The quantification of the extent of flooding on selected major Afrotropical lakes to guide management implications

The extent of flooding in vulnerable inland and lacustrine systems can demonstrate the coverage and the magnitude of such phenomenon for policy enhancement. This study examined the extent of flooding due to rising water levels in selected Afrotropical lakes to guide interventions that would sustain the livelihoods of communities affected. The years that were most prone to flooding (2010 and 2020) were used as a baseline in the extraction of changes in spatial extent and area of lacustrine shoreline, and rainfall and satellite altimetry data, using geospatial and remote sensing technologies. The extent of flooding was strongly but insignificantly related (R2 = 0.63; p = 0.07) to the sizes of the studied lakes and the amount of rainfall. Lakes with the smallest surface areas such as Baringo and Naivasha showed the greatest increase in flooding of 52.63% and 42.62%, respectively. Larger lakes such as Lakes Victoria (1.05%), Turkana (3.77%), and Tanganyika (0.07%) had the lowest increases in areal extent. Furthermore, the topography of the lakes studied further determined the residence time and the extent of flooding, such that lakes such as Edward (−0.09%) and Rukwa (−3.25%) receded during the period when other lakes were flooding. The information and data presented here provides the most up-to-date quantification of flooding to support adaptation strategies for inland lake systems and guide policy implementation

How the pre and post COVID-19 era have shaped system understanding of the socioeconomic impact of small-scale inland fisheries

The current study provided a socioeconomic quantification of small-scale inland fisheries in East Africa using fish market information data for major markets in the pre (2009–2017) and post COVID-19 containment (Jan–May 2022) eras. The socioeconomic status index (SEI) incorporated 6 dimensions: access to fresh fish, access to market, available fish processing (drying) infrastructure, favourable price range, high quantity range traded, and high seasonal profit margins; using three major commercial fishes (Nile perch, Tilapia and Dagaa) and the season (pre and post COVID-19) as the main independent variables. The SEI was calculated using a segmented sociometric scale interval as: ≥ 4.21Very High ≤5.00; ≥3.41 High ≤4.20; ≥2.61 Moderate ≤3.40; ≥1.81 Low ≤2.60; and ≤1.00 Very Low ≤1.80. The socioeconomic quantification was highly dependent on COVID-19 containment periods that reflected very high (pre COVID-19 = 4.67, post COVID-19 = 4.06) impacts on small-scale inland fisheries. This suggested a negative impact of COVID-19 on small-scale inland fisheries attributed to various factors such as disrupted value chains, reduced purchasing power among the customers, struggles by businesses to compensate for losses incurred during the pandemic, and diversion of economic focus. The impact had a lower proportion on Dagaa, given its low value compared to the other two major commercial species. The quantification of fish data during a pandemic is useful to provide mitigation measures for shocks that could be anticipated in the sector for sustainable fish-food systems