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. It is of major interest to estimate the feedback of arctic ecosystems to theglobal warming we expect in upcoming decades. The speed of this response isdriven by the potential of species to migrate, tracking their climateoptimum. For this, sessile plants have to produce and disperse seeds to newlyavailable habitats, and pollination of ovules is needed for the seeds to beviable. These two processes are also the vectors that pass geneticinformation through a population. A restricted exchange among subpopulationsmight lead to a maladapted population due to diversity losses. Hence, arealistic implementation of these dispersal processes into a simulation modelwould allow an assessment of the importance of diversity for the migration ofplant species in various environments worldwide. To date, dynamic globalvegetation models have been optimized for a global application andoverestimate the migration of biome shifts in currently warming temperatures.We hypothesize that this is caused by neglecting important fine-scaleprocesses, which are necessary to estimate realistic vegetation trajectories.Recently, we built and parameterized a simulation model LAVESI for larchesthat dominate the latitudinal treelines in the northernmost areas of Siberia.In this study, we updated the vegetation model by including seed and pollendispersal driven by wind speed and direction. The seed dispersal is modelledas a ballistic flight, and for the pollination of ovules of seeds produced,we implemented a wind-determined and distance-dependent probabilitydistribution function using a von Mises distribution to select the pollendonor. A local sensitivity analysis of both processes supported therobustness of the model's results to the parameterization, although ithighlighted the importance of recruitment and seed dispersal traits formigration rates. This individual-based and spatially explicit implementationof both dispersal processes makes it easily feasible to inherit plant traitsand genetic information to assess the impact of migration processes on thegenetics. Finally, we suggest how the final model can be applied tosubstantially help in unveiling the important drivers of migration dynamicsand, with this, guide the improvement of recent global vegetation models.

Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model: LAVESI-WIND 1.0