FEZ working group report.doc
A Preliminary Analysis of Food Economy Zones in Zambia
Introduction
To date, food security vulnerability analysis in Zambia has focussed on rural areas at the
District level, in terms of data collection and presentation. However, selected indicators of
vulnerability are often mapped across the whole country, with a subsequent explanation in
the text as to why an indicator or interpretation is not especially relevant in particular
districts. The meeting reported on here aims to start a progression to a refinement of the
current technique by delimiting zones (clusters of Districts) where a subsequent, customised
set of indicators will capture most of the components of household food security. The
procedure is to start by generalising, then refine the analysis by systematic selection of more
detailed data. The aim of the process is to better focus the choice of indicators for
monitoring, response and development.
Underlying this approach is the concept of food economy zones (FEZ). A FEZ is a
geographical area where the principal sources of household income, and, under a similar
approach, the livelihood system, are homogeneous. For example, zone ‘A’ may be defined
as being predominantly maize-growing with some livestock. Neighbouring zone ‘B’ might
see incomes dominated by fishing. The intention at this initial stage is not to say whether the
district income derived from maize is 75% or 80%, but to identify that maize is dominant, as
opposed to fishing, hence the location is attached to zone ‘A’ rather than zone ‘B’.
Note that we are working here with Districts because that is the smallest unit with common
data reporting across the whole country. There is much to be argued for a future refinement
of the techniques down to the community level. Such an approach would, for example,
make objective differentiation between livelihood systems in the valley and on the plateau of
individual Districts, or a separation of fishing communities alongside water bodies and
rivers. However, at this time, there are insufficient available data for a detailed delineation
and subsequent monitoring.
Once the FEZs have been proscribed through a clustering of Districts in this broad sense,
district data, and sub-district where possible, will be analysed to look at the relative
importance of the components within the region e.g. is the contribution of maize 70% or
80% in Area ‘A’. This latter progress will take time to refine, as opposed to a broad-sweep
approach in this initial delimitation.
The Process
A one-day working group was held with eleven Zambian participants drawn from a range of
institutions, and two overseas facilitators (the WFP VAM consultant and the regional VAM
Officer). See Annex 1 for names and affiliations.
An opening discussion focussed on the concept of food security arising from both production
and purchases, relating in themselves to availability and access. A contrast was drawn
between rural situations where the major part of access would be through self-production
and some through purchase, made possible by sale of labour, off-farm income, cash crops,
and so on, and urban areas that are dominated by purchases made possible through sale of
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labour in the formal (waged / salaried) or informal sectors. A brainstorming within the
group produced a collection of determinants for food security, listed in Table 1.
Table 1. Elements of food security in Zambia, round-table brainstorming
1 Nov. 2000
Maize
Tea
Thatching Grass
Cassava
Horticulture
Firewood extraction
Millet
Coffee
Timber extraction
Sorghum
Sugar Cane
Hunting / culling licenses
Sweet Potato
Oranges
Sale of food crops
African Potato
Water Melon
Remittances
Beans
Mangoes
Wages - full time, formal
Groundnuts
Palm Oil
Charcoal burning
Vegetables
Wheat
Cash crop sales
Rice
Wild Tamarind
Livestock sales
Onions
Cattle
Artisanal crafts
Pumpkins
Poultry / eggs
Beer brewing
Chikanda
Goats
Fish sales
Irish Potato
Sheep
Wild food sales
Cowpeas
Pigs
Prostitution
Livingstone Potato
Fish
Seasonal labour
Bambara Nuts
Caterpillars
Small scale mining
Mushrooms
Mice / rats
Stone crushing
Okra
Game Ranching
Vending
Pineapples
Game meat extraction
Marketeering
Bananas
Intswa (flying ants)
Cross border trade
Sunflower
Locusts / grasshoppers Rental of property
Paprika
Honey - wild
Bee products
Tobacco
Honey - domesticated
Money lending
Cotton
Dairy products
Begging
Cashew
Lobola
Mining / Quarrying
??Theft
The next step was to take each District in turn and collectively agree on the principal
determinants of food security through production and/or income generation. A three-part
scale was used:
1. Very Important in that particular District
2. Important in that particular District
3. Significant in that particular District
Findings from the discussion were collated on a flipchart as the discussion progressed, they
are presented here in Annex 2. This was a long process, taking up the remainder of the
working day. After the meeting, the consultant converted the flipchart results into
spreadsheets.
Maps were produced for each of the indicators identified in the district-by-district
discussion. These are presented in Annex 3. Note that the consultant slightly modified the
group interpretations by splitting wage income, primarily to bring out zones dependent on
waged agricultural activities, hence more likely to be impacted by drought, and the mining
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sector, more likely to be impacted by economic factors. A slight delay occurred at this time
because of the need to obtain a digital version of the new District boundary map. This was
obtained from the Central Statistics Office and converted to an appropriate format (BNA) for
mapping in the Mapviewer software through the generous assistance of the US Geological
Survey in Sioux Falls, South Dakota.
After preparing a composite spreadsheet and individual maps, the consultant grouped
Districts with similar patterns of food security indicators. This is a subjective process and
should, ideally, be checked using an objective approach. However, the product, shown
below in Figure 1, will be checked through circulation amongst the working group and other
parties. Again, this is a first step and refinement is seen as an essential process.
Figure 1: Food Economy Zones of Zambia
based on first analysis of information
from working group meeting held on
1 November 2000
4
1
Numbers refer to Table 2, see below
2
15
17
5
3
6
14
16
13
19
12
9
8
7
11
10
(9)
18
21
20
23
Note: colours are only for showing clusters. There is
no necessary linkage between clusters of identical
colours, with the exception of Mazambuka District
which is grouped with Chibombo etc.
22
Figure 1 contains three distinctively urban Districts with their own unique features,
Livingstone, Lusaka and Kabwe. There are also four Districts that seem to be unique,
especially when compared to their neighbours, Mpulungu, Nyimba, Kazungula and
Chavuma. These Districts should undergo particular attention from the members of the
working group to see if the interpretation is valid. Finally there are sixteen Food Economy
Zones containing from two to eight Districts.
Table 2 contains a summary of the Food Economy Zones mapped in Figure 1. Note that the
groupings are aiming to capture the broad features. This is a necessary compromise between
the detail shown in the individual maps (Annex 3) and provincial or national-scale
generalisations. Note also that at the extreme detail end of the spectrum, i.e. a zone with
only one district, it is difficult at this stage to summarise the system by excluding indicators
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identified in the working group e.g. Mpulungu. This may be possible later by using more
quantitative data on production and incomes.
Table 2 (part): Descriptions and members of Food Economy Zones based on working
group discussions, 1 November 2000
No. Geographic Area
Districts
Description
1
Luapula Province, northeastern
Northern Province
Chiengi, Nchelenge, Kaputa,
Kawambwa, Mwense, Luwingu,
Chilubi, Samfya
Cassava and fishing as
main components, consider
also cross-border trade.
2
Southern Luapula Province
Mansa, Milenge
3
Central Northern Province
Mporokoso, Mungwi, Kasama
4
Mpulungu District, Northern
Province
Mpulungu
5
Northeastern Northern Province
Mbala, Nakonde, Isoka
6
Southeastern Northern Province,
northern Eastern Province
Chinsali, Chama, Mpika, Lundazi,
Mambwe
7
Southern Eastern Province
Chipata, Chadiza, Katete, Petauke
8
Nyimba District, Eastern Province
Nyimba
9
Most of Central Province and
southwestern Northern Province
Serenje, Mkushi, Chongwe,
Chibombo, Mazabuka (not
geographically contiguous)
10
Southern Lusaka Province
Kafue, Luangwa
11
Lusaka District, Lusaka Province
Lusaka
12
Kabwe District, Central Province
Kabwe
13
Southern Copperbelt Province and
northwestern Central Province
Mpelembe, Masaiti, Kapiri Moshi
Cassava, millet and maize
as main components.
Cassava, millet as main
components, consider also
beans and maize.
Millet, mangoes, fishing,
cross-border trade, wages
from tourism and
transport.
Beans, maize and cattle as
main components, consider
also cross-border trade.
Maize and game meat as
main components, consider
also beans, groundnuts and
sorghum.
Groundnuts, maize,
cotton, cattle, pigs, goats
and cross-border trade as
main components, consider
also soya bean and
sunflower.
Groundnuts, maize,
bananas, game meat, and
timber as main components.
Maize, wheat, cattle and
agricultural wages as main
components, consider also
soya bean, irish potato,
vegetables, dairy and
poultry.
Fishing and game meat as
main components, consider
also maize.
Formal wages, trading,
vending/marketeering,
horticulture, vegetables,
and poultry as main
components, consider also
dairy and prostitution.
Wages and maize as main
components, consider also
cattle and dairy.
Sweet potato, maize, bee
products and charcoal as
main components.
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Table 2 (part): Descriptions and members of Food Economy Zones based on working
group discussions, 1 November 2000
No. Geographic Area
Districts
Description
14
Northeastern Copperbelt Province
Chililabombwe, Chingola,
Mufulira, Kalulushi, Kitwe,
Ndola, Luanshya
15
Eastern Northwestern Province
Solwezi, Kwanyama, Kasempa
16
Western Northwestern Province
Mwinilunga, Zambezi, Kabompo,
Mufumbwe
17
Chavuma District, Northwestern
Province
Chavuma
18
Western Province
Lukulu, Kalabo, Mongu, Kaoma,
Senanga, Shangombo, Sasheke
19
Western central Province and
northern Southern Province
Mumbwa, Itezhi-tezhi, Namwala
20
South-central Southern Province
Monze, Choma, Kalomo
21
Kazungula District, Southern
Province
Kazungula
22
Livingstone District, Southern
Province
Livingstone
23
Eastern Southern Province
Sinazongwe, Gwembe, Siavonga
Wages, mining, small-scale
mining, cross-border
trade, maize, vegetables,
dairy, poultry, charcoal as
main components, consider
also prostitution.
Maize, game meat and
sweet potato as main
components, consider also
timber.
Cassava and maize as main
components, consider also
fishing.
Maize, cattle and crossborder trade as main
components.
Cassava, maize, cattle and
fishing as main components,
consider also millet, timber
and cross-border trade.
Maize, cattle, fishing, game
meat and wages (tourism)
as main components.
Soya bean, sunflower,
maize, tobacco, cattle and
ag wages as main
components, consider also
wild fruits and mushrooms.
Cattle, maize, millet,
sorghum, fishing, game
meat and cross-border
trade as main components.
Wages, tourism and dairy
as main components,
consider also maize, wheat
and prostitution.
Cattle, fishing and goats as
main components, consider
also cotton and sorghum.
The working group opening discussion, represented in Table 1 above, listed about 70
components of food security, through access to food via production or purchase. Subsequent
working group discussions, district by district, then identified 53 of those components to be
very important, important or significant at the District level (see maps in Annex 3). The
interpretation presented in Table 2 reduces the number to 23 main components, having not
including the non-urban single District zones, as explained above. This is not to say that the
excluded components are insignificant. Rather, the scale of operation and the need for
summarisation through operational commonality will lead to some locally important
components not being included. Part of the iterative process of refinement is to review the
interpretation and amend where necessary.
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The Next Steps
The working group meeting was a first step. Results of the meeting have been tabulated,
mapped and interpreted to produce a map of Food Economy Zones in Zambia. This map
(Figure 1) needs validation and refinement, again drawing on local experience and expertise,
through, ideally, a second meeting or individual discussions. The refinement process should
be taken over by a local institution, which for the purpose of this discussion could include
the WFP Zambia VAM office as it has a vested interest in operational use of the results.
Following, or perhaps as part of the refinement and agreement on a final grouping, the
income from each of the main components for a particular FEZ should be quantified. This
will further refine potential target areas for monitoring and programmed development
prioritisation.
One of the working group members posed some questions after the meeting. These include
temporal aspects such as the impact of potential climate change, particularly observed
rainfall variability, and movements of people and livestock e.g. to central parts of Zambia
such as Mkushi. These are questions that need to be addressed through the development of
time series for the agreed indicators for each Food Economy Zone, going back as far as
consistent data will permit. The same temporal element suggests that this process should
perhaps be repeated every five years or so, using people that have up-to-date knowledge of
the country and starting from a clean slate in terms of discussions.
Finally, we return to the issue of geographic scale. District level data have been the basic
input to the VAM process over the last five years because that is the most detailed
disaggregated data readily available across the whole country for a number of indicators.
This represents, therefore, an operational reality. However, there are some marked withindistrict differences in food security reflected by the components discussed here, such as in
those districts with distinct physiographic features such as valley and plateau. In addition,
there is increasing demand for programme actions to be targeted at the household level,
which implies the need for data to support and monitor such operations.
Until widespread sub-district data become available and are collected in a data management
system, it will be necessary for the analytical focus to remain at the district level. However,
one hybrid approach may be to identify those districts of special interest through the process
described here and then, on an individual district basis, build up a more detailed, household
level database. This could then be used for monitoring, targeting and impact evaluation of
both food security conditions and programmed response.
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Annex 1
Members of Working Group Meeting
Mr. Francis Banda – Met Department
Mr. Lewis Bangwe - MAFF
Mr. Alfred Daka – WFP
Dr. Graham Farmer- VAM Consultant
Mr. Michael Isimwaa – MAFF
Mr. Richard Lisimba- FRA
Mr. Chembo Mbula- DMMU
Mr. Ronald Msoni – Mt. Makulu Research Station
Mrs. Chansa Mushinge -FEWS
Ms. Yande Mwape – DMMU
Mr. Erminio Sacco -WFP Region Office
Ms. Helen Samatebele- PAM
Mr. Ballard Zulu - FSRP
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Annex 2
Notes from district by district discussion
Note that CBT refers to cross border trade
No. District
1
Nchelenge
2
Chiengi
3
Kaputa
4
Kawambwa
5
Mwense
6
Mansa
7
Milenge
8
Samfya
9 Chilubi
10 Luwingu
11 Mporokoso
12 Mbala
13 Mpulungu
14 Kasama
15 Mungwi
16 Isoka
17 Nakonde
18 Chinsali
19 Mpika
V. Important
Important
Significant
Notes
Fish
Cassava
Fish
Cassava
Fish
Cassava
Fish (v.imp/imp)
Cassava
CBT
Palm Oil
palm oil increasing
CBT
Palm Oil
palm oil increasing
CBT
Game Meat
DRC refugees
Tea wages
Maize
Millet
Bananas
CBT
valley/plateau, wages (tea)
CBT
Cassava
Fish
Cassava
Maize (v.imp/imp)
Wages (v.imp/imp)
Cassava
Palm Oil
Millet
Trading
Maize
Millet
CBT (imp/sig)
Fishing
Rice
Cassava
Gane Meat
Fishing
Cassava
Cassava
Fishing
Maize
Game Meat (v.imp/imp) Maize
Cassava
Millet
Beans
Cattle
Maize
CBT
Mangoes
Fishing
Millet
Wages
Maize
Coff
Wages
Beans
Cassava
Millet
Cassava
Sorghum
Rice
Millet
Cattle
Rice
Beans
Maize
Cattle
Maize
Beans
CBT
Millet
Maize
Cassava
Beans
Wages
Millet
Game Meat
Beans (imp/sig)
Maize
Groundnuts
8
provincial capital
beans?
Trading
island
Beans
Millet
Beans
refugees
Millet
Sorghum
harbour, transport, tourinsm
provincial capital
Fishing
CBT
Okra
Groundnuts
Game Meat
Trading
Caterpillars
Cassava
Sorghum
Fishing
Irish Potato
shifting cultivation
valley/plateau, swamps, wages
(railway)
FEZ working group report.doc
No. District
V. Important
Important
20 Chama
Rice
Sorghum (v.imp/imp)
21 Lundazi
Maize
Groundnuts
Cattle (v.imp/imp)
Beans
Small scale mining
Maize
Cotton
Groundnuts
Wages
Game Meat
Maize
Maize (imp/sig)
Tobacco
Game Meat
CBT
Tobacco
Cotton
CBT
Game Meat
Rice
Tobacco
Cattle
Pigs (local sp.)
CBT
Sorghum
Wages (imp/sig)
Cotton
Goats
Sunflower
Soya Beans
Pigs
22 Chipata
23 Mambwe
24 Chadiza
25 Katete
26 Petauke
27 Nyimba
28 Serenje
29 Mkushi
30 Kapiri Mposhi
31 Kabwe
32 Chibombo
Maize
Cattle
CBT
Groundnuts
Cotton
Maize
Cattle
CBT
Groundnuts
Cotton
Maize
Cattle
CBT
Groundnuts
Cotton
Timber
Maize
Sweet Potato
Irish Potato
Maize
Tobacco
Vegetables
Irish Potato
Maize
Wheat
Soya Beans
Wages (esp. agric)
Charcoal burning
Maize
Sweet potato
Trading
Tobacco
Wages
Maize
Maize
Vegetables
Irish Potato
Significant
Notes
valley/plateau
Sorghum
Pigs (local sp.)
valley/plateau, 'vulnerable in
valley', polygamy (muslim), pigs
(local)
Goats
provincial capital, pigs (local)
Groundnuts
wages (tourism, wildlife)
Goats
Sunflower
Soya Beans
Pigs
Goats
Sunflower
Soya Beans
Pigs
Game Meat
Game Meat
Groundnuts
Bananas
Caterpillars
Game Meat
Wages
Cattle
Livingstone Potato
Coffee
valley/plateau, renamo/refugees,
ex-combatants from DRC and
Angola
CBT
Pigs
Sugar Cane
Small scale mining wages (agric)
Wheat
African Potato
Game Meat
valley/plateau, wages (agric)
Bee Products
Sunflowers
Fishing
Cattle
Dairy
Charcoal Burning
Wheat
Dairy
Poultry
Wages
Firewood
Fishing
9
Horticulture
Soya Beans
provincial capital, wages (agric,
power)
wages (tourism)
FEZ working group report.doc
No. District
33 Mumbwa
34 Chililabombwe
V. Important
Important
Significant
Notes
Vegetables
Maize
Cotton
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
Game Meat
Wages
Cattle
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Small scale mining
CBT
Vegetables
Dairy
Poultry
Maize
Charcoal burning
Wages
Tobacco
Mining
wages (tourism)
Prostitution
wages (industry, mining, timber,
govt.)
Prostitution
wages (industry, mining, timber,
govt.)
Prostitution
wages (industry, mining, timber,
govt.)
Prostitution
wages (industry, mining, timber,
govt.)
Prostitution
wages (industry, mining, timber,
govt.)
Prostitution
wages (industry, mining, timber,
govt.), provincial capital
Prostitution
wages (industry, mining, timber,
govt.)
Small scale mining
Bee Products
Coffee?
wages (agric), check coffee
35 Chingola
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
36 Kalulushi
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
37 Mufulira
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
38 Kitwe
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
39 Ndola
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
40 Luanshya
Wages (mining)
Wages (industry)
Timber
Wages (govt.)
41 Mpelembe
Maize
Wheat
Soya Beans
Sweet Potato
Charcoal Burning
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No. District
42 Masaiti
43 Lufwanyama
44 Solwezi
45 Mwinilunga
46 Chavuma
47 Zambezi
V. Important
Important
Significant
Maize
Sweet Potato
Charcoal Burning
Game Meat
Maize
Sweet Potato
Sweet Potato
Beans
Small scale mining
Soya Beans
Bee Products
Pineapple
48 Kabompo
Cattle
CBT
Bee Products
49 Mufumbwe
Maize
50 Kasempa
Maize
51 Lukulu
Cassava
Cattle
Fishing
Rice
Fish
Cassava
Cattle
Fishing
Cassava
Mangoes
Cattle
Maize
Cattle
Cassava
Timber (hardwoods)
Thatching Grass
Fishing
Cattle
52 Kalabo
53 Mongu
54 Kaoma
55 Senanga
56 Shangombo
CBT
Cattle
57 Sesheke
Cattle
Timber
Sorghum
CBT (Namibia)
Maize (v.imp./imp.)
Cattle
58 Kazungula
Wages
Small scale mining
Notes
wages (timber)
Cassava
Maize
Millet
Timber
Cassava
Maize
Cassava
Maize
Pumpkin
Game Meat
Wages (mining)
CBT
CBT
wages (mining), refugees,
provincial capital
Fishing
refugees (unita)
west bank inaccessible
Game Meat
Maize
Cassava
Game Meat
Bee Products
Cassava
Bee Products
Game Meat
Timber
Maize
Fishing
Timber
(hardwoods)
bee product export
Sorghum
CBT
Game Meat
Timber
Rice
Early Maize
Thatching Grass
Game Meat
Sweet Potato
Groundnut
Maize
Cassava
Timber
Fishing
Maize
Cassava
Millet
Fishing
Cassava
Maize
Sorghum
Millet
Fishing
Game Meat
CBT
11
CBT in diamonds
cut-off
refugees
Millet
Cashew Nut
provincial capital, maize is
early on flood plain
Tobacco
refugees, poor accessibility
poor accessibility
FEZ working group report.doc
No. District
V. Important
Important
Significant
Notes
59 Livingstone
Wages
CBT
Dairy
Prostitution (imp/sig)
Wheat
Maize
provincial capital, wages (tourism),
maize is peri-urban
60 Kalomo
Maize
Tobacco
Soya Beans
Cattle
Fishing
Cattle
Maize
Fishing
Game Meat
Cattle
Maize
Maize
Cattle
Sunflowers
Wages
wages (agric)
Game Meat
Wages
Prostitution
wages (tourism)
Wages
Prostitution
wages (tourism, hydro)
Tobacco
Soya Beans
Sunflower
Wages
Tobacco
Soya Beans
Sunflower
Wages
Sweet Potato
Cotton
Wheat
Soya Beans
Fishing
Wild Fruits
Mushrooms
wages (agric, govt.)
Game Ranching
Poultry
wages (agric, sugar industry)
Milk supply to Lusaka
Small scale mining
Sorghum
Soya Beans
Millet
Wages (mining)
Goats
Sorghum
Maize
wages (cotton, mining)
Bananas
Wages
Wild Fruits
Fishing
Cattle
Small scale mining
Game Meat
Game Meat
Cattle
Small scale mining
61 Namwala
62 Itezhi-tezhi
63 Choma
64 Monze
Maize
Cattle
65 Mazabuka
Sugar Cane
Maize
Cattle
Dairy
Wages
Fishing
Goats
Cattle
Cotton
Wages (ag ind)
Fishing
Cattle
Cotton
Fishing
CBT
Goats
Maize
Wages
66 Sinazongwe
67 Gwembe
68 Siavonga
69 Kafue
70 Luangwa
71 Chongwe
72 Lusaka
Fishing
Artisanal Crafts
CBT
Maize
Wheat
Horticulture
Vegetables
Dairy
Cattle
Poultry
Wages
Wages
Trading
Horticulture
Vegetables
Poultry
CBT
Vending/Marketeering
Prostitution
Prostitution
Dairy
12
Mushrooms
Maize
Millet
wages (hydro, tourism, agric)
wages (mining, quarrying,
industrial, agric)
Maize
Sorghum
Prostitution
Soya Beans
wages (agric)
national capital, wages (govt.,
tourism, business, institutions)
FEZ working group report.doc
Annex 3
Maps of Identified Components of Food Security
Note that for each District in turn, the working group collectively agreed on the principal
determinants of food security through production and/or income generation within that
district. A three-part scale was used:
1. Very Important in that particular District
2. Important in that particular District
3. Significant in that particular District
The findings were subsequently mapped and those maps are presented here. For technical
reasons of file size, the maps are stored in a number of separate files1
1
All relevant files are stored in a folder called FEZ Workgroup Nov 2000. Maps were generated using
Mapviewer software based on the data held in a file called “working group ranking.xls”. Boundary file used
was newzmdis.bna which may be further cleaned by the US Geological Survey and sent to WFP VAM. Map
files, extension GSM, were created for each component and have self-explanatory names. Relevant DOC files
are:
1. FEZ working group report.doc (this document)
2. roots and tubers.doc (GSM files in Word format)
3. legumes.doc (GSM files in Word format)
4. grains.doc (GSM files in Word format)
5. cash and tree crops.doc (GSM files in Word format)
6. livestock.doc (GSM files in Word format)
7. woodland products (GSM files in Word format)
8. mining and commerce.doc (GSM files in Word format)
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