The agricultural sector’s contribution to gross domestic product has been on the decline since the 1980's. Although the sector was dominated by sugarcane cultivation for over three centuries, a combination of international competition, low global market prices and rising production costs forced the government to shut down sugar cane production in 2005. Past and current climate-related threats to agricultural production include rainfall variability, drought and the destructive impacts of hurricanes. In Nevis, low and unreliable rainfall and extended periods of drought make moisture the most critical factor limiting agricultural productivity. The Commonwealth Scientific and Industrial Research Organisation (CSIRO) model projections show a slight decrease in sugarcane yields through to 2100 and indicate that inter-annual variations in rainfall are likely to be significant enough to adversely impact profitability. The Hadley Centre Coupled Model Version 2 (HADCM2) model projections are more severe, suggesting that sugarcane cultivation would only be possible in irrigated management conditions, for which there would be inadequate water. The model suggests that by the second quarter of the century, climatic conditions would be too dry for rain-fed agriculture, with yields being below economically viable levels. Efforts are ongoing to diversify the agricultural sector by incorporating non-traditional crops and livestock in an effort to improve food security and support rural communities. However, projections under both the CSIRO and HADCM2 models indicate potentially devastating impacts on non-traditional crops such as fruits, vegetables and livestock. In both islands, salinization of coastal aquifers will negatively affect the availability of water for agriculture, and in Nevis, rising sea levels are likely to lead to salinization of agricultural soils in lowland areas.
This section provides a summary of key natural hazards and their associated socioeconomic impacts in a given country. It allows for a quick assessment of most vulnerable areas through the spatial comparison of natural hazard data with development data, thereby identifying exposed livelihoods and natural systems.