Evaluating farm performance using agri-environmental indicators: recent experiences for nitrogen management in The Netherlands

Intensive agriculture, characterized by high inputs, has serious implications on the environment. Monitoring and evaluation of projects aiming at designing, testing and applying more sustainable practices require instruments to asses agronomic as well as environmental performance. Guidelines for Good Agricultural Practice (GAP) or Good Farming Practice (GFP) define sustainable practices but give limited insight into their environmental performance. Agri-environmental indicators (AEIs) provide information on environmental as well as agronomic performance, which allows them to serve as analytical instruments in research and provide thresholds for legislation purposes. Effective AEIs are quantifiable and scientifically sound, relevant, acceptable to target groups, easy to interpret and cost-effective. This paper discusses application of four AEIs for nitrogen (N) management in three Dutch research projects: 'De Marke', 'Cows and Opportunities' and 'Farming with a future'. 'De Marke' applied Nitrogen Surplus and Groundwater Nitrate Concentration in the design and testing of environmentally sound dairy systems. 'Cows and Opportunities', testing and disseminating dairy systems designed at 'De Marke', mainly applied Nitrogen Surplus, while 'Farming with a future' used Nitrogen Surplus, Groundwater Nitrate Concentration and Residual Mineral Soil Nitrogen to support arable farmers in complying with Dutch legislation (MINAS). Nitrogen Surplus is quantifiable, appealing and easy to interpret, but lacks scientific soundness or a good relationship with groundwater quality. Nitrogen Use Efficiency is sensitive to changes in management, while Residual Mineral Soil Nitrogen is appealing and cheap, but has difficulties in scaling. Groundwater Nitrate Concentration lacks clear rules for sampling, is labor consuming, expensive and mainly used in combination with other indicators. AEIs enhanced improvements in N management by facilitating (i) definition of project goals, (ii) design of desired systems, (iii) evaluation of applied systems and (iv) improving effective communication. AEI applications in other countries show a similar pattern as found in The Netherlands. Limitations to AEI application relate to inconsistencies between different indicators, heterogeneity of soil characteristics and linkages of N, carbon and water management. AEIs should be applied in an integrated evaluation, at a scale that reflects the farm's spatial variability. Simple AEIs like Nitrogen Surplus should be supported by other indicators and/or model calculations. The paper concludes that AEIs proved their value in design, implementation and testing of farming systems, but they should be used with care, always keeping in mind that indicators are simplifications of complex and variable processes.     

An Agent-Based Modeling Approach for Determining Corn Stover Removal Rate and Transboundary Effects

Bioenergy production involves different agents with potentially different objectives, and an agent’s decision often has transboundary impacts on other agents along the bioenergy value chain. Understanding and estimating the transboundary impacts is essential to portraying the interactions among the different agents and in the search for the optimal configuration of the bioenergy value chain. We develop an agent-based model to mimic the decision making by feedstock producers and feedstock-to-biofuel conversion plant operators and propose multipliers (i.e., ratios of economic values accruing to different segments and associated agents in the value chain) for assessing the transboundary impacts. Our approach is generic and thus applicable to a variety of bioenergy production systems at different sites and geographic scales. We apply it to the case of producing ethanol using corn stover in Iowa, USA. The results from the case study indicate that stover removal rate is site specific and varies considerably with soil type, as well as other factors, such as stover price and harvesting cost. In addition, ethanol production using corn stover in the study region would have strong positive ripple effects, with the values of multipliers varying with greenhouse gas price and national energy security premium. The relatively high multiplier values suggest that a large portion of the value associated with corn stover ethanol production would accrue to the downstream end of the value chain instead of stover producers.