[Case Tutorial] Practical Technology of Species Distribution Simulation Based on R Language BIOMOD2 Model

With the holding of the Global Conference on Biodiversity, both management agencies, research institutes, and universities are actively preparing. According to the latest work instructions of the State Forestry and Grass Administration, in view of the current nature reserves in my country, there are generally unclear protection goals and protection effects. Problems such as low levels of biodiversity and protection vacancies still exist, and it is urgent to scientifically identify biodiversity hotspot protection areas and protection vacancies.

  BIOMOD2 provides more than 10 species distribution simulation models to simulate the relationship between a specific species and its environment, trying to use environmental variables to simulate the ecological niche of a specific species.

【原文链接】：基于R语言BIOMOD2模型的物种分布模拟实践技术https://mp.weixin.qq.com/s?__biz=MzU5NTkyMzcxNw==&mid=2247532076&idx=4&sn=13c58174cf394a6dd7cfab4d0be0117c&chksm=fe68b846c91f31506f71e0a0f93f9ce24f98bb9bfa4772cef4b27c1a4e221ee38153da19a4e9&token=1245295760&lang=zh_CN#rd [Method]: Video tutorial + permanent review + long-term assistance of Q&A group + full set of courseware materials

【Introduction】:

Topic 1. "Overview of BIOMOD2 Model":

• Installation of software packages under the R platform
• The function and model introduction of the software package
• Fundamentals of Species Distribution
• Development, types and evaluation methods of species distribution models
• Factors Affecting the Accuracy of Species Distribution Models

Topic 2, "BIOMOD2 Model Operation": 

• Creation of species distribution files

1. Ways and Methods of Data Acquisition
2. Confirmation and screening of species distribution
3. Format of the data file

•  Choice of environment variables

1. Ways and methods to obtain environment variables
2. Selection and handling of environment variables
3. layer processing

•  Model parameters and their settings 

1. Model training and testing
2. weight setting
3. Pseudo-absences data and settings

• Model algorithm introduction and main parameters 

1. Models include: GLM, GBM, GAM, CTA, ANN, SRE, FDA, MARS, RF, and MAXENT.Phillips 

Topic 3, "Analysis and Interpretation of BIOMOD2 Model Running Results  ":

1. Evaluation of Model Effects
2. Contribution of variables (importance)
3. response curve

Topic 4. "Prediction and Analysis of BIOMOD2 Model":

• Scenario predictions under future climate change
• Changes in the species' suitable habitat area, conversion rate, etc.
• MESS analysis process and realization

Topic 5. "Application Cases of BIOMOD2 Model":

• Case based on a single model algorithm (MAXENT)

• Application cases based on combined forecasting models