Adaptation to climate change might not always occur, with potentially catastrophic results. Success depends on coordinated actions at both 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 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.@en

Land developers play a key role in land-use and land cover change, as they directly make land development decisions and bridge the land and housing markets. Developers choose and purchase land from rural land owners, develop and subdivide land into parcel lots, build structures on lots, and sell houses to residential households. Developers determine the initial landscaping states of developed parcels, affecting the state and future trajectories of residential land cover, as well as land market activity. Despite their importance, developers are underrepresented in land use change models due to paucity of data and knowledge regarding their decision-making. Drawing on economic theories and empirical literature, we have developed a generalized model of land development decision-making within a broader agent-based model of land-use change via land markets. Developer's strategies combine their specialty in developing of particular subdivision types, their perception of and attitude towards market uncertainty, and their learning and adaptation strategies based on the dynamics of the simulated land and housing markets. We present a new agent-based land market model that includes these elements. The model will be used to experiment with these different development decision-making methods and compare their impacts on model outputs, particularly on the quantity and spatial pattern of resultant land use changes. Coupling between the land market and a carbon sequestration model, developed for the larger SLUCE2 project, will allow us, in future work, to examine how different developer's strategies will affect the carbon balance in residential landscapes.@en

Urban sprawl is shaped by various geographical, ecological and social factors under the influence of land market forces. When modeling this process, geographers and economists tend to prioritize factors most relevant to their own domain. Still, there are very few structured systematic comparisons exploring how the extent of process representation affects the models' ability to generate extent and pattern of change. This chapter aims to explore the question of how the degree of representation of land market processes affects simulated spatial outcomes. We identify four distinct elements of land markets: resource constraints, competitive bidding, strategic behavior, and endogenous supply decisions. Many land-use-change models include one or more of these elements; thus, the progression that we designed should facilitate analysis of our results in relation to a broad range of existing land-use-change models, from purely geographic to purely economic and from reduced form to highly structural models. The description of the new agent-based model, in which each of the four levels of market representation can be gradually activated, is presented. The behavior of suppliers and acquirers of land, and the agents' interactions at land exchange are discussed in the presence of each of the four land-market mechanisms.@en

Coupled socio-ecological systems (SES) are complex systems characterized by self-organization, non-linearities, interactions among heterogeneous elements within each subsystem, and feedbacks across scales and among subsystems. When such a system experiences a shock or a crisis, the consequences are difficult to predict. In this paper we first define what a shock or a crisis means for SES. Depending on where the system boundary is drawn, shocks can be seen as exogenous or endogenous. For example, human intervention in environmental systems could be seen as exogenous, but endogenous in a socio-environmental system. This difference in the origin and nature of shocks has certain consequences for coupled SES and for policies to ameliorate negative consequences of shocks. Having defined shocks, the paper then focuses on modelling challenges when studying shocks in coupled SES. If we are to explore, study and predict the responses of coupled SES to shocks, the models used need to be able to accommodate (exogenous) or produce (endogenous) a shock event. Various modelling choices need to be made. Specifically, the 'sudden' aspect of a shock suggests the time period over which an event claimed to be a shock occurred might be 'quick'. What does that mean for a discrete event model? Turning to magnitude, what degree of change (in a variable or set of variables) is required for the event to be considered a shock? The 'surprising' nature of a shock means that none of the agents in the model should expect the shock to happen, but may need rules enabling them to generate behaviour in exceptional circumstances. This requires a certain design of the agents' decision-making algorithms, their perception of a shock, memory of past events and formation of expectations, and the information available to them during the time the shock occurred.@en

Coastal flood risk is defined as a product of probability of event and its effect, measured in terms of damage. The paper is focused on coastal management strategies aimed to decrease risk by decreasing potential damage. We review socio-economic literature to show that total flood damage depends on individual location choices in the housing market and on individual flood risk awareness. Low flood risk awareness leads to inefficient spatial developments and increased flood risk. We show that personal experience, risk communication, financial instruments like insurance from flooding and technical instruments like building on high elevations, are factors that increase individual risk awareness. Evidence that these factors indeed affect housing prices and land use patterns is provided. We discuss proactive instruments that can be used in coastal zone management in the Netherlands to increase individual risk awareness. We argue that policy-makers may create incentives giving individuals a possibility to make location choices that lead to less total flood risk in the coastal zone area.@en

Conventional sectoral management and piecemeal governance are considered less and less appropriate in pursuit of sustainable development. Ecosystem based marine spatial management (EB-MSM) is an approach that recognizes the full array of interactions within an ecosystem, including human uses, rather than considering single issues, species, or ecosystem services in isolation. Marine spatial planning and ocean zoning are emerging concepts that can support EB-MSM. EB-MSM is driven by high-level goals that managers aim to achieve through the implementation of measures. High-level goals and objectives need to be translated into more operational objectives before specific targets, limits and measures can be elaborated.Monitoring, evaluation and adaptation are necessary to ensure that marine management measures are both effective and efficient. Solid monitoring frameworks are the foundation of adaptive management, as they provide the necessary information to evaluate performance and the effectiveness of management actions. Marine protected areas (MPAs) - possibly set up in networks - constitute a key component in EB-MSM policies and practises and have been applied as a cornerstone in conservation of marine biodiversity, management of fish populations, development of coastal tourism, etc. Moreover, MPA experiences have provided methods and concepts (such as zoning) to a wider EB-MSM context. The assignment of values to biophysical features of the marine environment allows the direct assessment of related management choices and may assist EB-MSM.A range of monetary valuation techniques have been proposed to reduce attributes of goods and services to a single metric. However, in the marine environment such an approach is often over simplistic, and thus less reductive techniques may be necessary. Rather than producing a single metric, the results of non-monetary assessments guide policy allowing weight to be given as necessary to potential areas of conflict and consensus.Strategies to take into account climate change effects and geohazard risks in EB-MSM have been applied or proposed worldwide. EB-MSM regimes must be alert to such risks and flexible to account for changes.@en

This paper presents an agent-based model of a land market, which is used to explore the effects of land taxes on the land use in a coastal zone. The model simulates the emergence of land prices and urban land patterns from bottom-up via interactions of individual agents in a land market. A series of model experiments helps visualize and explore how economic incentives in a land market may influence the spatial distribution of land prices and urban developments, either leaving space for coastal ecosystems or not. We demonstrate that economic incentives do affect urban form and pattern, land prices and welfare measures. However, they may not always be sufficient to reduce the pressure on coastal ecosystems. Our results show that preservation of ecosystems may involve difficult trade-offs between economic and ecological priorities, as well as between healthy ecosystems and social equity. We also show how conventional economic modelling based on a representative agent, which is usually employed by policy makers, overestimates both environmental benefits and economic costs associated with the tax meant to preserve coastal ecosystems.@en

Dutch coastal land markets are characterized by high amenity values but are threatened by potential coastal hazards, leading to high potential damage costs from flooding. Yet, Dutch residents generally perceive low or no flood risk. Using an agent-based land market model and Dutch survey data on risk perceptions and location preferences, this paper explores the patterns of land development and land rents produced by buyers with low, highly skewed risk perceptions. We find that, compared to representative agent and uniform risk perception models, the skewed risk perception distribution produces substantially more, high-valued development in risky coastal zones, potentially creating economically significant risks triggered by the current Dutch flood protection policy.@en

We present the conceptual design of a new land-change modelling framework that builds on previous land-change research and models (i.e. ALMA, SOME, DEED). The design integrates agents of land change, land-market mechanisms, land-management behaviour and its ecosystem impacts, and land-policy scenarios into a single framework that can be used to address questions about land-change processes in exurban environments. The framework is implemented in Java, built using the Repast Simphony agent-based libraries within the Eclipse integrated development environment. The framework serves as a platform for integrating human and natural processes, as well as data that include social surveys of residential landscape and neighbourhood preferences as well as landmanagement behaviours, ecological field measurements of biomass in residential property parcels, interpretations of historical air photographs, and economic and household data acquired from local governments in Southeastern Michigan. The purpose of the framework is to provide an overarching design that can be extended into specific model implementations that evaluate, among other questions, how policy, land-management preferences, and land-market dynamics affect land-use and land-cover change patterns and subsequent carbon storage and flux.@en

Heterogeneity in both the spatial environment and economic agents is a crucial driver of land market dynamics. We present an agent-based land market model where land from agriculture use is transferred into urban. The model combines the microeconomic demand, supply, and bidding foundations of spatial economics models with the spatial heterogeneity of spatial econometric models in a single methodological platform. Heterogeneous agents exchange heterogeneous spatial goods via simulated bilateral market interactions. We model a coastal city where both coastal amenities and flooding or erosion disamenities drive land market outcomes, facilitating separate analysis of the effects of each driver on land rents and land development patterns. We also analyze the implications of homogeneous versus heterogeneous but unbiased flood risk perceptions. Since buyers with low risk perceptions drive market outcomes, spatial development under heterogeneous risk perceptions differs qualitatively, with more expansion into risky areas. Our results highlight the shortcomings of policy models based on representative agent assumptions and the importance of including agent-level data in empirical modeling.@en

This paper aims to understand the effects of biases in individual flood risk perception on aggregated land use patterns and their implications for macro policy. We develop a spatially explicit land market model and param-eterize individual risk perceptions with data from a survey held in the Nether-lands in 2008. Two sets of experiments are presented. A model with heteroge-neous agents produces qualitatively different results compared to a model with homogeneous agents. Individuals with low flood risk perception drive urban developments into the economically inefficient zone and leading to the increas-ing potential damage.@en

We present a new bilateral agent-based land market model, which moves beyond previous work by explicitly modeling behavioral drivers of land-market transactions on both the buyer and seller sides; formation of bid prices (of buyers) and ask prices (of sellers); and the relative division of the gains from trade from the market transactions. We analyze model output using a series of macro-scale economic and landscape pattern measures, including land rent gradients estimated using simple regression models. We first demonstrate that our model replicates relevant theoretical results of the traditional Alonso/Von Thünen model (structural validation). We then explore how urban morphology and land rents change as the relative market power of buyers and sellers changes (i.e., we move from a 'sellers' market' to a 'buyers' market'). We demonstrate that these strategic price dynamics have differential effects on land rents, but both lead to increased urban expansion.@en

This paper presents an agent-based model of a land market (ALMA-C) to simulate the emergence of land prices and urban land patterns from bottom-up. Our model mimics individual decisions to buy and to sell land depending on economic, sociological and political factors as well as on the characteristics of the spatial environment. To this we add ecological and environmental considerations and focus on the question of how individual land use decisions can be affected to reduce the pressure on the coastal zone ecosystem functions. A series of model experiments helps visualize and explore how economic incentives at a land market can influence the spatial distribution of activities and land prices in a coastal zone. We demonstrate that economic incentives do affect urban form and pattern, land prices and welfare measures. However, they may not always be sufficient to reduce the pressure on coastal zone ecosystems.@en

This paper presents a conceptual design for an agent-based bilateral residential land market. The design includes interactions between multiple buyers and sellers (household agents, developers, and rural land owners) and two local feedbacks to land value-price expectation formation based on local neighborhoods and spatial externalities. To address the methodological challenges inherent in the transition from equilibrium-based analytical models to agent-based simulation, we combine traditional deductive optimization models of behavior at the agent level with inductive models of price expectation formation. Relative to previous models, our proposed model is more closely linked to urban economics; contains a wider range of drivers of land use (LU); and addresses alternative models of division of gains from trade and determination of transaction prices, including models of bid and ask price formation. Our proposed approach is also closely linked to geographic cellular LU models, potentially uniting the strengths of these two disciplinary perspectives.@en

Recent uneven land use dynamics in urban areas resulting from demographic change, economic pressure and the cities' mutual competition in a globalising world challenge both scientists and practitioners, among them social scientists, modellers and spatial planners. Processes of growth and decline specifically affect the urban environment, the requirements of the residents on social and natural resources. Social and environmental research is interested in a better understanding and ways of explaining the interactions between society and landscape in urban areas. And it is also needed for making life in cities attractive, secure and affordable within or despite of uneven dynamics. The position paper upon "Actors and factors - bridging social science findings and urban land use change modeling" presents approaches and ideas on how social science findings on the interaction of the social system (actors) and the land use (factors) are taken up and formalised using modelling and gaming techniques. It should be understood as a first sketch compiling major challenges and proposing exemplary solutions in the field of interest.@en

The complexity and uncertainty inherent in environmental models must be considered and managed in an appropriate manner. This chapter presents a conceptual approach to deal with uncertainty, which considers the context of the purpose for which the model is developed. The four major modelling purposes identified - prediction, exploratory analysis, communication and learning - each focus on different modelling characteristics and roles of uncertainty. The notion of uncertainty is broadened, from being an attribute associated with the quality of information to also comprise modellers' beliefs and experiences. The chapter proposes ways in which uncertainty should be handled for each of the four modelling purposes and presents examples that illustrate the concepts. Various sources of uncertainty are considered relevant when modelling complex systems, and each source manifests differently in the data, structure or frame of the model.@en

We construct a spatially explicit agent-based model of a bilateral land market. Heterogeneous agents form their bid and ask prices for land based on the utility that they obtain from a certain location (house/land) and based on the state of the market (an excess of demand or supply). We underline the distinction between bid /ask price and individual willingness to pay/to accept and show that variations between them that reflect market conditions can influence land prices. Agents sort among locations with respect to distance from the city center and environmental spatial externalities. Aggregated outcomes such as land patterns and land prices are produced by the model. The basic model of buyers and sellers trading land in the urban area produces results identical to the monocentric urban model. However, more complex dynamics appears when environmental amenities and market-adjustment variable influence the formation of land prices.@en

Economic growth causes growing urbanization, extension of tourist sector, infrastructure and change of natural landscape. These processes of land use change attract even more attention if they take place in coastal zone area. In that case not only the efficient allocation and preservation of natural area, but also reduction of potential damage from flooding is important. Driven forces of land use at macro and micro levels should be taken into account. This paper presents an agent based model (ABM), which is designed to simulate land use change in coastal zone area based of human behaviour. The aim is to understand motives, types of connections and interactions between different actors and natural environment in order to get a feeling how different policy options and natural conditions might affect land use configuration. Microeconomic motives of land use decisions are in the focus of the research. Individual land use decisions are guided by economic and geomorphologic conditions, spatial planning and coastal protection policy. Each location choice is done according to a set of defined rules and land attributes. Space is represented as a grid of cells. Self-interested economic agents interact with each other trying to benefit from a certain type of land-use. We introduce the perception of risk of flooding in the model of land use as an innovative aspect of ABM simulations for water management problems. Based on decisions of spatially distributed individual economic agents operating in a policy framework, the model produces aggregated land-use patterns as an outcome. Understanding the factors that affect land use decisions will help policy makers design incentives to achieve policy objectives in coastal zone area. The proposed ABM will be applied to a study area in the province of North Holland in the Netherlands.@en