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Quantifying the role of forest disturbance regimes in macroecology and carbon cycling

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  • Full or part time
    Dr T Pugh
    Dr E Marais
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

big advances in assessing the frequency with which forests are impacted by large disturbances worldwide (Hansen et al., 2014), but in many ecosystems small-medium-sized disturbances may be much more important (Espirito-Santo et al., 2014). Quantifying the disturbance size-frequency spectrum across different forest types is crucial in order to understand large-scale forest dynamics. Such information will allow to address a range of questions related to macroecology and global carbon cycling.

This is an opportunity to carry out a PhD alongside the TreeMort team within the Biosphere-Atmosphere Exchange group at the University of Birmingham ( The student will work on quantifying the rates of forest disturbances across the disturbance size spectrum, across the range of forest environments worldwide, and understanding their implications for forest ecosystems. This will be achieved through analysis of LIDAR observations and high-resolution satellite remote sensing data. There will be the opportunity to apply the results within a state-of-the-art global ecosystem model, LPJ-GUESS (Smith et al., 2014), to achieve a complete flow from observations, to understanding, to implications. There is significant scope to tailor the project to the specific interests of the student.

The student will benefit from exciting training opportunities and international activity within the Birmingham Institute of Forest Research, resulting from the huge recent investment in forest research at Birmingham ( They will have the opportunity to develop skills in analysis of big data, quantitative ecosystem modelling and scientific code development. There will be substantial opportunities to build strong international links, collaborating with multiple global partners. Some existing experience of computer coding (e.g. R, Python, Matlab) or big data analysis would be an advantage.

For further details please contact Dr Tom Pugh ([Email Address Removed]). Applications can be submitted at any time via the University of Birmingham website.

Funding Notes

Self fund students


Espírito-Santo, F. D. B. et al. Size and frequency of natural forest disturbances and the Amazon forest carbon balance. Nat. Commun. 5, 3434 (2014).

Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–3 (2013).

Smith, B. et al. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11, 2027–2054 (2014).

How good is research at University of Birmingham in Geography, Environmental Studies and Archaeology?

FTE Category A staff submitted: 25.00

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