THE USE OF REMOTE SENSING, REGRESSION QUANTILES, AND GIS APPROACHES FOR MODELING OF SCALLOP LARVAE: A Case Study in Funka Bay, Hokkaido, Japan
Abstract: In the development
of scallop cultivation in Japan, larvae collection and propagation become an
important factor. Although the monitoring program has been conducted, modeling
of species distribution is becoming an important tool for understanding the
effects of environmental changes and resources management. This study was
conducted to construct a model for providing estimation of the scallop larvae
distribution in Funka Bay, Hokkaido, Japan using the integration of remote
sensing, Regression Quantile (RQ) and Geographic Information System (GIS)-based
model. Data on scallop larvae were collected during one year spawning season
from April to July 2003. Environmental parameters were extracted from multi
sensor remotely sensed data (chlorophyll-a and sea surface temperature) and a
hydrographic chart (water depth). These parameters together with larvae data
were then analyzed using RQ. Finally, spatial models were constructed within a
GIS by combining the RQ models with digital map of environmental parameters.
The results show that the model was best explained by using only sea surface
temperature. The highest larvae densities were predicted in a relatively broad
distribution along with the shallow water regions (Toyoura and Sawara to
Yakumo) and the deeper water areas (center of the bay). The spatial model built
from the RQ provided robust estimation of the scallop larvae distributions in
the study area, as confirmed by model validation using independent data. These
findings could contribute on the monitoring program in this region in order to
distinguish the potential areas for an effective spat collection.
Keywords: scallop larvae;
spatial distributions; regression quantiles; GIS; remote sensing; Funka Bay
Author: I Nyoman Radiarta
Journal Code: pperikanangg110023
