The role of forest demography in controlling the terrestrial carbon sink

Forest demography, that is the establishment and mortality rates of trees, and the structure of that vegetation within forests, is a fundamental factor underlying the function of a forest and the services it provides. Particular uncertainty exists as to the extent which forest demography current influences the amount of carbon taken up by forests across the globe. The terrestrial biosphere is known to take up about 30% of anthropogenic carbon emissions, but the causes of this uptake are poorly understood (Arneth et al., 2017). In the context of developing strategies to limit global climate change, improving understanding of forest carbon uptake is vital.

This is an opportunity to use a global vegetation model alongside new information about rates of forest disturbances globally, to help constrain the effects of forest demography on the global carbon sink. The student will join the Biosphere-Atmosphere Exchange group at the University of Birmingham, which has a particular focus on forest demography (see bioatmo.wordpress.com), and work closely with various international partners. The model used, LPJ-GUESS, is a state-of-the-art global vegetation model, widely used in major ecosystem assessments, and relatively rare in including explicit representation of forest demography (Smith et al., 2014). 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 (https://www.birmingham.ac.uk/research/activity/bifor/index.aspx). 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. Existing experience of computer coding (e.g. R, Python, Matlab, C) and running computational models 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.