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Fan, F., Henriksen, C. B., & Porter, J. (2018). Relationship between stoichiometry and ecosystem services: A case study of it organic farming systems. Ecological Indicators, 85, 400–408.
Abstract: Over the past five decades, the delivery of global Ecosystem Services (ES) has diminished and this has been driven partly by anthropogenic activities. Agro-ecosystems cover almost 40% of the terrestrial surface on Earth, and have been considered as one of the most significant ecological experiments with a potential to both contribute to and mitigate global ES loss. In the present study, six different ES (food and fodder production, carbon sequestration, biological pest control, soil water storage, nitrogen regulation and soil formation) were quantified in various organic farming systems and the hypothesis that there is a link between these ES and C:N, C:O and H:O stoichiometric ratios in farming systems was experimentally tested. The results show that different ES are correlated with the stoichiometric ratios to different extents. There are significant positive linear correlations between C:N stoichiometric ratios and all measured ES in the investigated organic farming systems, while not all the ES are correlated with the C:O and H:O ratios. This study has expanded the horizons of stoichiometry by linking a fundamental chemical property of molecules with an emergent property of organic farming systems, namely their ecosystem service provision.
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Francone, C., Cassardo, C., Richiardone, R., & Confalonieri, R. (2012). Sensitivity Analysis and Investigation of the Behaviour of the UTOPIA Land-Surface Process Model: A Case Study for Vineyards in Northern Italy. Boundary-Layer Meteorology, 144(3), 419–430.
Abstract: We used sensitivity-analysis techniques to investigate the behaviour of the land-surface model UTOPIA while simulating the micrometeorology of a typical northern Italy vineyard (Vitis vinifera L.) under average climatic conditions. Sensitivity-analysis experiments were performed by sampling the vegetation parameter hyperspace using the Morris method and quantifying the parameter relevance across a wide range of soil conditions. This method was used since it proved its suitability for models with high computational time or with a large number of parameters, in a variety of studies performed on different types of biophysical models. The impact of input variability was estimated on reference model variables selected among energy (e.g. net radiation, sensible and latent heat fluxes) and hydrological (e.g. soilmoisture, surface runoff, drainage) budget components. Maximum vegetation cover and maximum leaf area index were ranked as the most relevant parameters, with sensitivity indices exceeding the remaining parameters by about one order of magnitude. Soil variability had a high impact on the relevance of most of the vegetation parameters: coefficients of variation calculated on the sensitivity indices estimated for the different soils often exceeded 100 %. The only exceptions were represented by maximum vegetation cover and maximum leaf area index, which showed a low variability in sensitivity indices while changing soil type, and confirmed their key role in affecting model results.
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Lotze-Campen, H., von Lampe, M., Kyle, P., Fujimori, S., Havlik, P., van Meijl, H., et al. (2014). Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison. Agric. Econ., 45(1), 103–116.
Abstract: Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Intercomparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, for example, from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an ambitious mitigation scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in a high-emission scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.
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Mitter, H., Techen, A. - K., Sinabell, F., Helming, K., Kok, K., Priess, J. A., et al. (2019). A protocol to develop Shared Socio-economic Pathways for European agriculture. J. Environ. Manage., 252, Unsp 109701.
Abstract: Moving towards a more sustainable future requires concerted actions, particularly in the context of global climate change. Integrated assessments of agricultural systems (IAAS) are considered valuable tools to provide sound information for policy and decision-making. IAAS use storylines to define socio-economic and environmental framework assumptions. While a set of qualitative global storylines, known as the Shared Socio-economic Pathways (SSPs), is available to inform integrated assessments at large scales, their spatial resolution and scope is insufficient for regional studies in agriculture. We present a protocol to operationalize the development of Shared Socio-economic Pathways for European agriculture – Eur-Agri-SSPs- to support IAAS. The proposed design of the storyline development process is based on six quality criteria: plausibility, vertical and horizontal consistency, salience, legitimacy, richness and creativity. Trade-offs between these criteria may occur. The process is science-driven and iterative to enhance plausibility and horizontal consistency. A nested approach is suggested to link storylines across scales while maintaining vertical consistency. Plausibility, legitimacy, salience, richness and creativity shall be stimulated in a participatory and interdisciplinary storyline development process. The quality criteria and process design requirements are combined in the protocol to increase conceptual and methodological transparency. The protocol specifies nine working steps. For each step, suitable methods are proposed and the intended level and format of stakeholder engagement are discussed. A key methodological challenge is to link global SSPs with regional perspectives provided by the stakeholders, while maintaining vertical consistency and stakeholder buy-in. We conclude that the protocol facilitates systematic development and evaluation of storylines, which can be transferred to other regions, sectors and scales and supports intercomparisons of IAAS.
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Liu, X., Lehtonen, H., Purola, T., Pavlova, Y., Rötter, R., & Palosuo, T. (2016). Dynamic economic modelling of crop rotations with farm management practices under future pest pressure. Agricultural Systems, 144, 65–76.
Abstract: Agricultural practice is facing multiple challenges under volatile commodity markets, inevitable climate change, mounting pest pressure and various other environment-related constraints. The objective of this research is to present a dynamic optimization model of crop rotations and farm management and show its suitability for economic analysis over a 30 year time period. In this model, we include management practices such as fertilization, fungicide treatment and liming, and apply it in a region in Southwestern Finland. Results show that (i) growing pest pressure favours the cultivation of wheat-oats and wheat-oilseeds combinations, while (ii) market prices largely determine the crops in the rotation plan and the specific management practices adopted. The flexibility of our model can also be utilized in evaluating the value of other management options such as new cultivars under different projections of future climate and market conditions.
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