Fabian Bernhard

Fabian Bernhard

Scientific Collaborator

Geocomputation and Earth Observation, Institute of Geography, University of Bern

Land ecosystems shape our living space. They are furthermore fascinating, complex orchestrations of multiple, simulataneous processes that combine in nonlinear ways. I use mathematical models to study and probe their behavior under changed conditions.

Mathematical models are simplifications of complexities and interactions present in general, real world systems. To me, the art of modeling is to find the right balance between complexity and simplicity; between first principles and data assimilation; and between generalism and specificity. Keeping these balances and focusing on the research question at hand, I aim to tease out the relevant interactions and to correctly project the resulting dynamics and system trajectories. Throughout my own career’s ‘state trajectory’, I have applied analytical and numerical methods to analyze real world systems in fields related to mechanical engineering, pharmacology, or environmental sciences.

Most recently my research focus has been on ecohydrological processes in the soil-plant-atmosphere continuum: During my PhD project, I collected and analyzed time series of stable water isotopes in soil moisture and tree water at numerous Swiss forest sites. These data provide additional observations for hypothesis testing and model calibration of a process-based ecohydrological model LWFBrook90.jl.

Now, as a model developer and scientific programmer within the GECO group, my research focus is widening: spanning spatial scales from individual forest sites to the global, forest-covered area; spanning data sources from remote sensing, over flux towers, to optimality principles; and spanning the combined ecosystem cycles of water, energy, carbon, and nutrients.

Outside of work, I enjoy playing badminton, cycling, languages, traveling, sewing, and watching plants grow.

Interests
  • Soil moisture and vegetation dynamics
  • Terrestrial cycles of water, energy, carbon, and nutrients
  • Soil-plant-atmosphere continuum
  • Mathematical modeling = breaking down complexity
  • Nonlinear dynamical systems analysis
  • (Bayesian) model data fusion
  • Scientific computing
  • Open-source science and software
  • Julia programming language