The development, extension and application of TreeMig is a core project of the group dynamic macroecology.
Spatio-temporal vegetation dynamics, including plant species migration, plays an important role for range dynamics, carbon sequestration, climate-biosphere-feedbacks and biodiversity in the context of climate change. To assess future vegetation dynamics, large scale, spatio-temporal vegetation models simulating plant migration are indispensable.
We developed the TreeMig model, a spatially explicit and linked forest landscape model originally based on a forest gap model (Lischke et al., 1998), which takes additionally into account tree species migration (Lischke et al., 2006). In each cell (sidelength from 25m to 1km) of a rectangular grid, forest dynamics is simulated at the species level, including environment dependent reproduction, growth, competition, and mortality, and between-cell seed dispersal which allows the simulation of migration (Lischke et al., 2006). Within-cell vertical and horizontal structure is depicted by frequency distributions of tree density in height classes and therefore light attenuation.
An R-wrapper, a GUI, Tutorials and Documentation will be made available by the project TM-Wrapper.
Further model developments
Optimizing by optional Fast Fourier Transformation for seed dispersal (according to Lehsten et al, 2019) and by parallelization by simulating overlapping stripes of the simulation domain on different processors
Coupling with land abandonment(Rickebusch et al., 2007); avalanche dynamics in high alpine regions (Zurbriggen et al., 2014; Teich et al., 2012); rockfall dynamics (Moos & Lischke, 2022; Moos et al., 2021); hydrology, via phenology, leaf area area (project FORHYCS; Speich et al. 2018a, 2018b, 2020)
Upscaling by derivingmigration speeds from TreeMig simulations on a transect under various climatic, competitive and fragmentation conditions (Meier et al., 2012), simulating onlyrepresentative grid cells for certain processes (Nabel & Lischke, 2013; Nabel, 2015);
First regional scale (50*50 cells a 25m*25m) tests, initialized with seeds only in the center cell show first a wavelike spread of the pioneer species, and for species with low seed production strong effects of stochastic seed dispersal. Competition plays a major role in shaping the pattern.
Several simulation studies with TreeMig on the local to country scale demonstrated that climate change and species migration can drastically affect composition and distribution of forests in past and in the future (Lischke, 2020).
Simulations for the Holocene in the Valais region show a vivid dynamics of species composition, determined by succession and migration, which are triggered by immigration events and climate (Lischke, 2004, 2005; Lischke et al., 2006). In contrast, TreeMig simulations indicate that the afforestation (associated with a change in albedo and surface roughness) after a drastic temperature rice during the late-glacialis mostly driven by climate and positive feedbacks via nutrient dynamics and albedo for most species, initiating a successional pattern, which is later affected by the lagged immigration of Pinus (Lischke et al., 2013).
TreeMig has also been applied to simulate climate change driven forest composition to interprete the spread of Quercus ilex in Western France during the last century (Delzon et al., 2013) and the feedback with avalanches in the Dischma-valley in Davos (Zurbriggen et al. 2014, Teich et al. 2012).
Simulations in the boreal/arctic zone of Siberia with climate change indicate that migration of tree species lags the northward shift of their potential niches by several centuries (Epstein et al., 2007; Goetz et al., 2011; Lischke 2020), which has consequences for feedbacks to the climate system by changed albedo and carbon sequestration.
Swiss-wide simulations with 200m resolution driven by one climate change- and several scenarios for land-use change and migration point to strong climate and locally strong and overall moderate effects of land-use, competition and dispersal on species shifts (Lischke, 2020). The species shift upwards, and faster migrating species (e.g. Larch and Spruce) can block intermediately slow down slower migrating species (Stone pine and Beech). Such a blocking was also found in regional simulations of treeline shifts (Scherrer et al., 2020)