Ensemble modeling of black pomfret ( Parastromateus niger ) habitat in the Taiwan Strait based on oceanographic variables

PeerJ

article

Sandipan Mondal¹  Ming An Lee¹  Yu-Kai Chen⁴  Yi-Chen Wang¹ 

[1] Environmental Biology & Fishery Science, National Taiwan Ocean University;Center of Excellence for Ocean Engineering, National Taiwan Ocean University;Doctoral Degree Program in Ocean Resource and Environmental Changes, National Taiwan Ocean University;Coastal and Offshore Resource Research Center, Fisheries Research Institute, Council of Agriculture

关键词: Boosted regression tree;    Classification and regression tree;    Ensemble model;    Generalized additive model;    Generalized linear model;    Single algorithm;    Pomfret;   

DOI  :  10.7717/peerj.14990

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

The location, effort, number of captures, and time of fishing were all used in this study to assess the geographic distribution of Parastromateus niger in the Taiwan Strait. Other species distribution models performed worse than generalized linear models (GLMs) based on six oceanographic parameters. The sea surface temperature (SST) was between 26.5 °C and 29.5 °C, the sea surface chlorophyll (SSC) level was between 0.3–0.44 mg/m3, the sea surface salinity (SSS) was between 33.4 °C and 34.4 °C, the mixed layer depth was between 10 °C and 14 °C, the sea surface height was between 0.57 °C and 0.77 °C, and the eddy kinetic energy (EKE) was between 0.603 °C. According to the statistical findings, SST is merely a small effect compared to SSS, SSC level, and EKE in terms of impacting species distribution. By combining four effective single-algorithm models with no obvious bias, an ensemble habitat model was created. The ranges of 117°E–119°E and 22°N–24°N have the highest annual distributions of S.CPUE and nominal CPUE.

【 授权许可】

CC BY