The doctoral dissertation in the field of Biology will be examined at the Faculty of Science, Forestry and Technology, Joensuu campus and online.
What is the topic of your doctoral research? Why is it important to study the topic?
My doctoral research investigates how forests respond to environmental changes and extreme climatic events. It focuses on the immediate and carry-over effects of droughts and late-spring frosts on forest productivity, the impact of long-term nitrogen fertilization on drought sensitivity in boreal forests and spatial patterns of root-to-shoot ratios and their influence on biomass turnover time. Using eddy covariance data, long-term field experiments, and machine learning, my research reveals how forest type, climate, and management interact to shape carbon dynamics.
This topic is crucial because forests regulate the global carbon cycle and act as major carbon sinks, yet are increasingly threatened by climate extremes. Understanding these processes helps improve carbon-cycle models and supports sustainable forest management strategies to enhance forest resilience and carbon sequestration under future climate scenarios.
What are the key findings or observations of your doctoral research?
The key findings include forest responses to environmental change vary strongly with forest type, climate, and management. Extreme events such as droughts and late-spring frosts cause both immediate and long-term reductions in productivity, with needleleaf forests showing greater sensitivity. Long-term nitrogen fertilization enhances growth but increases drought vulnerability, revealing a trade-off between productivity and resilience. Spatial modeling further shows that variations in root-to-shoot ratios significantly affect biomass turnover time, linking belowground allocation to carbon-cycle stability.
These findings are valuable because they integrate ecosystem observations, experiments, and machine learning to uncover mechanisms of forest resilience, emphasize sustainable management strategies to enhance forest resilience under increasing climate extremes.
How can the results of your doctoral research be utilised in practice?
The results of my doctoral research can be utilised in practice by improving forest management and climate adaptation strategies. For example, they can be used to identify forest types or regions most vulnerable to drought or late spring frost and to design adaptive management practices, such as species selection, thinning, or fertilization strategies.
Moreover, integrating these results into ecosystem and climate models supports more accurate predictions of forest carbon dynamics, contributing to evidence-based climate mitigation and sustainable forest management planning.
What are the key research methods and materials used in your doctoral research?
My research combines observational, experimental, and modeling approaches to investigate forest responses to climate extremes and management. Key methods such as by using thirty-four eddy covariance in different forest types across the Northern Hemisphere to detect drought and late sprint frost events based on phenology period. Long-term field experiments in boreal Scots pine forests were analyzed to assess how nitrogen fertilization influences drought sensitivity, using physiological and meteorological measurements. In addition, machine learning models were applied to integrate field data, satellite observations, and environmental variables to map spatial patterns of root-to-shoot ratios and biomass turnover time across China’s forests.
The doctoral dissertation of Liang Chen, MSc, entitled Understanding gross primary productivity capacity and biomass turnover in northern hemisphere forests: environmental and biotic influences will be examined at the Faculty of Science, Forestry and Technology, Joensuu campus. The opponent will be Professor Daniel Metcalfe, Umeå University, Sweden, and the custos will be Professor Frank Berninger, University of Eastern Finland. Language of the public defence is English.
For more information, please contact:
Liang Chen, [email protected]
