R IIN T AMME, L ARS G ÖTZENBERGER, M ARTIN Z OBEL, J AMES M. B ULLOCK, D ANNY A. P. H OOFTMAN, A NTS K AASIK, M EELIS P ÄRTEL Predicting seed dispersal distances from simple plant traits

We collected available maximum dispersal distance data for plant species

576 plant species are currently represented in our database

We collected plant trait data from original studies or databases dispersal syndrome growth form seed mass seed releasing height terminal velocity

We related these plant traits to maximum dispersal distances

Average maximum dispersal distance increases from species with no special mechanisms for dispersal to ballistic, ant, wind, and animal dispersal 1.1 m 3.6 m 6.5 m 47.6 m 196 m

Average maximum dispersal distance also increases from herbs to shrubs and trees 5.2 m 24.4 m 295 m

We then built models to predict plant species’ maximum dispersal distances from simple plant traits

O BSERVED MAXIMUM DISPERSAL DISTANCE ( LOG ; M ) P REDICTED MAXIMUM DISPERSAL DISTANCE (L OG ; M ) Simple plant traits explained up to 60% of variation in maximum dispersal distances We used 2/3 of the data to build the models and 1/3 of the data as a test set to test the predictions For the test set we predicted dispersal distances using parameters from the models and related these to observed values

We provide a function dispeRsal to predict maximum dispersal distances for users’ own datasets

How to predict plant species’ dispersal distances using dispeRsal function in ?

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Download and install R is a free software environment for statistical computing and graphics

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Download and load dispeRsal function Simply download the dispeRsal file Double-clicking the file automatically opens R and loads the dispeRsal function

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Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH You can use Excel or similar software to prepare the dataset

Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH Enter the species names without authorship It is also possible to only include genus level

Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH Enter either tree, shrub, or herb Species growth form

Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH Enter either animal, ant, ballistic, wind.none, or wind.special Species dispersal syndrome You can use different online databases to obtain data on species’ dispersal syndrome

Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH Seed mass Enter the value in log10 transformed format (using mg) If no data is available, you can leave the cell empty

Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH If no data is available, you can leave the cell empty Enter the value in log10 transformed format (using m/s) Seed terminal velocity

Prepare the data file Your data file has to follow a specific format SpeciesGFDSSMTVRH If no data is available, you can leave the cell empty Seed releasing height (or plant height) Enter the data in log10 transformed format (using m)

For example… SpeciesGFDSSMTVRH Acer platanoidestreewind.special Abies albatreewind.special Viola montanaherbballistic Viola arvensisherbballistic Viola arvensisherbant

For example… Save your file in a comma separated file format (.csv) Make sure your data file is in the same directory as the dispeRsal file Note that you can enter a species multiple times to predict dispersal distance for different syndromes SpeciesGFDSSMTVRH Acer platanoidestreewind.special Abies albatreewind.special Viola montanaherbballistic Viola arvensisherbballistic Viola arvensisherbant

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your.data <- read.table(“YourFileName.csv”, header=TRUE, sep=“;”, dec=“.”) You may need to modify the values for separator (sep) and decimal (dec) depending on your file format Read in your data to

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dispeRsal(your.data, model=5) Use dispeRsal function

dispeRsal(your.data, model=5) The value for model can be either 1, 2, 3, 4, or 5 Use dispeRsal function 1 uses DS, GF, TV 2 uses DS, GF, SM, RH 3 uses DS, GF, RH 4 uses DS, GF, SM 5 uses DS, GF Choose the model depending on the data available (you can run the function several times using different models) Note that the simplest model (5) only uses DS and GF data even for species that have more data available

The output… SpeciesOrderFamilyDSlog10MDD _Family log10MDD _Order log10MDD _measured Acer platanoides SapindalesSapindaceaewind.special Abies albaPinalesPinaceaewind.special Viola montanaMalphigialesViolaceaballistic NA Viola arvensisMalphigialesViolaceaballistic Viola arvensisMalphigialesViolaceaant NA

The output… The function automatically assignes your species to a family and an order SpeciesOrderFamilyDSlog10MDD _Family log10MDD _Order log10MDD _measured Acer platanoides SapindalesSapindaceaewind.special Abies albaPinalesPinaceaewind.special Viola montanaMalphigialesViolaceaballistic NA Viola arvensisMalphigialesViolaceaballistic Viola arvensisMalphigialesViolaceaant NA

The output… The function predicts dispersal distances taking account the taxonomy of the species (family or order) SpeciesOrderFamilyDSlog10MDD _Family log10MDD _Order log10MDD _measured Acer platanoides SapindalesSapindaceaewind.special Abies albaPinalesPinaceaewind.special Viola montanaMalphigialesViolaceaballistic NA Viola arvensisMalphigialesViolaceaballistic Viola arvensisMalphigialesViolaceaant NA Note that the maximum dispersal distance values are log10 transformed (in m)

The output… If possible, also the measured maximum dispersal distance from the original data source is given SpeciesOrderFamilyDSlog10MDD _Family log10MDD _Order log10MDD _measured Acer platanoides SapindalesSapindaceaewind.special Abies albaPinalesPinaceaewind.special Viola montanaMalphigialesViolaceaballistic NA Viola arvensisMalphigialesViolaceaballistic Viola arvensisMalphigialesViolaceaant NA Note that the maximum dispersal distance values are log10 transformed (in m)

For more information…

dispeRsal is being presented by a research article in Ecology, which we kindly ask you to cite in case you use the tool and its output for your own publications Riin Tamme, Lars Götzenberger, Martin Zobel, James M. Bullock, Danny A. P. Hooftman, Ants Kaasik, and Meelis Partel (In press). Predicting species' maximum dispersal distances from simple plant traits. Ecology http://dx.doi.org/ /