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A model-based assessment of the environmental impact of land-use change across scales in Southern Amazonia

机译：基于模型的南亚马逊州土地利用变化对环境影响的评估

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This article describes the design of a new model-based assessment framework to identify and analyse possible future trajectories of agricultural development and their environmental consequences within the states of Mato Grosso and Para in Southern Amazonia, Brazil. The objective is to provide a tool for improving the information basis for scientists and policy makers regarding the effects of global change and national environmental policies on land-use change and the resulting impacts on the loss of natural vegetation, greenhouse gas emissions, hydrological processes, and soil erosion within the region. For this purpose, the framework combines the regional land-use models, LandSHIFT and alucR, the farm-level model, MPMAS, and the MONICA crop model, with a set of environmental impact models that are operating at the regional and watershed levels. As a first application of the framework, four scenarios with the time horizon 2030 were specified and analysed. Future land-use change will strongly depend on the interplay between the production of agricultural commodities, the agricultural intensification in terms of increasing crop yields and pasture biomass productivity, and the enforcement of environmental laws and policies. On the regional level, the scenarios with the highest increase in agricultural production in combination with weak law enforcement (Trend and Illegal Intensification) generated the highest losses in natural vegetation due to the expansion of agricultural area as well as the highest greenhouse gas emissions. Also, at the watershed level, these scenarios are characterised by the highest changes in river discharge and soil erosion that might lead to a further decline in soil fertility in the long term. Moreover, the analysis of the Sustainable Development scenario indicates that a shift in agricultural production patterns from livestock to crop cultivation, together with effective law enforcement, can effectively reduce land-use change and its negative effects on the environment. With the scenario analysis, we could illustrate that our assessment framework is capable to provide a large variety of valuable information to support the development of future land-use strategies in the study region.
机译：本文介绍了一种基于模型的新评估框架的设计，以识别和分析巴西南亚马逊州马托格罗索州和帕拉州农业发展的未来轨迹及其对环境的影响。目的是为科学家和决策者提供信息工具，以改善全球变化和国家环境政策对土地利用变化的影响以及由此对自然植被的丧失，温室气体排放，水文过程的影响，和该地区的水土流失。为此，该框架结合了区域土地使用模型LandSHIFT和alucR，农场一级模型MPMAS和MONICA作物模型，以及在区域和流域一级运行的一系列环境影响模型。作为该框架的第一个应用程序，指定并分析了时间跨度为2030的四个场景。未来土地用途的变化将在很大程度上取决于农产品的生产，提高作物产量和牧场生物量生产力方面的农业集约化以及环境法律和政策的执行之间的相互作用。在区域一级，由于农业面积的扩大以及温室气体排放量的增加，农业生产增长最高，加上执法不力（趋势和非法集约化）的情景造成自然植被的损失最大。同样，在流域一级，这些情景的特征是河流流量和土壤侵蚀的变化最大，从长远来看，这可能导致土壤肥力进一步下降。此外，对可持续发展方案的分析表明，农业生产方式从畜牧业向农作物种植的转变，加上有效的执法，可以有效减少土地用途的变化及其对环境的负面影响。通过情景分析，我们可以说明我们的评估框架能够提供大量有价值的信息，以支持研究区域未来土地利用策略的发展。

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