↓ Skip to main content

Machine Learning for Ecology and Sustainable Natural Resource Management

Overview of attention for book
Cover of 'Machine Learning for Ecology and Sustainable Natural Resource Management'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective
  3. Altmetric Badge
    Chapter 2 Use of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook
  4. Altmetric Badge
    Chapter 3 Boosting, Bagging and Ensembles in the Real World: An Overview, some Explanations and a Practical Synthesis for Holistic Global Wildlife Conservation Applications Based on Machine Learning with Decision Trees
  5. Altmetric Badge
    Chapter 4 From Data Mining with Machine Learning to Inference in Diverse and Highly Complex Data: Some Shared Experiences, Intellectual Reasoning and Analysis Steps for the Real World of Science Applications
  6. Altmetric Badge
    Chapter 5 Ensembles of Ensembles: Combining the Predictions from Multiple Machine Learning Methods
  7. Altmetric Badge
    Chapter 6 Machine Learning for Macroscale Ecological Niche Modeling - a Multi-Model, Multi-Response Ensemble Technique for Tree Species Management Under Climate Change
  8. Altmetric Badge
    Chapter 7 Mapping Aboveground Biomass of Trees Using Forest Inventory Data and Public Environmental Variables within the Alaskan Boreal Forest
  9. Altmetric Badge
    Chapter 8 ‘Batteries’ in Machine Learning: A First Experimental Assessment of Inference for Siberian Crane Breeding Grounds in the Russian High Arctic Based on ‘Shaving’ 74 Predictors
  10. Altmetric Badge
    Chapter 9 Landscape Applications of Machine Learning: Comparing Random Forests and Logistic Regression in Multi-Scale Optimized Predictive Modeling of American Marten Occurrence in Northern Idaho, USA
  11. Altmetric Badge
    Chapter 10 Using Interactions among Species, Landscapes, and Climate to Inform Ecological Niche Models: A Case Study of American Marten (Martes americana) Distribution in Alaska
  12. Altmetric Badge
    Chapter 11 Advanced Data Mining (Cloning) of Predicted Climate-Scapes and Their Variances Assessed with Machine Learning: An Example from Southern Alaska Shows Topographical Biases and Strong Differences
  13. Altmetric Badge
    Chapter 12 Using TreeNet, a Machine Learning Approach to Better Understand Factors that Influence Elevated Blood Lead Levels in Wintering Golden Eagles in the Western United States
  14. Altmetric Badge
    Chapter 13 Breaking Away from ‘Traditional’ Uses of Machine Learning: A Case Study Linking Sooty Shearwaters (Ardenna griseus) and Upcoming Changes in the Southern Oscillation Index
  15. Altmetric Badge
    Chapter 14 Image Recognition in Wildlife Applications
  16. Altmetric Badge
    Chapter 15 Machine Learning Techniques for Quantifying Geographic Variation in Leach’s Storm-Petrel (Hydrobates leucorhous) Vocalizations
  17. Altmetric Badge
    Chapter 16 Machine Learning for ‘Strategic Conservation and Planning’: Patterns, Applications, Thoughts and Urgently Needed Global Progress for Sustainability
  18. Altmetric Badge
    Chapter 17 How the Internet Can Know What You Want Before You Do: Web-Based Machine Learning Applications for Wildlife Management
  19. Altmetric Badge
    Chapter 18 Machine Learning and ‘The Cloud’ for Natural Resource Applications: Autonomous Online Robots Driving Sustainable Conservation Management Worldwide?
  20. Altmetric Badge
    Chapter 19 Assessment of Potential Risks from Renewable Energy Development and Other Anthropogenic Factors to Wintering Golden Eagles in the Western United States
  21. Altmetric Badge
    Chapter 20 A Perspective on the Future of Machine Learning: Moving Away from ‘Business as Usual’ and Towards a Holistic Approach of Global Conservation
Overall attention for this book and its chapters
Altmetric Badge

Mentioned by

23 X users
4 Facebook pages


76 Dimensions

Readers on

213 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Machine Learning for Ecology and Sustainable Natural Resource Management
Published by
Springer International Publishing, January 2018
DOI 10.1007/978-3-319-96978-7
978-3-31-996976-3, 978-3-31-996978-7

Grant Humphries, Dawn R. Magness, Falk Huettmann

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 213 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 18%
Researcher 39 18%
Student > Master 36 17%
Student > Doctoral Student 12 6%
Student > Bachelor 8 4%
Other 28 13%
Unknown 51 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 66 31%
Environmental Science 38 18%
Computer Science 17 8%
Earth and Planetary Sciences 7 3%
Engineering 7 3%
Other 12 6%
Unknown 66 31%