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64 SCF Folio Table 1. Forecasts given to farmers Hypothetic Assumption and Forecast Wet season for March–June, 2005–07; forecast with dry season for March-June 2008 Dry season for March–June, 2005–07; forecast with dry season for March–June 2008 Wet season for March–June, 2005–07; forecast with wet season for March–June 2008 Average season for March–June, 2005–07; forecast with dry season for March–June 2008 Average season for March–June 2005–07; forecast with La Niña for March–June 2008 Detailed Description of Event Farmers were told to assume that hypothetically, they experienced a rainy season for the last cropping season for three consecutive years. They were then given a dry season forecast for the incoming cropping season. Farmers were then allowed to make decisions for their farms, bearing the knowledge that forecasts are not always 100 percent accurate. Farmers were told to assume that hypothetically, they experienced drought for the last cropping season for three consecutive years. They were then given a dry season forecast for the incoming cropping season. Farmers are then allowed to make decisions for their farms, bearing the knowledge that forecasts are not always 100 percent accurate. Farmers were told to assume that hypothetically, they experienced a rainy season for the last cropping season for three consecutive years. They were then given another wet season forecast for the incoming cropping season. Farmers are then allowed to make decisions for their farms, bearing the knowledge that forecasts are not always 100 percent accurate. Farmers were told to assume that hypothetically, they experienced normal amount of rainfall for the last cropping season for three consecutive years. They were then given a dry season forecast for the incoming cropping season. Farmers are then allowed to make decisions for their farms, bearing the knowledge that forecasts are not always 100 percent accurate. Farmers were told to assume that hypothetically, they experienced normal amount of rainfall for the last cropping season for three consecutive years. They were then given a La Niña forecast for the incoming cropping season. Farmers are then allowed to make decisions for their farms, bearing the knowledge that forecasts are not always 100 percent accurate. scientific terms, 2) downscale the forecast to their locality, and 3) forecasters should “tell the truth.” The third suggestion emanated from their experience of a forecast of an unsuitable cropping season that did not come true. This resulted in an opportunity missed for the farmers to plant their crops. For farmers like them who rely on their ability to produce crops for sustenance of their households, missing an opportunity to plant crops may result in their inability to feed their respective families. The farmers also said that they use SCF in deciding farm activities. However, some of them likewise said that they just predict the climate by themselves and do not rely on SCFs provided by PAGASA. “Mo tan-aw tan-aw na lang ko og sakto ba kaha ipamugas ang panahon, ug sakto unya mo pugas pud ako mga silingan, aw mo pugas pud ko” (I just observe the climate, if my neighbors sow, I also sow), a farmer reported. Farmers also said that if they feel that a forecast will not materialize, they just ignore it, “Mo sugal na lang mi” (To some extent, we just gamble). By this statement, farmers mean that they are prepared to face the possibility of a cropping failure due to planting in an unfavorable climate condition. Farmers in Malaybalay had a hard time trying to understand the complex terms used in climate forecasts such as monsoons, intertropical convergence zone (ITCZ) and low- pressure areas. Because of this, farmers are unable to completely comprehend the information. Farmers’ decisions based on probabilistic climate forecasts For the various forecasts given them during the decisionmaking workshops, the following decisions came out (refer also to Table 2): Wet cropping season experience and dry forecast. For this situation, farmers said that they would cultivate only a small portion of their land to minimize cost for the labor of land preparation. They also said that if the dry season comes, they would plant crops resistant to drought (i.e., sugarcane, cassava, banana, and other similar crops) or short-season crops like sweet potato,
65 Table 2. Farmers’ responses to SCFs Experiential Data Analytical Data Farmers’ Decisions (Hypothetic Assumption) (Climate Forecast) Wet cropping season for Dry season Prepare a small portion of their land to minimize spending. If the dry three years season comes, plant crops which are resistant to drought or shortseason crops. Plant in small quantities to avoid too much input for an expected below-average output. Dry cropping season Dry season Find other means of earning income. Practise backyard gardening to for three years have an immediate source of food for their family. Raise farm animals such as chickens, goats, cows, and pigs to have alternative sources of income. Look for work in Malaybalay. Switch from corn to more drought-tolerant crops (high risk option). Wet cropping season Wet season Still plant corn, and plant other crops in the periphery to earn for three years additional income. There would be very little (or no) changes in their farming practices because of the rainy climate for the cropping season. Average cropping season Dry season Prepare a small portion of their land. Farmers and their families will for three years cultivate their land to minimize cost in land preparation. If the dry season comes, plant crops which are resistant to drought. Plant in small quantities. Average cropping season La Niña Plant crops that grow even with too much water or use corn varieties for three years that thrive under a wet climate condition. mongo, soybeans, cowpeas, and other leguminous plants so that before the dry season comes, they would have had finished harvesting. They added that they would leave the silage of their crops to fertilize the land. They maintained that they would plant in small quantities to minimize production cost for what they expect to be a low yield due to the dry climate. Dry cropping season experience and dry forecast. Under this situation, the decisions made by the respondents were more for sustaining their households and not for income. They reasoned that by the fourth year of a drought, they would have run out of savings for their families. Participants said that they would find alternative livelihood or other means of earning an income. One of the alternative sources of income they mentioned was to work as hired laborers in sugarcane plantations. They claimed that sugarcane is a drought-resistant crop; hence, sugarcane plantations will continue to operate even during drought. Some farmers said that they would find other work in Malaybalay. Other farmers said that they would practice handicraft making as an alternative source of income. As an immediate source of food, participants said that they would venture into backyard gardening. They claimed that it is easier to maintain crops when grown in small numbers. For these backyard gardens, they would use their used water at home to water their crops. Farmers said that they would also raise farm animals like chicken, goats, pigs, and cows for additional income. Wet cropping season experience and wet forecast. For this situation, participants said that they would still plant corn but will use the native or the “bisaya” variety. They claimed that the native variety is cheaper and grows well both in wet and dry seasons compared to the hybrid varieties. Other than corn, they would also plant other crops in the sides of their farm as a source of additional income. Average cropping season experience and dry forecast. Farmers’ decisions in this situation are similar to the decisions they have made in the wet forecast. Farmers said that they would cultivate corn in a small portion of their land. According to them, they will not hire laborers to cultivate their land. Instead, their family members will help, from land preparation to planting until harvesting. If the dry season comes, a small number of farmers said that they would plant crops that are resistant to drought such as banana, sugarcane, rubber, and cassava. They maintained that they would be planting in smaller quantities. Average season experience and La Niña forecast. For this situation, farmers were asked to assume that they have experienced an average climate for the cropping season for three consecutive years in the past and were then given a La Niña forecast for the present cropping
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SCF Folio A compilation of informat
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3 Administration (PAGASA), the Phil
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5 Learning the basics Dr. John Mull
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7 The dry season is also subdivided
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9 Tropical cyclone average tracks J
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11 inevitably have impacts on the v
Page 13 and 14: 13 Reaching out and increasing awar
Page 15 and 16: 15 To ensure that the SCFs are rend
Page 17 and 18: Communicating through climate indic
Page 19 and 20: 19 Table 1. Awareness, usefulness,
Page 21 and 22: 21 Very often, this leads to extrem
Page 23 and 24: 23 agency, PAGASA, and sent out to
Page 25 and 26: 25 municipality. LGUs may send in t
Page 27 and 28: 27 SCF is popular in Bukidnon but..
Page 29 and 30: 29 the Provincial Agriculture Offic
Page 31 and 32: 31 Analysis and research/survey res
Page 33 and 34: 33 As the results in this initial s
Page 35 and 36: 35 Table 2. El Niño and La Niña e
Page 37 and 38: 37 average, and wet years were calc
Page 39 and 40: 39 local corn growers. In guiding f
Page 41 and 42: 41 dominated regions of northern Ne
Page 43 and 44: 43 The influence of ENSO on frost r
Page 45 and 46: 45 It is the timing of the latest f
Page 47 and 48: A model for valuing seasonal climat
Page 49 and 50: 49 And on rice crop... Nueva Ecija
Page 51 and 52: 51 Security against climate variabi
Page 53 and 54: 53 been dominating the Table 1. Bor
Page 55 and 56: 55 The need to help rice and corn f
Page 57 and 58: 57 Figure 1. Rainfall outlook, July
Page 59 and 60: 59 In Cebu: use of SCF gives higher
Page 61 and 62: 61 units of N fertilizer based on g
Page 63: 63 Determining corn farmers’ deci
Page 67 and 68: 67 Project Team Australia Dr. Peter
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