Opportunities for FYPs 2021-2022

Below are brief descriptions of FYP project being offered in the Applied Plant Ecology lab 2021-2022. Please contact A/P Edward to express interest and set up a meeting (ted.webb@nus.edu.sg)
 
We use a wide array of data sets and geospatial techniques to inquire about changes in land cover in the Asian region. By joining the lab and undertaking a project, you will be exposed to a great deal of new skills that will enhance your professional opportunities. Keywords of the skills, data sets, and platforms you may encounter (depending on the project) include:
 
Ecosystem services valuation
Geographic Information Systems
Land cover change
Landscape statistics
Google Earth Engine
Remote sensing
Spatial conservation planning
Species distribution modeling
Plantation expansion and losses of forest ecosystem services
This project will assess the impact of plantation expansion on forest ecosystem service values in mainland Southeast Asia. The study will examine historical deforestation as a result of plantation expansion, particularly (a) oil palm and rubber in southern Myanmar and (b) rubber in northeast Cambodia. These changes will be linked with a quantification of the changes to ecosystem service values. An additional opportunity will be to create projections of future forest change based on historical expansion of these plantation tree crops utilising a land use/cover change modeling approach, particularly cellular automata. Subsequently, the study could also quantify the impacts on forest ecosystem service values as a result of simulated forest change in the future. 
Planning conservation areas in the Philippines based on climate macrorefugia
This project will evaluate the gaps in the representation of dipterocarp species within the national protected areas system of the Philippines in view of changes in species distributions under future climate change scenarios. From this initial analysis the work will identify additional conservation priority areas using spatial prioritisation tools towards safeguarding their macrorefugia in the future. The project is follow-up study of a recently published paper, Effects of climate change and land cover on the distributions of a critical tree family in the Philippines (see recently published paper here), and will potentially contribute to science-driven conservation planning and local-level interventions through in-country collaborators.
Conservation planning in mangrove ecosystems of Myanmar
This project will use spatial conservation planning to evaluate the current extent of protection for mangroves in Myanmar. Using data from our previous research on mangrove change, the project will make projections of future deforestation and combine that with a spatial conservation planning framework to identify the highest priority conservation mangrove sites in Myanmar.
The potential for dragon fruit farming on abandoned agricultural land in Nepal
Agricultural policies promoting new crops can greatly enhance farmer income but also lead to deforestation in ecologically sensitive regions. In Nepal, dragon fruit is an emerging high-value fruit crop, which has the potential to provide high economic gains for small holder farmers and reverse the trend of high agricultural abandonment in the country. The conversion of abandoned agricultural land into productive dragon fruit farms has the potential to benefit both farmers and conservationists. But where would be the best locations to farm dragon fruit in Nepal? This project will combine species distribution modelling with land-use land-cover change analysis to identify abandoned agricultural land suitable for dragon fruit farming.
Characterizing deforestation landscapes
This project will quantify various landscape metrics to characterize the process of fragmentation in a deforestation landscape. This study will be an extension of a study that identified hotspots of deforestation in SE Asia, thus providing enhanced metrics of a complex geographic landscape. You will utilize an array of data sources and analytical platforms, especially Google Earth Engine and SE Asia land cover datasets, to quantify the spatiotemporal changes in the selected landscape of SE Asia.
Skills gained / keywords: Deforestation, land cover change, GIS, landscape statistics