Refine
Document Type
- Doctoral Thesis (4)
Language
- English (4)
Has Fulltext
- yes (4)
Is part of the Bibliography
- no (4)
Keywords
- aDGVM2 (1)
- multi-stem architecture (1)
- plant life-form (1)
- savanna (1)
- shrub encroachment (1)
- shrub-tree dynamics (1)
- shrubs (1)
- trait trade-off (1)
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.
...
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.
...
Semi-arid African ecosystems influence trends and variability in global terrestrial carbon dynamics. However, there are uncertainties in potential effects of future climates for semi-arid ecosystems, especially for niche ecosystems. At the same time, African ecosystems provide the livelihoods and ecosystem services for around 1.4 billion people. Future population growth and associated changes in land use pose a challenge for the protection of African biodiversity. Therefore, this work focussed on future impacts of climate change on African ecosystems and carbon dynamics and also for African protected areas (PAs), where they may cooccur with other global change factors. Another focus was on uncertainties associated with future projections and with modelling the Nama Karoo, as an example of a semi-arid niche ecosystem. Dynamic vegetation models (DVMs) were the main research tool.
In Chapter 2, we analysed climate change impacts on African ecosystems and carbon pools until the end of the 21st century and associated uncertainties based on an ensemble of vegetation simulations with the DVM adaptive dynamic vegetation model (aDGVM). We investigated the impact of increased atmospheric CO2 concentrations and two climate change scenarios (medium (RCP4.5) and high emissions (RCP8.5); RCP - representative concentration pathway) on vegetation changes. Differences in the simulated vegetation were primarily driven by assumptions about the influence of CO2 on plants. Elevated CO2 concentrations led to increased total aboveground vegetation biomass and shrub encroachment into grasslands and savannas for both climate scenarios. In simulations without the direct influence of CO2 on plants, there was hardly any shrub encroachment and vegetation biomass decreased or varied between a slight decrease in some cases and a slight increase in others. Based on these results, biome changes due to climate change are likely in Africa in the future. Due to the large uncertainties in future projections, strategies to adapt to climate change must be flexible.
The simulated vegetation in Chapter 2 represented potential, natural vegetation and is particularly suitable to investigate PAs. However, PAs do not exist isolated from their environment and social developments. In Chapter 3, the vegetation projections with CO2 effect from Chapter 2 were combined with projections for population density and land use. Except for many PAs in North Africa, most PAs were adversely affected by at least one of the three drivers by the end of the 21st century in both investigated scenarios ("middle-of-the-road" and "fossil-fuelled development"). Cooccurrence of the drivers varied by region and scenario for PAs. Both scenarios implied increasing challenges for the conservation of African biodiversity in PAs. The impact of climate change on vegetation is likely to be exacerbated by socio-economic change for most African PAs. Strong mitigation of future climate change together with equitable societal development may facilitate successful ecosystem conservation.
The simulations in Chapters 2 and 3 showed large-scale patterns of vegetation change, but their low resolution makes them unsuitable for local analyses. In Chapter 4, the challenges of simulating smaller scale, semi-arid ecosystems and their carbon cycle were analysed for the Nama Karoo with the aDGVM2 and its shrub module. The aDGVM2 is based on the aDGVM, but represents plants more flexibly. In all tested aDGVM2 configurations, the carbon fluxes improved compared to initial simulations but still overestimated them. The measured morphology of the dwarf shrubs and soil water dynamics were not reproduced in aDGVM2. Semi-arid soil water dynamics and coping strategies of semi-arid dwarf shrubs under drought stress are not adequately implemented in the aDGVM2. Further field research on semi-arid water and carbon dynamics of vegetation is necessary to parameterise the aDGVM2 for dwarf shrubs. If these challenges are overcome, DVMs can be a powerful tool for much-needed research on the impacts of climate change on the Nama Karoo.
The analyses have shown that climate change under medium to high emission scenarios is likely to lead to large-scale changes in ecosystems and the carbon balance in Africa. Because lower emissions scenarios come with less uncertainty, climate change adaptation strategies likely need to be less complex or extensive if climate change is minimised. For African PAs, the challenges of climate change may be exacerbated by socio-economic factors to a regionally varying extent. This research suggests that successful ecosystem conservation depends on climate change mitigation measures and ensuring equitable, sustainable development. The shown uncertainties, e.g., in the implementation of the CO2 effect on plants or vegetation dynamics in more niche ecosystems, help to focus future research efforts and increase our understanding of the range of plausible futures we may need to adapt to.