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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

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Modeling invasive species spread in Lake Champlain via evolutionary computations.

B M Osei¹, C D Ellingwood, J P Hoffmann

¹Department of Mathematics and Computer Science, Eastern Connecticut State University, 83 Wndham St, Willimantic, CT 06226, USA. oseib@easternct.edu

Theory in Biosciences = Theorie in Den Biowissenschaften

|February 5, 2011

Summary

A new model framework using reaction diffusion and genetic algorithms accurately predicts invasive species spread. This approach successfully modeled Zebra mussel invasion dynamics in Lake Champlain.

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Area of Science:

Ecology
Mathematical Biology
Invasive Species Research

Background:

Biological invasions pose significant ecological and economic threats worldwide.
Predictive modeling is crucial for understanding and managing invasive species spread.
Existing models often lack the flexibility to incorporate complex ecological factors.

Purpose of the Study:

To develop a general modeling framework for biological invasions.
To integrate reaction diffusion equations with genetic algorithms for robust model selection.
To accurately predict the spread dynamics of invasive species, using Zebra mussels as a case study.

Main Methods:

Generalized reaction diffusion equations to include dispersal, advection, and density dependence (linear, non-linear, Allee effect).
Employed a genetic algorithm for automated, parsimonious model selection.
Validated the model using empirical data of Zebra mussel spread in Lake Champlain.

Main Results:

The combined reaction diffusion and genetic algorithm approach successfully identified parsimonious models for invasive spread.
Estimated Zebra mussel minimum wave spread rate at 22.5 km/year.
Predicted a northward advection rate of 60.6 km/year, closely matching the hydrologic residence time of Lake Champlain (60 km/year).

Conclusions:

The developed modeling framework effectively captures the hydrodynamic features influencing invasive species spread.
The approach provides a powerful tool for predicting and managing biological invasions in aquatic ecosystems.
Accurate modeling of invasive species dynamics is essential for effective conservation and management strategies.