Species Distribution Modelling (SDM): A Guide

Background

Species Distribution Modelling (SDM) is a technique widely used in many fields of natural and biological sciences to infer the ecological requirements of species and to predict their geographic distributions (Elith & Leathwick, 2009). Species distribution models can be used to support conservation decision making (Guisan et al., 2013). Forecasting endangered species distribution under climatic change scenario is increasingly used in conservation biology (Muñoz et al., 2013), while forecast the spread of invasive species is receiving a growing interest in invasion biology (Verbruggen et al., 2013). The aim of SDMs is to infer the probability of occurrence of a taxon given a set of variables (climate, elevation, soil type, etc.) that are assumed to be related to the distribution and habitat preferences of the taxon under study. 

This resource is a technical guide aimed at providing the basic elements needed to build a Species Distribution Model. 

Specific knowledge of the topic is not mandatory. However, in order to have a correct understanding of the information contained in the tutorial, and even more for a proper interpretation of the output, some basics of statistics (e.g., notions of modelling like GLM, GAM, etc.) and a sound knowledge of the statistic environment of R is recommended.

Learning Objectives

It is expected that, with this tutorial, participants will be better positioned to:

1. Illustrate distribution model concepts and how it applies to ecology, evolutionary biology and conservative biology;

2. Discuss procedures to obtain free occurrence database and techniques for cleaning and validating occurrency data;

3. Examine algorithms for modelling species occurrence and tests for evaluating robustness of the analysis;

4. Assess validity and correctness of output interpretation;

5. Simulate all the steps needed to realize a species distribution model (SDM) of a species of choice.

Contents and Structure

Training Blocks:

1. Occurrence data;

2. The environmental variables;

3. Running the analysis;

4. The output interpretation and test of robustness;

5. Survey of available software.

Target Audience

The tutorial is aimed at both students and researchers, that have the need or the interest to acquire the basic knowledge on how to realize a distribution model.

Production