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How will Northern Ecosystems respond to Global Environmental Change?

Dr Wolfgang Buermann (SEE), Dr. Roel Brienen (SoG) with Professor Emanuel Gloor (SoG)

Contact email: w.buermann@leeds.ac.uk

Background

Over the past 100 years, the northern high latitudes have warmed more rapidly than anywhere else on Earth due to amplifying (positive) physical feedbacks associated with sea-ice and snow cover changes (IPCC 2013). Observed biological responses of terrestrial ecosystems to this recent high-latitude warming may also drive feedbacks to regional and global climate warming, but our current understanding of these feedbacks is more limited. Positive feedbacks that may be important are due to changes in vegetation albedo associated with northward migration of tree lines and increased growth of shrubs in tundra regions (Pearson et al. 2013), as well as carbon dioxide and methane emissions from increasing fire occurrences (Kasischke & Turetsky 2006) and warming-driven losses of soil carbon from large terrestrial reservoirs (Schuur et al. 2015). Stabilizing (negative) feedbacks may emerge from increased plant growth (Figure 1) and carbon uptake, and changes in dominant growth forms which cause changes in albedo forcings (Beck & Goetz 2011).

In recent decades, several lines of observational-based evidence for strong northern ecosystem responses across multiple spatial scales have emerged. The amplitude of the seasonal cycle of CO2 has been increasing substantially since the 1960s over northern latitudes (Graven et al. 2013). Satellite vegetation studies provided evidence for a persistent ‘greening trend ‘ since the early 1980s across northern biomes (Fig. 1).

 

Figure 1. Spatial patterns of changes in satellite-based vegetation photosynthetic activity. Shown are trends in mean growing season (May-September) normalized difference vegetation index (NDVI) expressed as percentage change relative to the base year 1982. The NDVI is computed as the difference between near-infrared and red reflectance of the land surface and is indicative of potential photosynthetic activity. Areas showing statistically significant (p<0.1) trends are coloured, whereas areas with statistically insignificant trends are shown in white colour. Grey areas correspond to lands not considered in this study. This figure is adopted from Xu et al. (2013).             

 

In this project, the aim is to explore the role of vegetation dynamics behind the positive trend in the CO2 amplitude with a focus on multi-scale satellite observations and modeling approaches and from an ecosystem perspective.

 In this, context, two key hypotheses that will be tested in this project include

H1 Increase in photosynthesis driven by variations in climate, nutrients and/or land cover land use change

H2 Changes in geographic distribution of vegetation cover driven biome shifts and compositional changes.

Objectives

The objectives outlined below are suggestive and will also depend on your interests and background in this area of research. In the first phase of the project, a thorough understanding of ecosystem functioning from a satellite and model perspective is anticipated. For example, how can vegetation dynamics be monitored from space (see Figure 1)? How complex are ecosystem models? A possible research agenda for this project may involve:

  1. Observational analyses: apply novel statistical techniques on long-term satellite vegetation dynamics and climate data sets for the study period 1982-present to characterize the response of northern terrestrial ecosystems to ongoing global environmental change. There is also potential to do fieldwork (e.g. establishment of new sample plots in Siberia and possibly some tree rings) depending on your specific interests. 

  2. Ecosystem model analyses: apply state-of-the-art ecosystem models (e.g. JULES, CLM) to reproduce and better understand vegetation responses that have been identified in step 1 and to estimate corresponding changes in carbon cycling.

  3. Atmospheric transport analyses: Compare spatial distribution, magnitude and variability in simulated CO2 concentrations with observations. Here the outputs of the ecosystem models (step 2) will be used to drive the atmospheric transport model in forward mode to simulate the atmospheric CO2 concentrations. This step will also involve acollaborations with the TOMCAT atmospheric transport modeling group at Leeds (headed by Prof Chipperfield).

Potential for high impact outcome

This PhD project uses the existing world leading expertise within the School of Environment and School of Geography at the University of Leeds to address key issues in earth system science. By developing new and improved understanding as well as running and analyzing state of the art observational and model records, it will have the potential to have a major impact on earth system or climate science. Dr. Buermann, Dr. Brienen and Prof. Gloor are internationally renowned scientists working on issues pertaining to carbon cycle and earth system science.

Training

Through this PhD project you will become familiar with a number of essential tools (models and observations) that are applied in the study of satellite-based vegetation dynamics and the global carbon cycle. Hereby, you will benefit from working within a highly active and multidisciplinary group of scientists in the Leeds Ecosystem, Atmosphere & Forest (LEAF) Centre as well as the Ecology & Global Change Group in Geography. Dr. Buermann, Dr. Brienen and Prof. Gloor have also extensive international collaborations, and this PhD may also involve international travel for training purposes.

The successful PhD student will have access to a broad spectrum of training workshops put on by the Faculty that include an extensive range of training workshops in climate modelling, through to managing your degree, to preparing for your viva. A full listing is available through http://www.emeskillstraining.leeds.ac.uk/.

Requirements

A good first degree (1 or high 2i), or a good Masters degree in a physical or mathematical discipline, such as mathematics, physics, geophysics, engineering, meteorology, geography, or environmental science. Experience with programming languages is of advantage.

Further reading

Beck, P. S. A. & Goetz, S. J. Glob. Change Biol. 17, 2853–2866 (2011).

Euskirchen, E. S. et al., Glob. Change Biol. 13, 2425-2438 (2007).

Graven, H.D. et al., Science 341, 1085–1089 (2013).

IPCC 2013 (http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_SPM_FINAL.pdf)

Kasischke, E. S. & Turetsky, M. R. Geophys. Res. Lett. 33, L09703 (2006).

Schuur, E. A. G.. et al.,Nature. 520, 171–179 (2015)

Pearson, R. G. et al., Nature CC doi: 10.1038/NCLIMATE1858 (2013).

Xu, L. et al., Nature CC doi: 10.1038/NCLIMATE1836 (2013).

Related undergraduate subjects:

  • Biology
  • Engineering
  • Environmental science
  • Geography
  • Geophysics
  • Mathematics
  • Meteorology
  • Physics