An agent-based approach to explore the effect of voluntary mechanisms on land use change: A case in rural Queensland, Australia

Socio-hydrological modelling: a review asking "why, what and how?"

“…Such dynamics include "pendulum swings" that have been observed in areas such as the Murray-Darling Basin, where extensive agricultural development was followed by a realisation of the impacts this was having and subsequent implementation of environmental protection policies van Emmerik et al, 2014), the co-evolution of landscapes with irrigation practices and community dynamics (Parveen et al, 2015), as well as instances of catastrophe in which hydrological extremes not been catastrophic in themselves; rather, social processes that result in vulnerability have made extreme events catastrophic (Lane, 2014). There are also cases where social systems have not interacted with water in the way that was anticipated: examples include the virtual water efficiency and peak-water paradoxes discussed by Sivapalan et al (2014), and yet others where the perception, rather than the actuality, that people have of a natural system determines the way it is shaped (Molle, 2007).…”

“…Deadman et al, 2004;An et al, 2005;Matthews, 2006;Gibon et al, 2010;Valbuena et al, 2010Valbuena et al, , 2009). …”

“…The structure of the modelling framework allowed for the development of a fairly simple model that could show complex interactions between society and hydrology, producing emergent outcomes, and leading to development in thought around the subject. Another example of a system dynamics approach being taken in sociohydrological study is the work of Kandasamy et al (2014), where the co-evolution of human and water systems in the Murrumbidgee Basin (part of the Murray-Darling Basin) was investigated in a qualitative sense to form a system conceptualisation; this was then followed by work by van Emmerik et al (2014) in which this conceptualised system view was turned into a quantitative model, formed from coupled differential equations capable of modelling past system behaviour. In this case, a slightly different set of variables are investigated (reservoir storage, irrigated area, human population, ecosystem health and environmental awareness), which provide indicators of the economic and political systems in a more indirect (e.g.…”

Towards decision-based global land use models for improved understanding of the Earth system

“…ABMs represent individual decision making accounting for variation among and interactions between heterogeneous actors across different levels. They have been used for modelling LULCC in a wide variety of settings (Matthews et al, 2007;Brown et al, 2008;Evans and Kelley, 2008;Acosta-Michlik and Rounsevell, 2009;Valbuena et al, 2010b). Agent-based modelling is typically the domain of interdisciplinary science: while the behavioural sciences help to define decisionmaking structures, these interact with the geography of the physical environment (Janssen, 2003;Brown and Robinson, 2006;Young et al, 2006;Bithell et al, 2008;Collins et al, 2011).…”

Why Don’t More Farmers Go Organic? Using A Stakeholder-Informed Exploratory Agent-Based Model to Represent the Dynamics of Farming Practices in the Philippines

“…Agents' decision making to adopt and maintain organic agriculture is constrained by limited access to information about the optimal farming strategies and the economic resources available. The agents are driven by their individual goals and social behaviors, and they constantly adapt to changing agro-economic and ecological conditions [8,12,32]. Previous agricultural ABM research suggests that, to account for a fuller complexity of farmer decision making and provide room for experimentation aimed at sustainable resource use, agent behavior should be informed by both normative science (economics) and social science that more realistically represents the actual resource-use decision making [33].…”