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Department of Plant Sciences



Supervisor: Andrew Tanentzap (Plant Sciences
Co-Supervisors: Erik Emilson, Canadian Forest Service, Natural Resources Canada; Adam Pellegrini, Plant Sciences & Nick Payne, Canadian Forest Service, Natural Resources Canada
CASE Partner: Canadian Forest Service

Brief Summary

Exploiting novel sensor technologies to trace carbon fluxes and understand how forest management shapes biogeochemistry from a molecular- to landscape-scale.

Importance of research:

Forest management is a pillar of mitigating climate change. Yet forests lose vast amounts of carbon (C) from soils and dead plant material into receiving waters as dissolved organic matter (DOM). This leak risks releasing large amounts of C back to the atmosphere, largely by feeding microbial respiration. If even some of this plant-fixed CO2 is converted to CH4 by methanogens in waterlogged sites, it can even erase C gains on land (Drake et al. 2017). Although DOM has mostly been treated as a single pool of C, advances in ultra-high-resolution mass spectrometry have revealed it is a diverse mixture of thousands of different molecules, whose diversity can promote different types of microbial activity (Tanentzap et al. 2019 PNAS). Much of this chemical diversity originates from landscape heterogeneity (Kellerman et al. 2014). Thus, as forests change with management, climate warming and disturbance, so too should the pool of DOM in freshwaters and its contribution to regional C budgets.

Project summary:

This project will determine how the molecular diversity of DOM is shaped by forest management and influences landscape-level C sequestration. First, you will characterise biological/chemical processes causing lake-level CO2/CH4 emissions using eddy covariance in a long-term study lake. You will determine how much variation in chemical diversity is explained by microbes vs source material. Second, you will test experimentally the effect of forest management (e.g. fire, harvest, tree planting) on the regional C budget across multiple sites through its effect on chemical diversity. You will again use eddy flux data and track DOM and biological responses (e.g. bacterial/fungal productivity) in forests and lake waters before/after management. Observations can be scaled across ~450,000 km2 with historical disturbance data and remote sensing tools to make future forecasts.

What will the student do?

You will work with the Canadian Forest Service to establish two eddy flux towers at boreal study sites that you will select near the Turkey Lakes watershed, Ontario. You will plan experimental treatments (e.g. prescribed burns, forestry operations) by working with local partners. In the field, you will lead the calibration and optimisation of flux tower sensors. With an autonomous surface vessels (ASV) equipped with automated samplers and sensors, you will monitor chemical and biological processes at a high temporal resolution across the entire lake. The chemical diversity of DOM will be measured occasionally with ultra-high-resolution mass spectrometry and extrapolated with optical sensor data collected by the ASV. With statistical models, you will develop a predictive understanding of the flux tower data from lake-level metabolism and chemical diversity. You will determine if lake C fluxes respond similarly to disturbance as the surrounding forest, which you will monitor with field and remote sensing surveys. Finally, you will use DNA/RNA sequencing to characterise microbial communities and relate their dynamics to DOM with time series analyses, eg. empirical dynamic modelling.


  • Drake, T.W., Raymond, P.A. & Spencer, R.G.M. 2018. Terrestrial carbon inputs to inland waters: A current synthesis of estimates and uncertainty. Limnology and Oceanography Letters, vol. 3, pp. 132-142.
  • Kellerman, A.M., Dittmar, T., Kothawala, D.N. & Tranvik, L.J. 2014. Chemodiversity of dissolved organic matter in lakes driven by climate and hydrology. Nature Communications, vol. 5, pp.3804.
  • Tanentzap, A.J., Fitch, A., Orland, C. et al. 2019. Chemical and microbial diversity covary in fresh water to influence ecosystem functioning. PNAS, vol. 116, pp.24689-24695.

For details on how to apply to the Cambridge NERC Doctoral Training Partnerships see