The study examined the effects of two climate variables (rainfall and temperature) on the output of capture and aquaculture fisheries in Nigeria between 1980 and 2019. Secondary data spanning 39 years were obtained from reputable sources; National Bureau of Statistics, (NBS), Food and Agricultural Organisation Statistical data base (FAOSTAT) and Nigerian Metrological Agency (NIMET) for the study. Data were analysed using descriptive statistics such as averages, percentages and coefficients of variation. Inferential statistics employed in the study include Augmented Dickey-fuller Statistics (ADF), Johansen Co-integration techniques, and the error correction model. Results of descriptive analysis reveals a fluctuating trend in the annual temperature, rainfall, capture and aquaculture fisheries supply, averaging 300C, 200mm, 400 tonnes and 600 tonnes respectively over the study period. Inferential statistics results shows that the variables of the model became stationary after first difference, with a long run relationship existing among them. Results of error correction model reveal that annual rainfall (X1) and annual temperature (X2) lagged by one year positively affects the output of capture fisheries, while annual rainfall (X1) and annual temperature (X2) have an asymmetric effect on the output of aquaculture fisheries. The study concluded that climate change significantly influences the output of capture and aquaculture fisheries in Nigeria. Thus, for sustainable capture and aquaculture fisheries in Nigeria, it is recommended that laws should be enacted to control the emission of greenhouse gases to mitigate the effect of climate change on production and productivity of capture and aquaculture fisheries. Huge investment should be made in the construction of water dams, boreholes, and other water reservoirs to facilitate dry season aquaculture. Regulatory laws on capture fisheries should be reviewed and enforced to ensure sustainable production and productivity of capture fisheries.
Key Words: Capture fisheries, Aquaculture, Climate variables, Error correction analysis