
Forests are crucial in supporting biodiversity and providing ecosystem services. Understanding forest biodiversity dynamics under different management strategies and climate change scenarios is essential for effective conservation and management. This paper introduces the Forest Biodiversity Dynamics Prototype Digital Twin (pDT), integrating forest and biodiversity models to predict the effects of management options on forest ecosystems. The primary objective is to identify optimal management strategies that promote biodiversity, focusing on conservation and adaptation to different climate conditions. We start with the case of Finnish forests and bird species and plan to expand to include more European countries and a variety of species as the pDT is further developed.
multiobjective optimisation, mallintaminen, LAND, kestävä kehitys, LANDIS-II, Science, metsänkäsittely, metsäekologia, Q, forest management, Multiobjective Optimization Group, Computational Science, biodiversiteetti, metsäekosysteemit, joint species distribution models, biodiversity conservation, luonnonsuojelu, Laskennallinen tiede
multiobjective optimisation, mallintaminen, LAND, kestävä kehitys, LANDIS-II, Science, metsänkäsittely, metsäekologia, Q, forest management, Multiobjective Optimization Group, Computational Science, biodiversiteetti, metsäekosysteemit, joint species distribution models, biodiversity conservation, luonnonsuojelu, Laskennallinen tiede
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