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More people, more trees in SouthEastern Tanzania: local and globaldrivers of land-use/cover changesAndrew Kabanza a , Stefaan Dondeyne b , John Tenga a , DidasKimaro c , Jean Poesen b , Elly Kafiriti b & Jozef Deckers aa Naliendele Agricultural Research Institute, Mtwara, Tanzaniab Department of Earth and Environmental Sciences, CatholicUniversity, Heverlee, Belgiumc Department of Agricultural Engineering and Land Planning,Sokoine University of Agriculture, Morogoro, TanzaniaVersion of record first published: 04 Jan 2013.

To cite this article: Andrew Kabanza , Stefaan Dondeyne , John Tenga , Didas Kimaro , JeanPoesen , Elly Kafiriti & Jozef Deckers (2013): More people, more trees in South Eastern Tanzania:local and global drivers of land-use/cover changes, African Geographical Review, 32:1, 44-58

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RESEARCH ARTICLE

More people, more trees in South Eastern Tanzania: local and globaldrivers of land-use/cover changes

Andrew Kabanzaa, Stefaan Dondeyneb*, John Tengaa, Didas Kimaroc, Jean Poesenb, EllyKafiritib and Jozef Deckersa

aNaliendele Agricultural Research Institute, Mtwara, Tanzania; bDepartment of Earth andEnvironmental Sciences, Catholic University, Heverlee, Belgium; cDepartment of AgriculturalEngineering and Land Planning, Sokoine University of Agriculture, Morogoro, Tanzania

(Received 28 April 2012; accepted 29 October 2012)

Land degradation in South Eastern Tanzania, the country’s major cashew producing area,has been attributed to deforestation. By comparing land-use/cover maps derived from aerialphotographs of 1965 with maps derived from satellite images of 2002, we assessed howland-use changed in six villages, and relate these to local and global drivers. Land-use/coverchanges are complex processes, which we analyzed by determining the relative net changes,losses, persistence and gains of each land-use/cover categories. Widespread planting ofcashew trees only started in the 1960s; while the ‘villagisation’ program in the 1970s,altered settlement patterns as centrally planned villages were created. Population growth andrural development policies were major local drivers for land-use/cover change; internationaltrade and technological innovations were principal global drivers. Though populationincrease led to a reduction of natural vegetation, the spread of cashew trees resulted in acase of ‘more people, more trees.’ How far the ensuing deforestation affected thebiodiversity of the area and how sustainable the production of cashew nuts actually is,remains yet unresolved questions.

Keywords: cashew nut; deforestation; villagisation; population growth; land degradation

Introduction

General concern about land-use change arose from the realization that transformation in land-use/cover influences, surface hydrology, soil erosion, climate and biodiversity, hence the inter-est in processes leading to deforestation, desertification and other changes in naturalvegetation (Lambin, Geist, and Lepers, 2003). It is commonly accepted that the growinghuman population in the world increasingly needs more arable land, which results into adecline of world’s forests, grasslands and woodlands (Meyfroidt, Rudel, and Lambin, 2010).However, while land-use changes are often attributed to a single factor, such as shiftingcultivation or population growth, Lambin et al. (2003) argued that land-use change is alwayscaused by multiple interacting factors, with demographic, economic, technological, policy andcultural factors as the major underlying causes.

South Eastern Tanzania is the country’s principal production area of cashew nuts(Anacardium occidentale L.), one of Tanzania’s major export commodities (Topper andKasuga, 2003; CBT, 2008); in the period from 2003 to 2008 Tanzania ranked between the

*Corresponding author. Email: stefaan.dondeyne@ees.kuleuven.be

African Geographical Review, 2013Vol. 32, No. 1, 44–58, http://dx.doi.org/10.1080/19376812.2012.746093

� 2013 The African Specialty Group of the Association of American Geographers

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2nd and 8th world biggest cashew nut producing countries (FAO, 2011). Most of the cashewnuts are exported as raw nuts to India, where they are processed before being re-exported toEurope or North America (URT, 2008). Paradoxically, while South Eastern Tanzania isembedded in the world trade through the cashew production, due to the poor road infrastruc-ture has been isolated from the rest of the country and has often been regarded a backwardperiphery (Seppälä and Koda, 1998). Widespread planting of cashew trees, which are mostlygrown by smallholders, only took hold in the 1960s (Topper and Kasuga, 2003). At that timepeople in South Eastern Tanzania were living scattered over the area. In the 1970s, they wereresettled into newly created villages as part of the ‘villagisation’ program. Figure 1 illustratesthe impact of the introduction of cashew trees and villagisation on land-use/cover in SouthEastern Tanzania. The aim of the villagisation policy was to achieve rural transformationthrough village settlement schemes as had been recommended by the World Bank in 1960(Lugoe, 2008). By concentrating people in villages it was expected not only to facilitate theprovision of public services, but also to allow for the possibility of large-scale farming and,doing so, to increase productivity. Villagisation was implemented more systematically inSouth Eastern Tanzania than in other parts of the country (Coulson, 1977).

The Makonde plateau is the most important cashew growing area in South EasternTanzania and where land degradation processe s, such as soil erosion (Achten et al., 2008), soilacidification (Ngatunga et al., 2001; 2003) and losses of soil organic carbon (Rossi et al.,

Figure 1. Aerial photographs of 1965 and of 1981 illustrating land-use/cover changes around Lipalwe,at the southern edge of the Makonde plateau: (a) in 1965 people were living scattered and annual cropswere dominating the agricultural landscape (light coloured fields) which were in rotation with abushfallow (dark coloured fields); (b) in 1981 people were living in large villages (arrows); fields on theescarpment, which had annual crops in 1962 had reverted to woodland in 1981 (frame 1), while on theplateau cashew trees, appearing as dark dots, dominate the landscape (frame 2).

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2009), have been linked to land-use/cover changes. As the FAO statistics show (FAO, 2011),following a steady increase in the 1960s cashew nut production reached a peak of 145000 MTin 1973. Thereafter, it went into a catastrophic decline reaching a minimum in 1989 of 17000MT. As resettled people were bound to abandon their fields, this decline has partly been attrib-uted to the villagisation policy. Moreover, during this period, the government took control overthe marketing system leading to producer prices dropping from 70% of the export price in1972 to 24% of it in 1980. Production was further constrained in the 1970s by the outbreak ofpowdery mildew disease (Oidium anacardii Noack), a fungus whose spread was favored bythe many untended trees (Topper and Kasuga, 2003). Cashew nut production only recoveredwith the market liberalization in the 1990s, as farmers were getting favorable prices again(Rweyemamu, 2002). Meanwhile, internationally supported research found that sulfur iseffective to control the disease. The multi-donor funded Cashew Improvement Programpromoted the use of sulfur together with other improved crop husbandry practices, and socontributed to the recovery of the cashew nut production (Topper and Kasuga, 2003).

Understanding the patterns and processes of land-use/cover changes has become a funda-mental goal in studies when investigating the complex interactions between humans and theenvironment (Aldwaik and Pontius, 2012). The standard method for comparing land-use/coverstatus at two points in time is to determine a cross-tabulation matrix comparing swaps andoverall changes in land-use/cover categories. To gain more detailed insights into the land-use/dynamics Pontius, Shusas, and McEachern (2004) proposed to analyze the net change, loss,persistence and gain of land-use/cover categories.

Given the resettlement program, population growth and the increased cashew productionin South Eastern Tanzania, we wanted to assess how these changes may have affected land-use/cover changes. By focusing on in six villages, we particularly wanted to get betterinsights into the forces driving these changes. We therefore not only determined the overallchanges but also investigated how various potential drives may have affected the net change,loss, persistence and gain of areas allocated to settlement, annual crops, cashew orchards andnatural vegetation.

Materials and methods

Description of the study area

The Makonde plateau (38° 03’–40° 30’ E and 10° 05’–11° 25’ S) reaches 120 km inland andis separated from the coast by a narrow plain (Figure 2). Sloping from east to west, its alti-tude ranges from 80 to 927 m above sea level. The eastern, lower part has sharply incisedvalleys and is mapped as the ‘Makonde Dissected Plateau’; the western, higher part ismapped as the ‘Makonde High Plateau’ where a 300 metre high escarpment forms thewestern edge of the plateau.

Natural vegetation on the Makonde plateau is part of the Eastern African coastal forests,which is considered a global biodiversity hotspot (Timberlake et al., 2011). It consists primar-ily of woodlands, wooded grasslands and bushlands. Woodlands and pockets of evergreenforests also occur on the escarpment. The traditional cropping system is a fallow system: afterslashing and burning of forest or fallow vegetation, fields are cultivated for four years withmaize, upland rice, sorghum and cassava. Though cashew trees produce well on the plateau,they only produce below 800 meters above sea level, as at higher altitude the climate is toocold for fruit setting (Dondeyne et al., 2003a).

We studied land-use/cover changes in six villages: two on the Makonde Dissected Plateau(Naliendele, Nachunyu), two on the Makonde High Plateau (Mahuta bondeni, Nambunga)and two at the base of the escarpment (Chiwambo, Lipalwe) (Figure 2).

46 A. Kabanza et al.

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Land-use/cover maps

Land-use cover maps were made based on panchromatic aerial photographs of 1965 (scaleapproximate scale of 1:50,000, Survey and Mapping Division of Tanzania) and which werecompared with land-use/cover maps derived from Landsat TM images from 2002. Aerialphotographs were interpreted using mirror stereoscope. Image interpretation elements andcharacteristics such as relief, drainage pattern, vegetation cover, land-use, association ofobjects and features such as footpath and tracks were taken as key attributes for land coveranalysis following procedures as outlined by Dent and Young (1981) and Lillesand andKiefer (2000). The interpreted features were then used as a base for establishing broad classesof land cover units, which were delineated, digitised and converted into a GIS database(ESRI, 1995) to produce land-use/cover maps of the study sites for 1965 period. These mapswere geo-referenced to Universal Transversal Mercator (UTM) Coordinates zone 37 south,using the topographic maps as reference (sheets: Mtwara 296/3, Tandahimba 307/1, Newala306/4, Namikupa 307/3, Lulindi 306/3).

Landsat TM images of 2002 had been obtained from the US Geological Service.1 Theseimages were digital enhanced with the ERDAS software program (ERDAS, 2003). To rein-force the visual interpretability of the image, a color composite (Landsat TM bands 4 5 3)was prepared and its contrast was stretched using a Gaussian distribution function. Further-more, a 3 � 3 high pass filter was applied to the color composite to further enhance visualinterpretability of linear features, e.g. rivers, and patterns such as cultivation. To ensureaccurate identification of land-use/cover classes and geometric compatibility with informationobtained from aerial photo interpretation, the Landsat TM images were also geo-referenced tothe co-ordinate system of the national topographic maps (UTM37s). Subsequently, land unitsthat could visually be identified as homogenous land-use/cover classes were digitized onscreen using ArcView software (ESRI, 1995) to obtain maps comparable to, and compatiblewith, the ones derived from the aerial photographs.

The preliminary made maps were subsequently verified and corrected after cross checkingin the field in 2004. GPS was used to locate observation sites. Local people were involved togive additional information on land-use/cover.

Figure 2. Location of six study sites on the Makonde plateau in South Eastern Tanzania. Terrainimage derived from SRTMv4 data (available at http://srtm.csi.cgiar.org).

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Data analysis

Changes in land-use/cover between 1965 and 2002 was determined through an overlay analy-sis of the land-use/cover maps (Figure 3) using ArcView (ESRI, 1995). From this a changedetection matrix was derived indicating the area of each land-use/cover categories in 1965

Figure 3. Land-use/cover maps of 1965 based on aerial photographs and of 2002 based on LandSatimages for three village areas of South Eastern Tanzania.

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and 2002 and from which we also derived the relative net change, persistence, gain and lossof each land-use/cover category.

Following Pontius et al. (2004) we adopted the following definitions (see also Table 1);the net change of a land-use/cover category as:

Ni ¼ Ai;t1 � Ai;t2 ð1Þ

with Ni the net change of category i, and determined as the difference between its area (Ai) attime t1 and at time t2. Ni is negative when the total area decreased over time and positivewhen it increased.

The persistence (Aii) is the area which remained under the same land-use/cover category overtime and which, in a standard cross-tabulation matrix, is indicated on the diagonal as in Table 1.

The loss of a category (Li) is the difference between its initial area (Ai,t1) and thepersistence:

Li ¼ Ai;t1 � Aii � 0 ð2Þ

while the gain (Gi) is

Gi ¼ Ai;t2 � Aii � 0 ð3ÞBy combining equations (2) and (3), it can be seen that

Ni ¼ Gi � jLij ¼ Ai;t2 � Ai:t1 ð4Þ

As we wanted to compare land-use/cover changes across different villages we standardized thesevariables to relative values by dividing them by the respective total mapped area. Hence we define:

• the relative net change as ni = Ni/∑Ai;• the relative loss as li = Li/∑Ai;• the relative persistence as pi = Aii/∑Ai, and• the relative gain as gi = Gi/∑Ai.

where ∑Ai is the total mapped area of each of the study villages.

Table 1. General cross-tabulation matrix for comparing land-use/cover categories of two maps fromdifferent points in time.⁄

Time 2

Total time 1 LossCategory 1 Category 2 Category 3 Category 4

Time 1Category 1 A11 A12 A13 A14 A1,t1 A1,t1–A11

Category 2 A21 A22 A23 A24 A2,t1 A2,t1–A22

Category 3 A31 A32 A33 A44 A3,t1 A3,t1–A33

Category 4 A41 A42 A43 A44 A4,t1 A4,t1–A44

Total time 2 A1,t2 A2,t2 A3,t2 A4,t2 Σ Ai

Gain A1,t2 – A11 A2,t2 – A22 A3,t2 – A33 A4,t2 – A44

Source: adapted from Pontius et al. 2004.Note: ⁄The persistence of a category is indicated on the diagonal (indicated in bold); the gross gain and gross loss ofa category are determined as the difference between total area at a given time and the persistence; the differencebetween the gain and the absolute value of the loss equals the net change.

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The official demographic census data from 1965 and 2002 from the Tanzania NationalBureau of Statistics were used to investigate the relation between population dynamicsand land-use cover changes. Average annual population growth rates were calculatedassuming an exponential growth rate. Population density of the villages was estimatedbased on the census data of 2002 per village. How population growth was related to pop-ulation density was analyzed with ordinary least square regression, with a logarithmictransformation.

We determined the Pearson correlation coefficient (as R²) between the relative loss, per-sistence and gain of the settlement, annual crops, cashew orchards, and natural vegetationwith distance of the village center to the main road and with annual population growth. Thedistance to the main road is taken as a proxy for the accessibility of the village. The hypothe-sis was that accessibility and population growth would have a quantifiable influence on theland-use/cover changes. The other socio-economic processes were hypothesized to give ashort compelling story within the secondary data available so no statistical analyses weredone.

Results

The land-use/cover maps derived from the aerial photographs of 1965 and from the Landsatimages of 2002 are illustrated in Figure 3; the changes in areas per land-use/cover categoriesare presented in Table 2. It can be seen on the maps that whereas settlement areas were smalland scattered in 1965, these were agglomerated into large villages in 2002 (Figure 3). Theoverall increase of settlement areas is consistent with the general growth in population pervillage (Figure 4a and 4c). Strikingly average annual population growth is highest where

Figure 4. Demographic changes in relation to net land-use/cover of six villages of South-EasternTanzania.

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Table

2.Land-use/coverchangesbetween19

65and20

02in

sixvillagesof

theMakon

deplateau;

figu

resin

bold

correspo

ndto

grosspersistence.

Area(ha)in

1965

Area(ha)

in2002

Lan

d-use

per

landscap

eunitan

dvilla

geSettlem

ent

Annual

crop

sOrchard

Bushland

Woo

ded

grasslan

dWoo

dland

Forest

Mak

ondeDissected

Plateau

Naliendele

Bushland

1,98

813

236

053

696

0-

--

Ann

ualcrop

s34

535

7392

145

--

-Settlement

155

40

6-

--

Woo

dedgrassland

116

019

889

--

-Bushedgrassland

222

022

100

100

--

-Total

2,68

617

247

881

61,22

0-

--

Nachunyu

Bushland

378

014

773

125

-33

-Ann

ualcrop

s411

410

293

64-

148

-Settlement

90

81

0-

0-

Woo

dedgrasland

1,28

414

366

330

129

-44

5-

Bushedgrassland

60

20

3-

1-

Total

2,08

818

625

497

321

-62

7-

Mak

ondeHighPlateau

Mah

uta

bondeni

Bushland

160

200

122

140

4-

Ann

ualcrop

s45

068

2118

120

016

0-

Orchard

310

027

20

2-

Woo

dland

929

066

6023

078

0-

Settlement

3324

09

00

0-

Woo

dedgrassland

650

344

00

18-

Grassland

250

232

00

0-

Total

1,69

3112

9044

559

096

4-

Nam

bunga

Bushland

948

6547

33

232

-15

421

(Con

tinued)

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Table

2.(Con

tinued)

Area(ha)in

1965

Area(ha)

in2002

Lan

d-use

per

landscap

eunitan

dvilla

geSettlem

ent

Annual

crop

sOrchard

Bushland

Woo

ded

grasslan

dWoo

dland

Forest

Ann

ualcrop

s97

464

610

1116

4-

104

21Woo

dland

457

249

242

-38

00

Bushedgrassland

170

150

0-

02

Settlement

206

140

0-

00

Total

2416

137

1161

3839

8-

638

44

Escarpmentbase

Chiwam

boAnn

ualcrop

s19

30

2686

10

800

Orchard

124

04

102

100

71

Woo

dland

619

0117

172

4027

241

22Forest

280

00

00

028

Woo

dedgrassland

524

2317

321

832

780

0Settlement

81

25

00

00

Total

1,49

624

322

583

8310

532

851

Lipalwe

Bushland

159

1336

93-

-13

-Ann

ualcrop

s45

316

116

198

--

108

-Orchard

616

154

--

0-

Woo

dland

1,02

20

4118

6-

-79

5-

Woo

dedgrassland

219

037

152

--

30-

Grassland

724

214

350

--

22-

Settlement

83

05

--

0-

Woo

dedbu

shland

90

00

--

0-

Total

2,65

540

374

738

--

968

-

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population density was lowest, ranging from 2% in Nachunyu to 0.8% in Mahuta bondeni(Figure 4b).

Though overall, the area under annual crops increased (Figure 4c), this has not been thecase for all villages: in Lipalwe there has been a small net decrease (3%), but most remarked-ly in Mahuta bondeni the net decrease has been 20%. The most pronounced changes howeveris the net increase of cashew orchards (average 18%), which went along with a net reductionof natural vegetation (average –31%) (Figure 4c). Only in Nambunga, did the area withcashew orchards hardly change, because the area is too cool for cashew nuts as it is mostlyabove 700 m a.s.l.

Figure 5. Relative loss, persistence and gain of land-use/cover categories for the period 1965–2002 ofsix villages of South Eastern Tanzania.

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Figure 6. Correlation between the relative loss, persistence and gain of land-use/cover categories anddistance to main road, and annual population growth, of six villages of South Eastern Tanzania for theperiod 1965–2002. The linear regression lines indicate the general trend.

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The relative loss, persistence and gain of the different land-use/cover categories (Figure 5)provide more insights into the land-use/cover dynamics. First, even though the area underannual crops increased, relative large proportions were also ‘lost,’ resulting into shift (gain) inother areas. As the same observation holds for settlement areas, this trend is linked to theresettlement of people. Secondly, the graphs clearly show how cashew orchards became aprominent land-use/cover (Figure 5), while in 1965 it did not even occur in any of the studiedvillages expect for Chiwambo. Thirdly, natural vegetation lost large proportions of land, ofwhich mostly bushland, wooded grassland or woodland, and which has been mostlyconverted to cashew orchards. The patches of evergreen forest were persistent or even gainedsome portions of land.

From the correlation analysis, presented as R² in Figure 6, it can be seen that neitheraccessibility nor population growth had a strong impact on the land-use/cover changes. Onlythe distance to the main road is strongly correlated with the gain in settlement area; thisobservation is however rather trivial, as indeed major settlement areas will be directly servedby a major road. Furthermore, population growth had only a small impact on the relative gainof areas with annual crops. Neither accessibility nor population growth, did have muchimpact on the relatives changes in cashew orchards. They were though weakly correlated tochanges in natural vegetation.

Discussion and conclusions

As argued by Geist and Lambin (2002) and Lambin et al. (2003) land-use/cover changes aredriven by a complex of underlying causes, rather than by often claimed single factors such as‘shifting cultivation’ or ‘increasing population’ pressure. As this case study seems to supportthis point, we discuss the land-use/cover changes following the framework proposed by theseauthors but – even though these are interconnected – we make a distinction between localand global drivers. The concepts of net land-use/cover changes, coupled to loss, persistenceand gain, as proposed by Pontius et al. (2004), proved particularly helpful for analyzing theland-use/cover dynamics.

Demographic change is a first identified local driver for land-use changes. However, asour data indicate, one should be guarded for making a simplistic prediction. While overallpopulation increased and natural vegetation decreased (Figure 4), the correlation betweenthese two variables is weak (Figure 6). Strikingly, in Mahuta bondeni – where populationdensity is the highest – farmers have favored the expansion of cashew orchards over theannual crops (Table 2; Figures 2 and 5). Cashew being an important cash crop, this shift issurely driven by a local economic rationale. Still, given the low fertility of the soils on theMakonde plateau, but which are particularly well suited for cashew nut production(Dondeyne et al., 2003a), this trend also makes sense from an agronomic point of view.Overall the bigger increase of cashew orchards than of annual crops (Table 2, Figure 4c),points to one more case of ‘more people, more trees’ similar to the cases described by Morti-more and Tiffen (1994) in Kenya and Gobin et al. (1998) in Nigeria. At first sight this shiftmay lead one to conclude that it would have resulted in an increase in biomass carbon stockand hence may have contributed to climate change mitigation. However, in line with theargument made by Lambin and Meyfroidt (2011), specialising in a tree crop at the expenseof food crops will have led to a displacement of land-uses/covers where some other areasmay become deforested.

Rural development and land-use policies are a second local driver. The ‘villagisation’policy affected the distribution of people and land-use/cover with, as a first obviousconsequence, the creation of large, semi-urban villages. However, whereas Kikula (1997)argued that the villagisation program would have many long-term negative impacts, it is hard

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to identify such a single consequence on the Makonde plateau as in some areas, land wasabandoned and was reverted to bushland, woodland and even forests (Figure 1, Table 2,Figure 5). Villagisation however also affected land tenure, whereby people claiming descen-dance from first settlers have the strongest control over access to land. Land with casheworchards is typically controlled by elderly men, and the ensuing scarcity of good land is oftena source of social conflict (Dondeyne et al., 2003b; Becker, 2006). Whereas Bennett et al.(1979) mentioned that fallow period of up to 10 years was the rule in the 1970s, it is nowonly practiced by a minority of farmers.

The international cashew trade is obviously a first global driver which affected land-use/cover changes in South Eastern Tanzania. Price fluctuation will have influenced farmersdecisions when expanding cashew orchards which, since the economic liberalisation isstrongly influenced by the price in India (URT, 2008).

The introduction of new technologies is a second global driver. Obviously, the introduc-tion in the 1960s of cashew trees in the area heralded a revolution in South EasternTanzania’s landscape. Also, the production of cashew nuts could only recover in the 1990sand, be sustained at the current level, thanks to introduction of new varieties and techniquesto control pests and diseases, introduced through internationally supported research anddevelopment efforts as Topper and Kasuga (2003) reported. The presence of the harbor inMtwara, also puts the Makonde plateau in a comparative advantage to other areas in Tanzaniafor exporting the nuts. This harbor was build in the 1940s, as part of the infamous groundnutscheme, whereby the British authorities wanted to boost the production of edible oils to meettheir demand after the second world war (Coulson, 1977).

As our case studies show, local and global drivers of land-use/cover change led to anoverall reduction of natural vegetation in South-Eastern Tanzania. Both Burgess and Clarke(2000) and Timberlake et al. (2011) have argued that these vegetation types are of globalinterest in terms of biodiversity, but how these land-use/cover changes affected biodiversityhas not been investigated yet. The question of the sustainability of cashew nut productionalso remains unresolved. Of concern are the sensitivity of the soils of the Makonde plateaufor acidification, particularly due to the use of sulfur which is applied as a fungicide incashew groves (Ngatunga et al., 2001; Ngatunga, Dondeyne, and Deckers, 2003) and organiccarbon losses (Rossi et al., 2009), as well as their sensitivity to the formation of erosion gul-lies (Achten et al., 2008). The latter is very much a function of the effect of cashew groveson the local hydrology, a matter still being studied.

AcknowledgementThis study was conducted as part of the ‘Soil Conservation Management Project’ (ZEIN’2002’PR253)funded by the Flemish Inter-University Council (VLIR, Belgium) in partnership with the NaliendeleAgricultural Research Institute, Ministry of Agriculture and Food Security (Tanzania). Many thanks aredue to Mr Proches Hieronimo who provided assistance in the use of GIS and remote sensing.

Note1. Product: ETM+ L1T; path/row 165/67, 68, Scene information: ID: LE71650682002132SGS00,

Clouds Cover: 0% Date: 2002/5/12.

Notes on contributorsAndrew Kaggwa Kabanza is an Agricultural Research Scientist stationed at Naliendele AgriculturalResearch Institute, Mtwara, Tanzania. His research interests are land-use and evaluation, soil erosion,soil erosion control, soil and water conservation and natural resources management.

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Stefaan Dondeyne is a Research Fellow at the Department of Earth and Environmental Sciences KULeuven, Belgium. His research interests are soil geography, vegetation ecology, natural resourcesmanagement, participatory research and development approaches.

John Jasper Tenga is a senior Agricultural Research Scientist at Naliendele Agricultural ResearchInstitute Mtwara, Tanzania. His research interests are land-use planning, soil and water conservation andsoil fertility management.

Didas Nahumu Kimaro is an Associate Professor of Land and Water Management at the SokoineUniversity of Agriculture, Tanzania. His research interests are land-use/cover change, land-use planning,soil and water conservation, land degradation, landscape geography, ecology and health.

Jean Poesen is a Professor at the Department of Earth and Environmental Sciences, KU Leuven,Belgium. His research interests are in physical geography, geomorphology, land degradation, soil andwater conservation.

Elly Kafiriti is the Director for Research and Development at Naliendele Agricultural Research Institute,Mtwara, Tanzania. His research interests are participatory research with special interest in agronomy andbreeding of sesame, groundnuts and rice.

Jozef Deckers is a Professor of Soil Geography at the Department of Earth and Environmental Sciences,KU Leuven, Belgium. His research interests are soil geography, land evaluation, soil conservation, soilfertility management, sustainable farming systems in the tropics.

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