Computational modeling of species distributions and ecological patterns using environmental, geographic, and biological data.
Methods can combine GIS, environmental variables, statistical models, machine learning, spatial prediction, and uncertainty analysis.
Applications include habitat modeling, biodiversity assessment, ecological prediction, and conservation planning.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.