Kolloquium: Henrik Hartmann

Institutskolloquium

  • Datum: 23.01.2025
  • Uhrzeit: 14:00
  • Vortragende(r): Henrik Hartmann
  • Julius Kühn Institute for Forest Protection
  • Raum: Hörsaal (C0.001)
  • Gastgeber: Susan Trumbore
Digital forest twins – breaking the glass dome of forest vegetation models
Global warming and climate extremes can be precursors and triggers for tree vitality loss and mortality, often amassing to forest decline or dieback over large spatial scales. In many instances, even tree species that were considered drought and heat tolerant have experienced severe damage and dieback levels, suggesting a lack of process understanding of tree stress physiology. Research during the last decades has focused on improving our understanding of tree physiological responses to drought and heat and substantial progress has been achieved, like in unveiling the role of carbon reserves during periods of resource limitation. This knowledge may provide process realism for predictive vegetation models, which notoriously fail in realistically forecasting mortality, but progress is still in its infancy. In addition, vegetation modelling often ignores important drivers of forest dynamics and dieback, like insects or disease, making trees live under a glass dome.In this talk, I will present innovative approaches of the recently founded Julius Kühn-Institute for Forest Protection. In a vegetation model, we establish forest digital twins that are continuously fed by physiological data streams from trees in the forest, and implement mechanisms of tree vulnerability to biotic agents using entomological and pathological expertise. The large-scale application of this twin requires the extensive and near real-time integration of remote sensing data on forest condition and forest damage. Digital twins learn from real forest responses to climate extremes and incorporate interactions between trees and biotic agents, making the digital forest twin more than just trees under a glass dome. They learn from instantaneous behavior of trees to new conditions and thus constantly calibrate themselves - away from fixed model parameters and towards dynamic, nature-informed models. Digital twins may eventually be used as time machines for policy decision-making, allowing embracing uncertainty across management and climate scenarios.

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