scholarly journals Impacts of land-use management on ecosystem services and biodiversity: an agent-based modelling approach

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2814 ◽  
Author(s):  
Thomas J. Habib ◽  
Scott Heckbert ◽  
Jeffrey J. Wilson ◽  
Andrew J. K. Vandenbroeck ◽  
Jerome Cranston ◽  
...  
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Ecosystem Services ◽  
Timber Harvest ◽  
Successful Implementation ◽  
Management Decisions ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Land Use Decisions ◽  
Modelling System

The science of ecosystem service (ES) mapping has become increasingly sophisticated over the past 20 years, and examples of successfully integrating ES into management decisions at national and sub-national scales have begun to emerge. However, increasing model sophistication and accuracy—and therefore complexity—may trade-off with ease of use and applicability to real-world decision-making contexts, so it is vital to incorporate the lessons learned from implementation efforts into new model development. Using successful implementation efforts for guidance, we developed an integrated ES modelling system to quantify several ecosystem services: forest timber production and carbon storage, water purification, pollination, and biodiversity. The system is designed to facilitate uptake of ES information into land-use decisions through three principal considerations: (1) using relatively straightforward models that can be readily deployed and interpreted without specialized expertise; (2) using an agent-based modelling framework to enable the incorporation of human decision-making directly within the model; and (3) integration among all ES models to simultaneously demonstrate the effects of a single land-use decision on multiple ES. We present an implementation of the model for a major watershed in Alberta, Canada, and highlight the system’s capabilities to assess a suite of ES under future management decisions, including forestry activities under two alternative timber harvest strategies, and through a scenario modelling analysis exploring different intensities of hypothetical agricultural expansion. By using a modular approach, the modelling system can be readily expanded to evaluate additional ecosystem services or management questions of interest in order to guide land-use decisions to achieve socioeconomic and environmental objectives.

scholarly journals Facilitating informed land-use decisions through the modelling of ecosystem service trade-offs

2021 ◽  
Author(s):  
◽  
Nicola Scott
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Ecosystem Services ◽  
Diffusion Theory ◽  
New Technology ◽  
Land Utilization ◽  
Management Interventions ◽  
Land Use Decisions ◽  
Trade Offs ◽  
The Impact

<p>Increasing global populations are placing increasing pressure on our natural systems, reducing their capacity to produce the ecosystem services that we rely upon for human wellbeing (World Bank, 2004).   Clarifying the implications of land-use decisions across the range of ecosystem services is fundamental to understanding the trade-offs inherent in land-use options. LUCI (the Land Utilization and Capability Indicator) is an emergent Geographic Information Systems (GIS) based framework developed to enable the mapping of several ecosystem services in a spatially explicit manner. This process enables a clearer understanding of the inter-dependencies between ecosystems and potential implications and trade-offs of management interventions across a range of services.   There is however, limited understanding of the impact, utility and credibility of such tools for land-use decision-makers, or of how they perceive the information conveyed. This Thesis considered the impact that presenting information on land-use trade-offs through LUCI had on land-owners at the farm scale.   This research supports previous findings that information alone does not drive behaviour (or decision-making) (Kollmuss, 2002, Fisk, 2011; Kennedy, 2010; Mackenzie-Mohr, 2000; Stern, 2000). Similarly, perceived credibility was not the main driver of decision-making nor is it necessarily rationally based. However without it, voluntary adoption of a new technology or tool is unlikely. Therefore, in seeking to diffuse tools, such as LUCI within a community, process design should take into account the social structures and the characteristics of targeted individuals within that community. The influence of temporal and context specific factors on decision-making provides both barriers and opportunities for technology diffusion.  The research findings propose that when integrating new tools and technologies within communities, consideration is given to using a suite of tools, mechanisms and theories in concert such as Community-Based Social Marketing (Mackenzie-Mohr, 2011) and Diffusion Theory (Rogers, 2003) to facilitate improved diffusion and uptake by communities.</p>

scholarly journals Improving Representation of Decision Rules in LUCC-ABM: An Example with an Elicitation of Farmers’ Decision Making for Landscape Restoration in Central Malawi

2020 ◽  
Vol 12 (13) ◽  
pp. 5380 ◽  
Author(s):  
Ida Nadia S. Djenontin ◽  
Leo C. Zulu ◽  
Arika Ligmann-Zielinska
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Decision Rules ◽  
Well Being ◽  
Agricultural Landscapes ◽  
Agent Based ◽  
Social Actors ◽  
Land Use Decisions ◽  
Decision Making Processes ◽  
Restoration Practices

Restoring interlocking forest-agricultural landscapes—forest-agricscapes—to sustainably supply ecosystem services for socio-ecological well-being is one of Malawi’s priorities. Engaging local farmers is crucial in implementing restoration schemes. While farmers’ land-use decisions shape land-use/cover and changes (LUCC) and ecological conditions, why and how they decide to embrace restoration activities is poorly understood and neglected in forest-agricscape restoration. We analyze the nature of farmers’ restoration decisions, both individually and collectively, in Central Malawi using a mixed-method analysis. We characterize, qualitatively and quantitatively, the underlying contextual rationales, motives, benefits, and incentives. Identified decision-making rules reflect diverse and nuanced goal frames of relative importance that are featured in various combinations. We categorize the decision-making rules as: problem-solving oriented, resource/material-constrained, benefits-oriented, incentive-based, peers/leaders-influenced, knowledge/skill-dependent, altruistic-oriented, rules/norms-constrained, economic capacity-dependent, awareness-dependent, and risk averse-oriented. We link them with the corresponding vegetation- and non-vegetation-based restoration practices to depict the overall decision-making processes. Findings advance the representation of farmers’ decision rules and behavioral responses in computational agent-based modeling (ABM), through the decomposition of empirical data. The approach used can inform other modeling works attempting to better capture social actors’ decision rules. Such LUCC-ABMs are valuable for exploring spatially explicit outcomes of restoration investments by modeling such decision-making processes and policy scenarios.

scholarly journals Facilitating informed land-use decisions through the modelling of ecosystem service trade-offs

2021 ◽  
Author(s):  
◽  
Nicola Scott
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Ecosystem Services ◽  
Diffusion Theory ◽  
New Technology ◽  
Land Utilization ◽  
Management Interventions ◽  
Land Use Decisions ◽  
Trade Offs ◽  
The Impact

<p>Increasing global populations are placing increasing pressure on our natural systems, reducing their capacity to produce the ecosystem services that we rely upon for human wellbeing (World Bank, 2004).   Clarifying the implications of land-use decisions across the range of ecosystem services is fundamental to understanding the trade-offs inherent in land-use options. LUCI (the Land Utilization and Capability Indicator) is an emergent Geographic Information Systems (GIS) based framework developed to enable the mapping of several ecosystem services in a spatially explicit manner. This process enables a clearer understanding of the inter-dependencies between ecosystems and potential implications and trade-offs of management interventions across a range of services.   There is however, limited understanding of the impact, utility and credibility of such tools for land-use decision-makers, or of how they perceive the information conveyed. This Thesis considered the impact that presenting information on land-use trade-offs through LUCI had on land-owners at the farm scale.   This research supports previous findings that information alone does not drive behaviour (or decision-making) (Kollmuss, 2002, Fisk, 2011; Kennedy, 2010; Mackenzie-Mohr, 2000; Stern, 2000). Similarly, perceived credibility was not the main driver of decision-making nor is it necessarily rationally based. However without it, voluntary adoption of a new technology or tool is unlikely. Therefore, in seeking to diffuse tools, such as LUCI within a community, process design should take into account the social structures and the characteristics of targeted individuals within that community. The influence of temporal and context specific factors on decision-making provides both barriers and opportunities for technology diffusion.  The research findings propose that when integrating new tools and technologies within communities, consideration is given to using a suite of tools, mechanisms and theories in concert such as Community-Based Social Marketing (Mackenzie-Mohr, 2011) and Diffusion Theory (Rogers, 2003) to facilitate improved diffusion and uptake by communities.</p>

Agent-Based Simulations of Household Decision Making and Land Use Change near Altamira, Brazil

2002 ◽  
Author(s):  
Kevin Lim ◽  
Peter J. Deadman
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Computer Simulation ◽  
Natural Sciences ◽  
Social Simulation ◽  
Social Scientists ◽  
Agent Based ◽  
Natural Systems ◽  
Land Use Decisions ◽  
Human Systems

Individuals who influence decisions regarding the use of land, operate within a complex environment comprised of interacting elements that include both natural systems and human institutions. Individually, the elements of the natural and human systems that influence land-use decisions may be very complex. Within natural systems, dynamic processes, such as the hydrological cycle, and the distribution of biophysical resources, such as soil fertility, influence land-use decision making. Elements of an individual’s institutional environment can also influence the options and incentives that are available to an individual, and thus the land-use decisions that thhey make. Understanding the nature of these complex processes and interactions is a nontrivial task. However, agent-based simulation offers researchers a tool to better understand the nature of these complex systems. The recent development of computer simulation technologies by social scientists has provided a tool for not only predicting social phenomena, but also for better understanding the nature of these human systems. Replicative validity is not the goal of many social simulation efforts. Instead, researchers have focused on developing relatively simple simulations as tools for understanding the properties of social systems and the way in which interactions between actors at the local level results in the emergence of behaviors or phenomena at the global level. In this role, simulation becomes a tool for evaluating assumptions and exercising theories of action. Many of the techniques applied to social simulation can be traced back to earlier developments in the physical or natural sciences. For example, computer simulation has a relatively long history in the natural sciences in applications related to fisheries, forest environments, and watersheds. But recent advances in computer hardware and software technologies have made these technologies accessible to social scientists. Recently, we have seen simulation efforts that have included models of not only the natural system in question, but also the human system with which it interacts. In fields such as anthropology and resource management , human systems simulations are being developed which directly address the actions of human individuals or groups as they interact with a natural system. This approach to simulation is pursued in this chapter.

Modeling Farmer’s Decision-Making to integrate climate, land use and ecosystem functions

2020 ◽  
Author(s):  
Veronica Gaube ◽  
Claudine Egger ◽  
Christoph Plutzar ◽  
Andreas Mayer ◽  
Helmut Haberl
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Ecosystem Functions ◽  
Land Use Patterns ◽  
Study Region ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Biogeochemical Models

&lt;p&gt;Land use and climate change are important drivers of environmental change and pose a major threat to ecosystems. Although systemic feedbacks between climate and land use changes are expected to have important impacts, research has rarely focused on the interaction between the two drivers. One reason for this could be that forecasts of land use are hardly available on suitable spatial and thematic scales. Agent-based models (ABMs) represent a potentially powerful tool for creating thematic and spatially fine-grained land use scenarios. In order to derive such scenarios, the complex interaction between land users (e.g. farmers) and the broader socio-economic context in which they operate must be taken into account. On landscape to regional scales, agent-based modelling (ABM) is one way to adequately consider these intricacies. ABMs simulate human decisions, and with individual land owners/users as agents, they can simulate usage paths for individual plots of land in thematically fine resolution. Ideally, these simulations are based on an understanding of how farmers make decisions, including anticipated strategies, adaptive behavior and social interactions. In order to develop such an understanding, participatory approaches are useful because they incorporate stakeholders' perspectives into the model calibration, thereby taking into account culture and traditions that often play an important role in land use decisions. A greater proximity to stakeholder perspectives also increases the political relevance of such land use models. Here we present an example where we developed an ABM (SECLAND) parameterised for 1,329 stakeholders, mostly farmers, in the LTSER region Eisenwurzen (Austria) and simulate the changes in land use patterns resulting from their response to three scenarios of changing socio-economic conditions. Summarized in broad categories, the study region currently consists of 67% deciduous and coniferous forests (including logging), 19% grassland, 9% agricultural land and 6% alpine areas. SECLAND simulated small to moderate changes in these percentages until 2050, with little difference between the scenarios. In general, an increase in forests is predicted at the expense of grasslands. The size of agricultural land remains approximately constant. At the level of the 22 land use classes, the trends between the land use change scenarios differ more strongly. This ABM at the individual or farm level is combined with biodiversity and biogeochemical models that analyse how landowners' decision-making affects various ecosystem parameters. We conclude that agent-based modelling is a powerful tool for integrating land use and climate effects into ecosystem projections, especially at regional level.&lt;/p&gt;

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