Page 98 - Ecuador's Banana Sector under Climate Change

ecuador’s banana sector under climate change: an economic and biophysical assessment to promote a sustainable and climate-compatible strategy
projected rise in temperature (see Figure 18). In Figure 24, an increase in the risk of establishment towards highlands in the Andean region can be noted, as well as a decline in suitable areas in the coast and Amazon region, caused by high temperatures that limit conditions for the permanent establishment of the insect.
2.4 Recent history of extreme and moderate weather variability in export banana production areas and implications for the future
The 210 000 hectares of banana planted in Ecuador for export is a testimony to the suitability of the growing conditions for this crop. On average, banana prospers under the growing conditions of coastal Ecuador and is highly competitive on the world market. Average conditions, however, do not occur every year. In fact, behind the average temperature and rainfall, which is highly suitable for banana, are year after year, month after month and day after day variabilities, sometimes minor, but at other moments even catastrophic. Conde et al. (2006) highlighted variability in their analysis of the production of coffee
in Mexico and maize in Argentina. The general climate models used to project climate change do not yet generate information about variability. With projected increases in ocean temperatures, weather may become more variable, but such projections are not yet available. For the purpose of this study, an examination is made of the historical variability under the supposition that weather will remain
at least as variable in the future as it has been in the past. This variability and the uncertainty associated with it present a more immediate challenge to banana growers than the projected changes in average climate for 2030, 2050 and 2070.
The data used below to analyse weather variability were sourced from
time series at the Climate Research Unit of the University of East Anglia in the United Kingdom (CRU). This database, with month-by-month records for the past century, is based on a high-resolution grid (0.5 x 0.5 degrees). Data are interpolated from weather registries from over 4 000 weather stations across the globe. This database covers standard variables such as precipitation, daily average temperature and maximum monthly temperature, as well as other variables such as cloud cover, daily temperature range and frequency of days with frost and with rain (Harris et al., 2013).
To visualize the variability for the six selected points in coastal Ecuador, the monthly data from 1950 to 2009 was graphed as a function of the average for the period 1960-90. The resulting Figure 25 locates a data point for each year above or below the average temperature and rainfall for the reference period. The points which are closer to the centre point 0/0 are years that more closely reflect the average climate. Points which are close to the average are found within the blue box, with less than 25 percent variability in rainfall and ±1°C in temperature. The points outside the blue box - but inside the yellow box - show moderate variability from the average year with ±25 percent to ±75 percent in precipitation and with temperatures above ±1°C and less than ±1.5°C. Those points outside the yellow box are extreme years - either extremely wet or dry or extremely hot or cold. For Pichilingue, the extreme years (1983 and 1998) are El Niño years (NCAR, 2013).
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