|dc.description.abstract||Lam Dong is a province in the Central Highlands of Vietnam which has high biodiversity values. However, rapid socio-economic growth is causing environmental degradation. This research is directed at understanding the key driving factors behind individual choices about land use and the subsequent effects these may have on environmental degradation. Understanding individual motivations helps identify potential policy interventions and predict degradation with different policies. The research used a spatially explicit agent-based modelling approach (SeABM) to integrate spatial and non-spatial parameters in land use decisions. To determine the non-spatial parameters for the model, a questionnaire was used to collect demographic information from households. Spatial parameters were collected through data collection processes from different sources.
Based on the model that was developed, a number of simulations were done to evaluate the effect of different policy options compared to a base-line simulation. The effects were based on changes to four key measures – land use changes, soil erosion, carbon dioxide sequestration and landscape fragmentation. The scenarios evaluated were reducing population growth rate, improving households’ income, supporting low income households, promoting a perennial cashew crop, promoting acacia hybrid and promoting payment for forest environmental services. The baseline assumed that the population will grow at a rate of 2.7% per year as a normal rate. The number of mouths to feed in each household and the labours will also increase due to population growth. The cash balance of households may be deficit and lead to changes in their land uses to compensate for any loss. The land use changes will follow the historical trend described by several land use change modules results of analysing time-series satellite images.
Simulation outcomes with scenarios such as population growth, income growth and financial support did not deviate from the baseline scenario (the business as usual scenario). Moreover, they all potentially caused negative impact on the quality of the environment by increasing the amount of soil erosion, reducing the capacity to store more carbon dioxide in vegetative cover, and increasing the landscape fragmentation after 10 years.
Promoting perennial crops such as cashew in simulation had a positive effect on local livelihood. However, it still degraded environmental quality. Because this crop is usually planted at higher elevations with large spacing on steeper slopes, increased soil erosion results. Promoting acacia hybrid had a positive impact on livelihood and a lower negative influence on environmental outcomes. Acacia hybrid can be considered a good option as it is planted with higher density and has a higher growth rate compared to cashew, which helps reduce soil erosion on the ground and increase carbon sequestration. Providing payment for environmental services had a positive impact on environmental quality. The pressure on natural resources would be less if households had sustainable sources of income which encouraged them to protect and cultivate forest in the long term.
Based on the results of this research, several policy options would be suggested to harmonise both socio-economic growth and environmental quality. Land use conversion should be sustainably maximised if the current land use is not profitable for households. Long-term investment and long rotation for plantations at high elevation should be encouraged to reduce soil erosion and the restriction on rice land on flat areas needs to be flexible. Controlling the birth rate and improving education are also remedies to reduce the number of people depending heavily on agricultural activity and utilising forest products. Increasing incentive for forest protection and improving legal responsibility for violation in forest protection are highly recommended to encourage households to protect forest and sustainably benefit from it.
The results show that SeABM framework is capable of identifying land use dynamics in the future with different policy options. It has the potential to be used as a tool by policy makers in land use planning to explore new development alternatives. However, there are many gaps that can be improved upon with this research to have better modelling which captures the reality of land use decision-making behaviour.||en