To build climate resilience, local communities and national governments need to stabilize their ecosystems, both natural and managed ecosystems. The lack of systematic evaluation of past extreme events and their impacts and remaining challenges in representing the major management strategies in global impact models reduces our capacity to assess their usefulness for planning resilient ecosystem management. We will combine satellite data, ecosystem modeling for the entire biosphere and novel climate extreme detection methods to develop an improved understanding of the resilience of different ecosystems and methods for monitoring resilience over larger spatial scales. This project can be integrated with other BRaVE projects focusing on climate, economic or supply risks or other risks in human- managed ecosystems as a first step to understand risks and their implications. The PhD student will be trained in analyses of time series of satellite data, and computer modelling and benefit from expertise of the two main supervisors and integration in their national and international networks, as well as collaboration with PhD students from other disciplines to jointly develop methods for detecting climate risks applied on different scales.

Specific requirements and qualifications for applicants:

• Interest (and possibly knowledge) in programming and working with large, also global geographical and climatological data sets
• Interest (and possibly experience) in processing spatial data with R or Python
• Very good English skills, oral and in writing, including scientific writing
• Demonstrated capacity for timely completion of a high-quality research thesis