SPECIES DISTRIBUTION MODELING (R)

Goal

This is an attempt to model where a specie is expected to occur either now in places we haven’t looked to see if it’s there or in the future contingent upon changes in the environment. These models can be based on lots of factors but often it’s just environmental ones due to the availability to the kind of data we need. We will build a Generalized Linear model and two environmental predictors.

Dataset

We are using data for the North America Breeding Survey dataset for the hooded ward birds
Dataset attributes

• lon & lat - The location where the survey was conducted to see if the species was there
• present - 1 = Present, 0 = Absent

Enviromental data - Minimum temperature & Annual Precipitation
Current data - dataset from World crim
forecast data - dataset from the Couple Model Inter Comparison Project (CMIP5), a 50 year forecast.

Methodology

1. Load and install packages
2. Explore the data
3. Transform the data by combining data on enviromental factors with data on species occurences
4. We then build models relating to these two factors to one another
5. We then use those models to Predict where those species will occur
6. And use the predict function to provide forecast for a time in the future

Credits

Biostatistics - Makerere University School of Statistics
Weecology

Tools: R, Jupyter Notebooks

1. Load and install packages

2. Data Exploration