Modelling vegetation-climate interactions in South and Southeast Asia using a trait-based dynamic vegetation model

Abstract

Climate controls the broad-scale distribution of vegetation and change in climate will alter the vegetation distribution, biome boundaries, biodiversity, phenology and supply of ecosystem services. A better understanding of the consequences of climate change is required, particularly in under-investigated regions such as tropical Asia, i.e., South and South-east Asia, which is a host to 7 of the 36 global biodiversity hotspots. Conservation strategies would also require an in-depth understanding of the response of vegetation to climate change. Therefore, the main objective of this thesis was to investigate the impact of climate change and rising CO2 vegetation in tropical Asia. Dynamic global vegetation model (DGVMs) are the well-known tools to investigate vegetation-climate interactions and climate change impacts on ecosystems. In this thesis, I used a complex trait-based DGVM called adaptive dynamic vegetation model version 2 (aDGVM2). In Chapter 1, I presented a brief background of the phytogeography and discussed the exiting knowledge gap on vegetation-climate interactions in the region. One major disadvantage for available DGVMs studies for the tropical Asia is that most of them have used fixed plant functional types (PFTs) and do not explicitly represent the distinct varieties of vegetation type of the region such as Asian savannas. In Chapter 2, I discussed at great length to improve DGVMs for South Asia and discussed ways to include them in the model for better representation of region vegetation-climate interaction. I upgraded the current version of aDGVM2 and added a new vegetation type i.e., C3 grasses, and modified the sub-module to simulate photosynthesis for each individual plants to aDGVM2. In chapter 3, I used this updated version of aDGVM2 to simulate the current and future vegetation distribution in South Asia under RCP4.5 and RCP8.5 (RCP: representative concentration pathway). The model predicted an increase in biomass, canopy cover, and tree height under the presence of CO2 fertilization, which triggered transitions towards tree-dominated biomes by the end of the 21st century under both RCPs. I found that vegetation along the Western Ghats and the Himalayas are more susceptible to change due to climate change and open biomes such as grassland and savanna are prone to woody encroachment. In Chapter 4, the study domain was extended to include South-east Asia to verify if the model configuration used in Chapter 3 can also simulate vegetation patterns in tropical Asia. The aDGVM2 simulations showed a robust trend of increasing vegetation biomass and transitions from small deciduous vegetation to taller evergreen vegetation across most of tropical Asia. Shifts in plant phenology also affect ecosystem carbon cycles and ecosystem feedback to climate, yet the quantification of such impacts remains challenging. The study showed increased biomass due to CO2 fertilization, indicates that the region can remain a carbon sink given there is no other resource limitation. However, nutrient limitations on CO2 fertilization effects were not included in the study, and carbon sink potential has to be seen with caution. In Chapter 5, I focused on Asian savannas, which have been mismanaged since the colonial era due to misinterpretation as a degraded forest. I proposed a biome classification scheme to distinguish between degraded forest or woodland and savanna based on the abundance of grass biomass and canopy cover. I found that considering vegetation systems as woodland or degraded forest could easily be mistaken as a potential for forest restoration within a tree-centric perspective. This would put approximately 35% to 40% of a unique savanna biome at risk. Although projected woody encroachments may imply a transition toward the forest that benefits climate mitigation. This raises potential conflicts of interest between biodiversity conservation in open ecosystems, i.e., savanna and active afforestation, to enhance carbon sequestration. Proper management strategies should be taken into account to maintain a balance for both objective In conclusion, the model predicted that vegetation in South and South-East Asia would significantly shift towards tree-dominated biomes due to CO2-induced fertilization of C3-photosynthesis. The simulation under fixed CO2 and rising CO2 scenarios clearly showed that rising level of atmospheric CO2 is responsible for most of the predicted change in biome properties. This study is an important step towards understanding ecosystems of South and Southeast Asia, specifically savannas. The aDGVM2 can serve as tools to inform decision making for climate adaptation and mitigation for savanna. The thesis, thus contributes to our ability to improve conservation strategies to mitigate the consequences of climate change.