Get started with Species Distribution Modelling in Maxent

Learn the basics of species distribution modeling with presence-only data using Maximum Entropy (MaxEnt)
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  • Lectures 28
  • Length 1.5 hours
  • Skill Level Beginner Level
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 5/2015 English

Course Description

Looking to take the next step into your ecological analysis?

Species distribution models provide insight to the relationships between species distribution and the physical/anthropogenic environment. As an ecologist today, you should start looking towards analyzing spatial relationships between species and their environment, and develop your GIS skills. The world of GIS has made ecological research even more interesting, as it expresses results and relationships in visual form.

We cannot overemphasize the importance of GIS in ecology. In this course, we focus on one of the most powerful predictive models in spatial ecology today...Maxent. The Maximum Entropy Algorithm has been borrowed from other natural sciences and adapted in a really clever way to predict suitable environmental conditions for species across large landscapes. The opinion of researchers puts this algorithm as one of the leaders in terms of predictive accuracy. It is based on Machine Learning, and capable of handling multiple species in one model run.

In this course, we dive into the basic steps required to calibrate a model in Maxent.

You will learn the following:

  • Species Data Preparation: How to prepare your Species distribution data in excel spreadsheets. More usually than not, we receive species distribution data collected with a GPS device in spreadsheet format. Here you will learn how to prepare this data in the format required by Maxent.
  • Predictor variable Data Preparation: How to prepare environmental or predictor variables in the format required by Maxent. Maxent supports only specific formats of data, and we will walk through the process of preparing the data for use in the software.
  • Download Maxent: How download and install Maxent and increase the memory usable by the software. Sometimes, your data may be so heavy that Maxent runs out of memory. This course teaches you how to increase the memory available to Maxent.
  • Setting Maxent for a model run: How to set up Maxent, and customize the settings to change your model results.
  • Results Interpretation and Presentation: How to interpret the results generated by Maxent, and presenting the results in visual form using a GIS environment.

You will get tips on how to reduce spatial bias in models, and manipulating some of the settings that act behind the scenes to change Maxent's output.

So what are you waiting for? Sign up and get the ball rolling with Species distribution modeling using Maxent.

What are the requirements?

  • Working knowledge of GIS file formats
  • Some Statistics background, with understanding of terminology such as Model convergence, iteration and machine learning

What am I going to get from this course?

  • Format species distribution data into a format acceptable by Maxent
  • Format environmental layers in a GIS software to a format acceptable by Maxent
  • Download, install and Manage the memory available to Maxent
  • Manipulate Maxent's settings to customize model results
  • Interprete results generated by Maxent
  • Display Maxent's results in a GIS environment and maps

Who is the target audience?

  • This Species distribution model using Maxent is meant for people new to working with Maxent, It will come in handy to those who want to get introduced to Maxent and want to explore what the software does. Spatial ecologists with some statistics background and understanding of Species Distribution Modeling in general will find this useful and interesting.

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Course introduction
Course Introduction
Recommended Background Literature on MaxEnt
Download the Tutorial Data files
Species distribution models overview
Maxent and Background Samples
Section 2: ***Get your Bonus!***
**Claim your sign-up Bonus**
Your Special Invitation
Section 3: Downloading and Installing MaXent

In this lesson you will download MaxEnt into the project directory and make it ready to work.

Maxent Memory Management
Section 4: Data Preparation
The Case Study for this Webinar
Preparing the Species Distribution Data for Maxent
2 questions

This quiz tests your knowledge of formatting species presence data for Maxent

Preparing the Environmental variables for Maxent
Convert environmental layers to ASCII
Preparing the bias or background layer I
Preparing the bias or background layer II
This quiz tests your knowledge of data formatting for Maxent
2 questions
Section 5: Running the MaxEnt Model
Maxent Settings I - Interface at Launch
Maxent Settings II - Basic Settings
Maxent Settings III - Advanced Settings
Maxent Outputs and Features Notes
Section 6: Examining the MaxEnt Results
Results - Introduction
Model Evaluation
Prediction maps
Response Curves
Assessing variable importance
Section 7: Visualizing and presenting Maxent results in GIS
Prepare ArcGIS Workspace
Creating the Continuous probability map
Discrete Binary Suitability Surface.
Section 8: Closing notes
Closing remarks

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Instructor Biography

Neba Funwi-gabga, Database / GIS Specialist

I'm a professionally trained database developer, administrator and a Spatial Ecologist. My work experience spans multiple disciplines, including developing and maintaining databases for nonprofit organizations, performing data science tasks for research institutions, doing extensive data mining in the Oil and gas sector as well as spatial ecology. With over 10 years of experience, I currently coordinate database development for one of Canada's biggest nonprofit organizations. If you need services in oracle, PLSQL, TSQL, Python geospatial scripting or R programming, talk to me!!

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