Search Results (4)

Key fish breeding and other biodiverse areas in Malawian lakes are under threat from illegal fishing, the siltation of key breeding areas (due to deforestation-induced soil erosion), and the clearing of shoreline aquatic vegetation. Freshwater protected areas, also called sanctuaries, have the potential to support the restoration of degraded aquatic environments and protect fisheries’ biodiversity. In Malawi, community-managed fish sanctuaries have been established by beach village committees (BVCs) throughout Lake Malawi, Lake Malombe, Lake Chilwa and Lake Chiuta. The sanctuaries were established to conserve exploited stocks, preserve biodiversity, and enhance fisheries’ yield. The BVCs are aligned with local decentralized village development committees linked to District Councils. Together, they constitute a defragmented decentralized ecosystem-based management of fishery resources. A monitoring study was conducted in sanctuaries in the four lakes during the wet and dry season over three years (2016–2019). The monitoring was carried out to evaluate the sanctuaries’ biological performance. The results showed that community-managed sanctuaries contributed to a 24% increase in the total number of observed species. The Shannon Diversity Index increased from an average 1.21 to 1.52. Small and mid-size (<50 ha) sanctuaries showed a higher performance improvement than large (>50 ha) sanctuaries. This is likely due to multiple factors, including a higher level of fish movement and the greater ability of communities to surveil and enforce smaller sanctuaries. The participation of communities in monitoring enhanced the demonstration effects of sanctuaries. This, in turn, encouraged communities to expand the number and size of the sanctuaries. The biological performance results indicate that community-managed freshwater sanctuaries can be used to protect and restore fish biodiversity in freshwater lakes in Africa. Linking the BVCs to defragmented decentralized structures ensures that the interconnectedness between ecosystem uses, including forestry, agriculture, and tourism, which impinge on fish productivity, are addressed holistically. Full article

Inland freshwater shallow lake ecosystem degradation is indistinctly intertwined with human-induced factors and climate variability. Changes in climate and human-induced factors significantly influence the state of lake ecosystems. This study provides evidence of the driver, pressure, state, impact, and response (DPSIR) indicators for freshwater lake ecosystem dynamics, taking Lake Malombe in Malawi as a case study. We used the DPSIR framework and Tobit model to achieve the study’s objectives. The study’s findings indicate that top-down processes gradually erode Lake Malombe’s ecosystem state. The lake resilience is falling away from its natural state due to increasing rates of drivers, pressures, and impacts, indicating the lake ecosystem’s deterioration. The study shows that demographic, socio–economic, climatic drivers, pressures, state, and responses significantly (p < 0.05) influenced the lake ecosystem’s resilience. The study suggests that substantial freshwater ecosystem management under the current scenario requires a long-term, robust, and sustainable management plan. The findings from this study provide a roadmap for short-term and long-term practical policy-focused responses, particularly in implementing a freshwater ecosystem restoration programs in Malawi and Africa more broadly. Full article

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E₂), coefficient of determination (R²), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R², and E₂. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024. Full article

People living in fishing communities have a high burden of preventable water, sanitation, and hygiene (WASH) related diseases but have often been neglected in research and policy. We explored practices and perspectives on WASH among fishing villages around Lake Malombe, Malawi. We employed a mixed methods design, and data were initially collected through participant observations (five weeks), followed by a second phase of qualitative interviews (n = 16), focus group discussions (n = 7), and quantitative surveys (n = 242). We observed that safe water sources were scarce; latrines were basic; and handwashing facilities were limited. Seventy-one percent (n = 174) of households collected water from unsafe sources (open wells and the lake). Eighty-six percent (n = 207) of households had basic short-term latrines. Twenty-four percent (n = 59) of households had handwashing facilities with soap. Qualitative data supported these observations and identified additional factors which compounded poor WASH practices including, a high transient population associated with the fishing trade, poor infrastructure design and construction which lacked consideration of the environmental factors, context and social and cultural norms. As such, fishing communities are underserved and marginalised with constrained access to WASH services, which must be addressed through behaviour-centered and context appropriate solutions. Full article