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Whole-Systems Analysis of Environmental and Economic Sustainability in Arable Cropping Systems: A Case Study
Ist Teil von
Agronomy (Basel), 2019-08, Vol.9 (8), p.438
Ort / Verlag
Basel: MDPI AG
Erscheinungsjahr
2019
Quelle
EZB Free E-Journals
Beschreibungen/Notizen
The long-term sustainability of crop production depends on the complex network of interactions and trade-offs between biotic, abiotic and economic components of agroecosystems. An integrated arable management system was designed to maintain yields, whilst enhancing biodiversity and minimising environmental impact. Management interventions included conservation tillage and organic matter incorporation for soil biophysical health, reduced crop protection inputs and integrated pest management strategies for enhanced biodiversity and ecosystem functions, and intercropping, cover cropping and under-sowing to achieve more sustainable nutrient management. This system was compared directly with standard commercial practice in a split-field experimental design over a six-year crop rotation. The effect of the cropping treatment was assessed according to the responses of a suite of indicators, which were used to parameterise a qualitative multi-attribute model. Scenarios were run to test whether the integrated cropping system achieved greater levels of overall sustainability relative to standard commercial practice. Overall sustainability was rated high for both integrated and conventional management of bean, barley and wheat crops. Winter oilseed crops scored medium for both cropping systems and potatoes scored very low under standard management but achieved a medium level of sustainability with integrated management. In general, high scores for environmental sustainability in integrated cropping systems were offset by low scores for economic sustainability relative to standard commercial practice. This case study demonstrates the value of a ‘whole cropping systems’ approach using qualitative multi-attribute modelling for the assessment of existing cropping systems and for predicting the likely impact of new management interventions on arable sustainability.