• Journal of Ecology and Environment
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• v.35 no.4
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• pp.279-289
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• 2012

This study conducted a comparative analysis of benthic macroinvertebrate communities in the Fosu and Benya lagoons in Ghana, based on the anthropogenic effect on the two lagoons. Salinity, oxygen, temperature, conductivity, turbidity and pH were measured, invertebrate richness and species densities were determined. The AZTI Marine Biotic Index (AMBI) and multivariate statistics were used to determine the different responses of fauna to pollution. The fauna were categorized into five ecological groups based on the degree of tolerance of the different species to pollution: disturbance-sensitive species; disturbance-indifferent species, disturbance-tolerant species, second-order opportunistic species; and first-order opportunistic species. The Fosu Lagoon supported more pollution tolerant species, whereas the Benya Lagoon had more species that were sensitive to organic enrichment under relatively unpolluted conditions. Chironomus sp., which is adapted to virtually anoxic conditions, was the most abundant in the Fosu Lagoon whereas Nemertea sp. was the most abundant in the Benya Lagoon. The numerical and relative abundance (%) of all 7 taxa in the Fosu Lagoon was 1,359 and 92.35%, respectively. The numerical and relative abundance (%) of all 34 taxa in the Benya Lagoon was 2,459 and 87.52%, respectively. Expectedly, the level of dissolved oxygen in the less saline Fosu Lagoon was higher than that in the more saline Benya Lagoon. The reduced photoperiod and photosynthetic activities of aquatic plants might account for this trend. There is a need to implement comprehensive monitoring and management initiatives for sustaining the ecological health of coastal lagoons in Ghana in order to support the many people that depend upon these ecosystems for their livelihood.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.535-556
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• 2024

Measuring stock market volatility and its determinants is critical for stock market participants, as volatility spillover effects affect corporate performance. This study adopted a novel approach to analysing and implementing GARCH-MIDAS modelling methods. The classical GARCH as a benchmark and the univariate GARCH-MIDAS framework are the GARCH family models whose forecasting outcomes are examined. The outcome of GARCH-MIDAS analyses suggests that inflation, interest rate, exchange rate, and oil price are significant determinants of the volatility of the Johannesburg Stock Market All Share Index. While for Nigeria, the volatility reacts significantly to the exchange rate and oil price. Furthermore, inflation, exchange rate, interest rate, and oil price significantly influence Ghanaian equity volatility, especially for the long-term volatility component. The significant shock of the oil price and exchange rate to volatility is present in all three markets using the generalized autoregressive conditional heteroscedastic-mixed data sampling (GARCH-MIDAS) framework. The GARCH-MIDAS, with a powerful fusion of the GARCH model's volatility-capturing capabilities and the MIDAS approach's ability to handle mixed-frequency data, predicts the volatility for all variables better than the traditional GARCH framework. Incorporating these two techniques provides an innovative and comprehensive approach to modelling stock returns, making it an extremely useful tool for researchers, financial analysts, and investors.