Abstract: The empirical evidence of decline in ecosystem services (ES) over the last century has reinforced the call for ES quantification, monitoring and valuation. Usually, only provisioning ES are marketable and accounted for, whereas regulating, supporting and cultural ES are typically non-marketable and overlooked in connection with land-use or management decisions. The objective of this study was to quantify and value total ES (marketable and non-marketable) of diverse production systems and management intensities in Denmark to provide a basis for decisions based on economic values. The production systems were conventional wheat (Cwheat), a combined food and energy (CFE) production system and beech forest. Marketable (provisioning ES) and non-marketable ES (supporting, regulating and cultural) ES were quantified by dedicated on-site field measurements supplemented by literature data. The value of total ES was highest in CFE (US$ 3142 ha(-1) yr(-1)) followed by Cwheat (US$ 2767 ha (1) yr(-1)) and beech forest (US$ 2328 ha(-1) yr(-1)). As the production system shifted from Cwheat – CFE-beech, the marketable ES share decreased from 88% to 75% in CFE and 55% in beech whereas the non-marketable ES share increased to 12%, 25% and 45% of total ES in Cwheat, CFE and beech respectively, demonstrating production system and management effects on ES values. Total ES valuation, disintegrated into marketable and non-marketable share is a potential way forward to value ES and `tune’ our production systems for enhanced ES provision. Such monetary valuation can be used by policy makers and land managers as a tool to assess ES value and monitor the sustained flow of ES. The application of ES-based valuation for land management can enhance ES provision for maintaining the productive capacity of the land without depending on the external fossil-based fertilizer and chemical input. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract: Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work.

Abstract: The diversity in farmers’ objectives and responses to external drivers is usually not considered in integrated assessment studies that investigate impacts and adaptation to climate and socio-economic change. Here, we present an approach to assess how farmers’ stated objectives relate to their currently implemented practices and to preferred adaptation options, and we discuss what this implies for assessments of future changes. We based our approach on a combination of multi-criteria decision-making methods. We consistently assessed the importance of farmers’ objectives and adaptation preferences from what farmers say (based on interviews), from what farmers actually do (by analysing current farm performance) and from what farmers want (through a selected alternative farm plan). Our study was performed for six arable farms in Flevoland, a province in the Netherlands. Based on interviews with farmers, we reduced the long list of possible objectives to the most important ones. The objectives we assessed included maximization of economic result and soil organic matter, and minimization of gross margin variance, working hours and nitrogen balance. In our sample, farmers’ stated preferences in objectives were often not fully reflected in realized farming practices. Adaptation preferences of farmers largely resembled their current performance, but generally involved a trend towards stated preferences. Our results suggest that in Flevoland, although farmers do have more objectives, in practical decision-making they focus on economic result maximization, while for strategic decision-making they account for objectives influencing long-term performance and indicators associated with sustainability, in this case soil organic matter.