Assessing the impacts of human stressors on freshwater carbon cycling – Implications on CO2 emission and biodiversity conservation in Hong Kong


Grant Data
Project Title
Assessing the impacts of human stressors on freshwater carbon cycling – Implications on CO2 emission and biodiversity conservation in Hong Kong
Principal Investigator
Dr Baker, David Michael   (Principal Investigator (PI))
Co-Investigator(s)
Dr Liew Jia Huan   (Collaborator)
Professor Leung Kenneth Mei Yee   (Co-Investigator)
Duration
30
Start Date
2020-09-28
Amount
1299780
Conference Title
Assessing the impacts of human stressors on freshwater carbon cycling – Implications on CO2 emission and biodiversity conservation in Hong Kong
Presentation Title
Keywords
biodiversity conservation, CO2 emission, freshwater carbon cycling, Hong Kong, human stressors
Discipline
Environmental Research
Panel
Physical Sciences (P)
HKU Project Code
ECF Project 86/2019
Grant Type
Environment and Conservation Fund
Funding Year
2019
Status
On-going
Objectives
Organic carbon cycles are a key component of all freshwater ecosystems. Recent evidence suggests that human disruption of freshwater carbon cycles can result in aggravated carbon emissions and declines in biological diversity although the exact mechanisms remain unclear. We propose to assess both phenomena by testing two hypotheses. First, we will determine if human disturbance in river catchments unbalance natural carbon cycles by altering its microbial composition. We postulate further, that this will change rates of organic carbon processing, and thus affect carbon emission rates (e.g., CO2 release to the atmosphere). Second, we propose to assess the impacts of human-disrupted carbon cycles on river biodiversity. We postulate that impacted carbon cycles would alter resource availability (via primary production), resulting in resource limitations in sensitive/vulnerable freshwater species. To this end, we will quantify organic carbon cycles and associated freshwater micro- and macro- diversity across a human disturbance gradient. Empirical data collected from this project will be used to construct predictive models in the public domain (in open access publications), contributing to BSAP’s goals of addressing key knowledge gaps in ecosystem functions, mitigating anthropogenic climate change, and managing ecologically important natural streams and rivers.