OHI+ Kenya_Technical Report_2018

Ocean Health Index - Kenya 2018 17
Thus, this fishery result is only illustrative, and more suitable models for the existing length-based data
should be trialed e.g. spawning potential ratio, to improve the fit of the assessment to data-poor fisheries
and provide more accurate county-level scores.
4.1.3. Challenges
• Quality of data: Catch data are collected at coarse taxonomic levels with some common groupings
accounting for multiple species e.g. functional group, genus and family levels. Species level data is
available but is from selected landing sites and for relatively shorter temporal scales.
• Data gaps: Both spatial and temporal gaps exist for catch data across all counties. Spatial gaps in
catch data are obviously more evident in counties with scanty resources for monitoring (GoK, 2016).
Tana River is a case in point, despite it being in the Malindi-Ungwana bay productive zone fertilized
by outflow from the Sabaki and Tana rivers
• Allocating catch between counties: Often catches are landed in a different county to where they were
caught. Ideally, catch should be attributed to where the fish were caught, as it is more important for
management to know about the productivity of the fishing grounds (i.e. the amount of fish produced
and caught in their jurisdiction) rather than the amount of fish landed.
• Data access: Catch data is scattered across and within institutions, with no operational and up-to-date
central national database. Acquiring data from holders has been a long-standing issue among marine
research and management institutions and scientists.
4.1.4. Recommendations
Recommendations presented here are derived from the discussions held with the Technical and
Advisory Teams. Implementing these recommendations will improve the reliability of future
assessments.
Policy and Management
1. Implement management and policy strategies for gears rather than fish sizes and species as they are
easier to implement
2. Increase investment in monitoring and data collection to ensure data is collected at higher taxonomic
levels and alongside effort information, and at more fish landing sites across the country particularly
in areas with limited access and low reporting. This will allow for more accurate assessments with the
aim of moving Tanzania’s fisheries sector to a data-rich system
3. Ensure ‘fishing grounds’ are recorded for nearshore fisheries in future data collection
4. Continue discussions between Kenya Fisheries Service and County Fisheries departments to
encourage increased and improved county management of BMUs
5. Determine sustainable fisheries management targets: Catch-per-unit effort, biomass, and number of
fishers per Km 2
6. Support counties and BMUs to define co-management areas and implement area based
management approaches to improve coastal fisheries status through capacity development, policy
or legislation formulation and funding
7. Expand opportunities for sustainable domestic exploitation of off-shore fisheries for food security
8. Incorporate the OHI metric into policy circles and fisheries management approaches to support and
contribute to the Blue Economy movement