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

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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.
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Article
An Analysis of the Causes of Deforestation in
Malawi: A Case of Mwazisi
Susan Ngwira 1, * and Teiji Watanabe 2,*
1Graduate School of Environmental Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan
2Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan
*Correspondence: susanngwira1@gmail.com (S.N.); teiwata@mac.com (T.W.)
Received: 4 February 2019; Accepted: 11 March 2019; Published: 15 March 2019

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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 [2123]
, 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
to identify and analyze forest cover change and the underlying driving factors associated with the
proximate factors of deforestation on customary land in the rural area of Mwazisi, Malawi (Figure 1),
where no research about the drivers of deforestation has been conducted to date.
Land 2019, 8, x FOR PEER REVIEW 3 of 14
the proximate factors of deforestation on customary land in the rural area of Mwazisi, Malawi (Figure
1), where no research about the drivers of deforestation has been conducted to date.
Figure 1. Location of the study area.
2. Materials and Methods
2.1. Study Area
The Mwazisi zone, which is the customary land, is located to the west of the Rumphi district in
the northern region of Malawi. It consists of six Village Development Committees (VDCs) under the
Traditional Authority Chikulamayembe. Traditional Authority is a form of leadership in which the
authority of an organization or a ruling regime is largely tied to tradition or custom. The Mwazisi
zone is located along Vwaza Marsh Game Reserve (VMGR) and covers an area of 117 km², which
contains 1126 households. The total population of the study area is estimated to be approximately
6570. The area is mostly covered by Miombo woodlands with an average temperature of 22.5 °C in
the hot dry season [36]. The highest average annual precipitation falls in the month of January is 191
mm.
2.2. Methods
To detect changes in forest cover over a long time span [37–41], Landsat 5 Thematic Mapper (19
June, 1991 and 6 June, 2004) and Landsat 8 Operational Land Imager (25 May, 2017) images were
downloaded from the United States Geological Survey website [37]. ArcGIS 10.2 software was used
to preprocess (radiometric correction) the images. Preprocessing of satellite images prior to change
detection is essential and aims to establish a more direct linkage between the data and biophysical
phenomena [42]. The forest cover maps were generated using a maximum likelihood classifier.
Owing to an overlap of spectral signatures among classes, land cover was classified into two
categories: (1) forest cover, comprising forests and shrubs, and (2) non-forest cover, comprising built-
up, grass, and agriculture lands. Roofing materials, such as grass, made it difficult to separate built-
up areas from either agriculture or grass land. Before spatial analysis and a temporal comparison,
accuracy assessment was performed on each image by randomly selecting 100 sample points. The
sample points were then imported into the Google Earth for comparison. The overall accuracy of
classification was 96% for 1991 image, 94% for 2004 image, and 93% for 2017 image. The Kappa
coefficients of the classification were 0.92, 0.88, and 0.86 for 1991, 2004, and 2017, respectively.
Socioeconomic data on proximate and underlying factors [30] were collected using interviews,
focus group discussion, and field observations in August 2017; these methods are used by many
researchers in analyzing the factors of deforestation (for example, [34,43,44]). Structured interviews
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. The
Figure 1. Location of the study area.
2. Materials and Methods
2.1. Study Area
The Mwazisi zone, which is the customary land, is located to the west of the Rumphi district in
the northern region of Malawi. It consists of six Village Development Committees (VDCs) under the
Traditional Authority Chikulamayembe. Traditional Authority is a form of leadership in which the
authority of an organization or a ruling regime is largely tied to tradition or custom. The Mwazisi zone
is located along Vwaza Marsh Game Reserve (VMGR) and covers an area of 117 km
2
, which contains
1126 households. The total population of the study area is estimated to be approximately 6570.
The area is mostly covered by Miombo woodlands with an average temperature of 22.5
C in the hot
dry season [36]. The highest average annual precipitation falls in the month of January is 191 mm.
2.2. Methods
To detect changes in forest cover over a long time span [
37
41
], Landsat 5 Thematic Mapper
(19 June, 1991 and 6 June, 2004) and Landsat 8 Operational Land Imager (25 May, 2017) images
were downloaded from the United States Geological Survey website [
37
]. ArcGIS 10.2 software
was used to preprocess (radiometric correction) the images. Preprocessing of satellite images prior
to change detection is essential and aims to establish a more direct linkage between the data and
biophysical phenomena [
42
]. The forest cover maps were generated using a maximum likelihood
classifier. Owing to an overlap of spectral signatures among classes, land cover was classified into
two categories: (1) forest cover, comprising forests and shrubs, and (2) non-forest cover, comprising
built-up, grass, and agriculture lands. Roofing materials, such as grass, made it difficult to separate
built-up areas from either agriculture or grass land. Before spatial analysis and a temporal comparison,
accuracy assessment was performed on each image by randomly selecting 100 sample points.
The sample points were then imported into the Google Earth for comparison. The overall accuracy
of classification was 96% for 1991 image, 94% for 2004 image, and 93% for 2017 image. The Kappa
coefficients of the classification were 0.92, 0.88, and 0.86 for 1991, 2004, and 2017, respectively.
Socioeconomic data on proximate and underlying factors [
30
] were collected using interviews,
focus group discussion, and field observations in August 2017; these methods are used by many
researchers in analyzing the factors of deforestation (for example, [
34
,
43
,
44
]). Structured interviews
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
The sample size was calculated using Cochran’s (1963:75) formula [
45
] below to secure the
representativeness of the community:
n= (Z2p(1 p))/e2(1)
where nis the sample size, Zis constant, eis the level of precision, and pis the estimated proportion
of an attribute. The purpose of the household survey was to understand socioeconomic conditions,
forest dependency, and the awareness of local people regarding forest use and management, i.e.,
to examine economic and institutional factors as the underlying factors.
Interviews were also conducted with two officers from the Forestry Department and one officer
from the Department of Parks and National Wildlife, as well as two members of the Natural Resources
Committee (NRC), to identify problems and the current condition of forests in the study area. The focus
group discussion was conducted with officers from the Department of Agriculture regarding forest
management and challenges. Through the interviews and the focus group discussion, institutional
factors as part of the underlying factors were examined.
Field observations were also conducted in the farms and forests during the social surveys in 2017.
Photographs were taken to illustrate some of the causes of deforestation in the study area.
Secondary data such as, the prices of tobacco, maize, groundnuts, and soybeans and tobacco
farming practices, were collected from the Tobacco Control Commission of Malawi (TCCM),
the Agricultural Development and Marketing Corporation (ADMARC), the National Association
of Smallholder Farmers (NASFAM), the Labor Office, the Forestry Department, and the reports to
analyze the economic factors.
3. Results
3.1. Forest Change Analysis
The results of the classification show that forest was the dominant land cover in the year 1991
(Figure 2a); however, it has declined tremendously over the years. Forest covered 66% of the area in
1991 and decreased to 45.8% in 2017 (Table 1). The annual rate of forest cover loss between 1991 and
2004 was 1.3% and increased to 1.6% in the period between 2004 and 2017.
Land 2019, 8, x FOR PEER REVIEW 4 of 14
sample size was calculated using Cochran’s (1963:75) formula [45] below to secure the
representativeness of the community:
n = (Z²p (1 − p))/e² (1)
where n is the sample size, Z is constant, e is the level of precision, and p is the estimated proportion
of an attribute. The purpose of the household survey was to understand socioeconomic conditions,
forest dependency, and the awareness of local people regarding forest use and management, i.e., to
examine economic and institutional factors as the underlying factors.
Interviews were also conducted with two officers from the Forestry Department and one officer
from the Department of Parks and National Wildlife, as well as two members of the Natural
Resources Committee (NRC), to identify problems and the current condition of forests in the study
area. The focus group discussion was conducted with officers from the Department of Agriculture
regarding forest management and challenges. Through the interviews and the focus group discussion,
institutional factors as part of the underlying factors were examined.
Field observations were also conducted in the farms and forests during the social surveys in
2017. Photographs were taken to illustrate some of the causes of deforestation in the study area.
Secondary data such as, the prices of tobacco, maize, groundnuts, and soybeans and tobacco
farming practices, were collected from the Tobacco Control Commission of Malawi (TCCM), the
Agricultural Development and Marketing Corporation (ADMARC), the National Association of
Smallholder Farmers (NASFAM), the Labor Office, the Forestry Department, and the reports to
analyze the economic factors.
3. Results
3.1. Forest Change Analysis
The results of the classification show that forest was the dominant land cover in the year 1991
(Figure 2a); however, it has declined tremendously over the years. Forest covered 66% of the area in
1991 and decreased to 45.8% in 2017 (Table 1). The annual rate of forest cover loss between 1991 and
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
Figure 2. Forest cover maps of Mwazisi in (a) 1991; (b) 2004; and (c) 2017.
Table 1. Change in forest cover from 1991 to 2017.
Land Cover
1991 2004 2017
Area (ha)
% Area (ha)
% Area (ha)
%
Forest 7718.76 66.0 6560.37 56.1 5364.18 45.8
Non-forest
3983.85 34.0 5142.24 43.9 6338.43 54.2
Total area 11,702.61
100.0
3.2. Drivers of Deforestation
3.2.1. Proximate Factors of Deforestation
Agriculture Expansion
Interviews show that most households (80.7%) depend on agriculture to support their daily
livelihood while only 19.3% earn their living through business and employment. All households
grow a crop of maize as a staple food, and for the past 15 years, 47.6% of the households have
expanded their maize farm (Figures 3 and 4). On average, each household has expanded its
agriculture land by approximately 0.57 hectares during the past 15 years. Most households (91.2%)
expanded their maize farms due to an increase in family size (on average, each household has four
children) and a lack of farm inputs. The Pearson product-moment correlation coefficient also shows
a positive correlation between the frequency of the agriculture expansion and the number of children
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 2. Forest cover maps of Mwazisi in (a) 1991; (b) 2004; and (c) 2017.
Table 1. Change in forest cover from 1991 to 2017.
Land Cover 1991 2004 2017
Area (ha) % Area (ha) % Area (ha) %
Forest 7718.76 66.0 6560.37 56.1 5364.18 45.8
Non-forest 3983.85 34.0 5142.24 43.9 6338.43 54.2
Total area 11,702.61 100.0
3.2. Drivers of Deforestation
3.2.1. Proximate Factors of Deforestation
Agriculture Expansion
Interviews show that most households (80.7%) depend on agriculture to support their daily
livelihood while only 19.3% earn their living through business and employment. All households grow
a crop of maize as a staple food, and for the past 15 years, 47.6% of the households have expanded
their maize farm (Figures 3and 4). On average, each household has expanded its agriculture land by
approximately 0.57 hectares during the past 15 years. Most households (91.2%) expanded their maize
farms due to an increase in family size (on average, each household has four children) and a lack of farm
inputs. The Pearson product-moment correlation coefficient also shows a positive correlation between
the frequency of the agriculture expansion and the number of children in a household (correlation =
0.3764, p= 4.949 ×106).
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.
Table 1. Change in forest cover from 1991 to 2017.
Land Cover
1991 2004 2017
Area (ha)
% Area (ha)
% Area (ha)
%
Forest 7718.76 66.0 6560.37 56.1 5364.18 45.8
Non-forest
3983.85 34.0 5142.24 43.9 6338.43 54.2
Total area 11,702.61
100.0
3.2. Drivers of Deforestation
3.2.1. Proximate Factors of Deforestation
Agriculture Expansion
Interviews show that most households (80.7%) depend on agriculture to support their daily
livelihood while only 19.3% earn their living through business and employment. All households
grow a crop of maize as a staple food, and for the past 15 years, 47.6% of the households have
expanded their maize farm (Figures 3 and 4). On average, each household has expanded its
agriculture land by approximately 0.57 hectares during the past 15 years. Most households (91.2%)
expanded their maize farms due to an increase in family size (on average, each household has four
children) and a lack of farm inputs. The Pearson product-moment correlation coefficient also shows
a positive correlation between the frequency of the agriculture expansion and the number of children
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).
Land 2019,8, 48 6 of 15
Land 2019, 8, x FOR PEER REVIEW 6 of 14
Figure 4. Land being cleared for farming (Photo by Teiji Watanabe, 7 August 2017).
Tobacco Growing
Tobacco is the main cash crop in the area and is grown by 45.4% of households, while the
remaining households depend on subsistence farming. Of the tobacco farmers, 46.4% expanded their
agriculture land by an average of approximately 0.39 hectares per year. These farmers expanded their
agriculture land mainly to increase earnings or profit. The type of tobacco grown in the study area is
burley, which is air-cured in barns. Figure 5 shows that 69% of the farmers extracted wood from the
forest (including ropes and twigs) to construct the barns (Figure 6).
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).
Brick Burning
There are three types of building materials in Mwazisi: clay bricks, mud, and wood. Clay bricks
are the main building material and are used by 65.7% of the households (Figure 7). Clay bricks are
Figure 4. Land being cleared for farming (Photo by Teiji Watanabe, 7 August 2017).
Tobacco Growing
Tobacco is the main cash crop in the area and is grown by 45.4% of households, while the
remaining households depend on subsistence farming. Of the tobacco farmers, 46.4% expanded their
agriculture land by an average of approximately 0.39 hectares per year. These farmers expanded their
agriculture land mainly to increase earnings or profit. The type of tobacco grown in the study area is
burley, which is air-cured in barns. Figure 5shows that 69% of the farmers extracted wood from the
forest (including ropes and twigs) to construct the barns (Figure 6).
Land 2019, 8, x FOR PEER REVIEW 6 of 14
Figure 4. Land being cleared for farming (Photo by Teiji Watanabe, 7 August 2017).
Tobacco Growing
Tobacco is the main cash crop in the area and is grown by 45.4% of households, while the
remaining households depend on subsistence farming. Of the tobacco farmers, 46.4% expanded their
agriculture land by an average of approximately 0.39 hectares per year. These farmers expanded their
agriculture land mainly to increase earnings or profit. The type of tobacco grown in the study area is
burley, which is air-cured in barns. Figure 5 shows that 69% of the farmers extracted wood from the
forest (including ropes and twigs) to construct the barns (Figure 6).
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).
Brick Burning
There are three types of building materials in Mwazisi: clay bricks, mud, and wood. Clay bricks
are the main building material and are used by 65.7% of the households (Figure 7). Clay bricks are
Figure 5. Source of wood for barn construction in Mwazisi (n= 181).
Land 2019, 8, x FOR PEER REVIEW 6 of 14
Figure 4. Land being cleared for farming (Photo by Teiji Watanabe, 7 August 2017).
Tobacco Growing
Tobacco is the main cash crop in the area and is grown by 45.4% of households, while the
remaining households depend on subsistence farming. Of the tobacco farmers, 46.4% expanded their
agriculture land by an average of approximately 0.39 hectares per year. These farmers expanded their
agriculture land mainly to increase earnings or profit. The type of tobacco grown in the study area is
burley, which is air-cured in barns. Figure 5 shows that 69% of the farmers extracted wood from the
forest (including ropes and twigs) to construct the barns (Figure 6).
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).
Brick Burning
There are three types of building materials in Mwazisi: clay bricks, mud, and wood. Clay bricks
are the main building material and are used by 65.7% of the households (Figure 7). Clay bricks are
Figure 6. Barn for burley tobacco curing (Photo by Susan Ngwira, 9 August 2017).
Land 2019,8, 48 7 of 15
Brick Burning
There are three types of building materials in Mwazisi: clay bricks, mud, and wood. Clay bricks
are the main building material and are used by 65.7% of the households (Figure 7). Clay bricks are
burned before their use in construction and the source of energy is wood (Figure 8). Of the brick-walled
houses in the area, 68% used wood from the forests and 31% used wood left over after the clearing
of land for agriculture. Field results show that each brick-walled house used 4 metric tons of wood,
on average.
Land 2019, 8, x FOR PEER REVIEW 7 of 14
burned before their use in construction and the source of energy is wood (Figure 8). Of the brick-
walled houses in the area, 68% used wood from the forests and 31% used wood left over after the
clearing of land for agriculture. Field results show that each brick-walled house used 4 metric tons of
wood, on average.
Figure 7. Building materials used in Mwazisi (n = 399).
Figure 8. Clay bricks being packed for burning (Photo by Teiji Watanabe, 7 August 2017).
3.2.2. Underlying Driving Factors
Economic Factors
An analysis of the market systems of various crops grown in the area shows that tobacco has a
well-developed market structure designed to reach smallholder farmers in the rural areas [5,46–50].
The tobacco crops are sold to international companies based in the capital city of Lilongwe. The
tobacco growing is practiced as a form of contract farming, which helps smallholder farmers by
providing access to the market, inputs, and extension services [51]. That is, tobacco companies
provide loans, expertise, and transportation of the farm produce to the tobacco market. However, it
is more expensive and difficult for smallholder farmers to obtain expertise and loans on crops such
as ground nuts, maize, and soybeans. This has resulted in an increase in the number of tobacco
farmers despite its impact on the forests and environment.
A comparison of the average price of tobacco crop with others grown in the area, such as maize,
groundnuts, and soybeans, shows that tobacco has had the highest average price over the years
(Figure 9a). 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 (Figure 9b) shows
that maize has the highest average yield, followed by groundnuts.
Figure 7. Building materials used in Mwazisi (n= 399).
Land 2019, 8, x FOR PEER REVIEW 7 of 14
burned before their use in construction and the source of energy is wood (Figure 8). Of the brick-
walled houses in the area, 68% used wood from the forests and 31% used wood left over after the
clearing of land for agriculture. Field results show that each brick-walled house used 4 metric tons of
wood, on average.
Figure 7. Building materials used in Mwazisi (n = 399).
Figure 8. Clay bricks being packed for burning (Photo by Teiji Watanabe, 7 August 2017).
3.2.2. Underlying Driving Factors
Economic Factors
An analysis of the market systems of various crops grown in the area shows that tobacco has a
well-developed market structure designed to reach smallholder farmers in the rural areas [5,46–50].
The tobacco crops are sold to international companies based in the capital city of Lilongwe. The
tobacco growing is practiced as a form of contract farming, which helps smallholder farmers by
providing access to the market, inputs, and extension services [51]. That is, tobacco companies
provide loans, expertise, and transportation of the farm produce to the tobacco market. However, it
is more expensive and difficult for smallholder farmers to obtain expertise and loans on crops such
as ground nuts, maize, and soybeans. This has resulted in an increase in the number of tobacco
farmers despite its impact on the forests and environment.
A comparison of the average price of tobacco crop with others grown in the area, such as maize,
groundnuts, and soybeans, shows that tobacco has had the highest average price over the years
(Figure 9a). 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 (Figure 9b) shows
that maize has the highest average yield, followed by groundnuts.
Figure 8. Clay bricks being packed for burning (Photo by Teiji Watanabe, 7 August 2017).
3.2.2. Underlying Driving Factors
Economic Factors
An analysis of the market systems of various crops grown in the area shows that tobacco has a
well-developed market structure designed to reach smallholder farmers in the rural areas [
5
,
46
50
].
The tobacco crops are sold to international companies based in the capital city of Lilongwe. The tobacco
growing is practiced as a form of contract farming, which helps smallholder farmers by providing
access to the market, inputs, and extension services [
51
]. That is, tobacco companies provide loans,
expertise, and transportation of the farm produce to the tobacco market. However, it is more expensive
and difficult for smallholder farmers to obtain expertise and loans on crops such as ground nuts, maize,
and soybeans. This has resulted in an increase in the number of tobacco farmers despite its impact on
the forests and environment.
A comparison of the average price of tobacco crop with others grown in the area, such as maize,
groundnuts, and soybeans, shows that tobacco has had the highest average price over the years
Land 2019,8, 48 8 of 15
(Figure 9a). 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 (Figure 9b) shows
that maize has the highest average yield, followed by groundnuts.
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
Rumphi is 3.4% [52]. This has resulted in an increase in demand for land for both settlement and
agriculture.
Figure 11. Population of the Rumphi district 1977–2008 and projected population 2012–2016. Data
source: National Statistical Office (2016) and IHS4 (2017).
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.
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
Rumphi is 3.4% [52]. This has resulted in an increase in demand for land for both settlement and
agriculture.
Figure 11. Population of the Rumphi district 1977–2008 and projected population 2012–2016. Data
source: National Statistical Office (2016) and IHS4 (2017).
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 Rumphi is 3.4% [
52
]. This has resulted in an increase in demand for land for both settlement
and agriculture.
Land 2019,8, 48 9 of 15
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
Rumphi is 3.4% [52]. This has resulted in an increase in demand for land for both settlement and
agriculture.
Figure 11. Population of the Rumphi district 1977–2008 and projected population 2012–2016. Data
source: National Statistical Office (2016) and IHS4 (2017).
Figure 11.
Population of the Rumphi district 1977–2008 and projected population 2012–2016. Data
source: National Statistical 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
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.
Land 2019,8, 48 10 of 15
Land 2019, 8, x FOR PEER REVIEW 9 of 14
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
decreased from 66.0% in 1991 to 45.8% in 2017 (Table 1). The high rate of the deforestation is partly
owing to agriculture expansion, the liberalization of tobacco farming after 1995, and brick burning.
Figure 12. Summary of the interaction between underlying and proximate factors of deforestation in
Mwazisi.
Figure 12.
Summary of the interaction between underlying and proximate factors of deforestation
in 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 (Table 1). 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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... Our findings demonstrate that the third largest key LC change process was the "loss of treedominated savanna", mainly converting to rainfed cropland and shrubland (e.g., dry forest disturbances leading to a degraded dry forest). Although we report a net increase in deciduous tree cover in SSA with the majority of nations exhibiting a similar pattern, we also report large losses in deciduous tree cover in Mozambique (Silva et al., 2019;Sedano et al., 2020), Tanzania (Nzunda and Midtgaard, 2019;Mayes et al., 2015), Angola (Schneibel et al., 2017;Cabral et al., 2011), Malawi (Ngwira and Watanabe, 2019;Gondwe et al., 2019) and ...
... Mozambique (Jansen et al., 2008;Cramer, 1999) and Malawi (Ngwira and Watanabe, 2019) is one of the most widely recognised in the Miombo woodlands region. It has been reported that the expansion of tobacco cultivation in this region always comes at an expensive environmental cost since 1 kg of cured tobacco requires about 12 kg of firewood (Jew et al., 2017) with evidence of recent shifting cultivation occurring in the Miombo region (McNicol et al., 2015). ...
... The reduction of natural vegetation cover in Africa was the largest of all continents and the net natural vegetation cover lost in Africa contributed an astonishing 91% of the global net loss. Although the overall net change in forest cover was a net gain, there were considerable high deforestation rates in individual countries including Malawi (Ngwira and Watanabe, 2019) and Liberia (Enaruvbe et al., 2019), mainly due to the expansion of commercial crops such as tobacco in the former and rubber in the latter. ...
Thesis
Full-text available
Changes in global land cover (LC) have significant consequences for global environmental change, impacting the sustainability of biogeochemical cycles, ecosystem services, biodiversity, and food security. Different forms of LC change have taken place across the world in recent decades due to a combination of natural and anthropogenic drivers, however, the types of change and rates of change have traditionally been hard to quantify. This thesis exploits the properties of the recently released ESA-CCI-LC product – an internally consistent, high-resolution annual time-series of global LC extending from 1992 to 2018. Specifically, this thesis uses a combination of trajectories and transition maps to quantify LC changes over time at national, continental and global scales, in order to develop a deeper understanding of what, where and when significant changes in LC have taken place and relates these to natural and anthropogenic drivers. This thesis presents three analytical chapters that contribute to achieving the objectives and the overarching aim of the thesis. The first analytical chapter initially focuses on the Nile Delta region of Egypt, one of the most densely populated and rapidly urbanising regions globally, to quantify historic rates of urbanisation across the fertile agricultural land, before modelling a series of alternative futures in which these lands are largely protected from future urban expansion. The results show that 74,600 hectares of fertile agricultural land in the Nile Delta (Old Lands) was lost to urban expansion between 1992 and 2015. Furthermore, a scenario that encouraged urban expansion into the desert and adjacent to areas of existing high population density could be achieved, hence preserving large areas of fertile agricultural land within the Nile Delta. The second analytical chapter goes on to examine LC changes across sub-Saharan Africa (SSA), a complex and diverse environment, through the joint lenses of political regions and ecoregions, differentiating between natural and anthropogenic signals of change and relating to likely drivers. The results reveal key LC change processes at a range of spatial scales, and identify hotspots of LC change. The major five key LC change processes were: (i) “gain of dry forests” covered the largest extent and was distributed across the whole of SSA; (ii) “greening of deserts” found adjacent to desert areas (e.g., the Sahel belt); (iii) “loss of tree-dominated savanna” extending mainly across South-eastern Africa; (iv) “loss of shrub-dominated savanna” stretching across West Africa, and “loss of tropical rainforests” unexpectedly covering the smallest extent, mainly in the DRC, West Africa and Madagascar. The final analytical chapter considers LC change at the global scale, providing a comprehensive assessment of LC gains and losses, trajectories and transitions, including a complete assessment of associated uncertainties. This chapter highlights variability between continents and identifies locations of high LC dynamism, recognising global hotspots for sustainability challenges. At the national scale, the chapter identifies the top 10 countries with the largest percentages of forest loss and urban expansion globally. The results show that the majority of these countries have stabilised their forest losses, however, urban expansion was consistently on the rise in all countries. The thesis concludes with recommendations for future research as global LC products become more refined (spatially, temporally and thematically) allowing deeper insights into the causes and consequences of global LC change to be determined.
... About 39.7% of agricultural land in Malawi is degraded (Mbow et al., 2019), and more than 80% of the population resides in rural areas and depend on agriculture and forest resources for their food, energy, and other livelihoods needs but where poverty is disproportionately higher (World Bank, 2019). Urban residents rely on primarily charcoal for their cooking fuel, and urbanization rates are increasing in Malawi (Ngwira & Watanabe, 2019). This combination of factors fueled by rural livelihood aspirations and urbanization reliant on charcoal is a recipe for higher rates of deforestation. ...
... The rate of deforestation/biodiversity loss rates tends to vary spatiotemporally based on local context (e.g., law enforcement, collaborative management, political interference) under which drivers such as population, poverty, market access, and commodity prices operate to influence forest cover, degradation, regeneration, and perceptions of restoration outcomes (FAO & UNEP, 2020). As such, while studies have identified drivers of deforestation and understanding of restoration in Malawi more generally (Ngwira & Watanabe, 2019;Zulu, 2010), knowledge gaps may still exist due to local variations in contextual factors. Our study seeks to identify possible gaps in the understanding of the drivers of deforestation and how farmers perceive forest restoration in smallholder systems where poverty and food insecurity abound. ...
... Farmers identified agricultural land expansion, commercial charcoal production, burnt brick production, and climate change as the main drivers of deforestation in the study context. These observations are similar to findings in other studies in Malawi and subSaharan Africa (Ngwira & Watanabe, 2019;Zulu, 2010;Zulu & Richardson, 2013). An important, albeit nuanced, observation these previous studies have missed is how the interaction of different drivers act to reinforce deforestation. ...
Article
Deforestation drives climate change and reinforces food insecurity in forest‐dependent communities. What drives deforestation varies by location and is shaped by livelihood systems. But how locals perceive restoration is crucial for developing restoration policies. Evidence suggests that applying sustainable farming strategies can potentially restore forests and sustain livelihoods. Applying a broad‐based conceptualization of deforestation and restoration in policymaking, however, results in missed opportunities for addressing deforestation and restoration. Here, we explore the drivers of deforestation, the perceptions of restoration, the challenges to restoration among smallholder farmers in northern Malawi and examine how agroecology can contribute to restoring degraded agroecosystems. Participants report agricultural land expansion, charcoal production, climate change, burnt brick production and government subsidies as the major drivers of deforestation. We observed that though perceptions of forest restoration reflect farmers’ traditional ecological knowledge (TEK) to include reclamation of degraded farmlands, reconstruction of native tree species and replacement of felled trees on farmlands, there are challenges including splitting families to gain access to more subsidized fertilizers and food aid, embedded cultural practices, growing demand for charcoal in cities and weak ecosystem governance structures that hinder the effectiveness of restoration efforts. We, however, do find that agroecological intensification can increase yield from smaller farmlands and allow for larger and longer‐lasting fallows of spare lands which regenerates forests. Key overarching implications of these findings include the need to integrate livelihoods more explicitly into restoration plans, accounting for TEK in restoration policies in forest‐dependent communities and encouraging the adoption of agroecology. This article is protected by copyright. All rights reserved.
... Global temperature rise is the consequence of massive land use and land cover change and major forest loss is also the result of the same. According to ITTO (International Tropical Timber Organization), the current degraded forest land is 850 million ha and it is estimated to rise at the rate of 12.9 million ha/year [16]. Many studies [17,18] have agreed that vegetation could highly influence the global temperature by exchanging the incoming and outgoing energies. ...
... • NS/AP (Decision 1/CP. 16 The current status of REDD+ implementation details in different countries can be accessed from "REDD+ Web Platform". The "Lima REDD+ Information Hub" (decision 9/CP.19) is a part of REDD+ Web Platform which publishes information on REDD+ national strategies, reference levels, safeguards, and forest monitoring systems. ...
Article
Full-text available
Deforestation and forest degradation due to land use, land cover change (LULCC) have become one of the prime contributors to global greenhouse gas (GHG) emissions, after fossil fuel combustion. Greenhouse gas emission from forestry is occurring in the atmosphere as a result of forest biomass combustion, forest fires and decomposition of deadwood materials. This is how increasing carbon dioxide in the atmosphere is adding to the global warming and climate change. Many worldwide recognized studies have measured that forest ecosystems have the capacity to absorb more than 1/3rd of total carbon dioxide from the atmosphere which is the minimum requirement for keeping the atmospheric temperature under 2 °C by 2030. One of the commonly accepted methods for reducing carbon is carbon sequestration through forests. India has committed to capture 2.5 to 3 billion tonnes of CO2 by enhancing forest and tree cover through 2030. To achieve this target, India has adopted REDD+ (Reducing Emissions from Deforestation and Forest Degradation) strategy which aims to mitigate climate change by enhancing forest carbon sequestration through incentivizing forest conservation. Furthermore, this strategy strives to address the drivers of forest degradation and deforestation and also provides a roadmap for forest carbon stocks enhancement and sustainable forest management through REDD+ actions. This study investigates REDD+ contribution against global warming and climate change in India through forest carbon sequestration.
... The Worldwide literature on deforestation [7][8][9][10][11][12][13] identified a number of anthropogenic causes. However, population growth, accessibility and associated socio-economic factors ( Figure 1). ...
Article
Full-text available
Deforestation in remote mountainous regions is considered to be one of the fundamental elements for triggering changes in the biophysical environment driven by various socioeconomic parameters, particularly population growth and road construction in a previously inaccessible environment. A sudden increase in population exerts adverse impacts on the local natural resources, specifically forests. The present study is conducted in Tribal District Kurram, located in the northwestern mountainous belt of Pakistan. This study is aimed to analyze the temporal pattern of deforestation and to explore the impacts of population growth and accessibility on forest cover. It is based on remotely sensed data, focused group discussions, interviews and field observations. The satellite images were processed and classified using ArcGIS and ERDAS IMAGINE. The time span of this study is 1972 to 2019, which is further divided into three periods. The results revealed that almost half (48%) of the forest cover was reduced in ca. five decades. However, considerable variation has been observed in the deforestation rate during the study period. The results of this study revealed that both population change and accessibility have played a vital role in the deforestation process.
... In Malawi, where the majority of the population relies mainly on agriculture, there are severe threats to ecosystems and biodiversity posed by a high rate of deforestation (Government of Malawi, 2016), driven by climate change, agricultural land expansion and other livelihood activities (Ngwira and Watanabe, 2019). About 39.7% of agricultural land in Malawi is degraded (Mbow et al., 2019), and more than 80% of the population reside in rural areas and also rely on agriculture and forest resources for their food, energy and other livelihoods needs, but where poverty is disproportionately higher (World Bank, 2019). ...
Chapter
How can agroecological research methods effectively engage smallholder farmers, who provide over half of the world's food supply, and whose farm management activities have significant impacts on biodiversity and ecosystem services? This question is highly relevant in Malawi where the research took place, but in other low-income countries in Africa with mostly agrarian populations, in which multi-scalar processes drive high food insecurity, alongside declining biodiversity, worsening land degradation and climate change. We analyse an innovative transdisciplinary agroecological approach that attempts to bridge the science-practice-policy gap by examining the potential of agroecological measures to enhance functional biodiversity and ecosystem services. This study involves a longitudinal, case-control and participatory research design in a region where thousands of farmers have experimented with agroecological practices, e.g., legume intercropping, composting, and botanical sprays. Innovative transdisciplinary agroecological research activities involved farmer participatory research, ecological monitoring and field experiments, social science methods (both qualitative and quantitative), participatory methodologies (public participatory Geographic Information Systems - PPGIS and scenario planning and testing) and stakeholder engagement to foster science-policy linkages. We discuss the theoretical and methodological implications of this novel transdisciplinary and participatory approach about pluralism, decolonial and translational ecological research to foster sustainability and climate resilience of tropical farming systems.
... Along the same lines, firewood collection and charcoal production (whether for subsistence needs or as a source of income) are cited as key drivers of deforestation in Tanzania, Côte d'Ivoire, and elsewhere (Nzunda and Midtgaard, 2019;Kouassi et al., 2021). In Malawi, the construction industry is heavily reliant on wood energy for brick production (i.e., brick burning) (Ngwira and Watanabe, 2019). ...
Technical Report
Full-text available
Forest cover has been steadily declining in sub-Saharan Africa, with the area under forest falling from about 734 million hectares in 1990 to about 635 million hectares in 2018, a loss of 98.7 million hectares (based on FAOSTAT data). The rate of forest loss is also accelerating over time, as the average annual decline in forest area was 0.45% in the 1990s, 0.50% in the 2000s, and 0.60% from 2010 to 2018. Somewhat under the radar, medium-scale farms (between 5–100 ha) have emerged as an important category within the agricultural landscape of sub-Saharan Africa. In most African countries, medium-scale farms account for more land under cultivation than large-scale farms, and they have been rapidly growing in numbers. Medium-scale farms account for over 10% of farms in Ghana, Tanzania, and Zambia, and hold an even larger share of total cultivated land: 41% in Ghana, 26% in Nigeria, 47% in Tanzania, and 34% in Zambia. Moreover, the shares of land cultivated and crop production value that are attributed to medium-scale farms have been increasing over time, particularly in land-abundant settings. Medium-scale farms may cause or influence deforestation through both direct and indirect avenues. They can directly cause deforestation by accessing land that had not been previously used—notably, forestland. This forested land can be obtained through several processes: allocation by customary authorities, purchase from other landowners, long-term lease, or transfer of rights by government. Medium-scale farms can also indirectly influence deforestation by contributing to land scarcity, specifically if heightened land scarcity caused (at least partly) by medium-scale farm growth is what spurs smaller farms to revert to carving out forestland. Given the dearth of attention paid to medium-scale farms in sub-Saharan Africa, it is no surprise that few analysts have considered the link between the growth of medium-scale farms and patterns of deforestation. New approaches are needed to understand the links between medium-scale farm growth and deforestation. Because population-based household surveys tend to under-sample relatively large family farms and are therefore not a reliable source of information on medium-scale farms, farm-household surveys can employ stratified sampling or apply a census approach for larger farms. It is also important for these surveys to capture the agricultural ventures of urban-based or otherwise nonresident domestic investors. Several new questions also urgently merit attention in future research on this as-yet overlooked topic. (1) What are the direct and/or indirect links between medium-scale farms and deforestation in sub-Saharan Africa? (2) How does this link vary across different agro-ecologies, commodities, population densities, or land tenure systems? (3) What conditions mitigate the impact of medium-scale farms on deforestation? (4) What policy options would be most effective at limiting deforestation among medium-scale farms or attenuating the indirect link between medium-scale farm growth and deforestation by others? (5) Do the potential policy options differ when this issue is framed, not in terms of deforestation, but in terms of native forest restoration or agroforestry?
... In the Southern African Development Community (SADC) region, Malawi has the highest deforestation, which is represented by a net loss of some 30,000 to 40,000 hectares per year (Mauambeta et al., 2010). This forest loss is mainly attributed to agriculture expansion, infrastructure development, population growth, tobacco growing, brick making and excessive use of biomass (wood, charcoal, and agricultural waste) for cooking (Ngwira & Watanabe, 2019;Gowela & Masamba, 2002;Katumbiet al., 2015). Though the country's forest is declining, the COVID-19 has further led to a decline in forest area as people resolve to forests as an alternative means of livelihood. ...
Article
Full-text available
The rate of deforestation and degradation of forests in Malawi has been remarkably high as a result of high dependency on forests for cooking fuel, expansion of agriculture and population growth. Similarly, forests in Malawi are a source of livelihood, as well as safety nets for rural communities in times of unanticipated scarcity of food or as gap fillers during regular seasonal shortfalls of food supply. The forest sector also supports agriculture which is the backbone of the economy in various ways such as in soil erosion management, soil fertility improvement, and water flow regulation. These have made the forest sector key in economic growth and poverty alleviation in Malawi, which is among the world’s poorest countries. Hence, the forest sector in Malawi is of great importance to sustainable livelihood and development. However, the high dependence on forests particularly among rural households is prone to exacerbate deforestation and degradation of forests in the COVID-19 pandemic era. This is so because Malawi, just like in other parts of the world has experienced a decline in household income and loss of jobs as a result of the pandemic, leading to increased pressure on forests, especially among forest-dependent households. This study looked at the implication of COVID-19 on the forest sector in three ways; the demand and supply of forest products as well as forest management, by reviewing relevant literature. The review showed that the COVID-19 precautionary measures such as restriction of movement and closure of border disrupted the supply chain of forest resources, which resulted in a demand shortage. Also, the ‘work from home” measure, which keeps forest guard away from forests increasing the exploitation of forest and forest conservation training programmes as well as impedes tourism to forest reserves. Therefore, the knowledge of the implication of COVID-19 on Malawi’s forest is core in building a resilient and sustainable post-COVID-19 economy.
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This paper seeks to understand the potential for existing NBS-centered initiatives to better incorporate climate adaptation, thereby contributing to broader adaptation efforts needed to combat the climate emergency. It explores the barriers these initiatives face to offering enhanced adaptation support, as well as existing and new opportunities for accelerating adaptation actions, while improving monitoring and evaluation and capturing lessons learned.
Article
Interventions through co-management (CM) and government-management (GM) for forest reserves can mitigate degradation and deforestation. Few studies have investigated the driving forces of Land Use/Cover Change (LULCC) using Remote sensing and socioeconomic data to assess the impact of management strategies on woodlands. This study investigated factors influencing LULCC in two co-managed and two governmentmanaged forest reserves (FR) between 1999 and 2018 in Malawi. Images from the Environment for Analysing Images and data from respondents representing 30% of the communities surrounding four FR were analysed in SPSS. Woodland loss to grassland, agriculture was observed in Liwonde CM, Kaning'ina and Thambani GM FR. Communities' perceptions confirmed woodland conversion. Population increases and poverty exacerbated agriculture and wood energy use. Up-scaling CM requires improved empowerment processes and capacity building. There is a need to curb corruption, monitor licensing, and develop forest plans and law enforcement in GM FR. Promoting geospatial and socioeconomic analysis tools will enhance forest monitoring.
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Protected areas (PAs) transform over time due to natural and anthropogenic processes, resulting in the loss of biodiversity and ecosystem services. As current and projected climatic trends are poised to pressurize the sustainability of PAs, analyses of the existing perturbations are crucial for providing valuable insights that will facilitate conservation management. In this study, land cover change, landscape characteristics, and spatiotemporal patterns of the vegetation intensity in the Kasungu National Park (area = 2445.10 km2) in Malawi were assessed using Landsat data (1997, 2008 and 2018) in a Fuzzy K-Means unsupervised classification. The findings reveal that a 21.12% forest cover loss occurred from 1997 to 2018: an average annual loss of 1.09%. Transition analyses of the land cover changes revealed that forest to shrubs conversion was the main form of land cover transition, while conversions from shrubs (3.51%) and bare land (3.48%) to forest over the two decades were comparatively lower, signifying a very low rate of forest regeneration. The remaining forest cover in the park was aggregated in a small land area with dissimilar landscape characteristics. Vegetation intensity and vigor were lower mainly in the eastern part of the park in 2018. The findings have implications for conservation management in the context of climate change and the growing demand for ecosystem services in forest-dependent localities.
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Background: Change detection is useful in many applications related to land use and land cover (LULC) changes, such as shifting cultivation and landscape changes, land degradation and desertification. Remotes sensing technology has been used for the detection of the change in land use land cover in upper Rib watershed. The main objective of this study was to detect the land use change using remote sensing for sustainable land use planning in Upper Rib watershed. Methodology: The two satellite images for the year 2007 and 2018 were downloaded and used for detecting the land cover changes. Maximum likelihood classification was used in ERDAS Imagine tool for classifying the images. Ground truth points were collected and used for verification of image classification. Results: The accuracy of image classification were checked using the Ground truth points and the has showed an overall accuracy of 84% and a kappa coefficient of 0.8 which indicates the method of classification and the images used were very good. During this study period an agricultural land has showed an increasing trend by 13.78%, while grassland had decreased by 15.97% due to an increase of interest to cropland area. Conclusion: In Upper Rib watershed, there has been a significant land use change which was due to an increase in population with a high interest to croplands which resulted in an increase of agricultural land by 13.78% over 11 years period.
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Political transitions often trigger substantial environmental changes. In particular, deforestation can result from the complex interplay among the components of a system—actors, institutions, and existing policies—adapting to new opportunities. A dynamic conceptual map of system components is particularly useful for systems in which multiple actors, each with different worldviews and motivations, may be simultaneously trying to alter different facets of the system, unaware of the impacts on other components. In Myanmar a global biodiversity hotspot with the largest forest area in mainland Southeast Asia, ongoing political and economic reforms are likely to change the dynamics of deforestation drivers. A fundamental conceptual map of these dynamics is therefore a prerequisite for interventions to reduce deforestation. We used a system-dynamics approach and causal-network analysis to determine the proximate causes and underlying drivers of forest loss and degradation in Myanmar from 1995 to 2016 and to articulate the linkages among them. Proximate causes included infrastructure development, timber extraction, and agricultural expansion. These were stimulated primarily by formal agricultural, logging, mining, and hydropower concessions and economic investment and social issues relating to civil war and land tenure. Reform of land laws, the link between natural resource extraction and civil war, and the allocation of agricultural concessions will influence the extent of future forest loss and degradation in Myanmar. The causal-network analysis identified priority areas for policy interventions, for example, creating a public registry of land-concession holders to deter corruption in concession allocation. We recommend application of this analytical approach to other countries, particularly those undergoing political transition, to inform policy interventions to reduce forest loss and degradation. This article is protected by copyright. All rights reserved
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Deforestation and forest degradation has been observed to be rampant in Masito-Ugalla ecosystem, Kigoma Region, western part of Tanzania. This paper therefore, intended to assess the extent of deforestation and forest degradation in the area, and to determine their causes. A total of 101 respondents were considered as the sample size for this study. The methods used for data collection were household questionnaire interviews, in-depth interviews, focus group discussions, analysis of satellite images and direct observation. The findings indicated that deforestation was occurring in the study area. Satellite data revealed diminished closed woodland, bushed grassland, forest and thickets between 1990 and 2014. On the contrary, settlement area, cultivated land and open woodland had increased during the same time frame. Proximate factors causing deforestation and forest degradation included agricultural expansion, wood extraction and expansion of settlement area. Underlying factors included population growth, poverty, poor levels of education, lack of employment, corruption and embezzlement of public funds by politicians and senior government officials; and high demand for fuel-wood. Biophysical drivers like incidences of unplanned wildfires and socio trigger events notably civil strife were also important. In order to minimize the problem and based on the factors augmenting deforestation and forest degradation in the Masito-Ugalla ecosystem and their coupled negative consequences, effective environmental conservation education, increased patrols, effective law enforcement and provision of alternative energy sources are necessary.
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Background Deforestation due to tobacco farming began to raise concerns in the mid 1970s. Over the next 40 years, tobacco growing increased significantly and shifted markedly to low- and middle-income countries. The percentage of deforestation caused by tobacco farming reached 4 % globally by the early 2000s, although substantially higher in countries such as China (18 %), Zimbabwe (20 %), Malawi (26 %) and Bangladesh (>30 %). Transnational tobacco companies (TTCs) have argued that tobacco-attributable deforestation is not a serious problem, and that the industry has addressed the issue through corporate social responsibility (CSR) initiatives. Methods After reviewing the existing scholarly literature on tobacco and deforestation, we analysed industry sources of public information to understand how the industry framed deforestation, its key causes, and policy responses. To analyse industry strategies between the 1970s and early 2000s to shape understanding of deforestation caused by tobacco farming and curing, the Truth Tobacco Documents Library was systematically searched. The above sources were compiled and triangulated, thematically and chronologically, to derive a narrative of how the industry has framed the problem of, and solutions to, tobacco-attributable deforestation. Results The industry sought to undermine responses to tobacco-attributable deforestation by emphasising the economic benefits of production in LMICs, blaming alternative causes, and claiming successful forestation efforts. To support these tactics, the industry lobbied at the national and international levels, commissioned research, and colluded through front groups. There was a lack of effective action to address tobacco-attributable deforestation, and indeed an escalation of the problem, during this period. Conclusions The findings suggest the need for independent data on the varied environmental impacts of the tobacco industry, awareness of how the industry seeks to work with environmental researchers and groups to further its interests, and increased scrutiny of tobacco industry efforts to influence environmental policy.
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