Modeling a Potential Plant Habitat Using Machine Learning Methods

Abstract

The article is devoted to modeling the potential distribution area of the species Pulsatilla turczaninovii Kryl. et Serg. Plant ecological niche modeling is the process of building models using modern computer algorithms and bioclimatic data to predict the distribution range of plant species. The result of the simulation is a model that can be used to map the area of growth or residence of species, predict the range or analyze the impact of the environment on species.
 Data are required on both the presence of species and their absence in a particular territory to build effective models for predicting ecological niches of plants. View absence points (or background points) are not registered in databases, but can be generated using different approaches.
 This article describes the implementation of three approaches to selecting pseudo-absence points of species in an operationally divided territory and presents the result of modeling the potential distribution area of the species Pulsatilla turczaninovii Kryl. et Serg. using the random forest algorithm — the most popular way to build ensembles of decision trees. The software implementation of the model is carried out in the high-level Python programming language.