مدل شبیه سازی عاملی مبتنی بر بازار تجارت مواد مغذی برای مدیریت منابع طبیعی

Markets for nutrient trading, water quality and other ecosystem services are rapidly emerging across the world. A critical need is to improve the relationship between farmers’ decisions and their impact on natural resources. One of the basic requirements that links buyers and sellers of ecosystem services is an agreed upon unit of trade and a way to measure it. We develop an agent-based model (ABM) which is designed to formalize the interactions between the biophysics dynamics of the natural resources and the socio-economic factors. The simulation market builds on ABM paradigms in its concepts and is coded using the Matlab programming environment. The result shows that ABM is contributing to research questions in ecological economics areas of land-use change, public auction modeling, market dynamics, changes in owners’ perceived yield potential, owners’ gold, farming choice and water treatment choice aspects in human decision making and behavior change.

Markets for trading nutrients, water quality and other ecosystem services are rapidly emerging across the world [1]. Farm manager decisions are driven by economics. The only way money is earned is by selling farm products [2]. However, these decisions can have negative impacts on the environment. Currently, government imposes penalties to encourage farm managers to have low impact on the environment. The opportunity for trading ecosystem services creates other sources of income for farm managers [3]. Our aim is to develop a nutrient trading market that will link buyers and sellers of ecosystem services, and establish an agreed upon unit of trade and a way to measure it. Our hypothesis is that implementation of this nutrient market will result in farmer decisions having a positive impact on the adjoining ecosystems while providing economic benefits. Among the tools used in these various approaches, models often play a crucial part. Agent-based models (ABMs) are now widely acknowledged as suitable tools for representing and simulating complex systems dynamics [4]. ABMs allow the integration of experts’ hypotheses and multidisciplinary research issues, and take into account customs and practices of rural populations for managing shared space. Our hypothesis is that a nutrient trading market can be simulated well by applying an agent-based model. One of the basic requirements that links buyers and sellers of ecosystem services is an agreed upon unit of trade and a way to measure it. We develop an agent-based model (ABM) which is designed to formalize the interactions between the biophysics dynamics of the natural resources and the socio-economic factors. The simulation market builds on ABM paradigms in its concepts and is coded using the Matlab programming environment. The result shows that the ABM is contributing to research questions in ecological economics areas of land-use change, public auction modeling, market dynamics, changes in owners’ perceived yield potential, owners’ gold, farming choice and water treatment choice aspects in human decision making and behavior change.

Nutrient trading is an innovative, agent-driven approach for improving soil quality in a farming system. With this approach, the farmers work together constructively to achieve important ecological objectives. It is a mechanism by which buyers and sellers can strategically focus resources to produce the greatest public benefits at the lowest cost, thus resulting in the greatest ecological returns for the investments in resource conservation. It provides incentives for those who have access to low cost pollution reduction options to reduce their nutrient loads beyond what is required of them. They can then sell their excess credits to others who are unable to make reductions because of higher costs. Therefore, it greatly reduces the overall cost of improving soil quality. To make the agent-based approach to conservation a reality, we need functional and robust tools with high degrees of transferability across the world. Tools such as the Nutrient Trading Tool produced in cooperation with ARS Soil Plant Nutrient Research Unit and Nutrient.Net by the World Resources Institute are specific examples resulting from such efforts. These tools can evaluate and quantify benefits of conservation practices for the overall environmental quality with a few clicks of a mouse. New advances and developments are being made using GIS capabilities to enhance NTT capabilities for assessing the effects of best management practices and savings in reactive N losses that can potentially be traded [12]. As we move towards a new generation of environmental and economic challenges, it is important for farmers, municipalities, businesses and industries, and urban residents to work collaboratively toward ecological stewardship. The agent-based approach to natural resource conservation provides such an opportunity. It helps us improve our ecosystem and provide financial rewards for the environmental stewardship.