Modeling patterns of farm diversification in a Dutch landscape

In agrarische landschappen zijn het de beslissingen van de agrariërs die medebepalend zijn voor zowel het aanbod als de kwaliteit van de voortgebrachte landschapsdiensten. Het doel van dit proefschrift is inzicht te verschaffen in de ruimtelijke patronen van bedrijfsdiversificatie en na te gaan hoe deze patronen mogelijk in de toekomst zouden kunnen veranderen. De studie richt zich op de Gelderse Valle

An Analysis Of Agricultural Decision-Making For Phosphorus Runoff Reduction In The State Of Vermont

Eutrophication, stimulated by phosphorous (P) runoff from landscapes, compromises water quality and can have long-term impacts on the aesthetics, recreation, property values, and drinkability of bodies of water around the world. In the State of Vermont, efforts are underway to control the amount of P entering Lake Champlain per standards set forth in the Federal Clean Water Act. Agriculture has been identified as a major contributor to excess P in the waterways and will be managed according to Act 64, the Vermont Water Quality Act. The studies presented in this paper will introduce two independent methodologies proposed to aid in evaluating the farmer\u27s willingness to implement pro-environmental practices, (1) determining farmer values towards implementation of best management practices to inform policy, and (2) creating a multifunctional sustainability prioritization scheme for dissemination of Clean Water Fund resources. The Vermont Water Quality Act proposes Required Agricultural Practices (RAP) for agriculture in the State with a limited understanding of what the farming community desires from such a policy. This paper\u27s first article titled, Determining Farmer Values for Implementing Pro-Environmental Practices, analyzes twenty-four farmers and their associated values towards adopting pro-environmental practices for improved water quality. A hierarchical cluster analysis was used to segment farmers according to their adoption of best management practices on their farms. Further, a one-way analysis of variance (ANOVA) was conducted using dependent functional (quality), functional (price), and emotional, social, conditional, and epistemic variables to understand the variance between the segments. The results from this analysis illuminate farmer values. This information can be used to inform water quality policy, ecosystem service payments, communication strategy, and funding dissemination. The Clean Water Fund was created to support the implementation of water quality initiatives in various sectors throughout the State of Vermont. The resources within the fund are limited; therefore careful prioritization of farms for outreach is essential. In the article titled, Prioritizing Farms for Subsidies: A Multifunctional Approach, a prioritization methodology is presented using theory from the sustainable multifunctional agriculture literature. The sample includes vegetable, vegetable and meat, meat, and maple producers within the State. The diverse production types included in this study reflects the non-discriminatory—relating to production types—policies in Act 64. The study is limited by the exclusion of the dairy sector. Geographic Information Systems (GIS) software was used to map environmental practices on twelve farm landscapes to generate a spatial representation of environmental stewardship that was then translated into an environmental score. This environmental score was combined with social and economic data to prioritize farms based upon their multifunctional sustainability. This ranking methodology may be useful for the State of Vermont in determining the prioritization of Clean Water Fund resources using farm sustainability measurements

Representation of decision-making in European agricultural agent-based models

The use of agent-based modelling approaches in ex-post and ex-ante evaluations of agricultural policies has been progressively increasing over the last few years. There are now a sufficient number of models that it is worth taking stock of the way these models have been developed. Here, we review 20 agricultural agent-based models (ABM) addressing heterogeneous decision-making processes in the context of European agriculture. The goals of this review were to i) develop a framework describing aspects of farmers' decision-making that are relevant from a farm-systems perspective, ii) reveal the current state-of-the-art in representing farmers' decision-making in the European agricultural sector, and iii) provide a critical reflection of underdeveloped research areas and on future opportunities in modelling decision-making. To compare different approaches in modelling farmers' behaviour, we focused on the European agricultural sector, which presents a specific character with its family farms, its single market and the common agricultural policy (CAP). We identified several key properties of farmers' decision-making: the multi-output nature of production; the importance of non-agricultural activities; heterogeneous household and family characteristics; and the need for concurrent short- and long-term decision-making. These properties were then used to define levels and types of decision-making mechanisms to structure a literature review. We find most models are sophisticated in the representation of farm exit and entry decisions, as well as the representation of long-term decisions and the consideration of farming styles or types using farm typologies. Considerably fewer attempts to model farmers' emotions, values, learning, risk and uncertainty or social interactions occur in the different case studies. We conclude that there is considerable scope to improve diversity in representation of decision-making and the integration of social interactions in agricultural agent-based modelling approaches by combining existing modelling approaches and promoting model inter-comparisons. Thus, this review provides a valuable entry point for agent-based modellers, agricultural systems modellers and data driven social scientists for the re-use and sharing of model components, code and data. An intensified dialogue could fertilize more coordinated and purposeful combinations and comparisons of ABM and other modelling approaches as well as better reconciliation of empirical data and theoretical foundations, which ultimately are key to developing improved models of agricultural systems.Swiss National Science Foundatio

Multifunctionality in U.S. Rice Production: a Logit Analysis in Farmers Participation

Multifunctional agriculture is particularly fundamental to some working lands conservation policies and programs, such as the Environmental Quality Incentive Program (EQIP), Conservation Security Program (CSP) and Wildlife Habitat Incentive Program (WHIP). Farmers can also be engaged in providing recreational and agri-tourism services such as hunting, fishing, bird-watching, farm tours, petting zoos and hospitality services. Using the Agricultural Resource Management Survey (ARMS) we analyze factors associated with participation in conservation, recreation and agri-tourism activities as a function of farm structure, farm financial measures, production practices, and socio-demographic characteristics of the farm operator. To estimate the functional relationships we estimate a binary logistic model where the dependent variable takes a value equal to one if the farm operator reports in the ARMS survey participation in conservation programs, recreation or agritourism. Results show that the level of farm operator education and cultural practices that use conservation technical assistance are significant at the 0.01 and 0.10 levels, respectively, in explaining participation. Farm financial characteristics were not significant. Location (state where operator is located) is also not significant

Going beyond perfect rationality: drought risk, economic choices and the influence of social networks

Theoretical and experimental studies from psychological and behavioral sciences show that heuristics and social networks play an important role in decision-making under risk. The goal of this paper is to investigate the effects of empirical social networks and different behavioral rules on farmers’ irrigation adoption under drought risk and its impacts on several macroeconomic indicators such as the rate of adaptation, water demand and regional agricultural income. We present an application of a spatial economic ABM which is able to simulate the effect of droughts on crop production, farm income and farm decision-making. The agents’ population is parameterized using survey data, including data on social networks. Four experiments are conducted combining two climate scenarios with two behavioral scenarios (maximizers vs. heuristic-based agents). The results show that the adoption process follows a different path in the scenario with heuristic-based farmers. The adoption of irrigation is slower in the short run due to reliance on information from social networks and farmers’ uncertainty regarding drought events. This results in agricultural income loss and a lower water demand in the short run compared to the scenario with maximizing agent

An agent-based approach to model land-use change at a regional scale

Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local scales, while its application in regional studies is limited. This paper describes first a conceptual framework for ABM to analyse and explore regional LUCC processes. Second, the conceptual framework is represented by combining different concepts including agent typologies, farm trajectories and probabilistic decision-making processes. Finally, the framework is illustrated through a case study in the Netherlands, where processes of farm cessation, farm expansion and farm diversification are shaping the structure of the landscape. The framework is a generic, straightforward approach to analyse and explore regional LUCC with an explicit link to empirical approaches for parameterization of AB

Environmental impact of organic agriculture in temperate regions

Can organic agriculture elaborate a scientifically based, resource-efficien and agroecological approach to low-input farm management? This review examines the literature from temperate regions, with a particular emphasison Canadian and USstudies that relate to environmental and ecological impacts of organic agriculture with respect to (i )soil organic matter storage, (ii) soil quality/soil health, (iii) nutrient loading and risks of off-farm nutrient and agrochemical losses, (iv) biodiversity and (v) energy use and global warming potential. The context and implications of semi-arid conditions and low soil P levels, common to many organic farms in North America, and wide spread adoption of genetically engineered crops in conventional production, is also considered. The consensus of the data available to date indicates the distinctiveness of cropping, flora and habitat diversity, soil management regime, nutrient intensity and use efficiency and energy, and pesticide use in organic farming confer important environmental and ecological benefits. These include maintenance of soil organic matter and added return of carbon to soil, improved soil health, reduced off-farm nitrogen and phosphorus losses, enhanced vegetative and wildlife (bird) biological diversity, extended some times to other taxa depending on landscape context, improved support for pollinators and pollination and reduced energy use and improved energy efficiency. The continued evolution of organic agriculture to a more outcomes-based, agroe cological production system will require an expanded multi-disciplinary research effort, linked ideally to support from consumers and policy-makers on the basis of renewed under-standing of its potential contribution to global environmental sustainability