Land use and land cover change (LULCC) refers to human modification of the terrestrial surface of the Earth [1
]. The negative impact of LULCC on biodiversity, climate, water, soil, and air, in particular, and on ecosystem services in general, has been recognized as one of the greatest environmental concerns for human populations today [2
]. LULCC is not a recent phenomenon in Ethiopia; for example, the World Resource Institute (WRI) [2
] has reported such events to have occurred during 7000–1800 BCE. However, current LULCC is aggravated by the scale, speed, and long-term nature of civilization [1
Much of the direct change is a consequence of land use, and today about 40% of the land surface is used for agriculture (crops and pasture) [3
]. In addition to cropland, tree plantations, urbanization in order to produce food, timber, housing, and other commodities have resulted in the reduction of many ecosystem services, including biodiversity [4
Globally, agriculture and associated land use changes have been the principal drivers of deforestation and were responsible for 24% of global greenhouse gas (GHG) emissions in 2010 [5
]. From 1970 to 2011, CO2
emissions increased by about 90%, and agriculture, deforestation, and other land use changes have been the second largest sources of global carbon emissions, next to the use of fossil fuels [5
]. Agriculture accounts for 14% of GHG emissions (6.8 Gt of CO2
]. The GHG emissions from this sector are highly likely to increase as humans struggle to increase food production by the required 70% by 2050 [6
]. Tropical deforestation has been responsible for 15%–25% of annual global GHG emissions, and accounts for nearly 70% of total GHG emissions in Africa [7
For example, in Ethiopia, the estimated forest area in 1955 was 17 million ha, but by 1979 it dropped dramatically to 3.4 million ha, with the average annual loss shown in Table 1
]. However, FAO reported that 11.4% of land in Ethiopia is covered by forest [9
]. A highland reclamation study [10
] revealed the consequences of deforestation and permanent removal of other vegetation in the Ethiopian highlands. Accordingly, about 27.5 million ha of the areas examined showed significant signs of accelerated soil erosion, while about 14.5 million ha of land were considered the ‘worst affected areas’ and were recommended to be abandoned [8
LULCC contributes to climate change in Ethiopia. The agriculture sector (livestock, crop, and forestry) contributed 88% of the total GHG emissions in Ethiopia in 2010 [11
]. The total accounted GHG emissions during that period was 150 Mt CO2
e, of which 133 Mt CO2
e was from agriculture. Livestock exhibited the biggest share of GHG emissions (65 Mt CO2
e), followed by forestry (55 Mt CO2
e) and crop production (13 Mt CO2
]. The major activities contributing to GHG emissions in forestry were deforestation for agricultural expansion, forest degradation for fuelwood, and limited formal and informal logging [11
There is uncertainty as to how much the economy of Ethiopia may be affected as a result of the ongoing climate change, but a reduction of 10% or more of the GDP has been projected in all sectors by 2050 [13
]. Mideksa [14
] pointed out that climate change may hit economic development hard in two ways. Firstly, it will reduce agricultural production and output in the sectors linked to agriculture, which is likely to reduce the GDP of Ethiopia by about 10% from its benchmark level. Secondly, it will lead to income inequality in which the Gini coefficient increases by 20%, causing further decline in economic growth, which, in turn, will fuel poverty. (The Gini coefficient is mainly used to measure income inequality. The range of the coefficient is [0,1], with 0 representing perfect equality [15
]). Thus, climate change is expected to increase the proportion of people living in poverty, which ultimately may drive more LULCC.
On top of the impact on the economy, climate change and weather-related impacts in Ethiopia have claimed a lot of lives already. In addition to the number of animal lives lost as a result of the famines during 1972–1973 and 1984–1985, an estimate made by different authors indicated that the lives of 560,000 people were lost [16
]. Historically, more than 40 mass mortality famines are known to have afflicted Ethiopia in the past thousand years [17
]. For example, “The Great Ethiopian Famine” of 1882–92 claimed one-third of the population of Ethiopia [17
]. Despite the fact that human lives continued to be lost, the population in Ethiopia increased four-fold between 1990 and 1998 [18
LULCC analysis has become an important tool to generate evidence for decision-makers, spatial planners, local communities, or actors who are operating within a given landscape to formulate appropriate policies and strategies, generate data for spatial planning, and develop detailed land use plans as well as understand agents of change. Hence, LULCC analysis helps decision-makers ensure sustainable development and understand the dynamics of the changing environment [19
The current debate on the importance of the landscape approach requires sufficient data on land use and land cover to continue to successfully monitor the efficiency of the landscape approach. Therefore, information on spatial and temporal analyses of LULCC becomes indispensable.
Various authors addressed LULCC in Ethiopia, their focus varying greatly in terms of thematic area as well as spatial locations [20
]. However, comprehensive and national scale analysis was conducted by the Woody Biomass Inventory and Strategic Planning Project (WBISPP), which has produced land use and land cover maps for Ethiopia [27
]. All of these studies highlighted that land use and land cover change has an impact on biodiversity, water resources, forest and local livelihoods, among others. The main drivers are linked to farmland expansion and population growth.
LULCC analyses undertaken in the Bale Mountains Eco-Region (BMER) in Ethiopia are limited either spatially or temporally. For example, two studies conducted by different authors concentrated on the Bale Mountain National Park (BMNP) within the BMER, covering some 220,000 ha [28
]. The first study, which was carried out in 2007, detected changes over a period of 33 years by considering the years 1973, 2000, and 2005 [29
]. The second study considered changes over four decades, from 1973 to 2008, focusing specifically on the years 1973, 1987, 2000, and 2008 [30
]. Warra et al. [31
] have also analyzed aerial photographs from 1965 and 1973 and SPOT 5 from 2007 in the Kasso catchment of the BMNP. Another recent land cover analysis was undertaken by the Oromia Forest and Wildlife Enterprise (OFWE) with the support of FARM Africa and SOS Sahel for the preparation of a REDD+ Project Design Document [31
]. The study conducted by OFWE et al. [32
] covered the years 2000, 2005, 2009, and 2011. Spatially, the study that was carried out by OFWE is comparable with the current study, but the area covered in the study was smaller in area by at least 1.5 million ha.
The current study can be considered as a bridge between the studies carried out in 2007, 2012, 2013, and 2014, and similar future analyses. This study covered about 3.8 million ha of the BMER, which none of the above mentioned studies have addressed, and would fill the gap in information at both temporal and spatial scales. Additionally, this study is relevant to the Climate Resilient Green Economy (CRGE) Strategy of Ethiopia [11
] and UN Sustainable Development Goal indicator number 15.
The specific objective of the study was, therefore, to analyze LULCC between 1985 and 2015 in BMER, and identify major land uses that have undergone major changes using Remote Sensing (RS) and Geographic Information System (GIS). The following research questions were addressed: (i) Which LULC types gained or lost most as a result of the observed LULCC? (ii) What are the major drivers of the LULCC/deforestation? and (iii) What was the approximate amount of carbon stock removed as a result of deforestation during the study period?
In this study, three research questions were addressed, i.e., (i) Which LULC type either gained or lost most as a result of the observed LULC changes? (ii) What were the major drivers of the LULC change/deforestation? and (iii) What was the approximate amount of carbon stock removed as a result of deforestation during the study period?
4.1. Gain or Loss of LULC Types in Area Coverage Due to LULCC
The results revealed that farmland gained the most in area compared to other LULC types during the study period (1985–2015). On the contrary, forests lost substantial area (most) during the study period with an annual average deforestation rate of 4661 ha. The forest area decreased from 20.8 to 17.5% while farmland increased from 15.4 to 23.2% during the same period. The other two affected LULC types were shrubland and grassland. The shrubland decreased from 18.2% to 15.8%. Likewise, grassland lost 2.2% within the study period. Urban settlement gained 0.68%. In general, our study is in agreement with previous studies carried out in the area. All of the studies conducted in BMER revealed the expansion of farmland, while forest area exhibited a decreasing trend.
Between 1985 and 1995, an estimated area of 50,271 ha was converted to farmland from the other LULC types. Of this, 37.6%, 35.9%, and 16% represented areas lost from the forest, grassland, and shrubland LULC types, respectively. In the following 10 years (up to 2005), about 48% and 43% of the farmland was gained from forests and shrubland, respectively. Of the total farmland gained between 2005 and 2015, shrubland, forests, and grassland contributed 9%, 43.2%, and 42.3%, respectively.
Gibbs et al. [44
] confirmed that substantial amounts of new cropland in East Africa and South America were derived from shrubland. Farmland expansion in the BMER has intensified at the expense of three main LULC types and, to some extent, through conversion of the Erica-dominated and woodland LULC types. Demand for food for the growing population seems the probable driving force, among others, of farmland expansion from 1985 to 2015. This is justified by the correlation results indicated above. As discussed above, in the eco-region, an area of about 10,575 ha was annually added to farmland, mainly from the removal of forests. This finding is in line with the findings of Foley et al. [45
], who reported that agriculture is expanding in the tropics, and 80% of the area needed for this expansion comes from forests.
The extent of deforestation may vary from one year to another depending on various factors. Sometimes government policies tend to favor food security projects or programs that may intensify the rate of deforestation. For example, Wakjira et al. [46
] showed that local administrators in Harena Buluk District of BMER encouraged inward migration and settlements in the forests and other natural vegetation areas to increase the population of the district. Elections in Ethiopia were conducted during the years 1995, 2000, 2005, 2010, and 2015. The study made by Pailler [47
] demonstrated the presence of a relationship between elections and deforestation via different forms of payoffs, i.e., (i) allocating ‘underdeveloped’ land such as forest to landless individuals to settle and farm; (ii) allowing (legal or illegal) deforestation activities of large-scale agriculture firms; and (iii) increasing agricultural credit for farmers so that they can expand their agriculture land into forest areas. Drought forces many local people to migrate from drought-stricken areas to forest regions where better water, foraging opportunities, and irrigation for agriculture are found. Even though it was not well documented, many people from such areas have migrated and settled in the BMER since the mid-1990s [46
]. This has resulted in deforestation to create land for crop production.
The growth of farmland at the expense of other LULC types in the study area, especially forests, shrubland, and woodland, may be a manifestation of the weak or inappropriate institutional arrangements in the study area [48
]. The weak integration or coordination between and among various sectors that have interest in the landscape, lack of common planning tools capable of monitoring and evaluating the losses and gains of area coverage by the different LULC types and informing stakeholders accordingly, and giving priority to agriculture are among the major factors that have contributed to the observed undesirable losses in the area coverage of the different LULC types, especially forests.
4.2. Major Drivers of LULCC/Deforestation
LULCCs have been widely investigated in different parts of the world, e.g., in the USA and Europe [49
], South America [44
], Australia [51
], Asia, and Africa [44
], including Ethiopia [22
]. These studies have shown that the expansion of agricultural land, both for commercial and subsistence crop production, is the main driver of LULCC [52
]. The rate of cropland expansion worldwide is increasing [44
] at the expense of forests, grassland, shrubland, and other lands. For example, 27% of the tropical forest biome and 70% of the grassland worldwide have been converted to agricultural land [45
]. In East Africa, shrubland accounted for 8% of agricultural land [38
]. The results from this study revealed that the major driver for LULCC is expansion of cropland. This finding is in agreement with results from previous studies [19
Geist and Lambin [54
] confirmed that expansion of cropland and pasture (grazing in this study) accounted for 96% of the cases causing deforestation. They have emphasized that agricultural expansion is the most important proximate source of tropical deforestation. Underlying factors, e.g., poverty, and proximate factors, such as wood extraction and infrastructure development, discussed by Geist and Lambin [54
], were not assessed in the present study. However, OFWE et al. [32
] reported that weak law enforcement and population growth are underlying drivers of deforestation. Agricultural expansion was identified as a key driver of deforestation by OFWE et al. [32
Population growth has contributed to LULCC. For example, the results of a survey carried out by Geist and Lambin [54
] showed that 61% of deforestation was related to human population dynamics. This study also showed that farmland expansion is linked to population growth. A strong correlation was found between population growth and cropland expansion. Therefore, it can be concluded that population growth has driven the expansion of cropland in the area at the expense of grassland, forests, and shrubland. The human population inside the BMNP increased from 2500 in 1998 [50
] to >40,000 in 2003 [28
]. The knock-on effect of population growth on the Ethiopian wolf (Canis simensis
) in the Afromontane parts of the study area has been extensively documented by Randall et al. [55
]. One of the documented challenges, among others, has been genetic erosion of the Ethiopian wolf as a result of uncontrolled breeding with domestic dogs [55
Another driving force for expansion of farmland is, probably, government policy [54
]. Hillman [56
] has reported how the grazing areas used by pastoralists were converted to farmlands to grow crops. As a result, even in the 1980s, a shortage of grazing land for domestic livestock was witnessed, especially during cropping seasons [56
]. Hillman [56
] revealed that the northwestern, northern, and eastern parts of the BMNP or BMER were extensively used by pastoralists. Later on, extensive parts of these areas were allocated for large-scale production of wheat and other crops because of government policy. The pastoralists were forced to settle down through the “villag-ization” program [56
]. According to Teshome et al. [53
], the BMNP lost 12,000 ha of montane forest within 32 years and pastureland expanded at the rate of 2800 ha annually. These reports should not be surprising since the grassland has already been converted to farmland. Farmers had no choice but to use the Erica-dominated and Afroalpine LULC types for grazing their animals. The use of these LULC types for grazing may, subsequently, affect existing water systems and soil formation processes, endangering the sustainable flow of the major rivers (at least four) that spring from the plateau [56
] and serve several Eastern African countries. It can, therefore, be concluded that government policy has played a significant role in LULC dynamics in and around the BMNP.
Despite the fact that PFM and a Protected Area Management System exist in the BMER, encroachment and expansion of farmland to forests and grassland is still a major concern. Observing cattle and other domestic animals in the Erica-dominated and Afroalpine vegetation zones is common. Geist and Lambin [54
] reported that in-migration of farmers into forest zones to expand cropland and pasture was found to be a driver of deforestation in 47% of all the cases studied.
] and other studies (e.g., [44
]) are predicting the need for more food by 2050 because of growth in human populations around the world. The population in Ethiopia is ever-increasing and represents the second largest population in Africa. The annual population growth in the major part of the study area, the Bale Zone, is estimated at 77,000 (see the results section and Figure 7
). Therefore, to feed the growing population, obviously, increasing the area of cropland or farmland overrides other interests. However, when this is done in the absence of proper land use planning, and also when institutions are too weak to enforce the available laws/bylaws developed by user groups, such as Participatory Forest Management (PFM) User Groups [48
], the expansion of farmland becomes unsustainable. It cannot provide the solutions recommended by the FAO and other studies. The world needs a sustainable increase in food production (also consumption). Unsustainable expansion of farmland affects biodiversity (fauna, flora, and micro-organisms) and other ecosystem services, such as the water budget of an area; exposes landscapes to pests and diseases; leads to degradation of land [57
]; and leaves forest-dependent people more vulnerable to poverty. Nune et al. [58
] reported that a significant portion of the household income in BMER comes from forest resources. For example, forests contributed 40.2% and 18.8% to the household income in Harenna Buluk and Nansebo Districts, respectively. A recent publication on land degradation [59
] concluded that people living in and around degraded lands are actually poorer than those in areas that are not degraded.
4.3. Amount of Carbon Stock Removed due to Deforestation
In Africa in general, and Ethiopia in particular, LULCC has been the main driver of GHG emissions [7
]. In 2011, the Ethiopian government declared its intention to reduce GHG emissions to the 2010 level while the growth trajectory would stay in the double digits to make Ethiopia a middle-income country by 2025. One of the mechanisms to reach that stated target is through conservation of forest resources, application of climate-smart agriculture, livestock, and feed management, and the use of renewable energy [12
]. However, even today, emissions from deforestation are being witnessed. As a result of past and present anthropogenic factors as well as problems associated with inappropriate policy and institutional arrangements [58
], substantial amounts of GHGs are released, resulting in other negative impacts on the environment [44
]. About 30%–35% of global GHG emissions come from deforestation as well as methane and nitrous oxide emissions as a result of agricultural practices [45
]. Conservatively, about 24.6 million tons of carbon were removed from forest resources in BMER within the study period. Similarly, from shrubland alone, over 3 million tons of carbon were removed.
OFWE et al. [32
] used an allometric equation developed by Chave et al. [62
] and considered diameter at breast height (dbh) to determine the wood stock/volume in the BMER. Estimating wood stock in natural forests based on dbh alone may underestimate the wood stock or volume since the structure and composition of the forests vary depending on edaphic and other factors. The recommended approach for determining wood stock or volume is the measurement of the length of merchantable logs and diameters at the bottom, middle, and top of the logs. Newton’s formula is the most accurate method to determine the volume of a tree given the proper skill and instruments (such as a Spiegel relaskop to take the three measurements) are available [63
]. Once volume per ha is estimated, carbon stock using Biomass Expansion Factor could be estimated using the method developed by Brown [64
]. Therefore, the estimate made in this study can be improved if the abovementioned approach has been followed. Nevertheless, the estimate made by OFWE et al. [32
] still exceeds the estimate made by the Ethiopian Ministry of Environment, Forest and Climate Change. Very recently, the ministry has reported carbon stocks of 98.9 t of C·ha−1
and 57.7 t of C·ha−1
for Ethiopia in reference to moist and dry Afromontane forests, respectively [65
], whereas OFWE et al. [32
] estimated 191.28 and 126.71 t of C·ha−1
from similar forests, respectively, in BMER. The difference may be due to the approaches used in the estimation of carbon stocks. Also, BMER is a small area compared with the forest lands found in Ethiopia though the sampling intensity used by OFWE et al. [32
] was higher. In general, the method employed by OFWE et al. [32
] provides better results compared with the Tier 1 approach where default values are subject to a wide margin of error since the data are based on certain specific areas (tend to be biased) and biomes (very coarse) [7
Other losses associated with LULCC are GDP and ecosystem service values (ESVs). In the deforested regions of Ethiopia, the topsoil has already been substantially degraded, causing the soil depth to drop to less than 10 cm [66
]. In this region, especially in the highlands, it is estimated that 30,000 ha of productive lands are lost annually as a result of soil erosion. For example, the annual production lost due to soil erosion in the Amhara National Regional State alone is nearly 10,000 tons [27
]. The annual loss of GDP from the agriculture sector in the country has been estimated at 2.3% due to land degradation [67
]. Land degradation is linked to food insecurity, vulnerability to climate change, and poverty [59
]. Hence, land degradation and poverty are becoming inseparable problems for the rural poor. The loss of ESVs due to LULCC has not been investigated in this study. However, it has been shown that in Nenjiang River Basin, Northeast China, all of the ESVs declined from 1980 to 2005 [68
]. The total decline of $2.43 billion was mainly due to the cultivation of grassland (14.34% of the area in 1980) and wetlands (4.62% of the area in 1980) in the downstream plain. Similarly, a study focusing on the analyses of four decades of LULCC in the Munessa-Shashemene landscape, Ethiopia, revealed a loss of ESVs equivalent to $19.3–45.9 million [69
]. It is important to note that the value differs depending on the type of coefficient employed. Given the fact that the BMER ecosystem is one of the most unique ecosystems in the world, the ESVs lost would be unimaginably high. The loss of these EVSs in the BMER, thus, requires urgent investigation.
The unique genetic resources of BMER are under pressure. According to Vial et al. [64
], the population of livestock grazing in the Sanetti Plateau of the Bale Mountains has increased. Also, the production system is leading to the degradation of the habitat of the endemic Ethiopian wolf. This animal species depends on the giant mole-rat (Tachyoryctes macrocephalus
) for food. Both the Ethiopian wolf and giant mole-rat are already on the IUCN list of endangered species [70
] since their populations are declining. The habitat of the giant mole-rat has been highly degraded through trampling by domestic animals. The Ethiopian wolf has been under threat from domestic dogs, which also have the potential to transmit diseases [71
In general, the current drivers of LULCC in BMER are anthropogenic. Intervention in family planning, amongst other things, is required to maintain population growth commensurate to the carrying capacity of the area to ensure environmental sustainability. Equally, creating green jobs that can absorb the available labor force in the rural area to reduce or prevent further LULCC should be on the agenda for action in the future. Furthermore, transdisciplinary policies that equitably address social, economic, and environmental issues in the BMER are required.
Land allocation to different uses in the study area should be made based on principles of land use planning or spatial planning categories. There is a need to match the capability of the land with social needs, economic benefits, and ecological sustainability, and to prioritize interventions in such a way that benefits to present and future generations are ensured. This entails the active engagement of spatial planners [58
]. Failure to engage in such interventions would accelerate the ongoing trends of LULCC with undesirable consequences for the cover of forests, shrubland, and grasslands, and the associated deforestation and degradation of natural resources. This, in turn, would make the achievement of Sustainable Development Goals (SDGs, particularly 15.1, 15.2, 15.4, and 15.5) difficult for Ethiopia (see Box 1 for description of SGDs mentioned in this article). Therefore, a paradigm shift is required towards availing and implementing proper land use policies and dedicated institutions. Moreover, interventions that ensure the sustainable use of environmental resources in the study area need to be designed. Optimum rather than maximum utilization needs to be sought.
Sustainable Development Goal 15 and Its Targets (Source: [72
|15.1||By 2020, ensure the conservation, restoration, and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains, and drylands, in line with obligations under international agreements.|
|15.2||By 2020, promote the implementation of sustainable management of all types of forests, halt deforestation, restore degraded forests, and substantially increase afforestation and reforestation globally. |
|15.4||By 2030, ensure the conservation of mountain ecosystems, including their biodiversity, in order to enhance their capacity to provide benefits that are essential for sustainable development. |
|15.5||Take urgent and significant action to reduce the degradation of natural habitats, halt the loss of biodiversity, and, by 2020, protect and prevent the extinction of threatened species. |
|15.9||By 2020, integrate ecosystem and biodiversity values into national and local planning, development processes, poverty reduction strategies, and accounts. |
Remote sensing and GIS are beneficial tools for monitoring and evaluating temporal and spatial LULCC. Analyses of LULCC over three decades using these tools revealed trends and also which LULC types were affected, either positively or negatively. Landsat imageries are medium-scale remote sensing tools that are ideal for LULCC analyses [36
] of such scales as BMER. Eight major land use and land cover types were identified, and their extent in terms of coverage (ha) was assessed between 1985 and 2015. Finally, although the assessment of classification accuracy was not a simple task [39
], the overall accuracies of these classifications were 85.2%, 87.2%, 76.9%, and 87.9% for 1985, 1995, 2005, and 2015, respectively. BMER encompasses a very large area, and diverse soil types, topography, altitudinal variation, and vegetation density exist. In such situations, classification becomes difficult as a particular land cover, for example grassland, may depict different spectral signatures in the featured space, which is influenced by the agro-ecology in which the particular land cover is found [36
In total, 123,751 ha of forest, 93,078 ha of shrubland, 83,158 ha of grassland, 2473 ha of Erica-dominated land, 3601 ha of woodland, and 3455 ha of Afroalpine vegetation were lost during 1985–2015. The forest LULC type lost the most while farmland gained at the same magnitude. The capacity of forests to provide ecosystem services may be significantly constrained, which, directly and indirectly, may have impacts on the 12 million people living within and around the eco-region as well as Northern Somalia and Kenya due to the negative impact on rivers originating from the BMER.
The major driving force behind all these changes is farming. A strong correlation between the areas of farmland and cropland expansion was observed.
A strong correlation between population growth and cropland expansion was also observed. Some indications, such as local elections, may have an effect on LULCC, especially deforestation, but this needs further investigation. Government policy also contributed to LULCC where most grazing lands were converted to farmland. Weak institutional arrangements and weak law enforcement are other factors contributing to LULCC.
More than 24 million tons of carbon have been removed from the forest ecosystem during 1985–2015 in BMER. The majority of this carbon has, probably, been released into the atmosphere in the form of GHG. The potential of the forest ecosystem to absorb CO2 from the atmosphere has also been reduced. At this rate, achieving the goal set by the Government of Ethiopia of reaching middle-income country status by 2025 while maintaining GHG emission at the 2010 level may be difficult.
In the future, allocation of land to different uses needs to be based on land use policies. Tagging values for each land cover as per the SDG 15.9, which recommends integrating ecosystem and biodiversity values into national and local planning, etc., may be one mechanism for limiting the unplanned expansion of one LULC type at the expense of another.
In the future, further investigations are recommended on the impacts of economic forces, from local up to global levels; infrastructure development, such as roads; and poverty on LULCC in the BMER.