High-resolution bathymetries and shorelines for the Great Lakes of the White Nile basin

This article is licensed under a Creative Commons Attribution 4.0 International License.HRBS-GLWNB 2020 presents the first open-source and high-resolution bathymetry, shoreline, and water level data for Lakes Victoria, Albert, Edward, and George in East Africa. For each Lake, these data have three primary products collected for this project. The bathymetric datasets were created from approximately 18 million acoustic soundings. Over 8,200 km of shorelines are delineated across the three lakes from high-resolution satellite systems and uncrewed aerial vehicles. Finally, these data are tied together by creating lake surface elevation models collected from GPS and altimeter measures. The data repository includes additional derived products, including surface areas, water volumes, shoreline lengths, lake elevation levels, and geodetic information. These data can be used to make allocation decisions regarding the freshwater resources within Africa, manage food resources on which many tens of millions of people rely, and help preserve the region’s endemic biodiversity. Finally, as these data are tied to globally consistent geodetic models, they can be used in future global and regional climate change models.ECU Open Access Publishing Support Fun

Modelling and in situ observation of broadband acoustic scattering from the Silver cyprinid (Rastrineobola argentea) in Lake Victoria, East Africa

Funding: YY was funded by the China Scholarship Council. This work was supported by a grant from the UK Royal Society under the “International Collaboration” theme to ASB and RJK.Lake Victoria is the second-largest freshwater lake in the world, and fish from the lake are a vital food resource for millions of people living around it. The silver cyprinid (Rastrineobola argentea), a small schooling pelagic species known in Tanzania as “dagaa” contributes ca. 55% to the total annual catch (ca. 0.51 million tonnes (MT) in 2014). The acoustic target strength (TS, dB re 1 m2) of dagaa, a key factor for biomass estimation, is however not well described, and is a major source of uncertainty in biomass estimation. In this study, we developed a Kirchhoff-ray mode (KRM) model to predict the TS of dagaa at standard fisheries survey frequencies. The model was based on the morphology of the body and the dual-chambered swimbladder, as obtained from X-ray images of fish ranging in total length (TL) between 2.8 and 5.4 cm. The results suggested that the swimbladder (which comprises 2.6 to 8.2% of body volume) accounts for ca. 65 to 90% of the total backscattering at 120 kHz. The predicted TS was highly dependent on tilt angle, varying by 14.0 dB at 120 kHz across the tilt range 65–115˚ (where 0˚ is head up and 180˚ is tail up), and TS variability with tilt generally increased with increasing frequency. The tilt angle of acoustically tracked individual fish indicated a distribution of tilt angles with a mean and s.d. of 93.5 and 15.1°. Our model suggested a new tilt-averaged TS–TL relationship for dagaa [TS120 kHz=19.49log(TL)−70.3], which leads to a TS 1.5 dB higher than the value in the relationship presently used to estimate stock biomass. The new relationship will lead to a substantial reduction (by ca. 30%) in estimated biomass. The discrepancies between the mean relative frequency response of the in situ measurements of backscatter from dagaa and the KRM model predictions were in the range of -2.9–3.1 dB at frequencies from 45 to 250 kHz. The KRM modelling and in situ broadband measurements of dagaa will be beneficial for acoustic identification and behavioural studies of dagaa, and will enable improved biomass assessment, thereby underpinning sustainable long-term management.Publisher PDFPeer reviewe

Fish Breeding Areas as a Management Tool for Fisheries Resources in Lake Victoria, East Africa

The shallow inshore (< 5m deep) habitats of Lake Victoria are considered to be important breeding, nursery and feeding grounds for many fish species in the lake. These areas were identified, characterized and mapped in order to provide information on critical habitats that need protection. The breeding score of fish was above average (11 points) at 46 of the 89 sites that were sampled and these could be considered for protection as breeding and nursery grounds. The highest breeding scores (>24) were obtained at major river mouths and it is strongly recommended that these should be protected to benefit fish species that migrate up rivers to spawn. The size and location of these critical habitats need to be clearly demarcated to provide better scientific information for management decisions.Keywords: Breeding score, Fish migration, Nile perch, Protected areas, Tilapia

Automated classification of schools of the silver cyprinid Rastrineobola argentea in Lake Victoria acoustic survey data using random forests

The dagaa classification reported here was supported specifically by several Scottish Funding Council Global Challenge Research Fund (GCRF) grants from the University of St Andrews and the University of Strathclyde, by a GCRF Networking Grant to ASB and RJK from the UK Academy of Medical Sciences (GCRFNG\100371), and a Royal Society International Collaboration Award to ASB and Rhoda Tumwebaze, LVFO (ICA\R1\180123).Biomass of the schooling fish Rastrineobola argentea (dagaa) is presently estimated in Lake Victoria by acoustic survey following the simple "rule" that dagaa is the source of most echo energy returned from the top third of the water column. Dagaa have, however, been caught in the bottom two-thirds, and other species occur towards the surface: a more robust discrimination technique is required. We explored the utility of a school-based random forest (RF) classifier applied to 120kHz data from a lake-wide survey. Dagaa schools were first identified manually using expert opinion informed by fishing. These schools contained a lake-wide biomass of 0.68 million tonnes (MT). Only 43.4% of identified dagaa schools occurred in the top third of the water column, and 37.3% of all schools in the bottom two-thirds were classified as dagaa. School metrics (e.g. length, echo energy) for 49081 manually classified dagaa and non-dagaa schools were used to build an RF school classifier. The best RF model had a classification test accuracy of 85.4%, driven largely by school length, and yielded a biomass of 0.71 MT, only c. 4% different from the manual estimate. The RF classifier offers an efficient method to generate a consistent dagaa biomass time series.Publisher PDFPeer reviewe

Automated classification of schools of the silver cyprinid <i>Rastrineobola argentea</i> in Lake Victoria acoustic survey data using random forests

Biomass of the schooling fish Rastrineobola argentea (dagaa) is presently estimated in Lake Victoria by acoustic survey following the simple "rule" that dagaa is the source of most echo energy returned from the top third of the water column. Dagaa have, however, been caught in the bottom two-thirds, and other species occur towards the surface: a more robust discrimination technique is required. We explored the utility of a school-based random forest (RF) classifier applied to 120kHz data from a lake-wide survey. Dagaa schools were first identified manually using expert opinion informed by fishing. These schools contained a lake-wide biomass of 0.68 million tonnes (MT). Only 43.4% of identified dagaa schools occurred in the top third of the water column, and 37.3% of all schools in the bottom two-thirds were classified as dagaa. School metrics (e.g. length, echo energy) for 49081 manually classified dagaa and non-dagaa schools were used to build an RF school classifier. The best RF model had a classification test accuracy of 85.4%, driven largely by school length, and yielded a biomass of 0.71 MT, only c. 4% different from the manual estimate. The RF classifier offers an efficient method to generate a consistent dagaa biomass time series.</p