VULNERABILITY ASSESSMENT FOR MOZAMBIQUE 1997/1998 An Initial Analysis of Current Vulnerability to Food and Nutritional Insecurity Inter-sectoral Vulnerability Assessment and Mapping Group MAF, MPF, MOH, FEWS, WFP Maputo, February 1998

Vulnerability Analysis and Mapping Risk Analysis Domestic Resource Capacity VULNERABILITY Targeting Vulnerable districts 1) Droughts 2) Floods 3) Pests 4) Landmines 5) Physical access 6) Price changes 1) Livestock 2) Fisheries 3) Other sources of Income 4) Food Systems 5) Land use Assessment of District Level Food Production

C. Initiatives for a Collaborative Vulnerability Analysis · identify areas and population groups most vulnerable to food insecurity and specific nutritional deficiencies and problems; · promote inter-sectoral discussion on vulnerability in Mozambique, its causes and identify important interventions to mitigate and alleviate hronic and transitory food insecurity; · establish links between vulnerability analysis, policy formulation and planning interventions; and · ensure that there is a capacity within Mozambican institutions to periodically update the vulnerability assessment on a regular basis.

D. A Framework of Analysis Vulnerability: ¨ the probability of an acute decline in food access, or consumption levels, below some critical value. According to Chambers, vulnerability represents "defencelessness, insecurity and exposure to risks, shocks and stress... and difficulty in coping with them." Vulnerability to food and nutritional insecurity comprises two components: · the risk of an event occurring (e.g. drought, cyclone, floods, and pest outbreaks); and · the coping ability of households to deal with that event (such as income, asset ownership and other sources). An assessment of risk and coping ability should encompass a time frame both for short and medium-term perspective. Levels of income and assets (domestic resource capacity) are important in assuring food security of the population in the short-term along with availability and accessibility to health, nutrition and education services in the medium and long-term. In the sum:

. Assessment of Risks: Conditions for Food production A: Historical Drought-risk Areas.

C. Flood Risk/Prone Areas · First degree risk consists of 1.7 million hectares within an elevation of less than 20 metres above sea level (masl) and within 10 km. distance from major river basins, · Second degree flood risk is defined by an elevation of meters above sea level (masl) and comprises of 2.7 million hectares (an estimated 9.6%) of national land cover. · Third degree flood risk is defined by an elevation class of metres asl. and within 10 km of major rivers consists of nearly 4 million hectares; · Fourth degree flood risk is less endemic to flood risk than the other three types and it can only have an effect in some years as flood risk associated with dam water and/or regional floods.

D: Pest Infestation and their Occurrence · Red Locust affects principally maize and attacks are more common after floods. This pest is endemic in Buzi District, Sofala Province, Dondo, Nhamatanda and Gorongoza, Gondola, Manica and Sussundenga in Manica Province. · Green Locust is prevalent in the coastal zone in the central and northern provinces of the country, attacking rice and millet crops during the germination and early growth stages of plant development in rice and millet. · The spiny locust is endemic in Changara District in Tete, and its effect is limited to this area. · Army-worm is found principally in the Central Provinces of Sofala and Manica affecting maize, sorghum, rice and beans in the districts of Dondo, Nhamatanda and Gondola. · The emergence of this pest coincides generally with dry years or low humidity, and destroys plants in the vegetative growth stage. · Quellea birds are endemic in Gaza province, and are found principally in Chokwe District. particularly active in Cabo Delgado Province where they eat grain, which has been seeded. · Rats also have a heavy impact on maize production in some districts in the south, mainly after inundation or dry periods. Rats destroy the ears, and can destroy 100% of the harvest of a field. In all the country, rats are the source of large losses of grain from granaries.

E. Limitation of Physical Access to Roads

F. Market Price Changes White maize prices have risen sharply since the 1996/7 harvest, with an average increase between June and November 1997 of 92% in the 25 SIMA markets. Sharp price rises in the Centre and Centre North of the country: · Specifically the towns of Beira, Manica, Chimoio, Tete, Quelimane and Mocuba. · The rise in this area of the country reflects primarily the heavy export trade that emerged this year to Malawi as well as probably withholding of stocks in anticipation of poor harvest next season. · Angoche, Nampula Province has also seen a sharp rise, likely associated with its switching from surplus during the harvest to deficit currently (relatively little maize is produced in and around the city of Angoche). In contrast rice prices have been generally stable this year, with an average increase of only 3% in the 25 SIMA markets. · Quelimane (35%), Montepuez (29%) and Chokwe (26%) have shown the largest price increases. Cassava is a crucial crop for food security, being more drought resistant than maize and with a harvest period that falls during the hungry season. Analysis of cassava prices, however is problematical for several reasons: only a small proportion of production is marketed; and trade in this product is more localised than for maize and rice. · Prices in individual markets can rise and fall sharply, and at any point in time there may be large price differentials between different markets where prices range from less than 800 mts/kg to over 5,400 mts/kg. · And price changes from June to November range from negative 40% to positive 197%. The only general conclusion that can be drawn from the cassava data is that local cassava prices should be monitored closely in areas considered vulnerable.

Table ---.National cash market price behaviour of maize, rice and manioc during marketing year 1997/98 Source: Sistema Nacional de Informacao de Mercados Agricolas (SIMA, MAP/DE

G. Conditions of Health and Nutrition Principal causes of morbidity ( ): · Malaria, anaemia · malnutrition, pneumonia · measles, TB Meningitis

H: Landmine Risk · Landmine, a formidable threat to human lives, has a long history in Mozambique --- some were planted during the struggle for liberation and others during the civil war. · Two types of land mines were planted: the anti-personnel and anti- tank. · Official estimates indicate about 2 million mines throughout the country. The locations are mostly related to military defence positions along roads, military bases, and strategic locations such as bridges, factories, dams and some villages. · While agricultural land was not specifically targeted for landmine in terms of risk to food security, the fear of mines can have as great an impact as their physical existence.

II. Analysis and Results: Domestic Resource Capacity 1. Resources: Land Use

B: Food Systems of Mozambique · The planalto (highlands) and midlands food system: · The lowland plains and coastal food system: · Major river basin food system: · The drylands and semi-arid food system:

Cows Per Thousand Families Red: Less than 100 Yellow: Green: Pink: > 1000

Red indicates high numbers of centers while Blue indicates low numbers of centers

Those districts with less than 6 months staple food crop production can be further classified as follows: 1. Those where although staple food crop production is low, households are accustomed to relying on purchasing a significant proportion of their staple food needs. Those districts that have a more diversified income together with reasonable market access include Chokwe and Boane. Districts, which are dependent on market purchases but have low non-agricultural income include Marracuene and Moamba. The districts in this category do not face widespread malnutrition problems. 2. Those where animal production, remittances and fishing play an important role Massangena, Changara, Chicualacuala, Xai-Xai and Moamba. These districts also have a dependency on coping strategies such as ganho-ganho, donations, and consumption of wild plants and fruits. These districts do encounter nutritional problems, in particular in drought years. Cases of vitamin C deficiencies have been reported in Moamba, and in Changara, pellagra and vitamin A deficiency. 3. Those with extreme market isolation problems Magoe, Chemba, Mabalene, Chicualacuala, Govuro, Maringue, Massangena, Mabote, Chigubo and Cheringoma. Districts which normally encounter malnutrition include Magoe, Chemba, Maringue and Cheringoma which has had cases of pellagra and vitamin C deficiency reported; in drought years problems occur in Chicualacuala, Massangena, Mabote and Chigubo. 4. Those where there is substantial production variation within the district, e.g. Mutuarara, Guija and Masingir. This implies the need for intra-district targeting. Masingir has reported micro-nutriente deficiencies; and Mutarara has general problems with malnutrition.

2. An Approach to Targeting ¨ Here we are proposing to introduce an event-driven targeting of scarce resources. Targeting must consider variations within a given situation as vulnerability generated by different disaster event has different economic, social and environmental impacts. Targeting Objectives: · Allocating food and other resources to populations that face emergency conditions and their survival is threatened; · Assisting population in absolute poverty and whose livelihood system has been eroded over time through food and other resources; · Providing non-food resources to poor populations to improve their food access and utilisation; · Providing non-food resources for improved national food availability; Levels of targeting: · geographic, · community and · specific household /gender targeting. · However, due to limited data availability and the need to conduct an in-depth analysis of vulnerability issues, the discussion of initial framework for targeting is limited to geographic targeting with limited highlights about group targeting.

III. Conclusions, Responses and Interventions 1. Conclusions: Key Features of Food Insecure Districts The following key issue standout from the analysis: 1. The study acknowledges the fact that agricultural production and other data, in its present form, does not provide a complete picture of food availability and access. The significance of second season crop production, livestock, fishery and other sources of income for many districts in the country cannot be over emphasised. For example, limited assessment of second season crop suggests that the season provide, on average % of 1st season production. In future crop sector analysis, the government of Mozambique should seriously consider assessing second season crop assessment into its national food balance sheet on a regular basis. Also, future VA analysis should take this into consideration. 2. The analysis also suggests that food crop production is very important for the economy but is not the only determinant of vulnerability. Fishery, cash crop production, petty trading, livestock rearing, hunting and labour migration is important. It should, however, be noted that there is a significant variation of these alternative incomes between households and districts. This is determined by households' location in a particular food system or location in a particular geographic areas (access to South African mine industry). 3. Current analysis suggests that large number of districts are vulnerable to both transitory and chronic food insecurity, even in years of better than average climatic regimes.

Current Vegetation Analysis: Sample Outputs December 1991December 1997 January 1992 January 1998 Areas shaded in red show MUCH BELOW NORMAL vegetation

Price Changes between Sep 1997 and Dec 1997 Red and Yellow indicate areas where prices are greater than 125% of September prices in December Price change in Major Cities (dec-Sep 97) Cabo Delagado, Nampula, Niassa, and Zambezia show high price changes

Current Flood Risk: Sample output (1996/97)