Dataset

Data from: Distribution Pattern of Bivalve in Littoral Zone Gisi Village, Bintan District,Riau Island Province

SWP OBIS Open in mapper Explore occurrences

This study aims to determine the distribution pattern and type of bivalves in Littoral Zone Gisi Village. This study was conducted in November 2015 located in the littoral zone Gisi Village, Bintan district, Riau Island Province, Indonesia. Determination of the sampling method used in this research is Random Sampling with Visual Sampling Plan (VSP) software and the plot size 1x1 m2.The research results obtained 7 species of bivalves from 4 families. Distribution Pattern is Clumped. Diversity Index (H’) 1.746 medium categorized, Uniformity index (E) 0.8974 in conditions of high, dominance index (D) 0.1916 low categorized. The average value of the range of temperatures in the range of 29.93 - 31.2 C, salinity in the range of 27.28 - 28.78 ‰, the degree of acidity (pH) in the range of 7.40 - 7.9, and dissolved oxygen (DO) in the range of 7.71 - 8.05mg/l, and sediment type is mud.

Citation: Irawan A, Ferdiansyah H, Pratomo A (2021): Data from: Distribution Pattern of Bivalve in Littoral Zone Gisi Village, Bintan District,Riau Island Province. v1.1. Southwestern Pacific Ocean Biogeographic Information System (OBIS) Node. Dataset/Occurrence. https://nzobisipt.niwa.co.nz/resource?r=bivalvegisi&v=1.1

Published: August 22, 2021 at 23:49

URL: https://nzobisipt.niwa.co.nz/resource?r=bivalvegisi

Andri Irawan
Programme Study of Marine Science, FIKP UMRAH

Henky Ferdiansyah
Programme Study of Marine Science, FIKP UMRAH

Arief Pratomo
Programme Study of Marine Science, FIKP UMRAH

Andri Ferdiansyah
Programme Study of Marine Science, FIKP UMRAH

7
occurrence records
7
taxa
7
species

Taxa

Missing and invalid fields

Field Missing Invalid
maximumDepthInMeters 7
100.0%
minimumDepthInMeters 7
100.0%

Quality flags

The OBIS data quality flags are documented at https://github.com/iobis/obis-qc.

Flag Dropped Records
NO_DEPTH 7
100.0%

Measurement types

DNA derived data