Case study: Bogotá. Impact of climate change on Bogotá s food security and smallholder s livelihoods

Transcription

1 Case study: Bogotá Impact of climate change on Bogotá s food security and smallholder s livelihoods Authors: A. Eitzinger, P. Läderach, A. Quiroga, A. Pantoja, A. Benedikter, C. Bunn, J. Gordon International Center for Tropical Agriculture (CIAT), Managua, Nicaragua and Cali, Colombia Cali, Colombia, July

2 Table of Contents 1. Summary and main findings Background The research area: Bogotá Region The case: Food Security Bogotá General Problems Supply chains The normal case New concept Challenges Climate Change in Colombia Temperature rise: Water stress: Erratic precipitation: Pests and diseases: Climate change in the Bogotá metropolitan area Upgrading supply chains Our methodology Assessment of observed changes and farmers perceptions Results from focal workshops Farmers perceptions of historical climate Farmers perceptions of natural capital Farmers perceptions of physical capital Farmers perceptions of human capital Examples of farmers comments Farmers Comments from Boyacá Farmers Comments from Cundinamarca Climate change predictions for 2030 & The summary climate characteristics for 2030 and General climatic characteristics Extreme conditions Climate Seasonality Variability between models Regional changes in the mean annual precipitation (2030) Regional changes in the mean annual precipitation (2050) Regional changes in the mean annual temperature (2030) Regional changes in the mean annual temperature (2050)

3 6.6 Coefficient of variation of climate variables Exposure of most important crops to climate change Measure of agreement of models predicted changes Potato Current suitability Suitability for Potato by Suitability for Potato by Change in suitability by Change in suitability by Cassava Current suitability Suitability for Cassava by Suitability for Cassava by Change in suitability by Change in suitability by Rice Current suitability Suitability for Rice by Suitability for Rice by Change in suitability by Change in suitability by Availability and restrictions for agricultural production Land use Access Protection Combined restrictions for agricultural production Vulnerability of farmer s livelihoods to climate change Vulnerability Index Sensitivity & adaptive capacity of Bogota s farmer to climate change Capital stock analysis Cluster Analysis Site-specific vulnerability Estimated Carbon Footprint Corn Beans Strategies to adapt to the changing climate Farmer and supply-chain actors suggestions Group I

4 Group II Group III Group IV Plenary discussion Developing adaptation strategies from research Food security of Bogotá Community s vulnerability to climate change Conclusion References

5 Table de Figures Figure 1: Study area Figure 2: Analytical framework Figure 3: Farmers perceptions of historical climate trends Figure 4: Farmers perceptions on natural resources Figure 5: Farmers perceptions of physical capital - Roads Figure 6: Farmers perceptions of human capital road Figure 7: Climate trend summary 2030 and 2050 for Bogotá-area Figure 8: Mean annual precipitation change by 2030 for 7 study sites in the Bogotá region Figure 9: Mean annual precipitation change by 2050 for 7 study sites in the Bogotá region Figure 10: Mean annual temperature change by 2030 for 7 study sites in the Bogotá region Figure 11: Mean annual temperature change by 2050 for 7 study sites in the Bogotá region Figure 12: Coefficient of variation for annual precipitation and temperature 2030 and Figure 13: Measure of agreement of models predicting changes in the same direction as the average of all models at a given location for Figure 14: Current climate-suitability for Potato Figure 15: Suitability for Potato by Figure 16: Suitability for Potato by Figure 17: Climate-suitability change for Potato in Figure 18: Climate-suitability change for Potato in Figure 19: Current climate-suitability for Cassava Figure 20: Suitability for Cassava by Figure 21: Suitability for Cassava by Figure 22: Climate-suitability change for Cassava in Figure 23: Climate-suitability change for Cassava in Figure 24: Current climate-suitability for Rice Figure 25: Suitability for Rice by Figure 26: Suitability for Rice by Figure 27: Climate-suitability change for Rice in Figure 28: Climate-suitability change for Rice in Figure 29: Availability by land-use Figure 30: Road access in Bogota (distance-costs) Figure 31: Protected areas with buffer-zones in Bogota Figure 32: Combined availability of land-use, access & protected areas in Bogota

6 Figure 33: Vulnerability Index for 3 case studies Figure 34: Exposure compared between 3 case studies Figure 35: Sensitivity compared between 3 case studies Figure 36: Adaptive capacitive compared between 3 case studies Figure 37: Expected impact compared between 3 case studies Figure 38: Spider diagram of sensitivity and adaptive capacity for all producer Figure 39: Spider diagram of sensitivity and adaptive capacity for producer selling to Intermediaries Figure 40: Spider diagram of sensitivity and adaptive capacity for producer selling direct to consumer.. 40 Figure 41: Spider diagram of sensitivity and adaptive capacity for mixed producer (selling to Intermediaries and direct to consumer) Figure 42: Site-specific vulnerability by Figure 43: Site-specific vulnerability by Figure 44: Compared carbon footprint of corn and beans in Colombia

7 Table of Tables Table 1: Table of climate-suitability change for 2030 and Table 2: Table of changing climate-suitability versus land availability, numbers in grey are changes in area

8 1. Summary and main findings Main research findings Temperature increases by about 1.2 ºC by 2030 and 2.2 ºC by 2050 Rainfall increases over the year and the number of cumulative dry months decreases from 3 to 2 months. Farmers have observed recently that natural resources are being highly affected Area is facing a geographical shift of some crops to higher altitudes Paramos are presently important ecosystems for water storage Farmers depending on intermediaries are more vulnerable than farmers participating in the direct trade model facilitated by Oxfam This document reports on the results of a consultancy conducted for Oxfam GB to systematically address the challenge of climate change regarding farmers livelihoods and food security for the metropolitan area of Bogotá. In Bogotá s area the yearly and monthly rainfall will increase and the yearly and monthly minimum and maximum temperatures will increase moderately by 2030 and will continue to increase progressively by The overall climate will become more seasonal in terms of variation throughout the year with temperatures in specific districts increasing by about 1.2 ºC by 2030 and 2.2 ºC by 2050 and more seasonal in precipitation with the maximum number of cumulative dry month decreases from 3 months to 2 months. We analyzed the current and future biophysical suitability [EXPOSURE] of the main crops produced by smallholder-famers for the Bogotá metropolitan area. The results for potato and cassava, two of the most important crops, show a severe decrease in suitability, which implies that food needs to be supplied from areas further away from Bogota in order to assure food security in the capital. Areas with increased suitability in the future are located at higher altitudes known as Paramo, a fragile Andean ecosystem that provides environmental services to downstream populations. The assessment of the SENSITIVITY and the ADAPTIVE CAPACITY demonstrates that farmers participating in the direct trade model facilitated by Oxfam are less vulnerable to climate change than farmers solely depending on intermediaries. Farmers supplying both markets are the less vulnerable. The weakness in the financial asset is mainly due to inconsistent quality, in the case of the intermediary model it is also due to poor technical assistance. Limiting factors of the intermediary model also include the lack of credits and organization. After analyzing the data and questionnaires we went back to the farmer and supply-chain actor and shared with them the results of potential threats of a changing climate. In a participatory process we jointly developed adaption strategies. The three main strategies that supply chain actors identified to balance the impacts of climate are (i) information, training 8

9 and awareness, (ii) advocacy (local to global) and (iii) sustainable and ecological production. 2. Background 2.1 The research area: Bogotá Region The area adjoining Colombia s capital, more precisely Boyacá and Cundinamarca departments have been subject to this research. These areas host a very diverse landscape and three different climates stemming from the central and eastern Andean mountain ranges which pervade most parts of this region. Figure 1: Study area. The predominant highland area ranging from approximately 2000 to 3000 meters above sea level (masl) hosts cooler climate conditions. These so-called paramos allow cultivation of a wide array of staple crops such as potato, onion, corn, etc. Further down the hillside, more moderate temperatures determine flora and fauna. Providing a broad range of biodiversity between 1000 to 2000 masl farmers mostly cultivate common bean, string bean, pea, blackberry, tomato and tree tomato. In the marginal areas, however, sometimes even cassava, plantain, coffee and rice or on the opposite side potato and corn can be found, among others. The temperate conditions in the lower parts (e.g. the municipalities adjoining the Magdalena river basin in the west of Bogotá) inherently accommodate hot climate crops. Banana, coffee and sugarcane grow aside citric fruits and other tree crops like mango and papaya up to masl. Combined, the diversity of this region can comprise a significant part of the products to be found in the local Colombian diet. 2.2 The case: Food Security Bogotá Bogotá is home for more than 8 million people and is reported as being the third biggest city in South America and the 25 th worldwide ( The city hosts Corabastos, South America s 2nd largest marketplace for food items holding a supply level of approx. 1.4 million tons of products in Considering the importance of distance in terms of prices, three rings (anillos) of food supply around Bogotá can be defined (Montoya et. all, 2010). Growers from the Cundinamarca department primer anillo surrounding Bogotá provide 47% of food items to be offered in this market place, Boyacá, Tolima and Meta departments, Segundo anillo, add another 33% to its supply. Farmers from the four aforementioned regions supply roughly 70% of the food items consumed by the capital s citizens, thus contribute immensely to the food security of the city. In these areas most farmers are smallholders. This is especially true for the evaluated departments Cundinamarca and Boyacá, where roughly 90% of the growers own or cultivate 20ha of land at most, though most of the growers cultivate much less than this. 9

10 2.3 General Problems Although these people are key to Bogotá s and Colombia s consumption patterns and food supply, small-holders are the first to suffer from a magnitude of problems. Some of them have poor access to markets, little bargaining power and lack adequate access to infrastructure like roads and transport systems, among others. Geographic impediments and cultural and political challenges are additional factors not allowing them to organize themselves properly to overcome their deprived situation. Most of the small farmers in these regions are located in mountainous areas, living in remote locations far from important points of sale, agricultural assistance providers and other beneficial services. Associating on a community level can sometimes be observed, however, this often leads to the uprising of strong intermediaries who cut the profits per product to the farmers. Generally, the Colombian culture tends to accept the presence of powerful authorities which is likely to be counterproductive for the formation of social organizations, (Hofstede, 1984). Additionally, when asked about their major problems, farmers frequently mention contamination and deforestation caused by industrial exploitation, low per piece profit margins and poor commercialization, and the effect of human displacement on rural employment as the biggest challenges perceived in their lives. Low awareness due to a lack of communication between farmers and public institutions inhibits solutions to the farmers dilemma. Farmers also report changing climate patterns as a major hazard to their wellbeing, adversely affecting many aspects of their lives. 2.4 Supply chains The normal case In terms of commercialization, farmers from Boyacá and Cundinamarca departments are almost exclusively reliant on selling their agricultural products to Colombia s largest marketplace, Corabastos in Bogotá. The markups on products for the farmers in this supply chain shrink each time they pass through the hands of one of the many intermediaries such as collectors, transporters, traders, wholesalers and retailers. These middlemen prevail in the system since their businesses are of a greater scale: the small-holders cannot compete due to lacking resources, infrastructure and organization. Consequently, the intermediaries take advantage of their relative power over the poorly associated farmers by determining price levels on which the producers subsequently depend on. Moreover, small-holders are not even recognized as commercial partners in Corabastos since the high volume of products traded requires a certain scale only to be provided by major tradesmen or at least logistic centers. New concept Driven by aforementioned problems and their underdog position in the free market, smallfarmers in this area are confronted with a need to adapt their lives to cope with this unfortunate environment. In this context, the concept mercado de campesinos (farmer markets) initiated by OXFAM GB and supported by local NGOs provides a supply chain format which is new to the farmers. Participating producers sell their fruits and vegetables at as many as ten market locations throughout Bogotá, directly to the consumer. The local 10

11 NGO s ILSA and ADUC together with OXFAM GB provide the farmers with the necessary organization of transport means and market booths as essential inputs. Since intermediate stages can be skipped, this supply chain allows the producers to sell their products at a price lower than market level, however, generating relatively high profits for the farmers at the same time. Although small-holders depend on NGO support, mercado de campesinos provides an alternative marketing channel and imparts a sensation of being valuable to the farmers since they can directly interact with their clients. Established in 2004, mercado de campesinos is a very young concept and hence cannot replace the open market system for most of its participants. The majority of those selling directly to the consumer therefore choose to also sell to Corabastos. The advantage of this mixed-type supply chain is that the farmers benefit from having NGO support in terms of organization, training and direct sales, yet maintain their marketing opportunities at a higher scale through the open market system. This approach helps many small-holders to fill the transitional gap until better organization and structuring can be established through the new farmer s market concept. 3. Challenges 3.1 Climate Change in Colombia Climate change will likely have significant impacts on the agricultural sector in Colombia, which accounts for over one-tenth of the country s GDP and employs over one-fifth of its population. Temperature rise: By 2050, the average estimated increase in annual mean temperature is expected to be 2.5ºC, with a maximum of 2.7ºC in the Arauca department and a minimum of 2ºC in Chocó and Nariño. For those crops or departments experiencing temperature increases higher than 2.5 ºC, the impacts on agriculture will likely be severe. Water stress: Higher temperatures will be accompanied by melting glaciers in the Andes (perhaps fully gone by 2030) and the disappearance of important moorlands (perhaps 56% gone by 2050), which today act as important sources of water. Meanwhile, annual precipitation variability will continue to be an issue for the entire country, so water storage will be important. Erratic precipitation: The driest periods throughout the year will likely be less dry, while the wettest periods are projected to become wetter. Predictions show an average precipitation increase of 2.5% on a national scale by 2050, with a minimum change of -1.4% in Cesar and a maximum of 5.6% in Huila. The only exceptions are the dry regions in the Caribbean coast, whose likely decreases in precipitation constitute a major cause for concern. Scientists forecast that 36% of crops will face precipitation of above 3% in at least 60% of the areas in which they are grown. Changing precipitation patterns may alter flowering dates; affect biotic factors (e.g., pests, diseases, weeds) in different production systems, thus raising production costs; and change soil water availability. Heavy rains can lead to flooding, soil erosion, and massive crop loss. This may be exacerbated in the Pacific coast, where sea level rise may also cause flooding and salinization of soils. 11

12 Pests and diseases: Pests and diseases have already increased, and under progressive climate change this situation will likely worsen. Crops currently facing these issues include Musa (e.g., bananas, plantain) in areas above 500 meters above sea level (m.a.s.l), coffee in areas above 1500 m.a.s.l., potato in areas below 2500 m.a.s.l. as well as cacao, maize, and cassava. Strong chemical treatments can represent high economic costs for small farmers and long-term costs to the agro-ecosystem environment (Lau et. All 2010). 3.2 Climate change in the Bogotá metropolitan area Besides these socio-economic challenges, progressive climate change imposes an additional hurdle to fight poverty in rural livelihoods in the region around Bogotá. Assuming an increase of temperature, many crops essential for the region s food security will lose area as producers migrate uphill; others may even disappear. Regarding the former case, the central departments of Colombia will face a specific challenge. The highlands in this region are vital ecosystems hosting a wide array of flora and fauna such as essential forests maintaining the biological equilibrium, soil nutrition and stability. These so-called paramos hold an irreplaceable role as water dispensers for the many families and farms living on the hillsides and grasslands in the lower parts. Therefore, an upward migration of crops will likely imply deforestation and change of land use in the highlands, putting ecosystems, sustainability of small-holder agriculture and hence many rural livelihoods at unbearable risk. 3.3 Upgrading supply chains Although mercado de campesinos signifies a promising concept for many rural families and has already acquired over 2500 local growers as active participants, it remains unable to reach the scale which is necessary to fight poverty in the countryside around Bogotá. Farmers still depend on the inputs and organizational skills delivered by the NGOs, which in turn rely on funding. The legalization of the concept and acquisition of permission for points of sale has been a struggle and keeps inhibiting the process of closing the social imbalance between small farmers and the open market in order to put Bogotá s food security on firmer and fairer ground. 4. Our methodology Figure 2: Analytical framework. We base our research on the commonly used definition of vulnerability of the third assessment report (IPCC 2001) as outlined in the Working Group II report (McCarthy et al. 2001) in combination with the sustainable rural livelihood framework of Scoones (1998). Reviewing the state of the art of climate change vulnerability, Hinkel (2011), founds that this approach is appropriate to identify vulnerable 12

13 people, communities and regions when applied to narrowly defined local systems. Read full text of our methodology in chapter 2 of the Methodology document. 5. Assessment of observed changes and farmers perceptions 5.1 Results from focal workshops To obtain farmer s perceptions about climate and its changes that they observed during the last decades we conducted participatory workshops. These workshops utilized facilitators to guide the discussion of a group of farmers to unearth the necessary information. The entire discussions took place with the aid of charts and the farmers were asked to use beans and simple signs to indicate the magnitude, volume, frequency or intensity of specific variables. See more details on the procedure in chapter 4 of the Methodology report. Farmers perceptions of historical climate One of the first exercises farmers were asked to illustrate historical climatic change by assessing favorability of rainfall, temperature and wind in recent years. With the aid of beans, the level of favorability ascertained by indicating how good or bad these climatic events generally affected the production systems. Figure 3 shows high variability between years for rain and wind, and a declining trend for temperature. Figure 3: Farmers perceptions of historical climate trends. Farmers perceptions of natural capital Farmers reported on the historical calendar that deforestation is a noticeable problem in the community but this is not something that can be controlled by them (Figure 4). They reported that during the last centuries nearly all forest has been transformed for agricultural production. During a participatory workshop an elderly man from Guasca remembered the large-scale fires in the 60s burning vegetation for crops and cattle: the sky was black for days from the looming clouds of smoke. Of course, the situation has improved, but occasionally there is still agricultural burning for cattle or crops. While some municipalities started with reforestation activities, others keep on 13

14 extending their agricultural land trough slash and burn techniques. Figure 4: Farmers perceptions on natural resources. Furthermore, most workshops revealed that river pollution and soil erosion has increased (Figure 4) and needs an urgent solution. eight hours for Duitama) are to the farmers only way of transporting their products to the capital. In the meantime direct access roads to the farms are often lacking maintenance or reconstruction after landslides or washed away bridges. On our visit to a small village near Caqueza (which is quite close to Bogotá compared to other towns) we couldn t drive all the way to their farms and had to change to a shuttle service waiting for us on the other side of the improvised footbridge. Therefore products to the monthly mercado de campesino in Bogotá s main square is challenging, and requires starting the journey in the middle of the night to be prepared on the sales stand when the first Bogotanos come by in the morning. Farmers are used to improvise but it makes it makes them highly sensitive to the additional threats of climate change. Some other municipalities like La Vega reported improved road access recently and rated road situation as generally good (Figure 5). Farmers perceptions of human capital Farmers perceptions of physical capital Figure 5: Farmers perceptions of physical capital - Roads. The road situation is quite complicated in the metropolitan area of Bogotá. Generally long distances taking many hours to travel (up to Figure 6: Farmers perceptions of human capital road. As reported from the workshop participants, education is improving in almost all 14

15 municipalities, but farmers don t always rate that as good for their farming. Being a farmer is not desirable anymore and on-farm training is stagnant or declining, except in Duitama, where organic farming is becoming very popular and professional. Since children have started to study, they migrate to the city early and rarely come back to work on their parents farms. It was notable that most of the participants at the workshops were elderly people and the average age of people interviewed in the surveys was 47 years old. Because of the high level of migration, family capital was rated as bad in recent years (Figure 6). 5.2 Examples of farmers comments During the field work many farmer told us their personal stories and what kind of problems they are facing in their daily business, most of them are climate related. The following comments shows facts and situations from different regions. Farmers Comments from Boyacá Deforestation causes massive erosions during the rainy season, soils can hardly be sustained. Farmers Comments from Cundinamarca My sister grows excellent peaches just 200 meters down the hill, frost damaged the fruits, then rain destroyed them. Peach farmer, Colombia, Cundinamarca, Cháqueza, 2010 A few hundred meters of altitude and more frost can make a big difference on production levels. A lot of farmers are starting with livestock because there is not enough water, and there are increasing pest and disease problems for crops Farmer, Colombia, Cundinamarca, Cáqueza, 2010 Farmer, Colombia, Boyacá, Raquira, 2010 A farmer in this village noted that the commonly grown crops aren t doing well anymore because of changing climate patterns; there was also significant change in water 15

16 availability from the mountain springs, somebody told them, that there was seismic activity inside the mountain, so most water is now sprinkling out on the other side of the ridge. Residents have had to diversify their income streams. Some started egg production, others joined a program, initiated by the FNC (Federacion Nacional de Café), to start growing coffee. After three years they can do their first coffee harvesting, but have to adapt to more complex post processing before selling it. The aging of the farming population will become a problem in the near future for the whole region; under the same conditions young people don t want to continue farming. Uphill potato farmers waste too much water and pollute it. We hardly get sufficient, clean water for strawberry cultivation. Nowadays young people from our village don t like farming anymore, they go to the city, and only elderly people continue farming. Farmer, Colombia, Cundinamarca, Guasca, 2010 Strawberry is the main income for many families in the region of Guasca in the Cundinamarca department. They complain that water access needs to be regulated and payment services could help to conserve the catchment and provide sufficient clean water for all participants from the upper to the lower basin. Farmer, Colombia, Cundinamarca, Caqueza,

17 6. Climate change predictions for 2030 & 2050 In order to predict climate change we used historical climate data from database (Hijmans et al., 2005) as current climate. Variables included are monthly total precipitation, and monthly mean, minimum and maximum temperature. To generate the future climate we downloaded and downscaled Global Circulation Model (GCM) data from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. See detailed information ( current climate, Future climate ) in chapter 3 of Methodology-document. 6.1 The summary climate characteristics for 2030 and 2050 Figure 7: Climate trend summary 2030 and 2050 for Bogotá-area. Results are based on 19 GCM Models from 4 th (2007) IPCC assessment, A2 scenario (business as usual) General climatic characteristics The rainfall increases from 2208 millimeters to 2278 millimeters in 2050 passing through 2232 in 2030 Temperatures increase and the average increase is 2.2 ºC passing through an increment of 1.2 ºC in 2030 The mean daily temperature range increases from 9.6 ºC to 9.8 ºC in 2050 The maximum number of cumulative dry months decreases from 3 months to 2 months 17

18 Extreme conditions The maximum temperature of the year increases from 26.7 ºC to 29.4 ºC while the warmest quarter gets hotter by 2.3 ºC in 2050 The minimum temperature of the year increases from 15 ºC to 16.9 ºC while the coldest quarter gets hotter by 2 ºC in 2050 The wettest month gets wetter with 332 millimeters instead of 318 millimeters, while the wettest quarter gets wetter by 33 mm in 2050 The driest month gets wetter with 56 millimeters instead of 52 millimeters while the driest quarter gets wetter by 16 mm in 2050 Climate Seasonality Overall this climate becomes more seasonal in terms of variability through the year in temperature and more seasonal in precipitation Variability between models The coefficient of variation of temperature predictions between models is 3.1% Temperature predictions were uniform between models and thus no outliers were detected The coefficient of variation of precipitation predictions between models is 10.3% Precipitation predictions were uniform between models and thus no outliers were detected 6.2 Regional changes in the mean annual precipitation (2030) Figure 8: Mean annual precipitation change by 2030 for 7 study sites in the Bogotá region. The edges of the boxes indicate the mean maximum and mean minimum values and the ends of the line the maximum and minimum values. The mean maximum and mean minimum values are defined by the mean + or the standard deviation. The mean annual precipitation increases in 2030 on average by 24 mm and in 2050 by 70 mm. In 2030 and 2050 San Antonio del Tequendama will have larger increase in precipitation than others (Figure 8 and Figure 9). We observed the smallest increase in precipitation for 2030 and 2050 in Duitama. 18

19 6.3 Regional changes in the mean annual precipitation (2050) Figure 9: Mean annual precipitation change by 2050 for 7 study sites in the Bogotá region. 6.4 Regional changes in the mean annual temperature (2030) Figure 10: Mean annual temperature change by 2030 for 7 study sites in the Bogotá region. The mean annual temperature will increase progressively. The increase by 2050 is between 2 and 2.4 ºC (Figures 11) and for 2030 between 1.1 and 1.4 ºC (Figures 10). 19

20 6.5 Regional changes in the mean annual temperature (2050) Figure 11: Mean annual temperature change by 2050 for 7 study sites in the Bogotá region. The edges of the boxes indicate the mean maximum and mean minimum values and the ends of the line the maximum and minimum values. The mean maximum and mean minimum values are defined by the mean + or the standard deviation. 6.6 Coefficient of variation of climate variables CV precipitation 2030 CV precipitation 2050 CV temperature 2030 CV temperature 2050 Figure 12: Coefficient of variation for annual precipitation and temperature 2030 and The coefficient of variation (CV) for 2030 and 2050 climate variables ranges between 0 and 20%, and may therefore be accepted as reliable (Figure 12). 20

21 7. Exposure of most important crops to climate change What means exposure to climate change? Exposure to climate change Exposure is the character, magnitude and rate of climate change and variation. To determine Exposure to climate change we used most the most important crops from identified during the focal group workshops and assessed the current and future biophysical suitability of these crops under a changing climate. We use a mechanistic model based called Ecocrop (Hijmes et al., 2005) and the FAO database with the same name (FAO, 1998 available at srv/en/home) to spatially predict crop suitability without having prior knowledge or data available. The model essentially uses minimum, maximum, and mean monthly temperatures, and total monthly rainfall to determine a suitability index. We improved the model with data gathered using expert knowledge and evidence data collected in the field. See more detailed description in the Methodology report on chapter 3. Table 1: Table of climate-suitability change for 2030 and

22 Table 1 shows results of 19 crops and their climate suitability. Models indicate for many crops values of suitability between 80 and 100 which means excellent growing conditions under current climate conditions. For 2030 predictions shows suitability values between 60 and 80. Suitability is still very good and keeps excellent for Rice, Banana, Potato and Cassava. In the meanwhile some of the crops start decreasing their suitability by 2030, so are Mango, Orange, Papaya and corn one of these crops. For 2050 suitability is predicted with ongoing decline and Papaya and Orange are reaching values below 40 on climate-suitability and end up in marginal conditions for crop development and would not be with sufficient productivity. The right two columns show change in suitability as de anomaly between future and current crop suitability. Most affected crops are Guava, Mango, Orange, Papaya and Plantain with up to 47% average declining climate suitability. To see it as a whole food basket for the metropolitan area of Bogotá the average decrease of crops climate suitability is 13%. 7.1 Measure of agreement of models predicted changes Figure 13: Measure of agreement of models predicting changes in the same direction as the average of all models at a given location for The Measure of agreement of models predicting changes in the same direction as the average of all models at a given location is generally high (Figure 13). In the following section we present a more the detailed analysis of the three crops of most interest. Find maps of all crops on data collection disk! 22

23 7.2 Potato Current suitability Potato is an important contributor to Bogotá s food security, in 2003 more than 19 thousand tons per month were consumed in the Colombian capital. Cundinamarca and Boyacá are one of the traditionally know potato growing areas and today they have because of its climate excellent conditions for sufficient production to satisfy the high demand of the city (Figure 14). Figure 14: Current climate-suitability for Potato. With future predictions for suitable potato production areas climate suitability is decreasing in lower altitude and is on the other hand increasing suitability in higher regions, which are normally occupied by the paramos, the most important water conservation zones of the Andes (Figure 15/16). 23

24 Suitability for Potato by 2030 Figure 15: Suitability for Potato by Suitability for Potato by 2050 Figure 16: Suitability for Potato by

25 Change in suitability by 2030 Figure 17: Climate-suitability change for Potato in Change in suitability by 2050 Figure 18: Climate-suitability change for Potato in Map of suitability change show above discussed shifting of potatoes up to protected areas of the paramos close to San Antonio del Tequendama y San Bernardo (Figure 17/18). 25

26 7.3 Cassava Current suitability Figure 19: Current climate-suitability for Cassava. Suitability for Cassava by 2030 Figure 20: Suitability for Cassava by

27 Suitability for Cassava by 2050 Figure 21: Suitability for Cassava by Change in suitability by 2030 Figure 22: Climate-suitability change for Cassava in

28 Change in suitability by 2050 Figure 23: Climate-suitability change for Cassava in Cassava, currently excellent suitable in the Magdalena river basin and in the lowlands of Meta department (Figure 19) is losing its excellent conditions in this areas by 2030 (Figure 20) and progressively by 2050 (Figure 21). With predicted future climate, in some traditionally cassava producing regions of Colombia cassava is up to 30% less suitable (Figure 22/23). 28

29 7.4 Rice Current suitability Figure 24: Current climate-suitability for Rice. Suitability for Rice by 2030 Figure 25: Suitability for Rice by

30 Suitability for Rice by 2050 Figure 26: Suitability for Rice by Change in suitability by 2030 Figure 27: Climate-suitability change for Rice in

31 Change in suitability by 2050 Figure 28: Climate-suitability change for Rice in Rice can be outlined as one of the winning crops in the region and will increase its climate-suitability in many regions more than 10% by 2030 (Figure 25) and up to 30% (+6% average for entire region as shown in Table 1) increasing suitability by 2050 (see Figure 26). 31

32 8. Availability and restrictions for agricultural production In order to highlight the important role of land availability for agricultural production systems we analyzed as a next step the three main influencing factors for land availability: Land use Access (road distance) Protection As most important factor for availability of land for agricultural production we analyzed land use (Figure 29) and categorized water bodies and populated areas as not available for agriculture. Areas of currently covered by forest or perennial crop systems such as coffee are classified as available but needs a land use change and would be theoretically available. However it is not recommended to clear forest in order to generate cultivating areas. Remaining areas indicated as white areas available and currently occupied even as cropland, pastureland and areas with low vegetation or wasteland. The second factor to determine availability is accessibility or also called distance-costs. We calculated the distance of each geographical location (each pixel on the map) and its distance to the closest road in distanced categories; distance accessible < 500m, inconvenient access m, costly access > 2000m (see Figure 30). If the distance to the next road is higher, distance costs are also high. Last we used protected areas as barrier for availability for agricultural extension and calculated areas inside protected areas and within a distance of 5 Kilometers around protected areas (Figure 31). 8.1 Land use Figure 29: Availability by land-use. 32

33 8.2 Access Figure 30: Road access in Bogota (distance-costs) 8.3 Protection Figure 31: Protected areas with buffer-zones in Bogota. 33

34 8.4 Combined restrictions for agricultural production Combining the three availability factors we obtain weighted restrictions as result map (Figure 32) and can further discuss highly favorable land for agricultural production with positive and negative change in crop suitability as exposed areas to climate change to develop adaptation strategies. Figure 32: Combined availability of land-use, access & protected areas in Bogota. Table 2: Table of changing climate-suitability versus land availability, numbers in grey are changes in area. 34

35 In Table 2 climate suitability and restrictions to land in 1000 hectares are combined. For 2030 and 2050 can be observed, that most of highly favourable land is facing a negative suitability change. Except rice, banana, tomato, onion and tree tomato the rest of crops are having their highest suitability lost up to for 2030 and -351 in 2050 in available areas. The consequence of this fact is that farmer will tend to extent their production areas to higher altitudes, at the moment mostly occupied by paramos and will therefore not contribute to mitigate further climate change. The increase of pressure on the paramos and the change in agriculture borders may have drastic impacts of the downstream population depending on the natural resources provided by the paramo, epically water. 35

36 9. Vulnerability of farmer s livelihoods to climate change 9.1 Vulnerability Index To compare vulnerability between regions a vulnerability index has been constructed. It is a function of the exposure by the year 2030, the sensitivity and adaptive capacity, and the households expected impact of climate change. Vulnerability index = Exposure + Sensitivity + Adaptive Capacity + Expected Impact These components together describe the abstract concept of vulnerability in a comprehensive way. The data for our index originates from the suitability modeling exercise and our sustainable livelihood assessment. Additionally, we make use of information about the motivation to adapt ( expected impact ) that we derived during our household survey. All 4 variables have equal weights. Data has been transformed to a 1 to 3 ordinal scale, where 3 refers to high resilience and 1 to a high vulnerability. Thus, the index ranges from 4 high vulnerability to 12 high resilience. For details on the methodology, please refer to the accompanying methodology report. Figure 33: Vulnerability Index for 3 case studies As can be seen from the box plots overall vulnerability is lowest in Colombia when compared to the other focus regions. This result is confirmed as significant by Oneway-Anova and t-test statistics. While the means point to a ranking of the countries in terms of vulnerability, the whiskers make clear that this is deceptive. Colombia and Jamaica share a similar range of vulnerability. This means that in both countries inequality could be an issue. Even in the resilient Colombia households exist that are very vulnerable. A comparison of the components of our Index yields additional information about the differences between the countries. See more detailed description in the Methodology report on chapter 4. First, we discuss the accumulated result of our Index, then we present findings on its components. Figure 34: Exposure compared between 3 case studies 36

37 For the construction of the vulnerability index the change in suitability has been seperated into terciles of equal number of cases. The graph, however, shows the original values as this provides additional information. The box plots show that Jamaica and Colombia exhibit similar variation in direct climate change impacts, while Guatemala will experience homogenically a low impact. Differences exist mostly in the means of Colombia and Guatemala and Jamaica. Here, Colombia and Guatemala are clearly better off. This result is confirmed as significant by Oneway-Anova and t-test statistics. On average changes are moderate to slightly positive in Colombia. The shape of the boxplot of Colombia reflects the near normal distribution of suitability change values. This means that the most common value for suitability change is zero. However, about a third of the households faces negative changes of more than 10%. Thus, despite the high average, a vulnerable group in Colombia exists. average. This result is confirmed as significant by Oneway-Anova and t-test statistics. In the chapter that discusses the results of our sustainable livelihood assessment the reasons are discussed in more detail (see following section). Figure 36: Adaptive capacitive compared between 3 case studies Similar to the results of sensitivity the box plots and a comparison of means using Anova and repeated t-tests show a higher resilience of Colombia, compared to the other two focus regions. Interestingly, the range of adaptive capacity is nearly the same for all three countries, such that the difference can only be observed in the means. No differences exist between the least prepared and best prepared households of the three focus regions. However, weaknesses and strength result from different livelihood assets. In the chapter that discusses the results of our sustainable livelihood assessment the reasons are discussed in more detail (see next section). Figure 35: Sensitivity compared between 3 case studies In terms of sensitivity all three countries show the same range of probability of indirect impacts. A clear difference only exists in the means. Colombia shows a higher resilience on 37

38 10. Sensitivity & adaptive capacity of Bogota s farmer to climate change What is the sensitivity and adaptive capacity of a System to climate change? Sensitivity to climate change Figure 37: Expected impact compared between 3 case studies The data about expected impacts has been transformed onto a 1 to 3 scale such that data falls into terciles of equal size. This results in the odd shape of the box plots. Guatemala has the highest mean with 2.22 compared to Colombia (2.02) and Jamaica (1.76). Differences in means are significant between Jamaica and Guatemala. Also a small effect exists between Colombia and Jamaica. Thus Jamaica has the lowest mean. Colombia is the country that shows the highest resilience to climate change. On average, the lowest direct impacts in our study are expected, the access to livelihood capital that provides resilience to indirect impacts and capacity to adapt are highest. The motivation to adapt is lower than in Guatemala which could be reason to concern as some farmers will experience negative suitability changes of their crops. Thus, while the average household in our survey is more resilient than in the other two countries, very vulnerable households are present in our sample. These should not be ignored. Sensitivity is the degree to which a system is affected, either adversely or beneficially, by climate variability or change. The effect may be direct (e.g., a change in crop yield in response to a change in the mean, range or variability of temperature) or indirect (e.g., damages caused by an increase in the frequency of coastal flooding due to sea-level rise). Adaptive capacity Adaptive capacity (in relation to climate change impacts), the ability of a system to adjust to climate change (including climate variability and extremes), to moderate potential damages, to take advantage of opportunities, or to cope with the consequences. 38

39 10.1 Capital stock analysis Figure 38: Spider diagram of sensitivity and adaptive capacity for all producer. The spider diagram of the modes of the different capital forms separated into sensitivity and adaptive capacity suggests a clear result. In this diagram 1 represents a low vulnerability and 3 a high vulnerability; i.e. a value of three for adaptive capacity is a high adaptive capacity, a value of one means a low adaptive capacity. In contrast, for Sensitivity 3 stands for a low sensitivity and 1 for a highly sensitive capital form. Given this ranking the diagram suggests that farmers in the Bogotá area are not very sensitive to climate change. Three of the five capital forms receive a mode of 3, meaning that the most frequent answer has been such that it fell into the highest category. The exception is financial capital which falls into the lowest category. Similarly, the adaptive capacity shows high values for all categories. However, what cannot be seen from this diagram is that the most frequent answer for financial capital is actually does not apply which implies a lack of access to this capital form. Thus, this form appears to be of crucial importance to vulnerability in the region. As is the case in the other two countries, sensitivity of financial capital is high because nearly all farmers state that they experience an impact of climate change on the quality of their products, negatively impacting their income. Credits appear to be reasonably designed and are accessible to more households than in the other countries, thus despite the high sensitivity this region is more resilient. However, adaptive capacity is low for the same reasons: Alternative crops are only available to a part of all households interviewed. Furthermore certification of any kind is nearly absent. This results in an extreme distribution of answers: Those who have access to certification fall into a high resilience category as conditions are favorable, nevertheless, many simply lack access to such alternatives. Figure 39: Spider diagram of sensitivity and adaptive capacity for producer selling to Intermediaries 39

40 Principal characteristics of the individual groups are as follows regarding the asset indicators: Figure 40: Spider diagram of sensitivity and adaptive capacity for producer selling direct to consumer Figure 41: Spider diagram of sensitivity and adaptive capacity for mixed producer (selling to Intermediaries and direct to consumer) 10.2 Cluster Analysis Cluster analysis yields three clusters for sensitivity and four clusters for adaptive capacity. The sensitivity clusters may be ranked according to their sensitivity; they are characterized by low, intermediate and high sensitivity. The four adaptive capacity clusters could not be ranked as clearly and were thus labeled clueless, low, intermediate and organic direct marketers. Sensitivity: Sensitive Households: Short or no membership in organization No credit access No answers to the questions whether the water is drinkable and the question of who takes care of the water supply -> No idea about the water? Bad houses Intermediate households Active work in an organization for many years Bad road access Credit access Climate changes cause changes in insect pattern Low sensitivity households: Frequent crop rotation Flat land Organic fertilizers used Training about markets received Member in an organization for a long time Multiple organization Relies on own production for consumption Adaptive Capacity: Clueless Households Small but outstanding group Do not answer who they sell to Do not answer how to control pests Do not answer whether they know about alternative technologies Bad water quality Households with low adaptive capacity No training No or bad technical assistance 40

41 Infertile soils Parents take care of water transport This is only a small group, most people do not carry water at all, therefore this has to be interpreted as Has to transport water Recycling of household waste Possibly recycling is understood as Reuse trash No answer to quality of water question Intermediate/Prepared households Franco soils Water from pipe or nearby Male parent in organization Own car Good technical assistance Short distance to markets Short training period (1day) No pest control applied Single provision from organization Has some sort of certificate Organic direct Marketers Receives training Many days of training per year Household labor available Organic pest control Sells to consumer Takes part in multiple activities of organizations 10.3 Site-specific vulnerability For the analysis of site specific vulnerability we employ the IPCC s standard definition of vulnerability. It is a function of the exposure as crop to climate suitability change by the year 2030 or rather 2050, the sensitivity and adaptive capacity of the farm system. Vulnerability = Exposure + Sensitivity Adaptive Capacity Similar to our Vulnerability Index based analysis we derive proxies for sensitivity, adaptive capacity and exposure based on our household survey data. We mapped results to show which farmer are highly vulnerable to a changing climate. (Please note that in order to map vulnerability we had to change the scale in comparison to previous chapters). Figure 42: Site-specific vulnerability by 2030 On the horizontal axis Exposure is plotted as crop to climate suitability change (1 low and -3 high); the vertical axis shows Sensitivity rated from 0 (low) to 3 (high); the size of the bubbles indicates the Adaptive Capacity and low Adaptive Capacity is classified as big size and high capacity to adapt to a changing climate are shown as small bubbles. The background color of the chart shows the vulnerability in traffic light colors. Red means high vulnerability and green low. Significant attention must be given to those big sample points in the upper left red colored corner; these are those with maximum Vulnerability to predicted climate change. Mapped survey sample points show clearly, that for 2030 the vulnerability of Bogotá s farmers is still moderate (Figure 42), by 2050 more of them move towards the left corner into higher Vulnerability (Figure 43). 41

42 11.1 Corn The value for corn cultivation in Colombia results in a 0.3 kg CO2e/kg. Compared with the literature value from the well accepted database GEMIS 4.6 from the Oeko-Institute it is 43% less. The result is mainly driven by less primary and secondary energy use Beans Figure 43: Site-specific vulnerability by Estimated Carbon Footprint The carbon footprint of a product presents the total sum of all greenhouse gas emissions caused by a product s supply-chain expressed in kg Co 2 e (e=equivalent) per kg product. In this chapter the aim was to calculate a comprehensive carbon dioxide equivalent footprint for corn and beans. For more details on the methodology see chapter 6 of the Methodology report. The beans in Colombia produced have higher Product Carbon Footprint (PCF) on primary level than beans from large-scale farming in Northern America. Most probably the difference in carbon footprint is due to the different yields (case study Colombia 2115 kg/ha; literature value > 2600 kg/ha). Röös et al. (2010) states, it is a common characteristic of agricultural products in general, that the yield proved to be the most influential parameter, since the accumulated emissions from a cultivated area are divided across the yield from that area. During the field work we collected necessary data to calculate the on farm carbon footprint via the Cool Farm Tool. Most farmers in the Bogotá region don t have enough records and reliable data to collect. We therefore interviewed experts to get estimation for corn and beans an average application of fertilizer and pesticides, no information on residue management and farm management. Most farmer in the region don t have own transport and do not use energy on the field and for primary processing. Figure 44: Compared carbon footprint of corn and beans in Colombia 42