World Development Vol. 38, No. 9, pp. 1241–1250, 2010� 2010 Elsevier Ltd. All rights reserved.

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Do Forests Help Rural Households Adapt to Climate

Variability? Evidence from Southern Malawi

MONICA FISHERInternational Food Policy Research Institute – Lilongwe, Malawi

MOUSHUMI CHAUDHURYUnited Nations Development Program, Environment and Energy Group, NY, USA

and

BRENT MCCUSKER *

West Virginia University, Morgantown, WV, USA

Summary. — Data from rural Malawi are used to assess the role of forests in rural household adaptation to climate variability, and toexamine implications for adaptation to future climate change. Although forests do not currently play a role in anticipatory adaptation byrural households, they do appear important for reactive coping: providing food during shortages, and a source of cash for coping withweather-related crop failure. We find households most reliant on forests have low income per person, are located close to forest, and areheaded by individuals who are older, more risk averse, and less educated than their cohorts.� 2010 Elsevier Ltd. All rights reserved.

Key words — climate variability, climate change, adaptation, forests, poverty, Malawi

* Colleagues Ed Carr, James Chimphamba, and Joseph Hodge deserve

many thanks for their collaboration during the Malawi fieldwork. We

thank Duncan Chikwita, Ealubie Chikwita, the late Frank Mwazangati,

Veronica Phiri, Chimwemwe Phiri, the late Sydney Nasambo, Phillip

Kunjirima, Carolyn Malekwa, Madalitso Mafungwa, and Tieferanji Phiri

for excellent survey research assistance. Many thanks are due to our res-

pondents at the study sites. Bruno Locatelli and Gerald Shively provided

valuable comments on an earlier version of the paper. This research was

made possible by support provided by the National Science Foundation

under Grant No. 0721018, the Centre for International Forestry Research,

and the United States Agency for International Development Agreement

No. EDH-A-00-06-0003-00, awarded to the Assets and Market Access

Collaborative Research Support Program (AMA CRSP). All views, inte-

rpretations, recommendations, and conclusions expressed in this paper are

those of the authors and not necessarily those of the supporting or coll-

aborating institutions. Final revision accepted: February 8, 2010.

1. INTRODUCTION

Global climate change is an inequitable phenomenon. Con-sider sub-Saharan Africa: it accounts for only 2% of globalcarbon dioxide emissions, but is expected to suffer a dispro-portionately large share of the negative impacts of global cli-mate change (CDIAC cited in UNDP, 2007). Currently, theAfrican continent is warming at the rate of 0.05 �C per decade(Elasha et al., 2006), and the Intergovernmental Panel on Cli-mate Change (IPCC) predicts that the rate of increase in meantemperature will be 0.2–0.5 �C per decade by 2020. Risingtemperatures in Africa are expected to adversely affect biodi-versity, water supplies, and agricultural production, with sub-sequent negative consequences for an estimated 75–250million people (IPCC, 2007a).

The scientific consensus that climate change is alreadyoccurring and will continue into the future makes it imperativeto understand the adaptive capacity of the rural poor. Adap-tation is defined herein as adjustment in response to actualor expected climatic stimuli in order to minimize harm to nat-ural and human systems (IPCC, 2007b). Adjustment can alsobe made to exploit beneficial opportunities related to climaticstimuli. Rural people in Africa are particularly vulnerable toclimatic variations due to widespread poverty, poor healthand education, food insecurity, lack of technology and infra-structure, and limited access to credit opportunities(Nangoma, 2007). 1 More optimistically, African farm house-holds have historically coped with climate variability by sellingphysical assets, planting different crop varieties, migrating foremployment, and diversifying into non-farm activities(Maddison, 2006; McLeman & Smit, 2006; Thomas, Twyman,Henny, & Hewitson, 2007).

The study of adaptation to climate change presents a clearchallenge. If the effects of global climate change have not yet

1241

been experienced or are just beginning to be felt, it is difficultto gain insight into the potential for human adaptation, whichis necessary for policy makers to plan for expected societalchanges. Much of the literature on adaptation draws on thepast 50+ years of studies on how people have responded toprevious natural disasters. Researchers predict how ruralhouseholds might adapt to future climate change, based onhow they changed their behaviors when confronted with pastclimatic events. The current study follows this analytical ap-proach.

This paper focuses on the potential role of forests in adap-tation of rural households to climate variability. Previous re-search suggests that households at tropical forest marginsrely on forest resources to cope with climate events (Eriksen,Brown, & Kelly, 2005), but we are aware of only two pub-lished studies that are quantitatively rigorous (McSweeney,

1242 WORLD DEVELOPMENT

2004; Takasaki, Barham, & Coomes, 2004). Therefore, weexamine how rural households in Malawi currently cope withclimatic variability, assess the role of forests in the adaptationstrategies, and consider the potential role of forests in long-term adaptation. Specifically, data from a 2008 rural house-hold survey (n = 200) are used to investigate (a) the degreeto which households engage in forest activities as an ex anteresponse to climate variability, (b) whether households copewith weather-related crop damages by increasing their relianceon natural forests, and (c) the characteristics of householdsmost reliant on forests for adapting to climate variability.

The paper begins with a literature review of adaptationstrategies used by farmers in sub-Saharan Africa. The next sec-tion provides background on climate and forest conditions inMalawi. This is followed by a description of the householdsurvey and study data. We then turn to the empirical analysesto examine whether rural Malawians rely on forests to copewith climate variation. Statistical results indicate that forestsdo not currently play a role in anticipatory adaptation. How-ever, forests do appear to be important for reactive adaptationamong rural households, providing food in times of foodshortage, and a source of cash for coping with weather-relatedcrop failure. We find that households most reliant on forestsfor reactive coping have low income per person, are locatedclose to forest, and are headed by individuals who are older,more risk averse, and less educated than their cohorts. Theseresults are discussed in terms of their implications for design-ing policies to improve Malawi’s adaptive capacity.

2. ADAPTATION TO CLIMATE VARIABILITY ANDCHANGE IN SUB-SAHARAN AFRICA

This section draws on climate change adaptation and natu-ral hazards literatures to describe some key ways Africanfarmers have responded to extreme weather events. Thesestrategies are generally categorized as anticipatory or reactiveadaptation (Smith, 1997). Anticipatory adaptation involvesadvance preparation for the consequences of change; reactiveadaptation involves coping with the effects of change after anatural disaster or once gradual climatic changes have startedto have significant impacts. The distinction between anticipa-tory and reactive adaptation may be blurred, since an anticipa-tory strategy may also be a reactive one. For example, incomediversification, migration, and selling of assets can be viewedas both anticipatory and reactive strategies to a drought orflood. The current study categorizes anticipatory and reactiveadaptation in the same way that adaptation strategies are gen-erally referred to in the literature.

The current study and the literature reviewed herein empha-size adaptation to climatic stimuli. However, rural householdsin low-income countries must simultaneously respond to amuch broader range of factors, including environmental, soci-etal, political, and economic impacts (Leichenko & O’Brien,2008; Reid & Vogel, 2006). Therefore, it is difficult to deter-mine the degree to which a single stressor, such as climatechange, impacts behavior.

(a) Adaptation strategies in agriculture

Adoption of new technologies and other changes in agricul-tural practices are anticipatory adaptation strategies that havelong been used by African farmers. Crop diversification hashelped insure against effects of rainfall variability, as differentcrops are affected differently by climatic events (Adger, Huq,Brown, Conway, & Hulme, 2003). The planting of drought

resistant crops is another common adaptation strategy. Insome parts of Eastern and Southern Africa, for example, theplanting of new varieties of pigeon peas, which are relativelydrought tolerant, may gain importance in the future, as thesevarieties survive when crops like maize fail (Kandji & Verchot,2007). High yielding varieties of maize are used in many Afri-can countries, including Malawi, primarily to supply more cal-ories per unit area, but also because the seeds are relativelydrought resistant and mature faster than indigenous varieties(ICRISAT, 2004; Thomas et al., 2007). Farmers in South Afri-ca have increased the space between plants, due to the fall inmoisture levels, and have drawn on social networks to accessalternate water sources on land beyond their village (Thomaset al., 2007). In Zambia, farmers have adopted minimum-till-age methods that trap moisture, improve soil quality, and min-imize soil erosion, resulting in a 10-fold yield increase anddecreased dependency on rain (Oxfam, 2006).

(b) Adaptation strategies involving water use and storage

Water collection and storage are important strategies foradapting to drought in Africa. Farmers in Kenya use trashlines, stone bunds, Fanya Juu, and log lines for rainwater har-vesting (Tengberg, Ellis-Jones, Kiome, & Socking, 1998), 2 andalso catch run-off in small dams or waterholes. A drawback isthese techniques are extremely labor and energy intensive, andlabor constraints or off-farm employment opportunities maypreclude their application. Uncertain land tenure and low agri-cultural prices also deter the use of these techniques (Kandji &Verchot, 2007).

Irrigation technology plays an important role in mitigatingthe effects of drought. In semi-arid parts of Tanzania, farmershave traditionally used Ndiva, a small-scale water system, andaccess to Ndiva is based on membership in water users’ associ-ations. However, the effects of Ndiva use are difficult to deter-mine, because farmers who use this technology tend to havebetter farm management, stronger social networks, and im-proved access to information, and are thereby generally betterprepared for drought (Enfors & Gordon, 2008).

(c) Income diversification as an adaptive strategy

Income diversification is an adaptation strategy that can beboth anticipatory and reactive. Farmers may search for off-farm income sources to reduce the impact of anticipated cli-mate variability and change. During the 1984 drought inBurkina Faso, for example, hunger incidence was higher inthe less drought-prone Mossi Plateau than in the northernSahelian zone, because households in the latter area diversifiedtheir incomes as an adaptation to drought (Barrett, Reardon,& Webb, 2001). On the other hand, various development orga-nizations are helping African farmers diversify their incomesas a reactive strategy. For example, micro-credit programshelped women in a drought-stricken area of Mali learn tomake soap and energy-efficient stoves, so that they were lessreliant on the sale of valuable assets to cope with the drought(UN/ISDR, 2008).

(d) Finance and insurance as adaptive strategies

As an anticipatory strategy, smallholders may participate ingroup weather-insurance that provides financial protectionwhen natural disasters result in crop failure. In 2005, Malawibecame the first African country to combine the use of weath-er-insurance and micro-finance schemes. Micro-finance helpedfarmers purchase high yielding groundnut seeds that would

DO FORESTS HELP RURAL HOUSEHOLDS ADAPT TO CLIMATE VARIABILITY? EVIDENCE FROM SOUTHERN MALAWI 1243

otherwise have been unaffordable. Some farmers took outloans that included weather insurance, which entitled themto receive benefits when rainfall fell below a specified thresh-old, regardless of actual losses (Hess & Syroka, 2005). If adrought occurred, the farmers paid a fraction of the loandue; the rest was paid by the insurer (Linnerooth-Bayer &Mechler, 2006).

(e) Migration as an adaptive strategy

Migration can be an anticipatory or reactive strategy, and ismost accessible to people with high human capital, and withaccess to social networks and services in the intended migra-tion destination (McLeman & Smit, 2006). People in theSudan, Kenya, and various parts of the Sahel migrated priorto or after a drought, in search of employment in areas less af-fected by drought (Eriksen et al., 2005; McLeman & Smit,2006). Similarly, five million people from Burkina Faso andMali have migrated to the Ivory Coast since the 1960s insearch of natural resources and employment (Toulmin,2005). Over 100,000 people from flood-prone areas of Mozam-bique relocated to new locations in 2000, after a massive flood(Pat & Schroter, 2008). Although migration and relocation arecommon adaptations to climate variability, these strategiescan lead to a loss of cultural and social security, and increasedland conflicts in host countries. Cross-country migration maybecome less feasible in the future, as countries respond toincreasing conflicts by tightening their borders.

(f) Sale of assets as an adaptive strategy

The sale of assets, particularly livestock, is commonly em-ployed in Africa as an anticipatory or a reactive strategy to re-duce the impact of weather shocks. During the drought of thelate 1990s in Ethiopia, for example, farmers sold their oxen tobuy food (Carter, Little, Mogues, & Negatu, 2004). Whilehelpful in the short-term, the sale of these valuable animals,which are used to till the land, reduced the ability of ruralEthiopians to cope with future droughts. The sale of cattlewas also an important mechanism for coping with droughtin Zimbabwe (Kinsey, Burger, & Gunning, 1998). In the lattercase, however, the sale of cattle was associated with accumu-lation of livestock wealth as an anticipatory adaptation, be-cause the value of cattle for weathering drought providedthe incentive to build up the cattle herd.

(g) Use of forest resources as an adaptive strategy

Forest resources, such as non-timber forest products(NTFPs), have long served as safety nets or “natural insur-ance” to help cope with environmental and economic shocks(Angelsen & Wunder, 2003; Shively, 1997), 3 and are animportant part of livelihood strategies in southern Africa(Cavendish, 2000; Paumgarten, 2005; Shackleton & Shackleton,2004). Households utilize forest resources in their daily liveli-hood activities (e.g., wood for fuel consumption and/or ex-change) or as a coping strategy in extreme events (e.g., foodsduring famine).

There are several reasons why low-income households resid-ing at forest margins turn to forests in the face of misfortune.First, forests are often held under state or communal tenure,with their resources freely available to local populations, dueto government failure to enforce property rights or to weak-ened traditional regulation of resource-use (Baland &Platteau, 1996). Second, extracting forest resources generallyrequires limited levels of financial, physical, or human capital

(Neumann & Hirsch, 2000). Third, diverse forest products areoften available at times when other income sources are not, forexample, when crops fail (Byron & Arnold, 1999; Pattanayak& Sills, 2001). Thus, when misfortunes such as weather eventsstrike, forests “can make the difference between good and badnutrition, between recovered health and prolonged illness, orbetween food security and starvation” (Angelsen & Wunder,2003, p. 23).

Previous studies have shown that rural households and gov-ernments use forests to prepare for and mitigate the impactsof climate variability. In Senegal, which has been struck by suc-cessive droughts since the 1970s, people practice agroforestry,using trees as windbreaks that help protect soils, create microcli-mates for a variety of crops, and reduce desertification (Oxfam,2006). In drought-prone areas of northeastern Nigeria, farmersactively protect trees on farms and in forests to manage biodi-versity and reduce desertification (Mortimore & Adams,2001). As part of the National Action Plan for Adaptation,the government of Burkina Faso has initiated large-scale refor-estation programs, planting fast growing, drought tolerant treesto reduce the impacts of desertification (Kalame, Nkem, Idin-oba, & Kanninen, 2009). In Kenya and Tanzania, six out of16 strategies for dealing with drought involved the use of indig-enous plant species found in forests (Eriksen et al., 2005). Forestgathering was also an important strategy for coping with covar-iate flood shocks in Peru, particularly in households with fewphysical assets and more adult members (Takasaki et al.,2004). In rural Honduras, young households with few liquid as-sets were found to sell forest products when crops failed due tonatural disaster (McSweeney, 2004).

3. STUDY CONTEXT

(a) Climate variability in Malawi

Malawi provides a useful setting for studying householdadaptation to climate variability. The climate is highly vari-able: 40 weather-related disasters occurred during 1970–2006, including 16 drought or flood events after 1990 (Action-Aid, 2006). These weather events resulted in chronic foodshortages, greater poverty, and deterioration in health condi-tions (Nangoma, 2007). For example, flooding in 2001–02led to famine and an estimated 1000 deaths, and a droughtin 2005 caused food shortages for more than 4.7 million ofthe 13 million people in Malawi (Devereux, 2006).

Malawi’s mean annual temperature increased by 0.9 �CDuring 1960–2006 (McSweeney, New, & Lizcano, 2008), anda 1.1–3.0 �C increase in mean annual temperature is forecastby 2060 (McSweeney et al., 2008). Increased temperature is of-ten correlated with changes in precipitation; however, rainfalltrends are difficult to detect in Malawi, due to the strong influ-ence of the El Nino Southern Oscillation. The only statisticallysignificant change in rainfall during 1960–2006 was a 5.8 mmper decade decline during December, January, and February,the middle of the November to March/April agricultural sea-son; but this is almost irrelevant given that average monthlyrainfall is 217 mm for these months (McSweeney et al.,2008). Although the amount of rain on days with extremerainfall has increased, the number of days with heavy rainfallhas decreased (McSweeney et al., 2008). Model projections forfuture changes in annual rainfall vary widely, including bothpositive and negative changes, but models that assume rela-tively high carbon emissions consistently predict increases inthe proportion of rainfall that falls during extreme rain events(McSweeney et al., 2008).

1244 WORLD DEVELOPMENT

Together, rising temperature and declining rainfall wouldadversely affect about 90% of Malawi’s smallholder farmers,who depend on rain to grow crops, including the staple, maize(UNDP, 2007). The impact of future climate variability andchange in Malawi will depend partly on the adaptive abilityof rural households. Like other African countries, Malawi isvulnerable to climate change, because (a) the country is al-ready drought prone (Devereux, 2006), (b) rain-fed agriculturecontributes about 40% of gross domestic product, and (c) thecountry is very poor, with three-fifths of the population livingbelow the poverty line (Mukherjee & Benson, 2003). Further-more, technologies for coping with climate variability, such asearly warning systems and irrigation, are limited; access toinformation and the population’s ability to process that infor-mation is low; and political, social, and economic institutionsare weak (Nangoma, 2007).

(b) Malawi’s forests and forest management

Malawi’s forests are dominated by closed, deciduous wood-land known colloquially as miombo, which are the most com-mon vegetation type in central, southern, and eastern Africa(Campbell, Frost, & Byron, 1996). Miombo provides a widerange of products and services that are essential to rural com-munities (Cavendish, 2000; Dewees, 1994; Fisher, 2004). How-ever, Malawi is losing forest cover at a rate of 2.4% per year,which is likely to reduce the usefulness of forest resources as astrategy for adapting to effects of climate variability (FAO,2001 cited in UNEP, 2002).

The primary threat to Malawi’s forests is clearing for agri-cultural expansion (GOM, 1998a). Smallholder farmers oftenhave to clear forest land to grow sufficient food, and in manycommunities, open access to land is customary, due to theweakening of traditional controls over land allocation(GOM, 1998a; Place & Otsuka, 1997). 4 Intensive extractionof wood is another threat to Malawi’s forests; approximately90% of the country’s total energy needs is provided by biomass(GOM, 1998a). Moreover, the productivity of miombo wood-lands is generally low, and at current levels of demand, woodharvest rates far exceed sustainable yield. The estimated deficitfor woodfuels rose from 1.6 to 4.9 million cubic meters During1983–90 (GOM, 1998b).

Forests in Malawi have not yet been utilized as a resourcefor reducing the impact of extreme weather events. Vision

Table 1. Selected characte

Attribute Village 1 Village 2

Populationestimate

1,439 2,357

Main livelihoodactivities

Agriculture, forestguard, sawyer, beer

brewing, agriculturalcontract labor

Agriculture, foguard, tour guide,

transporter, bbrewing, agricul

contract laboMarket access 3 km to trading center;

13 km to town0.5 km to trading

10 km to towMain source offorest resources

Mulanje Mountain Forest Reserve (MMFR) coveand pine plantations. The forest has been

Distance toMMFR

0.25 km 0.25 km

Forestmanagement

There are Forestry Department regulations regacharcoal burning, felling t

Mulanje Mountain Conservation Trust (MMCT),Mountain Forest currently being implemented at s

local people to create/maint

2020, a long-term government plan that promotes sustainabledevelopment and public awareness about climate change is-sues, does not mention the role of forests. Tree plantingschemes to combat deforestation and protect forest resourcesduring extreme weather events have not yet been integratedinto the government’s adaptation strategies (ActionAid,2006). Although the National Adaptation Plan of Action(NAPA) of 2006 contains some forestry activities, such asafforestation and reforestation programs to control siltation,it largely ignores the role of forests in minimizing the impactof droughts and floods. Finally, Malawi’s forest conserva-tion policies, such as the National Forest Policy of 1996and the National Forestry Program of 2001, do not link for-ests with adaptation to climate change (Kambewa & Utila,2008).

4. FIELD SITES AND DATA

Data for the present study come from a household surveycompleted in four rural villages in Mulanje District, Malawi,between January and December, 2008. The sample villageswere chosen to represent a range of household livelihoodsand of access to forests and markets (Table 1). In each village,a simple random sample of 50 households was selected forinterviews, providing an overall sample size of 200 house-holds. 5

A male–female enumerator team was based in each of thefour villages, and spent six months in 2008 interviewing resi-dents of the sample households. The collection of high qualitydata was insured by close supervision of enumerators by twoof the authors, interviews with groups of household residentsto obtain more complete information, and separate interviewswith women and men, when this was judged to be conducive todisclosure of sensitive data. Household information includeddemographics, income (collected quarterly to reduce the recallperiod), expenditures, wealth holdings, food security, agricul-tural production, risk attitudes, forest use, adaptation strate-gies, and perceptions of climate variability.

The main source of forest products in the study villages isthe Mulanje Mountain Forest Reserve (MMFR, Table 1),which includes miombo woodland at its base, afro-montaneforest near its summit, and pine and eucalyptus plantationsat various locations. The MMFR has been managed for

ristics of study villages

Village 3 Village 4

472 443

restplank

eerturalr

Agriculture, sawyer, beerbrewing, agricultural

contract labor

Agriculture, charcoalmarketing, tea estate

employment

center;n

1 km to bi-weeklymarket; 15 km to town

3 km to town

ring 640 km2 comprising miombo woodland and afro-montane forest,heavily degraded particularly at locations proximate to villages

4 km 0.5 km

rding extraction of specific products (e.g., firewood has headload fee;imber without permit, hunting are prohibited)a GEF project recently established. Forest co-management of Mulanjeelected sites. MMCT has increased number of forest patrols and hiredain firebreaks and hiking trails on the mountain

DO FORESTS HELP RURAL HOUSEHOLDS ADAPT TO CLIMATE VARIABILITY? EVIDENCE FROM SOUTHERN MALAWI 1245

conservation purposes since 1927, initially by the colonial gov-ernment and by the Forestry Department since independencein 1964. The Mulanje Mountain Conservation Trust, a non-governmental organization, has played a supporting manage-ment role since around 2002. Recent regulations governingforest resources reflect the National Forestry Act of 1997.Some activities are strictly forbidden in the reserve: crop culti-vation, charcoal production (illegal in Malawi), and hunting.Other forest activities are allowed upon payment of a licensingfee to the Forestry Department: collection of head loads ofdead wood, grazing of animals, and felling/removal of trees(with controls on the species of trees, closed periods, andquantities). Collection of some NTFPs such as fruit, mush-rooms, wild vegetables, and caterpillars, is allowed free ofcharge. The Forestry Act outlines punishment for violationsof the rules, which includes fines, confiscation of collectedmaterials, and imprisonment. In practice, regulations concern-ing forest use are often circumvented or ignored altogether,although random enforcement does deter extensive overuse.

Forest activities that provided sources of income to the sam-ple villages during 2008 were classified as (a) forest employ-ment (forest guard, Forestry Department officer, mountainguide/porter, plank transporter, and sawyer), (b) extractionof NTFPs (firewood, bamboo, thatching grass, forest foods,traditional medicine, and wood crafts) for sale or home con-sumption, (c) timber marketing, and (d) charcoal sales. Therelative importance of specific forest activities differed duringthe agricultural and non-agricultural periods (Figure 1). Ratesof NTFP and charcoal extraction were relatively low duringthe agricultural period, due to increased demand for house-hold labor for farming activities. Another reason for relativelylow charcoal sales during the rainy agricultural period is thatkiln management is difficult in wet conditions. Demand forforest products also varies across seasons; for example, de-mand for bamboo for brick firing or home construction peaksin the non-agricultural period, when home construction/repairis common. Firewood demand for heating is relatively high inthe cold, non-agricultural months of June and July. In con-trast, timber extraction and forest employment did not showseasonal differences for several reasons. First, forest jobs, suchas forest officer or forest guard, are annual, rather than sea-sonal employment. Second, a number of household headsmoved temporarily to Northern Malawi during the agricul-tural period, when food and income were scarce, to work atsawmills or to engage in timber extraction/sales.

Figure 1. Forest-derived income, by season.

There are many local markets for forest products. Forestfoods are sold within villages. Firewood, bamboo baskets,and traditional medicines are sold in local weekly marketsand in nearby towns, such as Mulanje and Phalombe. Char-coal is in high demand, and many households informally re-ported selling it as far away as Blantyre (80 km). Localeconomic arrangements regarding the sale of charcoal andMulanje cedar were difficult to quantify since charcoal produc-tion is illegal in Malawi, and the collection of Mulanje cedar ishighly regulated.

5. ANALYSIS OF EMPIRICAL DATA

(a) Use of forests by rural households in Malawi for anticipatoryadaptation

The use of forests for income generation is common at thestudy sites: on average, forest income accounted for 30% of to-tal household income in 2008. 6 Only the agricultural incomeshare (35%) is greater. It is plausible that observed diversifica-tion of income through forest use partly represents anticipa-tory adaptation to climate variability, a hypothesis we nowinvestigate. To begin, Table 2 presents survey evidence onrural Malawians perceptions of how, if at all, climate is chang-ing. We examine whether Malawi meteorological data(McSweeney et al., 2008) agree well with farmers’ responsesto a series of questions about whether they had observedchanges in local climate over the past 10 years. 7

The strongest statistical evidence from Malawi meteorolog-ical data is that average temperatures are rising (McSweeneyet al., 2008). In the sample, the percentage of respondentswho believe temperatures in their village have risen, fallen,or remained unchanged in the last 10 years is 75%, 10%, and15%, respectively (see Table 2). Thus, the majority of re-sponses are in qualitative agreement with the temperaturedata. As for rainfall, Malawi rainfall data do not show statis-tically significant trends, as was discussed earlier. Respondentsreported the following observations for rainfall quantity dur-ing the rainy season over the last 10 years: rainfall has in-creased (34%), rainfall has declined (59%), and rainfall hasstayed roughly the same (6%). Thus, farmers’ perceptions ofrainfall trends do not agree well with the rainfall data. It islikely that responses were influenced by the 2007–08 rainy sea-son in which extremely heavy January rains caused fertilizerrunoff and crop damage and were followed by a Februarydry spell that resulted in additional crop damage. The 2008harvest was consequently a poor one. Some farmers blamethe poor harvest on the heavy January rains; others blamethe February dry spell.

Table 2. Farmers’ perceptions of climate variability and change

Variable Proportion 95% Conf. interval

Average temperature during the rainy season over the past 10 years

has _____Increased 0.75 [0.68, 0.81]Decreased 0.10 [0.06, 0.15]Not changed 0.15 [0.10, 0.20]

Average rainfall during the rainy season over the past 10 years

has _____Increased 0.34 [0.27, 0.41]Decreased 0.59 [0.52, 0.66]Not changed 0.06 [0.03, 0.09]

Table 3. Farmers’ reported adaptations to climate variability: anticipatoryand reactive

Variable Proportion 95% Conf.interval

Anticipatory adaptation mechanisms

Switch from local to hybrid maize 0.22 [0.16, 0.28]Crop diversification 0.09 [0.05, 0.13]Grow drought-resistant crops 0.08 [0.04, 0.12]Income diversification (non-forest) 0.06 [0.03, 0.09]Forest diversification 0.03 [0.003, 0.05]Other 0.08 [0.04, 0.11]

Reactive adaptation mechanisms

Search for contract work (ganyu) 0.57 [0.50, 0.64]Start up a small business 0.30 [0.24, 0.38]Forest product marketing 0.21 [0.15, 0.26]Assistance from family,friends, government

0.08 [0.04, 0.12]

Sell livestock 0.03 [0.003, 0.05]

Table 4. The importance of forest foods in times of famine

Variable Proportion 95% Conf. interval

Forest foods are ––—–– for surviving a famine

Very important 0.67 [0.60, 0.74]Important 0.20 [0.14, 0.26]Somewhat important 0.05 [0.02, 0.09]Not important 0.08 [0.04, 0.12]

Proportion of meals a week that are derived from

the forest ––—–––—–––—–

When food is plentiful (after harvest) 0.10 [0.08, 0.12]During a famine 0.57 [0.47, 0.68]Food that assists householdin surviving a famine isderived from forests

0.26 [0.19, 0.33]

1246 WORLD DEVELOPMENT

Considering that most respondents perceive changes in localclimate, a natural question is whether households have chan-ged their behaviors to prepare for climate variability. Respon-dents were, therefore, asked, “Has your household made anychanges in farming, livestock, forest, wage, or business activi-ties in anticipation of poor rainfall during the agricultural per-iod?” In the sample, 39% responded that changes had beenmade. Table 3 presents proportions and 95% confidence inter-vals for anticipatory adaptations reported by sample house-holders. Note that the sum of percentages exceeds 39%because some respondents provided more than one adaptationstrategy. The data seem to indicate that forest diversification isnot a current strategy for reducing ex ante the impacts of cli-mate variability: only 3% of households reported the use ofthis mechanism. The most common modifications made areto agricultural practice, with the dominant change being fromlocal to hybrid maize seed. This is not unexpected given thatmany smallholders say they want to be self-sufficient in maize,the staple crop, partly because of concerns about food marketunreliability during periods of calorie shortfall (Alwang &Siegel, 1999). Hybrid maize is an important option for adapt-ing to climate variability because it is early maturing and highyielding (ActionAid, 2006). A key impediment to the growingof hybrid maize is the need to apply fertilizer to achieve yieldgains over local maize. The latter constraint has been relaxedin recent years with the Malawi Government’s fertilizer cou-pon program in which poor farmers receive a coupon, whichin 2008 represented about a 90% subsidy on the price of fertil-izer.

(b) Do rural households in Malawi use forests for reactiveadaptation?

The evidence in the last section suggests that households atthe study sites do not use forests for anticipatory adaptation.In this section we investigate the role of forests in reactiveadaptation to climate and other risks. In addressing this ques-tion we begin with survey evidence on the importance of forestfoods in times of famine and then turn to regression analysisto study the role of forests as a source of earnings to cope withclimate variation.

(i) Reliance on forest foods to survive famine.Table 4 presents proportions and 95% confidence intervals

for three variables related to forest food consumption. 8 Find-

ings indicate that forest foods are used as substitutes for cropsduring poor weather events. In one survey question, respon-dents were asked the importance of forest foods for helpingtheir household survive a famine. Although famine is not al-ways the result of weather shocks, in Malawi all recent famineshave been related to drought or flood. As shown, the majorityof households (67%) reported that forests are very importantfor this purpose; only 8% of households stated that forestsare not important for weathering famine. The survey also re-corded the proportion of meals per week in which householdsconsume forest foods just after a good maize harvest (whenfood is abundant) and during a famine. Forest foods are farmore commonly consumed in a time of famine (57% of meals)than when food is abundant (10%). Finally, households wereasked what foods, if any, they consume only in times of fam-ine. Among the more common categories of reported foodsare those derived from forests, representing 26% of householdresponses. In particular, mpama a drought-resistant forest yamis very important for surviving famine at the study sites. It isconsumed mainly in times of famine, because local people gen-erally find it unpalatable and it is very time consuming to col-lect, as it grows deep underground.

(ii) Reliance on forests to cope with weather-related cropfailure.

The evidence described above indicates that forest foodshelp households to smooth consumption in the face of climatevariability. Forests may also indirectly assist households byoffering opportunities to earn cash to buy food. We askedhousehold heads how their household responds when toomuch or too little rainfall results in a poor maize harvest.Householders responded that to cope they engage in short-term contractual work either in their village or in anothervillage or city (57%); start a small business (30%); engage inforest product marketing or forest-based employment (21%);seek assistance from family, friends, or the government (8%);and sell livestock (3%). The sum of percentages exceeds 100because some householders reported more than one copingmechanism. As indicated by the confidence intervals ofTable 3, only short-term contract work is significantly moreimportant than forests for coping with weather-related cropfailure at the study sites.

(c) What are the characteristics of households most reliant onforests for adaptation?

A regression model is estimated in order to examine the fac-tors associated with use of forests for coping with weather-re-lated crop failure. The empirical model is a Probit regressionof the form

DO FORESTS HELP RURAL HOUSEHOLDS ADAPT TO CLIMATE VARIABILITY? EVIDENCE FROM SOUTHERN MALAWI 1247

F i ¼ a0 þ a1Ai þ a2Ri þX

j

bjHji þX

k

dkLki þX

l

dlDli þ ei:

Dependent variable F is a binary variable indicating whetherthe household reported the use of forests for shock coping.Household-level explanatory variables were chosen based onempirical studies of rural household forest reliance (Fisher &Shively, 2005; McSweeney, 2004; Takasaki et al., 2004) andare defined as follows: A is age of the household head; R isthe household head’s risk attitude as measured by a game ofchance following Schechter (2007); vector H includes two hu-man capital variables, a binary variable for whether the house-hold head has at least primary school education and a binaryvariable indicating the householder was in very good or excel-lent health during the study year; and L is a vector of fourvariables associated with living standards in Malawi: femaleheadship, income per capita, farm size per household resident,and goat ownership (Mukherjee & Benson, 2003; World Bank,1996). 9 In rural Africa, livestock acquisition remains a keyform of wealth accumulation (Dercon, 1998). Goats are a rel-atively liquid asset that can be sold in response to price signals,to smooth consumption, or to provide financial capital to starta business. Village-level variables are represented by D: dis-tance to the Mulanje Mountain Forest Reserve (MMFR)and distance to Forestry Department (FD) headquarters.The latter variable is a proxy for enforcement of ForestDepartment regulations, which forbid forest product market-ing.

Table 5 presents summary statistics for explanatory vari-ables and Probit model results. Calculation of standard errorsuses the Huber/White heteroskedasticity-consistent estimatorof variance, adjusted for within-cluster (village) correlationwith use of a village identifier variable. 10 Note that for binaryvariables, the marginal effects are interpreted as the percentagepoint change in the probability of using forests for shock cop-ing as a result of a discrete change in the explanatory variable.At the 0.05 significance level, seven of the point estimates areindividually significant.

Parameter estimates for the variables age and age squaredindicate that age of the householder is negatively correlatedwith use of forests for coping with climatic shocks until thehouseholder reaches the age of 58 years, at which point thecorrelation becomes positive. Young households may rely onforests for adaptation because they have less access to othercoping strategies. For example, they have had little time to

Table 5. Summary statistics and probit results

Variable Summary statistics

Mean or proportion Std. dev

ConstantAge (years) 45.35 18.4Age squared – –Risk attitude 18.04 17.8Primary education (0/1) 0.29 –Healthy (0/1) 0.43 –Female headship (0/1) 0.31 –Income per capita (in Mk1,000) 2.87 2.60Farm size per capita (acres) 0.63 1.33Number of goatsDistance to MMFR (km) 1.25 1.59Distance to FD (km) 0.25 –Number of observationsPseudo R-squared

* Implies significance at the 0.05 probability level or better.

build up their stocks of liquid assets and are unlikely to receiveremittances from grown children residing elsewhere. Thathouseholds headed by an individual over the age of 60 aremore reliant on forests for shock coping than middle-agehouseholds is somewhat puzzling. In particular, the physicaldemands of forest activities should make forest shock copingless accessible to elderly households.

Results indicate that households that are relatively riskaverse, as measured by a householder’s investment in a gameof chance, are less likely to use forests to smooth consumptionwhen crops fail. This is as expected since many forest activitiesin the study area are risky. Some forest activities entail phys-ical risk, for example, pit sawing and plank carrying are some-what dangerous. Plank carriers transport planks fromForestry Department plantations at 2,000 m to the valley at800 m. This is done on very steep and often slippery terrainand injuries are common. In addition, forest product market-ing is in violation of existing Forestry Department rules. Inparticular, charcoal and timber marketing are subject to severepunishment. For example, during the study period several ofour male respondents were hospitalized when ForestryDepartment patrolmen beat them as punishment for charcoalburning.

We find that households headed by an individual who has atleast a primary education and who is in very good health are,respectively, 46% and 27% less likely to use forests for copingwith weather-related crop failure.10 These findings conform toprior expectation since education and health signal to prospec-tive employers an individual’s potential productivity, increas-ing the likelihood of being hired in relatively remunerativelabor markets.

Of the three living standards variables, only income per ca-pita is statistically significant at standard test levels. As shown,income per capita has a negative association with use of forestsfor reactive adaptation. The observed relationship is consis-tent with other studies in the poverty-environment literature(Cavendish, 2000; Fisher, 2004; Reddy & Chakravarty, 1999)and may reflect that poor households possess few liquid assetsto sell at critical times and face collateral-related constraints toborrowing in credit markets. Access to credit may influencewhether an individual has the possibility to migrate in searchof work or to start up a business.

Finally, we find that households are more reliant on for-ests for shock coping if they have easy access to forest re-sources as represented by distance to the MMFR. It may

for use of forests for reactive adaptation

Probit regression results

iation Coefficient Robust std. error Marginal effect

�0.086 0.636 –5 �0.036* 0.010 �0.009

0.0003* 0.0001 0.00015 0.007* 0.004 0.002

�0.325* 0.146 �0.076�0.184* 0.053 �0.045

0.263 0.253 0.069�0.089* 0.023 �0.022�0.015 0.050 �0.0040.071 0.058 0.018�0.278* 0.065 �0.070

0.125 0.074 0.0311800.13

1248 WORLD DEVELOPMENT

be that distance to forest matters because net benefits toforest extraction fall as the travel time to a collection siteincreases. Thus, findings indicate that the response of forestresource extraction to weather shocks declines along a spa-tial gradient.

6. CONCLUSION

The results of the present study indicate that Malawianfarmers have some awareness of changes in local climate; inparticular, they accurately perceive that average temperaturehas risen in the last ten years. Farm households have triedto adapt to this change in an anticipatory manner, primarilyby substituting hybrid for local maize varieties. While theuse of forests for ex ante adaptation was uncommon amongthe sample households, forests did play an ex post role inadaptation to climate variability. Consistent with observationsin other tropical countries, Malawian forests act as safetynets—forest foods help the rural poor survive famine, and for-est resources are important sources of cash earnings whichhelp cope with weather-related crop failure. Results of thepresent study indicate that households which have low incomeper person, are located in proximity to forest, and are headedby individuals who are older, more risk averse, and less edu-cated than their cohorts are particularly dependent on forestsfor coping with climatic shocks, probably because they havelimited access to other coping mechanisms, such as asset sales.However, additional research is needed to better assess the ex-tent to which access to forests in rural Malawi and in otherdeveloping countries can help the poor adapt to climate vari-ability and change. We recommend the collection of quantita-tive data, based on a large, nationally representative sample,that track behavioral changes over time in response to climaticevents. Complementary qualitative data should also be col-lected to enhance interpretation of the quantitative data.

Study findings indicate that poor farmers in Malawi use for-ests to cope with climate variability, which may indicate a rolefor forests in future climate change adaptation, but forestdepletion is already occurring at a rapid rate (FAO, 2001 citedin UNEP, 2002). Therefore, Malawi’s formal policies need toencourage sustainable management of forested lands, and acombination of forest-based adaptation and other adaptationsto climate variability and change is necessary to reduce trade-offs between the maintenance of household living standardsand conservation of forest resources (e.g., for climate changemitigation and biodiversity protection). NAPA includes someforestry activities, such as afforestation and reforestation pro-grams to control siltation, but additional protective policies

are needed. Programs that encourage sustainable managementof forests are likely to be most effective if they provide incen-tives to protect forests and plant trees, rather than simply re-strict forest access. Forest restrictions have generally beenunsuccessful in Malawi. For example, the government banon charcoal burning in the 1990s has done little to curb pro-duction (Makungwa, 1997). Illegal logging and forest clearingoccur in state forest reserves, despite high fines imposed onviolators (Knacck Consultants, 1999). Furthermore, restrictedforest access would probably lead to reduced welfare amongthe poor, since increased reliance on forest resources as a re-sponse to climate variability is higher among the poor thanthe non-poor.

One promising incentive-based approach to forest conserva-tion is market development of under-exploited NTFPs, suchas honey, forest fruits, and bamboo crafts, which can increaselocal incentives to sustainably manage those resources. Carefulimplementation is necessary, however, because the rise in va-lue of NTFPs may lead to over-harvesting (Neumann &Hirsch, 2000). Another potential approach is to provide gov-ernment assistance to community-company forestry partner-ships, which have proven useful for conserving forests andimproving rural welfare in some areas (Scherr, White, &Kaimowitz, 2002). Companies typically provide necessarymaterials, low-interest loans, and technical assistance forestablishing and managing small woodlots on farm or custom-ary land. In return, companies have rights to buy the maturetrees.

It will also be important for the government to develop asuite of adaptation policies that reduce the vulnerability ofpoor households to climatic variability. The negative im-pacts on farm households of future droughts and floodscan be reduced through a variety of agriculture-relatedinvestments. Under NAPA, for example, irrigation infra-structure is being developed across Malawi, which is crucialfor adaptation in a country of farmers who primarily growrain-fed crops. Other proven approaches include agricul-tural extension activities that encourage farmers to plantsome of their land in drought-resistant crops, such as cas-sava; investments in soil and water conservation practices,such as terracing and construction of earth dams; andgroup weather-insurance schemes that provide financialprotection from weather-related crop failure. Public invest-ment in health care and education services will help ruralMalawians utilize forest-based and other the adaptationstrategies, and households that are identified as particularlyvulnerable should receive priority in implementation ofthese policies.

NOTES

1. Vulnerability has been defined in numerous ways, and there is nocurrent consensus on an appropriate definition (Fussel, 2007; Kelly &Adger, 2000). The current study uses a broad understanding of vulner-ability that encompasses low anticipatory or reactive adaptive capacity tohazardous events (Webb & Harinarayan, 1999).

2. Fanya Juu is a structure used to trap rainwater, in which a type of backslope trench is dug, and soil is thrown upslope to form a riser bank(Kandji & Verchot, 2007).

3. Non-timber forest products include honey, edible plants and animalsfound in forests, gum arabic, rattan, bamboo, cork, nuts, mushrooms,resins, essential oils, and plant and animal parts for pharmaceuticalproducts.

4. Forest resources are not freely available simply because they are heldunder communal tenure. In many societies, forests have been sustainablymanaged by long-standing community-based management systems inwhich norms and rules define the rights of community members to usespecific forest resources (Fortmann & Bruce, 1988). Unfortunately, suchsystems can be transformed into de facto open access areas in the face ofmarket, population, and modernization pressures (Blaikie & Brookfield,1987).

5. The sample size was reduced from 200 to 182 households during thesurvey year. Households left the sample, because they moved awaypermanently (11); enumerators were unable to interview respondents (4);respondents refused to continue participation, because they felt costs ofparticipation outweighed the survey’s benefits (2); and the female

DO FORESTS HELP RURAL HOUSEHOLDS ADAPT TO CLIMATE VARIABILITY? EVIDENCE FROM SOUTHERN MALAWI 1249

householder passed away (1). Commercial forest activities at the studysites included forest-based wage work (employment as a pit sawyer, plankcarrier, forest guard, or mountain guide) and forest-based business(traditional medicine practice; and marketing firewood, charcoal, forestfoods, wood crafts, and wooden furniture).

6. The climate variability questionnaire was conducted with bothhusband and wife in male-headed households; interviews took place at adistance, so that husband and wife could not overhear each other. In somehouseholds, the response of the husband and wife differed. In such cases,we use the response of the household head for the analyses.

7. Although in male-headed households, the climate variability ques-tionnaire was conducted with both husband and wife, the response ofwives is used for analyses related to forest foods, since females providedmore accurate information on household food consumption.

8. In southern Malawi, the raising of cattle is limited by land scarcity;goat ownership is more common. Data for 1997/98 from Malawi’sIntegrated Household Survey (n = 10 698) showed that only 3.7% ofhouseholds in the south owned cattle, while 20% owned goats.

9. Clustering on village of residence accounts for possible non-indepen-dence of observations within villages. We expect households living in thesame village to be similar to each other, due to shared social and economicopportunities or residential selection processes.

10. Marginal effects in the Probit model indicate percentage point, ratherthan percentage change. To arrive at a percentage figure, the marginaleffect is divided by the predicted probability of using forests for reactiveadaptation (0.167).

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