Skip to main content

Analyzing the Abundance Trend of Uroteuthis edulis in Northern Taiwan Waters Using a Generalized Linear Model

  • Date:2018-06-30
  • Volume:26
  • No:1
  • Page:1-12
  • Auther:Ke-Yang Chang, Kae-Yih Wang and Cheng-Hsin Liao

Uroteuthis edulis is one of the main catch species of the torch light fishery in Taiwan. Because cephalopod resources are heavily affected by the environment and fluctuate annually, the population in the fishery has become vulnerable to collapse resulting from overfishing, a possibility that highlights the importance of resource assessment. In this study, the catch per unit effort (CPUE) was used as the resource index to correlate with the environmental factors, including the previous year CPUE, the monthly Arctic Oscillation Index, the monthly Oceanic Niño Index, the temporal-spatial sea surface temperature (SST) and the sea surface chlorophyll-a (SSC), and a generalized linear model (GLM) was used to establish the U. edulis resource assessment model to predict the abundance trend of the resource. This study showed that there was no significant correlation between the resources in the previous year and the resources in the coming year. Among all environmental factors, the SST in the upwelling in the northern Taiwan waters (the main breeding ground) during the spring breeding season (in March of the fishing year) was positively correlated with the squid population abundance. The SST after the end of the spring breeding season (in May of the fishing year) and the SST in the East China Sea continental shelf (the feeding ground) during growing (in April of the fishing year) were negatively correlated with the squid population abundance. The SSC was negatively correlated with the squid population abundance. The generalized linear model selected by Akaike Information Criterion included the SST in upwelling in April and the SST in the East China Sea continental shelf in April into the model and their explanatory rate was 89.3%. Based on the GLM established in this study, the resource forecasting showed that the resource indicator exhibited a downward trend in 2016, which was consistent with what was actually observed.