Modeling invasive plant spread: The role of plant-environment interactions and model structure
Authored by SI Higgins, DM Richardson, RM Cowling
Date Published: 1996
DOI: 10.2307/2265699
Sponsors:
Foundation for Research Development
Flora Conservation Committee of the Botanical Society of South Africa
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
Alien plants invade many ecosystems worldwide and often have substantial
negative effects on ecosystem structure and functioning. Our ability to
quantitatively predict these impacts is, in part, limited by the absence
of suitable plant-spread models and by inadequate parameter estimates
for such models. This paper explores the effects of model, plant, and
environmental attributes on predicted rates and patterns of spread of
alien pine trees (Pinus spp.) in South African fynbos (a
mediterranean-type shrubland).
A factorial experimental design was used to: (1) compare the predictions
of a simple reaction-diffusion model and a spatially explicit, individual-based simulation model; (2) investigate the sensitivity of
predicted rates and patterns of spread to parameter values; and (3)
quantify the effects of the simulation model's spatial grain on its
predictions.
The results show that the spatial simulation model places greater
emphasis on interactions among ecological processes than does the
reaction-diffusion model. This ensures that the predictions of the two
models differ substantially for some factor combinations. The most
important factor in the model is dispersal ability. Fire frequency, fecundity, and age of reproductive maturity are less important, while
adult mortality has little effect on the model's predictions. The
simulation model's predictions are sensitive to the model's spatial
grain. This suggests that simulation models that use matrices as a
spatial framework should ensure that the spatial grain of the model is
compatible with the spatial processes being modeled.
We conclude that parameter estimation and model development must be
integrated procedures. This will ensure that the model's structure is
compatible with the biological processes being modeled. Failure to do so
may result in spurious predictions.
Tags
Dynamics
ecology
population
Rates
Biological invasions
Interspecific competition
Wind dispersal
Organisms
British-isles
Seeds