2011
DOI: 10.1890/09-1887.1
|View full text |Cite
|
Sign up to set email alerts
|

Selecting statistical models and variable combinations for optimal classification using otolith microchemistry

Abstract: Reliable assessment of fish origin is of critical importance for exploited species, since nursery areas must be identified and protected to maintain recruitment to the adult stock. During the last two decades, otolith chemical signatures (or "fingerprints") have been increasingly used as tools to discriminate between coastal habitats. However, correct assessment of fish origin from otolith fingerprints depends on various environmental and methodological parameters, including the choice of the statistical metho… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

6
96
0
2

Year Published

2012
2012
2020
2020

Publication Types

Select...
6

Relationship

1
5

Authors

Journals

citations
Cited by 102 publications
(104 citation statements)
references
References 64 publications
6
96
0
2
Order By: Relevance
“…Habitat discrimination based on otolith fingerprints from LA-ICPMS measurements was achieved using a random forest (RF) algorithm (Breiman 2001), recently shown to be highly accurate for Sparus aurata habitat differentiation in the study area (Mercier et al 2011b). Although the method is still new to ecologists, it has been widely used in bioinformatics (e.g.…”
Section: Discussionmentioning
confidence: 99%
See 4 more Smart Citations
“…Habitat discrimination based on otolith fingerprints from LA-ICPMS measurements was achieved using a random forest (RF) algorithm (Breiman 2001), recently shown to be highly accurate for Sparus aurata habitat differentiation in the study area (Mercier et al 2011b). Although the method is still new to ecologists, it has been widely used in bioinformatics (e.g.…”
Section: Discussionmentioning
confidence: 99%
“…Among the chemical elements measurable in the otoliths, some can be less informative than others, and bring more noise than signal in habitat classification (Mercier et al 2011b). In order to identify the optimal RF classifier for reconstruction of fish movement from otolith signatures, i.e.…”
Section: Discussionmentioning
confidence: 99%
See 3 more Smart Citations