The pattern of growth, condition factor and gillnet selectivity of a commercially important sheatfishes (Kryptopterus lais) from waters of Sungai Batang, Indonesia towards sustainable management

Main Article Content

Ahmadi A

Abstract

The present study describes the growth pattern, the condition factor, and the gillnet selectivity of Sheatfishes (Kryptopterus lais) from Waters of Sungai Batang, Indonesia. This species is commercially exploited and highly vulnerable to overfishing. Meanwhile, the exploitation rate is greater than the growth rate of the fish. The fish samples were purchased directly at the fishing village once every 2-week during the sampling period. A total of 170 specimens of K. lais comprising 78 males and 92 females (total length of 88-215 mm and weigh of 7-89 g) were empirically evaluated. Both males and females grew negatively allometric (b = 2.34 - 2.76). No significant difference was observed in total length and body weight between males and females. However, females had body depth and the condition factor (Kn) value greater than males. The highest percentage of catches fell between 140 and 149 mm in total length (TL) (17.39 - 20.51%) and weighed between 15 and 19 g (20.65 - 21.79%). The mean Kn values ranged from 0.77 ± 0.18 to 0.93 ± 0.14, indicating that fish were still in good condition. The size at first maturity of males and females was predicted as 149 and 147 mm TL. The length at first capture and selection factor obtained were 150 mm TL and 2.36, implying gear selectivity should be improved. The present gillnet was considered female-biased gear with male to female ratio of 1: 1.2. This study provides the baseline scenario for formulating a sustainable fisheries management strategy since many aspects of the K. lais fishery are not disclosed.

Article Details

How to Cite
A, A. (2022). The pattern of growth, condition factor and gillnet selectivity of a commercially important sheatfishes (Kryptopterus lais) from waters of Sungai Batang, Indonesia towards sustainable management. Asia-Pacific Journal of Science and Technology, 27(01), APST–27. https://doi.org/10.14456/apst.2022.20
Section
Research Articles

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