Schönhart, M., Schauppenlehner, T., Kuttner, M., Kirchner, M., & Schmid, E. (2016). Climate change impacts on farm production, landscape appearance, and the environment: Policy scenario results from an integrated field-farm-landscape model in Austria. Agricultural Systems, 145, 39–50.
Abstract: Climate change is among the major drivers of agricultural land use change and demands autonomous farm adaptation as well as public mitigation and adaptation policies. In this article, we present an integrated land use model (ILM) mainly combining a bio-physical model and a bio-economic farm model at field, farm and landscape levels. The ILM is applied to a cropland dominated landscape in Austria to analyze impacts of climate change and mitigation and adaptation policy scenarios on farm production as well as on the abiotic environment and biotic environment. Changes in aggregated total farm gross margins from three climate change scenarios for 2040 range between + 1% and + 5% without policy intervention” and compared to a reference situation under the current climate. Changes in aggregated gross margins are even higher if adaptation policies are in place. However, increasing productivity from climate change leads to deteriorating environmental conditions such as declining plant species richness and landscape appearance. It has to be balanced by mitigation and adaptation policies taking into account effects from the considerable spatial heterogeneity such as revealed by the ILM. (C) 2016 Elsevier Ltd. All rights reserved.
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König, H. J., Uthes, S., Schuler, J., Zhen, L., Purushothaman, S., Suarma, U., et al. (2013). Regional impact assessment of land use scenarios in developing countries using the FoPIA approach: findings from five case studies. J. Environ. Manage., 127 Suppl, S56–S64.
Abstract: The impact of land use changes on sustainable development is of increasing interest in many regions of the world. This study aimed to test the transferability of the Framework for Participatory Impact Assessment (FoPIA), which was originally developed in the European context, to developing countries, in which lack of data often prevents the use of data-driven impact assessment methods. The core aspect of FoPIA is the stakeholder-based assessment of alternative land use scenarios. Scenario impacts on regional sustainability are assessed by using a set of nine regional land use functions (LUFs), which equally cover the economic, social and environmental dimensions of sustainability. The cases analysed in this study include (1) the alternative spatial planning policies around the Merapi volcano and surrounding areas of Yogyakarta City, Indonesia; (2) the large-scale afforestation of agricultural areas to reduce soil erosion in Guyuan, China; (3) the expansion of soil and water conservation measures in the Oum Zessar watershed, Tunisia; (4) the agricultural intensification and the potential for organic agriculture in Bijapur, India; and (5) the land degradation and land conflicts resulting from land division and privatisation in Narok, Kenya. All five regions are characterised by population growth, partially combined with considerable economic development, environmental degradation problems and social conflicts. Implications of the regional scenario impacts as well as methodological aspects are discussed. Overall, FoPIA proved to be a useful tool for diagnosing regional human-environment interactions and for supporting the communication and social learning process among different stakeholder groups.
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Mueller, L., Schindler, U., Shepherd, T. G., Ball, B. C., Smolentseva, E., Hu, C., et al. (2012). A framework for assessing agricultural soil quality on a global scale. Archives of Agronomy and Soil Science, 58(sup1), S76–S82.
Abstract: This paper provides information about a novel approach of rating agricultural soil quality (SQ) and crop yield potentials consistently over a range of spatial scales. The Muencheberg Soil Quality Rating is an indicator-based straightforward overall assessment method of agricultural SQ. It is a framework covering aspects of soil texture, structure, topography and climate which is based on 8 basic indicators and more than 12 hazard indicators. Ratings are performed by visual methods of soil evaluation. A field manual is then used to provide ratings from tables based on indicator thresholds. Finally, overall rating scores are given, ranging from 0 (worst) to 100 (best) to characterise crop yield potentials. The current approach is valid for grassland and cropland. Field tests in several countries confirmed the practicability and reliability of the method. At field scale, soil structure is a crucial, management induced criterion of agricultural SQ. At the global scale, climate controlled hazard indicators of drought risk and soil thermal regime are crucial for SQ and crop yield potentials. Final rating scores are well correlated with crop yields. We conclude that this system could be evolved for ranking and controlling agricultural SQ on a global scale.
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Sanna, M., Bellocchi, G., Fumagalli, M., & Acutis, M. (2015). A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models. Env. Model. Softw., 73, 286–304.
Abstract: The use of a variety of metrics is advocated to assess model performance but correlated metrics may convey the same information, thus leading to redundancy. Starting from this assumption, a method was developed for selecting, from among a collection of performance indicators, one or more subsets providing the same information as the entire set. The method, based on the definition of “stable correlation”, was applied to 23 performance indicators of agrometeorological models, calculated on large sets of simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation. Two subsets were determined: {Squared Bias, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index, Modified Modelling Efficiency}, {Persistence Model Efficiency, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index}. The method needs corroboration but is statistically founded and can support the implementation of standardized evaluation tools. (C) 2015 Elsevier Ltd. All rights reserved.
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Rusu, T., Moraru, P., Coste, C., Cacovean, H., Chetan, F., & Chetan, C. (2014). Impact of climate change on climatic indicators in Transylvanian Plain, Romania. Journal of Food, Agriculture and Environment, 12(1), 469–473.
Abstract: The condition of land degradation in Transylvanian Plain and its effects, being the result of local extreme physical-geographical conditions, is susceptible to degradation (evidenced by the erodibility index), which overlaps the extreme climatic conditions. Thermal and hydric regime monitoring is necessary in order to identify and implement measures of adaptation to the impacts of climate change. Soil moisture and temperature regimes were evaluated using a set of 20 data logging stations positioned throughout the plain. Each station stores electronic data of ground temperature at 3 depths (10, 30, 50 cm), the humidity at the depth of 10 cm, the air temperature (at 1 m) and precipitations. Climate change in the past few years has significantly altered the climatic indicators of the Transylvanian Plain. Precipitations, although deficient in terms of annual amounts, through their regime, have a negative influence on the plant carpet. Pluvial aggressiveness index reveals, for the research period, a first peak of pluvial aggressiveness during the months of February-April, then in July and in autumn, the months of October-November. This requires special measures for soil conservation, both in autumn and early spring, soil tillage measures being recommended, which ensure the presence of plant debris and vegetation in early spring but especially in summer and autumn. Climatic indicators determined for the period 2008 – 2012 point out, in Transylvanian Plain, a semi-arid Mediterranean climate through the rain factor Lang, respectively semi-arid (in the South) – semi-wet (in the North) according to the De Martonne index. This climatic characterization requires special technological measures for soil conservation.
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