In the previous sections I have outlined the global role of human land use and climate change as major drivers of ecosystem change in the Anthropocene. I have given some examples of the multitude of observed and simulated impacts resulting from the two drivers that have been reported in the scientific literature. The overarching question of this dissertation is:
• What are the individual and joint impacts of human interference with the biosphere through climate and land use change during the Anthropocene?
In the context of this dissertation ‘land use’ refers to the use of land for crop production or the use as pastures and rangelands. Built-up area, while locally important in cities, only covers≈0.5 million km2 globally and is not included as a global driver of biome change in this analysis (Klein Goldewijk et al.2010). ‘Climate change’ refers to changes in temperature, precipitation and cloud cover (radiation) beyond interannual variability.
Direct effects of changes in atmospheric CO2 concentration on vegetation are also included in climate change impacts.
Using these definitions, I will explore the following questions:
1. Given that the climate policy debate is focussed very much on temper-ature targets, what are the risks of different levels of global warming for ecosystems? Is there a ‘safe’ level of warming where impacts remain low?
For this question, I will explore eight emissions scenarios for the 21st century span-ning the range from strong mitigation to business as usual with a high reliance on fossil fuels. These scenarios are constructed specifically to lead to global warming of 1.5 to 5 K compared to the pre-industrial level in 2100. Each scenario will be assessed for a number of climate models in order to account for GCM uncertainty.
Anthropocene? When did human activities start to become a force of major ecosystem change? Which of the two forcings, land use or cli-mate change, has been the dominant one?
For this question, I will trace the expansion of agriculture from 1700 to today, as well as the rise in CO2 concentrations following the Industrial Revolution and the resulting climate change during the 20th and early 21st century.
3. How do projected population growth (with the associated demand for land) and climate change interact in pushing the biosphere further out of its Holocene state? Given that climate mitigation may entail a sizeable contribution of biofuels to the global energy mix, are there trade-offs between land use change and climate change?
For this question, I will explore a number of integrated assessment scenarios that provide projections of both future emissions and land use until 2100.
3. Methodology
3.1. Metric of biosphere change
In this dissertation I will focus on the impacts of land use and climate change on the carbon and water cycle of the terrestrial biosphere as well as vegetation composition in terms of major functional types. While these aspects represent only a subset of the full impact of human actions they are crucial to the functioning of the biosphere within the Earth system as a whole. Vegetation productivity and structure determine to a large extent the ability of ecosystems to provide habitats, food and other resources to consumers such as animals and, ultimately, humans as well.
I will use an aggregated metric of joint changes in macroscopic ecosystem features, including carbon and water fluxes and stores as well as vegetation structure, to evaluate
3.2. Biosphere model ecosystem changes caused by climate and land use change (‘Γ’ metric, Heyder et al.
2011). The metric operates under the assumption that substantial changes in these basic characteristics ‘imply far-reaching, potentially self-amplifying transformations in the underlying system characteristics, food chains and species composition’ and a risk that ‘adaptation fails on short time scales and the system restructures or collapses’
(Heyder et al.2011). It allows for a spatially explicit, globally consistent quantification of ecosystem change over time under both historical and future scenario conditions.Γ values range between 0 and 1. Values below 0.1 are interpreted to indicate a risk of minor, values between 0.1 and 0.3 a risk of moderate, and values above 0.3 a risk of major ecosystem changes. To illustrate the magnitude of change corresponding to a certainΓ value, Figure B.2 in Appendix Bpresents the difference between present-day biomes, assuming each biome was transformed completely into the others. As shown, moderate changes (0.1<Γ<0.3) may already correspond to the difference between similar, yet distinct biomes — such as a temperate broadleaved and a temperate coniferous forest — while major changes (Γ>0.3) indicate a transformation to a completely different biome.
While the originalΓ metric was developed to assess climate-driven changes in natural ecosystems, I will expand it here to apply it to both climate-driven and land-use-driven changes. Details about the calculation of the different components of Γ are provided in section E.1 and section E.2 ofAppendix E.
3.2. Biosphere model
I will use the well-established dynamic global vegetation model (DGVM) LPJmL (Sitch et al.2003; Bondeau et al.2007) to quantify shifts in the carbon and water cycle as well as dynamic vegetation composition of the terrestrial biosphere in response to climate and land use change. LPJmL is capable of simulating key physiological and ecological processes such as phenology, photosynthesis, respiration, carbon allocation and turnover between tissue pools, and evapotranspiration for natural vegetation, represented by 9 plant-functional types (PFTs, Sitch et al.2003), agricultural ecosystems represented by 12 crop-functional types (CFTs) and managed grasslands (Bondeau et al.2007), and herbaceous and woody plants grown as dedicated 2nd-generation biomass plantations (Beringer et al. 2011). PFTs of the natural vegetation compete for light, space and water, and their composition in a grid cell is determined dynamically based on climatic
suitability, growth efficiency, climatic stress and fire disturbance (Thonicke et al.2001;
Sitch et al.2003). Crops, managed grasslands and biomass plantations grow on prescribed areas and may be irrigated or rainfed (Bondeau et al.2007; Beringer et al. 2011). Since the model is being developed continuously, the different parts of this dissertation use different versions of LPJmL. A more in-depth description of relevant model processes is provided in each part.
3.3. Scenarios
I will explore the first research question outlined above using a new set of climate change scenarios created specifically for this analysis. The generation of the ‘PanClim’ climate dataset is described in Part II of this thesis. The ‘PanClim’ scenarios are based on 8 stylised emissions trajectories chosen from a large ensemble of emissions scenarios to specifically reach a global warming of 1.5, 2, 2.5, 3, 3.5, 4, 4.5 and 5 K above pre-industrial level around the year 2100. The scenarios contain no further socioeconomic information.
The second research question comprises a historical analysis. I will use a historical land use reconstruction based on the HYDE database and enriched with additional topical detail on crop types and irrigated areas to assess the impact of historical land use change on the biosphere (Klein Goldewijk and van Drecht2006; Portmann et al.2010). Observed climate data and a reconstruction of historical atmospheric CO2 concentrations will be used to assess the impact of historical climate change on the biosphere (Keeling et al.2001; Schneider et al. 2011; Becker et al.2013; University of East Anglia Climatic Research Unit (CRU) et al.2013; Harris et al.2014).
The third research question expands upon the historical analysis conducted for research question 2. I will use the Representative Concentration Pathways (RCPs) which were developed by integrated assessment models (IAMs) (van Vuuren et al. 2011a). The RCPs include both emissions scenarios and land use scenarios for the 21st century based on a set of socioeconomic assumptions. Climate change projections based on the RCPs were produced by a large number of climate models as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5, Taylor et al.2012). The RCP land use
3.3. Scenarios PNVpresent climate change PNVCC
effect
Figure I.3.: Illustration of reference conditions. Left: Setup for research question 1: Climate change impact is calculated as the difference between natural vegetation under climate change (PNVCC) and natural vegetation under present-day climate (PNVpresent). Right: Setup for research question 2 and 3: LUCCC refers to a simulation with climate change and land use change. PNVCCrefers to a simulation with climate change, but without any land use.
LUCnoCCrefers to a simulation with land use change, but with a constant reference climate.
PNVnoCCrefers to a simulation using a constant reference climate and without any land use. Earth image by NASA Goddard Space Flight Center.
scenarios have been harmonised to provide a common spatial and temporal resolution and a smooth transition from historical land use patterns (Hurtt et al.2011).
To assess the changes driven by climate and land use change, it is necessary to define suitable sets of reference conditions for each of the research questions. For question 1, I will use natural vegetation under present-day climate as the reference for the changes to natural ecosystems caused by climate change (PNVpresent, left panel in Figure I.3).
Future climate change impacts are commonly assessed in comparison to a baseline representative of present-day conditions (Carter et al.1994).
For research questions 2 and 3, I will use potential natural vegetation as a reference for the impact of human land use on the biosphere (PNVCC, right panel inFigure I.3). In order to be comparable, the reference for climate change impacts should ideally be ‘a world without anthropogenic climate change’ which, however, is not easily defined. Based on attribution studies, human activities are extremely likely the cause for the majority
be detectable as early as the mid-19th century (Abram et al.2016), the contribution from internal variability, natural and anthropogenic forcing to early observed warming is difficult to quantify (Bindoff et al. 2013). Also taking into account the availability of observation-based gridded climate data, which are used to drive the LPJmL model, climate conditions representative of the first 30 years of the 20th century will be used as the climatic baseline, referred to as ‘noCC’ in Figure I.3. LUCnoCC provides the reference conditions for the impacts of climate change, i.e. a world without climate change, but with land use. Finally, PNVnoCC provides the reference for the combined impact of climate and land use change (right panel inFigure I.3).