Schubert, Aidan, Nyingi, Wanja, Tuda, Paul ORCID: https://orcid.org/0000-0002-5629-9406, Aura, Christopher M., Obiero, Kevin, Manyala, Julius, Cowx, Ian G., Vianna, Gabriel M., Ansell, Matthew, Meeuwig, Jessica J. and Zeller, Dirk (2021) Reconstructing Kenya’s total freshwater fisheries catches: 1950–2017. Marine and Freshwater Research, 73 (1). pp. 57-70. DOI https://doi.org/10.1071/MF21189.

Text Tuda2021.pdf - Published Version Download (1MB)

Abstract

Most freshwater fisheries occur in developing countries, where freshwater fish underpin local food security and small-scale fisheries livelihoods. Comprehensive catch data are fundamental to support the sustainable management of freshwater fisheries. However, freshwater catch data reported by the Food and Agriculture Organization of the United Nations (FAO) on behalf of countries under-represent freshwater fisheries because they are dominated by fragmented and highly dispersed small-scale sectors, often with no designated landing sites. Kenya is an emerging economy with socioeconomically important freshwater fisheries and ongoing food security concerns. We undertook a reconstruction of freshwater fisheries catch data for Kenya for the period 1950–2017, aiming to improve the comprehensiveness of existing reported baseline data and to provide a more ecologically and spatially relevant time series dataset for research and management uses. We reconstructed catches for 16 major waterbodies in Kenya and found catches to be 32% higher than the data reported by the FAO on behalf of the country. The subsistence sector (small-scale, non-commercial, personal consumption) accounted for 71% of unreported catches, compared with 29% for artisanal sector catches (small-scale, commercial), suggesting that non-commercial catches for direct local consumption are substantially under-represented in nationally reported statistics and should receive greater attention to support sustainable food security in Kenya.

Document Type:	Article
Programme Area:	PA1
Research affiliation:	Integrated Modelling > Resource Management
Refereed:	Yes
Open Access Journal?:	No
DOI:	https://doi.org/10.1071/MF21189
ISSN:	1323-1650
Date Deposited:	03 Dec 2021 10:36
Last Modified:	25 Jun 2024 12:57
URI:	http://cris.leibniz-zmt.de/id/eprint/4783

Actions (login required)

View Item