Estimating impacts of climate change policy on land use: an agent-based modelling approach.
Bottom Line: The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer's decisions affect farm conversion and the resulting land use at a catchment scale.Higher GHG prices provide a greater net reduction of emissions.While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.
Affiliation: Landcare Research, Auckland, New Zealand.
Agriculture is important to New Zealand's economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer's decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.
No MeSH data available.
Related in: MedlinePlus
Mentions: These aspects are reinforced when exploring the resulting land use maps at the conclusion of each model run. Analysing at a farm parcel level, we developed a probability that the farm will result in each of the three main enterprises, across the four GHG prices, and network effects. Fig 8 highlights that regardless of the GHG price network effects amplify the financial benefits of the Dairy enterprises. This results in the clustering of the enterprise within the Plains and Foothills productivity zones. This amplification is reversed for Sheep & Beef while GHG prices play stronger role in the likelihood of a farm resulting in a Forestry enterprise.
No MeSH data available.