversity. At present, these functions are jeopardized by climate change, which is likely to be accelerated in coming decades. Beside climate change, management decisions (most important cutting and manuring frequency/amount) have a high impact on grassland yields and soil C and N dynamics. In pre-alpine regions climate change is increasing the length of the growing season mainly due to an earlier start in spring (Chang et al. 2017). Together with later autumn senescence, higher temperatures, higher CO2 concentrations and changed soil water and nutrient availability this can lead to significant changes in biomass development throughout the year. Under real field conditions, the farmer cuts the grass on demand and influenced by biomass development as well as climate and soil conditions. With an earlier start of the growing season farmers likely do the first cut earlier, which will also influence timing of further cutting and manuring events throughout the year. Similarly, drought will likely cause a delay in cutting. Thus, instead of using fixed management dates (for cutting and manuring) derived from current climate conditions, within long term climate change scenarios (e.g. RCP4.5, RCP 8.5), it is necessary to dynamically fit the timing of management practices depending on plant development as affected by predicted climate conditions.A new management module for the process-based biogeochemical model LandscapeDNDC (Kraus et al., 2014; Haas et al., 2013; Kiese et al., 2011), was designed and implemented which fulfills this topic by imitating an intensive managing farmer. Depending on simulated aboveground biomass development and detailed rule-sets, timing of grassland management (cutting and manuring) are set dynamically over the time of climate change scenario studies.The new management module was applied on two different pre-alpine grassland sites for which comprehensive data on management and yields were available. At first, the module was calibrated and successfully validated for the time period of measurements; i.e. 2012-2016. It was then applied on 90 years of climate change scenario simulations with the representative concentration pathways (RCP) 4.5 and 8.5 and comparing grassland C and N dynamics with a scenario run based on static management i.e. fixed dates.Results show that climate change affects grassland growth of especially during the start of the growing season with significant earlier first cutting dates particularly for RCP 8.5. Overall, the carbon and nitrogen stocks decrease with climate change highlighting a risk on soil fertility and thus productivity of montane grassland soils. [ABSTRACT FROM AUTHOR]