Prosul climate change adaptation thematic study

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Pro-poor Value Chain Development Project in the Maputo and Limpopo Corridors
A thematic study of climate change and
adaptation responses for horticulture,
cassava and red meat value chains in
southern Mozambique
Financed by:
Proposal submitted by the African Climate & Development Initiative (ACDI),
University of Cape Town (UCT)
Physical address: ACDI, Geological Sciences Building, University of Cape Town
Postal address: Private Bag X3, Rondebosch, 7701, South Africa
Tel: +27 (0) 21 650 5598
Email: zoe.visser@uct.ac.za

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Acknowledgements
We acknowledge and thank the following people who have contributed their time and expertise to
guide the project:
 Mr Daniel Ozias Mate, Project Coordinator, Projecto de Desenvolvimento de Cadeias de Valor
nos Corredores de Maputo e Limpopo (PROSUL), for overseeing this project.
 We owe sincere thanks to Mr Egidio Mutimba, who spent many hours coordinating meetings,
driving on field trips, translating for our researchers, and engaging with stakeholders.
 Mr Anacleto João Chibochuane Duvane, Director Nacional Adjunto, Instituto Nacional De
Meteorologia.
 Ms Etelvina da Conceicao Mazalo, Chefe do Gabinete de Estudos e Difusão, CENACARTA (Centro
Nacional de Cartografia e Teledetecçäo) for supporting the ACDI team with access to GIS map
data.
 Mr Inãcio Nhancale, Direcçäo Nacional de Extensão Agrãria (DNEA), for providing the bigger
picture of agriculture and the nature and uptake of extension services.
 Mr António Mavie, Gestor Técnico Nacional FEWS NET Moçambique, for providing extensive
data on crops and pricing movements in food markets and general household vulnerability.
 The enthusiastic members of the six field focus groups who supplied us with so much
information at the following sites: 1) Marracuene, 2) Lunane – Xai Xai, 3) Chidenguele –
Manjacza, 4) Josina Machel – Inharreme, 5) Hoyo Hoyo – Mabelane, 6) Island Josina Machele –
Manhiça.
Recommended Citation:
African Climate and Development Initiative, (2016). A thematic study on climate change and
adaptation responses for horticulture, cassava and red meat value chains in southern Mozambique.
A report to PROSUL – Centre for the Promotion of Agriculture. University of Cape Town.

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Executive Summary
PROSUL is a pro-poor agricultural value chain development project in the Maputo and Limpopo
corridors of southern Mozambique. The project is managed by the Ministry of Agriculture and Food
Security (MASA). The aim of PROSUL is to sustainably increase financial returns to smallholder
farmers, including interventions on climate resilience, land tenure and gender equity. The objectives
of this study are to evaluate the impacts of climate change on three agricultural value chains, namely
red meat, horticulture and cassava, in the three southern Mozambican provinces of Maputo, Gaza
and Inhambane.
The methods used to assess the climate change impacts on the abovementioned agricultural value
chains included inter alia: i) a review of historical climatic and meteorological data; ii) analysis of
predicted climate change over the next 10 to 20 years based on CORDEX Regional Circulation Models
(RCMs); iii) analysis of current land use through remote sensing; iv) mapping of complex climate-
related risks and vulnerabilities within the target districts; v) appraisal of the exposure and sensitivity
of the respective agricultural value chains and ecosystems to climate hazards; and vi) identification
of appropriate adaptation responses.
The analysis of historical climate shows that maximum temperatures in the Inhambane and Gaza
provinces increased by an average of ~0.2 °C during the period 2000-2010. Within the same period,
average minimum temperature increased across Gaza province by up to 0.3-0.4°C relative to
historical baseline climate. Although the increases in average temperatures appear small, these
increases reflect an increase in the frequency of events such as extremely high temperatures and
heatwaves. Analysis of climate models indicate that maximum and minimum temperatures will
continue to increase during the next 10-20 year period. In addition to the observed and predicted
increase in average temperate, it is also predicted that Mozambique’s agriculture sector will be
affected by changes in rainfall as a result of climate change. Analysis of CORDEX RCMs predict that
the length of dry periods is increasing and that the length of the rainy season is shortening. These
predictions are supported by observations obtained through field interviews conducted with
farmers. In Maputo and Inhambane provinces, farmers report that the onset of the rainy season has
shifted and occurs relatively late compared to historical rainfall patterns, whereas farmers in Gaza
province report that the rainy season begins earlier than usual as a result of climate change. In all
provinces, farmers report that the cessation i.e. the end of the rainfall season is arriving relatively
earlier. Climate models project an increase in extreme rainfall.
Fieldwork undertaken in support of this study included interviews with various government
authorities and extension providers. These engagements provided valuable insights into some of the
challenges experienced by those providing technical services and advice to farmers. Interviews were
conducted with farming associations at the farm level and in some informal markets (including one
in Maputo). The multi-criteria decision analysis (MCDA) is based largely on the data and information
collected during this process. Information gathered during the fieldwork phase of this study found
evidence that climate change is already resulting in negative impacts on agricultural value chains. In
the horticultural value chain, high temperatures reduce the quality and market value of fresh
produce and increase spoilage. In the red meat value chain, high temperatures coupled with dry
periods and overstocking causes negative impacts on the health, condition and productivity of
livestock. Occurrence of insect-borne disesases is relatively high and may be exacerbated by
increased temperatures as well as limited access to veterinary services. The tendency to accumulate
livestock as a form of wealth increases the vulnerability of farmers to intense drought events, which
may cause significant loss of livestock and result in negative consequences for livestock-dependent
households, particularly in the country’s primary red meat production areas. Cassava production is

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also negatively affected by the changes in Mozambique’s climate conditions, including through the
increased prevalence of pests such as whitefly which are vectors of Cassava Mosaic Disease (CMD).
The top priorities that emerge from the MCDA process mostly relate to improved infrastructure and
greater access and use of water. Water access is needed to irrigate horticulture, improve water
availability in the cassava value chain, and for watering of livestock. A key problem in all three of the
product value chains is the challenge of transporting perishable products to their various markets.
This challenge is partly due to a lack of infrastructure and facilities such as livestock slaughterhouses,
refrigeration and cold chain facilities for fresh goods, and post-harvest processing of cassava and
other staple crops. The development of such facilities and infrastructure is constrained by the
limited availability of electricity infrastructure. Infrastructure for processing allows for increased
production, earlier processing post-harvest, and better storage before sale. Electricity and
infrastructure are therefore key to being climate adaptive and increasing resilience to climate
change. The red meat value chain does not operate optimally or derive significant revenue for its
stakeholders. Animals tend to die during challenging climate conditions such as drought, and with
little capacity to reduce stock numbers during trying times, stock owners end up losing significant
wealth. When there is drought, and stock numbers are high, the grazing resources deplete at a faster
rate. Current practices of storing wealth in livestock numbers exacerbate this situation.
The horticultural and cassava value chains can be improved if farmers have more access to water
during times of need such that they are more climate adaptive and provide more income to farmers.
Farmers will also benefit if they are able to transport greater quantities of better quality produce
into the market system. The field work and MCDA outputs also indicate the benefits of crop
diversification, as it appears that competition in the value chains, especially in that of cassava,
results in low returns to the farmers. Vulnerability mapping provides some insights into the areas of
highest climate sensitivity. These are largely in the more arid western areas and show the highest
levels of degradation. Interventions are required in these areas as a matter of priority. The
interventions of PROSUL should prioritise those areas which have been identified by this study as
being the most vulnerable to climate change and related shocks.
Key recommendations include:
1. Focusing on the development of enabling infrastructure
2. Wherever possible, increase access to water for irrigation and livestock
3. Increase access to electrification for the establishment of facilities for processing and cold
storage, such as abattoirs with high standard slaughter protocols.
4. Promote access to low-cost options for control of disease vectors in livestock, such as
installation of spray races for cattle dipping
5. Promote/increase access to low-cost options for water-efficient drip-irrigation, especially where
boreholes are the main source of irrigation water.

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Contents
Acknowledgements.................................................................................................................................2
Recommended Citation: .........................................................................................................................2
Executive Summary.................................................................................................................................3
1. Introduction ..................................................................................................................................11
1.1. Overview of PROSUL.............................................................................................................11
1.1.1. PROSUL strategy............................................................................................................11
1.1.2. Institutional arrangements and government policy context........................................12
1.2. Aims and objectives of the Climate Change Thematic Study ...............................................12
1.3. Climate vulnerability of southern Mozambique...................................................................13
1.4. Introduction to the red meat, horticulture and cassava value chains..................................14
1.4.1. Red meat.......................................................................................................................14
1.4.2. Horticulture...................................................................................................................14
1.4.3. Cassava..........................................................................................................................14
1.5. Additional factors of consideration to the value chains.......................................................15
1.5.1. Gender issues................................................................................................................15
1.5.2. Land tenure...................................................................................................................15
2. Methodology.................................................................................................................................16
2.1. Field work..............................................................................................................................17
2.2. Climate analysis.....................................................................................................................17
2.3. Vulnerability mapping...........................................................................................................18
2.4. Multi-criteria decision analysis .............................................................................................18
2.5. Introduction to the Climate Analysis ....................................................................................19
2.6. Recent climate trends (1981-2014) ......................................................................................21
2.6.1. Temperature .................................................................................................................21
2.6.2. Rainfall ..........................................................................................................................22
2.6.3. Concluding remarks and summary findings of observed trends ..................................23
2.7. Future climate.......................................................................................................................27
2.7.1. Temperature .................................................................................................................27
2.7.2. Rainfall ..........................................................................................................................28
2.7.3. Concluding remarks and summary of findings of projected changes...........................29
3. Descriptions of the value chains...................................................................................................29
3.1. The red meat value chain......................................................................................................29

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3.1.1. Value chain environment..............................................................................................30
3.2. The horticultural value chain ................................................................................................34
3.3. The cassava value chain........................................................................................................38
4. Mapping of exposure to floods and drought................................................................................41
4.1. Definitions and approaches ..................................................................................................41
4.2. Drought exposure and loss of vegetation cover...................................................................42
4.2.1. Biophysical sensitivity of vegetation cover to drought.................................................43
4.2.2. Drought effects or over-grazing?..................................................................................44
4.2.3. Implications of exposure to drought.............................................................................46
4.3. Flooding.................................................................................................................................50
5. Applying a Multi-Criteria Decision Analysis ..................................................................................51
5.1. Introduction ..........................................................................................................................51
5.1.1. Linking the vulnerabilities in the value chains to adaptation options ..........................51
5.2. Multi-criteria decision analysis .............................................................................................51
5.2.1. The criteria....................................................................................................................52
5.2.2. Values used in each criterion and ranking score ..........................................................52
5.2.3. Results of the Multi-criteria Decision Analysis..............................................................53
6. Adaptations in the value chains....................................................................................................64
6.1. Adaptations in the red meat value chain..............................................................................64
6.1.1. Climate risks and related pressures..............................................................................64
6.1.2. Adaptation priorities.....................................................................................................66
6.1.3. Geographical areas for prioritisation............................................................................66
6.2. Adaptations in the Horticulture value chain.........................................................................68
6.3. The cassava value chain........................................................................................................70
7. Conclusions ...................................................................................................................................74
7.1. Key recommendations..........................................................................................................75

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7.1.1. Promoting climate-resilient agriculture........................................................................75
7.1.2. Providing for knowledge management.........................................................................76
7.1.3. Developing capacity within CEPAGRI on a regional climate change agenda................77
8. References ....................................................................................................................................78
9. Appendices....................................................................................................................................80
9.1. Appendix A: Logical framework ............................................................................................80
9.2. Appendix B: Value chain analysis..........................................................................................84

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List of Figures
Figure 1: Annual mean total precipitation for each grid cell for the period 1981-2014. Data taken
from the CHIRPS dataset. Units [mm]....................................Erro! Marcador não definido.
Figure 2: Rainfall anomalies for each grid cell. Data taken from the CHIRPS dataset. Units [mm]Erro!
Marcador não definido.
Figure 3: Annual mean temperature for each grid cell for the period 1981-2014. Data taken from the
CRU TS3.23 dataset. Units [Celsius].......................................................................................24
Figure 4: Difference between decadal maximum mean temperature and maximum mean
temperatures for the entire period from 1981 to 2012 (a-c), decadal minimum mean
temperatures and minimum mean temperatures for the entire period from 1981 to 2012
(d-f). Data taken f m CRU TS3.23 dataset. Units [degree Celsius].........................................25
Figure 5: Climatological rainfall onset month (a) and cessation month (b), averaged for the period
1981 to 2014. Based on data from the CHIRPS dataset........................................................25
Figure 6: Decadal mean annual rainfall onset (a) and cessation (b) trends for the period 1981 to
2014. Based on data from the CHIRPS dataset. Units [days/decade]...................................26
Figure 7: Decadal trends in precipitation indices (table 1) over the period 1981 to 2014. Indices
shown at the top left and units in the top right. Based on data from the CHIRPS dataset.
Stippling indicates regions where trends are significant at the 95% level............................26
Figure 8 Projected multi-model mean changes (in %) in precipitation indices (table 1) for the period
from 2036 to 2065 under RCP8.5 emission scenario, relative to the reference period from
1976 to 2005. Stippling indicates grid points with changes that are not significant at the
95% level................................................................................................................................29
Figure 9 Individual NDVI values per district over a range of years, indicating the progressive drying of
the region, especially the western parts...............................................................................45
Figure 10: Within-season NDVI comparisons for the districts of southern Mozambique, indicating
how close each district was to the medium-term average for January. Redder colours
indicate the largest deficits. ..................................................................................................48
Figure 11: The NDVI anomaly for January 2016 at the height of the drought, relative to the long-
term mean for Januarys (2001-2015). The gold colours represent drought impacts on near
natural vegetation, influenced by national parks. The orange and red colours represent the
drought and human impacts on vegetation cover................................................................49
Figure 12: Flooding hazard map of southern Mozambique, based on satellite images of historically
flooded areas, in relation to districts. Source: FEWS NET (2014).........................................50
Figure 13 Priority areas (Postos) for value chain interventions - red meat and horticulture...............67
Figure 14 The First to fourth order model/schema of climate impacts (Source: (Petrie et al., 2014). 77
List of Tables
Table 1: PROSUL project provinces and districts for the value chains of red meat, horticulture and
cassava (Source: PROSUL, 2016). ..........................................................................................11

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Table 2 Definitions of the indices of precipitation extremes used
(Sourcehttp://etccdi.pacificclimate.org/list_27_indices.shtml) ...........................................22
Table 3 The red meat value chain components and primary actors ...................................................32
Table 4 Climate influences on the red meat value chain.....................................................................33
Table 5 The horticulture value chain components and primary actors...............................................36
Table 6 Climate influences on the horticulture value chain. ...............................................................37
Table 7 The cassava value chain components and primary actors......................................................40
Table 8 Climate influences in the cassava value chain ........................................................................41
Table 4 Top 10 adaptation options, ranked from most important to least desirable, with
explanations of the criteria used to derive their position in the ranking table (not final). An
explanation of the evaluation scores is given in the main text. ...........................................................54
Acronyms
AOGCM Atmosphere Ocean Coupled General Circulation Models
ASAP Automatic Standard Application for Payments
CDD Consecutive Dry Days
CEPAGRI Centre for the Promotion of Agriculture
CMD Cassava Mosaic Disease
DADTCO Dutch Agricultural Development and Trading Company
DNEA National Directorate of Agriculture Extension
DUAT Direito de Uso e Aproveitamento de Terra (Right to use and Benefit from Land)
ENSO El Niño/Southern Oscillation
ETCCDI Expert Team on Climate Change Detection and Indices
FFS Farmer Field School
GCM Global Cirulation Models
Ha Hectares
IFAD International Fund for Agricultural Development
IFDC International Fertiliser Development Centre
IIAM Mozambique Institute of Agricultural Research - Instituto de Investigação Agrária de
Moçambique
INAM National Institute of Meteorology
ITCZ Inter-tropical convergence zone
LAI Leaf Area Index
MASA Ministry of Agriculture and Food Security
MCDA Multi Criteria Decision Analysis
NDVI Normalised Difference Vegetation Index
PRA Participatory Rapid Appraisal
PRCPTOT Total Annual Precipitation
PROSUL Pro-Poor Value Chain Development Project in the Maputo and Limpopo Corridors
R95pTOT Annual precipitation on very wet days (total of rainfalls above the 95th
percentile)

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RCM Regional Circulation Model
RCP Representative Concentration Pathways
SDII Simple Day Intensity Index – the average rainfall of rainy days
SNV/ILRI A combination of SNV – the not-for-profit international development organisation
founded in the Netherlands and ILRI, the International Livestock Research Institute
SWIO South West Indian Ocean
WMO World Meteorological Organisation

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1. Introduction
The outcomes of this study are to provide solutions to the following: How can PROSUL mainstream
climate change into Centre for the Promotion of Agriculture CEPAGRI, promote climate-resilient
agriculture, provide for knowledge management and develop capacity within CEPAGRI on a regional
climate change agenda? The study develops an analysis of climate change based on observed and
modelled future climates, and field work to obtain data about the various value chains of red meat,
cassava and horticulture. Data obtained from this process informs a multi-criteria decision analysis
(MCDA) which attempts to prioritise the most effective and cost-beneficial adaptations that will
improve climate resilience.
1.1. Overview of PROSUL
PROSUL is a pro-poor agricultural value chain development project in the Maputo and Limpopo
corridors, within the Centre for the Promotion of Agriculture (CEPAGRI), which itself is a subsection
of the Ministry of Agriculture and Food Security (MASA). The objective of PROSUL is to sustainably
increase financial returns to smallholder farmers through higher production volumes, higher quality
product in the three value chains of horticulture, red meat and cassava, through improved market
linkages, more efficient farmer organisations, a higher farmer share of the final added value and
interventions on climate resilience, the implementation of land tenure and greater gender equity
(PROSUL, 2016). PROSUL has various funders, including the International Fund for Agricultural
Development (IFAD), Spanish Trust Fund Loan, the ASAP Grant, Government of Mozambique and
other private investors and beneficiaries (PROSUL, 2016).
The target area for PROSUL’s projects is 19 districts in Maputo, Gaza and Inhambane provinces
(Table 1).
Table 1: PROSUL project provinces and districts for the value chains of red meat, horticulture and
cassava (Source: PROSUL, 2016).
Value Chain Province Districts
Red meat Maputo Manhiça; Magude
Gaza Chókwè; Guijá; Chicualacuala; Massingir; Mabalane
Horticulture Maputo Moamba; Marracuene; Namaacha; Boane
Gaza Xai-Xai; Manjacaze; Chókwè; Guijá; Chibuto
Cassava Gaza Manjacaze
Inhambane Zavala; Inharrime; Jangamo; Morrumbene; Massinga
1.1.1. PROSUL strategy
The general objective of the project of increasing incomes of farmers in the red meat, horticultural
(in the irrigation areas) and cassava value chains is to be done through technical assistance in
production, provision of support services for increasing that production and the quality of product,
increasing access to various markets, and through providing means for adaptation to challenging
climates (climate change), all with a particular focus on gender and especially women.

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Specifically,
 The improvement, rehabilitation and expansion of selected irrigation schemes;
 Strengthening of links between actors in the value chain; and
 Creating an enabling environment for the development of the value chains.
The aims and objective of the PROSUL project design documents, as well as the Terms of Reference
for this study, note that the PROSUL programme should have a climate resilience approach that is
private-sector driven, and should have market linkages (local markets – which have lower quality
barriers and can absorb production). It should also develop services (link smallholders with service
providers), promote sustainability of farmers organisations, increase returns to farmers and develop
innovative business models.
1.1.2. Institutional arrangements and government policy context
The PROSUL project takes place within the context of various government departments and line
functions, along with the associated policies. The government departments of concern in the
PROSUL context are the following:
PROSUL is the responsibility of the Centre for the Promotion of Agriculture (CEPAGRI) in the Ministry
of Agriculture (MASA). CEPAGRI is a public institution responsible for promoting commercial
agriculture and agro-industries. The Ministry of Agriculture and Food Security (MASA) – formerly
MINAG, is responsible for organising and ensuring the implementation of legislation and policies
concerning livestock, irrigation, agro-forestry plantations and food security as well as ensuring food
and nutritional security for the population. Other responsibilities include promoting inter-sectoral
coordination regarding the formulation, monitoring, evaluation and implementation of the policy
framework.
The government policies with which PROSUL is also particularly aligned include the Poverty
Reduction Action Plan (PARP), which is a policy for rural economic growth, and the Strategic Plan for
Agricultural Development (PEDSA), which has a goal to convert subsistence farming to market-
orientated agriculture that ensures food security for the country and improves farmers’ income. It
also aligns with the National Plan for Agribusiness Development (PNDA), as well as the Agricultural
Extension Master Plan (AEMP), also aimed at improving production, productivity and farmer
incomes.
Other government departments and policies of relevance to the PROSUL programme specifically
concerning climate change and agricultural production include: the Ministério da Terra, Ambiente e
Desenvolvimento Rura – MITADER (Ministry of Land, Environment and Rural Development –
formerly the Ministry of Environmental Coordination -MICOA), which is responsible for land use
planning and demarcation. Under this falls the National Adaptation Program of Action (NAPA) on
climate change adaptation, and the National Plan for Agribusiness Development (PNDA). Also under
this ministry is the environmental fund Fundo Nacional do Ambiente (FUNAB), which was
established in 2000 as the National Implementing Entity (NIE) for the Adaptation Fund of the IPCC,
with the purpose of promoting sustainability and responding to climate change issues.

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1.2. Aims and objectives of the Climate Change Thematic Study
The objectives of this study, as set out in the PROSUL Terms of Reference, are to
1. Assess current land use and capability through remote sensing analytics,
2. Review climatic and meteorological historic data,
3. Assess potential impacts of climate change over the next 10 to 20 years,
4. Analyse the climate-related risks and vulnerabilities in the target districts,
5. Appraise the exposure and sensitivity of the value chain products and ecosystems to climate
hazards, and
6. Propose adaptation responses.
1.3. Climate vulnerability of southern Mozambique
The climate of the southern Mozambique interior ranges from arid to semi-arid, while the coastal
regions are subtropical, with higher humidity and annual rainfall and a marked seasonal rainfall
distribution. The whole region is subject to frequent droughts and is highly exposed to cyclones,
especially along the coast. Gaza Province has an aridity index of between 0.2–0.4: potential
evapotranspiration is more than double precipitation, indicating its general dryness. Drought is a
climate hazard experienced frequently across the region.
The dominant mode of climate variability in the region is closely related to El Niño/Southern
Oscillation (ENSO) in the Pacific Ocean, with a pattern of negative correlation between net
photosynthesis (plant growth) and the El Niño phase of ENSO. This is especially strong in the lower
Limpopo River Basin (Williams and Hanan, 2011). During the El Niño (+ve) phase, rainfalls are usually
substantially lower than average, resulting in increased and extended periods of water stress in
plants, causing an inhibition of CO2 metabolism and decreasing plant growth and photosynthesis
(Tezara et al., 1999). However, the variations in the Indian Ocean, especially via the Indian Ocean
Dipole, also influence rainfall patterns either reinforcing the ENSO influence or cancelling it out. This
makes predictions of drought based on ENSO phase difficult and potentially hazardous to the people
of the region. In sum, too little is known about the combined influences and dynamics of these
climate-forcing ocean-atmosphere couplings.
Large amounts of rainfall occur occasionally over the mid and lower Limpopo River Basin as a result
of cyclones and tropical storms in the South West Indian Ocean (SWIO), causing landfall over the
Mozambique coastline. Additionally, warm-cored low-pressure systems on the boundary of the
Inter-tropical Convergence Zone (ITCZ) create large systems of atmospheric convergence
(Engelbrecht et al., 2013) . The result is several days of torrential rain and regional flooding, which
can destroy crops1
. These events are also particularly devastating for subsistence livelihoods because
1
E.g. In 2001, Cyclone Leon-Eline, caused enormous damage to the livelihoods of people living on the Limpopo
flood plain and completely flooded the town of Chokwe, leading to the closure of businesses important to the
economy of the town.

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the floods occur mostly during the January to March late summer season when plants like maize are
in the seed-set stage, resulting in severe crop losses.
Despite the agriculturally rich soils of the flood plain, farming households are generally poor, have
small land holdings and are left in a state of desperation when the torrential rains – and related
flooding – result in the destruction of their crops. Poor roads are made worse during the wet season
and heavy rainfalls, increasing the isolation of some settlements. Transport routes to the major
markets are insufficient – for example, Mabalane is poorly integrated into the national economy.
The region is covered with a thick bush scrub, as well as a savannah ecosystem with grasses and
medium-height trees. The general aridity (mean annual rainfall ranges from 400–600 mm/year)
means that maize production is marginally viable in some places, but experiences a high failure rate
because of the variability of the climate.
1.4. Introduction to the red meat, horticulture and cassava value chains
Agriculture in the southern provinces of Maputo, Gaza and Inhambane is mostly constituted by the
red meat, horticultural and cassava value chains. While in specific areas these are the majority of
livelihood-supporting activities, in reality many households take part in more than one of the value
chains or activities. A short description of PROSUL interventions and expected outcomes in the
various value chains follows.
1.4.1. Red meat
The purpose of the PROSUL project with regards to the red meat value chain is to increase the
income to cattle, goat and sheep producers through improved production techniques and climate
smart actions, as well as better organised markets (PROSUL, 2016). The project plans to positively
impact 5600 smallholder ruminant producers. The lead service provider here is the SNV/ILRI
Consortium (PROSUL, 2016).
1.4.2. Horticulture
The purpose of the PROSUL project with regards to the horticulture value chain is to increase income
to smallholder farmers producing irrigated vegetables by increasing the productivity (volume and
efficiency) and quality of vegetables for both domestic and commercial market segments (PROSUL,
2016). Key components of the project include rehabilitating 2100 hectares of irrigable land or
previously irrigated land that has now fallen into disrepair or been damaged in severe floods, and
additionally, improving linkages with the various value chain stakeholders such as traders and the
market segments. The objective is to positively impact 4800 smallholder farmers. The Lead Service
Provider is the Gapi-SI/Novedades Agricolas.
1.4.3. Cassava
Cassava - otherwise known as manioc or manihot esculenta - is a perennial shrub of South America
of the Euphorbiaceae family and is a major source of carbohydrates for many millions of people (El-
Sharkawy, 2004). It is the third largest source of carbohydrates in the tropics after rice and maize.
Its value stems from its drought tolerance and ability to grow on poor soils – which admirably fits the
description of parts of southern Mozambique (PROSUL, 2016).

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The purpose of the PROSUL project with regards to the cassava value chain is to increase the quality
of the product and yield (PROSUL, 2016). This will be done by i) introducing improved varieties of
cassava, ii) strengthening farmer organisations, iii) promoting outgrower schemes, and iv) improving
farmers’ access to support services. The project plans to positively impact 8000 smallholder farmers
with a cultivation area of ~2800 hectares (PROSUL, 2016). The Lead Service Provider in this value
chain is the SNV/Mahlahle Consortium. The target areas in the cassava value chain tend to be far
from markets, thus the marketing and commercial aspects of the product are less important than
improving the food security of households in those districts where PROSUL is implementing the
cassava value chain.
1.5. Additional factors of consideration to the value chains
The sensitivity of the value chains to climate change is affected by other issues that concern the
stakeholders within these value chains, particularly gender and land tenure. Separate thematic
studies have been conducted to understand the implications of gender and land tenure issues on
PROSUL activities and planning.
1.5.1. Gender issues
While important progress has been made on increasing the political representation of women, as
well as improving access to education and health, less progress has been made on improving the
socio-economic status of women, including levels of employment, agricultural productivity and
income in Mozambique (Tvedten, 2011). Gender inequality in Mozambique results in increased
vulnerability to environmental challenges such as severe climatic variability – women do not have
access to the same resources as men do, which has implications for the climate resilience of the
family unit. A gendered response to climate change and development challenges is therefore
necessary, as it has been shown that increasing the social and economic standing of women results
in increased wealth of households. Additionally, it has been shown elsewhere (for example in
Zambia) that women tend to introduce changes to agricultural methods, such as adaptations to
climate change, faster than men (Arslan et al., 2013).
1.5.2. Land tenure
In Mozambique, all land is owned by the state. Land use rights can however be held by people and
organisations. The regularisation of land tenure and land registration is the purpose of the Direito de
Uso e Aproveitamento de Terra or DUAT (Right to use and Benefit of Land). DUATs are necessary
because of increasing competition for land. Land grabbing in some areas has led to the loss of
livelihoods by local communities. There is also a significant problem around land access and
production efficiency. People with large amounts of land held under DUAT have a higher efficiency

16
and production than people with small land rights2
. The lack of land tenure and access to land are
issues that are likely to increase the sensitivity of people and farming systems to climate change.
2. Methodology
Restating the objectives, this study reviews climatic meteorological historic data and assesses the
potential impacts of climate change over the next 10 to 20 years. These are addressed in the climate
analysis section below. The study also assesses current land uses through remote sensing analytics
and analyses the climate-related risks and vulnerabilities in the target districts. This is contained in a
separate section using Normalised Difference Vegetation Index (NDVI) mapping to determine the
amount of greenness and vegetation in the landscape and uses various techniques to determine the
amount of change due to drought and to human agency.
The study then describes and appraises the exposure and sensitivity of the value chain products and
ecosystems to climate hazards. The report does this by providing a description of each value chain,
which was conducted through fieldwork. It examines the exposure of each stage of each value chain
to climate hazards, and their sensitivity to these hazards. It uses quantitative data where possible
and qualitative assessments where only such information is available. It examines the socio-
economic system around each value chain for constraints imposed by climatic variation, which may
enhance the sensitivity of the value chain to climate hazards and therefore increase vulnerability.
The details of these methods are provided below. Finally, it provides recommendations on reducing
both the sensitivity of the value chains to climate hazards and, where possible, reducing exposure to
such hazards. The study uses a ranking system to classify the importance of each possible
adaptation.
The final objective of this report is to produce a list of adaptation options that are climatically
resilient that will serve the PROSUL objectives of increasing smallholder farmer income. The study
takes the form of an assessment of the potential impacts of climate change on specific agricultural
value chains in the context of existing and emerging development challenges in the region. The
adaptation options are developed from examining exposures, sensitivities and inefficiencies in the
value chains especially as they pertain to climatic and other environmental conditions.
2
If someone used a particular piece of land for more than 10 years, they become the rightful holder of the DUAT for that
plot without further consideration, although the owner of the land is still the state. Threats of loss of land are already in
place – there is competition between communities and also outside investors who “grab the land”. DUATs serve to
provide a legal basis for protecting and maintaining sole rights of use to parcels of land. DUAT holders may go into
partnership with outside investors, however, meaning that the benefits of the use of the land can also flow to the investor.
This may introduce conflict over land-use rights at times when it becomes unclear how the benefits of the use of the land
many be apportioned. Investors however bring benefits of the introduction of improved technology, higher production
and improved yields.

17
The report does not go into detail on services provided by the government, for example, except
where they might be affected by climate. Exposure and sensitivities in the value chains are identified
by data collection exercises, which are field trips to the region to meet different stakeholders in the
system, as well as the undertaking of remote research such as extracting and evaluating general
circulation model (GCM) and downscaled Regional Circulation model (RCM) results. This includes
remotely sensed changes in vegetation cover that result from drought and human influences, and
flood extent, relating to extreme events. The different sections of this report address all of the
above components. The methodology chosen to assess these goals is described below.
2.1. Field work
Field work has been an important method of collecting the relevant information for this thematic
study. Two field trips have been held to date. The ACDI expert team was accompanied by PROSUL
team members and had the benefit of their project experience.
The first field trip involved meeting with PROSUL personnel, project service providers responsible for
the liaising between PROSUL and farmer groups and other agricultural role players within target
areas. The team also gathered data for the vulnerability map and climate change vulnerability
assessment. Data-collection meetings held in the capital on this first field trip included:
 Mr Anacleto João Chibochuane Duvane, Director Nacional Adjunto, Instituto Nacional De
Meteorologia regarding access to climate data.
 Ms Etelvina da Conceicao Mazalo, Chefe do Gabinete de Estudos e Difusão, CENACARTA (Centro
Nacional de Cartografia e Teledetecçäo) regarding access to GIS data for different layers that
would go into vulnerability mapping and other aspects of mapping.
 Mr Inãcio Nhancale, Direcçäo Nacional de Extensão Agrãria (DNEA) regarding the national context
of agriculture and the design and uptake of extension services.
 Mr António Mavie, Gestor Técnico Nacional FEWS NET, Moçambique regarding available data on
crops and pricing movements in food markets, and general household vulnerability.
The second field trip was devoted to obtaining farmer inputs to the data collection process, which
required visits to individual farming communities and consultations with those farmers on their
challenges. Farming communities were visited in the following places:
 Marracuene;
 Lunane – Xai Xai;
 Chidenguele – Manjacza;
 Josina Machel – Inharreme;
 Hoyo Hoyo – Mabelane; and
 Island Josina Machele – Manhiça.
2.2. Climate analysis

18
A climate analysis evaluated the following:
 Historical trends in selected climate parameters across the three provinces and districts in which
PROSUL has projects;
 Projected trends of these same parameters based on regional circulation models (RCMs);
 The differences in the projected trends from historical trends, which is the indicated change in
the selected parameters;
 Mapping of these parameter differences; and
 The likely impacts of these changes on the 3 value chains.
2.3. Vulnerability mapping
Vulnerability mapping is required to spatially assess which value chains have a higher vulnerability to
climate hazards in particular areas than in others. The results will allow PROSUL to target particular
areas for investments that reduce specific climate vulnerabilities, and also help to avoid investments
that could be compromised by the effects of climate change.
Vulnerability is a state of being open to an injury or harm, which can have a variety of causes. These
include physical, social, economic and political factors. Sensitivity is the degree to which a hazard
affects something or someone. To be vulnerable is, therefore, to be both exposed to a hazard and to
be sensitive to that hazard.
People or systems are more sensitive to a stressor when they are affected by small changes in
exposures. Multiple underlying stresses can make an individual or a social-ecological system more
sensitive to exposure to a hazard than might normally be expected. For example, plants stressed by
a lack of soil moisture or high temperatures become more sensitive when exposed to disease
pathogens. Sensitivity can also have a time dimension, in which the degree of sensitivity varies
seasonally, annually or inter-annually, for example, sensitivity to drought.
Mapping experts and climate change experts mapped hazards in relation to the location of assets
(for example, the exposure of farmland to floods), and also mapped sensitivity to specific hazards.
Vulnerability maps are produced for each of the value chains by integrating the projected climate
changes, which includes spatial changes in rainfall and temperature, along with flood zones and the
sensitivity of biomass production in rangeland/grassland as a function of the quantity of rainfall in
the growing season. AHVRR / NDVI maps of rangeland cover are given in a later section as an
indicator of vegetation cover and the flood zone is developed as another set of vulnerability zoning
for flooding using observed data.
2.4. Multi-criteria decision analysis
Multi-criteria decision analysis (MCDA) is a useful tool for evaluating possible interventions when the
context is complex and there are many possible courses of action. The basic approach of MCDA is to
divide decisions into smaller, understandable parts, analyse each of these parts and then integrate
these parts into meaningful solutions.
We take this approach by looking at the key influences on each of the value chains - adaptations to
climate change should not be made in the absence of consideration of other necessary pressures on

19
each of the value chains. This MCDA tests the long list of adaptation options through a process of
discussion and assessment, rating each adaptation option based on a set of agreed-upon criteria (for
example, cost-effectiveness, cultural appropriateness, etc). Our evaluation is then based on a rating
of alternatives, considering the various evaluations, discussions, re-ratings of the various options and
then the establishment of decision options.
Ideally, the criteria should be decided upon with relevant national stakeholders so that the process
of arriving at recommended options is clear and those affected have had a part in developing the
solutions. The PROSUL team is taking part in validating the adaptation options and the outcomes of
this process may modify the rankings and outcomes in this report somewhat.
2.5. Introduction to the Climate Analysis
Mozambique is situated on the southeast coast of Africa between 10°S and 27°S. The majority of the
country is located in the inter-tropical zone which experiences a predominantly maritime climate.
The southern parts of Mozambique are characterized by distinct wet and dry seasons and
experience a high degree of inter-annual variability of precipitation, with a mean annual rainfall
ranging from 300 to 1000 mm/year. Figure 1 shows the annual total rainfall variability over southern
Mozambique. The east to west gradient of decreasing vegetation cover corresponds to the east to
west rainfall gradient of decreasing rainfall, along with an increasing coefficient of variation. The
driest areas lie in the western interior of Gaza province. Seasonally, the principle controls on
precipitation are the north/south migration of the inter-tropical convergence zone (ITCZ). The ITCZ
forms when the north-east airflow from the East Africa monsoon meets the south easterly trade
winds off the Indian Ocean. Heavy rainfall is caused both by tropical depression formation as well
the passage of tropical cyclones. The weather and climate features are modulated from year to year
by the main modes of natural tropical climate variability, namely the El Niño Southern Oscillation
(ENSO) (Gaughan, et.al. 2015). El Niño and La Niña events are natural variations in the climate
system and occur on average every 4-7 years, but ENSO and its impacts display significant variability
on decadal time scales (Power and Colman, 2006). The negative phase of ENSO, which is El Niño,
usually results in drier conditions over southern Mozambique (Manhique et al., 2011). Another
mode of variability that affects summer rainfall in the region is the subtropical South Indian Ocean
Dipole (IOD) (Reason, 2001). IOD consists of sea-surface temperature (SST) of opposite sign in the
Southwest and southeast India Ocean. When the SST is warm (cool) in the southwest Indian Ocean
and cool (warm) in the southeast Indian Ocean, increased (decreased) summer rainfall may occur
over the region (Reason, 2001).
Figure 2 illustrates typical variations of rainfall from the annual mean from 1981 to 2014. Annual
rainfall is calculated from July to June in order to represent the austral (southern hemisphere)
summer rainfall season. There is also high variability both among years with above normal rainfall
and among years with below normal rainfall. For example, in 1991/92, southern Africa including
Mozambique experienced one of the longest droughts which had extensive socio-economic impacts
(e.g. Vogel and Drummond 1993). And in 1999/2000 it experienced the worst flooding events in
many decades which left over 700 people dead and half a million homeless (Dyson and van Heerden,
2001). Figure 3 shows the annual mean temperature. The south of the country experiences a mean
temperature range of between 20-26°C.

20
Figure 1: Annual mean total precipitation for each grid cell for the period 1981-2014. Data taken
from the CHIRPS dataset. Units [mm]

21
Figure 2: Rainfall anomalies for each grid cell for rainfall data from 1981-2014. Data were taken
from the CHIRPS dataset. Units [mm]
This chapter provides a trend analysis of historical climate data and downscaled rainfall projections
over southern Mozambique. Projections of temperature change from the various sources discussed
(Section 2.7) do not show the range of variations of rainfall during the downscaling process,
especially as altitudinal changes across the study region are small. Temperature changes are taken as
is from the GCM ensembles. The historical trend analysis reviews the period 1981-2014, while
projections focus on the 2036-2065 period under a high level emission scenario (RCP 8.5). For the
historical analysis, we have used two observed gridded data sets, CRU TS (monthly temperature
statistics) and CHIRPS (daily rainfall) respectively. The results of this analysis of historical
temperature data show a clear warming trend. Both maximum and minimum temperatures were
warmer, on average in the decade of 2000s. An analysis of extreme climate indices suggests that
rainfall is becoming more intense, yet with longer dry-spell durations in between. There are also
indications of a later onset of the rainfall season and an earlier cessation of rain, reflecting an overall
shortening of the rainfall season. We have used dynamically downscaled data from the Coordinated
Downscaling Experiment (CORDEX) for developing the future climate projections. Under a high-
emission scenario (RCP8.5 – which is what the world is currently tracking), projections indicate that
towards mid-century (2036-2065), the number of rainfall events may increase. This is coupled with
longer dry spell periods, indicating that rainfall may become more concentrated and intense into the
future.
2.6. Recent climate trends (1981-2014)
Studies of recent historical changes in climate in Africa, including Mozambique, are hampered by the
availability of meteorological station data. Gridded products based on satellite derived precipitation
estimates or merged satellite data and station observations are an alternative, provided their
accuracy is well known. Due to these constraints in observational weather station data, rainfall and
temperature data from Climate Research Unit (CRU TS 3.21, Harris et al., 2014) and Climate Hazards
Group InfraRed Precipitation with Stations (CHIRPS, Peterson et al., 2013) are used to study the
historical changes. The CRU TS data is made up of monthly time series of various climate variables,
which include maximum and minimum temperature and rainfall. The data, which is based on over
4000 global weather stations, is available for the period 1901-2014 and is gridded to 0.5 x 0.5 degree
spatial resolution. The CHIRPS data, on the other hand, comprises daily rainfall data only. It is a
combination of satellite and weather station rainfall data and is available for the period 1981-2014,
gridded to 0.05 x 0.05 degree spatial resolution. Historical trends are calculated using linear
regression for each grid point for both CHIRPS and CRU datasets. The Mann-Kendall test was then
used to evaluate the statistical significance of trends at 95% confidence level. Statistical significance
implies that the result is unlikely to have occurred by chance. A lack of statistical significance does
not imply that changes have not occurred, but rather that they are most likely a result of
randomness rather than an underlying process.

22
2.6.1. Temperature
Figure 4 shows the difference between the mean (maximum and minimum) decadal (10 years)
temperature and the mean (maximum and minimum) temperature over the 1981 to 2012 period at
each grid cell from the CRU data set. Here one can clearly detect a warming signal, as all locations
were warmer, on average, in the 2000s than in the 1980s. However, it is also apparent that in some
locations more recent decades maximum temperatures have been cooler than preceding decades;
for example, Maputo province was cooler in the 1990s and 2000s than in the 1980s (Fig 4 a-c).
Maximum temperatures have increased by 0.2 °C and minimum temperature as increased by 0.2-
0.3°C in the 2000s over Inhambane and Gaza provinces. Tadross (2009), using station data across
Mozambique since 1960 to 2005 also found that temperatures have increased over most of the
country. Caution is required with the CRU data because in recent decades it does not have the
benefit of sufficiently dense ground station data with which to provide high confidence in accuracy.
Nevertheless, this is the best data available.
2.6.2. Rainfall
Rainfall related climate hazards are associated not just with seasonal mean rainfall, but also with
extreme weather events. It is, therefore, necessary to consider a number of different rainfall indices.
The World Meteorological Organization (WMO) Commission for Climatology and the Expert Team on
Climate Change Detection and Indices (ETCCDI) have developed a set of 27 indices based on daily
temperature and precipitation. Of these, the six indices that are based on daily precipitation are
used for the study of rainfall characteristics over the region. These indices or statistics are described
in Table 1.
Table 2: Definitions of the indices of precipitation extremes used
(Sourcehttp://etccdi.pacificclimate.org/list_27_indices.shtml)

23
Figure 5 shows the climatological rainfall onset and cessation month for the region based on CHIRPS
dataset. Onset and cessation are defined from anomalous rainfall accumulation in a given day
[A(day)] as:
( ) ∑ ( )
Where R(n) is the daily rainfall and Rs is the long-term (1981-2014) daily mean (Liebmann et al.,
2007). The calculations used 1 July as the starting date, which is, climatologically, the driest month.
The date on which this sum [A(day), or anomalous accumulation] is a minimum is the date of onset,
while the date of the maximum sum marks the rainy season withdrawal. This method is both
objective and defined locally - that is, based on the climate of the area of interest.
Over Maputo province, rainfall starts in November while over Gaza and Inhambane it starts in the
following month of December. The cessation of rainfall over Gaza and Inhambane is in February
while over Maputo it is in February and March. For the period of 1981-2014, rainfall onset has
shown an increase in days, i.e., starting late by 5-15 days per decade over southern Maputo and
parts of Inhambane province (Figure 6) (note – the values of 5-15 days per decade is the response
only for the period of data viewed and does not imply a stable trend). In most of Gaza province
rainfall onset has shown a decrease of about 10-25 days per decade, which means that there is a
trend towards an earlier start of rainfall season. Over most of Maputo and parts of Gaza the rainfall
onset has shown a trend toward an earlier cessation of about 10-25 days, which means that the
rainfall season is getting shorter. In other regions of southern Mozambique, there is a trend towards

24
a later cessation. Over southern Inhambane, rainfall cessation showed a trend of occurring earlier at
about of 20-38 days per decade over the relatively short record of the data.
Figure 7 shows decadal trends in rainfall indices (see table 1) over the period 1981 to 2014. Stippling
indicates grid points where trends are significant at the 95% level. Over much of the region, the
number of consecutive dry days (CDD) has shown an increase of about 20 to over 100 days per
decade, with significant trends along the coast of Inhambane. On the contrary, total annual
precipitation (PRCPTOT) shows an increasing trend from 20 to over 100 mm per decade over
Inhambane and most of Gaza. Over Maputo, PRCPTOT shows a southward decrease trend with more
than 100 mm per decade in the far south. The number of rain days with precipitation above 20 mm
(R20mm) follows the same pattern of PRCPTOT with increases and decreases of 5 days per decade.
In general, the annual total precipitation on very wet days (R95pTOT) and annual maximum five-day
precipitation (Rx5day) show an increasing trend over Inhambane and Gaza and decreasing trend
over much of Maputo. The same pattern of the trend is also found for rainfall intensity (SDII) with
significant later cessation trends in most of Inhambane. SDII is the Simple Day Intensity Index,
which is the ration of annual rainfall to the number of days during the year in which rainfall
occurred, or the average rainfall of rainy days.
2.6.3. Concluding remarks and summary findings of observed trends
 Maximum temperatures have increased by 0.2 °C over most of Inhambane and Gaza province in
the decade of 2000s, based on observations.
 Minimum temperatures have increased across the region, with Gaza province experiencing the
highest increase of 0.3-0.4°C.
 Projections suggest that maximum and minimum temperatures will continue to increase.
 Changes in rainfall are much harder to detect due to the spatial and temporal heterogeneity of
the rainfall pattern. However, results suggested that rainfall characteristics have changed in the
past. An overall increase in the number of Consecutive Dry Days (CDD) was observed across the
region. The pattern of changes in the wet indices is similar, with increases in Gaza and
Inhambane province and decreases in Maputo Province.
 The onset of the rainy season has shifted to later dates over southern Maputo and parts of
Inhambane Province, while in most of Gaza province it has started earlier, according to the data.
 Over Maputo Province, rainfall cessation has shifted to an earlier time, with both later onset and
earlier cessation suggesting a shortening of the rainfall season.

25
Figure 3: Annual mean temperature for each grid cell for the period 1981-2014. Data taken from
the CRU TS3.23 dataset. Units [Celsius].
Figure 4: Difference between decadal maximum mean temperature and maximum mean
temperatures for the entire period from 1981 to 2012 (a-c), decadal minimum mean temperatures
and minimum mean temperatures for the entire period from 1981 to 2012 (d-f). Data were taken
from CRU TS3.23 datasets. Units [degree Celsius].

26
Figure 5: Climatological rainfall onset month (a) and cessation month (b), averaged for the period
1981 to 2014. Based on data from the CHIRPS dataset.
Figure 6: Decadal mean annual rainfall onset (a) and cessation (b) trends for the period 1981 to
2014. Based on data from the CHIRPS dataset. Units [days/decade].

27
Figure 7: Decadal trends in precipitation indices (table 1) over the period 1981 to 2014. Indices
shown at the top left and units in the top right. Based on data from the CHIRPS dataset. Stippling
indicates regions where trends are significant at the 95% level.
2.7. Future climate
General Circulation Models (GCMs) are the primary source of information on possible changes to
large scale circulation patterns and, in the case of Atmosphere Ocean GCMs (AOGCMs),
corresponding changes in the global ocean systems. However, AOGCMs typically only resolve the
global atmosphere at scales of several hundreds of kilometres as computational constraints current
restrict the simulation of higher resolutions for the long simulation periods required for climate
change studies. As a result, dynamical downscaling models called Regional Circulation Models (RCM)
are sometimes used to simulate a small spatial domain at much finer resolutions (50km or finer).
The intent of dynamical downscaling is to resolve local scale climate features caused by topography,
land surface variations (eg. forests or lakes), coastlines, etc. as well as potentially better simulate
smaller scale weather events such as extreme convective rainfall events. Because they resolve finer
spatial scales, they often can simulate the local climate more accurately (compared with
observations) than GCMs and so could be considered more reliable or accurate. However, RCMs are
always driven by GCMs so any biases or errors present in the driving GCM will impact the
performance of the RCM. Also, even RCMs make many simplifications and cannot resolve the very
fine scales (such as cities) so suffer from many of the same limitations as GCMs. It is for this reason
that both GCM projections and downscaled RCM (or statistically downscaled) projections should be
considered when exploring future climate projections for a region. The GCM projections should be

28
used to inform our thinking about large scale regional changes while the RCMs may provide
information on more local scale responses in areas of complex topography, along coastlines, or with
regards to extreme events.
For the analyses of climate change projections over the region, data from two Regional Circulation
Models (RCMs, - COSMO-CLM and RCA4) from the Coordinated Regional Downscaling Experiment
(CORDEX) are used – the only data available at the time of the analysis. The two RCMs were each
used to downscale the output from four GCMs (MPI-ESM-LR, HadGEM2-ES, CNRM-CM5, and EC-
EARTH), resulting in an eight-member ensemble of downscaled climate projections over the study
region of southern Africa. All simulations were performed at a grid resolution of 0.44°x 0.44°, giving
grid spaces of approximately 50 km over the Africa domain. The RCM projections are forced by the
Representative Concentration Pathways (RCPs, Moss et al. (2010)). The RCPs are prescribed
greenhouse-gas concentration pathways (emission scenarios) throughout the 21st century,
corresponding to different radiative forcing stabilization levels by the year 2100. For this study the
RCP8.5 was used, which represents a high-level emission scenario and “business as usual” scenario.
RCP8.5 corresponds to a rising radiative forcing pathway leading to 8.5 W/m2 in year 2100,
equivalent to ~ 1370 parts per million (ppm) CO2 (Moss et al., 2010).
2.7.1. Temperature
Under the RCP 8.5 scenarios, global mean temperatures are projected to rise from 2.6°-4.8°C under
RCP8.5 by 2081- 2100, compared to the climate of 1986-2005. In the south-eastern part of Africa,
temperatures will also increase, but slower than the global mean, especially closer to the coast
(Niang et al., 2014). Inland and in the drier areas, temperatures are expected to increase faster than
the global mean. These projected results are robust, meaning that several different sources agree
on the sign and quantum of change, comparing with the 5th
Assessment Report (AR5) of the IPCC and
CORDEX (see for example Dosio and Panitz, 2016). Hot days and heat waves are projected to
become more frequent and cold days less frequent (IPCC, 2007). Niang et al. (2014) and Tadross
(2009), using statistical downscaling of 7 GCMs under the old special report on emission scenario A2
(SRES) “business as usual” found that minimum and maximum temperature are projected to
increase over the period 2046-2065 compared to 1960-2000. Mean temperatures are expected to
rise by 1.5-3 °C.
2.7.2. Rainfall
Global patterns of projected changes in rainfall are much less spatially uniform than projected
warming. Rainfall is generally projected to increase at high latitudes and near the equator and
decrease in regions of the sub-tropics, although regional changes may differ from this pattern (IPCC,
2007). Figure 8 shows the multi-model ensemble mean of projected changes in the climate indices
(see Table 1) under RCP8.5, at annual timescales for the period of 2036 to 2065 relative to 1976 to
2005. Changes that are not significant at the 5% significance level are indicated by stippling. As
reflected in the figure there is a projected increase in CDD over southern Mozambique of about 20%,
although not statistically significant. PRCPTOT is also projected to increase by 0-10% over most of
Inhambane and parts of Gaza.

29
On the contrary, rainfall is projected to decrease over Maputo and southern Inhambane and other
parts of Gaza. R20mm is projected to increase over most parts of southern Mozambique by about
10%. There is a general increase in the wet indices (R95pOTOT, Rx5day), with statistically significant
changes. These changes, which are accompanied by projected increases in SDII. The projections are
thus suggesting that in the future most of southern Mozambique may experience an increase in
overall intensity of heavy rainfall events with longer consecutive dry days (CDCD).
Figure 8: Projected multi-model mean changes (in %) in precipitation indices (table 1) for the
period from 2036 to 2065 under RCP8.5 emission scenario, relative to the reference period from
1976 to 2005. Stippling indicates grid points with changes that are not significant at the 95% level.
2.7.3. Concluding remarks and summary of findings of projected changes
 Temperature means are expected to rise about 2.6 – 4.8 °C and above over the longer term to
end-of-century in the inland areas – for example of Gaza Province, but at lower rates of 1.5 – 3.0
°C over the coastal regions.
 This means in the next 10-20 years, mean temperatures will rise ~ 0.5 – 1.0 °C, with an increase
over that time span of 5 – 10 more heatwaves at the end of the 20 year period.
 More hot days and hot nights will be experienced across the region.
 What this means at local levels are a greater number of temperature extremes, i.e. the
frequency of temperature anomalies (really hot days) will increase.
 Changes in the characteristics of rainfall are expected to continue into the future, with an
increase in rainfall extremes and increases of consecutive dry days over most parts of southern
Mozambique.

30
 The total annual change in rainfall is inconclusive from the modelling, but there will be more
consecutive dry days.
 There are no models available that will assist with the forecast on possible changes in cyclone
frequency and intensity.
 The likely climate changes with the most impact are temperature increases.
 A more detailed analysis of climate changes could have been undertaken if local meteorological
datasets from INAM had been made available to the study team.
3. Descriptions of the value chains
3.1. The red meat value chain
The key characteristics of the red meat value chain (which includes cattle, goats and sheep) in
southern Mozambique are:
 A cultural tendency to retain animals instead of developing a throughput of livestock and
revenue generation.
 Livestock lose condition during drought and high mortality rates from disease then result.
 Poor productivity and reduced off-take occur as a result of low access to services (veterinary,
breeding, communication, extension and credit).
 A lack of incentive to sell at poorly organised markets.
 There is a lack of pasture, especially in the months of August, September and October (before
the start of the rainy season), with very little supplementary feeding.
 Stocking densities are too high for sustainable pasture management and this is indicated by
substantial losses in vegetation cover during severe drought (see Section5 on the exposure and
sensitivity analysis using NDVI imagery to assess drought and human influence impacts).
 There is limited access to water, which increases animal stress and requires travelling long
distances between available grazing and water sources, with a resultant loss in animal condition.
 Floods, which restrict the movement of animals.
3.1.1. Value chain environment
Mozambique remains a net meat importer and as of 2014 (the latest data available), the country
imported US$ 600,000 of meat products from South Africa, from where it obtains most of its meat
import products (UNCTAD, 2016). The locally sourced animals are lower-value than those grown by
South African large-scale commercial operations, which can invest in access to good quality
feedstock, veterinary resources, feedlots, good pasture management and yield, and breeding
programmes that produce high-yields with fewer animals.
Within the study area, it is clear that the red meat value chain is not vertically integrated in any way,
in that there is no systematic chain from producers to the market. Farmers tend to sell on an ad hoc
basis according to needs and the infrastructure needed to cater for these sales and different stages
in the value chain is limited.

31
The primary areas of production have soils of low nutrient status, which results in low fertility and
less favourable pasture growth and exacerbated by overgrazing, results in poor quality pasture
forage as feed and reducing growth rates of livestock which graze on it. Markets and trading
channels are relatively limited; only a few animals a week (on average) are traded (in total, or within
a community) and the limited quantity coming onto the market limits access to markets by
producers because of the lower frequency of traders who need higher numbers for efficient
transport. This also limits incentives for commercialisation and investment. This situation creates a
relative isolation, which was exemplified by the observed conditions at Mabalane. There are also
gaps among value chain actors in the larger markets., that is, small producers are not making sales
into the higher-income urban centres, which are mostly supplied by imported meat from South
Africa (UNCTAD, 2016).
The situation at Mabelane is an example that is likely repeated elsewhere across the three
provinces, in various forms. The outlying village of Hoyo Hoyo lies at the end of a rugged unpaved
track 35kms north of the small town of Mabelane. While this area is near the Limpopo River, it is in
a low rainfall area, with thicket scrub – i.e. a dry eutrophic savannah – dense arid sand thicket and
woodland, dominated by multi-stemmed short trees, which serves as grazing and browse resource.
In areas of settlement, significant areas have been cleared of vegetation entirely, exposing large
amounts of soil (topsoils have long gone or are non-existent) to rainfall, leading to severe erosion
and sediment transfer along gullies. There is substantial evidence of high sediment loads in the
streamlines and high levels of overland flow from heavy rainfall. Travel and communications through
this land type are difficult and time-consuming because such roads are single tracks with no
construction features, except for a single culvert across a substantial gulley. Passage along this road
during a period of heavy rainfall is impossible, according to locals. Floods and droughts affect this
area; while crops are grown on the flood plain, pastures include the remainder of the scrub thicket
zone. The simultaneous failure of crops and livestock production is relatively frequent and the
community is vulnerable to climatic extremes.
In this community, animals are being sold as a result of the hunger induced by the 2015-2016
drought – household food stores were observed to be empty, with little prospect of new stores in
the short term. Cattle farming is not a business but more of a cultural activity and as a store of
wealth, however, the people would like it to be a business. Animal productivity in the area is low –
there is little pasturage – and some areas area completely overgrazed. Most (if not all) households
that own cattle also own goats – it would be unlikely to find a household which owned only goats.
While the farmers would rather sell cattle, households prefer to own cattle, goats less so.
Additionally, animal traction for ploughing is important for the cultivation along the banks of the
Limpopo River.
Pricing and market performance of animal sales is a source of tension within the community and its
relationship to stock traders. Interviewees noted that if a willingness to sell is displayed or evident,
the price that is offered per animal is driven down to about to 6000Mts per animal. At a cattle fair,
better prices can be achieved, roughly 10,000 – 12,000Mts. This does not pertain everywhere and
indicates the current crisis with which the community is faced. At the Island Josina Machele
community in Manhiça district, which is coastal and has a higher rainfall, lower temperatures and
more grazing potential, farmers would obtain about 18,000 to 20,000 Mts for an animal, depending

32
on size and weight before a scale was installed. Now, as a result of the scale presenting impartial
evidence to both seller and buyers, the farmers can obtain up to 32,000 Mts per head, according to
feedback from the community.
During the rainy season, there is a problem getting animals to the cattle fairs because the poor road
conditions and strongly flowing streams prevent movement. Animals are sold during seasons of poor
crop production as well as during productive seasons. The study site at Josina Machele provides a
useful example of other red meat-producing areas in the more coastal regions. Generally, the
community prefers to sell young bulls as the mode of sale. The biggest difficulties are the distance
to the market and not having water available for stock watering – meaning stock must be driven
from far (up to 18km one-way trek for water), with constant trekking from grazing to watering and
back again, which reduces livestock vigour. From Hoyo Hoyo to the next village is a cattle drive of
2hrs if a cattle fair is located there, to Mabelane it takes 20–30 hrs to get cattle there by hoof.
Various diseases of livestock abound, common symptoms include blood in urine, which possibly
indicates the presence of Babesiosis (redwater/ Texas cattle fever). Mortality of cattle increases
during times of stress, especially during drought. Animal mortality decreases with interventions
from animal health specialists. A new disease is apparently affecting cattle skins but can be treated
well if caught early. Grazing is affected by the excessive heat and there are few watering points in
the Mabelane area, which means much time must be spent moving animals between watering
points and grazing. The heat affects milk production, although these are not dairy cows (which
would be affected even more). As a result, milk production is very low. Milk on sale in shops is
imported from South Africa.
The focus in this area should be on production and yield. The introduction of new races/improved
stock will help with productivity. One option for increasing income from livestock farming is to use
more small stock – goats. These animals are the most important source of meat domestically and
can achieve 1500Mts per animal with traders. More frequent sales of smaller animals that are quite
tolerant of higher temperatures and relative poor pasture could increase income for the livestock
farmers.
Transport is, however, a big problem – cattle currently have to be driven to market 35kms away,
arriving in poor condition, having lacked water for the journey and resulting in lower prices. A
livestock scale has been installed at Mabelane but was not working at the time of the field visit,
caused by a mechanical problem. The abattoir here also does not have electricity and therefore
does not have carcass cooling and refrigeration facilities. Only a few animals are slaughtered at a
time because of the need to quickly move the stock before the carcass deteriorates in the hot and
humid conditions, which would result in a substantial loss to the farmer or owner of the carcass.
This lack of suitable infrastructure reduces the throughput of whatever rudimentary facilities do
exist and the result also reduces the abilities of the farmers to envisage a higher rate of animal
movement to markets and beyond.
Table 3: The red meat value chain components and primary actors
Value Chain Actors

33
Component (primary actors in bold)
Inputs Small-holder farmers: Few to none. Breeding is from own stock. Breeds
are indigenous but farmers are looking for better stock. Veterinary
pharmaceuticals must be purchased in Maputo 2-3 times a year, fewer in–
the more remote districts. Support services are very limited. Some
farmers are attempting hay production and storage for later use but are not
achieving sufficient compaction, required to preserve freshness and aroma
in the material by expelling most of the air.
Production Small-holder farmers: Farmers herd livestock – goats and cattle, and grow
out animals. Animal productivity is low – there are high loss rates from
disease and poor condition, a result of poor pasturage, over-stocking and
low-quality animals and relatively low levels of veterinary services. Animals
are small in stature. Numbers of animals per household are variable and
uncertain. Water stress is a common problem and there is no
infrastructure to water livestock. Trekking for water is a common problem,
with one-way trips of 10+kms and up to 18kms mentioned. Dip tanks
against tick-borne diseases are non-operational. Animal mortality increases
with animal stress (loss of quality grazing, water stress and outbreaks of
disease), but decreases with attention by animal health specialists. Heat
stress affects grazing quality as well as milk production, which is a small by-
product from cows that do not have a dairy function.
Sales Small-holder farmers, traders: Animals are largely sold when the stock
owner needs cash, sometimes in an emergency situation during low food
stocks or sudden cash needs. Goats are the primary red meat consumed
locally. Cattle, which must be driven to the local cattle fair over large
distances in some cases – e.g. 35kms which takes 20-30 hrs on a cattle
drive, therefore arrive in poor condition before the sale to traders. During
the rainy season, local roads become impassable to vehicles and sales are
not possible.
In Mabalane, cattle sold for 6,000Mts if the prices were depressed (forced
sales) but up to 10,000 – 12,000Mts if better prices could be achieved at a
cattle fair and higher if scales brought more precision to the bargaining
system and greater equity. In Manhiça District, animals sold for 18,000Mts
– 20,000Mts and up to 32,000Mts for since weighing scales were
introduced. Cash is banked in Manhiça but less so in Mabalane. Goats can
achieve 1,500Mts per animal with traders.
Meat production-
slaughter
Small-holder farmers, traders: Goats are mostly slaughtered locally for
choice by the stockholders or locally purchased and consumed. Cattle
slaughter takes place either in the few existing local abattoirs, which have
low standards of hygiene and no carcass cooling and refrigeration facilities,
or in Maputo where such facilities do exist. Transport conditions of animals
are poor and arrive at the Maputo slaughterhouses very thin, which
compromises meat quality. Where meat is inspected, diseased animals may
be destroyed and the owner loses the animal, and thus his investment.
Marketing Small-holder farmers, Traders: Little to none. Phone calls to traders
connect the livestock farmers to traders. Traders have their own market
links to meat sellers. Market performance is poor and demand for quality
meat is not met by supply.
Retail Traders: The retail selling of meat from these rural areas was not observed
in this study. However, often the traders or new owners of the animals

34
remove the carcasses from the slaughterhouse soon after processing for
sale into the markets, without rapid chilling and intensive air draught, ,
which is an unhygienic practice and leads to rapid loss of quality of the
meat. Inspection processes are also poor and do not necessarily prevent
these practices. Refrigeration facilities at abattoirs are generally rare.
Table 4: Climate influences on the red meat value chain.
Value Chain
Component
Climate and climate change influences
Inputs Poor rains reduce hay production, heat stress reduces grass and forage
productivity and quality.
Production Poor rains and heat stress reduce the quality and quantity of grazing, a lack
of grazing requires substantial movement of animals between watering and
feed sources. Water may be scarce and with high temperatures, animal
stress increases. Tick-borne disease outbreaks occur in the rainy season.
Consecutive abnormally wet seasons increase tick loads. High humidity and
temperatures boost tick activity and disease transmission (Bournez et al.,
2015).
Sales Getting animals to sales is difficult during the hot, dry season (water
scarcity) or when heavy rainfalls make the roads impassable for traders
buying and trucking animals away.
Meat production-
slaughter
Warmer conditions may exacerbate food safety if upgrades are not
concluded timeously.
Marketing None
Retail None
3.2. The horticultural value chain
The key characteristics related to the horticulture value chain in southern Mozambique are:
 A lack of access to water in the hot climate, as well as the poor state of irrigation schemes. The
infrastructure has been severely damaged in several large floods and canals also contain
substantial sediment loads, which reduce their efficiency;
 Low productivity – yields are low due to the lack of improved cultivars, poor production
practices, heavy weed loads, and high spoilage post-harvest;
 Poor water use efficiency by the Water Users’ Associations;
 The exposure of the horticultural value chain to flooding;
 Land degradation;
 Lack of access to improved seeds, inputs and mechanisation;
 High pest and disease load;
 High temperatures and precipitation result in pest and disease problems;
 Too much of the same product at the same time (tomatoes) – resulting in competing in the
markets and low prices within a limited period of harvest;

35
 Low levels of development of support services;
 Limited knowledge of horticultural techniques by smallholder famers;
 Poor quality and quantity of produce.
The horticultural value chains being considered in the PROSUL project area consist of small-holder
farmers producing small amounts of produce in a largely informal and traditional manner, with most
produce being consumed domestically and surplus sold into local or nearby markets for cash. They
are mostly located on the Limpopo River flood plain (and are therefore exposed to the hazards of
floods), on the Nkomati River floodplain in the southern parts nearer to the major markets, including
Maputo. Medium-scale and large-scale (commercial) farmers are not part of this analysis. The
horticultural producers have a variety of conditions under which production occurs; much of that in
the PROSUL project area of interest involves irrigation. Most of the horticultural farmers are
incorporated into Farming Associations and specifically for horticulture – Water User Associations.
Some farmers have plots close to the system of canals and diversions associated with the Lower
Limpopo Irrigation system, which is a substantial but dilapidated infrastructure remaining from the
Portuguese colonial period. The irrigation system improvements that need to take place include
cleaning channels and rehabilitating the irrigation system, removal of silt and the installation of
sluice gates. However, floods repeatedly damage the irrigation system. A progamme of irrigation
system rehabilitation in this study area is very expensive. In 1989 the state company doing these
repairs at this location vacated the area and has not returned. The question then is whether huge
expenditure on rehabilitation of the irrigation system is a wise investment? Improved wells and
boreholes are needed and required and in fact may be a cheaper option of obtaining water and
getting it to crops than the irrigation system – more resilient to floods and easier to maintain.
Elsewhere, water for fields is obtained from wells, which are generally 3+ to 5m deep but can be as
little as 0.3m, next to the field. Channels and water are close to the field edge but irrigation of crops
often cannot take place because there is no piping and getting the water from the channels onto the
fields, even over a short distance of a few metres, is very difficult. The people in some small farming
association do not even have hand-held watering cans. Local drainage systems are inadequate for
draining of water when rainfall is intense.
At the height of the drought, harvests are still possible although yields are low for people farming on
the flood plains. Farming remains possible because water is always close at hand just below the soil
surface in very shallow wells and available for the vegetable growers. With the low river levels, salt
intrusion from the ocean becomes problematical, however.
The critical climate issues in this area are the lack of rainfall and the strong, drying winds. The
climate in the last 2 years – build up to the 2015/2016 El Niño, apparently has been very difficult to
cope with, according to these people. There has been very little rain in the hot season (DJF). Crop
stress and the associated crop diseases have set in. New diseases that have never been seen before
are appearing. Prices rise in the market dramatically with the drought, moving from 250Mts to
450Mts per bushel, which benefits the farmers but the higher-end prices are not always achievable.

36
The local roads are very sandy and carry little traffic, making vehicular access difficult. Produce must
then be carried by individuals (on heads) to the main road (N1) five kilometres away for onward
shipment to Xai Xai. The difficulties for transport illustrated here are replicated widely elsewhere in
the region, at greater or smaller distances from major roads and commercial centres.
Temperature probably has a greater influence on crop productivity and quality than rainfall in the
horticultural area of the Limpopo and Nkomati river floodplains. When it is hot and rain occurs,
farmers can manage the diseases (the crop is not severely affected). However, when it is hot and
there has been no rain, the farmers cannot manage the diseases, likely because if the increased
plant stress leads to greater susceptibility to attack by pests. Pests include snails on young carrots,
rats, scale insects and white fly. Drought has a direct influence on disease and pest burden, which
increases during the drier weather. In December-January-February (DJF) – the price of cabbage
rises dramatically. During this hot season, crop yields decline substantially in quality and harvested
leaves quickly wilt. Generally, horticultural products are harvested and delivered during the hot
season through to the beginning of the fresh season, or winter – June-July-August (JJA). Seedlings in
January are sometimes lost to the high temperatures. Seedlings need to be planted in the shade and
irrigated in the afternoon and not in the morning.
The rainy season is expected to start in August but now seems to start in December. It would rain
substantially in the highland areas starting August and in November in the lowland vegetable
growing area. When heavy rains are expected, the farmers stop cropping. Heavy rains are not
expected in February. While heavy rains can do damage, they are preferred above dry periods
because it prevents salt water penetrating from the tidal Nkomati River system. Heavy rain also
“washes out the land” and is antagonistic to pests. In this area, the wind, which is too high in the
critical growth period, is a problem for crop production.
Numerous problems exist in production and sales. Access to seeds and transport are significant
issues for smallholders. Land preparation is done by using animal traction or tractors for ploughing,
animal traction is more expensive than tractors because they take longer to undertake the required
tasks even though their daily rate is lower, however both systems are costly to the smallholder. Soils
are very heavy – clay-rich vertisols, which makes cultivation difficult. Pest infestations reduced
yields, especially “leaf cutters”. The farmers battle constantly with reeds, which emerge from the
ground within two weeks of clearing and substantially reduce crop yields. There are low investment
and re-investment in the farming enterprise. There is little infrastructure to see.
Gender differences exist in the farming and processing of the product. Women undertake more
farming that allows them to sell in the local markets for cash and also work about 4-5 hours on the
farm (cultivating, weeding and harvesting), while men work for about 6 hours and spend most of the
time irrigating the crops (in some instances using watering cans) and the activity is very labour-
intensive.
The farmers presented madumbi/taro/cocoyams/Colocasia esculenta as a good option. It is well
accepted in the market, grows well in the flood plains when planted near water and survives
flooding very well. The only problem with madumbies is the formation of oxalic acids and raphides
in the corm. Fresh madumbies degrade quickly like cassava roots do. However, the populace, which
is skilled at dealing with the anti-nutritional factors and toxicity and short shelf life of cassava, can

37
quickly understand how to deal with the processing of madumbies. Okra was also noted as a good
product by the farming groups.
Table 5: The horticulture value chain components and primary actors
Value Chain
Component
Actors
(primary actors in bold)
Inputs Small-holder farmers: Primarily self-stored seed which is of relatively low
quality. Also seed purchases from companies where available -
government, Pannar and others. Access to good quality seed is a perennial
problem. Credit facilities are few to non-existent.
Preparation Small-holder farmers: Small-scale emergent farmers with rudimentary
tools and equipment on small farms/plots of 0.3 – 5ha. Additional labour is
contracted in where possible, animal traction or tractor-hauled land
preparation is undertaken where feasible and affordable. Weeding and
other tasks are undertaken manually. Labour availability is a constraint and
limits production because not enough land can be prepared in the
individual holdings. Male members of households may often be missing –
working elsewhere in the larger centres or possibly in other countries, eg
South Africa. Male farmers often also saw the responsibility of horticultural
activity as a role for females, while they focused on livestock.
Production Small-holder farmers: Those which are considered irrigation-driven are
mostly within the flood plain of the Limpopo River, working in small farming
associations but usually on their own plots. Crops grown include
tomatoes, cassava, maize, okra, green beans, cabbages, carrots, sweet
potato, potatoes, bananas, onions, small amounts of rice and madumbies
(taro/Colocasia esculenta/cocoyams), roughly in that order of production.
Okra is a crop of interest to the smallholders. Women sell most of the
Okra, along with carrots, green beans and tomato, into local markets. Okra
gets the best value in the market at 250 – 350Mts per bushel, is relatively
stress tolerant and has a longer production season and is a “favoured crop”
because of its relatively high productivity and capacity for income
generation.
Harvesting Small-holder farmers: Mostly/entirely by the owners of the small
farms/plots, using manual labour, contracting in extra labour where and
when available or needed.
Post-harvest and
processing
Small-holder farmers: Owner-driven but sometimes within farming
associations of a number of people as a means of sharing resources.
Extremely limited in scope with little value addition in terms of process or
storage. The products must be taken to the market and largely sold within
the day, especially where these concern leafy vegetables.
Marketing Small-holder farmers: Market development - little to none.
Retail Small-holder farmers: Selling into local open-air markets of small towns for
cash, or via local middlemen (mostly women) in these markets, or traded
for other food or cash crops. Most of the crops produced are for domestic
consumption or for cash needs by sale in these markets. Wheeled
transport of product is very limited and products are often carried by hand.
Lengthy walking times to markets leads to losses of quality. Product quality
is highly variable and non-uniform, reducing potential income. Buyers are

38
local people in the local markets of the small towns, often along the
roadside in which passing traffic offers value. Some of this produce does
reach the major centres such as Maputo, where it can be observed for sale
at the road side and in informal markets. In the shopping centres and
supermarkets, much of the green produce on sale is imported from South
Africa.
Table 6: Climate influences on the horticulture value chain.
Value Chain
Component
Climate and climate change influences
Inputs Seedlings may be compromised by excessive temperatures and water stress
Preparation Heavy rains may interfere with land preparation
Production High temperatures and low rainfall reduce yields substantially, through
plant-water stress and high diseases and pests burden. Low rainfall seasons
and prolonged droughts result in saltwater intrusion to shallow
groundwaters in coastal areas. The rainfall seasons starting later and
ending earlier (in some places) or later (in others) affects yield. High
windspeeds damage crops. Cyclones damage crops and infrastructure,
therefore the frequency of cyclones is of importance to resilience.
Harvesting Heavy rains in the late growth season and harvesting period damage the
crops
Post-harvest and
processing
High humidity and temperatures result in rapid spoilage of the products
and encourage a high pest burden.
Marketing None
Retail High temperatures result in quick loss of quality and therefore the value of
the products in the local markets.
3.3. The cassava value chain
The key characteristics of the cassava value chain in southern Mozambique are:
 Large distances from the main markets
 A highly competitive local environment with low prices obtained for the product, which is
labour intensive
 Climate influences yields and pest burdens - high temperatures and low moisture availability
reduced yields. High temperatures increase pest activity
 Has significant potential for post-harvest processing into ground flours which can be bagged and
hermetically sealed.
The primary cassava-producing areas in the PROSUL project study area are in Inhambane Province,
although cassava is widely grown across all provinces. The area is exposed to cyclones, which
destroy crops and houses. Rainfall is perceived to becoming more intense, but not necessarily

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