The impact of overgrazing on desertification
BSc Internship report by: M. H. Markus
Wageningen, 28 April 2011
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The impact of overgrazing on desertification
A case study in Botswana at the Mopipi study site of the DESIRE project.
BSc Internship Erosion and Soil & Water Conservation
LDD 70824
24 credits
Submission date: April 2011
Student:
M.H. Markus
Reg. Nr.: 890409544050
Study: BSc International Land and Water Management (BIL)
Supervisor:
Dr. E. Argaman
WUR ESG / Land Degradation & Development
Droevendaalsesteeg 4, 6708PB, WAGENINGEN
Internship provider:
DESIRE Project
Supervisor:
Dr. J.R. Athlopheng
University of Botswana / Department of Environmental Science
P/Bag UB0704, GABORONE
BSc Internship report Land Degradation and Development Group at Wageningen University
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Summary
This report is the outcome of a research done in the BSc Internship Erosion and Soil & Water
Conservation. The internship provider is the DESIRE project. The DESIRE project has been set up for
desertification mitigation and remediation of land. The DESIRE project has about 18 study sites over
the world. One of these is the Mid-Boteti area in Central District, Botswana. The responsible partner
for this study site is the Department of Environmental Science of the University of Botswana.
Overgrazing is seen as one of the causes of desertification in the Boteti Area in Central Botswana.
Desertification will lead to a reduction of the land productivity and availability of natural resources
which will negatively influence people’s welfare.
In this study the impact of overgrazing on desertification is analyzed firstly by studying the
environmental changes in the area perceived by the local inhabitants. This has been done by
interviewing people from the villages Mopipi and Rakops. Secondly, the effects of grazing on
vegetation and soil parameters were studied. This has been done by defining the effects of grazing
on vegetation and soil based on a literature study. These effects were then placed in a system
diagram to understand the importance and relating effects of a particular process. Also the effects of
grazing were analyzed in many plots in different grazing areas. Thirdly this study looked for trends of
changing land cover by analyzing remote sensed time series data and for trends in the rainfall pattern
of the area for the last decades using the Mann-Kendall rank correlation method.
From the interviews the conclusion has been drawn that in fifteen years time the perception and
attitude of stakeholders did not change much. People have a notification of environmental changes
which is mainly an increase of bushes and a decrease of trees and ground layer vegetation cover.
Also changes in soil quality were noticed. People mentioned that soil becomes more loose and salty.
People have many ideas of possible causes. Most frequently called is a lack of rainfall and increasing
soil salinity. People are fatalistic to actually take action to combat these changes. The reason for this
is that people say they cannot do anything or they don’t know what to do. A possible solution is,
according many people, education in use of natural resources. But still they do not start education by
themselves. However there are many people who think planting of trees can help a lot. A few people
also mentioned to control the movement of grazing.
By drawing a system diagram of the effects of grazing the impact on desertification can be shown.
From this diagram and from comparing the results of the field measurements, the best significant
indicator of grazing is the biomass production. In the non grazed area twice as much mean biomass
per square meter has been found than on the grazed areas. On a long time scale the low biomass
production can result in high losses of land productivity because it will affect the nutrient status and
infiltration capacity of the soil. Also the cover of two grass species differed in the two areas. Soil
parameters did not differ significantly between both areas. By defining different grazing areas it was
found that woodland and shrubland savannah are most vulnerable for overgrazing. Soil
characteristics showed compaction in many areas but this could not be related to the real impact of
overgrazing on desertification from this study only. Annual grass species, which can be indicators of
overgrazing, were found in the different grazing areas but not widely spread. Visible effects of
grazing on soil and vegetation around watering points was only in a maximum range of 30 meters
around the particular watering point. Boreholes can be a larger contributing part of wind erosion
than wells because of the soil types you can find both watering points.
The rainfall trend analysis showed that there is no probable trend for the period 1960 to 2000.
Because only annual data were used the result can differ from the perception of stakeholders. In the
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study it was not possible to relate rainfall directly to temporal and spatial land cover because a lack
of useful data. However, from NDVI time series data it was clear that especially grassland grazing
areas did have a significant negative trend. This means that the biomass production has decreased.
From this study it is not possible to point out the factors which have influenced this decrease. Further
study to this topic can be done because the NDVI showed to be an indicator for biomass production
and can give more insights in the factors causing desertification if it is combined with information on
locations of cattle posts and intensity of grazing around and density of stock on those cattle posts.
The reducing effect of grazing on the biomass is the biggest concern in the grazing areas around
Mopipi. Education is one of the good solutions to reduce the negative process of desertification.
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Table of contents
Summary ................................................................................................................................................. 5
Table of contents ..................................................................................................................................... 7
Internship information ............................................................................................................................ 8
Organization ........................................................................................................................................ 8
Botswana ............................................................................................................................................. 9
1. Introduction ....................................................................................................................................... 11
1.1 Desertification ............................................................................................................................. 11
1.2 Overgrazing ................................................................................................................................. 12
1.3 This study..................................................................................................................................... 12
1.4 Research questions and objectives ............................................................................................. 13
2. Methodology ..................................................................................................................................... 14
2.1 Study area.................................................................................................................................... 14
2.2 Perception of stakeholders ......................................................................................................... 15
2.3 Effect of grazing on vegetation and soil parameters .................................................................. 16
2.3.1 Between a grazed and a non grazed area ............................................................................ 16
2.3.2 Between different grazing areas .......................................................................................... 18
2.3.3 Around watering points........................................................................................................ 18
2.4 Land cover changes in relation to rainfall ................................................................................... 18
4. Results and discussion ....................................................................................................................... 20
4.1 Perceptions of stakeholders ........................................................................................................ 20
4.2 Effect of grazing on vegetation and soil parameters .................................................................. 23
4.2.1 Introduction .......................................................................................................................... 23
4.2.2 Between a grazed and a non grazed area ............................................................................ 24
4.2.3 Between different grazing areas .......................................................................................... 26
4.2.4 Around watering points........................................................................................................ 28
4.3 Land cover changes in relation to rainfall ................................................................................... 29
4.3.1 Rainfall time series ............................................................................................................... 29
4.3.1 NDVI time series ................................................................................................................... 30
5. Conclusion and recommendations .................................................................................................... 37
Acknowledgements ............................................................................................................................... 40
References ............................................................................................................................................. 41
Appendix I – Grazing area types ............................................................................................................ 47
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Internship information
In this preliminary chapter information is given about this internship. Firstly the organization in which
this internship is hold is described and after this the country were the study is performed.
Organization
This internship is accomplished within the DESIRE project. Over the last decade there have been at
least 40 large international research projects that focused on the topic of desertification and land
degradation in the European Union and Northern Africa (DESIRE project, 2009). By comparing these
projects, it has been showed that only a few of these projects have been dedicated to remediation
and prevention strategies. Therefore the EU asked for an integrated project on the topic of
“Combating land degradation and desertification”. Alterra, part of the Wageningen University and
Research Centre concern (Wageningen UR), started the DESIRE project which is funded by the EU.
The goal of the DESIRE project, or “Desertification Mitigation and Remediation of Land, a global
approach for local solution” as full named, is the establishment of promising alternative land use and
management conservation strategies (Baartman et al, 2007; DESIRE project, 2009). The project is
based on starting a Harmonized Information System (HIS) to achieve the goal of the project. HIS is a
data and knowledge centre for all partners in the DESIRE project. The other way in which the
approach for local solution will be achieved is to bridge the information gap between stakeholders
and scientists. Finally the results will be translated to practical guidelines for all stakeholders like
governmental authorities, policy makers, NGOs, land users, land owners, and local communities.
The DESIRE project is a global initiative with 20 partners from the EU and Northern Africa and 8
partners from elsewhere. Around the world 18 study sites have been selected, that are affected by
one or more desertification related problems (DESIRE project, 2009).
The project is divided in different working blocks (WB). The WB1 inventoried the 18 hotspot target
areas and organized both spatial environmental data and socio-economic data of stakeholder groups.
WB2 used this information and available results from other EU projects to define and evaluate sets of
desertification indicators. WB3 used the information of the first two working blocks to develop a
series of conservation and remediation strategies in close cooperation with the stakeholders. The
achieved indicators are tested for their efficiency in the monitoring phase in WB4 and used to
organize the monitoring results into a framework. The strategies from the third working block are
implemented in each of the hotspot areas in the fourth working block as well. The efficiency is
measured and modelled over the course of several years. The goal of WB5 is to upscale the results of
WB4 and model them on a larger scale, forecasting regional effects of combating desertification both
in environmental and socio-economical terms. WB6 finally runs parallel to the other working blocks
in that it designs a harmonized data information system to which all working blocks contribute data,
and organizes the dissemination of the results.
This internship is done at the DESIRE project study site in Botswana. The Boteti area has been the
focus of many projects to combat desertification. These projects identified the Boteti area as
desertification hotspot and as area of extreme human-induced wind erosion. The desertification
related problems in the Boteti area are wind erosion, vegetation degradation and overgrazing
(Baartman et al, 2007).
The responsible partner for the study in the Boteti area is the Department of Environmental Sciences
of the University of Botswana. In the Boteti area several workshops have been kept to work through
de working blocks of the DESIRE project. These workshops showed that the main issue according to
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the community is poverty due to their dependence on natural resources, which are poor soils and
depleting vegetation cover. The desire of the community is technical help or interventions which
address their livelihood situation. After all, the goal in the Boteti area is based on the reduction of
the depletion of trees. The reason for this objective was the background of the DESIRE project. The
DESIRE project is an environmental management project and could not answer to the desire of
technical help (Magole et al., 2008).
For the reduction of depletion of trees several strategies have been evaluated by the University of
Botswana and the community. The out coming of this strategy study is to enhance the use of biogas
instead of firewood which had the best commitments made by the stakeholders.
Botswana
Botswana is a country in the southern part of Africa, see figure 1. It is locked in between Namibia,
Zambia Zimbabwe and South-Africa. The geographic location is 18o-25 o South and 20 o -30 o East. The
country has an area of 582.000 square kilometres. 80% of the area is covered by the Kalahari Desert.
The Kalahari, though, is covered with woodland, close-tree savannah and shrub savannah and is not a
poor desert like the Sahara (Darkoh, 1997). However, Botswana is one of the most desertified
countries in Sub-Saharan Africa according to Barrow (Barrow, 1991).
Fig. 1.On the left side location of Botswana in Southern Africa, on the right side Botswana.
The country has a mean altitude of approximately 1000m. above sea level and is generally flat.
Botswana is an arid or semi-arid country with an average annual rainfall of 250mm in the south-west
of the country and 650mm in the north-east of the country. Almost all of the rain falls during the
rainy season which is during the summer months from October to April (Masilo et al., 2002).
From these data four main ecological regions can be recognized in the country. Namely the hardveld,
the sandveld, the alluvial plains of the Okavango-Chobe system and the lacustrine plains of the
Makgadikgadi Pans. The Okavango delta and Chobe delta are inland water systems. The Okavango
delta is the largest inland water system of the world.
Botswana became an independent country in 1966. Before the independency, Botswana was a
British protectorate under the name Protectorate of Bechuanaland (Asselman et al, 1988). This
protectorate was organized in the first place because of the request of local leaders for protection
against the Boers. The Boers formed their own Free State ruling the Transvaal, but were continually
threatening to take over Tswana lands in Botswana (McIntyre, 2007). In the second place it was
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created to compete with Germany, which annexed South West Africa (now Namibia) in 1884. Since
1966 the country has a parliamentary republic. Sir Seretse Khama is president of the country. The last
elections were in October 2009. Botswana is a stable country and one of the least corrupt countries
of Africa.
Before outstanders settled in Botswana there were already people living with a long history. The
earliest people living in Botswana were the Bushman or properly named Khoisan. These people were
hunter-gatherers. Nowadays only a few (that is an estimation of 6000 in 1973) of the people still live
as hunter-gatherers (Mark et al, 1973). The hunter-gatherer activities are replaced by agricultural
activities like livestock holding and arable farming (Asselman et al, 1988). The livestock holding is an
important part of the income or self substitution for many households. In 2003 37.5% of the
households kept livestock, including rural and city households (Majelantle, 2009). However the
agricultural sector is only 4.1% of the total GDP. The main sector dominating the economy is the
mineral sector which contributes for about 34% of the total GDP (Masilo et al., 2002).
The economy has been growing quickly since independency. The country was relative poor. But in a
few decades the economy expanded and there were changes in the structure of production. The
exploration of minerals and diamonds was one of the stimulators of this growth. Also the
government had started development programmes focusing on education, health facilities and
communications and infrastructure.
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1. Introduction
One of the sources of income for people around the world is to raise cattle. One of the problems in
the land degradation domain is desertification. We might ask if these two facts are related and how
they are related. In this introduction the desertification problem is considered and also the relation
with cattle grazing and desertification. Finally the need for studying this topic is declared and
research questions and objectives are given.
1.1 Desertification
In many studies Botswana is described as a desertified area in southern Africa (Rensberg van et al.,
1971; Vegten van, 1979; Cooke, 1981; Cooke, 1983, Masilo et al., 2002; Arntzen et al., 1994; Darkoh,
1997; Reed, 2005; Reed et al., 2006; Athlopheng et al., 2009). Before speaking about the occurrence
or severity of desertification in Botswana we need to give a definition of desertification. Without
definition there will be a continuing process of confuse about the occurrence and severity as stated
by Dahlberg (1994). During desertification and dry land degradation studies there has been a
changing paradigm in the definition of desertification. The idea that desertification is mainly the
expansion of deserts and the idea that land degradation would result in desert-like conditions like
the Sahara desert, has been swift to the idea that desertification is the degradation of land in aridlike regions and that desertification will decrease the productivity of land without the thought that
there should be an absolute land productivity loss. There also has been a change in the ideas about
the causes of desertification. The idea that desertification was only due to the influence of human
activities has been excluded nowadays (Dahlberg, 1994).
In this study we will use the definition according to the United Nations Convention to Combat
Desertification (UNCCD) which has been extended by Brauch and others (2009): “desertification is
the degradation of land in arid, semi-arid and dry sub-humid areas. It is caused primarily by human
activities and climatic variations. Desertification does not refer to the expansion of existing deserts. It
occurs because dryland ecosystems, which cover over one third of the world‘s land area, are
extremely vulnerable to over-exploitation and inappropriate land use”. These words indicate the
importance of studying desertification because degradation of land will lead to a reduction in the
biological and economic potential of land. In most cases this will affect people in their way of
surviving or it will affect people’s welfare.
Soulé (1991) and Reynolds (2001) state that desertification consists of three major components, i.e.,
the meteorological, ecological and human dimensions (that is socio-economic dimensions) of
desertification. The socio-economic dimensions are often related to the loss of habitat, the
fragmentation of crucial habitat and issues of overexploitation (Geist, 2005). Although desertification
may be enhanced by the named factors, other environmental factors will play a role in it as well. The
soils are important as well as the climatically conditions and changes. The soils can have
characteristics which are crucial for desertification. Soil genesis, for example, will indicate the
severity of a loss of topsoil. A loss of topsoil can reduce the growth of vegetation by the loss of
nutrients. Climate is important in the way it can induce or reduce desertification. Soulé and Reynolds
noted that meteorological dimensions are important but climatically dimensions are more important.
Day to day or momentary changes in rainfall or temperature will not change the rate of
desertification but climatically changes will do. If an area has a negative trend in rainfall over many
years desertification can be induced (Agrasot et al, 1986).
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1.2 Overgrazing
As mentioned in previous paragraph desertification is partly a natural problem. In Botswana a great
part is due to the pressure of overexploitation by grazing as well (Darkoh, 1997). Usually
overexploitation by grazing is called overgrazing. Also the term overstocking is used. Theoretically
overgrazing occurs if the carrying capacity of rangeland will be exceeded (Leeuw and Tothill, 1990).
The theory assumes that at a particular site potential climax vegetation occurs (Heady, 1975).
Factors affecting this potential climax vegetation are rainfall, evaporation, soil and slope (Field,
1977). The carrying capacity describes the ability of an area to graze livestock in terms of the area
required at a particular time and is most times expressed in similar units to the stocking rate.
Potential carrying capacity describes the long term potential of an area for grazing livestock without
the natural resources being depleted (Field, 1977). The conclusion is that overgrazing occurs when
the carrying capacity will be exceeded. Desertification due to overgrazing occurs when the potential
carrying capacity will be exceeded. The idea that overgrazing can occur even in the short term, as in
times of seasonally droughts, is shared by the model of Barrett (Barret, 1989).
There are different manners of recognizing overgrazing. The first manner is to run carrying capacity
models for a particular area with the actual stocking numbers. The second manner is to identify if
there are indicators of land degradation caused by grazing. This can be done by the interpretation of
the knowledge of local people and by remote sensing. Overgrazing leads to an increase of soil
compaction and soil crust formation and a decrease of biotic crust and perennial grass cover (Muir,
2010). Other indicators are; concentrated trampling by cattle; large-scale vegetation changes;
extinguish of vegetation species and invading of other inedible species and a loss of topsoil by wind
erosion (Darkoh, 1997). These forms are also observed in the Boteti Area (Magole et al, 2008). To get
to know the drivers of desertification and to predict the severity of overgrazing towards
desertification, the effects of overgrazing should be studied.
1.3 This study
Although desertification, and overgrazing in special, is a frequently studied topic there is still the
need to continue with studies to these topics. One of the reasons for this is mentioned by Mearns
(1996) who says that the environmental consequences of livestock production is varying widely,
depending on the opportunities and constraints affected by different production systems,
institutional and policy contexts. Darkoh (1997) argues the importance of choosing an appropriate
temporal and spatial scale. To really understand desertification a long timescale should be chosen.
Although in the Consultancy Report prepared by the Department of Environmental Science of the
University in Botswana an analysis of desertification has been done in 1994 which also included the
analysis of the rangelands (Arntzen et al., 1994). Between that study and this study lies fifteen years
already. This means that it is still important to study desertification and overgrazing again in the
Boteti area. Moreover in the analysis of the University of Botswana causes of rangeland degradation
are listed and the impact on desertification as well, but there is no study done on the overgrazing in
relation to ground layer vegetation and soil parameters specifically.
Usually rangeland monitoring is based on a combination of plant, animal and soil indicators of range
condition (Reed Dougill, 2010). In this study the focus will be on vegetation and soil and the
perception of people. The importance of studying the soil parameters is important in this area
because it also can have major influence on the vegetation growth. The area is characterized by
saltpans as well. Salts in the soil increase the efforts by plant roots to take up water. These efforts
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can have a similar effect as severe droughts by making water less available for uptake by plant roots
(USDA, 1998). To study the impacts of overgrazing without taking into account the salinity can easily
affect the conclusions. Because there is a common thought by inhabitants of the Boteti area that the
rainfall has been decreasing since the 1980’s (Arntzen et al., 1994 & Magole et al. 2008), it is worth
to relate this to the impact of overgrazing on desertification as well.
Because the perception of stakeholders places a major role in the DESIRE project, interviews with
inhabitants of the area are important to know their perception of environmental changes caused by
desertification.
1.4 Research questions and objectives
The following research questions are set up for this research. The answers on this questions can be
found by aiming for the research objectives. They also provide a base to learn how to work in the
field and how to deal with different kind of data to gain insight in a problem.
Research questions:
1. What is the impact of overgrazing on desertification?
2. Does overgrazing have a major influence on desertification compared to other
dimensions like changes in the rainfall pattern?
Research objectives:
1. To assess soil parameters like compaction and salinity in various grazing zones.
2. To evaluate the effects of overgrazing on ground layer vegetation cover and relate
them to the soil parameters.
3. To analyze spatial and temporal land cover by remote sensing and changes in rainfall
pattern to give sight in desertification.
4. To assess key vulnerabilities and impacts in the study area and possible adaptations.
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2. Methodology
The methodology needed for answering on the questions and objectives as can be read in the
introduction are given now. First the study area is defined. After that the methodology is given in
three parts. Firstly the methodology is described to evaluate the problem and awareness of
inhabitants of the study area. This gives much more information than simple field data can give. It
especially makes us aware of what has done, what need to be done or what should not be done in
relation to the problem. The second part deals with the methodology for assessing the relation
between ground layer vegetation cover and soil parameters. This will give more information of the
current state of the study area. In the last part the methodology is described for the evaluation of
rainfall and NDVI data to analyze the temporal land cover.
2.1 Study area
The Boteti Area in Central Botswana has much to do with desertification. The Boteti study area
focuses on the villages Rakops and Mopipi with an estimated combined area of 3,000 square
kilometres (see figure 2). The Boteti Area falls in the Central District Administration (146,531 km2.).
The district administrations are the highest hierarchic levels of the local politic system. All district
administrations are subdivided in sub-districts. Boteti is the smallest (34,956 km2.) sub-district in the
Central District area. The site is located between coordinates 24°-25° east and 20°30'-21°15' south
(Athlopheng et al, 2009).
Fig. 2. On the left side Botswana, on the right side cut out of Boteti Area. (Source: Google Earth)
The Boteti Area was fixed in many studies with desertification as topic (Athlopheng et al, 2009). One
of these studies is the Intergovernmental Convention to Combat Desertification (Government of
Botswana, 1994). The Boteti Area was chosen because it was one of the areas identified as
“desertification” hotspots in the country and was also identified on the GLASOD map, which has
been made by International Soil Reference and Information Centre (ISRIC), as an area of extreme
human induced wind erosion (Government of Botswana, 1994). The GLASOD map was made by the
GLASOD project of ISRIC and is a world map of human-induced soil degradation. Data were complied
in cooperation with a large number of soil scientists throughout the world, using uniform guidelines
and international correlation.
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Fig. 3. Study area with the village of Mopipi in the centre. (Source: Google Earth)
This study especially focused on the area around the village Mopipi (figure 3). Mopipi is located
24o52’20” east and 21o12’06” south. The landscape around Mopipi is characterized by its pan
environment. There is no standing surface water in most of the pans close to Mopipi. More northern
of the village starts the Makgadikgadi Nature Reserve which has pans with standing water. The pan
environment is described by Sims (1981) as a separate agroclimatical zone. This zone is characterized
by a summer average temperature of 24oC-27 oC and a winter average temperature of 15oC-22 oC.
Rainfall is 450-550mm a year with a variation of 40-50% in any one year. Most of the rain is falling in
the summer months which are October till April (Sims, 1981). Soils in the area have a texture of
heavy clays, silts or fine sands, depending on the kind of sedimentation process, namely fluvial,
aeolian or lacustrine deposits. Soil depth is 1-3 m. if not interrupted by calcrete layers. Because the
occurrence of these calcrete layers, which are often near the surface, the drainage can also be
limited. Drainage is medium to poor. The overall area is flat but a maximum of a slope of 2% exists
(Sims, 1981; Holst van, 1981).
Most people have cattle or arable land to provide their household for food and income. Other ways
of income are small shops or contracted work at the mines in Orapa for the company Debswana.
Livestock is usually kept at cattleposts, which are located in a range from close to the village to 30
kilometres away from the village. Arable farming takes place at the riverbeds. Formerly people used
to practice the so called molapo farming. However the Boteti river has not been flowing around
Mopipi since the 1980’s. Farming in the riverbed is depending on the rainfall and higher moisture
content of the soil in the riverbed nowadays. Other rainfed agriculture can be found on the sandveld
areas some 15 kilometres southern of the village.
2.2 Perception of stakeholders
To get to know the perception of stakeholders, interviews have been hold during November and
December with people from the villages Mopipi (30 interviews) and Rakops (20 interviews). The
interviews were based on households which were randomly selected. The reason of doing interviews
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in Rakops as well was the original objective to do also fieldwork studies around Rakops. Finally this
was not possible due to immobility. The field study focused thus only on the area around Mopipi.
Dahlberg and Blaikie defined four components in their framework of environmental changes,
namely: macro-economic and political factors; livelihood strategies; land management and
environmental outcomes (Dahlberg, 1997). Although there are processes working through all of
these components and although they are affecting each other, the interviews were limited to the
components land management and environmental outcomes because of the purpose of this study
which focuses on the vegetation and soil in relation to grazing.
The main focus of the interviews was to know what environmental changes are noticed by
stakeholders and to know what they see as causes for these changes. In the interviews a separation
in environmental changes has been made between vegetation and soil aspects. The second focus in
the interviews lied on the perception of people to take action to combat desertification and what
kind of solutions they think are useful. The interview was set up as a structured but open interview,
which means that there were no objects presented to choose from at each question. Only the
changes/solutions brought in by stakeholders were noted. During the interviews a Setswana speaking
person assisted with translation. The outcomes of the interviews were analyzed with the software
SPSS using frequencies and crosstabs to find relations to the answers and the characteristics of
particular households.
2.3 Effect of grazing on vegetation and soil parameters
The effect of grazing on vegetation cover and soil parameters are split up in three parts. First to
analyze the effect in a grazed and a non grazed area. Then to analyze the effect between different
grazing areas and thirdly to analyze it around watering points.
2.3.1 Between a grazed and a non grazed area
The proposal of this study was to compare different areas with different grazing intensities. During
the transects the conclusion was made that there are no non grazed areas. In the time for this study
it was not possible to identify grazing intensities or to set up a method to control the intensity in
different areas. To base the intensity only on the visible indicators like dung, a nearby kraal or the
visible effects of grazing on vegetation was not good enough to differentiate between areas.
Finally a non-grazed area was found with was a fenced area around a radio-tower located at
21o13'52" south and 24o53'53" east. According to people living nearby this area the area was fenced
since 1998. In this area 25 random square meter plots were studied. To compare the results with a
grazed area the same method was applied for 25 plots outside the fenced area, but close to the
fenced area. The choice to take just the area outside the fence was to be sure that differences were
not caused by differences in weather and soil characteristics.
At each side a plot of one square meter was defined using a rectangle cord on which 10cm. marks
were made. At each plot the vegetation and the soil was studied. In table 1 the parameters of study
are summed up.
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Table 1. Vegetation and soil parameters studied at each plot
Vegetation
Ground layer vegetation cover
Abundance of grass species
Species richness
Biomass
Soil
Texture
Structure
Trampling
Compaction
Abundance of living crust
Abundance of physical crust
Acidity
Salinity
The ground layer vegetation cover was estimated and was given as a percentage. This seems not to
be an adequate method but is the most common method for this purpose (Zhou et al., 1998). After
gaining some experience this method becomes a practical method and can especially be used to
compare different areas. The richness of the species was estimated as well. The distinction should be
made between vegetation cover and vegetation density. Often these two are used as having the
same meaning. However density is related to the distance between plants. In this study the species
richness was given as a percentage of the cover of one particular specie over the total cover of the
plot. If a specie was abundant but the richness of this specie was not possible to estimate because of
the extreme low coverage than a value of 5% was noted. The biomass is defined as the above ground
air dried biomass of grasses and herbaceous vegetation. In each area, outside and inside the fence,
the biomass was measured for ten square meter plots. The ground layer vegetation was cut in the
square meter plots including the parts of the vegetation which were hanging over to the outside plot
and excluding the parts hanging over to the inside of the plot.
The analysis of the soil was done by studying the upper part of the root zone (0-15cm.). The texture
and structure of the soil were based on the Soil Survey Manual (Soil Survey Division Staff, 1993a). If
there was a visible effect of trampling by cattle this was noted. The compaction was measured using
a 06.03 Pocket Penetrometer from Eijkelkamp Agrisearch Equiment with a standard spring constant
of 12 pounds per inch. Also a 14.10 Pocket Vane Tester from Eijkelkamp Argisearch Equipment. The
registered value of the compaction and shearstress was defined as the average value of five
measurements at each square meter plot. The shearstress was measured as well because it
quantifies the compaction and physical crust. Normally the Vane Tester is used for the determination
of shear strength of cohesive soils. The thickness of the crust was also noted as well as the
abundance of living crust.
At each square meter plot one soil sample was taken which consisted of soil from the upper part of
the root zone (0-15cm.) and was analysed in the laboratory to define the acidity and salinity. The
acidity was measured using an electrical pH meter of Hanna Instruments. The samples measured
were prepared as 1:5 air dried soil to distilled water extracts, which is a common used method to
estimate pH (CRCV, 2006). The soil pH is a measure for the concentration of free hydrogen ions (H+)
that are in the soil (USDA, 1998).
The salinity was analysed by measuring two characteristics of the samples. These were the electrical
conductivity (EC) and the total dissolved solids (TDS). The electrical conductivity measured from
aqueous solutions is the most common method of analysing the salinity of a soil if more expensive
instruments for measuring the electrical conductivity of a bulk soil cannot be used (Slavich et al.,
17
1993; Rhoades et al., 1999; Tunstall, 2004; IAARD, 2008). For the measurement of the electrical
conductivity a 1:5 air dried soil to distilled water extract was used, a so called EC1:5 extract. Every
extract was shaken for one hour and the measuring cell was placed after settlement of the soil
particles at the top of the solution. This procedure is also used by Loveday (1974). The EC1:5 has been
measured using an OAKTON conductivity meter of EUTECH instruments which calibrated
automatically to the temperature. The temperature is influencing the electrical conductivity as well,
so it is important to measure values at a standardised temperature.
The resulting value of this method is a measure of the total quantity of soluble salts per unit weight
of soil. This method can be used for soil balance studies, though is not a desirable measure of the
concentration of soluble salts in the soil water. To study the effects of salinity on plant growth the
latter measure is needed because plants take up water from the soil water and not directly from soil
particles. The EC1:5 values were recalculated using conversion factors to get the ECe, which is the
electrical conductivity of an extract of a saturated soil-paste. The extract of a saturated soil-paste is
best comparable to the field situation (Slavich et al., 1993; Loveday, 1974).
2.3.2 Between different grazing areas
To identify different grazing areas six transects were done from without Mopipi. The direction in
which the transects were walked, was based on map based knowledge of the area. To definition of
differences between these areas was based on land cover or land use. For each area at least fifteen
plots were studied. At each plot the same handling was done as at the grazed and the non grazed
area as described in 2.3.1. Only the biomass was not measured because this was highly variable in
the different areas and was only depending on the different species of ground layer vegetation.
2.3.3 Around watering points
Finally also three watering points were studied. Watering points are frequently visited by cattle and
can be used to see the effects on soil and vegetation. Two boreholes and one well were studied. At
each watering point four transects were done and the soil looseness/compaction and vegetation
cover was described every 5 meters until there was no visible difference anymore. The compaction
was not measured because the lack of a softer spring for the handheld penetrometer which can
measure lower penetration resistance values.
2.4 Land cover changes in relation to rainfall
Often the outcomes of workshops of the DESIRE project and other studies show that a shortage of
rainfall is the existent perception of stakeholders in the Boteti area. Therefore a trend analysis of the
annual rainfall was done using the Mann-Kendall rank correlation method. In Microsoft Excel a
spreadsheet was created to calculate the Mann-Kendall’ S and the probability of the outcome. The
rainfall data used were achieved at Rakops from 1960 until 2005 by Botswana Meteorological
Services. However the data for 2001 until 2004 were missing. This means that the actually analysed
trend is for forty years. In the available rainfall data of Mopipi there were too many missing years so
that a trend analysis could not be done for this village.
To study the land cover changes in the area MODIS remote sensing NDVI time series data for the
period 2000-2010 are used. This do not answer to the needs to investigate objective 3 fully, because
it does give only little information on spatial change. However, spatial data was freely available only
18
with a too course pixel size to depict different grazing areas. The NDVI (Normalized Difference
Vegetation Index) is a formula which gives an index for the density of plant growth on a certain place.
This index is calculated from the visible red and near infrared reflection of vegetation as:
(ρNIR - ρRED)
NDVI =
(ρNIR + ρRED)
The index ranges from minus one to plus one. The more close to plus one the healthier the
vegetation and thus the higher the production. By grazing of cattle healthy plants are eaten, so the
biomass decreases and on more soil is uncovered. This can then result in a lower NDVI index. The
NDVI is chosen above other vegetation indices such as the Photosynthetically Active Radiation (fPAR)
and the Leaf Area Index (LAI) because the NDVI also gives us information on soil cover. Bare soil has a
typical NDVI value. Because in this research it is not assumed that overgrazing is the main factor
resulting in desertification in the Boteti area, the explanation in order factors must be kept open. The
NDVI is also used as drought indicator (NASA, 2010). For the study to desertification this NDVI can be
a good way of assessing the severity and the extent in which desertification takes place.
The used data of the MODIS programme are MODIS NDVI 16-day time series data (MOD13Q1). This
data has a pixel width of 0.25x0.25km. The raw data is quality assessed as ‘marginal data’ (Didan &
Huete, 2006; NASA, 2010b). This means that before analysis of the data, they have to be checked on
irregular and anomalous numbers. Anomalous numbers are filtered by hand in Excel. Collection of
the data is done with the MODIS GLOBAL SUBSETS tool. By selecting spots for which NDVI data is
collected use has been made of the landscape characterization as done in the outcomes of the
fieldwork. There is also a distinguishing made between the sizes of the spots. For each grazing area
type a 0.25x0.25 km area and a 2.25x2.25km area NDVI time series data are collected. The locations
of the spots are given in table 2.
Table 2. Location of collected time series data
Grazing area type
Open Woodland
Shrubland
Grassland
Pan Grassland
Location
Latitude
-21.13000
-21.21333
-21.19417
-21.17496
Longitude
24.89528
24.91250
24.78194
24.82306
After processing the data into useful data the different time series where first detrended to
distinguish from seasonal fluctuations. The seasonal fluctuations help to interpret the trend in the
NDVI time series data for the period 2000-2010. The trend of the different time series has been
calculated with a regression technique. This trend is interpreted to see if there is any positive or
negative trend present in the time series. A significant positive or negative trend tells us that the
health of plants or biomass is increasing or respectively decreasing in the given time.
The aim of this research was to compare the trend in NDVI values with the trend in the rainfall.
Unfortunately the available rainfall data and NDVI data were not available for the same time period.
For the rainfall data it was not possible to gain data by the University of Botswana neither by the
Botswana Meteorological Services for the period 2005-2010. Since the rainfall data for 2001-2004
were missing the actual data series was from 1960 until 2000. NDVI data are only available from 2000
until current. This means that a comparison with rainfall and NDVI was not possible. This was not
expected at the preparation of the research. However both data series, rainfall and NDVI, gives us
information on the climatic impact of desertification in the Boteti area.
19
4. Results and discussion
In this chapter the results and discussion are given in the same three parts as given in the
methodology to analyze the extent of the problem.
4.1 Perceptions of stakeholders
Almost all of the stakeholders interviewed are using communal land. This is important to notice
because of the different view of farmers on environmental changes within different land tenure ship
complexes. Tenure ship is one of the factors in the physical and social setting on which the choice of
practices is based (Dahlberg et al, 1999).
By analysing the answers related to livestock there was no significant evidence that overgrazing takes
place in the area. Indicators for overgrazing related to livestock are the health of the livestock and
time before cattle is coming back to watering points (Rayburn, 2000; Reed et al., 2008). Of the
stakeholders who kept livestock 20% have seen a decline in the health of their livestock. However,
40% did not notice any changes in health of livestock. The remaining 40% saw the health of their
livestock changing from year to year or from season to season. They perceive the changes of the
health as caused by temperature and rainfall patterns.
Many stakeholders were aware of changes in the biophysical environment around their village and in
grazing areas. This was already noticed fifteen years ago in a study of Arntzen (Arntzen et al. 1994).
Changes around the village in the last decades are especially noticed changes in vegetation cover.
Though 32% of the people did not notice changes in land cover around the village at all. Of the
stakeholders 7% mentioned an increase of vegetation. Another 44% percent noticed a decrease of
vegetation cover. A definition should be given to vegetation to understand the difference between
increased and decreased vegetation cover. The people who noticed an increase were almost all
talking about thorn bushes, but they who noticed a decrease were talking about trees or ground
layer vegetation like grasses. Only a few individuals used terms like land degradation and soil erosion.
Important is that 17% of the people who noticed changes in vegetation cover mentioned that these
changes were depending on the season. There were not enough interviews kept to make a valid
analysis to conclude if there was a difference in perceived changes by the inhabitants of the two
villages Mopipi and Rakops.
In the interviews a distinction was made between changes around the village and changes in the
grazing areas. This was done to see if changes could possibly be caused by grazing. The results of this
showed that most of the people mentioned the same changes as they noticed around the village. But
now more people (39% instead of 32%) said that there were no changes in land cover and less people
noticed a decrease of ground layer vegetation and trees in the grazing areas (36% instead of 44%).
The results of this analysis shows that there has not been changed much in the awareness of
environmental issues compared to the study of Ringrose and others (1996a) who concluded that
environmental problems are connected to a decline in natural resource availability in the 1980’s and
1990’s and that this decline was widespread. This was already concluded as well in an earlier
published paper of Chanda (1994).
Because grazing has also impacts on the soil the stakeholders were asked if there have been any
changes according the soil in the lasts decades. Many people (40%) have not noticed any changes.
But the changes that were mentioned by some individuals were soil erosion and more infertile soils.
Half of the stakeholders mentioned that the soil have become more loose; more salty or more loose
20
and more salty. These stakeholders had almost all arable land. Stakeholders with only livestock have
a less awareness of changes of soil.
The results of asking people what could be possible causes for the change they mentioned are shown
in table 3. Most of the people do have an idea of possible causes, but one tenth did not. The reason
that people had no idea is related to their view on the environmental changes. The 10% that did not
have any idea did also not notice any change. Remarkable in here is that the percentage of ‘no idea’
is smaller than the percentage of people who did not see any changes. This is because after asking
them about the changes the general point of view of other people of changes in the area was told.
This means that people don’t see any changes by themselves, but they are aware of risks for changes
which can occur.
The three most counted causes are ‘not enough rain’, ‘too salty soil’ and ‘overgrazing’. People
perceive the lack of rainfall by far as most important. The same conclusion, although with a different
name, is done in by Chanda (1996). He found that people in Boteti Area saw droughts as the primary
cause of resource use problems. One third of the people who mentioned the lack of rainfall
mentioned a different possible cause beside it. Overgrazing has been perceived as a reasonable
cause but only mentioned by one tenth of the people. They who mentioned overgrazing as cause, all
had livestock. There was no relation between the type of farming (livestock, arable farming or both)
and the mention of too salty soils as cause. Looking to the overall of mentioned causes there is a
similarity between the perception of stakeholders in the area and the perception of scientists,
although the thought about the most important contributors differs.
Table 3. Mentioned causes of noticed change in percentage of times mentioned by an individual over the total of
stakeholders per single cause. (This means that it is not possible to sum percentages)
Mentioned causes of noticed change
No idea
Percentage
10%
N=48
5
Not enough rain
Soil is too salty
Overgrazing
People are cutting trees
Climate change/global warming
Increasing temperature
Misuse natural resources
Strong winds
Not enough vegetation
Wildfires
River stopped flowing
Sandy soil or unfavourable soil
69%
10%
8%
6%
4%
2%
2%
2%
2%
2%
2%
2%
33
5
4
3
2
1
1
1
1
1
1
1
In table 4 the mentioned possible activities which could stop changes or reverse the current
environmental situation in a more desirable one are shown. One tenth of the people had no ideas to
take action. These people were not the same as those who did not have any idea about possible
causes of noticed change. One other tenth of the people said that relying on the government is the
only thing you can do. A major part of the people perceives that there are no possibilities at all to
take action. This fatalistic attitude was concluded fifteen years ago as well. In that study the
conclusion was made that there is a man-under-nature situation. This definition was made by
21
geographers Burton, Kates and White. From this definition it means that people may encourage
environmental degradation by their attitude (Chanda, 1996).
Table 4. Mentioned possibilities to reverse environmental changes in percentage of times mentioned by an individual
over the total of stakeholders per single possible activity. (This means that it is not possible to sum percentages)
Mentioned possible activities to reverse negative changes
Nothing
No Idea
Hope/rely on government for action
Percentage
33%
10%
10%
N=48
16
5
5
Plant trees
Educate people to stop misusing natural resources
Control movement of grazing
Build a concrete dam
Use iron fences instead of cutting trees for the making of fences
Harvest rainwater
Dig wells
Let Thamalakane river overflow to Boteti Subdistrict
Reduce amount of production of carbon
21%
13%
6%
4%
4%
2%
2%
2%
2%
10
6
3
2
2
1
1
1
1
Though there exist a passive attitude by the major part of the people there are mentioned also many
possible activities to stop negative environmental changes. The most mentioned of these is to plant
trees. After this, education is said to be a good activity. This is however still an activity which people
do not start by themselves, but is dependent on other institutions. A small percentage mentioned
also to control the movement of grazing. This is an important indicator of the perceptions about
overgrazing. Some people see that there is a relation between controlling grazing and environmental
changes.
Most of the people are thinking that changes they mentioned will continue in the future. Almost
everyone was worried about environmental changes in their livelihood, only two persons were not.
These two conclusions are remarkable because not everyone could give solutions to stop negative
changes. It also showed that the prediction of the ongoing of negative environmental changes of a
study from almost fifteen years ago came true. One of the conclusions in this report is that negative
environmental changes (reductions in vegetation cover and long-term water supplies) would likely
continue unchanged unless direct government intervention and local social commitment contrived to
reverse the process (Ringrose et al., 1996a).
The perception of habitants of the area showed a high awareness of environmental changes around
Mopipi. From the open interviews it was not clear what people did know about overgrazing. More
specified interviews should be hold with aspect on effects of grazing, awareness of overgrazing and
mitigations to overcome desertification by overgrazing.
22
4.2 Effect of grazing on vegetation and soil parameters
4.2.1 Introduction
Overgrazing has many effects on the environment and specifically on vegetation and soil parameters
as mentioned in the introduction of this study. In figure 4 the effects of overgrazing on vegetation
and soil are ordered in a system diagram. The figured effects are based on a literature study. This
diagram is essential to understand the impact of overgrazing on desertificication. Instead of the first
block ‘cattle grazing’ man can also read ‘exceeding potential carrying capacity’. If this would be done
the diagram can be modified to show the overall feedback. The result of doing this is a positive
feedback loop. This means that the impact of overgrazing (grazing exceeding the potential carrying
capacity) on desertification is severe because the negative changes or effects enhance themselves in
the system if cattle grazing will not be reduced. The feedback loops will cause an increase in severe
land degradation processes which will have impact not only on biophysical part of desertification but
also on the socio-economic part because the productivity of land, on which the living of the people
depends, will decrease.
Fig. 4. Effects of cattle grazing on land and vegetation processes.
From this diagram we can conclude that the effects of grazing basically are levelled. The primary
effects are the direct effects on vegetation (decreased leaf area and decreased soil cover) and on soil
(biotic soil crust formation, disturbance of root system, soil compaction, soil loosening and
compaction). We can also conclude that the severity of the effects on dry land degradation is
increasing further away from the primary level. The results of the study on the effects of grazing on
soil and vegetation in the different areas have to be related to this diagram to conclude if there is
overgrazing and what the impact is on desertification.
23
4.2.2 Between a grazed and a non grazed area
The non grazed area is an area which has been fenced for more than ten years. The effect of
overgrazing on the biomass production was the most significant indicator of grazing in the grazed
area compared to the non grazed area. The clipping of biomass on a square meter quadrate showed
that the mean biomass of the grazed area was 36 gram/m2 and the mean biomass in the non grazed
area was 84 grams/m2. A Levenes statistical test showed that there was a significant difference
between the two areas accounting the biomass.
However the cover by ground floor vegetation was less different between the two areas. In the non
grazed area a mean cover of 30% was found while in the grazed area a mean cover of 20% was
found. Based on these values we cannot say that grazing has a direct effect on the vegetation cover
of the soil.
Soil compaction and crusting can be increased if overgrazing occurs. Comparing the two areas it
showed that the compaction measured as mean penetration resistance was higher in the grazed area
(3.6 kg./cm2.) than in the non grazed area (3.0 kg./cm2.). Though, both of these values are classified
as intermediate penetration resistance (Soil Survey Division Staff, 1993b). Here the notification
should be made that half of the measurements in the grazed area reached the maximum measurable
value of the pocket penetrometer. But it is still than not likely that the penetration resistance in the
grazed area will fall in a higher class because than the values should exceed 20.0 kg/cm2. The
shearstress mean values for both sites were 0.3 kg/cm2. Also the physical crust formation did not
show a difference between the two areas. For both areas we found a mean value of 2mm. with a
small range of only two millimetres. Crust forms through processes of wind and rainfall on the above
soil layer. Crusts, also named physical crust to differ between biological/living and chemical crusts,
form when organic matter is depleted from the surface layer and soil aggregates become weak.
During showers raindrops disperse the soil into individual particles that clog soil pores, seal the
surface, and form a layer that is dense when dry (USDA, 2001). The reason of no differences between
compaction and crusting in the two areas can be the relation of compaction and crusting to the
raindrop impact and thus to the soil bareness. Because the soil cover showed not a big difference
between the two areas it is reasonable that there is no difference in compaction and crusting.
Another reason which validates this is the same soil texture in the two areas. At the test plots of the
non grazed area there were twice as much notifications of living crust than at the test plots of the
grazed area.
The pH values and the ECe values of the grazed and the non grazed area are almost the same.
Respectively pH=7.9 and pH=8.4 and 2.3 dS/m. and 2.1 dS/m. The values show no severity of
alkalinity or salinity (Soil Survey Division Staff, 1993c) However a modification of the data had to be
made. One of the plots of measured ECe in the non grazed area was on a completely bare patch. The
ECe of this plot had a value of 6.3 dS/m. which is classified as moderate or even high salinity. This
shows that salinity has a major impact on the bareness of the soil for extremely low cover.
The abundant grass species in the two areas are shown in table 5. All of these grasses are perennials.
This perennial grasses are also called ‘decreasers’ because the decrease in areas of heavy grazing. If
decreasers are high abundant in on the range it indicates that the range is being maintained in good
condition (Field, 1976). There condition of the areas is good if we only look at the abundance of the
grass species. The most remarkable differences between the two areas are the abundance of
Stipagrostis uniplumis and Schmidtia pappophoroides. Stipagrostis uniplumis is a grass that recovers
slowly when grazed (Field, 1976). The high abundance of Schmidtia pappophoroides in the non
24
grazed area can be explained by the characteristic of this specie and the historical background of the
area. The area was fenced since 1998 according to information of locals. It seemed that for the
clearing of trees and shrubs of the area they used burning. Schmidtia pappophoroides is fire resistant
because of the swollen basal internodes (Field, 1976).
Table 5. Abundance of species in a grazed and non grazed area. (‘G’ represents the abundance in the grazed area, ‘N’
represents the abundance in the non grazed area)
Name of grass specie
Cenchrus ciliarus
Eragrostis echinochlodia
Eragrostis rigidior
Stipagrostis uniplumis
Schmidtia pappophoroides
Mean abundance of species at plots as percentage of total cover
of ground layer vegetation
N <5%
G 0%
N 5%
G 0%
N 10%
G 15%
N 30%
G 65%
N 50%
G <5%
If we go back to the system diagram in figure 1 we can conclude that there is not a big difference of
the studied parameters in the different areas. This means that grazing has little impact on soil
compaction in this study area. Because there is physical and living crust formation in both of the
areas it means that wind erosion will not easy occurs. Only if this crust is destroyed by trampling
wind erosion will easily occur. The most sever effect of grazing is the decrease of biomass. Because
most of the areas around Mopipi are flat soil erosion caused by surface run off will not be a sever
effect of this decrease of biomass production. The impact of grazing on desertification is small on
local and temporarily scale.
To conclude the impact of overgrazing on desertification on local scale further research should be
necessary. The most important thing is to study the effects on different grades of grazing intensity. In
this study this was not possible because of the immobility to go further than 10 kilometres away
from the village and because man will found grazing on every place if it is not fenced or barricaded to
avoid cattle from grazing this place. To do this monitoring different fenced areas at the different
grazing areas as described in 4.3.3 should be monitored for several years. In these areas the same
vegetation and soil parameters must be studied as were done in this study. But to fully understand
the effects of grazing and the relations between these effects extra parameters should be assessed
as well. These parameters are: nutrient availability, infiltration capacity and root system
development.
The compaction was due to availability of facilities and mobility only measured by a handheld
penetrometer with which the compaction of the top layer of the soil was measured. The results in
this study showed that the compaction of the top layer did not much differ between a grazed and a
non grazed area and between different types of grazing areas. This does not automatically mean that
there is no compaction in the area caused by grazing. Compaction deeper (0-50cm.) in the soil should
be studied as well.
25
4.2.3 Between different grazing areas
During the transects the following different areas of land cover or land use were defined: woodland
savannah, characterised by trees in an open or more closed formation; shrubland savannah,
characterised by shrubs in an open or more closed formation; grassland savannah, characterised by
the absence of trees and shrubs; pan land, characterised by bare soil and only a few grass and shrub
species; arable land, characterised by cultivation; river(bed), characterised by a high variety of
vegetation species and a soil with a high moisture content. In appendix I pictures are given for each
specified area. Also areas can be found with a mix of characteristics of more than one of the above
described areas. Trees and shrubs are many times abundant at the same area. Extra classification
could thus be made if the study was focused on differences in land use over time. To simplify the
effects of grazing between different areas this is not done. During walking the transects the
conclusion was made as well that the only areas of no grazing are the fenced areas like arable land.
All of these other defined areas are under grazing. However the intensity of grazing and thus the
impact on desertification depends on the characteristics of each area.
In table 6 the mean values of the studied parameters are shown for each area. In this table soil
texture is listed first because land cover or land use is dependent on soil types. Other influencing
factors like topography and climate are very homogenate in the studied area so that they are not
taken in consideration.
Table 6. Characteristics of different grazing areas
Texture
Area
Ground
layer
cover
30 %
Living
crust
Crust
Penetration
Shearstress
Salinity
Sand/
Loamy sand
Sand/
Loamy sand/
Clay
Loamy sand/
Clay
Woodland
savannah
Shrubland
savannah
50 %
2 mm.
>4.00 kg/cm2
0.26 kg/cm2
2.67 dS/m
40 %
30 %
2 mm.
>4.00 kg/cm2
0.42 kg/cm2
1.94 dS/m
Grassland
savannah
40% or
70%1
60 %
3 mm.
2.40 kg/cm2
0.26 kg/cm2
Pan land
<5 %
0%
11mm.
>4.00 kg/cm2
0.49 kg/cm2
3.28 or
103.56
dS/m1
144.64
dS/m
Clay
2
Clay
Riverbed
90 %
<5 %
0 mm.
1
Depending on distance to pans. Around pans typically a high cover is found.
2
Not measurable due to roots/high moisture content.
2
2
The values show that the ground layer cover does not vary much between the different types of
savannah. Although there is a mean of 60% cover in grassland savannah if this grassland is near or
around pans. Around these pans the grass specie Odyssea paucinervis is found. This specie is not
desirable forage for livestock but is more resistant to salinity than other species. We can conclude
that the areas which are desirable for grazing, woodland, shrubland and grassland savannah have a
relative low cover. These areas need the highest concern to be aware of overgrazing. The results
does not show if the low cover in this areas is caused by grazing or will be as low if there is no grazing
at all.
26
The living crust abundance shows that almost half of the time there was living crust noticed in the
studied plots. Remarkable is that the physical crust is abundant almost everywhere and with not
much variance. Almost all times the crust is only a small layer. This is actually positive because it
prevents the occurrence of wind erosion. The penetration and shearstress does not give much insight
in the effects of grazing in the different areas. The most important reason of this is that many times
the penetration resistance was exceeding the maximum measurable value of the handheld
penetrometer. The presented values are classified as intermediate penetration by the Soil Survey
Division Staff (1993b). The pH values of the areas rang from pH=8.14 to pH=9.20. The classification is
moderately alkaline (pH=7.9-8.4) to very strongly alkaline (pH>9.0) but the average values are
classified as strongly alkaline (Soil Survey Division Staff, 1993b).
The mean salinity values are falling in a low salinity class except for the pans and the grassland areas
around it. The severity classification of the salinity measured in TDS did not give a different rank of
salinity in the areas than the severity classification measured in ECe. This means that the
concentration of total dissolved salts available in the water gives not a different conclusion of the
salinity than when using the ECe. If values were varied widely it was possible that there were for
example sodic soils. Values of ECe and TDS can differ because salts in water have a different ability to
conduct electricity due to the differences in ions characteristics. The salinity and cover are not
correlated to each other. In table 7 the different grass species are listed which were abundant in the
different areas. Behind the name also the area where the specific type can be typically found is listed.
The life-span and rangeland condition indicators based on Field (1976) are also written down. In the
last column a final mark is given for every specie in relation to the health of rangeland.
Table 7. Grasses noticed around Mopipi, cursive typed species are sparsely found. (Source last two columns: Field,
1976)
Species
Area1
Life-span
Anthephora pubescens
Aristida congesta
Cenchrus ciliarus
Grassland savannah
Shrubland savannah
Grassland savannah
Shrubland savannah
Shrubland savannah
Grassland savannah
Grassland shrubland
Woodland savannah
Shrubland savannah
Grassland savannah
Woodland
Grassland savannah
Shrubland savannah
Woodland savannah
Shrubland savannah
Grassland savannah
Woodland savannah
Shrubland savannah
Grassland savannah
Riverbed
Shrubland savannah
Pan and riverbed
Grassland savannah
Perennial
Perennial
Perennial
Chloris virgata
Enneapogon cenchroides
Eragrostis biflora
Eragrostis denudata
Eragrostis echinochloidea
Eragrostis gumnuflua
Eragrostis rigidior
Ischaemum brachyatherum
Odyssea paucinervis
27
Rangeland condition indicators
Positive (P) or Negative (N)
Low resistance to grazing (P)
Indicator of overgrazing (N)
Annual
Increaser specie (N)
Perennial/annual
Annual
Indicator of overgrazing (N)
Increaser specie (N)
Perennial
Perennial
Perennial
Perennial
Perennial
Perennial
Not grazed (P)
Shrubland savannah
Schmidtia pappophoroides
Grassland savannah
Perennial
High resistance to grazing (P)
2
Stipagrostis uniplumis
Woodland savannah Perennial
Slow recover when grazed (P)
Oropetium capense
Shrubland savannah Perennial
Stipagrostis uniplumis
Grassland
Perennial
Slow recover when grazed (P)
Urochloa trichopus
Woodland
Annual
Increaser specie (N)
1
Areas are ranked in order of highest percent of cover of specific specie with the area with highest cover of
specie named first.
2
When grazed these two types could not be differentiated from each other.
Table 7 shows that there are only a few annual species found, namely Chloris virgata, Enneapogon
cenchroides, Eragrostis biflora and Urochloa trichopus. These species are increasers and show a less
desirable condition of the rangeland. However, all of these species were only observed at a few plots.
The effect of salinity on the cover of each specie showed no correlation. Most values of high cover
percentages were found around the value of 2 dS/m, thus falling in the low salinity class. Two
species, Eragrostis echinoclodia and Odyssea paucinervis, were also found in more sever salinity
classes. Based on these vegetation analysis results we cannot conclude that there is overgrazing.
However we can conclude that woodland savannah and shrubland savannah are of most concern in
relation to overgrazing because the most undesirable species are found in this area. If we relate this
to the total ground layer cover shown in table 6 we see that woodland savannah has the lowest
mean cover followed by shrubland savannah. This is another reason which validates the concern.
If we fit this results in the system diagram we find that effect of grazing is not sever in pan land and
on the riverbed. For the pans this is because they consist of bare clayey soils. The bareness is not
caused by grazing but by the salinity. Also the grassland savannah areas directly around the pans are
not affected by overgrazing because of the high cover of Odyssea paucinervis. The riverbed is not
severely affected by grazing because there is a high cover already due high moisture content and
fertile soils. Woodland, shrubland and grassland savannah areas are more sever affected by grazing
because of the sandy soils. Overgrazing in these areas will have the largest impact on overgrazing.
4.2.4 Around watering points
Watering points are areas which are frequently visited by cattle and around these points the effects
of trampling is visible. Two factors influencing the effect of trampling around watering points is the
type of watering point and the type of soil. These two factors are often related to each other. Two
types of watering points are studied and these types are also the mainly used types of watering
points to water cattle. The two types are a well and a borehole.
The definition of the well is sometimes also used for a pond. This type of watering point exist of a
depression in the landscape where surface runoff water is collected and which sometimes also is
recharge by ground water. Around Mopipi the ponds are often located were loamy or clayey soils
exist. This means that through influence of wetting and drying a compact soil is created around the
water.
The borehole is a artificial type of watering point. Here a hole is bored or dug in the ground to get a
free excess to the groundwater. Usually the water is taken up by hand but sometimes there is also a
engine driven pump. Around Mopipi this type of watering point is typically found in the higher areas
which have more sandy soils. However often there are calcrete layers just below the soil surface or
within a depth of 3 meters (Holst, 1981).
28
Trampling can both results in soil compaction as in soil loosening. Both processes can be existent at
the same location. However loosening only occurs at the top layer of the soil but compaction can
occurs deeper in the soil profile as well as at the top layer (Warren et al. 1986; Mulholland et al.
1991; Eldridge et al. 2009). Trampling results also in a decrease of vegetation cover.
The results of the watering point study showed that visible loosening of the top layer of the soil was
in a range of 15 meters around the boreholes while the well showed no soil loosening at all. The
mean ground floor vegetation cover around the boreholes was less than 5% in a 5 meter range, 20%
in a range of 5 to 20 meter. In a larger range there was no difference with the overall cover of the
area around the boreholes which was between 20% and 60%. At the well there was 0% cover in a
range of 15 meter. From a range of 15 to 25 meter there was a highly variable cover with a mean of
25%. In a larger range there was no difference in cover with the overall cover of the area.
These results show that the effect of cattle grazing around watering points is low. However this study
only considered the top layer of the soil. If the whole soil profile will be taken in consideration then
possibly other conclusions will drawn like in the studies of Warren and others (1986), Mulholland and
others (1991) and Ringrose and others (1996b).
4.3 Land cover changes in relation to rainfall
In this paragraph the rainfall time series and the NDVI time series are depicted, described and
analysed. As described in the methodology of this report the rainfall and NDVI series are not linked
together, because the time series were not overlapping each other.
4.3.1 Rainfall time series
In figure 5 the annual rainfall per year is shown. Most countries of southern Africa experience highly
variable rainfall patterns like many semi-arid climates of the World (Batisani et al., 2009). Rainfall
varies extremely from time and space. In figure 5 this variability is also shown. The difference in
rainfall in between two single continuous years can reach over the 400 mm.
Annual Rainfall Rakops
Annual Rainfall …
700
Rainfall (mm.)
600
500
400
300
200
100
Fig. 5. Annual rainfall in Rakops from 1960 until 1998.
29
1998
1996
1994
1992
1990
1988
1986
1984
Year
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
0
Because rainfall data is non-parametric data a non-parametric test have to be used to calculate the
trend in a series of data. Mann-Whitney-Pettitt method and Mann-Kendall rank correlation method
are two methods widely used for rainfall trend analysis (Parthasararthy et al., 1974; Cheng et al.,
2004; Batisani et al. 2009). The Mann-Kendall test, used in this analysis, compares the relative
magnitudes of sample data instead of the data values themselves. Each data value is compared to all
subsequent data values. Mann-Kendall statistic (S) is a value that is 0 when there is no trend,
negative when there is a decreasing trend and positive if there is a increasing trend. The S calculated
in this analysis was S= -77. However the probability of this decreasing trend should be calculated as
well. Kendall (1975) describes a normal-approximation test that could be used for datasets with
more than 10 values. First the variance of S needed to be calculated which was Var(S) = 6327. Next
the normalized test statistic Z was calculated from S and Var(S) which was Z=0.95546. And finally the
probability density function for a normal distribution with a mean of 0 and a standard deviation of 1
was calculated. This probability for the rainfall data trend S in this analysis is 0.6297. Because this
value is less than the probability level of 95% significance it means that there is no trend in the
annual rainfall pattern on the forty year timescale.
This result is different from the conclusion from Batisani and others (2009) that rainfall has been
decreasing on both annual and monthly bases across Botswana. The closest rainfall recording station
used in that study is located in Maun. The reason of the difference can be the high variability of
rainfall in space. The study of Arntzen and others (1997) concluded that there was no decreasing
rainfall trend in the as well.
The results of the interviews showed that most people see a decreasing rainfall pattern as reason for
the environmental changes. In this study the rank correlation method of Mann-Kendall showed
however that there was no decreasing trend in the rainfall for the period 1960 to 2000. However the
perception of people should not just be moved away after concluding this.
There are more aspects of the rainfall pattern which should be analysed. In this study only the mean
annual rainfall was used. Monthly rainfall could be analysed as well. But the most important thing is
the daily rainfall. From the annual rainfall trend analysis nothing can be said about possible changes
in rainfall intensity for example on a much shorter timescale. The days of no rain are very important
for this as well. People notice the rainfall especially in days of rain because they do not measure
rainfall on a long time scale. Annual rainfall can be still the same when intensity increases but the
days of rainfall are decreasing. Also the variety of this rainfall should be studied to give more insight
on the reliance on arable farming as alternative for keeping livestock. For seeding and other stages of
arable farming it is very important to know when the rain will fall. Actually at the moment there is no
daily rainfall data available for the Mopipi.
4.3.1 NDVI time series
Firstly the NDVI time series data were checked upon irregular and anomalous data. The results of this
check was that some values were deleted because of two reasons. The first reason was an fault in the
measurement, NDVI values were zero on times where one interval (16 days) before the date and one
interval after the date the values were not zero. Zero would mean that there is no or hardly any
biomass production. Such values only are found in places of standing water. The second reason was
that values were unusually higher or lower than the surrounding values. The problem here was that
this check could not be done that accurately because over time the values are fluctuating highly. This
30
means that it was often not possible to see which values were correct and which were not. However
the data were still used because the quality assessment of MODIS was set as useful.
After preprocessing the data was tested on the linearity. For every time series dataset the linear
trend was calculated and also a seasonal adjustment was applied on every set. These three series
were presented in a graph to see the effect of the seasonal adjustment and the trend in the NDVI
data as can be seen in figure 6. Seasonal adjustments shows the seasonal fluctuations. The seasonal
fluctuations are important to consider in this case because we have to deal with a wet and a dry
season. However from the seasonal adjustment there were only some places which helped to
interpret the graph. In none of the graphs a clear seasonal pattern has become visible due to the
highly fluctuating NDVI values.
Fig.6. NDVI time series for Open Woodland (0.25 km. x 0.25 km.)
This is repeated for every type of grazing land. There has also been checked if the NDVI pattern of
the different grazing areas were significantly different. They all were. This means that with the NDVI
data we can distinguish different grazing areas which are also distinguished visually in the field.
However it will be harder to make classifications based on these pattern especially in the dry
seasons. In figure 7 and figure 8 the NDVI time series are shown in which the NDVI values of each
land type are plotted in one graph. Also the mean of the NDVI values is plotted in graph 9. For all
these figures the wet season which is from October to April is visualised with blue blocks. These
figures show that the differences in NDVI is most clear in the wet season. In the dry seasons the NDVI
values are floating around 0.2. Liao and others (2005) take a value of 0.2 as the minimal value for
plant cover. Closer to 0 it will mean bare soil. This means that in dry seasons the herbaceous biomass
is low. In dry seasons the top lies around 0.55 as can be seen in figure 9. As this will be the maximum
value in the time series the graph shows us the dryer years (2002, 2003, 2005, 2007, 2009 and 2010).
However for this 10 year period it is not declarable from the graph if these years are extremely dry or
if the other years are extremely wet. Therefore a longer temporal scale is needed. In figure 10 the
trend lines of the different time series are plotted. In table 8 the slope of these linear trends are
shown, as well as the description of the part of declared variance (R2). Also the significance is shown
in the last column. The trend line is tested with a linear regression method against a line with b=0.
31
Table 8. Characteristics of linear trend lines ( y = ax + b) for different grazing areas for the period 2000-2010
Slope of trend
line (b)
-5.40 E-05
R2
Significance
Significant
0.25 km.
Intercept of
trend line (a)
0.32
0.2 E-02
0.433
No
2.25 km.
0.25 km.
2.25 km.
0.25 km.
2.25 km.
0.25 km.
2.25 km.
_
0.33
0.27
0.27
0.38
0.37
0.23
0.29
0.31
-9.42 E-05
-5.67 E-05
-7.06 E-05
-3.33 E-04
-3.71 E-04
-2.59 E-06
-1.99 E-04
-2.00 E-04
0.1 E-02
0.1 E-02
0.4 E-02
0.2 E-01
0.3 E-01
0.4 E-02
0.3 E-01
0.1 E-01
0.361
0.361
0.349
0.014
0.005
0.976
0.005
0.066
No
No
No
Yes
Yes
No
Yes
No
Grazing area
Width
Open
Woodland
Shrubland
Grassland
Pan Grassland
Uncategorized
mean
From table 8 we can conclude that all the time series show a negative trend. However only three of
them show a significant trend.
From the graphs we can see that there is clearly a correlation between the NDVI and the rainfall. In a
study of Scanlon and others (2002) it has been showed that there is indeed a relation between NDVI
and rainfall. Also the conclusion of Dahlberg (2000) is that plant production is increasing strongly
with slight increase in rainfall. Further we see that in the months October to April (day 275 to day
120) there is a peak in the NDVI. However, this does not yet say anything about the long term
degradation of the land due to climatically factors, because rainfall data for the period in which the
NDVI data was not available. The next thing is now to look at the lower peaks. Lower peaks are
important for grazing because in during lower peaks (and assumed less rainfall) drought impact
becomes greater and recovery in the other seasons is reduced (Dube and Pickup, 2001). The
fluctuating NDVI data does supports the notification of people that the health of their cattle is
changing with temporal changes of rainfall and temperature (paragraph 4.1). A low NDVI indicates
low biomass production. Feed for the cattle is based on vegetation available in the environment.
There is no use of additional feed and in the area grasses are not collected and stored for dryer
periods. During the dry seasons the NDVI values even fall below 0.2 which is a limit for vegetation
cover. However this NDVI time series graphs do not show reason for concern about environmental
change for the last ten years.
Furthermore we can conclude that the last ten years there is no decrease of NDVI in most of the
tested areas. All areas were accessible for grazing. For the given time period we cannot see if grazing
has had a large influence because areas which were closed for grazing for which the NDVI values are
known were not available. The ungrazed area analyzed in 4.2.2 was not big enough to use in the
MODIS subsets.
From the graphs in figures 7 en 8 it is also clear that the NDVI for the different types of grazing area
behave the same in wet and dry seasons. Only for the small sport Pan Grassland line it is different.
This line fluctuates irregular and does not show the peak in wet seasons. This can be caused by the
type of vegetation found in this type of grazing area. Odyssea paucinervis is found mostly in this area
in combination with bare soils of the pans. This type of grass is tough and can resist dry seasons very
well. The differences in minimum and maximum NDVI values per year is highest for grassland. This
shows that grasses are most dependent on the type of weather. It also shows that if these grasslands
are grazed in dry seasons it can easily leads to dry land degradation. However for the spots token in
this time series it is visible that the areas can establish in wet seasons.
32
Fig. 7. NDVI time for different grazing areas on the larger scale spots (2.25 km. x 2.25 km.) for the 10 period (2000-2010), blue blocks indicate wet season.
Fig. 8. NDVI time for different grazing areas on the small scale spots (0.25 km. x 0.25 km.) for the 10 period (2000-2010), blue blocks indicate wet season.
Fig. 7. Mean NDVI values of all categories and spot sizes over the 10 years period (2000-2010) Black line indicates the lineair trend, blue blocks indicate wet season.
Fig. 8. Trend lines of all NDVI time series over the 10 years period (2000-2010)
34
The second area which a large difference in NDVI is Open Woodland. This difference is also related to
the type of vegetation. In this areas the leaves of the trees are detected and this results in high peaks
in wet seasons and lower values in dry seasons. This is not related to grazing because the cattle does
not eat from these trees. It can only be related to the change in environment due to woodcutting.
Which is by locals also seen as problem for desertification. Also woodcutting is not visible in these
figures. Although not all trend lines are significant, it is remarkable that all of them have a negative
slope as can be seen in table 8 and figure 9 for the mean of the NDVI values. This is an another
argument that the different areas behave the same over time.
The question still remains what these graphs do show for the relation between vegetation, grazing
and climatically conditions. Therefore we need to look at the temporal changes and the types of
areas in which significant changes are occurring. The trend lines are visible in figure 10. The trend
lines for both area widths for Grassland are significant and the trend line for the widest Pan
Grassland spot is significantly negative. The significant lines also describe most of the variances in the
time series as can be seen in table 8 in the column for the variance (R2). Again it is hard to conclude
things because rainfall data for this period is missing. But because it is concluded that all types of
grazing areas are fluctuating in correlation with climatically conditions the trend can be suspected to
behave the same over the ten years time unless other factors are influencing the biomass
production. From this point of view it is remarkable that grassland is decreasing significantly. This
could mean two things. First if it is assumed that climatically conditions have changed over time, for
example the rainfall is decreased, the different types of grazing areas behave different or react
different on this. But it is concluded that grassland behaves in biomass production the same on wet
and dry seasons and should then also react the same on long term variation in rainfall. Thus in this
case other factors should influence Grassland but not Open Woodland. This can be factors like
temperature. Secondly if in this case grazing would be the factor which is influencing this over the
ten years time period a negative trend should be expected by the type Grassland but not by other
types on which grazing does not have effect. Since cattle do not eat the grasses found in Pan
Grassland type this should not change over time as well. But in figure 10 and table 8 it can be
concluded that it decreases as well. For this reason a conclusion cannot be made about the influence
of factors for a decreasing trend in the Grassland and Pan Grassland grazing area type. For a longer
period there has been done study to changes in vegetation. This study has been executed in 1996
and gives the conclusion that there is no downward trend in rainfall data (Ringrose et al., 1996a). In
the same study the conclusion is done that natural vegetation does not fully recover after seasonal
drought periods. This cannot be seen in the graphs presented in this paper. Lambin and Ehrlich
(1997) concluded in a study to land cover change in Sub-Saharan countries that erratic land cover
change is caused by interannual climatic variability and temporary modifications in seasonality.
However, again these modifications cannot be read from the presented graphs. Interesting is that in
a more recent study of Moleele and Mainah (2003) the conclusion is drawn that there is a clear
change in land cover since 1970. This change is characterized by the drawback of grass cover up to 18
kilometres from settlements and the increase of woody encroachers closer to the settlements, which
was also found in the study area. This means that if rainfall did not change but land cover did change
the human factor plays a major role instead of climatically changes for the desertification process in
central Botswana. However in the study of Moleele and Mainah (2003) there is no clarification which
human factor is most influencing the changes. The effect of this human factor is clear but it is not
that sever that it decreases the productive potential of the land (Dahlberg, 2000).
For the reasons mentioned in the previous paragraph, the next general conclusion can be drawn
about the spatial and temporal land cover based on NDVI data in relation to rainfall. Firstly there is a
clear tendency in rainfall and biomass production for all grazing area types. Secondly spatial land
cover has not been conducted in this analysis because of the unusable of spatial land cover data,
which means that for a spatial analysis data with a small pixel size is needed. For spatial cover change
it is also desired to have more knowledge or data about the locations of cattle posts and watering
points from where a high grazing pressure starts. Thirdly, there is a clear negative trend in general for
the biomass production of the last ten years, from which some of the grazing area types has a
significant decrease but covering rainfall data is missing which means that it is hard to say something
for the long term temporal change in relation to rainfall. Fourthly more information about the
location of cattle posts and watering points, but also information about stocking density for the last
ten years is needed to draw conclusion about temporal land cover change and the effect of grazing
on this change. For these four clarifications we can say that it is not visible from the analyzed data
that grazing has a big influence on desertification in the area for the last ten years. Because the total
Boteti area is already degraded this conclusion can be misleading because data for before the ten
years period and data about the ungrazed condition of the lands are not available or collected.
Further investigation of this topic should consist of the following points. Collecting locations of cattle
posts in the field. At every cattle post a collection of data for the time the post exists and the density
of cattle of that time should be collected. It must be taken into account that these cattle posts do not
always exists for very long times. It sometimes depends on the type of watering point. If it is based
on boreholes cattle posts will move to other places if that will give better grazing lands but if cattle
posts are located around a pond cattle posts can stay there for a longer time. The same problem of
the locations of cattle posts was founded by Dube and Pickup (2001). This study might be useful in
further research because they show also the effects of rainfall variability on grazing gradients around
focal points. The only thing is that they conclude it for semi-commercial grazing. The effect of noncommercial grazing and the places of grazing are not taken into account. From the Meteorological
Service of Botswana accurately rainfall data should be collected for the last 40 years. Also NDVI data
for analysis of the biomass production must be collected for more precisely described points. A data
collection of points with different grazing densities and intensities must be taken and also several
spots where grazing is not or hardly existing. This can be the most difficult because most of the areas
are accessible for grazing. An alternative can be to collect data from for example comparable
locations in the Makgadikgadi Pans, which are in theory not accessible for cattle, or locations much
further away from Mopipi. Then a similar approach can be worked out as in this study. Trend line
analysis with linear regression approach can give again information on the biomass production over
time. However it is then important to look for a method to have a more accurate preprocessing of
the raw NDVI data. This can be done by building a filter which looks at surrounding pixel information
of a given pixel value.
36
5. Conclusion and recommendations
The scope of this thesis was to give insight in the effect of (over)grazing on desertification in the
Boteti area in Botswana and more specifically, around the village Mopipi. The study was performed
in several study terrains, namely: the perception of villagers; field data assessment; temporal rainfall
data and temporal and spatial remote sensed data. The combination of these four terrains were
answering to the objectives which were:
1. To assess soil parameters like compaction and salinity in various grazing zones.
2. To evaluate the effects of overgrazing on ground layer vegetation cover and relate
them to the soil parameters.
3. To analyze spatial and temporal land cover by remote sensing and changes in rainfall
pattern to give sight in desertification.
4. To assess key vulnerabilities and impacts in the study area and possible adaptations.
From the information founded in these four terrains and following the objectives it was possible to
answer to the research questions which were:
1. What is the impact of overgrazing on desertification?
2. Does overgrazing have a major influence on desertification compared to other
dimensions like changes in the rainfall pattern?
The impact of overgrazing on desertification around Mopipi is mainly dependent on the type of
grazing area. The characteristics of each defined area attributes to the effects grazing can have on
soil and vegetation. The grassland savannahs around pans are of no concern. Because of the high
salinity values these areas are dense covered with a salt tolerant specie, Odyssea paucinervis, which
is not a desirable forage specie. The riverbed has a high moisture content and fertile clayey soils
which cause a high cover of ground layer vegetation with many different grass species.
In general the other areas, woodland, shrubland and grassland savannah are characterised mainly by
soil with fine sands or loamy sand texture. In most of these areas a crust and surface compacted
layer exists which prevents from wind erosion but can limited root development. Grazing can
stimulate soil loosening by trampling which can cause enhanced desertification. The effects of
trampling can be seen around watering points. The best indicator of overgrazing in the area is the
amount of biomass of ground layer vegetation. Grazing can cause areas with biomass values two
times lower than in areas without grazing. The biomass production is the most concerned effect of
grazing as having impact on desertification in the Boteti area. A system diagram showed that a
decrease in leaf area of ground layer vegetation reduces the amount of biomass. This results in a
reduced infiltration capacity but more important in a more negative nutrient status. On a longer time
scale this can affect the abundance of vegetation. More specific, the abundance for desirable forage
species, which will affect the potential carrying capacity in two ways. First the potential carrying
37
capacity will be reduced so that there is less forage available per livestock unit. This means that it will
affect people’s income, thus the socio-economic part of desertification. The second way is that it will
increase the pressure on the available grazing areas. This attributes to the positive feedback loop
which means that the biophysical part of desertification will be affected negatively in a continuing
way no solutions appear. This will also influence the recovery of grass growth after drought periods.
This recovery cannot be fully met.
From the perception of stakeholders on environmental changes around the villages Mopipi and
Rakops and in the grazing areas followed that there is a low awareness of overgrazing, though there
is by many people the notification of a negative change in the natural resource availability of the
environment. This has been also showed in other studies. Most of the people have a passive attitude.
But some villagers also try to do something by planting trees and other plants. The education of
people in the Boteti area is important to increase the awareness of overgrazing and desertification;
to increase the awareness of possible activities to positively influence the negative environmental
changes and to stimulate the perception that people can take action starting by themselves. It also
showed that through the workshops of the DESIRE project and the many studies already done in the
past years in the Boteti area, people are not more aware of the changing environment and the
consequences of this. Here it shows the problem that only people that are willing to do something
are reached by projects and hardly those who have the passive attitude. The perception in general of
people is not that they link (over)grazing with desertification. They most time mention a reduced
amount of rainfall.
From the rainfall data and other studies it cannot be shown that there has been a decreased rainfall
in the last decades. Main factors of desertification are human influences and climatically factors.
From the rainfall analysis and the activities of people the conclusion can be made that human
influences play a major role in the desertification process in the Boteti area. However, this study did
not focus on the activities other than grazing. But a possible consequence of desertification or dry
land degradation in the area can also be collecting of fire wood. The analysis of NDVI time series data
showed that there is not a overall negative trend. However only grassland areas showed a negative
trend. This does not clearly show the effect of climatically factors. Because there are no facts
pointing to a decrease or increase in biomass through a decrease or increase in rainfall. But it clearly
shows the relation between rainfall and NDVI for most of the typified grazing areas.
The following points are recommended. First some points for improvement of the study to
desertification in the Boteti area and also some points in order to decrease the ongoing process of
desertification.
To improve results for this study the following points has to be made. (1) The study has to be
executed with the focus on cattle instead of villages. This will result in a better overview and more
clear view on the effect of grazing. This means that cattle posts has to be located and cattle has to be
followed in the grazing patterns. This should be done at least for a wet and a dry season. Favourable
would be a more than one year track to see also the effect of drier and wetter years on vegetation.
(2) Rainfall data has to be collected for the location of Mopipi and also remote sensing data has to
have a higher resolution. Favourable would be a classification of the area for more years to see which
typified grazing areas are changing and how much and how fast the process of bush encroachment
takes place.
To slow down the process of desertification the following points are important to consider. There are
other points found in other studies, such as destocking but the effect of this measure is not executed
38
in this study. So the following points are mainly from considerations gained in this study. (1) In
projects and studies in the area it is important to take into account all kind of villagers and not only
people who are motivated to join workshops. The environment can only get in a better condition if
everyone is stimulated to apply methods to stop dry land degradation. (2) Education is an important
factor. The education is well organized in Botswana. Scientific reports and views should also be
adapted at the level of primary and secondary education. (3) Grazing can be more controlled if use is
made of fences. Especially around villages the conditions are extremely poor with small amounts of
biomass. This means that the vegetation does not have time to recover. When use is made of fences
and areas are non-grazed for a certain periods the conditions of the soil can improve.
In general we can say that this study helped to link perspectives of villagers and field data to see
what the effects are of (over)grazing on desertification. However to give more insights in this effect
the points mentioned above have to be followed.
39
Acknowledgements
First of all I would like to thank Chaboneka Maremba who helped me really to introduce me to the
area around Mopipi and who could provide me answers on many questions from my side. He also
became a good friend to talk with for the hours of the day which were too hot to work. Through him
I could also visit some cattle posts around Mopipi.
I would like to thank Dr. E. Argaman for his aid with finding an internship provider and for his advice
and comments on my study process. Thanks also for Dr. J.R. Atlhopheng for advice in the fieldwork
and in the analysis of the soil samples and organizing all kind of general facilities.
Finally I would like to thank Dr. J.G. Maphanyane for her hospitality in providing me a room for the
period in Gaborone. She helped me a lot with arranging practical things as well.
40
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Appendix I – Grazing area types
Appendix I - Figure 1: Woodland savannah
Appendix I - Figure 2: Shrubland savannah
47
Appendix I - Figure 3: Grassland savannah
Appendix I - Figure 4: Pan land
48
Appendix I - Figure 5: Arable land
Appendix I - Figure 6: River(bed)
49