The role of social interaction in farmers' climate adaptation choice

Adaptation to climate change might not always occur, with potentially\ud catastrophic results. Success depends on coordinated actions at both\ud governmental and individual levels (public and private adaptation). Even for a “wet” country like the Netherlands, climate change projections show that the frequency and severity of droughts are likely to increase. Freshwater is an important factor for agricultural production. A deficit causes damage to crop production and consequently to a loss of income. Adaptation is the key to decrease farmers’ vulnerability at the micro level and the sector’s vulnerability at the macro level. Individual adaptation decision-making is determined by the behavior of economic agents and social interaction among them. This can be best studied with agentbased modelling. Given the uncertainty about future weather conditions and the costs and effectiveness of adaptation strategies, a farmer in the model uses a cognitive process (or heuristic) to make adaptation decisions. In this process, he can rely on his experiences and on information from interactions within his social network. Interaction leads to the spread of information and knowledge that causes learning. Learning changes the conditions for individual adaptation decisionmaking. All these interactions cause emergent phenomena: the diffusion of adaptation strategies and a change of drought vulnerability of the agricultural sector. In this paper, we present a conceptual model and the first implementation of an agent-based model. The aim is to study the role of interaction in a farmer’s social network on adaptation decisions and on the diffusion of adaptation strategies\ud and vulnerability of the agricultural sector. Micro-level survey data will be used to parameterize agents’ behavioral and interaction rules at a later stage. This knowledge is necessary for the successful design of public adaptation strategies, since governmental adaptation actions need to be fine-tuned to private adaptation behavior

Modeling Agricultural Production Considering Water Quality and Risk

Environmental goals often conflict with the economic goals of agricultural producers. The Cottonwood River in Minnesota is heavily polluted with nitrogen, phosphate and sediment from agricultural sources in the watershed. Goals of profit maximization for producers conflict with those of effluent alleviation. We incorporate water quality goals and risk into a mathematical programming framework to examine economically efficient means of pollution abatement while considering a wide range of alternative production practices.Production Economics,

Climate change impacts on water for irrigated horticulture in the Vale of Evesham. Final Report

This project has undertaken a scoping review and assessment of the impacts of climate change on irrigated horticulture in the Vale of Evesham, an area of intense irrigated production located within the Environment Agency’s Warwickshire Avon CAMS Catchment. The research was based on a combination of methodologies including desk-based review of published and grey literature, computer agroclimatic and water balance modelling, GIS mapping, meetings with key informants and a stakeholder workshop. Future climate datasets were derived from the latest UK Climate Impacts Programme (UKICIP02) climatology, using selected emission scenarios for the 2020s, 2050s and 2080s. These scenarios were then used to model and map the future agroclimatic conditions under which agriculture might operate and the consequent impacts on irrigation need (depths of water applied) and volumetric demand. This was complimented by a postal survey to abstractors and a stakeholder workshop, to identify, review and assess farmer adaptation options and responses. The key findings arising from the research, implications for water resource management and recommendations for further work are summarised below. Using a geographical information system (GIS), a series of agroclimate maps have been produced, for the baseline and selected UKCIP02 scenario. The maps show major changes in agroclimate within the catchment over the next 50 years. The driest agroclimate zones are currently located around Worcester, Evesham, Tewkesbury and Gloucester, corresponding to areas where horticultural production and irrigation demand are most concentrated. By the 2020s, all agroclimate zones are predicted to increase in aridity. By the 2050s the entire catchment is predicted to have a drier agroclimate than is currently experienced anywhere in the driest parts of the catchment. This will have major impacts on the pattern of land use and irrigation water demand. Cont/d

Forest Management Zone Design with a Tabu Search Algorithm

Increased conflicts between timber production and environmental protection led some analysts to advocate land-use segregation, often referred to as forest management zoning. The objective of zoning is to create ecologically desirable non-fragmented forest reserves and group timber production areas. We formulate an integer programming model of forest zoning that explicitly addresses clustering of spatial units allocated to timber production and reserve zones while also promoting separation of these zones. A tabu search algorithm is developed, implemented and tested using a case study. The case study results indicate that up to 5% of the net financial return is sacrificed with a 'satisfactory' grouping of units within each zone. A 'good' separation between the reserves and timber production zone is achieved at the cost of further decline of the net financial return up to 11% relative to the unconstrained case.forest planning, integer programming, reserves, tabu search, timber production, zoning

Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Spatial stochastic programming model for timber and core area management under risk of stand-replacing fire, A

2012 Fall.Includes bibliographical references.Forest harvest scheduling has been modeled using deterministic and stochastic programming models. Past models seldom address explicit spatial forest management concerns under the influence of natural disturbances. In this research study, we employ multistage full recourse stochastic programming models to explore the challenges and advantages of building spatial optimization models that account for the influences of random stand-replacing fires. Our exploratory test models simultaneously consider timber harvest and mature forest core area objectives. Each model run reports first-period harvesting decisions for each stand based on a sample set of random fire. We integrate multiple model runs to evaluate the persistence of period-one solutions under the influence of stochastic fires. Follow-up simulations were used to support multiple comparisons of different candidate forest management alternatives for the first time period. Test case results indicate that integrating the occurrence of stand-replacing fire into forest harvest scheduling models could improve the quality of long-term spatially explicit forest plans