Search

Future climate change is expected to significantly alter the growth of vegetation in grassland systems, in terms of length of the growing season, forage production, and climate-altering gas emissions. The main objective of this work was, therefore, to simulate the future impacts of foreseen climate change in the context of two pastoral systems in the central Italian Apennines and test different adaptation strategies to cope with these changes. The PaSim simulation model was, therefore, used for this purpose. After calibration by comparison with observed data of aboveground biomass (AGB) and leaf area index (LAI), simulations were able to produce various future outputs, such as length of growing season, AGB, and greenhouse gas (GHG) emissions, for two time windows (i.e., 2011–2040 and 2041–2070) using 14 global climate models (GCMs) for the generation of future climate data, according to RCP (Representative Concentration Pathways) 4.5 and 8.5 scenarios under business-as-usual management (BaU). As a result of increasing temperatures, the fertilizing effect of CO2, and a similar trend in water content between present and future, simulations showed a lengthening of the season (i.e., mean increase: +8.5 and 14 days under RCP4.5 and RCP8.5, respectively, for the period 2011–2040, +19 and 31.5 days under RCP4.5 and RCP8.5, respectively, for the period 2041–2070) and a rise in forage production (i.e., mean biomass peak increase of the two test sites under BaU: +53.7% and 62.75% for RCP4.5. and RCP8.5, respectively, in the 2011–2040 period, +115.3% and 176.9% in RCP4.5 and RCP8.5 in 2041–2070, respectively,). Subsequently, three different alternative management strategies were tested: a 20% rise in animal stocking rate (+20 GI), a 15% increase in grazing length (+15 GL), and a combination of these two management factors (+20 GI × 15 GL). Simulation results on alternative management strategies suggest that the favorable conditions for forage production could support the increase in animal stocking rate and grazing length of alternative management strategies (i.e., +20 GI, +15 GL, +20 GI × 15 GL). Under future projections, net ecosystem exchange (NEE) and nitrogen oxide (N2O) emissions decreased, whereas methane (CH4) rose. The simulated GHG future changes varied in magnitude according to the different adaptation strategies tested. The development and assessment of adaptation strategies for extensive pastures of the Central Apennines provide a basis for appropriate agricultural policy and optimal land management in response to the ongoing climate change. [ABSTRACT FROM AUTHOR]

Simulating the dynamics of plant species or types in grassland communities remains an open area of research for which the Community Simulation Model (CoSMo) offers novel approaches. The grassland model ModVege was first parameterised based on a functional vegetation typology, in which types "A" and "B" include fast-growing grass species with a phenology-dependent nutrient-capture strategy inherent to fertile grasslands, while the nutrient conservation strategy and late flowering characterise the other types as "b". ModVege was then coupled to the CoSMo rule set to dynamically simulate the relative abundance of plant functional types or individual species, assessed across fertilised and unfertilised, abandoned and mown conditions in a grassland site of the Massif Central of France. While for the simulation of aboveground biomass, model performance is not unambiguously linked to explicit consideration of plant diversity, the simulation of relative abundance for the whole community is satisfactory (relative root mean square error of ~13–25% when simulating functional types and ~28–52% when simulating species). This study extends previous studies by coupling CoSMo, for the first time, to a grassland-specific model and applying it to conditions (long-term observations, extended number of plant species, absence of fertilisation, frequent mowing and abandonment) never investigated before. [ABSTRACT FROM AUTHOR]

Climate and management affect grassland plant diversity but studies vary regarding the magnitude of changes in plant species richness. Here we develop a comprehensive understanding of species richness modification due to management (mowing) and climate (warming) variations worldwide, and present the results of two meta-analyses from 999 and 1793 records (articles). Recorded articles had at least one experiment with a case-control design. The results show that both mowing (43 articles) and warming (34 articles) modify species richness, which on average increased by c. 32% with once-a-year mowing (against no mowing) and declined by c. 13% with warming (against ambient temperature). Our meta-analysis on the mowing regime supports the humped-back model, with one or two cuts per year being the level of disturbance optimising species richness. We also observed that warming-induced reduction in species richness is lower in dry climates (< 300 mm yr-1) and at low elevations (< 1000 m a.s.l.). Where available, we accounted for harvested biomass as a concomitant variable and we found that overall it decreased by c. 21% (mowing) and increased by c. 11% (warming). The evidence provided of an opposite response of species richness and harvested biomass to disturbance is consistent with the competitive-exclusion hypothesis of negatively correlated patterns between the two outcomes (high taxonomic diversity with low biomass production, and vice versa). The reported difficulties in finding representative studies in previous meta-analyses and in the present ones highlight the need to orient future research towards long-term experiments on the combined effects of mowing and warming for a more robust inference of environmental and management constraints on grassland performance. [ABSTRACT FROM AUTHOR]

A potential strategy for mitigating nitrous oxide (N2O) emissions from permanent grasslands is the partial substitution of fertilizer nitrogen (Nfert) with symbiotically fixed nitrogen (Nsymb) from legumes. The input of Nsymb reduces the energy costs of producing fertilizer and provides a supply of nitrogen (N) for plants that is more synchronous to plant demand than occasional fertilizer applications. Legumes have been promoted as a potential N2O mitigation strategy for grasslands, but evidence to support their efficacy is limited, partly due to the difficulty in conducting experiments across the large range of potential combinations of legume proportions and fertilizer N inputs. These experimental constraints can be overcome by biogeochemical models that can vary legume‐fertilizer combinations and subsequently aid the design of targeted experiments. Using two variants each of two biogeochemical models (APSIM and DayCent), we tested the N2O mitigation potential and productivity of full factorial combinations of legume proportions and fertilizer rates for five temperate grassland sites across the globe. Both models showed that replacing fertilizer with legumes reduced N2O emissions without reducing productivity across a broad range of legume‐fertilizer combinations. Although the models were consistent with the relative changes of N2O emissions compared to the baseline scenario (200 kg N ha−1 yr−1; no legumes), they predicted different levels of absolute N2O emissions and thus also of absolute N2O emission reductions; both were greater in DayCent than in APSIM. We recommend confirming these results with experimental studies assessing the effect of clover proportions in the range 30–50% and ≤150 kg N ha−1 yr−1 input as these were identified as best‐bet climate smart agricultural practices. Key Points: A partial substitution of fertilizer nitrogen with symbiotically fixed nitrogen could mitigate nitrous oxide (N2O) emissions in grasslands by around 130 Gg yr−1Experimentally testing this mitigation option is challenging so modeling offers means to identify the optimum legume/fertilizer combinationThe models showed that net benefits to N2O mitigation and yield can be achieved across a wide range of legume/fertilizer combinations [ABSTRACT FROM AUTHOR]

Process‐based crop and grassland models estimating carbon (C) and nitrogen (N) dynamics are widely used to investigate best management practices in agriculture. They integrate several processes in a complex structure, but studies where modules corresponding to specific processes extracted from the whole model structure are assessed independently are uncommon. With the support of documented aerobic incubation trials in manure‐amended soils, a sensitivity analysis was performed on the C–N cycling processes of four modules (MOD1–4), corresponding to the models APSIM, EPIC, FASSET and STICS. The results showed that the parameter 'substrate use efficiency' had the most effect on the predicted values of net CO2 emissions and net N mineralization, together with the C/N ratio of the soil microbial biomass. They explained 74–75% on average of both output variances, whereas parameters determining manure C and N partitioning and first‐order decomposition constants of manure pools explained, on average, an additional 17–19%. Efforts should be focused on calibrating these parameters for more accurate simulations. The greater sensitivity of both outputs to parameters related to manure pools in more complex modules (MOD2–4) facilitates their adaptation to specific contexts, whereas MOD1 probably requires that parameters related to soil pools are also adapted to specific applications. Parameter interactions were limited, becoming noticeable only in situations of N‐limited soil organic matter decomposition. Models MOD1 and MOD3 allowed the C/N ratio of the soil microbial biomass to vary temporarily; therefore, they were less sensitive to mineral N availability and more easily adapted to a wide range of situations. This study provides essential information to support the development of state‐of‐the‐art biogeochemical models. Highlights: We compared four C–N modules embedded in process‐based biogeochemical models.We used sensitivity analysis to assess the simulation of manure decomposition in soil.We identified a few parameters that influenced CO2 emissions and N mineralization.We found that substrate use efficiency explained most of the output variance for all models. [ABSTRACT FROM AUTHOR]

Highlights • We assessed the grassland model CoSMo whit data from different plant mixtures. • The model was able to reproduce time trends of species composition and yield. • Simulations were performed to analyse climate change impact on grassland dynamics. Abstract Plant diversity supports the high aptitude of grassland covers to provide fodder production for animal feeding and contribute to the storage of carbon, while also granting pollination and aesthetics of landscapes. This ability depends on the management intensity of the grassland system, physical constraints and climatic characteristics. Most of current grassland models simulating the impact of weather conditions, soil fertility and the intensity of use of grassland systems (by grazing and/or mowing) on fodder production and carbon-nitrogen fluxes inherit eco-physiological and biophysical details from crop models without considering explicitly temporal changes in taxonomic and functional composition. The dynamic grassland model CoSMo (COmmunity Simulation MOdel) includes a set of rules to simulate explicitly seasonal changes in species composition of managed grasslands under various soil, climate and management drivers, and it is consistent with the degree of complexity of the most generic crop simulators. The incorporation of CoSMo functionalities into the standalone crop simulators CropSyst and WOFOST is proposed as a way to: (i) reduce the uncertainty in estimations of harvested aboveground biomass (AGB) and (ii) simulate dynamically the relative abundance of species (for respectively the whole community and individual species). Considering three mixtures of grassland species (with increasing complexity from Mix 1 to Mix 3) in a mown hay meadow in central Italy (Massa Marittima, 43° 03′ N, 10° 53′ E, 380 m a.s.l.), we show that CoSMo overall improved the model ability to reproduce observed AGB in Mix 1 and 2 (e.g. with CropSyst in Mix 2 relative root mean square error [ RRMSE ] lowered from 35.01 to 25.27%) while the model performance for Mix 3 appeared as not unambiguously linked to considering plant diversity. An assessment of the relative abundance estimates for the whole community indicates 30%< RRMSE <40% with both CoSMo-coupled CropSyst and WOFOST in Mix 1 and Mix 2, while it increases up to ∼60% in Mix 3. The consequences of explicitly accounting for plant diversity for simulated grassland outputs depend on the conditions evaluated, which require further studies. However, our results suggest that grassland modelling omitting plant diversity dynamics are likely over- or underestimating harvested biomass of the plant community, thus biasing projections of future fodder production and estimates of animal feed supplies. This work proves for the first time that CoSMo can support the simulation of grassland systems beyond its theoretical framework. [ABSTRACT FROM AUTHOR]

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented).Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance. [ABSTRACT FROM AUTHOR]

Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. [ABSTRACT FROM AUTHOR]

Abstract: The Pasture Simulation model (PaSim) was used to simulate agronomic and environmental services at 12 grassland sites in France, comparing near past climate conditions (1970–1999) and projections for near (2020–2049) and far future (2070–2099). Modelled climate change impacts were assessed using statistical and threshold-based analysis on managed (intensive, extensive) grasslands (permanent, sown), comparing shallow and deep soils, and for an ensemble of emission scenarios, climate models, and downscaling/initialization methods. Results show a significant drift of all sites towards more arid climates by the end of the century. Significant reductions in annual water drainage and herbage protein content are projected, together with new opportunities for annual and seasonal herbage production, in spring and winter especially. Simulated future conditions also show an increased interannual and seasonal variability of production. Contrary to expectations, current natural conditions reflecting large water availability are not expected to reduce future risks of negative climate change impacts on grassland systems. Notably, milk production from aftermath grazing of permanent grasslands established on deep soils at Mirecourt (humid site) is estimated to fall down below one-third of the current median value in four out of 30 years (∼13%) for 2070–2099, whereas similar shortfalls were not observed with the baseline climate. Balancing risks and opportunities, permanent extensive grasslands can be viewed as a trade-off between the continuity of grassland service provision and the mitigation of greenhouse gas emissions. [Copyright &y& Elsevier]

Associated with livestock farming, grasslands with a high diversity of plant species are at the core of low-input fodder production worldwide. However, this Special Issue does not fully consider climate-induced biodiversity change and the extent to which population growth, urbanisation, land-use change, consumption lifestyles and resource exploitation threaten grassland biodiversity as key factors directly or indirectly associated with climate change. For instance, innovative systems at the interface of grassland and cereal production hold promise for reconciling production objectives with the preservation of biodiversity and soil-water-air resources, and pave the way for a multifunctional, sustainable and more climate-resilient agriculture. [Extracted from the article]

Semi-natural grasslands are particularly important in mountainous areas of Romania, being the only source of forage for many farmers. The aim of this study was to investigate the changes in forage quantity and quality as a result of Urea Ammonium nitrate (UAN) liquid fertilization. The experiment was carried out in the eastern part of Apuseni Mountains, Romania on a Festuca rubra L.-Agrostis capillaris L. grassland located at 1240 m altitude. Studies were made over three years of experimental trial (2014–2016) and covered four experimental plots in three replicates, as follows: V1–control plot, unfertilized; V2–plot fertilized with 50 kg UAN ha−1 year−1; V3–plot fertilized with 75 kg UAN ha−1 year−1, and V4–plot fertilized with 100 kg UAN ha−1 year−1. The experimental plots were harvested once per year and the botanical composition, dry matter yield and forage quality were assessed. Our results showed important changes in forage quantity, quality and diversity as a result of UAN fertilization. Starting from the second experimental year the dominance/co-dominance ratio changed favoring the species from Poaceae family. Dry matter increased as a result of UAN fertilization but forage quality was negatively affected by the higher percentage of participation of species from other botanical families which have higher crude fiber content and lower crude protein. Based on our results we recommend moderate fertilization with UAN up to 50 kg UAN ha−1 year−1 for semi-natural grasslands located in soil-climatic conditions similar to those in our experiment. [ABSTRACT FROM AUTHOR]

Multi-species grasslands are reservoirs of biodiversity and provide multiple ecosystem services, including fodder production and carbon sequestration. The provision of these services depends on the control exerted on the biogeochemistry and plant diversity of the system by the interplay of biotic and abiotic factors, e.g., grazing or mowing intensity. Biogeochemical models incorporate a mechanistic view of the functioning of grasslands and provide a sound basis for studying the underlying processes. However, in these models, the simulation of biogeochemical cycles is generally not coupled to simulation of plant species dynamics, which leads to considerable uncertainty about the quality of predictions. Ecological models, on the other hand, do account for biodiversity with approaches adopted from plant demography, but without linking the dynamics of plant species to the biogeochemical processes occurring at the community level, and this hampers the models' capacity to assess resilience against abiotic stresses such as drought and nutrient limitation. While setting out the state-of-the-art developments of biogeochemical and ecological modelling, we explore and highlight the role of plant diversity in the regulation of the ecosystem processes underlying the ecosystems services provided by multi-species grasslands. An extensive literature and model survey was carried out with an emphasis on technically advanced models reconciling biogeochemistry and biodiversity, which are readily applicable to managed grasslands in temperate latitudes. We propose a roadmap of promising developments in modelling. [ABSTRACT FROM AUTHOR]

• Grassland model PaSim used to simulate a mown grassland system in central France. • Climate-dependent timeseries of optimal forage yield generated. • Remarkable increase in simulated forage yield (>29%) observed in the long term. • Annual forage yield values robustly correlated with teleconnection patterns. • Skillful seasonal forecasts of forage yield attained from climatic predictors. Climate Services (CS) provide support to decision makers across socio-economic sectors. In the agricultural sector, one of the most important CS applications is to provide timely and accurate yield forecasts based on climate prediction. In this study, the Pasture Simulation model (PaSim) was used to simulate, for the period 1959–2015, the forage production of a mown grassland system (Laqueuille, Massif Central of France) under different management conditions, with meteorological inputs extracted from the SAFRAN atmospheric database. The aim was to generate purely climate-dependent timeseries of optimal forage production, a variable that was maximized by brighter and warmer weather conditions at the grassland. A long-term increase was observed in simulated forage yield, with the 1995–2015 average being 29% higher than the 1959–1979 average. Such increase seems consistent with observed rising trends in temperature and CO 2 , and multi-decadal changes in incident solar radiation. At interannual timescales, sea surface temperature anomalies of the Mediterranean (MED), Tropical North Atlantic (TNA), equatorial Pacific (El Niño Southern Oscillation) and the North Atlantic Oscillation (NAO) index were found robustly correlated with annual forage yield values. Relying only on climatic predictors, we developed a stepwise statistical multi-regression model with leave-one-out cross-validation. Under specific management conditions (e.g., three annual cuts) and from one to five months in advance, the generated model successfully provided a p -value<0.01 in correlation (t -test), a root mean square error percentage (%RMSE) of 14.6% and a 71.43% hit rate predicting above/below average years in terms of forage yield collection. This is the first modeling study on the possible role of large-scale oceanic–atmospheric teleconnections in driving forage production in Europe. As such, it provides a useful springboard to implement a grassland seasonal forecasting system in this continent. [ABSTRACT FROM AUTHOR]

Climate Services (CS) provide support to decision makers across socio-economic sectors. In the agricultural sector, one of the most important CS applications is to provide timely and accurate yield forecasts based on climate prediction. In this study, the Pasture Simulation model (PaSim) is used to simulate, for the period 1959-2015, the forage production of a mown grassland system (Laqueuille, Massif Central of France) under different management conditions, with meteorological inputs extracted from the SAFRAN atmospheric database. The aim is to generate purely climate-dependent time series of optimal forage production, a variable that is found to maximize the years of brighter and warmer weather conditions at the grassland.In the long term, a remarkable increase in simulated forage yield (>29%) is obtained in all simulations between 1959-1979 and 1995-2015. Such increase seems consistent with observed rising trends in temperature and CO2 and multi-decadal changes in incident solar radiation. At interannual timescales, Sea Surface Temperature anomalies of the Mediterranean (MED), Tropical North Atlantic (TNA), equatorial Pacific (El Niño Southern Oscillation), and the North Atlantic Oscillation (NAO) index, appear robustly correlated with annual forage yield values. Relying on climatic predictors uniquely, a stepwise statistical multi-regression model with leave-one-out cross-validation is developed in this work. Under specific management conditions (e.g., 3 annual cuts) and from 1 to 5 months in advance, the generated model successfully provides a p-value<0.01 in correlation (t test), a root mean square error (RMSE) percentage of 14.6% (1.24 t DM ha-1) and a 71.43% hit rate predicting above/below average years in terms of forage yield collection. These results may help in stimulating the debate about understanding the climate mechanisms at play in European grasslands and provide a useful springboard to implement a grassland seasonal forecasting system in France. [ABSTRACT FROM AUTHOR]

Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grassland systems caused by changes in management practices. To support agricultural policies, it is however important to contrast the responses of alternative models, which can differ greatly in their treatment of key processes and in their response to management. We applied eight biogeochemical models at five grassland sites (in France, New Zealand, Switzerland, United Kingdom and United States) to compare the sensitivity of modelled C and N fluxes to changes in the density of grazing animals (from 100% to 50% of the original livestock densities), also in combination with decreasing N fertilization levels (reduced to zero from the initial levels). Simulated multi-model median values indicated that input reduction would lead to an increase in the C sink strength (negative net ecosystem C exchange) in intensive grazing systems: −64 ± 74 g C m −2  yr −1 (animal density reduction) and −81 ± 74 g C m −2  yr −1 (N and animal density reduction), against the baseline of −30.5 ± 69.5 g C m −2  yr −1 (LSU [livestock units] ≥ 0.76 ha −1  yr −1 ). Simulations also indicated a strong effect of N fertilizer reduction on N fluxes, e.g. N 2 O-N emissions decreased from 0.34 ± 0.22 (baseline) to 0.1 ± 0.05 g N m −2  yr −1 (no N fertilization). Simulated decline in grazing intensity had only limited impact on the N balance. The simulated pattern of enteric methane emissions was dominated by high model-to-model variability. The reduction in simulated offtake (animal intake + cut biomass) led to a doubling in net primary production per animal (increased by 11.6 ± 8.1 t C LSU −1  yr −1 across sites). The highest N 2 O-N intensities (N 2 O-N/offtake) were simulated at mown and extensively grazed arid sites. We show the possibility of using grassland models to determine sound mitigation practices while quantifying the uncertainties associated with the simulated outputs. [ABSTRACT FROM AUTHOR]

Highlights: [•] We simulate grassland processes over large areas for climate change impact studies. [•] We parallelize simulations with pixel-based Pasture Simulation model (PaSim). [•] We perform simulations with 8×8km resolution for metropolitan France (∼10,000pixels). [•] We report 25h (speedup of 200) for the simulation on a 200-processor cluster. [ABSTRACT FROM AUTHOR]

Highlights: [•] We run the Morris sensitivity-analysis method to the Pasture Simulation model. [•] Both uniform and normal distributions are employed to 28 vegetation parameters. [•] Sensitivity of nine outputs is examined at seven grassland sites in Europe. [•] Nine influential parameters are identified for model calibration. [•] We study the plasticity of the model with climate conditions. [Copyright &y& Elsevier]