Case study: Bogotá

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 2011
1
Table of Contents
1.
Summary and main findings ................................................................................................................. 8
2.
Background ........................................................................................................................................... 9
2.1
The research area: Bogotá Region ................................................................................................ 9
2.2
The case: Food Security Bogotá .................................................................................................... 9
2.3
General Problems........................................................................................................................ 10
2.4
Supply chains .............................................................................................................................. 10
The normal case .................................................................................................................................. 10
New concept ....................................................................................................................................... 10
3.
Challenges ........................................................................................................................................... 11
3.1
Climate Change in Colombia ....................................................................................................... 11
Temperature rise: ............................................................................................................................... 11
Water stress: ....................................................................................................................................... 11
Erratic precipitation: ........................................................................................................................... 11
Pests and diseases: ............................................................................................................................. 12
3.2
Climate change in the Bogotá metropolitan area....................................................................... 12
3.3
Upgrading supply chains ............................................................................................................. 12
4.
Our methodology ................................................................................................................................ 12
5.
Assessment of observed changes and farmers’ perceptions ............................................................. 13
5.1
Results from focal workshops ..................................................................................................... 13
Farmers’ perceptions of historical climate ......................................................................................... 13
Farmers’ perceptions of natural capital.............................................................................................. 13
Farmers’ perceptions of physical capital ............................................................................................ 14
Farmers’ perceptions of human capital .............................................................................................. 14
5.2
Examples of farmers’ comments ................................................................................................ 15
Farmers Comments from Boyacá ....................................................................................................... 15
Farmers Comments from Cundinamarca............................................................................................ 15
6.
Climate change predictions for 2030 & 2050 ..................................................................................... 17
6.1
The summary climate characteristics for 2030 and 2050 ........................................................... 17
General climatic characteristics .......................................................................................................... 17
Extreme conditions ............................................................................................................................. 18
Climate Seasonality ............................................................................................................................. 18
Variability between models ................................................................................................................ 18
6.2
Regional changes in the mean annual precipitation (2030) ....................................................... 18
6.3
Regional changes in the mean annual precipitation (2050) ....................................................... 19
6.4
Regional changes in the mean annual temperature (2030) ....................................................... 19
6.5
Regional changes in the mean annual temperature (2050) ....................................................... 20
2
6.6
7.
Coefficient of variation of climate variables ............................................................................... 20
Exposure of most important crops to climate change ....................................................................... 21
7.1
Measure of agreement of models predicted changes ................................................................ 22
7.2
Potato.......................................................................................................................................... 23
Current suitability ............................................................................................................................... 23
Suitability for Potato by 2030 ............................................................................................................. 24
Suitability for Potato by 2050 ............................................................................................................. 24
Change in suitability by 2030 .............................................................................................................. 25
Change in suitability by 2050 .............................................................................................................. 25
7.3
Cassava ........................................................................................................................................ 26
Current suitability ............................................................................................................................... 26
Suitability for Cassava by 2030 ........................................................................................................... 26
Suitability for Cassava by 2050 ........................................................................................................... 27
Change in suitability by 2030 .............................................................................................................. 27
Change in suitability by 2050 .............................................................................................................. 28
7.4
Rice .............................................................................................................................................. 29
Current suitability ............................................................................................................................... 29
Suitability for Rice by 2030 ................................................................................................................. 29
Suitability for Rice by 2050 ................................................................................................................. 30
Change in suitability by 2030 .............................................................................................................. 30
Change in suitability by 2050 .............................................................................................................. 31
8.
Availability and restrictions for agricultural production ..................................................................... 32
8.1
Land use ...................................................................................................................................... 32
8.2
Access .......................................................................................................................................... 33
8.3
Protection ................................................................................................................................... 33
8.4
Combined restrictions for agricultural production ..................................................................... 34
9.
Vulnerability of farmer’s livelihoods to climate change ..................................................................... 36
9.1
10.
Vulnerability Index ...................................................................................................................... 36
Sensitivity & adaptive capacity of Bogota’s farmer to climate change .......................................... 38
10.1
Capital stock analysis .................................................................................................................. 39
10.2
Cluster Analysis ........................................................................................................................... 40
10.3
Site-specific vulnerability ............................................................................................................ 41
11.
Estimated Carbon Footprint ........................................................................................................... 42
11.1
Corn ............................................................................................................................................. 42
11.2
Beans ........................................................................................................................................... 42
12.
Strategies to adapt to the changing climate ................................................................................... 43
12.1
Farmer and supply-chain actors suggestions .............................................................................. 43
Group I ................................................................................................................................................ 43
3
Group II ............................................................................................................................................... 43
Group III .............................................................................................................................................. 44
Group IV .............................................................................................................................................. 44
Plenary discussion ............................................................................................................................... 45
12.2
Developing adaptation strategies from research ....................................................................... 45
Food security of Bogotá ...................................................................................................................... 45
Community’s vulnerability to climate change .................................................................................... 45
13.
Conclusion ....................................................................................................................................... 46
14.
References ...................................................................................................................................... 47
4
Table de Figures
Figure 1: Study area. ..................................................................................................................................... 9
Figure 2: Analytical framework. .................................................................................................................. 12
Figure 3: Farmers’ perceptions of historical climate trends. ....................................................................... 13
Figure 4: Farmers’ perceptions on natural resources. ................................................................................ 14
Figure 5: Farmers’ perceptions of physical capital - Roads. ....................................................................... 14
Figure 6: Farmers’ perceptions of human capital road. .............................................................................. 14
Figure 7: Climate trend summary 2030 and 2050 for Bogotá-area. ........................................................... 17
Figure 8: Mean annual precipitation change by 2030 for 7 study sites in the Bogotá region. ................... 18
Figure 9: Mean annual precipitation change by 2050 for 7 study sites in the Bogotá region. ................... 19
Figure 10: Mean annual temperature change by 2030 for 7 study sites in the Bogotá region. ................. 19
Figure 11: Mean annual temperature change by 2050 for 7 study sites in the Bogotá region. ................. 20
Figure 12: Coefficient of variation for annual precipitation and temperature 2030 and 2050. ................. 20
Figure 13: Measure of agreement of models predicting changes in the same direction as the average of
all models at a given location for 2050. ..................................................................................................... 22
Figure 14: Current climate-suitability for Potato. ....................................................................................... 23
Figure 15: Suitability for Potato by 2030. ................................................................................................... 24
Figure 16: Suitability for Potato by 2050. ................................................................................................... 24
Figure 17: Climate-suitability change for Potato in 2030. .......................................................................... 25
Figure 18: Climate-suitability change for Potato in 2050. .......................................................................... 25
Figure 19: Current climate-suitability for Cassava. ..................................................................................... 26
Figure 20: Suitability for Cassava by 2030. ................................................................................................. 26
Figure 21: Suitability for Cassava by 2050. ................................................................................................. 27
Figure 22: Climate-suitability change for Cassava in 2030. ........................................................................ 27
Figure 23: Climate-suitability change for Cassava in 2050. ........................................................................ 28
Figure 24: Current climate-suitability for Rice. ........................................................................................... 29
Figure 25: Suitability for Rice by 2030......................................................................................................... 29
Figure 26: Suitability for Rice by 2050......................................................................................................... 30
Figure 27: Climate-suitability change for Rice in 2030. .............................................................................. 30
Figure 28: Climate-suitability change for Rice in 2050. .............................................................................. 31
Figure 29: Availability by land-use. ............................................................................................................. 32
Figure 30: Road access in Bogota (distance-costs) ..................................................................................... 33
Figure 31: Protected areas with buffer-zones in Bogota. ........................................................................... 33
Figure 32: Combined availability of land-use, access & protected areas in Bogota. .................................. 34
5
Figure 33: Vulnerability Index for 3 case studies ........................................................................................ 36
Figure 34: Exposure compared between 3 case studies............................................................................. 36
Figure 35: Sensitivity compared between 3 case studies ........................................................................... 37
Figure 36: Adaptive capacitive compared between 3 case studies ............................................................ 37
Figure 37: Expected impact compared between 3 case studies................................................................. 38
Figure 38: Spider diagram of sensitivity and adaptive capacity for all producer........................................ 39
Figure 39: Spider diagram of sensitivity and adaptive capacity for producer selling to Intermediaries .... 39
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)...................................................................................................... 40
Figure 42: Site-specific vulnerability by 2030 ............................................................................................. 41
Figure 43: Site-specific vulnerability by 2050 ............................................................................................. 42
Figure 44: Compared carbon footprint of corn and beans in Colombia ..................................................... 42
6
Table of Tables
Table 1: Table of climate-suitability change for 2030 and 2050. ................................................................ 21
Table 2: Table of changing climate-suitability versus land availability, numbers in grey are changes in
area. ............................................................................................................................................................ 34
7
more seasonal in precipitation with the
maximum number of cumulative dry month
decreases from 3 months to 2 months.
1. Summary and main findings
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.
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
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.
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 2050. 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
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
and awareness, (ii) advocacy (local to global)
and (iii) sustainable and ecological production.
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 1.000 masl. Combined, the
diversity of this region can comprise a
significant part of the products to be found in
the local Colombian diet.
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.
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 25th worldwide
(http://www.citymayors.com). 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
2008. 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.
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
9
2.3 General Problems
2.4 Supply chains
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.
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
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.
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.
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.
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.
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
11
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).
3.3 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.
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.
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
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.
Figure 3: Farmers’ perceptions of historical climate
trends.
See more details on the procedure in chapter 4
of the “Methodology report”.
Farmers’ perceptions of natural capital
Farmers’ perceptions of historical climate
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
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.
13
extending their agricultural land trough slash
and burn techniques.
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
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.
Farmers’ perceptions of physical capital
Figure 5: Farmers’ perceptions of physical capital Roads.
Figure 6: Farmers’ perceptions of human capital
road.
The road situation is quite complicated in the
metropolitan area of Bogotá. Generally long
distances taking many hours to travel (up to
As reported from the workshop participants,
education is improving in almost all
14
Farmers Comments from Cundinamarca
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).
“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
5.2 Examples of farmers’
comments
A few hundred meters of altitude and more
frost can make a big difference on production
levels.
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.
“A lot of farmers are starting with livestock
because there is not enough water, and there
are increasing pest and disease problems for
crops”
Farmers Comments from Boyacá
“Deforestation causes massive erosions during
the rainy season, soils can hardly be sustained.”
Farmer, Colombia, Cundinamarca, Cáqueza, 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
Farmer, Colombia, Boyacá, Raquira, 2010
15
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.
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.”
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.
“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, 2010
16
6. Climate change predictions for 2030 & 2050
In order to predict climate change we used historical climate data from www.worldclim.org 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 4th (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
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
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
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 2050.
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
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 http://ecocrop.fao.org/ecocrop/
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 2050.
21
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 2050.
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
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
Suitability for Potato by 2030
Figure 15: Suitability for Potato by 2030.
Suitability for Potato by 2050
Figure 16: Suitability for Potato by 2050.
24
Change in suitability by 2030
Figure 17: Climate-suitability change for Potato in 2030.
Change in suitability by 2050
Figure 18: Climate-suitability change for Potato in 2050.
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
7.3 Cassava
Current suitability
Figure 19: Current climate-suitability for Cassava.
Suitability for Cassava by 2030
Figure 20: Suitability for Cassava by 2030.
26
Suitability for Cassava by 2050
Figure 21: Suitability for Cassava by 2050.
Change in suitability by 2030
Figure 22: Climate-suitability change for Cassava in 2030.
27
Change in suitability by 2050
Figure 23: Climate-suitability change for Cassava in 2050.
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
7.4 Rice
Current suitability
Figure 24: Current climate-suitability for Rice.
Suitability for Rice by 2030
Figure 25: Suitability for Rice by 2030.
29
Suitability for Rice by 2050
Figure 26: Suitability for Rice by 2050.
Change in suitability by 2030
Figure 27: Climate-suitability change for Rice in 2030.
30
Change in suitability by 2050
Figure 28: Climate-suitability change for Rice in 2050.
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
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 500-2000m, 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
8.2 Access
Figure 30: Road access in Bogota (distance-costs)
8.3 Protection
Figure 31: Protected areas with buffer-zones in Bogota.
33
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
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 682 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
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.
Figure 33: Vulnerability Index for 3 case studies
Vulnerability index = Exposure + Sensitivity +
Adaptive Capacity + Expected Impact
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.
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.
See more detailed description
Methodology report on chapter 4.
in
the
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
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
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
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).
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.
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.
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.
38
be of crucial importance to vulnerability in the
region.
10.1 Capital stock analysis
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 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.
Figure 39: Spider diagram of sensitivity and adaptive
capacity for producer selling to Intermediaries
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
39
Principal characteristics of the individual groups
are as follows regarding the asset indicators:
•
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
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.
40
•
•
•
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
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.
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.
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).
Vulnerability = Exposure + Sensitivity – Adaptive Capacity
41
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.
11.2 Beans
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.
Figure 43: Site-specific vulnerability by 2050
11. 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 Co2e (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.
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
More detailed and with other case studies and
crops compared results can be find in the
carbon footprint report from our contributor
Soil & More International.
strengthen against intermediaries; training for
consumers (talks to key entities & hospitals) give value to food; greenhouses and production
systems; local merchants (less dependent on
intermediaries);
interchange
between
production areas depending on their climatesuitability; knowledge Exchange; strengthen
family (grants and technical support); give more
opportunities to farmer; Advocacy (farmers
rights); present attractive agriculture projects to
young people; improve housing, roads, taped
water, land reclamation (displaced people);
rural health care system.
12.Strategies to adapt to the
changing climate
After having analyzed the collected data of the
first field work phase we went back to the
communities and presented preliminary results
of their vulnerability to climate change to
farmer and supply-chain actors. In participatory
workshop we jointly developed adaptation
strategies on community and supply chain level.
In the second part they compiled three main
adaptation strategies out of the collected ideas:
1. Improve
resource
and
on-farm
management
2. Advocacy
3. Improve marketing and production
See detailed approach of conducted workshops
in chapter 5 of Methodology report.
12.1 Farmer and supply-chain
actors suggestions
During the workshop we formed four groups, in
the following section their individual
recommended adaptation strategies are lined
out:
Group II
In this group took part: OXFAM, ILSA (Instituto
Latinoamericano para una Sociedad y un
Derecho alternativo), Mercados Campesinos
organization. Outcome of brainstorming:
Group I
In this group participated producers from the
south-west paramo-region and mercados
campesinos coordinating organization ADUC
(Asociación Departamental de Usuarios
campesinos de Cundinamarca). At the
beginning they started the brainstorming to
collect all ideas that came into mind:
Awareness & training about climate change
factors; measurement and monitoring of rainfall
and temperature patterns; advocacy with
government organizations – on local level to
protect & control paramos and catchments;
identify land conflicts; strengthen organizations
base; adaptation and mitigation strategies are
included in agendas of producer and
organizations; produce more information about
productions systems & crops; clean production
as a mechanism for mitigation and adaptation;
comprehensive vision that shelters more
regions; make diagnostics and follow up;
Reforestation with native plants, avoid
deforestation; awareness (farm management);
prepare soil organically; recover native seeds
(for inputs); water management, parks &
paramo; associate at community level to
43
change model: switch from extensive farming to
intensive farming (forages); make analysis of
water sources and their development /
involvement to climate change; as they have
better adaptive capacity, promote women's
organizational processes; good farming practice
(less water, technology packages, best seeds);
seed conservation (native seed bank to ensure
access and diversity).
and training to the community, officials and
social actors, politicians in relation to the causes
and effects of alternatives; identify risk areas
and areas providing the map and include the
proposals in the POT-disclose; in each area to
identify potential causes of high pollution to
establish degrees of responsibility that is given
to the mitigation.
Main 3 adaptation strategies:
1. Establish training- and education
programs
2. Identifying areas of highest risk
3. Identification of areas of potential
climate change causes
Developed main 3 adaptation strategies of
group two:
1. Advocacy: local, national and global
2. Promote clean production
3. Strengthen grassroots organizations
especially women
Group IV
ADUC, ANDAS (Asociación Nacional de Ayuda
Solidaria) and CICC (Comité de Interloción
Campesino y Comunal). Ideas:
Group III
Producer from central-region, ADUC and Mesa
advocacy
rural
women
organization.
Brainstorming results:
Organic and clean production (inputs, native
seeds, good cultural practices diversified
agricultural practices); advocacy of those in
charge of climate change (transnational
industries) social recovery for damages;
awareness of the population (education and
social culture); environmental conservation
(water, flora and fauna); water: a fundamental
human right not to the privatization;
appropriate soil use; recovery of ancestral
knowledge; democratic and participatory design
of a policy for the rural development
(agricultural mandate); economy must serve
man, not serve to the economy; women in
power; mother nature preserve; organic
production preserves the environment, women
in power accelerates this process.
Training and education; identify high risk areas,
knowing the POT; establish agreement with
major industries producing non-polluting
elements; establish a seed bank; preserve our
watersheds with native species; strengthen and
provide conditions for the initiatives of rural
women and youth in conservation and
agricultural and livestock production (manure,
windbreaks, digesters, awareness campaigns);
processing and sorting garbage; following up on
information received to see what percentage
we influence; establish a map to identify
potential areas for agriculture and livestock;
identify the cause in each area and pockets of
high contamination and liability agreements;
working for the defense of our mountains to
avoid being exploited by foreign firms
indiscriminately; establish training programs
3 main adaptation strategies:
1. Organic production
44
2. Awareness of population
3. Advocacy
affected their production. To protect crops from
this damages natural protection like
Agroforestry Systems could play an important
role as alternative to traditional and widespread
slash and burn agriculture (CIAT, 2010). For
example the Quesungual Slash & Mulch
Agroforestry System, coming originally from the
southwestern of Honduras includes the
principles: No slash and burn; permanent soil
cover; Minimal disturbance of soil; efficient use
of fertilizer. Application of these Quesungual
principals can result in significant benefits for
farmer: increased resilience to extreme natural
events; increase in productivity by improving
soil and water; surpluses of mayor staple foods;
availability of firewood; reduced greenhouse
gas emissions and increased carbon
sequestration;
conservation
of
local
biodiversity.
Plenary discussion
After presenting all ideas and proposed
adaptation strategies, following most important
were selected:
3 main strategies from workshops



Information, training and
awareness
Advocacy (local to global)
Sustainable and ecological
production
12.2 Developing adaptation
strategies from research
Adaptation strategies to assure Bogotá’s
food security
Food security of Bogotá
As main result from analyzing nineteen crops on
their biophysical suitability to predict future
climate conditions feeding the metropolitan
area of Bogotá can be stated, that many of
them are losing climate-suitability and will
decrease their productivity for the future. To
satisfy the demand of an eight-million-city,
efficiency of the food production system must
be improved to guarantee food security.




Crops are geographically shifting and will harm
important ecosystems close by. Land conflicts
and displaced farmer need to be reintegrated in
the territorial allocation in a narrow space.

On farmer’s perceptions, in recent year’s
damages caused by strong weather events
occurred mostly as direct or following
consequences of wind, excess rainfall and frost,
Information of potential climate
change impacts
Pilot implementation of
reorganized production (cropshifting)
Alternative crops for highly
exposed crops to climate change
Introduce Agroforestry systems:
e.g. Quesungual System
Low carbon agriculture to
mitigate climate change
Community’s vulnerability to climate
change
Presented results in chapter nine shows that
there are two groups of farmer having a low
45
financial capital (those selling direct to
consumer and those selling to intermediary), all
of them have high natural and moderate
physical capital. Human capital is low by those
elling to intermediary and we assume a low
education level for this farmer group. The social
capital is generally good, except for farmer
selling to intermediary.
13.Conclusion
In Bogotá’s metropolitan area the yearly and
monthly rainfall will increase and the yearly and
monthly minimum and maximum temperatures
will increase by 2030 and will continue to
increase progressively by 2050.
The implications are that the distribution of
suitability within the current food production
areas for Bogotá will change and for some crops
quite seriously by 2050.
For the adaptation strategies should be focused
on the group of farmer which are only selling
their products to the intermediaries, their
financial dependency from agriculture seems to
be very high. But their high vulnerability comes
mostly from instable quality and missing
technical assistance.
Shifting farming systems are a high threat for
water conserving paramos in the higher
altitudes.
The group selling only on farmers market is also
highly vulnerable because of high sensitivity in
financial and social capital; at least they have a
very high adaptive capacity, thus their
vulnerability is lesser.
Political
territorial
distribution
and
displacement of farmer in the whole region
plays an important role.
There are many possibilities to adapt to the
changing climate. The winner are thus are
willing to adapt to an evolving climate.
Adaptation strategies for impacts on
livelihoods title see GTE







Checklist for further actions
against climate change in Bogota
Training and awareness building
of communities for climate
change.
Improve credit-access
Income diversification
Building alliance along value-chain
Strengthening of local capacity to
countered with adaptation
strategies
Resuscitate traditional knowledge
e.g. natural weather signs
Knowledge sharing and best
practice learning from climate
similar areas.




46
Choose the best adaptation
strategies against climate
change
Learn to manage the risk
associated with capricious
weather: wind, ongoing rainfall,
frost.
Implement and adjust
adaptation strategies together
with policy makers
Start mitigating to reduce the
adverse affects of climate
change by reducing emissions
14.References
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System: An Eco-Efficient Option for Rural Poor. Cali:
International Center for Tropical Agriculture.
City Mayors, (2011). The largest cities in the world and
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Hijmans, R. J, S. E Cameron, J. L Parra, P. G Jones, and
Andy Jarvis. 2005. Very high resolution interpolated
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Hinkel, Jochen. 2011. “Indicators of vulnerability and
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10.1016/j.gloenvcha.2010.08.002.
Lau, C.; Jarvis, A.; Ramírez, J. 2010. Colombian
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the Intergovernmental Panel on Climate Change.
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Mondragon, H., Montoya, G (2010). Canasta basica de
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Röös, E. C. Sundberg, P. Hansson, (2010): Uncertainties in
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