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Institute
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.
Shrubs are a characteristic component of savannas, where they coexist with trees and grasses. They are often part of woody encroachment phenomena, which have been observed globally, and the determinant of shrub encroachment cases, which are particularly of concern in African savannas. In response to climate change and land use change, African savannas are vulnerable to biome shifts and shrub encroachment is a process driving and explaining this risk.
We contribute to furthering the understanding of shrubs biogeography and ecology by considering the number of stems of woody plants to characterise shrubs phenotype and strategy. We postulate that shrubs are multi-stemmed, compared to single-stemmed trees and integrate this assumption in aDGVM2 (adaptive Dynamic Global Vegetation Model 2). Modelling a trait representing the number of stems of a woody plant implies a trade-off between single-stemmed plants having higher height growth potential and multi-stemmed plants having higher hydraulic capacity but limited height growth. Multi-stemmed individuals, being shorter, are more likely to suffer severe damage from fires than tall single-stemmed trees managing to grow their crown out of the flame zone.
We simulate potential vegetation over sub-Saharan Africa at 1° spatial resolution, with aDGVM2 and compare it to simulations without our shrub model turned on. We also test the impact of fire by including or excluding it from our simulations. To assess the accuracy and relevance of our approach, we benchmark our overall model’s performance against multiple satellite derived products of above ground biomass (AGBM), and against specific field measurements of AGBM. We further benchmark our results against vegetation cover type derived from satellite data.
We demonstrate that shrubs can be modelled as multi-stemmed woody plants in African savannas based on whole-plant trait trade-off without being predefined as static functional types. Indeed, the addition of our shrub model to aDGVM2 allows for shrubs to emerge dynamically through community assembly processes without a priori categorisation. Our shrub model also improves the simulated vegetation patterns simulated by aDGVM2 in sub-Saharan Africa, particularly in savannas. The simulated pattern of stem number per woody individual broadly follows our assumptions about biogeographic patterns as it is lowest in equatorial African forests and increases in savannas and grasslands as precipitation decreases. Shrubs are more abundant in more water-stressed regions where they have a competitive advantage over trees due to their increased relative water transport potential. However, in arid and hyper-arid regions, further investigations are required. Simulated shrub prevalence is higher in more open and fire prone landscapes, where woody cover and biomass are reduced.
Adding shrubs to aDGVM2, while increasing complexity allows for greater simulated diversity. As resilience and resistance of ecosystems have been shown to be influenced by diversity, such model development is necessary to improve our ability to forecast ecosystems responses to changes. However, there are challenges to fully tap this benefit. Assessing the accuracy and relevance of our approach is challenging. Data and simulations are conceptually different which limit the possibility to conclude based on comparison. Benchmarking challenge is exacerbated by the variability existing among satellite derived products and site studies observations. In areas of extremely low biomass and vegetation cover, such as deserts and semi-deserts, the accuracy of our model is more concerning as small differences in absolute values are relatively more important.
Categorisation of life-forms shapes our understanding of their ecology and biogeography, thus, consensus about their definition is direly needed. To contribute to this debate, we investigate how vegetation distribution patterns arising from our shrub model inform our understanding of shrub biogeography. First, shrub distribution in trait space (considering stem number), relatively to environmental drivers, concurs with our assumptions. Second, shrub spatial distribution is consistent with our characterisation assumptions. Third, the role of simulated shrubs in an ecosystem supports realistic ecological dynamics. Our model allows for, shrubs to exhibit a specific phenotype, but also a specific life-strategy, which we characterise in terms of persistence strategy (shrubs are mainly resprouters, in contrast to trees, which can be either resprouters or reseeders) and in terms of resource acquisition (rooting strategy) and allocation (carbon investment). Adding stem count as a trait to aDGVM2 increase the range of simulated functional diversity.
Our shrub model allows for aDGVM2 to simulate realistic ratio of grass to woody vegetation across sub-saharan Africa. Similarly, it simulates ratio of shrubs to trees consistent with our hypotheses.
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The overarching goal of the thesis was to create a holistic predictive framework, a vegetation model, by improving the representations of and interactions between the biosphere, hydrosphere, atmosphere and pedosphere. Vegetation models rep- resent a crucial component of Earth system model since the properties of the land surface, via interactions with the atmosphere, can have extremely large climatic effect. Yet, there remains great uncertainty associated with the dynamics of the vegetated land surface. Various vegetation models have been critiqued for numerous reasons including overly simplistic representations of vegetation, prescribed vegetation, poor representations of diversity, inaccurate representations of competition, non-transparent model calibration, and poor responses to drought. The purpose of the creation of this "next generation" model was to address deficiencies common to current vegetation modelling paradigms.
The representation of the biosphere within this framework was improved via two separate development axes. First, ecological realism was improved by integrating concepts from community assembly theory, co-existence theory, and evolutionary theory. Explicitly, rather than defining teleonomic rules to define plant behaviour the process of natural selection is modelled. By modelling the pro- cess of natural selection and its affect on relative fitness, myriad "rules" which continually adapt to biotic and abiotic conditions "come out" as a consequence of the modelled dynamics rather than being "put in". In aDGVM2 (adaptive Dynamic Global Vegetation model 2) communities of plants and their trait values evolve through time, this evolution is constrained by trade-offs between traits. Poorly performing individuals are more likely to die and produce fewer copies of themselves, this results in a filtering of trait values. Further, the community and species’ trait values can evolve through successive generations via reproduction, mutation and crossover which we approximate by using a genetic optimisation algorithm. Thus, a plant community consisting of individuals and species with potentially novel and diverse trait values is assembled iteratively through time.
We tested the assertion that improved integration of concepts from community assembly, evolutionary, and co-existence theory could address limitations of DGVMs in Chapter 2. We demonstrated that such an approach does indeed allow diverse communities of plants to emerge from the modelling framework. We showed that the position of the emergent communities in trait space differed along abiotic gradients and that, in simulations where reproductive isolation was simulated, communities emerged which were composed of multiple co-existing clusters in trait-space. Simulated trait values of co-existing strategies emerging from aDGVM2 were often multimodal, indicative of the emergence of multiple life- history strategies.
Second, to successfully model how natural selection forms a community requires accurate representation of how resource availability affects fitness. In the majority of dynamic global vegetation models (DGVMs) there is no real representation of plant hydraulics with plant water availability being calculated as a simple function of relative soil moisture content and root fractions across a number of soil layers. Worryingly, a number vegetation models appear to under represent the magnitude of these observed responses to drought. This was deficiency was ad- dressed in Chapter 3 by designing a simplified version of the cohesion tension theory of sapwood ascent where elements determining plant conductances are considered in series and implementing a set of trait trade-offs which influence a plant’s hydraulic strategy whereby hydraulic safety trades-off against xylem and leaf conductivity.
Interactions between the biosphere, pedosphere, and hydrosphere can also potentially mediate water resource availability and thus fitness. In the majority of DGVMs the volume of soil explored and explorable by plant roots in fixed glob- ally and usually constrained to a depth not greater than 3m. However, we know that soils can have a strong effect on vegetation distributions, that soil depth is not constant globally, and that plants root to variable depths.
In Chapter 4 I explored interactions between soil depth, plant rooting and the emergent properties of communities and highlighted the importance of considering interactions between the biosphere, hydrosphere, pedosphere, and fire. Here I demonstrated that, in addition to fire and precipitation, edaphic constraints on the volume of soil explorable by plant roots (e.g. by shallow soils, lateritic layers, anoxic conditions due to water logging, toxicity resulting from heavy metal concentrations) can affect the process of plant community assembly, alter the mean values of multiple traits in communities, and the trait diversity of communities.
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