Domestic food production and hazard vulnerability jamaica

INTRODUCTION Jamaica is a small, open, commodity-export and tourism dependent economy Agriculture remains central to the Jamaican economy despite a declining contribution to GDP In 2010, agriculture accounted for 5.7% of Jamaica’s GDP Agriculture is the largest direct source of employment (22% of the workforce) 9 of the 14 parishes are over 70% rural [STATIN, 2004] 65% depend on agriculture as the major source of their livelihood

CONCEPTUAL FRAMEWORK Political –economy approach (theoretical standpoint) Vulnerability from the hazards perspective where: “ Vulnerability is a function of the external hazard or stress and the internal capacity to manage and cope with or adapt to stress” (Ziervogel et al, 2006) Combined with a livelihoods approach “ Assessment of individuals’ vulnerability through a livelihoods lens to incorporate its determinants (assets, capital and capabilities [Bebbington, 1999; Carney, 1998])” The concepts of vulnerability, food security and adaptation are established within the context of a livelihoods approach Global change and multiple stresses

‘ Double-Exposure’ Contextual Framework… Coined by O’Brien & Leichenko (2000) “ Double exposure refers to the fact that certain regions, sectors, ecosystems and social groups will be confronted both by the impacts of climate change, and by the consequences of globalization” Application to Jamaica

Multiple Stresses Contextual Framework… Global processes are not the only threat farmers face “ there is a need to develop a better understanding of the impact of multiple stresses on vulnerable groups based on local experiences, and to feed this into various policy arenas” Decisions made by farmers often occur within the context of multiple stresses According to Ziervogel et al (2006)

Climate change Climate change has altered natural hazards (?) Climate change as a slow-developing geophysical hazard Implication for Small Island Developing States (SIDS) Identical extreme events can have different impacts…why? Before we talk about vulnerability we must understand the ‘place’ Moving beyond the one-size fits all ideology

Jamaica Climate Change Projections Source: UNDP (2008)

IMPACTS OF HURRICANES AND DROUGHTS Office of Disaster Preparedness (disaster week), 1989

IMPACTS OF HURRICANES AND DROUGHTS Recent changes in extreme events such as hurricanes, droughts and floods Between 2002 and 2007 agricultural sector was affected by 12 extreme weather events; 7 hurricanes 2 spells of drought 3 extended periods of heavy rains Amounting to US$285.7 million in damage to the sector

IMPACTS OF HURRICANES AND DROUGHTS HOW RESILIENT ARE LOCAL FARMING SYSTEMS TO THESE EVENTS? WHAT ARE FARMERS DOING TO COPE WITH THESE EVENTS?

SOUTHERN ST. ELIZABETH 94% of the residents in St. Elizabeth are classified as rural dwellers (MOA, 2002) Majority of whom depend on agriculture as a source of livelihood St. Elizabeth is the bread basket of the country Southern St. Elizabeth is major source area for domestic food supply Environmental conditions marginal for agriculture low rainfall but good soils and topography

MARGINAL ENVIRONMENTAL CONDITIONS

COMMODIFICATION OF GUINEA GRASS Supplier: 30 x 1000 (10sq = 1acre) = $30 000 Cutter: $30 000 Transporters (< 1 miles): $1000 x 3 = $3000 Loaders: $1500 x 3 (at least 3 workers need) = $4500 Laborers: $1000 x 3 = $3000 Grand Total: $75 000 (US$800) Average farm size: 3 acres

Methodology Previous work in the area (June 2006), see McGregor et al, forthcoming Three reconnaissance trips were taken back into the area Two months of field work (June 15 to August 16, 2007) Survey of 282 farming households in four communities (Potsdam, Top Hill, Southfield and Flagaman) Detailed ethnographic work on Hurricane Dean (August 17 -29, 2007) Follow-up survey on Hurricane Dean and a Two weeks long rainfall event (September 21-29, 2007) Community No. of counted houses Sample at 10% confidence interval Potsdam 217 67 Top Hill 472 80 Southfield 316 58 Flagaman 461 77 TOTAL 282

Methodology … Participant Observation

Coping strategies of farmers Planting methods Moisture-loss reduction During droughts Recovery

Planting Methods Coping strategies… Planting crops that are resilient to dry conditions (scallion, beetroot, sweet potato, cassava) Plant a ‘quick’ crop Plant crops with multiple use Scale-down production during the dry season Avoid planting in the dry season

Moisture-loss reduction Coping strategies… Mulching ‘ Edging’ or perimeter planting (guinea grass, cassava, corn and gungu) Drip irrigation Timing the application of water

During droughts Coping strategies… Sacrifice a portion of crops under cultivation Share water Borrow water or money buy water Mulch thicker Spray crops with chemicals

Recovery Coping strategies… Cultivate on a smaller more manageable scale Seek off-farm employment Temporary exit from farming Reliance on livestock

CLIMATE CHANGE RISK PERCEPTION Risk perception is based on intuition, experience and emotions and is a function of hazards in context (Mitchell, 1999) Perceptions of climate change in the two areas are similar…but the impacts will be different Droughts are getting worse…more longer and more intense “ The difficulty with drought is you don’t know when it starts and you don’t know when it ends” Rainfall patterns increasingly unpredictable “ The days of relying on the old mariner’s poem to guide planting schedules (June-too soon, July-stand by, August-look out you must, September-remember, October-all over) has long gone” Less gentle ‘crop-friendly’ rainfall and more high-intensity rainfall events

(A) Mean monthly rainfall (mm) for Southfield, St. Elizabeth Parish, Jamaica. (B) Frequency of farmers’ perceptions of dry and rainy months (C) Frequency of farmers’ perceptions of the most severe dry month in terms of crop damage

Perceived environmental changes 65% of farmers -- Droughts are getting worse 67% of farmers --change in weather pattern Bush fires are more frequent Less “garden rains” and more “pond rains”

LIVELIHOOD VULNERABILITY INDEX Livelihood Vulnerability Index (LVI) approach is a relatively new approach to vulnerability assessment which uses primary household data to construct composite indices (Hahn et al, 2009) While the sustainable livelihoods approach addressed issues of sensitivity and adaptive capacity there is a need to develop a new approach for vulnerability assessment that “integrates climate exposure and accounts for household adaptation practices in order to comprehensively evaluate livelihood risk resulting from climate change” (Hahn et al, 2009) The LVI was first expressed as a composite index of seven major components ( socio-demographic profile, livelihood, health, social network, food, water and natural disaster and climate variability ) The LVI values were then aggregated into the IPCC’s vulnerability components (Exposure, Sensitivity and Adaptive capacity)

MAJOR COMPONENTS SUB-COMPONENTS EXPLANATION OF VARIABLE SOURCE Social networks Percentage of farmers who operate independently Computed by extracting farmers who indicated that they do not work with other farmers (operate independently) Author’s research Percentage of households lacking access to assistance from outside community Created by selecting and filtering households that do not receive assistance from outside the community Author’s research Percentage of households without any member in any community group or organization Computed by selecting and filtering household in which no member is a part of any community group or organization Author’s research Livelihood strategies Percentage of households in which no member has off-farm employment Computed by selecting and filtering farmers who indicated that no off-farm activity exist in their household Author’s research Average Agricultural Livelihood Diversification Index (range: 0.20–1) The inverse of (the number of agricultural livelihood activities +1) reported by a household. Diversification Index = 1/(n + 1) Hahn et al (2009) Percent of households dependent solely on agriculture as a source of income Created by filtering farmers who indicated that agriculture was their only source of income Hahn et al (2009) Income diversification index (range: 0–1) The inverse of number of alternative income generating activities (alternative income activities +1). Income diversification index = 1/(n + 1). Similar method used by Hahn et al(2009) to compute the Average Agricultural Livelihood Diversification Index Author’s research Socio-demographic Percentage of farmers above the mean age (52 years) Derived from the variable ‘Age’ and recoded to exclude farmers under the age of 52 years Author’s research Percentage female-headed household Variable was computed by filtering females who declared that they were heads of their households Hahn et al (2009) Percentage of household heads with no schooling Variable was computed by selecting heads of households who did not receive any formal education Hahn et al (2009) Percentage of households with > 4 children Created by extracting all the households with more than 4 children Author’s research Percent of households with more than 5 members Created by extracting all the households with more than 5 members Author’s research Water security Percentage households reporting water problem Derived from the number of farmers indicating that they face problems obtaining water for farm and household Author’s research Percentage of households that do not practice water harvesting Derived from the number of farmers indicating that they do not practice water harvesting Author’s research Percentage of households that buy water Derived from the number of farmers who are dependent on purchased water Author’s research Percentage of farmers primarily dependent on rainfall Derived from the total number of farmers who depend on the rainfall to cultivate crops Author’s research Food Percentage of households dependent on farm for food Computed from the number of farmers who indicated that they rely of their farm for food Author’s research Percentage of farmers having problems obtaining planting material Created from the number of farmers who have problems obtaining planting material Author’s research Average Crop Diversity Index (range: 0–1) Computed by inversing the number of crops grown by each farmer +1. Diversity Index = 1/(n + 1). Similar method used by Hahn (2009) to compute the Average Agricultural Livelihood Diversification Index Author’s research Natural disasters and climate variability Percentage of farmers with more than 4 production failures in the last 10 years Computed by averaging the number of ‘major’ crop failures experienced by farmers in the last 10 years (which is 4) and then filtering the number of farmers who fall above this threshold Author’s research Percentage of farmers reporting that they do not practice disaster mitigation Created by combining the number of farmers reporting that they do not do anything to mitigate the impacts of droughts and hurricanes Author’s research Percentage of farmers taking more than 6 months to restore production levels Computed by recoding the variable ‘recovery time’ to filter all farmers reporting that they take more than one year to restore production levels after crop failure to to a hurricane or a drought event Author’s research Percentage of farmers not receiving early warning information Derived from the number of farmers reporting a lack of disaster related information (warnings and updates) Author’s research Percentage of farmers who do not receive assistance from RADA Derived from the number of farmers who stated that they have never received assistance from RADA Author’s research Food imports Average number of crops not grown because of food imports Computed by averaging the number of crops not grown by farmers because of food imports (weighted according to the main cash crop in each community) Author’s research Percentage of farmers negatively affected by food imports Derived from the number of farmers in each community who indicated that they are negatively affected by food imports Author’s research Percentage of farmers who have lost market to food imports Derived from the number of farmers who indicated that food imports as the reason for them not having a market for their produce Author’s research Natural and physical assets Percentage of farmers not owning farmland Computed by recoding the variable ‘land tenure’ to filter all the farmers who indicated that they do not own their farmland Author’s research Number of farm plots (inverse) Created by inversing the number of plots owned by a farmer +1. Farm plot index = 1/(n + 1). Similar method used by Hahn et al (2009) to compute the Average Agricultural Livelihood Diversification Index Author’s research Percentage of farmers not having access to enough farmland Derived from the number of farmers reporting insufficient amount of farmland Author’s research Farm technology usage (inverse) Computed by summing (out of a total of 4) the number of farm technology items (hybrid seeds, synthetic fertilizer, agro-chemicals and drip irrigation) used by farmers Author’s research

LIVELIHOOD VULNERABILITY INDEX Very Low = 0-0.20 Low = 0.21-0.30 Moderate= 0.40-0.60 High= 0.60-0.80 Very High= 0.81-1

LIVELIHOOD VULNERABILITY INDEX Community Total Potsdam Top Hill Southfield Flagaman Vulnerability Very Low 1 4 6 4 15 6.7% 26.7% 40.0% 26.7% 100.0% Low 7 11 7 7 32 21.9% 34.4% 21.9% 21.9% 100.0% Moderate 24 38 21 41 124 19.4% 30.6% 16.9% 33.1% 100.0% High 26 25 20 19 90 28.9% 27.8% 22.2% 21.1% 100.0% Very High 9 2 4 6 21 42.9% 9.5% 19.0% 28.6% 100.0% Total 67 80 58 77 282 23.8% 28.4% 20.6% 27.3% 100.0%

The LVI-IPCC framework IPCC framework Major components Exposure Natural disaster and climate variability Food imports* Adaptive capacity Socio-demographic profile Livelihood strategies Social network Natural and physical assets* Sensitivity Water Food

The LVI-IPCC framework IPCC components Major components Potsdam Top Hill Southfield Flagaman Exposure Natural disaster and climate variability 0.64 (1) 0.54 (4) 0.61 (2) 0.56 (3) Food imports 0.59 (2) 0.54 (3) 0.60 (1) 0.54 (3) Adaptive capacity Socio-demographics 0.31 (1) 0.35 (4) 0.34 (3) 0.32 (2) Livelihood strategies 0.59 (4) 0.46 (1) 0.56 (3) 0.52 (2) Social network 0.61 (1) 0.78 (3) 0.64 (2) 0.81 (4) Natural and physical assets 0.28 (2) 0.30 (4) 0.29 (3) 0.26 (1) Sensitivity Water 0.60 (1) 0.53 (4) 0.58 (2) 0.55 (3) Food 0.46 (2) 0.45 (3) 0.46 (2) 0.50 (1) LVI Score 0.510 0.494 0.510 0.508 IPCC components Potsdam Top Hill Southfield Flagaman Exposure 0.62 (1) 0.54 (4) 0.61 (2) 0.55 (3) Adaptive capacity 0.46 (2) 0.47 (2) 0.45 (1) 0.48 (3) Sensitivity 0.53 (2) 0.49 (4) 0.52 (3) 0.54 (1) LVI-IPCC framework [(Exposure – Adaptive capacity ) x Sensitivity] 0.09 (1) 0.03 (4) 0.08 (2) 0.04 (3)

Conclusions Farmers in St. Elizabeth Parish are keenly aware of annual rainfall patterns and have adapted their agricultural practices to take advantage of natural moisture surpluses The somewhat marginal environment for agriculture in this area means that farmers are particularly sensitive to changes in weather and climate, with many expressing concerns about an increase in drought The perception that droughts are worse now than in the past underscores farmers’ feelings of increased vulnerability to changes in their local environmental setting Beyond climate conditions, socioeconomic factors might serve to increase the sense of insecurity among farmers and thus amplify the impacts of environmental change It is clear from the record of interviews that smallholder farmers need help to adapt to changes in rainfall patterns.

Domestic food production and hazard vulnerability jamaica

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Domestic food production and hazard vulnerability jamaica