The Spatial Invasion Simulator (SIS) is a spatially explicit,
two-species lattice model. To explore alternative restoration and
invasion scenarios, the two species are designated as Exotic and Native.
Individuals of each species occupy discrete cells on a square lattice. At each time step individuals have
some probability of mortality
(100% if they are annuals). Unoccupied cells are colonized by either
species, depending on their dispersal
mode, their abundance, and the positive
soil feedback state generated by the previous cell occupant.
Positive soil feedback decreases the probability of the other
species establishment and survival. The strength of the feedback
increases with time of occupancy of the species up to the maximum value.
The Model assumes the following:
- The environment is homogenous (there is no variation in the geography, soil type, etc.) and that species are identical in their environmental requirements.
- Net feedback is positive (or zero, i.e., positive feedback effects are greater than or equal to negative feedback effects).
- There is no long-term seedbanking: all propagules come from the previous time step.
Alternative management scenario options include:
- Solarizing the soil (resetting the initial soil feedback state).
- Control of the exotic species (increasing exotic mortality).
- Augmenting native seed production (decreasing exotic/native seed ratio).
The model was written and developed C. Parameters are set in the web-form and the model is executed through a command-line call via Perl-CGI scripts. The source code is open source in accordance with the Open Source Initiative definition.
The model outputs four text files (initial and final lattices, species abundance over time, and a log file). A script written in R (http://www.r-project.org) creates a PDF file (click here for example) containing plots of the output and the log information. Adobe Reader is required to view the file.
The code for the original prototype, developed in R, is also available. Note that lattices larger than 10x10, and longer iterations can be very slow to run.
Acknowledgments: We are very grateful to Margaret Royall for web design and to Harry Mangalam, University of California Irvine Network & Academic Computing Services for his help with the web interface development. This project was supported by a grant from the Center for Invasive Plant Managment (CIPM).
Disclaimer: this software is
provided soley for educational use; the authors accept no
responsibility for decisions based on model results. Restoration and invasive
plant management are best performed within an ecologically-based