Project Details
Projekt
Predicting changes in biodiversity and space use by co-analysis of animal movement data with EO products: an empowerment approach
Applicant
Professor Dr. Martin Wikelski
Subject Area
Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
Term
since 2024
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 522760169
The interplay between organisms and their environment significantly shapes ecosystem functionality and stability. However, climate change, habitat loss and biodiversity decline have disrupted this balance in many regions worldwide. To understand these interactions, ecological research increasingly relies on integrating high-resolution ecological data with Earth Observation (EO) data, such as wind and vegetation information. This integration is crucial for studying species behaviour, habitat preferences and biodiversity measures.However, working with EO data poses challenges due to their complexity and distribution across various platforms. Accessing and transforming these data for analysis is time-consuming and error-prone, hindering the progress of ecological research. Moreover, the interdisciplinary nature of EO science makes it challenging for computational ecologists to choose and utilize the available tools.To address these challenges, this subproject aims to develop demonstrator case studies focusing on climate-induced changes in freshwater availability and their impact on animal movement and species distribution. It involves close collaboration between remote sensing experts, computer scientists and computational ecologists. By integrating expertise from these domains, we will develop reusable components for efficient and reproducible data analysis workflows.The subproject will leverage MoveApps, a serverless, cloud-native platform for animal tracking data analysis, to integrate EO data seamlessly. This integration will enable researchers to analyse animal movement data in combination with EO data more effectively. The ultimate goal is to generally empower the ecological community to gain insights into how species movement is influenced by environmental conditions and processes.The subproject will also focus on a specific use case in the Arctic, where climate change has significant impacts on freshwater availability and biodiversity. By combining tracking data of Arctic migratory birds with high-resolution EO data, it aims to understand how these species respond to changing environmental conditions. Predictive modelling will be employed to anticipate future changes in species distribution and movement patterns.In addition to developing analysis tools, the subproject will address research challenges such as managing big data, integrating different platforms, and ensuring system efficiency and reproducibility. The results will be evaluated and validated through extensive testing and collaboration with regional ecology experts. Ultimately, the subproject aims to advance our understanding of animal-environment interactions and support evidence-based management decisions in ecological conservation.
DFG Programme
Research Units
