Get started with Species Distribution Modelling in Maxent
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Get started with Species Distribution Modelling in Maxent

Learn the basics of species distribution modeling with presence-only data using Maximum Entropy (MaxEnt)
4.2 (43 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
591 students enrolled
Created by Neba Funwi-gabga
Last updated 3/2016
English
Current price: $10 Original price: $105 Discount: 90% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 1.5 hours on-demand video
  • 2 mins on-demand audio
  • 6 Articles
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • 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
View Curriculum
Requirements
  • Working knowledge of GIS file formats
  • Some Statistics background, with understanding of terminology such as Model convergence, iteration and machine learning
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.

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.
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Curriculum For This Course
28 Lectures
01:37:55
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Course introduction
5 Lectures 11:21

Recommended Background Literature on MaxEnt
00:44

Download the Tutorial Data files
00:39


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***Get your Bonus!***
2 Lectures 00:19
**Claim your sign-up Bonus**
00:18

Your Special Invitation
00:01
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Downloading and Installing MaXent
2 Lectures 08:22

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

Download and Install MaxEnt
06:54

Maxent Memory Management
01:28
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Data Preparation
6 Lectures 31:15
The Case Study for this Webinar
00:26

Preparing the Species Distribution Data for Maxent
05:40

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

Species data formatting for Maxent
2 questions

Preparing the Environmental variables for Maxent
07:42

Convert environmental layers to ASCII
01:44

Preparing the bias or background layer I
12:45

Preparing the bias or background layer II
02:58

This quiz tests your knowledge of data formatting for Maxent
2 questions
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Running the MaxEnt Model
4 Lectures 17:55

Maxent Settings II - Basic Settings
04:13

Maxent Settings III - Advanced Settings
05:43

Maxent Outputs and Features Notes
02:21
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Examining the MaxEnt Results
5 Lectures 12:15
Results - Introduction
01:49

Model Evaluation
04:02

Prediction maps
01:25

Response Curves
02:15

Assessing variable importance
02:44
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Visualizing and presenting Maxent results in GIS
3 Lectures 13:19
Prepare ArcGIS Workspace
02:19

Creating the Continuous probability map
04:47

Discrete Binary Suitability Surface.
06:13
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Closing notes
1 Lecture 01:44
Closing remarks
01:44
About the Instructor
Neba Funwi-gabga
4.0 Average rating
82 Reviews
1,685 Students
4 Courses
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!!