ORCID

Document Type

Article

Abstract

The shallow margins (<10 m depth) of Lake Victoria, comprising ca. 9% of the lake’s total area, have been suggested to harbour up to 35% of the lake’s fish biomass based on limited trawl data. However, since standardized lake-wide acoustic surveys began in 1999, these nearshore waters have remained inadequately sampled due to the inability of research vessels to operate in shallow waters, creating one of the largest data gaps in the assessment of Africa’s most productive inland fishery. This study addresses this longstanding sampling gap by conducting near-horizontal acoustic surveys at 17 sites along the Tanzanian shoreline. A total of 65 surveys over 6 rounds were conducted between November 2019 and March 2023, using an open canoe equipped with a broadband echosounder (Simrad EK80, centre frequency 200 kHz). Concurrent beach seine and gillnet sampling provided species composition and size information, and biomass was estimated using echo counting and geostatistical methods. Shallow margins cover ca. 10.2% (3528 km²) of the Tanzanian sector within the 10 m isobath and 19.5% (6736 km²) within the 20 m isobath. Estimated total biomass ranged from 0.26 to 0.68 million tonnes (MTs) in the 20 m strip and from 0.15 to 0.37 MTs in the 10 m strip. Tilapia and haplochromines dominated the biomass in most surveys, while Nile perch contributed a smaller but persistent fraction. These findings identify the shallow margins as a quantitatively important biomass domain in the Tanzanian sector and highlight the need for dedicated shallow water sampling in future fisheries assessment and ecosystem modelling.

Publication Date

2026-09-26

Publication Title

ICES Journal of Marine Science

Volume

83

Issue

9

ISSN

1054-3139

Acceptance Date

2026-09-09

Deposit Date

2026-09-29

Funding

This research was supported by a Challenge Led award from the UK Royal Society (CHL\R1\180111) to Andrew Brierley, Robert Kayanda and Safari Kinung’hi.

Keywords

horizontal beam, broadband acoustic, habitat, geostatistics, GAMM

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Share

COinS