An Analysis of the Causes of Deforestation in Malawi: a Case of Mwazisi

land

Article An Analysis of the Causes of Deforestation in Malawi: A Case of Mwazisi

Susan Ngwira 1,* and Teiji Watanabe 2,* 1 Graduate School of Environmental Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan 2 Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan * Correspondence: [email protected] (S.N.); [email protected] (T.W.)

Received: 4 February 2019; Accepted: 11 March 2019; Published: 15 March 2019

Abstract: Deforestation is recognized as a major driver of the loss of biodiversity and ecosystem services. It also disturbs natural processes such as biogeochemical, hydrological, and ecological cycles. In Malawi, deforestation is estimated to be responsible for the loss of 33,000 hectares per year, and is mainly attributed to agriculture expansion, tobacco growing, and excessive use of biomass. However, little research has been conducted at either the local level or that of forests located on customary land. This research aimed to identify and analyze the underlying driving factors associated with the proximate factors of agriculture expansion, tobacco growing, and brick burning in Mwazisi. Landsat images for 1991, 2004, and 2017 were downloaded from the United States Geological Survey website and used to analyze changes in forest cover. Interviews with households (n = 399) and Natural Resource Committee members, a focus group discussion with key officers, and observations were conducted during field data collection in 2017. The results of the land cover analysis showed that forest covered 66% of the study area in 1991, and by 2017 it had decreased to 45.8%. Most households depend on wood from customary land forests for tobacco curing (69%) and brick burning (68%). Furthermore, 47.6% of the households have expanded their agriculture land by approximately 0.57 hectares during the past 15 years. The interview survey and the focus group discussion identified that the underlying driving factors towards these anthropogenic activities are: (a) population growth, (b) poverty, (c) expensive alternative building materials, (d) lack of awareness, (e) lack of resources, (f) lack of commitment from the tobacco companies, and (g) market system of the cash crops grown in the area. In conclusion, a set of economic, institutional, social, and demographic factors, which are associated with imbalanced relationship between rural and urban areas, underpin agriculture expansion, tobacco growing, and brick burning, and have thereby contributed to the decline of the forest cover in Mwazisi, Malawi.

Keywords: underlying factors; proximate factors; socioeconomic survey; forest change; local level

1. Introduction Deforestation is known as one of the most important elements for changes in land use and land cover. It is recognized as a major driver of the loss of biodiversity and ecosystem services. Globally, it has been occurring at an alarming rate of 13 million hectares per year [1]. It is believed that high population growth coupled with the rapid expansion of agriculture is responsible for the accelerated rates of deforestation, especially in developing countries [2]. Malawi is a developing country in which enormous pressure is being exerted on forest resources. Forest cover of the country reduced from 47% in 1975 to 36% in 2005 [3]. This is the highest deforestation rate in the Southern African Development Community (SADC) region, representing a net loss of some 30,000 to 40,000 hectares per year [3]. This forest loss is mainly attributed to agriculture expansion and excessive use of biomass, such as wood, charcoal, and agricultural residues mostly used for cooking

Land 2019, 8, 48; doi:10.3390/land8030048 www.mdpi.com/journal/land Land 2019, 8, 48 2 of 15 and heating [4]. That is, biomass accounts for 88.5% of the country’s energy demand, 6.4% comes from petroleum, 2.8% from electricity (hydro power), and 2.4% from coal [5,6]. Agriculture is a source of livelihood for more than 90% of the rural and urban population and represents more than three quarters of national exports [7]. The expansion of subsistence agriculture to meet the food needs of the burgeoning population has been one of the main causes of deforestation in Malawi [8,9]. While 62% of the land was agriculture in 1991, by 2008, the agriculture land had reached 70% [10]. In commercial farming, tobacco is one of the major export crops and accounts for approximately 67% of the export earnings from agriculture in Malawi [11,12]. However, the percentage of deforestation caused by tobacco farming is very high—it reached 26% by the early 2000s [13]. Tobacco is further ranked as the highest user of wood among non-household users in Malawi. It involves the use of wood and twigs in construction of barns for air-cured tobacco and firewood for fuel-cured tobacco. The construction industry is also heavily reliant on wood energy for brick production and is ranked second from tobacco in this regard. The brick-making industry alone consumes approximately 850,000 metric tons of wood per year [14,15]. That is, biomass in the form of wood fuel is the largest form of primary energy consumed in Malawi. Malawi obtains 88% of its total energy and 98% of its household energy from traditional biomass, while access to modern energy is less than 10% [15,16]. Inefficient production and unsustainable use of biomass energy have contributed to environmental degradation, such as high deforestation, desertification, and soil erosion [5,6]. There are three land categories in Malawi: public land, private land, and customary land. Public land is the land held in trust for the people of Malawi and managed by the government [17]. Private land is the land that is registered as private under the Registered Land Act [17]. Customary land is the land used for the benefit of the community as a whole within the boundaries of a traditional management area (Land Act 2016). Customary land is held or used by community members under customary law and is under the jurisdiction of the customary traditional authorities [18]. The customary land makes up around 85% of the total land in Malawi [19]. Forest resources on customary land are usually most accessible to the majority of the rural residents (for example, [20]), and are also very important because they provide not only timbers/fuel wood but non-timber forest products for both rural and urban population. Although previous studies and projects have provided a fundamental understanding regarding the protection of forests and forests’ contribution to rural development [21–23], achieving a reduction in deforestation requires an understanding of how local people utilize and manage forest resources. That is, their behavior and impact on the forests differ substantially, despite the fact that each local community operates under the same national legislation [24]. Local-level data provide rich information on how people at the local level interact with forest resources. Conversely, country-level data on the rates of deforestation do little to help policymakers and scholars unravel the web comprising the causes of forest loss [24,25]. Deforestation rates vary significantly within each country, and furthermore, an understanding of the causes of such dynamics and unique variation within the country is critical for the establishment of proper interventions. Several studies on agriculture expansion, benefits and tradeoffs of tobacco, land tenure, biomass use, population, and poverty, and their impacts on forest resources have been conducted in Malawi (for example, [26–28]). However, only a few studies have been conducted at the local level about the drivers of deforestation, especially on customary forest land [22,29]. There are some anthropogenic proximate factors or causes of deforestation, which are human activities or immediate actions such as agriculture expansion that directly impact forest cover [30]. In the case of Malawi, agriculture expansion, tobacco growing, and brick production are regarded as the major proximate factors of deforestation. Underlying driving factors or forces are fundamental social processes such as population dynamics that underpin the proximate causes [30]. Classification of the underlying driving factors varies from area to area as that of the proximate factors do [30–32]. Deforestation has been discussed in a research framework of land science with the focus on the proximate factors and underlying driving factors (for example, [33–35]); however, there are no studies Land 2019, 8, 48 3 of 15 using such a research framework in Malawi. This study, adopting this research framework, aims Land 2019, 8, x FOR PEER REVIEW 3 of 14 to identify and analyze forest cover change and the underlying driving factors associated with the proximatethe proximate factors factors of deforestation of deforestation on customary on customary land land in in the the rural rural area area ofof Mwazisi, Malawi Malawi (Figure (Figure 1), where1), no where research no research about about the drivers the drivers of deforestation of deforestation has has been been conducted conducted toto date.date.

FigureFigure 1. 1. LocationLocation of of the the study study area. area.

2. Materials2. Materials and and Methods Methods

2.1. Study2.1. Study Area Area TheThe Mwazisi Mwazisi zone, zone, which which is is the the customary customary land, is is located located to tothe the west west of the of theRumphi Rumphi district district in in the northernthe northern region region of Malawi.of Malawi. It It consists consists ofof sixsix Village Development Development Committees Committees (VDCs) (VDCs) under under the the TraditionalTraditional Authority Authority Chikulamayembe. Chikulamayembe. TraditionalTraditional Authority Authority is isa form a form of leadership of leadership in which in which the the authority of an organization or a ruling regime is largely tied to tradition or custom. The Mwazisi authority of an organization or a ruling regime is largely tied to tradition or custom. The Mwazisi zone zone is located along Vwaza Marsh Game Reserve (VMGR) and covers an area of 117 km², which is located along Vwaza Marsh Game Reserve (VMGR) and covers an area of 117 km2, which contains contains 1126 households. The total population of the study area is estimated to be approximately 11266570. households. The area is The mostly total covered population by Miombo of the woodlands study area with is an estimated average temperature to be approximately of 22.5 °C in 6570. ◦ The areathe hot is mostlydry season covered [36]. The by highest Miombo average woodlands annual withprecipitation an average falls temperaturein the month of of January 22.5 C is in 191 the hot dry seasonmm. [36]. The highest average annual precipitation falls in the month of January is 191 mm.

2.2. Methods2.2. Methods To detectTo detect changes changes in in forest forest covercover over over a along long time time span span [37–41], [37– Landsat41], Landsat 5 Thematic 5 Thematic Mapper Mapper(19 (19 June,June, 19911991 and and 6 6June, June, 2004) 2004) and and Landsat Landsat 8 Operational 8 Operational Land Imager Land Imager(25 May,(25 2017) May, images 2017) were images weredownloaded downloaded from from the United the United States StatesGeological Geological Survey website Survey [37]. website ArcGIS [37 10.2]. software ArcGIS was 10.2 used software was usedto preprocess to preprocess (radiometric (radiometric correction) correction) the images. the Preprocessing images. Preprocessing of satellite images of satellite prior to images change prior detection is essential and aims to establish a more direct linkage between the data and biophysical to change detection is essential and aims to establish a more direct linkage between the data and phenomena [42]. The forest cover maps were generated using a maximum likelihood classifier. biophysicalOwing to phenomena an overlap [ of42 ]. spectral The forest signatures cover among maps were classes, generated land cover using was a classified maximum into likelihood two classifier.categories: Owing (1) forest to an cover, overlap comprising of spectral forests signatures and shrubs, among and (2) classes, non-forest land cover, cover comprising was classified built- into two categories:up, grass, and (1) agriculture forest cover, lands. comprising Roofing materials, forests andsuch shrubs,as grass, and made (2) it non-forestdifficult to separate cover, comprising built- built-up,up areas grass, from and either agriculture agriculture lands. or grass Roofing land. materials,Before spatial such analysis as grass, and madea temporal it difficult comparison, to separate built-upaccuracy areas assessment from either was agriculture performed or on grass each land. image Before by randomly spatial analysisselecting and100 asample temporal points. comparison, The accuracysample assessment points were was then performedimported into on the each Google image Earth by for randomly comparison. selecting The overall 100 accuracy sample of points. The sampleclassification points was were 96% then for 1991 imported image, into 94% the for Google 2004 image, Earth and for 93% comparison. for 2017 image. The overall The Kappa accuracy coefficients of the classification were 0.92, 0.88, and 0.86 for 1991, 2004, and 2017, respectively. of classification was 96% for 1991 image, 94% for 2004 image, and 93% for 2017 image. The Kappa Socioeconomic data on proximate and underlying factors [30] were collected using interviews, coefficients of the classification were 0.92, 0.88, and 0.86 for 1991, 2004, and 2017, respectively. focus group discussion, and field observations in August 2017; these methods are used by many researchersSocioeconomic in analyzing data on the proximate factors of anddeforestation underlying (for factorsexample, [30 [34,43,44])] were collected. Structured using interviews interviews, focuswere group conducted discussion, with and399 (256 field females, observations 141 males) in August heads of 2017; households these methodsusing random are usedsampling by many researcherstechnique—66 in analyzing households the factorswere randomly of deforestation selected in (for five example, VDC areas [34 and,43 69,44 in]). one Structured VDC area. interviews The were conducted with 399 (256 females, 141 males) heads of households using random sampling technique—66 households were randomly selected in five VDC areas and 69 in one VDC area. Land 2019, 8, 48 4 of 15

Land 2019, 8, x FOR PEER REVIEW 4 of 14 The sample size was calculated using Cochran’s (1963:75) formula [45] below to secure the samplerepresentativeness size was of calculated the community: using Cochran’s (1963:75) formula [45] below to secure the representativeness of the community: 2 2 nn= = (Z (Z²pp(1 (1− − p))/ee² (1)(1) where n is the sample size, Z is constant, e is the level of precision, and p is the estimated proportion proportion of an attribute. The purpose of the household survey was to understand socioeconomic conditions, forest dependency, dependency, and and the the awareness awareness of of local local people people regarding regarding forest forest use use and and management, management, i.e., i.e., to examineto examine economic economic and and institutional institutional factors factors as asthe the underlying underlying factors. factors. Interviews were were also conducted conducted with with two two officers officers from from the Forestry Forestry Department Department and and one one officer officer from the the Department Department of of Parks Parks and and National National Wildlife, Wildlife, as well as as well two asmembers two members of the Natural of the Resources Natural ResourcesCommittee Committee (NRC), to identify (NRC), problems to identify and problems the current and condition the current of forests condition in the of study forests area. in the The study focus area.group The discussion focus group was conducteddiscussion withwas conducted officers from with the officers Department from ofthe Agriculture Department regarding of Agriculture forest regardingmanagement forest and management challenges. and Through challenges. the interviews Through the and interviews the focus groupand the discussion, focus group institutional discussion, institutionalfactors as part factors of the as underlying part of the factors underlying were examined.factors were examined. Field observations werewere also also conducted conducted in in the the farms farms and and forests forests during during the socialthe social surveys surveys in 2017. in 2017.Photographs Photographs were takenwere taken to illustrate to illustrate some some of the of causes the causes of deforestation of deforestation in the in study the study area. area. Secondary data such as, the prices of tobacco, maize, groundnuts, and soybeans and tobacco farming practices, practices, were were collected collected from from the the Tobacco Tobacco Control Control Commission Commission of Malawi of Malawi (TCCM), (TCCM), the Agriculturalthe Agricultural Development Development and and Marketing Marketing Corporation Corporation (ADMARC), (ADMARC), the the National National Association Association of Smallholderof Smallholder Farmers Farmers (NASFAM), (NASFAM), the the Labor Labor Office, Office, the the Forestry Forestry Department, Department, and and the the reports reports to analyze the economic factors.

3. Results Results

3.1. Forest Change Analysis The results of the classification classiﬁcation show that forest was the dominant land land cover cover in in the year 1991 (Figure 22a);a); however,however, itit hashas declineddeclined tremendouslytremendously overover thethe years.years. ForestForest coveredcovered 66%66% ofof thethe areaarea inin 1991 and decreased to 45.8% in 2017 (Table 1 1).). TheThe annualannual raterate ofof forestforest covercover lossloss betweenbetween 19911991 andand 2004 was 1.3% and increased to 1.6% in the period between 2004 and 2017.

Figure 2. Cont. Land 2019, 8, 48 5 of 15 Land 2019, 8, x FOR PEER REVIEW 5 of 14 Land 2019, 8, x FOR PEER REVIEW 5 of 14

Figure 2. Forest cover maps of Mwazisi in (a) 1991; (b) 2004; and (c) 2017. Figure 2. Forest cover mapsFigure of Mwazisi 2. Forest in (a cover) 1991; maps (b) 2004; of Mwazisi and (c) 2017.in (a) 1991; (b) 2004; and (c) 2017.

TableTable 1. Change in forest cover from 1991 to 2017. Table 1. Change in forest cover from 1991 to 2017. 19911991 2004 2004 2017 2017 LandLand Cover Cover 1991 2004 2017 Area (ha) Land% Cover Area (ha) % Area (ha) % Area (ha) % Area (ha)Area (ha) %% Area Area (ha) (ha) %% Area (ha) % Forest 7718.76 66.0 6560.37 56.1 5364.18 45.8 Forest 7718.76 66.0Forest 6560.37 7718.76 56.1 66.0 5364.18 6560.37 45.8 56.1 5364.18 45.8 Non-forest 3983.85 34.0 5142.24 43.9 6338.43 54.2 Non-forest 3983.85 34.0Non-forest 5142.24 3983.85 43.9 34.0 6338.43 5142.24 54.2 43.9 6338.43 54.2 Total area 11,702.61 100.0 Total area 11,702.61 100.0Total area 11,702.61 100.0 3.2. Drivers of Deforestation 3.2. Drivers of Deforestation3.2. Drivers of Deforestation 3.2.1. Proximate Factors of Deforestation 3.2.1. Proximate Factors of3.2.1. Deforestation Proximate Factors of Deforestation Agriculture Expansion Agriculture Expansion Agriculture Expansion Interviews show that most households (80.7%) depend on agriculture to support their daily Interviews show that mostInterviews households show (80.7%) that most depend households on agriculture (80.7%) to depend support on their agriculture daily to support their daily livelihood while only 19.3% earn their living through business and employment. All households livelihood while only 19.3%livelihood earn their while living only through 19.3% business earn their and living employment. through All business households and growemployment. All households grow a crop of maize as a staple food, and for the past 15 years, 47.6% of the households have a crop of maize as a staplegrow food, a andcrop for of themaize past as 15 a years,staple 47.6% food, ofand the for households the past 15 have years, expanded 47.6% of the households have expanded their maize farm (Figures 3 and 4). On average, each household has expanded its their maize farm (Figuresexpanded3 and4). On their average, maize each farm household (Figures has 3 expanded and 4). On its agricultureaverage, each land household by has expanded its agriculture land by approximately 0.57 hectares during the past 15 years. Most households (91.2%) approximately 0.57 hectaresagriculture during the land past by 15 approximately years. Most households 0.57 hectares (91.2%) during expanded the past their 15 years. maize Most households (91.2%) expanded their maize farms due to an increase in family size (on average, each household has four farms due to an increase inexpanded family size their (on average,maize farms each due household to an increase has four in children) family andsize a(on lack average, of farm each household has four children) and a lack of farm inputs. The Pearson product-moment correlation coefficient also shows inputs. The Pearson product-momentchildren) and correlation a lack of farm coefﬁcient inputs. also The shows Pearson a positive product-moment correlation betweencorrelation coefficient also shows a positive correlation between the frequency of the agriculture expansion and the number of children the frequency of the agriculturea positive expansion correlation and between the number the frequency of children of in the a householdagriculture (correlation expansion and = the number of children in a household (correlation−6 = 0.3764, p = 4.949 × 10⁻⁶). 0.3764, p = 4.949 × 10 ).in a household (correlation = 0.3764, p = 4.949 × 10⁻⁶).

Figure 3. Households that have expanded their agriculture land during the past 15 years (n = 399). Figure 3. Households that have expanded their agriculture land during the past 15 years (n = 399). LandLand 20192019,, 88,, 48x FOR PEER REVIEW 6 6 ofof 1514 Land 2019, 8, x FOR PEER REVIEW 6 of 14 Land 2019, 8, x FOR PEER REVIEW 6 of 14

Figure 4. Land being cleared for farming (Photo by Teiji Watanabe, 7 August 2017). Figure 4. Land being cleared for farming (Photo by Teiji Watanabe, 7 August 2017). FigureFigure 4. 4. LandLand being being cleared cleared for for farming farming (Photo (Photo by by Teiji Teiji Watanabe, 7 August 2017).2017). TobaccoTobacco Growing Growing Tobacco Growing TobaccoTobacco isis thethe mainmain cashcash crop crop inin thethe areaarea andand isis growngrown byby 45.4%45.4% ofof households,households, whilewhile thethe Tobacco is the main cash crop in the area and is grown by 45.4% of households, while the remainingremainingTobacco households households is the main depend depend cash on on crop subsistence subsistence in the area farming. farming. and isOf Of grown the the tobacco tobacco by 45.4% farmers, farmers, of households, 46.4% 46.4% expanded expanded while their their the remaining households depend on subsistence farming. Of the tobacco farmers, 46.4% expanded their agricultureremainingagriculture householdsland land by by an an average averagedepend of ofon approximately approximately subsistence farming. 0.39 0.39 hectares hectares Of the per pertobacco year. year. farmers,These These farmers farmers 46.4% expanded expandedexpanded their theirtheir agriculture land by an average of approximately 0.39 hectares per year. These farmers expanded their agricultureagricultureagriculture land landland mainly bymainly an average to to increase increase of approximately earnings earnings or or profit. profit. 0.39 hectares The The type type per of of year.tobacco tobacco These grown grown farmers in in the the expanded study study area area their is is agriculture land mainly to increase earnings or proﬁt. The type of tobacco grown in the study area is burley,agricultureburley, which which land is is air-cured mainlyair-cured to in inincrease barns. barns. Figure earningsFigure 5 5 shows orshows profit. that that The 69% 69% type of of the ofthe tobaccofarmers farmers grown extracted extracted in the wood wood study from from area the the is burley, which is air-cured in barns. Figure5 shows that 69% of the farmers extracted wood from the forestburley,forest (including (including which is ropesair-cured ropes and and in twigs) twigs) barns. to to Figure construct construct 5 shows the the barns barns that 69%(Figure (Figure of the 6). 6). farmers extracted wood from the forest (including ropes andand twigs) toto constructconstruct thethe barnsbarns (Figure(Figure6 6).).

FigureFigure 5.5. SourceSource ofof woodwood forfor barnbarn constructionconstruction inin MwazisiMwazisi ((nn == 181).181). Figure 5. Source of wood for barn construction in Mwazisi (n = 181). Figure 5. Source of wood for barn construction in Mwazisi (n = 181).

Figure 6. Barn for burley tobacco curing (Photo by Susan Ngwira, 9 August 2017). FigureFigure 6. 6. BarnBarn for for burley burley tobacco tobacco curing curing (Photo (Photo by by Susan Susan Ngwira, Ngwira, 9 9 August August 2017). 2017). Figure 6. Barn for burley tobacco curing (Photo by Susan Ngwira, 9 August 2017). BrickBrick Burning Burning Brick Burning ThereThere are are three three types types of of building building materials materials in in Mwazisi: Mwazisi: clay clay bricks, bricks, mud, mud, and and wood. wood. Clay Clay bricks bricks areare the theThere main main are building building three types material material of building and and are are materials used used by by in65.7% 65.7% Mwazisi: of of the the clay households households bricks, mud, (Figure (Figure and 7). wood.7). Clay Clay Clay bricks bricks bricks are are are the main building material and are used by 65.7% of the households (Figure 7). Clay bricks are Land 2019, 8, 48 7 of 15

Brick Burning Land 2019, 8, x FOR PEER REVIEW 7 of 14

LandThere 2019, 8 are, x FOR three PEER types REVIEW of building materials in Mwazisi: clay bricks, mud, and wood. Clay 7 of bricks 14 areburned the mainbefore building their use material in construction and are usedand bythe 65.7%source of of the energy households is wood (Figure (Figure7). 8). Clay Of bricksthe brick- are burnedwalledburned houses before before their in their the use area,use in constructionin 68% construction used wood and and the from the source sourcethe offorests energyof energy and is wood 31%is wood used (Figure (Figure wood8). Of 8).left the Of over brick-walled the afterbrick- the housesclearingwalled in of houses the land area, for in 68%theagriculture. area, used 68% wood Field used from results wood the showfrom forests thethat andforests each 31% brick-walledand used 31% wood used house leftwood over used left after over4 metric the after clearing tons the of ofwood,clearing land on for average. of agriculture. land for agriculture. Field results Field show results that show each that brick-walled each brick-walled house house used 4used metric 4 metric tons tons of wood, of onwood, average. on average.

FigureFigure 7. 7. Building Building materialsmaterials used in in Mwazisi Mwazisi ( n (n = = 399). 399).

Figure 8. Clay bricks being packed for burning (Photo by Teiji Watanabe, 7 August 2017). FigureFigure 8. 8. ClayClay bricks bricks being being packed packed for for burning burning (Photo by by Teiji Watanabe, 7 AugustAugust 2017).2017). 3.2.2. Underlying Driving Factors 3.2.2. Underlying Driving Factors EconomicEconomic Factors Factors Economic Factors AnAn analysis analysis of of the the market market systems systems ofof variousvarious crops grown grown in in the the area area shows shows that that tobacco tobacco has has a a well-developedAn analysis of market the market structure systems designed of various to reach crops smallholder grown farmersin the area in the shows rural that areas tobacco [5,46–50]. has a well-developed market structure designed to reach smallholder farmers in the rural areas [5,46–50]. well-developedThe tobacco crops market are structure sold to international designed to companiesreach smallholder based in farmers the capital in the city rural of Lilongwe. areas [5,46–50]. The The tobacco crops are sold to international companies based in the capital city of Lilongwe. The tobacco Thetobacco tobacco growing crops isare practiced sold to internationalas a form of contractcompanies farming, based which in the helps capital smallholder city of Lilongwe. farmers by The growing is practiced as a form of contract farming, which helps smallholder farmers by providing tobaccoproviding growing access is topracticed the market, as a inputs,form of and contract extension farming, services which [51]. helps That smallholder is, tobacco companies farmers by access to the market, inputs, and extension services [51]. That is, tobacco companies provide loans, providingprovide loans, access expertise, to the market, and transportation inputs, and of extensionthe farm produce services to [51].the tobacco That is, market. tobacco However, companies it expertise, and transportation of the farm produce to the tobacco market. However, it is more expensive provideis more loans, expensive expertise, and difficultand transportation for smallholder of the farmers farm toproduce obtain expertiseto the tobacco and loans market. on crops However, such it and difﬁcult for smallholder farmers to obtain expertise and loans on crops such as ground nuts, maize, is moreas ground expensive nuts, andmaize, difficult and soybeans. for smallholder This has farmers resulted to in obtain an increase expertise in theand number loans on of crops tobacco such and soybeans. This has resulted in an increase in the number of tobacco farmers despite its impact on as farmersground despite nuts, maize, its impact and on soybeans. the forests This and environment.has resulted in an increase in the number of tobacco the forests and environment. farmersA despite comparison its impact of the onaverage the forests price ofand tobacco environment. crop with others grown in the area, such as maize, A comparison of the average price of tobacco crop with others grown in the area, such as maize, groundnuts,A comparison and ofsoybeans, the average shows price that of tobacco tobacco has crop had with the others highest grown average in the price area, over such the as years maize, groundnuts, and soybeans, shows that tobacco has had the highest average price over the years groundnuts,(Figure 9a). and This soybeans, motivated shows 71.3% that of thetobacco farmers has while had the availabilityhighest average of loans price and over the the market years motivated 28.8%. However, a comparison of the average yield per hectare per year (Figure 9b) shows (Figure 9a). This motivated 71.3% of the farmers while the availability of loans and the market that maize has the highest average yield, followed by groundnuts. motivated 28.8%. However, a comparison of the average yield per hectare per year (Figure 9b) shows that maize has the highest average yield, followed by groundnuts. Land 2019, 8, 48 8 of 15

(Figure9a). This motivated 71.3% of the farmers while the availability of loans and the market motivated 28.8%. However, a comparison of the average yield per hectare per year (Figure9b) shows LandLandthat 20192019 maize,, 88,, xx hasFORFOR the PEERPEER highest REVIEWREVIEW average yield, followed by groundnuts. 8 8 ofof 1414

FigureFigureFigure 9.9. 9. ((aa()a) Average)Average Average annualannual annual pricesprices prices ofof of burleyburley burley tobacco,tobacco, tobacco, maize,maize, maize, G/nutsG/nuts G/nuts (groundnuts),(groundnuts), (groundnuts), andand andsoybeanssoybeans soybeans perper kilogram;kilogram;per kilogram; ((bb)) averageaverage (b) average yieldyield yield inin kilogramskilograms in kilograms perper hectarehectare per hectare ofof soybeans,soybeans, of soybeans, G/nuts,G/nuts, G/nuts, maize,maize, maize, andand tobacco.tobacco. and tobacco. DataData source:source:Data source: TCCM,TCCM, TCCM, ADMARC,ADMARC, ADMARC, WorldWorld World Bank,Bank, Bank, andand NASFAM.NASFAM. and NASFAM.

DataDataData fromfrom from thethe the fieldfield ﬁeld surveysurvey survey showshow show thatthat that 86.1%86.1% 86.1% ofof thethe of householdshouseholds the households inin MwazisiMwazisi in Mwazisi livelive belowbelow live thethe below nationalnational the povertypovertynational line line poverty (<1 (<1 US$/day) US$/day)line (<1 US$/day) with with an an withaverage average an average income income income of of approximately approximately of approximately 14,151.5 14,151.5 14,151.5 MK/month MK/month MK/month (19.84 (19.84 US$/month)US$/month)(19.84 US$/month) (Figure(Figure 10). (Figure10). DueDue 10 toto). poverty,poverty, Due to poverty,householdshouseholds households havehave failedfailed have toto purchase failedpurchase to purchase farmfarm inputsinputs farm (to(to inputs improveimprove (to soilsoilimprove fertility),fertility), soil whichwhich fertility), hashas which ledled toto has anan expansionexpansion led to an expansion ofof cultivationcultivation of cultivation landland toto increaseincrease land to thethe increase harvestharvest the yield.yield. harvest yield.

Figure 10. n FigureFigure 10.10. AverageAverageAverage monthlymonthly monthly incomeincome income ofof of thethe the familiesfamilies families interviewedinterviewed inin MwazisiMwazisi (( nn == 399).399). 399). The alternative building materials, such as cement (raw material for cement bricks) are regarded as TheThe alternativealternative buildingbuilding materials,materials, suchsuch asas cementcement (raw(raw materialmaterial forfor cementcement bricks)bricks) areare regardedregarded expensive by most households (96.9%), considering that most of the households live below the national asas expensiveexpensive byby mostmost householdshouseholds (96.9%),(96.9%), consideringconsidering thatthat mostmost ofof thethe householdshouseholds livelive belowbelow thethe poverty line (Figure 10). The alternative energy sources for brick burning recognized by households nationalnational povertypoverty lineline (Figure(Figure 10).10). TheThe alternativealternative energyenergy sourcessources forfor brickbrick burningburning recognizedrecognized byby (12%) in the study area are animal manure, crop remains, and petroleum; however, the interview householdshouseholds (12%)(12%) inin thethe studystudy areaarea areare animalanimal manure,manure, cropcrop remains,remains, andand petroleum;petroleum; however,however, thethe survey indicated that these households also lack technical knowledge. interviewinterview surveysurvey indicatedindicated thatthat thesethese householdshouseholds alsoalso lacklack technicaltechnical knowledge.knowledge. Demographic Factors DemographicDemographic FactorsFactors There are no population data for the study area; however, there are data for Rumphi (Figure 11). There are no population data for the study area; however, there are data for Rumphi (Figure 11). ThereThere is an are increasing no population trend data in populationfor the study in area; the districthowever, and there an are annual data populationfor Rumphi growth(Figure 11). rate There is an increasing trend in population in the district and an annual population growth rate of Thereof Rumphi is an increasing is 3.4% [52 trend]. This in haspopulation resulted in in the an district increase and in demandan annual for population land for bothgrowth settlement rate of Rumphi is 3.4% [52]. This has resulted in an increase in demand for land for both settlement and Rumphiand agriculture. is 3.4% [52]. This has resulted in an increase in demand for land for both settlement and agriculture.agriculture.

FigureFigure 11.11. PopulationPopulation ofof thethe RumphiRumphi districtdistrict 1977–20081977–2008 andand projectedprojected populationpopulation 2012–2016.2012–2016. DataData source:source: NationalNational StatisticalStatistical OfficeOffice (2016)(2016) andand IHS4IHS4 (2017).(2017). Land 2019, 8, x FOR PEER REVIEW 8 of 14

Figure 9. (a) Average annual prices of burley tobacco, maize, G/nuts (groundnuts), and soybeans per kilogram; (b) average yield in kilograms per hectare of soybeans, G/nuts, maize, and tobacco. Data source: TCCM, ADMARC, World Bank, and NASFAM.

Data from the field survey show that 86.1% of the households in Mwazisi live below the national poverty line (<1 US$/day) with an average income of approximately 14,151.5 MK/month (19.84 US$/month) (Figure 10). Due to poverty, households have failed to purchase farm inputs (to improve soil fertility), which has led to an expansion of cultivation land to increase the harvest yield.

Figure 10. Average monthly income of the families interviewed in Mwazisi (n = 399).

The alternative building materials, such as cement (raw material for cement bricks) are regarded as expensive by most households (96.9%), considering that most of the households live below the national poverty line (Figure 10). The alternative energy sources for brick burning recognized by households (12%) in the study area are animal manure, crop remains, and petroleum; however, the interview survey indicated that these households also lack technical knowledge.

Demographic Factors There are no population data for the study area; however, there are data for Rumphi (Figure 11). There is an increasing trend in population in the district and an annual population growth rate of RumphiLand 2019, 8is, 483.4% [52]. This has resulted in an increase in demand for land for both settlement9 and of 15 agriculture.

FigureFigure 11. Population of of the Rumphi district 1977–2008 and projected population 2012–2016. Data source:source: National National Statistical Statistical Office Ofﬁce (2016) and IHS4 (2017).

Institutional Factors The Forest Act is a fundamental tool for proper forest use and management of private, customary, and public land in Malawi. The results from the field survey, however, show that 95.2% of households are unfamiliar with the Act. Most households (97.7%) are unaware of the prohibition of forest wood extraction for brick burning. Furthermore, 97.8% of tobacco farmers are unaware of the prohibition of forest wood extraction for tobacco processing. The focus group discussion and interviews with the officers from agriculture and forestry reveal the existence of financial and material constraints in the district. This has led to a reduction in field activities, such as monitoring, awareness campaigns, and law enforcement, especially on customary land forests. With few resources in the district, priority is mostly given to the forest reserves (one gazette and three proposed forest reserves). Tobacco companies have been involved in deforestation mitigation activities, notably tree planting. However, the initiative has yielded few results. Field survey data show that approximately 10,980 tree seedlings were distributed to tobacco farmers by four tobacco companies in 2016. The quantity of tree seedlings given to each farmer is determined by the size of the farm (i.e., 130 trees seedlings per 0.5 hectares). Almost all farmers (94%) planted the seedlings; however, only approximately 257 seedlings survived. The farmers complained about the late distribution of the seedlings (usually distributed towards the end of the rainy season), which resulted in the low survival of the planted seedlings. The focus group discussion and interviews identified that the four tobacco companies do not monitor their farmers while they are planting and caring for the distributed seedlings. Furthermore, there is lack of collaboration between the tobacco companies and governmental departments. That is, the companies rarely share information, resulting in officers’ failure to follow up on any activities conducted by the tobacco companies.

4. Discussion

Institutional Factors The Forest Act is a fundamental tool for proper forest use and management of private, customary, and public land in Malawi. The results from the field survey, however, show that 95.2% of households are unfamiliar with the Act. Most households (97.7%) are unaware of the prohibition of forest wood extraction for brick burning. Furthermore, 97.8% of tobacco farmers are unaware of the prohibition of forest wood extraction for tobacco processing. The focus group discussion and interviews with the officers from agriculture and forestry reveal the existence of financial and material constraints in the district. This has led to a reduction in field activities, such as monitoring, awareness campaigns, and law enforcement, especially on customary land forests. With few resources in the district, priority is mostly given to the forest reserves (one gazette and three proposed forest reserves). Tobacco companies have been involved in deforestation mitigation activities, notably tree planting. However, the initiative has yielded few results. Field survey data show that approximately 10,980 tree seedlings were distributed to tobacco farmers by four tobacco companies in 2016. The quantity of tree seedlings given to each farmer is determined by the size of the farm (i.e., 130 trees seedlings per 0.5 hectares). Almost all farmers (94%) planted the seedlings; however, only approximately 257 seedlings survived. The farmers complained about the late distribution of the seedlings (usually distributed towards the end of the rainy season), which resulted in the low survival of the planted seedlings. The focus group discussion and interviews identified that the four tobacco companies do not monitor their farmers while they are planting and caring for the distributed seedlings. Furthermore, there is lack of collaboration between the tobacco companies and governmental departments. That is, the companies rarely share information, resulting in officers’ failure to follow up on any activities conducted by the tobacco companies.

4. Discussion

4.1. Interaction between Underlying and Proximate Factors of Deforestion This study revealed the existence of multiple underlying driving factors towards the proximate factors of agriculture expansion, tobacco growing, and brick burning. Furthermore, this study identified that each underlying driving factor underpins one or multiple proximate factors, as shown in Figure 12. An analysis of the satellite images shows a significant areal reduction in the forest cover; it Landdecreased2019, 8, 48from 66.0% in 1991 to 45.8% in 2017 (Table 1). The high rate of the deforestation is 10partly of 15 owing to agriculture expansion, the liberalization of tobacco farming after 1995, and brick burning.

FigureFigure 12. Summary of of the the interaction interaction between between underlying underlying and and proximate proximate factors factors of ofdeforestation deforestation in inMwazisi. Mwazisi.

An analysis of the satellite images shows a significant areal reduction in the forest cover; it decreased from 66.0% in 1991 to 45.8% in 2017 (Table1). The high rate of the deforestation is partly owing to agriculture expansion, the liberalization of tobacco farming after 1995, and brick burning. Agriculture supports the livelihood of most households in Mwazisi. Subsistence farming mostly involves crops such as maize, groundnuts, and soybeans (ground nuts and soybeans are usually intercropped with maize). A statistical analysis of the field data showed a positive correlation between the frequency of the agriculture expansion and the number of children in a household (correlation = 0.3764, p-value = 4.949 × 10−6, significance value = 0.05). This finding is in line with the literature, which states that the largest net loss of forest area and large gain in agriculture area (in the low income group of countries) are associated with an increase in the rural population [53] as well as urban population. Nonetheless, agriculture expansion depends not only on an increase in the number of children in a household but also on other factors, such as poverty. Households cannot afford sufficient farm inputs, such as fertilizer, to restore soil fertility, which has further resulted in the expansion of cultivation land to increase the harvest yield. The poverty ratio is higher in rural areas than in urban areas in Malawi—about 43% of the population in the rural areas reside in poverty, compared with 14% of the urban population [54]. Most smallholder farmers in the rural areas of Malawi may have little access to fertilizer because of its high price [55]. With regards to the tree planting initiative in tobacco farming, farmers complained about the late distribution of seedlings which affected the survival of the planted seedlings. A study by Clarkson [56] showed that many farmers would devote their resources to planting trees if they were able to source seedlings at an appropriate time in the year. Appropriate timing for seed distribution and monitoring would help to increase the survival rate of the planted tree seedlings as the interviewees accounted for. Also, the tobacco companies demonstrate a lack of commitment. The tobacco companies do not monitor farmers when they are planting and managing the care of the distributed tree seedlings. In 2016, among approximately 10,980 tree seedlings distributed, 257 seedlings were alive, as described earlier. These findings are similar to the results obtained by the Extension Service of Malawi, which found that 80% of the estate farmers had failed to follow the government’s recommendation to plant trees on 10% of the farm land [11]. The tobacco companies are much more interested in the economic benefits of tobacco and pay little attention to the forest degradation caused by tobacco [11]. Currently, tobacco farmers meet their wood needs with trees from the forests nearby—burley tobacco requires 158 trees for every 0.15 hectares of tobacco [57]. Bricks are the main building materials in both urban and rural settings in Malawi, and the wood needed for brick production is extracted from natural woodlands or forests. The alternative building Land 2019, 8, 48 11 of 15 materials, such as cement, are regarded as expensive, especially for rural residents, because most households live below the national poverty line (Figure 10). When comparing the clay bricks produced in an open kiln with those produced by an alternative method called Vertical Shaft Brick Kiln (VSBK or Eco-kiln), which consumes less fuel and also uses carbonaceous waste or coal, the price of each VSBK brick is three times more expensive than that of bricks produced in an open kiln [58]. Consequently, people opt for the cheaper bricks. The VSBK method also requires a huge amount of capital for its establishment and it mostly targets the urban population, which only constitutes 14.39% of households, compared to households in the rural areas of the northern region, which comprise 86.61% [52,58].

4.2. Deforestation on Customary Land The majority of users of wood energy are found in the customary land in rural areas, where almost 90% of the population lives [52]. According to the literature [59] over 50% of the wood energy in Malawi comes from customary forests and woodlands. Forests on customary land are managed by the rural community; therefore, proper knowledge, support, and empowerment are required, although they are imbalanced between the rural and urban areas. According to Sillah [60], the awareness level of the local population concerning conservation and rational utilization of forest resources must be augmented to acquire the active participation and commitment of communities and individuals. The ﬁndings of this study, however, show a low level of awareness among those in the local population regarding forest use and management. The lack of resources at the district level has partly contributed to the problem. For example, the forestry budget for one year (2016–2017) for Rumphi was 9366.87 US$ with a monthly budget of 780.57 US$. This has resulted in a reduction in law enforcement, awareness campaigns, and monitoring, especially for customary land forests as the interviewees accounted for. Developing countries barely meet the ﬁnancial, material, and personnel requirements for sustainable forest management. People continue to illegally extract wood from customary land forests for either commercial or non-commercial purposes.

4.3. Measures to Mitigate Pressure on Forests Tobacco is an important cash crop in Malawi, as it accounts for 35% of the Gross Domestic Product [3]. The results of this study suggest the existence of a number of factors that motivate farmers to grow tobacco over other cash crops, which include: (1) the availability of loans facilitated by the tobacco companies, (2) a better price for tobacco compared to that of other cash crops, and (3) easy access to tobacco information and the availability of a market for the crop. These results are similar to those of the research conducted by the Centre for Agricultural Research and Development [61]. Hall [53] reported that most governments send out mixed messages regarding their concern for people and the environment, while actively and assiduously promoting the very economic sectors that drive deforestation. If the supply chains for alternative crops were developed to the level of tobacco supply chains, the prices and proﬁtability of these crops would also grow and eclipse those of contract tobacco [56]. This, in turn, would help to reduce the pressure on forest resources exerted by tobacco farming. The alternative for brick burning in the study area would be an introduction of stabilized soil bricks (SSBs) [16,62] and promotion of its use. This method involves the use of either soil alone or a mixture of soil and a minimum amount of 10% cement. The mixed soil and cement are compressed at high pressure and are cured under a shade [16]. This method produces bricks using very little or no energy; therefore, this alternative would lead to reduction of deforestation.

4.4. Limitation of the Study Although this study found a decrease in forest cover, higher spatial resolution images would be able to separate overlapping classes, such as forest and shrubs, and built-up grass and agriculture lands, more accurately. The results of the social survey may be applied to some local areas in the country, Land 2019, 8, 48 12 of 15 but an accumulation of similar studies is necessary to understand the similarities and differences among its local levels.

5. Conclusions Landsat images were used to assess forest cover changes of the study area. Forest cover in Mwazisi was reduced from 66% in 1991 to 45.8% in 2017. Qualitative and quantitative methods were used to assess socioeconomic conditions, forest dependency, and the underlying driving factors of deforestation. Households continue to depend on forest resources for (1) agriculture expansion, (2) tobacco curing, and (3) brick burning. The underlying factors towards these anthropogenic factors are the market system, poverty, and population growth, expensive alternative building materials, lack of awareness, lack of resources, and lack of commitment. Each of these underlying drivers of deforestation interacts with single or multiple proximate factors. Additionally, there are multiple underlying driving factors working together to underpin each proximate factor of deforestation, thereby impacting the forest cover reduction in Mwazisi. Synergies also exist between some underlying driving factors, such as a lack of awareness and resources. A set of economic, institutional, and demographic factors underpin agriculture expansion, tobacco growing, and brick burning in Mwazisi, Malawi. The following recommendations would facilitate the reduction in the deforestation rate: Providing technical support to the village heads and Community-Based Natural Resources Management Committee on forest management, and monitoring the tobacco companies operating in the district.

Author Contributions: Conceptualization, S.N. and T.W.; methodology, S.N. and T.W.; validation, S.N. and T.W.; investigation, S.N. and T.W.; writing—original draft preparation, S.N.; writing—review and editing, S.N. and T.W.; visualization, S.N. and T.W.; supervision, T.W.; funding acquisition, S.N. and T.W. Funding: This research was partially funded by the Japan International Corporation Agency (JICA). Acknowledgments: We are grateful to the Japan International Cooperation Agency (JICA) and the Japan International Cooperation Centre (JICE) for the scholarship (African Business Education Initiative (D-16-05395)) to S.N. and the funding for fieldwork during this research. Conflicts of Interest: The authors declare no conflict of interest.

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