Product catalogue
Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness
Spatial distribution of sponge species richness (SSR) and its relationship with environment are important for marine ecosystem management, but they are either unavailable or unknown. Hence we applied random forest (RF), generalised linear model (GLM) and their hybrid methods with geostatistical techniques to SSR data by addressing relevant issues with variable selection and model selection. It was found that: 1) of five variable selection methods, one is suitable for selecting optimal RF predictive models; 2) traditional model selection methods are unsuitable for identifying GLM predictive models and joint application of RF and AIC can select accuracy-improved models; 3) highly correlated predictors may improve RF predictive accuracy; 4) hybrid methods for RF can accurately predict count data; and 5) effects of model averaging are method-dependent. This study depicted the non-linear relationships of SSR and predictors, generated spatial distribution of SSR with high accuracy and revealed the association of high SSR with hard seabed features.
<b>Citation:</b> Jin Li, Belinda Alvarez, Justy Siwabessy, Maggie Tran, Zhi Huang, Rachel Przeslawski, Lynda Radke, Floyd Howard, Scott Nichol, Application of random forest, generalised linear model and their hybrid methods with geostatistical techniques to count data: Predicting sponge species richness, <i>Environmental Modelling & Software</i>, Volume 97, 2017, Pages 112-129, https://doi.org/10.1016/j.envsoft.2017.07.016
Simple
Identification info
- Date (Creation)
- 2016-07-12
- Date (Publication)
- 2025-02-09T23:23:15
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/101063
- Cited responsible party
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Role Organisation / Individual Name Details Author Li, J.
External Contact Author Alvarez, B.
External Contact Author Siwabessy, J.
Place and Communities Internal Contact Author Tran, M.
External Contact Author Huang, Z.
Place and Communities Internal Contact Author Przeslawski, R.
External Contact Author Radke, L.
External Contact Author Howard, F.
External Contact Author Nichol, S.
Place and Communities Internal Contact Publisher Elsevier Ltd
External Contact
- Name
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Environmental Modelling & Software
- Issue identification
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Volume 97, November 2017
- Page
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112-129
- Purpose
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Submission Environmental Modelling & Software Journal
- Status
- Completed
- Point of contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Resource provider Place and Communities Division
External Contact Point of contact Huang, Z.
Place and Communities Internal Contact
- Spatial representation type
- Topic category
-
- Geoscientific information
Extent
Extent
))
- Maintenance and update frequency
- As needed
Resource format
- Title
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Product data repository: Various Formats
- Protocol
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FILE:DATA-DIRECTORY
- Name of the resource
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Data Store directory containing the digital product files
- Description
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Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- theme.ANZRC Fields of Research.rdf
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EARTH SCIENCES
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- Keywords
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machine learning - ML
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feature selection
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predictive accuracy
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spatial predictive model
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spatial prediction
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model selection
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- Keywords
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Published_External
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Resource constraints
- Title
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Creative Commons Attribution 4.0 International Licence
- Alternate title
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CC-BY
- Edition
-
4.0
- Access constraints
- License
- Use constraints
- License
- Other constraints
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© 2017 The Authors
Resource constraints
- Title
-
Australian Government Security ClassificationSystem
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
- Language
- English
- Character encoding
- UTF8
Distribution Information
- Distributor contact
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
Voice facsimile
- OnLine resource
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Link to Journal
Link to Journal
- Distribution format
-
Resource lineage
- Statement
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Submission Environmental Modelling & Software Journal
- Hierarchy level
- Dataset
Metadata constraints
- Title
-
Australian Government Security ClassificationSystem
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
- Metadata identifier
-
urn:uuid/5bca6f88-2881-49f5-9be6-ae59cd7219d5
- Title
-
GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
- Contact
-
Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Owner Brooke, B.
Place and Communities Internal Contact Point of contact Huang, Z.
Place and Communities Internal Contact
Type of resource
- Resource scope
- Document
- Name
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Journal Article
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with uuid
- Citation identifier
- eCatId/101063
- Date info (Creation)
- 2025-06-19T23:41:13.778Z
- Date info (Creation)
- 2016-07-12T09:43:24
- Date info (Revision)
- 2025-06-19T23:42:14.382Z
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
- Edition
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Version 2.0, September 2018
- Citation identifier
- https://pid.geoscience.gov.au/dataset/ga/122551