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Outline four problems facing forestry in Kenya and explain how to draw a compound bar graph for crop production data.
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c) Four problems facing forestry in Kenya:
- Deforestation for agriculture: Expansion of agricultural land leads to the clearing of forests, reducing forest cover.
- Illegal logging: Unauthorized felling of trees for timber and charcoal production contributes significantly to forest degradation.
- Forest fires: Both natural and human-induced fires destroy vast areas of forest, impacting biodiversity and timber resources.
- Encroachment for settlement: Growing population pressure leads to human settlements expanding into forest areas, reducing forest land.
a) i) Drawing a compound bar graph for Wheat, Maize, and Rice paddy from 2008 to 2012 with a scale of 1 cm representing 50,000 tonnes (or 50 '000 tonnes).
To draw the graph:
- Draw a horizontal axis (X-axis) for the years (2008, 2009, 2010, 2011, 2012).
- Draw a vertical axis (Y-axis) for the total production in '000 tonnes. Label the axis "Production ('000 tonnes)".
- Mark the scale on the Y-axis: 1 cm = 50 '000 tonnes.
- For each year, calculate the cumulative production for Wheat, then Wheat + Maize, then Wheat + Maize + Rice paddy.
- Draw a bar for each year, with the total height representing the sum of the three crops.
- Segment each bar:
- The bottom segment represents Wheat.
- The middle segment (above Wheat) represents Maize.
- The top segment (above Maize) represents Rice paddy.
- Use different patterns or colors for each crop segment and include a legend to identify them.
Here are the calculated heights for each segment (in cm) based on the scale:
| Year | Wheat ('000 tonnes) | Wheat (cm) | Maize ('000 tonnes) | Maize (cm) | Rice paddy ('000 tonnes) | Rice paddy (cm) | Total ('000 tonnes) | Total (cm) |
|---|---|---|---|---|---|---|---|---|
| 2008 | 82.1 | 1.64 | 340.5 | 6.81 | 24.3 | 0.49 | 446.9 | 8.94 |
| 2009 | 123.1 | 2.46 | 191.0 | 3.82 | 0.01 | 0.00 | 314.1 | 6.28 |
| 2010 | 190.2 | 3.80 | 294.6 | 5.89 | 44.0 | 0.88 | 528.8 | 10.58 |
| 2011 | 100.9 | 2.02 | 405.8 | 8.12 | 0.01 | 0.00 | 506.7 | 10.13 |
| 2012 | 155.0 | 3.10 | 387.3 | 7.75 | 40.3 | 0.81 | 582.6 | 11.65 |
a) ii) Four disadvantages of using a compound bar graph to represent data:
- Difficulty in comparing individual components: It can be challenging to accurately compare the sizes of segments that are not at the base of the bars across different years.
- Visual clutter: If there are many categories or years, the graph can become cluttered and difficult to interpret.
- Hard to read exact values: Estimating the precise value of a segment that starts above the baseline can be difficult without additional labels.
- Not ideal for showing trends of individual components: While it shows the total trend, it's less effective for visualizing the individual trend of each component over time compared to a line graph.
a) iii) Three reasons why Kenya produces more maize than Rice:
- Climatic suitability: Maize is more adaptable to Kenya's diverse climatic conditions, including semi-arid regions, whereas rice requires specific wetland or irrigated environments.
- Dietary staple: Maize is the primary staple food for the majority of Kenyans, leading to higher demand and widespread cultivation across the country.
- Land availability and traditional farming: More land is suitable for maize cultivation, and maize farming is a more traditional and widespread practice with established infrastructure compared to rice.
b) Two other methods that can be used to represent the data in the table:
- Multiple line graph: Each crop's production can be represented by a separate line, showing trends over time.
- Simple bar graph: Individual bar graphs can be drawn for each crop to show its production across the years
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