4.5 Article

Use of different geometric morphometrics tools for the discrimination of phenotypic stocks of the striped clam Ameghinomya antiqua (Veneridae) in north Patagonia, Argentina

Journal

FISHERIES RESEARCH
Volume 101, Issue 1-2, Pages 127-131

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.fishres.2009.09.018

Keywords

Ameghinomya antiqua; Fisheries management; Geometric morphometrics; Phenotypic stock; Shell shape variation

Categories

Funding

  1. Centro Nacional Patagonico (CONICET)
  2. PICT [1398]

Ask authors/readers for more resources

The striped clam (Ameghinomya antiqua (King, 1832)) metapopulation of the San Jose Gulf is a good model for phenotypic stocks studies based on the shell shape variation in different fishing grounds. These sites show differences in circulation, tidal currents, coastal topography, and bathymetry. Furthermore, it is known that the diverse environments produce differences in the growth rate of this species. In the current work, we study the shell shape changes in the striped clam from different fishing grounds of the San Jose Gulf through geometric morphometrics methods. Outlines and landmarks analyses were successful to determinate the provenance of the individuals, with almost the 90% of correct assignations for the most of the fishing grounds. The different methodologies showed variations in diverse morphological traits, and as a result different patterns of the shell shape among localities were evidenced. Moreover, each site presented a typical shell shape. Our results showed that the geometric morphometrics methods are powerful tools to identify and separate intra-specific groups. This approach is applicable to other exploited species with subtle shape variations. (C) 2009 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available