格拉斯哥喀里多尼亚大学招收气候科学博士

格拉斯哥喀里多尼亚大学招收气候科学博士

About the Project

REFERENCE NUMBER

Please use the following reference number: SCEBE-22SF-CLIFE-Ollauri

Either select from the drop down list or refer to the reference number in the prospective applicant text box if applying that way.

BACKGROUND

The ability of forest ecosystems to store carbon (C; e.g. CO2) above and belowground makes afforestation one of the leading measures to fight climate change. Atmospheric CO2 is trapped in the vegetation and then stored in the forest soil, from where it cycles back to the atmosphere as a result of soil respiration (SR). SR is a complex soil microbial process depending on the soil properties and composition, hydro-climatic conditions, and vegetation type. The succession of drying and wetting hydrological cycles within the forest soil seems to trigger “hot-spots” and “hot-moments” of SR, by which large amounts of CO2 are released from the soil. Over 50 % of this CO2 may be released in dissolved form, entering the soil solution and, thus, being potentially lost through soil percolation and then transported to other environmental compartments. Yet, the latter component of the C cycle has been largely neglected, leading to systematic underestimations of SR and to an inaccurate account on the contribution of forest ecosystems to mitigating climate change.

AIMS

The aims of the project are to:

• Explore the combination of biological, edaphological, and climatic factors regulating Soil Respiration

• Investigate plant traits contributing to the formation of “hot-spots” and “hot-moments” of soil respiration

• Quantify C leakage through soil percolation

• Build numerical models able to describe and predict C leakage in forest soils under different climate scenarios

• Disseminate the project outcomes to relevant stakeholders

CANDIDATE SPECIFICATIONS

The successful applicant will be able to demonstrate understanding of ecosystems functioning and biogeochemical and hydrological cycles. Expertise undertaking field and laboratory work is desirable. A good grasp of statistical methods and tools, such as R, is preferable. Effective oral and written communication skills are mandatory.

Candidates are invited to submit a more detailed research proposal (of a maximum of 2000 words) on the project area as part of their application.

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