Production in metric tons per hactare was computed for five year data points basing on the available statistics. From table 3, production and land area per crop for each crop for a five year period is shown. The table shows that production for crops like Bananas, Beans and Cassava was declining by 2008.
Table 3: Production in metric tons per hactare
Food security and projections
Food security was measured in terms of required amount of food to feed the growing population at different years and availability of agricultural land to grow this food. Using results from table 1 and linear regression analysis, an agricultural land model was developed to project available land at different years; y=8924.2-246t where, y = agricultural land in hectare and t = time (years). Average production for all crops in metric tons per hactare between 2004-2008 was determined to be 4.77ton/ha. Average Per capita consumption for an adult as per Paul. W et.al, (1991) for Bananas (220kg), Sweet potatoes (82kg), Beans (19.2kg) and Cassava (128kg) was determined to be 112.3kg (0.1123 metric tons). The Population for different years was projected basing on the 3.8 Kampala growth rate (UBOS, 2002) and only 54.4% of the total population (average adults) at each year was included in the calculation.
In table 3, the following formulas were used to determine amount of food required for average adult population for each year, required agricultural land and Food security status in terms of availability of land to grow this food.
F = PC
A1 = PC/Mh
Fs = A0 – (PC/Mh) or A0 – A1
Where; F = food required for that population at that year, P = Population of that year, C= per capita consumption, A1 = required agricultural, Mh = production in metric tons per hactare, Fs =Food security, A0 = Available Agricultural land, land to grow food for that year (see results in table 4 and figure 2). +ve positive Fs result would mean food security but the the negative –ve results meant food insecurity.
Table 4: Projected production, land and food security status in terms of agricultural land availability.
Results from table 4 show that by 1994, Kampala region was already food insecure in terms of availability of land for agriculture with a land deficit of 2682ha. From 1994 onwards as urbanisation increased through increasing population, the agricultural land deficit gap kept on widening as a result of reducing available land as shown in figure 3. Currently the region is food insecure by a deficit of 15536ha to grow food for the current population almost tripling the available 4989ha. Other conditions remaining constant, figure 3 also shows that available agricultural land in Kampala region will cease out by the year 2030.
Figure 3: Required, Available and Deficit gap of agricultural land for years between 1994-2034Discussion
Built-up land increased at a rate of 12% between 1994-2004 which increase led to a decline in agricultural land by 3%. It is important to note that as time increases the world population is increasing so this increase will continue impacting negatively on agricultural land. Table 4 shows a continuing decline in agricultural land from 8624ha, 1994 to 4989ha, 2010 thus making a 42% decline and 85% decline by year 2034. This decline also saw a 4% decrease in food production from 2004-2008. For example between 2004-2008 there was a decline of 3.8%, for Bananas, 12.5% and 5.7% for Beans and cassava respectively.
Likewise national production for crops like Bananas has been decreasing from 3.5% in 2006, 2% and 1.5% in 2007 and 2008 respectively (UBOS, 2009). The average daily calorie intake of Ugandans per person stands at 2,360 kcal. Out of this, 94 % comes from vegetal products (Abele et.al, 2006). Uganda being an agro economy, vegetal products constitute a bigger percentage on household diet. The reduction in land to grow vegetal products is likely to cause ill-health and malnutrition among households that depend on land as source of livelihood.
Lillian, N. et.al (2003) pointed out that many poor people in Kampala lack land ownership rights and instead gain access to land in poor areas like wetlands, road and railway reservations and waste disposal sites while Others utilize their backyards or encroach on undeveloped land left to fallow by landowners. It is important to note that these spaces are too small to produce significant amount of food. It is further noted that city authorities and utility service providers keep on tampering these areas by slashing crops to give way for the services. This all undermines food production in the region.
Urbanisation has also increased Land fragmentation in Kampala region. Sardik, N. (2002) points out that land fragmentation affects food production and is a direct result of rapid population growth in many poor countries. He further points out that very small landholdings which are too small to provide a tolerable livelihood turn into part-time farms, with some household members staying at home to tend crops while others migrate in search of wage employment. Sirte. L (2008) further stressed that increased food production and consumption is undermined by rapid population growth, unequal land distribution, shrinking landholdings and widespread land degradation. The reduction in man power and reduced fertility of the land automatically reduces acreage of land that would be put to growing crops.
In some cases the poor have sold out land to prospective developers and moved to cheaper places outside Kampala. The new landlords have changed the use to built-up by putting up commercial shops, residential and institution. This has led to the decline in available land for agricultural. Sardik, N. (2002) also argues that on small land holdings there is over use of the land through use of agrochemicals which eventually degrades the soil. In this fertility of the soil is reduced and so productivity of the land. The land holder will opt to put it to other use which in most cases would not be agricultural use. This continues to reduce agricultural land, food production and thus impacting negatively on agricultural biodiversity in the region.
It is still doubtable whether developing countries (Uganda inclusive) will have Urban-Rural migrations to have a situation where Agricultural land would increase at decreasing Built-land land. The fact that rural-urban migrations and natural growth are leading to high rates of urbanisation, agricultural biodiversity and food production are still decreasing up to a point of zero if no measures are put in place to conserve land for agriculture.
To improve food production and acreage of agricultural land, Agnes, M and Magaret, K (1994) recommended use of agronomic methods such as irrigation, fertilizers, pesticides and high yielding crop varieties. This would be impractical in a wider part of Kampala region which depends on a convention water system. Also some parts of Kampala lack access to the lake which would provide enough water for this activity. More so, too much use of pesticides would result into pollution of water sources and wetland habitats through rain wash. This would inventuary lead to loss of wetland and underground biodiversity
In conclusion, Kampala region like other developing regions facing high rates of urbanisation require a policy that incorporates population growth, per capita consumption and natural resource utilization. This would always check on how much natural resource is available to sustain the population. In this way, measures combating population growth and resource utilization would be determined. This will reduce the risks ahead of human life in terms of land and food availability
It is important to note that the project measured food security basing on assumption that people are growing food within Kampala and did not consider food and other consumed crop types that come from outside Kampala region.
Also the decline in crop production could have been partly due to crop pests. Abele et.al 2006, noted a general decline in production of Bananas and Cassava which could have been due to the outbreak of Banana Xanthomonas Wilt and Cassava Mosaic. These diseases have had a negative impact on banana production in the past few decades.
Also only 54% of the total population was included in the calculations. Reliable statistic on consumption per capital was only available for the average adults (18+ years).
Abele, S., Twine, E. and C. Legg (2006). Food security in the major cassava growing regions of Uganda. C3P Food Security Briefs No.1. Ibadan, Nigeria (IITA). http://c3project.iita.org/
Agnes, M.S., Magaret, K.M. (1994). Uganda food balance sheet, Ministry of Finance and Economic Planning.
Lillian, N. K., Augustus, N., David, M., Juliet Kiguli (2003). Access to Land for Urban Agriculture in Kampala
Oldeman, L.R., Hakkeling, R.T.A., Sombroek, W.G., 1999. World map of the status of human-induced soil degradation: Global assessment of soil degradation. International Soil Reference and
Information Centre (ISRIC), Wageningen, The Netherlands.
Peter, W., Yeko, M., Chales, O. and Paul, Wagubi (1991). Uganda Food Security and Exports;
Statistical document. Ministry of Health, Nutrition divivsion.
Sadik, N (2002) Population growth and the food crisis. http://www.fao.org/docrep/U3550T/U3550T02.HTM
Sirte, Libyan Arab Jamahiriya (2008). Water for Agriculture and Energy in Africa: the Challenges of Climate Change. Uganda National Investment Brief
UBOS (2002). Uganda Population and Housing Census; Bureau of statistics.
UBOS (2009). Uganda Bureau of Statistics; Statistical Abstract.
The project has introduced me to new and scientific methods of analysing spatial data, depicting changes over time and measuring quantity of risk ahead. Most of the methods used in this project where learnt in class while some I read about them but I had never applied them at such a level. The project has increased my capacity to analyze more and more!
From participating in the project, I have gained technical skills using geographical technologies. Remote sensing sofware like ENVI EX, ArcGIS and spatial analyst operations were new to me. In as much as some training was provided on how to use it, I explored more of this software on my own something that was not so easy but more beneficial in the end.
Also that one requires more than one geographical tool/software for biodiversity and conservation analyses. The project showed that the GPS captures data but does not analyze it while ENVI is good at remote sensing and ArcGIS good at spatial analysis. Technique gained here is that “at what stage do i transfer into another tool environment, what conversions do I need to do and so on.” It is crucial to understand the GRID, RASTER, VECTOR formats and when each is required.
It has come to my understanding that data is everywhere but not available anywhere. In executing this project I came across a lot of secondary data and institutions. However, availability of what I wanted specifically was a problem as much of it was in fragments. Some was for years out of my scope, some in different units while some raw and other semi processed. I have learnt that this causes a change in the planned methodology. The type data and stage at which data is got will determine the appropriate methodology and formulas to use.
I can not leave out the social side of it. I got exposed to new fellow academicians, great mentors and biodiversity conservation experts. The timely electronic communication, discussions gave a good feeling of family as being part of the MYCOE/SERVIR Biodiversity Initiative in Africa.
I would like to thank our mentors and trainers for the guidance provided in accomplishing this project, different organizations; the AAG, RCMRD, SERVIR-AFRICA, ESRI, ITT among others for the leadership, training and facilitation offered in this project. Lastly, special thanks go to Dr.Patricia Solis and the team for the coordination work, well done!
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