Simulating long-distance seed dispersal in a dynamic vegetation model


  • Rebecca S. Snell

    Corresponding author
    1. Faculty of Forestry, University of Toronto, Toronto, ON, Canada
    Current affiliation:
    1. Forest Ecology, Institute of Terrestrial Ecosystems, Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland
    • Correspondence: R. S. Snell, Faculty of Forestry, University of Toronto, Toronto, ON, Canada M5S 3B3.


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  • Editor: Bill Shipley



Predicting the migration of vegetation in response to climate change is often done using a climate-driven vegetation model; however, the assumption of full migration (where seeds are not limited by distance or barriers) is a common criticism. Previous efforts to incorporate limitations on seed dispersal have occurred exclusively in bioclimatic envelope models. This paper describes how limitations on seed dispersal were integrated into a physiologically based dynamic vegetation model, LPJ-GUESS.


An idealized landscape, representative of temperate and boreal forests in North America.


LPJ-GUESS already simulates establishment, growth, reproduction and competition. I used a generic seed dispersal kernel to determine the probability of dispersal between grid cells, and a logistic function to determine the spread between patches within a grid cell. Plant functional types were parameterized to represent three temperate tree species, Acer, Pinus and Tsuga, by using published dispersal kernels and life-history measurements. Simulations were run with full and limited migration, and compared with past vegetation migration rates.


Using the old assumption of full migration, the entire landscape was colonized at the same time (migration rates of 270–380 m year−1). With the new limited dispersal, species colonized the landscape one row at a time, at rates which corresponded well with independent migration estimates based on genetic or pollen reconstructions (Acer, 141 m year−1; Pinus, 76 m year−1). Tsuga was the only species where simulated migration rates (85 m year−1) were quite a bit slower than historical migration estimates.

Main conclusions

The new model was able to simulate reasonable migration rates, which is a substantial improvement over previous assumptions of full migration. Migration estimates which include the effects of limitations on dispersal, demography, competition and plant physiology will also improve our understanding of how climate change and various other processes can influence plant range shifts.