Overview Environmental heterogeneity (EH), covering the heterogeneity of vegetation, land cover, soil, topography and climate, is a key factor determining biodiversity patterns and ecosystem processes. We need accurate EH data to understand the mechanisms driving diversity loss and generate solutions to bend the biodiversity curve. We also need the dynamics of EH at different spatial scales to understand why the change of biodiversity differ at local, regional, and global scales.
However, a lack of accurate spatial quantification of EH and their change over time have hampered our understanding of the driving mechanisms and their application in biodiversity conservation. Recent developments in Remote Sensing (RS) techniques and the accumulation of high-resolution RS data (e.g., vegetation structure) over time offer the opportunity to quantify EH more accurately.
The goal of the project is to develop a methodological framework to accurately quantify the dynamics of environmental heterogeneity and apply it to specific ecosystems (e.g., terrestrial, aquatic, urban or agricultural systems) to further our understanding of the mechanisms shaping the spatiotemporal patterns of diversity. Moreover, a case study will be carried out to develop landscape-specific measures to maintain or restore specific species diversity (e.g., bird diversity).
The appointed candidate will work closely with a multidisciplinary team including academic staff from multiple fields (e.g., ecology, RS, and environmental sciences) and relevant PhD candidates. The candidate will learn and utilize knowledge and methodology from different fields and gain multidisciplinary skills.
Key tasks - Integrate multi-source data to quantify the dynamics of environmental heterogeneity (EH) across space and time
- Analyze the relationships between the dynamics of EH and species diversity
- Apply the knowledge to develop landscape management measures to maintain/restore targeted species communities