Shrub Encroachment into Grassland and its Impact on Kafue lechwe in Lochinvar National Park, Zambia. Berhanu Solomon Genet

Transcription

1 Shrub Encroachment into Grassland and its Impact on Kafue lechwe in Lochinvar National Park, Zambia Berhanu Solomon Genet March 2007

2 Shrub Encroachment into Grassland and its Impact on Kafue lechwe in Lochinvar National Park, Zambia by Berhanu Solomon Genet March 2007 Thesis submitted to the International Institute for Geo-information Science and Earth Observation in partial fulfilment of the requirements for the degree of Master of Science in Geo-information Science and Earth Observation, Specialisation: Environmental system analysis and management for terrestrial ecosystems (ESAM) Thesis Assessment Board Prof. Dr. A.K.Skidmore (Chairperson) Prof. Jan van Groenendael (External Examiner) Radbound University Nijmegen Dr. H.AM.J. van Gils (1 st Supervisor) Drs. H. Kloosterman (Member) INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS

3 Disclaimer This document describes work undertaken as part of a programme of study at the International Institute for Geo-information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute. I certify that although I may have conferred with others in preparing for this assignment, and drawn upon a range of sources cited in this work, the content of this thesis report is solely my original work. Berhanu Solomon Genet

4 Dedicated to Mr. Solomon Genet and My family

5 Abstract Encroachment of shrub is perceived as a problem in different parts of world particularly in arid, semiarid grasslands and river basins of Africa, Australia, and North America. It has been recognized by different writers undermining the productive capacity of grassland ecosystems. As part of the wider problem, this thesis is aimed at addressing the problem of shrub encroachment and its impact on the endemic herbivore Kafue lechwe Kobus leche kafuensis Gray, 1850 in Lochinvar National Park. The park is located in one of the world s Ramsar site called the Kafue Flats. Three images from December 19, 1986 (Landsat TM); March 28, 1994 (Landsat TM) and March 09, 2005 (ASTER) were used for mapping of shrub encroachment. Field work was conducted form September 23 to October 22, 2006 to collect ground references and other ancillary data. The Maximum likelihood classifier was trained to produce the spatio temporal change in shrub expansion. Historical census of Kafue lechwe combined with own field observations were used to study their distribution. Statistical relationship between the distribution of Kafue lechwe and shrub and grass abundance at observation plots is tested using regression analysis. The 1986 Landsat image classification has revealed that shrub cover at that time was only 2% of the area of the park. The image was aimed to represent the situation of land cover contemporary with the construction of Ithezi-thezi Dam. Shrub encroachment was severe afterwards and covered 16% of the park area in Of all conversions, the conversion of grass to shrubs was the highest, with 19% of the grassland area of 1986 converted into shrubland in Hydrological factors emanated from the change in the flooding regime following the construction of Ithezi-thezi Dam were identified as the root causes of encroachment of shrub in the park. Nutrient depletion from the soil profile caused by the trapping of sediments behind the dam as well as associated magnifying factors including overgrazing by lechwe, and seed dispersal by flood have been identified as major factors. The regression analysis also showed that shrub abundance explained the variation in Kafue lechwe distribution at -61.7% implying that there is a moderately strong negative relationship between shrub cover and Kafue lechwe count at observation plots. Shrub encroachment also has been a major factor for habitat fragmentation by limiting the free movement of lechwe between the Chunga Lagoon and the grassland area. The end result of this has been low grazing efficiency of lechwe because of increased travel time in search of pasture and high vulnerability for possible poaching. Shrub encroachment was also responsible for the decline in population estimate of Kafue lechwe both in the park and in the wider Kafue Flats over the past two decades. Population estimate in the national park has dropped by 56% in 2005 from that of The overall analysis of the study, thus, revealed that there is a substantial area of shrub encroachment in Lochinvar National Park which is a threat for the grazer herbivores, especially for the endemic Kafue lechwe. The previous attempt to minimize the shrub cover in the park using labour-based chopping alone has been found unsustainable unless the root cause of the problem is equally addressed, namely the effect of change in the natural flooding regime. Other measures including the introduction of appropriate browser wild animals in the park, sowing appropriate grass seeds in overgrazed and shrub cleared areas should accompany with the simulation of the natural flooding regime. i

6 Acknowledgements First of all I would like to thank the Almighty God who helped me to accomplish this MSc work with his power and love. He encouraged and helped me in all ups and downs to reach at this level of success and I glorify his name. I wish to thank the Government of the Netherlands for offering me the ITC fellowship and support. My deepest gratitude goes to my first supervisor Dr. H.A.M.J van Gils. You have been of active supervision, dedicated help and advice beginning from the formulation of the research area to the overall process of this MSc work. Thank you for your patience and friendliness that you showed me. I have learned a lot from you; above all the essence of scientific research. I would like also to thank Dr. Yousif. A. Hussin for he has indicated me possible area of research, guidance and support on the field during data collection as well us for his comments on the draft thesis. I would like to thank also Dr. David Rossitor who provided me substantial help on statistical sections during my research work. I would like to thank Mr. Marco Galyster (GeoVision consultancy, Arnhem, the Netherlands) for subsidizing field logistic supply and provision of satellite images. World Wide Fund for Nature (WWF)-Zambia office for facilitating field logistic support; the Zambian Wildlife Authority for providing lechwe data; Mr. Griffin Kaize (ZAWA) and Ms. Mwangala Simate (WWF-Zambia) who both assisted me in identification of shrub species on the field; and Mr. Dassius Mweene (Wildlife Police Officer) who provided me security service during my stay in the park. I am also happy to express my great appreciation to the entire staff of ITC from whom I had a privilege of acquiring substantial knowledge and experience during my study period. A special thank goes to Dr. M.J.C. Weir for his dedicated help in all educational affairs and Mr. Beno for his cooperation in time of urgent printing works. My most hearted thank also goes to Mr. Adrie, Ms. Jinny, Mr. Andrie and Ms. Kurniati, all from Holland for their hospitality and encouragement that they provided me during my study period. God bless you. My everlasting gratitude goes to my wife Ms. Zufan Kebede for she has properly managed my family during my stay in the Netherlands and always encouraged me to carry out my study successfully. ii

7 Table of contents 1. Introduction Background Research problem and justification Research objective General objective Specific objective Research questions Hypothesis Research approach Literature Review Shrub encroachment Lechwe (Kobus leche) Dichrostachys cinerea and encroaching shrubs Image classification Accuracy assessment Vegetation change detection Correlation and regression Materials and methods Study area Climate Landscape and vegetation Drainage Materials used Methods Sampling Digital satellite image processing...17 Image pre-processing...17 Image classification...17 Change detection Kafue lechwe aerial survey Statistical relationship between variables Results Land cover mapping and analysis Classification accuracy Satellite image classification Land cover 1986, 1994 and Land cover change...26 Land cover change 1986 to Land cover change 1986 to Land cover change 1994 to Distribution and population size of Kafue lechwe...34 iii

8 4.2.1 Spatial distribution of Kafue lechwe Statistical analysis for the relationship between variables Descriptive statistics Correlation analysis between paired variables Regression analysis of Kafue lechwe distribution on explanatory variables Multiple regression of lechwe distribution on explanatory variables Change in the population size of Kafue lechwe Discussion Landcover quantification Shrub encroachment and driving forces Nutrient depletion Change in the grazing pattern Seed dispersal Other factors Distribution of Kafue lechwe and shrub encroachment Population estimates of Kafue lechwe and shrub encroachment Shrub control and the future of Kafue lechwe Conclusions and recommendations Conclusions Recommendations References Appendices iv

9 List of figures Figure 1-1: Daily discharge of the Kafue River at Hook Bridge: Oct Sept Figure 1-2: Daily discharge of the Kafue River downstream of Itezhi-tezhi Dam: Oct Sept Figure 1-3: General conceptual framework of the study...6 Figure 2-1: The endemic Kafue lechwe (Kobus leche kafuensis) and encroaching shrub...9 Figure 2-2: a) D. cinerea shrub b) Acacia shrub...9 Figure 3-1: Location of Lochinvar National Park...13 Figure 3-2: Flow chart of the overall method used in this study...15 Figure 3-3: Distribution of observation points on ASTER image..16 Figure 4-1: Park area under different land cover (Dec. 19, 1986, Mar. 28, 1994 and Mar. 09, 2005)..22 Figure 4-2: Average annual water level above sea level at Nyimba hydro station / /05.23 Figure 4-3: Mean monthly discharge (m 3 s -1 ) from the Kafue River post and pre- lthezi-thezi...23 Figure 4-4: Classified Landsat TM image of December 19, Figure 4-5: Classified Landsat TM image of March 28, Figure 4-6: Supervised classification ASTER image of March 09, Figure 4-7: Land cover change in Lochinvar National Park. (Dec. 19, 1986 Mar. 09, 2005)...27 Figure 4-8: Land cover change in Lochinvar National Park (Dec. 19, 1986 Mar. 28, 1994)...33 Figure 4-9: Land cover change in Lochinvar National Park (Mar. 28, 1994 Mar. 09, 2005)...33 Figure 4-10: Distribution of Kafue lechwe in Lochinvar National Park...34 Figure 4-11: Regression of lechwe count on shrub cover...37 Figure 4-12: Regression of lechwe count on grass cover...38 Figure 4-13: Regression of lechwe count on distance from the Chunga Lagoon...39 Figure 4-14: Regression residual Quantile-Quantile plots...40 Figure 4-15: A ) Q-Q plots of regression residuals lechwe count explained by shrub cover and distance from the lagoon; B) regression residuals lechwe count explained by grass cover and distance from the lagoon Figure 4-16: Population estimate of the Kafue lechwe within the Kafue Flat...43 Figure 5-1: Oblique view of shrub encroachment near to the Chunga Lagoon taken...49 v

10 List of tables Table 3-1: Materials used in this study and their sources Table 4-1: Error matrix for ASTER image of March 09, Table 4-2: Land cover December 1986, March 1994 and March Table 4-3: Area under each land cover from December 1986 to March Table 4-4: Land cover change in Lochinvar National Park (December 1986 to March 2005) Table 4-5: Land cover change in Lochinvar National Park (December 1986 to March 1994) Table 4-6: Land cover change in Lochinvar National Park (March 1994 to March 2005) Table 4-7: Monthly distribution pattern on lechwe in the Kafue Flats before the construction of the Ithezi-thezi dam Table 4-8: Descriptive statistics of the variables Table 4-9: Summary of Spearman's correlation (R) matrix Table 4-10: Summary of the simple regression statistics Table 4-11: Shapiro-Wilk normality test statistics Table 4-12: summary of the multiple regression statistics Table 4-13: Shapiro-Wilk normality test statistics for residuals of combined variables vi

11 List of Appendices Appendix I: Graphical presentation of temporal changes in permanent land covers...61 Appendix II: Annual average water level above sea level at Nyimba hydrological station...61 Appendix III: All changes to shrubs and to other classes December 19, 1986 to March 09, Appendix IV: All changes to shrubs and to other classes December 19, 1986 to March 28, Appendix V: All changes to shrubs and to other classes March 28, 1994 to March 09, Appendix VI: Historical census on population estimates of Kafue lechwe in the Kafue Flats...65 Appendix VII: Field shrub observation points...66 Appendix VIII: Field Kafue lechwe observation points and number observed...68 Appendix IX: Validation points for classification of Aster image of March 09, Appendix X: Shrub and grass cover and distance from the Chunga Lagoon computed...72 Appendix XI: Field data sheet used in recording shrub observation at sampling points...73 vii

12 Abbreviations ASTER CCC ETM GIS GPS Ha Q-Q Sqrt TM USA UTM WWF ZAWA ZESCO Advanced Spaceborne Thermal Emission and Reflection Radiometer Civilian Conservation Corps Enhanced Thematic Mapper Geographic Information System Global Positioning System Hectare Quantile- Quantile Square root Thematic Mapper United States of America Universal Transverse Mercator World Wide Fund for Nature Zambian Wildlife Authority Zambian Electric Supply Corporation viii

13 1. Introduction 1.1. Background The conservation of plants diversity is important not only for their economic and ecological value but also for the betterment of future generation. However, the conservation and management of plant species in natural environment is not an easy task. Under natural condition environmental factors like temperature, rainfall, soil type and altitude shape the natural floristic gradient of a particular place (Cox et al., 1976). Some sort of balance also exists in nature that enables vegetation and animal population to co-exist indefinitely (Tainton, 1999). The natural floristic gradient and mutual balance, however, is usually interrupted by human induced land use changes (Maurer et al., 2006) which consequently brings about impact on heterogeneity and distribution of plant and animal species. The interference in some situation reaches at a stage where even secondary succession would not be possible or might take long time. (Mouissie et al., 2005; McGlynn and Okin, 2006) indicated that shrub encroachment into grassland has been an indication of gradual shrink in plant species diversity and decrease in temporal dynamics of primary production. Increased shrub cover also causes decline in moisture availability and soil organic content (Laliberte et al., 2004; Goslee et al., 2003). A Study conducted in Tsavo National Park (Wijngaarden, 1985) showed that different animal species tend to concentrate in similar vegetation zones seeking for quality source of pasture though few tend to occupy particular sites like water points and protection zones. This indicates that habitat fragmentation due to change in vegetation composition modifies the spatial distribution of wild animals, especially big herbivores. This has been growing problem in arid and semiarid regions of the world particularly in Africa, Australia, and North America where vegetation pattern is being transformed at an increasing rate because of mainly unsustainable human practices (McGlynn and Okin, 2006; Pineda and Halffter, 2004). Change in vegetation ecology and other environmental impacts have been recognized in several African river basins in association with expanding socio-economic activities. To mention some, after the construction of the Aswan High Reservoir ( ) on the River Nile, valuable archaeological sites from lower Nubia moved from their historical place because of frequent flood hazard from Lake Nasir. The previous fertile natural floodplains also lost their silt since water is now trapped behind the dam resulting in low agricultural and pasture production. The Kariba Dam (1959) constructed on River Zambezi in Zimbabwe is also an environmental concern down stream of the reservoir for it has been a threat for human and wildlife. It is memorable that on the 'Operation Noah'about 6,000 large animals and several small ones were captured and removed from their natural habitat due to the flood threat emanated from rising water level of Lake Kariba (Ven et al., 1991). Change in vegetation composition was also seen on Pongolo River after the construction of Pongolapoort Dam in Republic of South Africa. During winter season when the water is kept in the dam, soil moisture downstream declined and plants were exposed to water stress causing long term impact on the natural ecosystem 1

14 (Furness and Breen, 1982). The construction of Maga Dam (1979) in Cameroon led to serious ecological degradation in which annual grass and shrub invaded the productive perennial grassland reducing re-growth in dry season. This was a major problem reducing the carrying capacity of wildlife down stream in Waza National Park (Scholte, 2005). Due to such unsustainable human practices, several ecosystems have been affected in the world. However, considerable number of integrated efforts towards management of plant biodiversity resources have been also successful (Rocchini et al., 2006). Therefore, findings of such types of problems are important for further policy interventions. Lochinvar National Park is part of the internationally recognized Ramsar site in the Kafue Flats known by its being the habitat for diverse flora and fauna. It is specially well known by its endemic Kafue lechwe Kobus leche kafuensis Gray, 1850 (Simukonda et al., 2002) (Figure 2-1). Similar to other river basins of Africa, several studies have indicated that there is a change in the vegetation structure and associated animal life in the Kafue Flats over a long time because of mainly expanding human interest in the resources use of the wetland (Chabwela and Siwela, 1986; Ellenbroek, 1987). This study, therefore, deals with one aspect of the problem which is related to shrub encroachment and its impact on the spatial distribution of the endemic Kafue lechwe over the past two decades. 1.2 Research problem and justification Historically before the construction of the Ithezi-thezi dam (1978) on the Kafue River, the floodplain was entirely covered by grassland communities including Vossia cuspidate (Roxb.) Griff., Echinochloa scabra (Lam.) Roem. & Schult. and Brachiaria rugulosa Stapf which occupied the lower part of the Flat. The higher part was occupied by meadow grass communities including Panicum repens (L.), Leersia denudate Launer, Sacciolepis africana C. E. Hubbard & Snowden, Paspalidium obtusifolium (Del.) N.D. Simpson and Acroceras macrum Stapf (Ellenbroek, 1987). According to Ellenbroek, these grassland communities were giving high quality grazing for wildlife as well as for livestock communities. Gradually, both natural and human pressure has affected the normal functioning of ecosystem in the area. Studies indicated that the construction of Ithezi-thezi dam which produces 50% of Zambia s electricity on Kafue River, has been causing dramatic impact on plant composition of Lochinvar National Park as well as the Kafue Flat as a whole (Kampamba, 1988; Chabwela and Siwela, 1986). It has been also causing inundation of the upper floodplains affecting the natural flood regime of the wetland (Brown et al., 2003; GEO-Vision and ITC, n.d). Before its construction, the natural floodplain was inundated between April and May. This was the time when the high flow resulted in excess of the capacity of the river channel (170 m 3 s -1 ). The flow gradually slowed down between October and November. After the construction of the dam, however, the smooth natural flow has been replaced by sudden flooding exceeding 170m 3 s -1 in dry season and as low as 20 m 3 s -1 in wet season. Flooding has been recorded twice as large as the previous natural normal in floodplains during the pick dry season as water accumulated in wet season is released to operate the turbines in dry season (Mumba and Thompson, 2005). A study conducted at Hook Bridge, 60 km upstream of Itezhi-tezhi Dam showed the daily discharge of 500 m 3 s 1 between the periods October 1978 September 2000 which is a flow in excess of 170 m 3 s -1 (Figure 1-1). This was the only means to see the historical natural flow of the river before the dam s construction. The same study showed the effect of the dam on downstream river flow. The smooth natural flow is replaced by sudden rise and fall in water flow due to large volumes of water were 2

15 released from the dam and terminated at different seasons of the year and even variation occurred within weeks and months (Figure 1-2). This has caused considerable change in natural flood extent down stream and some changes in ecological condition have been also recognized following this hydrological change (Mumba and Thompson, 2005) which its cause and effect is discussed in detail in this thesis. Figure 1-1: Daily discharge of the Kafue River at Hook Bridge: October 1978 September 2000 (start of each hydrological year is labeled). Source: Mumba and Thompson, Figure 1-2: Daily discharge of the Kafue River downstream of Itezhi-tezhi Dam: October 1978 September 2000 (start of each hydrological year is labeled). Source: Mumba and Thompson, 2005 The encroachment of native shrubby species like different species of Acacia shrubs, Dichrostachys cinerea (L.)Wight & Arn shrubs (henceforth D. cinerea ), and the expansion of the invasive alien shrub Mimosa pigra L. (henceforth M. pigra ) into the floodplain of the Kafue Flat are evidences for habitat fragmentation. Schuster, 1980 cited by (Kapungwe, 1993) argued that vegetation change caused by change in flooding regime could have disrupted the ecology of Kafue lechwe. Similar studies (Smit, 2004) indicated that several other savannah lands in Southern Africa have been also encroached by woody species causing decrease in grazing capacity and in serious cases total absence 3

16 of herbaceous plants. It has been also recognized that shrub encroachment in Namibia has significantly reduced the economic contribution of livestock (Meika et al., 2001). Shrub encroachment in savannah lands of Swaziland and Southern Africa was expanding at a rate from 2% in 1947 to 31% in 1990 causing habitat fragmentation (Roques et al., 2001). This type of trend is a threat for both wildlife and livestock resource. Studies conducted on shrub encroachment into grassland indicated that unless immediate appropriate measures are taken shrub encroachment can reach at a stage that would be difficult to reverse and restore (Brown et al., 2003; Goslee et al., 2003). As part of the Kafue Flats, thus, encroachment of shrubs into grasslands of Lochinvar National Park could also be a menace for wildlife especially for the endemic Kafue lechwe. Mouissie et al. (2005) indicated that shrub encroachment has a negative impact on large herbivores limiting their distribution and movement for grazing and seed dispersal. In line with this it was essential to conduct detail spatial and temporal study on shrub encroachment and associated impact on herbivore animals which can be availed for planning and management of biodiversity resources. Due to limiting resource to study larger areas like Kafue Flats, detailed studies made in small pilots like Lochinvar National Park can also be carefully generalized to a larger scale. In this context, this study aims to analyze the situation of shrub encroachment in the park following the construction of Ithezithezi Dam and its possible impact on the endemic Kafue lechwe (Kobus leche kafuensis). 1.3 Research objective General objective To detect and analyse changes in vegetation pattern in Lochinvar National Park with special emphasis on encroachment of native and invasive alien shrubs and its impact on Kafue lechwe Specific objective To identify and quantify the dynamics of major vegetation cover types following the construction of the Ithezi-thezi dam (1978). To identify the extent of grassland converted into shrub after the construction of the dam for the time 1986, 1994 and To investigate the association between shrub encroachment and change in the surface area of grassland. To investigate the association between shrub encroachment and change in the water level of Chunga Lagoon. To investigate the relation between the abundance of shrub and the spatial distribution of the Kafue lechwe. To determine the linkage between shrub encroachment and the trend of the population estimate of the Kafue lechwe. 4

17 1.3.3 Research questions How much area was occupied by shrub and grassland in the year closer to the construction of the dam in 1986 and after, 1994 and 2005? How much area of the grassland is converted into shrub between 1986 to 1994 and 2005 and at what rate? Is there any association between shrub encroachment and change in grassland area? Is there any association between the change in the water level at Chunga Lagoon (as a proxy for change in flooding regime) and the extent of shrub encroachment? Is there any relation between shrub abundance and the spatial distribution of Kafue lechwe? Is there linkage between the trend of shrub encroachment and the population of Kafue lechwe in temporal dimension? Hypothesis The total area occupied by grass cover decreased continuously from 1986 to 2005 while between the corresponding years shrub cover increased. There is significant association between shrub encroachment and change in the area of grassland. Lowering in water level at Chung Lagoon over long time (as a proxy for change in natural hydrological regime) gave way for shrub encroachment. Shrub abundance has significant negative impact on the spatial distribution of Kafue lechwe. Shrub expansion has negative repercussion on the historical population estimate of the Kafue lechwe. 5

18 1.4 Research approach The overall conceptual framework of the study is presented on figure 1.3. Research conceptualization Temporal satellite images of the study area Problem statement Research objective Image preprocessing Research design Data collection Training data Field observation Secondary data Temporal land cover map K. lechwe census data Other secondary data Change in grass and shrub Statistical analysis Research result and output Input in the Development Plan of Lochinvar National Park Figure 1-3: General conceptual framework of the study 6

19 2 Literature Review 2.1 Shrub encroachment Several studies used both bush and shrub interchangeably in dealing with encroachment into savannah and grassland. Brown and Archer (1999) and Bok (1999) considered the process of expansion of woody species into grassland as shrub invasion. Van Gils, 1984 as cited by (Esselink et al., 1991) described bush encroachment as the replacement of grassland by vegetation dominated by woody species. A study conducted in Ethiopia on rangeland condition has treated bush encroachment as the advancement of woody species into rangelands lowering the grazing quality as well as limiting the accessibility of grazing lands (Tefera et al., 2006; Solomon et al., 2006). Meika et al. (2001) defined bush encroachment as the conversion of savannas to dense, acacia-dominated thickets with little grass cover. Wikipedia free Encyclopaedia distinguished bush and shrub from a tree by its multiple stems and height less than 6 m tall. For this study the term shrub will be used to include bush and characterized by multi stemmed woody alien-invasive and native shrubs having height less than 5 m. The cause of change in vegetation cover, including shrub encroachment is a subject of controversy. Some suggest one or the combination of both natural and human-made. In Southern United States, long persisted drought ( ) which was caused by climate change had been the major factor for shrub establishment. Those shrubs had the ability to overcome the moisture stress through tapping water and nutrition deep from the sub-surface soil (Laliberte et al., 2004). In Southern African rangelands (Bok, 1999; Moleele et al., 2002) and the wide Borena semi arid rangeland of Ethiopia (Tefera et al., 2006), the main cause for shrub encroachment was attributed to anthropogenic factors mainly overgrazing. Overgrazing has been also one of the causes for invasion of grass by shrub in Southern African grassvelds (Tainton, 1999). In these areas as grazing pressure increased on palatable grass, unpalatable herbs and shrubs increased getting an opportunity to utilize the limited nutrient and moisture available. In some cases areas around bore holes and other water points where the animals tend to concentrate, have been identified as centres of rangeland degradation (de Leeuw et al., 2001). This is an evidence that rangeland deterioration through time gives way for unpalatable encroaching species to establish and later spread through ingestion process (Bok, 1999). This may not be a case for some encroachers like Acacia karoo Hayne, which spread through sexual reproduction and there spread may be hindered in situations of there flower and pods is eaten by animals (Tainton, 1999). Occasional periods of rainfall well above the average have also been indicated as a cause for woody species to withstand dense grass communities (Acocks, 1988 as cited by Tainton, 1999). Study conducted at Ruma National Park in Kenyan Lambwe Valley, indicated that decrease in fire occurrences and fencing resulted in severe shrub encroachment. Previously in these areas recommended fire was taking place and browsers were free to get into the park and feed on palatable 7

20 woody species (Muriuki et al., 2005). In contrary (Bok, 1999) showed that bush fire also kills some important species. 2.2 Lechwe (Kobus leche) Lechwe antelope Kobus leche Gray, 1850 is antelope sub-species which is one of the most important herbivore found in Central African floodplain. It is found in the floodplains of Angola, Botswana, Namibia and Zambia (Streever, 1999). Three species have been identified: the Black lechwe Kobus leche smithemani Gray, 1850, the Red lechwe Kobus leche leche Gray, 1850 and the Kafue lechwe Kobus leche kafuensis Gray, 1850 which is shown on figure 2-1. Of the three species, the red lechwe is the most widely spread over the upper drainage basin of the Zambezi, Okavango and the Congo River basin. The black lechwe and the Kafue lechwe, however, occur only in Zambia. The black lechwe is endemic to the Bangweulu Basin and the Kafue lechwe is endemic to the Kafue Flats. Lechwe weigh up to 100 kg and its stand reaches up to 100 cm at the shoulders. Male lechwe have long elegant, lyre-shaped horns and their size is larger than the female. Lechwe lives in herds and the size of herds vary from 20 to 2000 (Kapungwe, 1993; Kampamba, 1988). It is semi-aquatic grazer which likes spending time in shallow water and is rarely seen in more than 5 km from water (Kamweneshe, 2000 as sited by Simukonda et al., 2002). It has been indicated that the presence of large population of Kafue lechwe in particular place is dependent on the availability of food resource on the plains (Ellenbroek, 1987). During the high peak wet season (April May), lechwe is in food stress because larger area is covered by water. Between June and November, when the flood cover recedes, the fresh grass starts to give wider habitat for lechwe. Mating of lechwe occurs throughout the year with high breeding season from mid December to mid March (Kampamba, 1988). Kapungwe (1993), Kampamba (1988), Chabwela and Siwela (1986) have indicated the occurrence of change in vegetation composition in general terms in the Kafue Flats following the construction of the dam in Mumba and Thompson (2005) addressed the occurrence of M. pigra shrub in the flats. The investigation of the grassland area encroached by major shrubs, mapping temporal and spatial change as well as assessing its impact in Lochinvar National Park s lechwe community is the subject of this study. 2.3 Dichrostachys cinerea and encroaching shrubs D. cinerea is a semi-deciduous thorny shrub reaching up to 10 m tall when it reaches a tree stage. It has a messy appearance, usually multi-stemmed and with crooked branching, having a light conical or roundish crown (Figure 2-2.a). The bi-pinnate leaves have 6 to 19 pairs of pinnae, with a rod-like grand between some or all pairs of pinnae, and each pinnae has 8 to 41 pairs of leaflets. The leaflets tend to close up if the heat of the day goes up. The spines are single, straight and grey reaching up to 4 cm in length. D. cinerea shrub is found all over Zambia and also widespread throughout the rest of Tropical Africa and extends up to Asia and Indonesia (Storrs, 1995). It occurs in Munga thorny woodlands together with other thorny Acacia species (van Gils, 1988 ). The pods are browsed by large animals (Storrs, 1995) and in some places fix nitrogen (van Gils, 1988 ). However, it becomes a serious encroaching pest of grazing lands forming dense impenetrable thickets (Tainton, 1999; Storrs, 1995). On the other hand D. cinerea together with other co-occurring shrub species like Acacia tortilis (Forsk.) Hayne, Balanites aegyptiaca (L.) Delile have been recommended for rehabilitation of degraded water stressed Rift Valley zones of eastern and south-eastern part of Ethiopia. This 8

21 recommendation emanated from low mid-day (3.05 to 4.85 MPa), predawn ( 1.98 to 3 MPa) and wide diurnal (1.16 to 2.25 MPa) water requirement and their ability to withstand drought (Gebrekirstos et al., 2006). Acacia nilotica (L.) Willd. Ex Delile and D. cinerea were also recommended as important supplementary source of protein for browsers like goat in semi-arid environment during the dry season (Smith et al., 2005). The collection of their fruit, grinding and feeding to goats has been considered as possible mechanism for controlling shrub encroachment into the rangelands (Mlambo et al., 2004). Figure 2-1: The endemic Kafue lechwe (Kobus leche kafuensis) and encroaching Mimosa pigra shrub-lochinvar National Park. Photo Sep The M. Pigra shrub forms impenetrable dense thicket and invades several wetlands forming threat for biodiversity resources. It is recognized by its competition with pasture lands. The seed germinates on moist soil of seasonally receding floodwaters. It can tolerate seasonal flooding and produces floating seeds which gives opportunity to spread to other places (Paynter, 2006; Indira, personal communication on her unpublished MSc thesis work on M. pigra mapping and modelling; own field observation). In the Kafue Flats it appeared as invasive shrub after mid 1980s. Its invasion have been considered as one aspect of change in the vegetation composition of the Kafue Flat following the change in flooding regime (Mumba and Thompson, 2005). Figure 2-2: a) D. cinerea shrub b) Acacia shrub 9

22 2.4 Image classification Image classification involves the analysis of multi-spectral image data and the application of statistically based rules. The principle is that pixel is assigned to a class based on its feature vector, by comparing it to predefined clusters in the feature space (Bakker, 2004). The two methods used are first, the use of a computer to examine each pixel in the image individually with a view to making judgments about pixels specifically based upon their attributes; and the second approach involves human interpreter extracting information by visual inspection of an image composed from the image data (Richards, 1986). In supervised classification method the classifier requires representative sample from the field data known as training areas. The classifier then classifies each pixel depending on the closeness to the training sample. Each pixel in the data set is then compared numerically to each category in the interpretation key and labelled with the name of the category it looks most like (Lillesand and Kiefer, 2004). In unsupervised classification the image data are first classified by aggregating them into the natural spectral grouping, or clusters, present in the scene. Then the image analyst determines the land cover identify of these spectral groups by comparing the classified image data to ground reference data (Lillesand and Kiefer, 2004). 2.5 Accuracy assessment The quality of the information derived from remotely sensed data is determined by using accuracy assessment methods. It allows comparing the pixels in your thematic raster layer to reference pixels, for which the class is known. This is a way of comparing your classification with ground truth data, previously tested maps, aerial photos, or other data (Leica Geosystems, 2003). It is accomplished by selecting a sample of pixels from the thematic map and checking their labels against classes determined from reference data gathered during field visits. This allows the possibility of checking whether it is wrongly or correctly classified using the ground truth data (Lillesand and Kiefer, 2004). 2.6 Vegetation change detection Change detection is one aspect of monitoring land cover. Direct field measurement and observation is the most accurate method of monitoring change. As the size of the area becomes large, however, sampling becomes essential which may further leads to subjective judgement and incompleteness (Torrion, 2002). As the area becomes bigger the cost involved and the time factor makes it impractical and unwise to make direct ground survey. This calls for the application of modern remote sensing in vegetation change detection studies. This in turn involves analysis of temporal and spatial spectral changes of satellite images taken for the same place. In this study, thus, the post classification change detection which involves overlaying classified maps in GIS environment and extraction of changes in land cover (Lunetta, 1999) was carried out. 10

23 2.7 Correlation and regression Correlation is a measure of closeness or the relative strength of linear association between two sample variables. This is carried out without assuming any causation between the two variables to be compared (Moore and McCabe, 2003). If we assume some sort of dependency between the variables to be compared we can think of carry out regression analysis which involves the relationship between dependent or response variable Y and the independent or explanatory variable X. It is a useful statistical technique to make an inference about the change in one set of variable based on its relation with other set of variable. Relation may be linear or nonlinear. Linear relation is the easiest and simplest which denotes any change in X results in a proportional change in Y. While in some cases curvilinear regression such as, exponential, logistic, etc. may exist (Snedecor and William, 1989; StatSoft, 2006; Harnett, 1982). 11

24 3 Materials and methods 3.1 Study area The Lochinvar National Park is geographically located between 15 o 43'05 'to 16 o 00'49 'S and 27 o 10'45 'to 27 o 18'30 'E. It is situated in central Zambia within the Kafue Flats along the Kafue River (Figure.3-1). The Flat in general has biologically diverse ecosystem which part of it is designated as internationally recognized wetlands site under the Ramsar Convention (Mumba and Thompson, 2005). It encompasses extensive plain of savannah wetlands having a total area of about 6,500 km 2. The diverse landscape of the area has supported diverse wildlife and vegetation community. It was the home of among the 10 best-stocked birdlife in the world and very high number of large herbivores dominated by the endemic Kafue lechwe (Ellenbroek, 1987). As part of the Kafue Flats the Park extends for 33 km from the Kafue River in the north to low wooded hills in the south with a total area of 428 km 2. The endemic Kafue lechwe dominate the park but also other wild animals like zebra, buffalo, oribi, bush pig, bush buck, reed buck also inhabit the area. Hippos and crocodiles are also common in the Chunga Lagoon (Zambian Wildlife Authority, 2005a). It was established as a ranch in 1908 by the British South Africa Company which later was declared as part of the Kafue Flats Game Management Area in Finally it was sold to the Zambian government and gazetted as a game reserve in 1966, and as a National Park in 1968 (Zambian Wildlife Authority, 2005a) Climate May to September is known as cool-dry season with temperature reaching 16 C but it gets cold at night. During hottest months between October and November temperature reaches up to 41 C. The average annual rainfall over the flat is between mm. The wettest season starts from November and extends up to April when rain usually occurs in the afternoon and night time (Kampamba, 1988) Landscape and vegetation The Park is situated on the southern edge of the Kafue Flats, a wide floodplain of the Kafue River between Itezhi-tezhi dam in the west and Kafue Gorge in the east (Zambia National Tourist Board, 2006). The park is generally recognized by three vegetation zones: The woodland, termitaria and the floodplain. The floodplain is largely characterized by hydrophyte water meadows like, Acroceras macrum Stapf, Panicum repens-leersia L. and Paspalidium obtusifolium (Del.) N. D. Simpson (Chabwela and Siwela, 1986; Ellenbroek, 1987). Other woody species of Mimosa pigra, different Acacia species and D. cinerea were also observed in the floodplain (own observation). The termitaria zone is characterized by the presence of several termite mounds with largely grassland and few 12

25 wooded vegetation. The ground cover of termitaria zone is dominated by Setaria sphacelata (Schumach.) Moss, Panicum maximum Jacq., Digitaria milinjiana (Rendle) Stapf, Brachiaria regulosa Stapf, and the overstorey by Combretum ghasalensa Engl. & Diels, Philiostigma thonningii, Albizia anthelmintica (A. Rich.) Brongn. (Chabwela and Siwela, 1986; Ellenbroek, 1987; own observation). Several Acacia shrubs were also seen as a pure stands in the grasslands of the termitaria zone. The southern area is mainly covered by woodlands dominated by Munga woodland, Combretum Loefl. and Colophospermum Mopane (Kirk ex Benth.) Kirk ex J. Leonard trees. The dominant grass species in this zone are Andropogon spp. L., Hyparrhenia spp. Fourn., Setaria spp. P. Beauv., Eragrostis spp. Wolf, and Panicum spp. L. (Ellenbroek, 1987; own observation). Lochinvar National Park Figure 3-1: Location of Lochinvar National Park Drainage The major river in this region is the Kafue River which originates along the watershed between Zambia and the Democratic Republic of Congo. The river meanders for a total of over 700 km, often forming floodplains or swamps, before flowing into the Zambezi River on the southern border of Zambia. The river as it drains 20% of Zambia s surface area; it is also the only source of life in the park. Moreover, the Kafue River forming a wetland regime provides source of water for extensive 13

26 endemism and biological diversity (Constantin and New, n.d). Except this we don t find any other permanent river in the park. However during high rainfall seasons small streams emerge that flow into the lagoon or remain within the park (Figure 4-6). 3.2 Materials used Table 3-1: Materials used in this study and their sources Materials 1. Digital Data Scanned topographic map of the park scale 1: 50,000 Landsat TM Satellite images of December 19, 1986, March 28, 1994 and ASTER March 09, 2005 Kafue lechwe aerial survey, October Other data Water level- Nyimba hydrological station (1980/ /05) 3. Software Arc GIS: Arc Map version 9.1 ERDAS IMAGINE version 8.7 Microsoft Office Applications R-Statistical Software 4. Field Equipment Measuring tape GPS Compass Binocular Geo-vision Geo-vision Source Zambian Wildlife Authority (ZAWA) Zambian Electric Supply Corporation (ZESCO) ITC ITC ITC ITC ITC ITC ITC ITC 3.3 Methods The methodological procedure followed in this study is presented using flow chart (Figure 3-2). It shows the steps followed beginning from acquisition and classification of multi-temporal satellite images of the study area to the extraction of the required information from both secondary and primary data to answer the research questions. The details of the main steps are described under the sub-titles of this section. 14

27 Land cover Primary and Secondary Data Satellite image 1986 Supervised classification Land cover map 1986 Satellite image 1994 Supervised classification Land cover map 1994 Satellite image 2005 Supervised classification Land cover map 2005 Training set Own lechwe observation (2006) Field observation Lechwe survey 2005 Secondary data Lechwe census Historical hydro data Attribute table & change map ( ) (GIS operation) Map overlay Attribute table & change map ( ) Attribute table & change map ( ) Subset the map based on each area of interest Observation Point data Create buffer of 400m at each point Create area of interest based on buffers Popula tion change Change in water level (Chunga) Quantitative information on shrub and grass cover change & Change maps Attribute table of each subset area Extract quantitative information on shrub and grass cover Join quantitative information in Excel Correlation and regression analysis Result Discussion, conclusion and recommendations Figure 3-2: Flow chart of the overall method used in this study Sampling Stratified random cluster sampling design was used to carry out primary field data collection. Several vegetation studies usually deal with stratified sampling because vegetation zones may show some strata. There were two reasons in choosing this method. The first reason was it provides separate estimates of the mean and variance of each stratum. Secondly, for a given sampling intensity, it often gives more precise estimates of the population parameter than would a simple random sample of the same size (Freese, 1990; Moore and McCabe, 1999). Based on this scientific ground, the study area was classified into 7 spectral classes using unsupervised classification on the recent satellite image, ASTER March The numbers of spectral classes were chosen based on background information, literature review about the vegetation cover of the study area and the spectral information

28 stratified random samples were generated based on the size of the strata in ERDAS IMAGINE 8.7. The coordinates of those points were entered into GPS and using its navigation facility the sampling points were visited on the field. Once reaching each sampling points on the field, 2 more cluster samples were laid 200 m north and south of each points (as adapted from van Gils et al., 2006). On the field additional 10 points with their clusters were visited which we considered as unique and unrepresented within the original random points generated. In general, the total number of samples visited in this study was 121. The overall sampling layout is presented on figure 3-2. At each sampling plot presence of shrub was recorded every 50 cm along line intercept of two perpendicular crossed lines of 20 m length laid north-south and east-west. From this, data on abundance was calculated and the type of shrub identified for each plot which further was used in training the satellite image. Field Observation Points Legend observation_points Kilometers Figure 3-3: Distribution of observation points on ASTER image, spectral band combination 3, 4, 2. GPS location of observation points (Appendix VII) 16

29 3.3.2 Digital satellite image processing Image pre-processing Landsat TM image of December 19, 1986 and March 28, 1994 and ASTER image of March 09, 2005 were selected for this research. Landsat of March 1994 was orthorectified from the source in WGS 84 and we did re-projection to the Zambian coordinate system (Map projection, UTM Zone 35; Projection method, Transverse Mercator; Datum, Arc 1950; and Ellipsoid, Clarke 1880). We also georeferenced ASTER image of March 2005 and Landsat of December 1986 using the same coordinate system mentioned above. In the process the thermal 6 th band of Landsat TM as well as the backward looking 3B and bands 10 to 14 of ASTER were excluded from layer stacking. The 15 m pixel size of ASTER image was re-sampled to 30 m resolution to make it ready for map overlay. Since a single ASTER scene was not covering the study area, two scenes were mosaiced to cover the whole of the study area. Moreover, the scanned topographic map of the study area was geo-referenced. The software used in this process was ERDAS IMAGINE version 8.7. Image classification One hundred and twenty one training sets were used to train the ASTER Image of March 09, 2005 which its acquisition time was close to the field work period. First it was classified into 9 cover classes using supervised maximum likelihood classifier in ERDAS IMAGINE, which later recoded into 6 required classes. The initial nine classes were water, D. cinerea shrub, Acacia shrub, M. pigra shrub, floodplain grass, termitaria grass, grass and herbs, submerged grass and woodlands. Originally, the above grasslands were divided into four because they were showing distinct spectral signature. Later they were recoded into one grass class. Therefore, the numbers of classes considered for the final land cover mapping were six (Figure 4-6). The classification result was assessed with 107 validation points (Appendix IX) collected from the field. Guided by the 2005 land cover classification and also based on field information about the previous land cover situation we extracted trainings classes for the classification of the Landsat 1986 and 1994 images through peer-visual interpretation. Similarly, step of recoding into 6 classes was also conducted for the two classified images. Since there was no field observation for those years accuracy assessment was not possible. Moreover, since the resolution of Landsat is 30 m and Aster image is 15 m we expect the underestimation of shrub cover for some small patches may not be detected by the pixel size of the sensors. Change detection In this study post classification change detection was carried out (Lunetta, 1999). First the three temporal images were classified separately into similar classes. Similar classes were given similar code and colour representation so that there will be no confusion of classes. Then three phases of land cover change was conducted using map overlay in GIS environment in ERDAS IMAGINE using its matrix utility. Namely, December 1986 March 1994, March 1994 March 2005 and December 1986 March The resulting change matrix attribute table was having various categories of cover changes. The attribute tables of the three change maps were further recoded to produce the relevant classes needed for the study. Finally, two types of land cover change maps were produced. The first was with the aim of detecting areas and proportions of grass and water body encroached by 17

30 shrubs within the above specified periods. In this case, the classes shown on the change maps were change of grass to shrubs, water to shrub, grass to woodlands, change of others, no change in water, no change in grass and no change in others. The second types of maps were those aimed to show all changes to D. cinerea, Acacia and M. pigra shrubs. In addition, detail information on areas change and rate of change for different classes were computed in their corresponding tables. 3.4 Kafue lechwe aerial survey The lechwe aerial survey was conducted between October 14 to 18, 2005 with joint collaboration of Zambian Wildlife Authority and World Wide Fund for Nature (WWF) - Zambia office. In this survey a stratified random sampling technique was used to count Kafue lechwe over the whole of Kafue Flats. First reconnaissance survey was conducted. Based on preliminary aerial reconnaissance survey, strata of high, medium and low densities were identified. Using global positioning system (GPS) boundaries of the strata were determined. Then, a series of strata covering the whole of Kafue Flats were laid. Two observers were assigned to count the animals within a swath of 400 m wide on right and left side of the aircraft. In the Lochinvar National Park all transects were located north of the edge of the woodlands, because from experience and the reconnaissance survey result the grazer, Kafue lechwe was not found within the woodlands (Zambian Wildlife Authority, 2005b). For this study 19 observation points which were covered by the survey in the Lochinvar National Park were taken for analysis. Moreover, since the numbers of observation points obtained from aerial survey were not sufficient to make inference about the population estimate and scientific judgement, own estimation made on the field at 26 GPS points were included in the study. In order to observe the trend in lechwe population estimate in the historical past, surveys from 1970 to 2005 obtained from secondary sources were also used. 3.5 Statistical relationship between variables Quantitative information on percentage shrub and grass cover was extracted from the classified map of March 2005 at lechwe observation points within 400 m radius using area of interest facility in ERDAS IMAGINE. This was the area considered to count lechwe at each observation plot during the lechwe aerial survey, The variables to be tested for possible correlation were percentage shrub cover, percentage grass cover, distance of observation points from the Chunga Lagoon and distribution of lechwe (in terms of count) at observation plots. The objective was to examine the association between each of the variables as well as consequently assess the impact of shrub abundance, grass abundance and distance from the lagoon on the spatial distribution of Kafue lechwe. Harnett (1982) indicated that in correlation analysis it is usually necessary to assume that both variables are normally distributed, while in regression analysis only the dependent variable needs to assume normal distribution. As bivariate population is usually far from normal all the variables indicated above were more or less skewed and square root data transformation (Freese, 1990) which brought relative improvement was applied. The result was two of the variables (Kafue lechwe count, and distance from the lagoon) have approximated normal distribution. The variables, shrub and grass cover, however, although there was slight improvement in skewness they were far from normal. As a result the non-parametric Spearmans correlation test was preferred to observe the closeness of the relationship between variables. For the regression analysis we considered distribution of lechwe as 18

31 response variable and shrub cover, grass cover and distance from the lagoon as explanatory variables. Since the dependent variable was approximated to normal distribution (Harnett, 1982) both simple and multiple regression analysis were possible. In addition, the assumption of normal distribution of the regression residuals was also checked to verify the fitness of the regression model (Moore and McCabe, 2003). 19

32 4 Results 4.1 Land cover mapping and analysis Classification accuracy The confusion matrix and Kappa statistics of the classification result for ASTER image of March 2005 (Figure 4-6) is shown in table 4-1. Table 4-1: Error matrix for ASTER image of March 09, 2005 Cover D.cinerea shrub Acacia shrub M.pigra shrub Grass Woodland Water Total Error of commission (%) Users accurac y (%) D.cinerea shrub Acacia shrub M.pigra shrub Grass Woodland Water Unclassif ied Total Error of omission Producer s accuracy Overall classification accuracy % Overall Kappa statistics The highest users accuracy in shrubs class was for D. cinerea followed by Acacia shrub. The shrub M. pigra showed relatively lower users accuracy (61.54%). The reason being the spectral signature of M. pigra was mixing largely with grass class. The users accuracy for grass class was 73.02%. Water and Woodland vegetation classes were having a user accuracy of 100%. Only 1 reference point was found out to be unclassified. In general, the overall classification accuracy was 75.7% with the Kappa statistics of The supervised classification result of Landsat December 1986 and March 1994 is 20

33 presented on figure 4-4 and figure 4-5 respectively. Since there was no field observation for those years accuracy assessment was not possible Satellite image classification The classification result of Landsat image of December 1986 (Figure 4-4) revealed that there was no area covered by D. cinerea and M. pigra shrubs during that time. Acacia shrub occupied a very small area. The classification of Landsat of March 1994 (Figure 4-5) has shown that D. cinerea and M. pigra shrubs covered areas near to the lagoon. D. cinerea covered special area close to which is now called Lechwe Tented Camp. M. pigra also occupied few areas near to the water body. In 1994, Acacia shrubs occupied a wider area than that of The March 2005 (Figure 4-6) satellite image classification has also revealed that D. cinerea has expanded its encroachment along the lagoon from south-east to north-east and some portions close to south-western part of the lagoon. Acacia shrubs occupied the central, western and some part of the southern grassland of the park. M. pigra also occupied areas extending from the north-eastern to the south-western part of the park close to the lagoon Land cover 1986, 1994 and 2005 The area under each land cover classes during the three periods is presented in table 4.2. The grass cover decreased continuously from 1986 (66%) to 1994 (58%) and in 2005 (49%). In contrary, shrubs (D. cinerea, M. pigra and Acacia shrubs) increased from 2% of the park area in 1986 to 16% in Of all other shrubs Acacia shrub was showing faster increase in aerial coverage as compared to other types of shrubs in the above mentioned periods. The area under woodland increased at a relatively slower rate from 19% of the park area in 1986 to 21% in The trend in permanent land covers during those periods is presented using bar chart on figure 4-1. Moreover, the relationship between permanent covers from 1986 to 2005, with shrubs combined together is shown with line graph in appendix I. Table 4-2: Land cover Cover class ha % cover ha % cover ha % cover Grass 23, , , M. pigra shrub , Acacia shrubs , , D. cinerea shrub Water 4, , , Woodland 6, , , Total 35, , ,

34 70 Cover (%) Grass M. pigra shrub Acacia shrub D. cinerea Cover class shrub Woodland Figure 4-1: Park area under different land cover December 19, 1986, March 28, 1994 and March 09, The area of the national park under water cover was fluctuating on the three image acquisitions times. This doesn t represent permanent water cover; rather it shows only the water cover at the time of image acquisition by the satellite. This is indicated on figure 1-2 by the chart showing daily measurement of the River Kafue water flow downstream of Itezhi-tezhi Dam which discharges into the Chunga Lagoon. From the chart we can understand that water level at Chunga Lagoon at any particular day or week can vary depending up on the release of water from the dam. As a result, to avoid confusion of interpretation, the water class is avoided from the graphic representation on figure 4-1. Instead, the situation of water extent at Chunga Lagoon best represented on figure 4-2 and 4-3. Although water level data of Nyimba station for pre-dam construction years could not be found, we observed the situation for the past 20 years (Figure 4-2). Nyimba is located downstream of the Itezhitezhi Dam at the entry point of Kafue River to the Chunga Lagoon and thus clearly represents the hydrological change in the Lagoon. The data is based on the daily record which is averaged to monthly and subsequently to the annual average (Appendix II). Based on this data we can observe that in early 80 s the annual average water level of the Chunga Lagoon was more or less higher than the one after 1985/86. The exception being in 2000/2001, the overall trend dropped after mid 80s. Pre and post-itezhi-tezhi dam hydrological situation at Chunga Lagoon was also best represented by water discharge from the River Kafue measured at Nyimba station (Figure 4-3). According to the graph, the pick discharge after the construction of the dam was much lower than before the construction of the dam causing a decline in annual average water level at Chunga Lagoon (Mumba and Thompson, 2005). In other words, the average water extent of the Chunga Lagoon post Itezhitezhi decreased. This strengthens our hypothesis that states encroachment of woody species into the grassland is associated with change in hydrological factor which is discussed in detail in the next chapter. 22

35 Water level (m) Average annual water level / / / / /97 Year 1998/ / / /05 Figure 4-2: Average annual water level above sea level at Nyimba hydrological station 1980/ /05 Source: Zambian Electric Supply Corporation. Figure 4-3: Mean monthly discharge (m 3 s -1 ) from the Kafue River post and pre- lthezi-thezi Dam operation. Source: Mumba,

36 Land Cover December 1986 Chunga lagoon Legend Park office Stream Road Acacia shrub Grass Water Woodland Kilometers Figure 4-4: Classified Landsat TM image of December 19, 1986 based on area knowledge 24

37 Chunga Lagoon Land Cover March Kilometers 540 Park office Stream Road Acacia shrub D. cinerea shrub Grass M. pigra shrub Water Woodland Legend Figure 4-5: Classified Landsat TM image of March 28, 1994 based on area knowledge Chunga Lagoon Land Cover March Kilometers 540 Park office Stream Road Acacia_shrub D. cinerea shrub Grass M. pigra shrub Water Woodland Legend Figure 4-6: Supervised classification ASTER image of March 09, 2005 based on field observation and training samples

38 Comparison of land cover was also conducted for the period between 1986 and Total area under grass cover decreased at a rate of 1.4 % per year. In contrary Acacia shrub cover increased at a rate of 22.1 % per year which is the highest rate of shrub cover increase. D. cinerea and M. pigra were not detected in 1986 and their percentage rate could not be calculated. The total area occupied by D. cinerea and M. pigra cover classes in March 2005, however, was and 1, ha respectively. The woodland vegetation also increased at a rate of 0.5% per year (Table 4-3). The situation of water class as discussed above is a bit different and can not be accounted for permanent increase in aerial extent. Table 4-3: Area under each land cover from December 1986 to March 2005 Cover class Increase Decrease Increase Decrease ha. ha ha ha ha/ year % /year ha/ year % / year Grass 23, , , D. cinerea shrub N.A - - Acacia shrub , , M. pigra shrub 0 1, , N.A - - Water 4, , * - - Woodland vegetation 6, , Total 35, , * Water class represents only cover on the time of image acquisition and thus avoided from calculation of rate. N.A= not applicable because there is no cover in Land cover change Land cover change 1986 to 2005 Land cover change result obtained from overlaying the classified images of December 1986 and March 2005 is presented on figure 4.7. Visual interpretation of the maps revealed that most of the areas of the grassland encroached by shrubs (D. cinerea, M. pigra and Acacia, merged together) were the one located adjacent to the lagoon and identified as floodplain grassland. The shrubs density decreased as we go away from the lagoon. There were also few areas of previous water body now occupied by shrubs. Statistical output of the change matrix (Table 4-4) also revealed important facts. The total area of original grass cover changed to all shrubs (category 1, 2 and 3) was about 4, ha, which was 12.4% of the total area of the park and 18.71% of the grassland area of the With this, the rate of change from grass to shrubs comes 1% per year. The conversion of grass to acacia shrub had the highest percentage (6.24 %) of the park area. Of the total area of water body (4,741.2 ha) occupied in 1986, ha was changed to all types of shrubs in This accounted to 2.26 % of the water body and 0.31% of the total area of the park in The area change indicated in the table as from shrubs to grass is purely due to few spectral confusion created between some grass and 26

39 shrub classes. A total of 3, ha of grassland were changed to woodland, which constitutes 9.67% of the total area of the National Park and 14.59% of the original grassland. Changes around the Lagoon shown as change of others, is largely from water to grass or grass to water. We didn t want to show as permanent change in the classes because of the very inconsistency of the water cover associated with regulated flooding which is liable to change within a week or month (as described in section 4.1.3). But the fact is that the size of water cover in the park shrank through time (Figure 4-2, and 4-3). The above statistical fact, thus, showed that the proportion of change of grassland to shrub is much higher than its change to any other classes which in turn resulted in the corresponding decline in grass cover. All cover class changes to shrubs from 1986 to 2005 were also assessed using map overlay. With the result we observed that among the conversion to the three shrubs, the conversion of all cover classes to acacia shrub was so fast holding 0.41% of the total park area per year followed by conversion to M. pigra with 0.29% per year (appendix III). Land Cover Change December 1986 to March 2005 Chunga Lagoon Legend Park office Stream Road Change of grass to shrubs Change of grass to woodland Change of others Change of water to shrubs No change_grass No change_others No change_water Kilometers Figure 4-7: Land cover change in Lochinvar National Park within two decades (December 19, March 09, 2005). 27

40 Table 4-4: Land cover change in Lochinvar National Park (December 1986 to March 2005) Category Change in cover Change in ha % Change (of the park area) Rate of change ha/year 1 Grass to Acacia shurb 2, Grass to D. cinerea shrub Change class 3 Grass to M. pigra shrub 1, Total changes of grass to shrubs 4, Water to Acacia shurb Water to D. cinerea shrub Water to M.pigra shrub Total Changes of water to shrubs Grass to water Grass to Woodland vegetation 3, Total Change of grass to others 4, Water to grass Water to woodland Woodland to M. pigra shrub Woodland to Acacia shrub Woodland to D. cinerea shrub Woodland to Water Woodland to grass 1, Acacia shrub to grass Acacia shrub to water Acacia shrub to Woodland Acacia shrub to D. cinerea shrub Acacia shrub to M. pigra shrub Total changes to other classes 3, Change of grass and water to shrubs Change of grass to other classes Change of other classes Total changes 12, No change in shrubs (Acacia) No change in grass, water and woodland , No change in shrubs No change in others Total no changes 22,

41 Land cover change 1986 to 1994 Analysis of land cover change was also carried out to establish the trend of change within intermediate years. Accordingly, out of the total grassland area of 1986, about ha which accounted to 7.6% was changed to shrubs in This change holds 5% of the park area. Of this, the change to Acacia shrubs was the fastest followed by change to M. Pigra shrub. During this period about ha of the water cover changed to shrubs which accounted to 0.06 % of the park area. In addition to the occupation of the previous grass cover by shrubs, about ha of the grassland were also overtaken by the woodland (Table 4-5). The visual interpretation of the change map clearly revealed the fact that shrubs were expanding more along the floodplain grasslands near to the Lagoon and central-northern portion (Figure 4-8). The change of some shrubs to grass is purely attributable to spectral confusion. The analysis of all other cover changes to shrubs showed that the conversion to Acacia shrub was at annual rate of 0.54 % of the park area followed by D. cinerea with 0.09 % of the park area per year (Appendix IV). Table 4-5: Land cover change in Lochinvar National Park (December 1986 to March 1994) Category 1 Change in cover (1986 to 1994) Grass to Acacia shurb Change in ha % Change (of the park area) Rate of change ha/year 1, Grass to D. cinerea shrub Grass to M. pigra shrub Total changes of grass to shrubs 1, Water to Acacia shurb Water to D. cinerea shrub Water to M. pigra shrub Total change of water to shrubs Grass to water 1, Grass to woodland 2, Total changes of grass to others 4, Water to grass Water to woodland Change class Change of grass and water to shrubs Change of grass to other classes Change of other classes Woodland to M. pigra shrub Woodland to Acacia shrub

42 Category Change in cover (1986 to 1994) Change in ha % Change (of the park area) Rate of change ha/year Change class 13 Woodland to D. cinerea shrub Woodland to water Woodland to grass 2, Acacia shrub to grass Acacia shrub to water Acacia shrub to woodland Acacia shrub to D. cinerea shrub Acacia shrub to M. pigra shrub Total chnges to other classes 3, Total changes 10, No change in shrubs (Acacia, D. Cinerea, M. pigra shrubs) No change in shrubs 22 No change in grass, water and woodland 2, No change in others Total no changes 2, Land cover change 1994 to 2005 Analysis of land cover change for the periods (Table 4-6) revealed that of the total grassland area of 1994, 18.98% changed to all types of shrubs in The rate of change was ha per year which was faster than that of the year Within those periods ha of the original water cover was changed to shrubs which were at a rate of ha per year. The rate at which shrubs occupied the previous water surface was also faster than that of This can be observed from the change map that considerable areas of previous water areas were occupied by shrubs (Figure 4-9). Next to shrub encroachment, grassland was also suffering by the occupation of woodlands where 3, ha area was over taken in this period. The overall conversion of all other classes to shrubs as revealed by the map overlay indicated that the rate of conversion showed a slight increase in all cases than that of The rate of conversion of D. cinerea has grown from 0.09 to 0.16% of the total park area per year, for Acacia from 0.54 to 0.64 % and that of M. pigra from 0.09 to 0.49 % of the park area per year (Appendix V). 30

43 Table 4-6: Land cover change in Lochinvar National Park (March 1994 to March 2005) Category 1 Change in cover (1986 to 1994) Grass to M. pigra shrub Change in ha % Change (of the park area) Rate of change ha/year 1, Grass to Acacia shurb 2, Grass to D. cinerea shrub Total change of grass to shrubs Water to M. pigra shrub , Water to Acacia shurb Water to D. cinerea shrub Total change of water to shrubs Grass to water Grass to woodland 3, Total change of grass to others 3, Water to grass Water to woodland Woodland to M. pigra shrub Woodland to Acacia shrub Woodland to D. cinerea shrub Woodland to Water Woodland to grass 2, Acacia shrub to grass Acacia shrub to water Acacia shrub to Woodland Acacia shrub to D. cinerea shrub Acacia shrub to M. pigra shrub D. cinerea shrub to M. pigra shrub D. cinerea shrub to Acacia shrub D. cinerea chrub. to grass Change class Change of grass to shrubs Change of Water to shrubs Change of Grass to other classes Change of other classes 31

44 Category Change in cover (1986 to 1994) D. cinerea shrub to water D. cinerea shrub to woodland Change in ha % Change (of the park area) Rate of change ha/year Change class M. pigra to grass M. pigra shrub to Acacia shrub M. pigra shrub to D. Cinerea shrub M. pigra shrub to water M. pigra shrub to woodland Total changes to other classes 5, Total changes 13, No change in shrubs No change in (Acacia, M. pigra and shrubs D. cinerea) 32 No change in grass, water and woodland 21, No change in others Total no changes 21,

45 Chunga Lagoon Kilometers Park office Stream Road Change of grass to shrub Change of grass to woodland Change of others Change of water to shrub No change_grass No change_others No change_water Legend Land Cover Change December 1986 to March 1994 Figure 4-8: Land cover change in Lochinvar National Park (December 19, 1986 to March 28, 1994) Chunga Lagoon Kilometers Park office Stream Road Change of grass to shrub Change of grass to woodland Change of others Change of water to shrub No change_grass No change_others No change_water Legend Land Cover Change March 1994 to March 2005 Figure 4-9: Land cover change in Lochinvar National Park (March 28, 1994 to March 09, 2005)

46 4.2 Distribution and population size of Kafue lechwe Spatial distribution of Kafue lechwe Mapping of the distribution of Kafue lechwe in Lochinvar National Park using the October 2005 aerial survey and field observation has shown that lechwe observation points were distributed in the northern portion of the park which is closer to the Chung Lagoon (Figure 4-10). As one goes southwards from the lagoon points of observations become thinner where nothing was located in the woodlands. We have also assured during our stay in the park from October 9 to 14, 2006 that it was hardly possible to see Kafue lechwe in the woodlands and in the upper termitaria. The number of lechwe counted at each observation points also vary. The statistical analysis in section deals with analysis of the spatial distribution of Kafue lechwe and factors influencing its distribution. Spatial Distribution of Kafue Lechwe Chunga Lagoon Legend Kafue_lechwe_count Stream Road Park office Acacia_shrub D. cinerea shrub Grass M. pigra shrub Water woodland Kilometers Figure 4-10: Distribution of Kafue lechwe in Lochinvar National Park based on aerial survey of October 2005 and own field observation. 34

47 The distribution of lechwe within different landscape zones in the Kafue Flats before the construction of the Ithezi-thezi dam as summarized by Chabwela and Ellenbroek (n.d) is presented in table 4-7. The description is aimed at explaining the temporal and spatial variation of lechwe distribution with variation in natural flooding regime. This helped us to analyse how dam construction also modified the distribution of Kafue lechwe which in turn has aggravated bush encroachment. Table 4-7: Monthly distribution pattern on lechwe in the Kafue Flats before the construction of the Ithezi-thezi dam. Period Levees & lagoons Tall grass floodplain Grassland December x x Short grass floodplain grassland Termitaira grassland January x x x February x x x March x x Woodland April x x May x x June x x July x x August x x September x x x October x x November x x Source: (Chabwela & Ellenbroek, n.d) Statistical analysis for the relationship between variables Descriptive statistics The summary statistics presented on table 4-8 was used to get better understanding about the structure and distribution of the data set of the variables understudy. The variables were shrub cover, grass cover, the shortest possible distance of observation plots from the lagoon and Kafue lechwe count (distribution). Shrub cover at the observation plots varied from zero shrub cover to maximum of 80.81% cover with high variability indicated by the standard deviation. As regards to the grass cover some plots showed 100% cover with minimum of 10%. The maximum distance of lechwe observation points from the lagoon was 6 km with average distance of 2 km. Lechwe count at observation points varied from 300 lechwes to 5 (raw data -Appendix X). 35

48 Table 4-8: Descriptive statistics of the variables No. Parameter Shrub cover (%) Grass cover (%) Distance from Chunga Lagoon (km) Kafue lechwe count 1 Mean Median Minimum Maximum Standard deviation Correlation analysis between paired variables The non-parametric Spearman s Correlation Coefficient (R) showed that there is very high negative linear association (-95.0%) between grass and shrub cover. This indicated that at any particular observation plot as the shrub cover increased the grass cover decreased because of the occupation by shrubs and vice versa. We have also observed a fairly strong negative association between shrub cover at observation plots and the distance of observation plots from the lagoon indicating the decline in shrub cover as we go away from the Chunga Lagoon. The grass cover at observation plots and distance from the lagoon were having moderately strong positive correlation (74%), which indicated that abundance of grass cover increased as we go away from the lagoon. The distribution of lechwe was also having moderately strong negative association (-78.2%) with shrub cover and also moderately positive association with grass cover (72.6%). This implies that Kafue lechwe count was generally getting lower in place of high shrub abundance and vice versa. Similarly, the count was generally getting higher in places of high grass cover. The association between distance from the lagoon and lechwe distribution was rather weak with R = Table 4-9: Summary of Spearman's correlation matrix Shrub cover Grass cover Distance from the Chunga Lagoon Kafue lechwe count Shrub cover Grass cover Distance from the Chunga Lagoon Kafue lechwe count

49 Regression analysis of Kafue lechwe distribution on explanatory variables Literature review has shown that there is some sort of causation between shrub and grass abundance and distance from the lagoon on the one hand, and lechwe distribution on the other (section 2.2). As a result, in our regression analysis we considered shrub cover, grass cover and distance from the lagoon as explanatory variable and distribution of lechwe (lechwe count) as response variable. The hypothesis was that the distribution of lechwe at each observation plot was influenced by the abundance of shrub cover. The scatter plots and the corresponding regression line (Figure 4-11) showed that there is negative linear relationship between the two variables with slope and intercept The statistics result of the linear regression in table 4-10.a showed the p-value of 1.0e-10 which is very close to zero, and adjusted R 2 of This indicates that, at 43 degree of freedom and 95% confidence interval, we can reject the null hypothesis that states there in no relationship between shrub cover and lechwe count. Therefore, shrub cover has explained 61.7 % of the variation in Kafue lechwe distribution. sqrt(lechwe_count) Intercept: slope: The regression equation relating the two variables is, Y = X (equation 1) Where, X = % shrub cover at observation plot. y= lechwe count at observation plot. sqrt(shrub_cover) Figure 4-11: Regression of lechwe count on shrub cover Table 4-10: Summary of the simple regression statistics a) Regression of Lechwe count on shrub cover Estimate Std. error t value Pr(> t ) Statistics (Intercept) < 2e-16 Adj-R 2 =0.617 Sqrt (Shrub cover) e-10 p-value= 1.00e-10 df= 43 37

50 b) Regression of Lechwe count on grass cover (Intercept) Adj- R 2 = Sqrt (Grass cover) e-09 p-value= 6.41e-09 df= 43 c) Regression of Lechwe count on Distance from the lagoon (Intercept) sqrt(distance from the lagoon) Adj- R 2 = 0.17 p-value: df= 43 Second, it was necessary to test if other variables are also more important to explain lechwe distribution. We hypothesized that lechwe as a grazer; its distribution is influenced by the abundance of grass. The scatter plot and the best fitted regression line (after square root data transformation), which is linear (Figure 4-12) indicated that there is positive linear relationship between the explanatory variable grass abundance and lechwe distribution with slope of 1.74 and intercept The regression statistics on table 4-10.b also showed that 53.7% of the variation in lechwe distribution is explained by grass abundance. Therefore, with 43 degree of freedom and p-value of 6.41e-09 which is < 0.05, with 95 % being correct we reject the null hypothesis that states there is no relationship between the two variables. sqrt(lechwe_count) Intercept: slope: The regression equation relating the two variables thus is: Y = X (equation 2) Where, X = % grass cover at observation plot. Y= lechwe count at observation plot sqrt(grass_cover) Figure 4-12: Regression of lechwe count on grass cover 38

51 Distance from the Chunga Lagoon has explained 17 % of the variation on lechwe distribution, which is considered as very weak relationship. The scatter plot on fig 4-13 also showed the spread of much of the observations out from the fitted regression line confirming the existence of large residuals. The significance of p-value (which is less than the critical value of 0.05), however, indicates that there is certain level of relationship which don t allows us to reject the alternative hypothesis. Therefore with 95% being correct we accept the alternative hypothesis that states distance from the Lagoon has weak influence on the distribution of Kafue lechwe (Table 4-10.c). sqrt(lechwe_count) Intercept: 5.34 slope: The regression equation relating the two variables thus is: Y= X (equation 3) Where, X = distance from the lagoon. Y = lechwe count at observation plot. sqrt(distance_from_the_lagoon) Figure 4-13: Regression of lechwe count on distance from the Chunga Lagoon Diagnostics of the simple regression analysis Residuals were plotted to assess the fitness of a regression line in which the best fitting one should explain the structure of the relation and what is left over (the residuals) should just be noise. Thus, for the best fitted least square regression line the residuals should be approximately normally distributed (Moore and McCabe, 2003). The quantile-quantile plots and the corresponding Shapiro-Wilk normality test (W) were carried out to test the normality of residuals. With the result, in all three cases the quantile-quanitle plot showed the residual plots of the regression are aligned along the Q-Q line which is a proof for their approximating normality (Figure 4-14). Shapiro test of normality has also ascertained that the regressions of lechwe count on shrub cover with % of being correct with the p-value of ; The regression of lechwe count on grass with 97.45% and p-value of ; the regression of lechwe count on distance from the Chunga Lagoon at 95.82% and p-value of , the residuals are normally distributed (Table 4-11). Therefore, we can conclude that the regression lines well fitted to show the above three relationships. In the following section we examined the impact of combined explanatory variables on the distribution of lechwe in Lochinvar National Park using multiple regression analysis. 39

52 Normal Q-Q Plot Normal Q-Q Plot Sample Quantiles A Sample Quantiles B Theoretical Quantiles Theoretical Quantiles Normal Q-Q Plot Sample Quantiles C Theoretical Quantiles Figure 4-14: Regression residual Quantile-Quantile plots of A = lechwe count on shrub cover B = lechwe count on grass cover C = lechwe count on distance from the lagoon Table 4-11: Shapiro-Wilk normality test statistics Residuals Residuals of the regression of lechwe count on shrub cover Residuals of the regression of lechwe count on grass cover Residuals of the regression of lechwe count on distance from the lagoon p-value W Multiple regression of lechwe distribution on explanatory variables The result of simple regression analysis has led to the need for looking at the impact of multiple variables on the distribution of Kafue lechwe. Due to the strong negative co-linearity of grass and shrub cover (Table 4-9), to avoid redundancy of information that lowers R 2 we didn t combine the two to explain the variation for distribution of lechwe. First, shrub cover and distance from the lagoon were taken as explanatory variable to explain the response variable lechwe distribution. The result showed that the two together explained 61.7% of the variation in lechwe distribution (Table 4-12.a). 40

53 This result was equal to the one explained by shrub cover alone as a single variable (Table 4-10.a). As shown in the p-value of the variable distance from the lagoon its coefficient was statistically insignificant to explain the variation in the distribution of lechwe when we combine it with shrub cover in the model. The combined regression equation explaining the variation in lechwe count Y would be: Y = X X 2 (equation 4) Where, X 1 is % shrub cover at observation plot and X 2 is distance from the lagoon. Second, grass cover and distance from the lagoon were tested for their relationship with distribution of lechwe. The overall adjusted R 2 has shown slight improvement which is with significance value of p close to 0 (Table 4-12.b). Compared to the regression explained by the grass cover alone in the simple regression model, the contribution of distance from the Lagoon in combined model was very low. As shown by the p-value of distance from the lagoon, its coefficient (0.07) is also statistically insignificant when combined with grass cover. However, since it added slight improvement for R 2 we can t say that it contributed nothing. The combined regression equation explaining the variation in lechwe count Y is thus, Y = X X 2 (equation 5) Where, X 1 is % grass cover at observation plot and X 2 is distance from the lagoon Table 4-12: summary of the multiple regression statistics a) Regression of Lechwe count on shrub cover and distance from the lagoon Estimate Std. error t value Pr(> t ) Statistics (Intercept) e-11 sqrt(shrub cover) Sqrt(Distance from the lagoon) e b) Regression of Lechwe count on grass cover and distance from the lagoon (Intercept) sqrt(grass cover) e-07 Sqrt(Distanc from the lagoon) R 2 = p-value: 6.8e-10 df = 42 R 2 = p-value: 1.17e-08 df = 42 41

54 Diagnostics of the multiple regression analysis Diagnosis of residual quantile-quantile plot of the combined regression analysis (Figure 4-15 A and B) showed that the residuals have approximated normal distribution since they are almost aligned along the quantile-quantile line to indicate the fitness of the combined regression model. This has been further tested using Shapiro-Wilk normality test (W). The result showed that in both cases the p- value is significant to accept the null hypothesis that the residual distribution is normal (Table-4-13). Normal Q-Q Plot Normal Q-Q Plot Sample Quantiles Theoretical Quantiles A Sample Quantiles Theoretical Quantiles B Figure 4-15: A ) Q-Q plots of regression residuals lechwe count explained by shrub cover and distance from the lagoon; B) regression residuals lechwe count explained by grass cover and distance from the lagoon. Table 4-13: Shapiro-Wilk normality test statistics for residuals of combined variables Residuals Regression of lechwe count on shrub cover and distance from the lagoon Regression of lechwe count on shrub cover and distance from the lagoon p- value W

55 4.2.3 Change in the population size of Kafue lechwe. Historical census data beginning early 1970s obtained from several sources were compiled by several writers (Kapungwe, 1993; Simukonda et al., 2002) (Appendix VI). All census periods covered the whole of Kafue Flats and it was hardly possible to distinguish the part covering the Lochinvar National Park. No documented raw spatial data was also found that could allow us to extract the part of the National Park. The census years which were possible to identify the estimate within the Park based on different reports was for the years 1993, 2001 and The estimated total lechwe population within the park in 1993 was 13,917 (Kapungwe, 1993); in 2001 the population within the park was estimated about 13,327 (Simukonda et al., 2002). The figure has dropped to around 6,137 in 2005 (Zambian Wildlife Authority, 2005b). The population estimate of 2005 has dropped by 55.9% from that of The situation has been reflected also in the overall estimate of the flats. The lechwe population within the flat has been relatively stable from 1970 to 1973 with an estimate of between nearly 110,000 to 94,000 respectively (Figure 4-16). Rapid decline is observed in 1975 with around 81,000 and subsequent sharp decline to 45,000 in 1981 and 41,000 in From 1987 to 1993 there was a fluctuation in population between 50,000 to nearly 70,000. From 1999 on wards there was a continuous decline in population which the lowest than ever before (38,448) is recorded in The continuous population decline from 1993 to 2005 within Lochinvar national Park discussed above is, thus, in harmony with the population decline within the Kafue flat between those periods Population estimate Census year Figure 4-16: Population estimate of the Kafue lechwe within the Kafue Flat over the past 35 years ( ). 43

56 5 Discussion 5.1 Landcover quantification The pattern of land cover in Lochinvar National Park was having tremendous difference during the study period (1986 to 2005). This can easily be recognized by side-by-side inspection of the maps produced from the classification of satellite images of the two years. On the map of December 1986 (Figure 4-4), grass covered the vast majority of the park s area which accounted to 66% of the total area of the park. Apart from water, the other dominant land cover that can easily visually recognized was the woodland vegetation which occupied most of the south-eastern and few areas in the western portion of the park. The woodlands during this year occupied 19% of the total area of the park. The acacia shrub on the map can only be recognized by careful observation. Digital quantification, however, revealed that only 2% of the park area was occupied by acacia shrub. The 1986 land cover map represents the situation of only 8 years after the operation of the Ithezi-thezi dam which is considered as the root cause for the disruption of the natural vegetation composition of the Kafue Flats. The land cover pattern changed considerably after nearly 2 decades, in During this year the grassland size dropped to 49% of the total area of the park. M. pigra and D. cinerea showed a pattern of occupation adjacent to the lagoon but in spatially distinct location and by no means mixed with each other. Acacia shrub, however, was widely spread throughout the park with particular domination in the middle floodplain as well as the western part of the area which was previously occupied by grass. The dominant species of acacia shrubs identified during the field work were Acacia Karroo, Acacia kirkil Oliver, Acacia nilotica, Acacia albida Delile, Acacia robusta Burch. and Acacia nigrescens Oliver. In some places they form a dense thicket which was very difficult to penetrate because of their thorn and dense short canopy. In some parts they form a sparse cover mixed with different types of grass and few single stands of other types of trees. In areas where acacia shrub was prevalent we noticed the presence of several termite mounds up to 1m height and tall grasses like Hyparrhenia rufa (Nees) Stapf and Setaria incrassate (Hochst.) Hack. Before 1980s, shrub and tree growth were restricted to higher places of the termitaria zone (Ellenbroek, 1987). Field interview with local people, however, revealed that new termite mounds have emerged into the previous grassland area, especially in the past 10 years. Termitaria zone is generally considered as the transitional zone between woodland and floodplain. D. cinerea and M. pigra shrubs are not detected by Landsat image of December In 1994, however, M. pigra covered 242 ha which later in 2005 grew to 1,952 ha. Mumba and Thompson (2005) as well as field discussion with the local people indicated that before 1980 M. pigra occupied only less than two hectares near to the lagoon now called Nampongwe stream. The field observation of September 2006 which was dry season revealed that in some places it formed scattered patches mixed with grass cover, while in other places it occupied a wider area which was difficult to penetrate because of its thorns. It looked green in wetter parts located close to the lagoon. These areas 44

57 previously were part of the main floodplain largely dominated by highly palatable grass like Penicum repens, Vossia cuspidate, Echinochaloa scabra and Acroceras macurm. D. cinerea covered 618 ha of land in 2005 which in 1994 satellite image it was detected in a very small localized area of 261 ha. In most of the places it is found in a continuous interlocked stands and together with its long and strong thorns it doesn t allow easy movement. Moreover, one can also recognize a rather slow northward expansion of woodlands into the grassland due to primary succession as visualized on figure 4-7, as change of grass to woodlands. The general trend of land cover in 1986, 1994 and 2005 is a continuous decline in grassland cover and the corresponding remarkable rise in shrub covers (see Figure 4-1 and Appendix I). 5.2 Shrub encroachment and driving forces Visual comparison of the land cover map of December 1986 (Figure 4-4) and land cover change map of December 1986 to March 2005 (Figure 4-7) gives a clear impression that most of the changes occurred in areas where previously were covered by grass. These areas were mainly recognized as floodplains and water meadows which were giving palatable grass to the wildlife community (Ellenbroek, 1987). In total about 7,724 ha grass cover of the 1986 was changed to shrubs and woodlands. Of this 56% is change to shrubs. The grass communities changed to D. cinerea and M. pigra shrubs were the one located closer to the lagoon and were also areas regularly inundated by flood for long season. Areas changed to acacia were distributed in the central part of the park. In addition, about 107 ha water cover of the 1986 was permanently changed to shrubs in From the above analysis we can observe that the largest proportion of the changes of grass to other classes is occurred by encroachment of shrubs. The average rate of change from grass to shrubs from 1986 to 2005 was, thus, about 228 ha per year which is 1% per year (Table 4-4). The question was what caused the change in vegetation composition specifically bush encroachment? This type of question is a subject of controversy in different parts of the world which several writers recommended to be approached in relation to the local driving forces (Moleele et al., 2002; Laliberte et al., 2004; Tefera et al., 2006). The ecology of most African wetlands is influenced by socioeconomic developments. The growing economic interest to the African wetland resources such as hydroelectric development, fishing, hunting and agriculture has been subject to the alteration of the natural ecosystem. The construction of the dam on the Lake Chad s catchments in Nigeria has resulted in the recession of the shoreline by 40 km between April 1984 and January Because of dyke construction for irrigation in the Senegal River Delta 2,400 ha of floodplain was lost. Other examples such as the construction of the Cabora Bassa dam on Zambezi River, Aswan dams on Nile River, Pongolapoort Dam in Republic of South Africa directly caused the flooding of the reservoir and disruption of the natural regular flow downstream in the floodplains. The downstream change was explained in terms of lack of nutrient sedimentation and variation in soil moisture. This has resulted gradual change in vegetation composition and associated animal life system (Streever, 1999). Before the construction of Ithezi-thezi dam, the natural flooding regime in the Lochinvar National Park was such that flooding begins in November and December where the lower floodplains start to inundate. With increasing run-off caused by local rainfall, the water level raise and wider areas continues to inundate through January, February and March. Under normal rainfall condition towards 45

58 the end of rainy season (April and May) much of the Park area except the upper termitaria and the woodlands were submerged. Most of the aquatic and semi-aquatic plants were growing well during that time. Other types of grass were also able to grow fast enough to keep pace with the gradually rising flood water. Following the decrease in run-off upstream of the Kafue Flats with ending rain season, the flood start to recede being drained by Kafue River and by that time most of the plants have matured. After that the floodplain were giving best quality grass for wildlife in general and the dominant Kafue lechwe in particular for the rest of the dry season (June to November) (Kafue Basin Research Committee of the University of Zambia, 1978). The construction of Ithezi-thezi Dam in the upper catchments of the Kafue River was intended to assure a continuous backing of water for the Kafue Gorge main power plant which is located downstream from Lochinvar National park. This has greatly affected the natural seasonal flow and extent of flooding (Kapungwe, 1993; Howard and Williams, 1982). As part of the Kafue Flats the driving force behind change in vegetation cover in Lochinvar National Park is attributable to the change in the hydrological pattern following the construction of mainly the Ithezi-tezhi Dam. The long-term variation in the flood extent within Lochinvar National Park is clearly observed by the general decline of the water level measured at Nyimba hydrological station from 1982/83 to 2004/05 averaged from daily measurement (Figure 4-2). The decline in the peak water flow of the Kafue River during the major rain season after the dam construction measured at Nyimba station (Figure 4-3) is also strong evidence about the shrink in water extent of the Chunga Lagoon in the park. The earliest possible Landsat TM image of December 19, 1986, was used to observe the pattern of vegetation cover following the construction of the dam and have impression about the situation before. The sideby-side inspection of the land cover map on figure 4-4, change maps on figure 4-8 and 4-9 revealed that there was encroachment of shrubs to some of the areas of previous water covers as well as in floodplain grass communities located in close proximity to the lagoon. The following ecological analysis is given for the association of shrub encroachment with the hydrological factors Nutrient depletion Before the construction of the dam, the regular seasonal flooding was important to transport and deposit large amount of silt and organic matter over the large part of the floodplain. The nutrient cycle downstream at the floodplains dramatically disrupted because of the trapping of minerals behind the dam. Esselink et al., (1991) in the study conducted elsewhere indicated that mineral depletion from the soil stock due to over utilization favoured shrub encroachment; the nutrient uptake by the plant is most effective at the nutrient rich upper section of the soil profile which can be reached by the roots of the plants. This constituted only small section of the stock in the soil profile. The issue was related to the ability of some shrubs to tap nutrition from sub-surface soil and assimilate, while others like some short rooted grass can utilize only if available on top soil in soluble form and if not die out. The same situation happened on the grazing plains down stream of Aswan High dam and other river basin (section 1.1) after dams construction, their productivity declined (Ven et al., 1991). Following the construction of the dam up stream of the Kafue River at Ithezi-thezi, occurred deficiency of some important nutrients which could have been deposited by silt. The continuous export and assimilation of some minerals including phosphorus (P) and nitrogen (N) (Esselink et al., 46

59 1991) by the grass communities and wildlife over a long time could not give any other possibility to be returned back to the soil with the required amount and speed. This ended-up with continuous depletion of nutrients from the top soil which in the final analysis resulted in food shortage for the short rooted grass communities. The situation of P which is less complex in keeping balance in plantsoil system as compared to N fixation makes it more limiting factor for plant growth. In addition, the shrink in the flooding extent in the floodplain and the short duration of flooding has been a barrier for some nutrients from being ready in soluble form to be assimilated by grass and herbaceous communities (Esselink et al., 1991). D. cinerea which its root pattern is categorized as vigorous root sucker together with co-occurring acacia shrubs which have extensive lateral and taproots and both deciduous shrubs (Gebrekirstos et al., 2006), however, have the capacity to withstand drought by absorbing nutrition in dry condition. In addition D. cinerea is also recognized by its ability to withstand nitrogen deficiency by fixing N from the air (Mlambo et al., 2004; van Gils, 1988 ). The final result, thus, was the establishment and expansion of shrubs in places of grass taking additional advantage of not being palatable by the Kafue lechwe. This is also related to the issue of grazing pressure to be discussed in the next section Change in the grazing pattern As indicated in section 5.2, before the construction of Ithezi-thezi Dam the pattern of natural flooding forced Kafue lechwe to gradually move out from the floodplain starting the beginning of the rainy season (November) to the end of the rain season (May) during which lechwe were restricted to graze in termitaria zone (Table 4-7). In some areas of the floodplain the water depth was reaching 5 m above the ground so that no grazing was possible (Kafue Basin Research Committee of the University of Zambia, 1978). That was the time when the floodplain grass gets time to regenerate and mature until it will be ready for the next dry season grazing. Following Ithezi-thezi Dam, The long rain season flow of River Kafue and the supplying runoff have been trapped behind the dam for the need of regular supply of water to the hydroelectric generation downstream of the Lochinvar National Park in dry season. This completely changed the grazing pattern and allowed Kafue lechwe to graze all year round in the floodplains. It is quiet obvious that the grass production per unit of land became lesser than the requirement by the animals causing overgrazing and biomass depletion. This further gave way for unpalatable shrubs to easily expand by using the less competitive advantage created in using the available limited moisture and nutrient Seed dispersal Studies conducted elsewhere indicated that extraordinary flooding and disturbance plays a major role in seed dispersal (Parolin, 2006; Vogt, 2006). A number of acacia shrub species observed in the national park and D. cinerea propagate mainly by their seeds (Storrs, 1995). The highly invasive, M. pigra also propagate by its seed (Heard, 2005). The frequent irregularity in water level of Chung Lagoon emanated from controlled flooding is thus an advantage for fast propagation of the seeds to expand their range easily across the grassland being transported by extreme flooding (Mumba and Thompson, 2005; Laliberte et al., 2004). That is why the density of shrubs (especially D. cinerea and M. pigra) established was higher near to the frequent drift lines in close proximity to the lagoon 47

60 (Figure 4-6; own observation). Therefore, change in the natural flooding regime and associated irregularity of flooding favoured shrubs to encroach wide area of the grassland Other factors Although we can not ignore the influence of fire as a long-term impact (Bok, 1999), field observation and interview with the park authorities showed that the whole eastern section of the park which is relatively drier during dry season and vulnerable to frequent fire because of its closeness to settlement was not as such encroached by shrubs (Figure 4-6). The issue of encroachment by domestic animals to cause overgrazing is also very minimal in the Lochinvar National Park. That is because the park has defined boundary and allowing grazing by domestic animals is banned by law. In addition, the regular patrol by scouts and the fine discourages illegal grazing (Mweene, Personal Communication) It is also worthwhile to consider why D. cinerea and M. pigra formed a spatial separation in their encroachment pattern? Literature review demonstrated that M. pigra forms dense, mono-specific thicket which supports reduced diversity (Heard et al., 2005). A study conducted in Australia also revealed that M. pigra seedlings easily germinate on moist soil left by receding flood line (Paynter, 2006). Other study conducted in Australia has proved that the survival of M. pigra largely depends up on availability of light and its growth rate is retarded under shads and canopy cover (Steinbauer, 1998). Based on the above studies we can notice that in the Lochinvar National Park M. pigra occupied in the spatially distinct location because it favours reasonably sufficient soil moisture areas for its growth and areas free from any other shade-forming plants like D. cinerea. A lot of new seedlings as well as matured stems of M. pigra covered the fore-front floodplains in close proximity to the Chunga Lagoon indicating that mimosa is fast enough to colonize new moist soil areas which are left by the shrink of the flood line. The ecology of D. cinerea, however, enables it to colonize areas which becomes dry for long period and nutrient deficient areas (Gebrekirstos et al., 2006; van Gils, 1988 ). This justifies the why of this shrub is located inland on relatively higher drier places next to the lagoon-fore-fronted M. pigra. It is also apparent that the inland located covers of M. pigra are the one established long time ago when the flood line was closer to that point and continued its expansion afterwards being propagated by floating seed dispersed in time of huge release of water from the Ithezi-thezi Dam. This can easily be traced by looking at the land cover map of 1994 on figure 4-5 where the beginning of M. pigra invasion are traced nearer to the pools of water and the lagoon. Other factors responsible for spatial isolation of the two shrubs are left for further detail studies. In summary, based on the ecological analysis given in section 5.2 we can conclude that moisture stress and the depletion of soil nutrients and above ground biomass which their root cause is change in the flooding regime through time resulted in shrubs to overwhelm the hydrophytes floodplain grass communities. 48

61 Chunga Lagoon Figure 5-1: Oblique view of shrub encroachment near to the Chunga Lagoon taken from the aircraft during the field work (October 2006). Photo by Indira Thomas. 5.3 Distribution of Kafue lechwe and shrub encroachment The study of lechwe distribution needs careful understanding by relating it with the historical process of shrub encroachment and the current land cover situation of the Park. Previous chapters revealed that over the past two decades a large area of grassland which was used as the habitat of lechwe is overtaken by invasive alien and native shrubs. Visual impression of the distribution map figure 4-10 showed many observation points are located close to the water body. The association between digital land cover categorization at each observation points and the corresponding distribution of lechwe, however, revealed interesting facts. The quite high correlation of shrub and grass cover with the distribution of lechwe revealed the fact that there is fairly strong association between them. Lechwe count at observation plots was positively associated with grass cover and vice versa. On the other hand lechwe count was negatively associated with shrub cover. As reflected by regression analysis (Table 4-10), shrub abundance explained the distribution of lechwe well followed by grass abundance. This implies that the distribution was strongly negatively influenced by shrub cover. This emanates from the very nature of lechwe being a grazer to avoid shrubby areas. Grass cover explained the variation in Kafue lechwe fairly good in the second level indicating that the presence of large population is also dependent on the availability of grass. The distribution map has taken our attention to observe the impact of distance from the Chunga Lagoon. The result was so weak though not to be neglected at all. Out of 45 observation points 26 of them which make 57% were located within 2 km distance from the lagoon. However, large bush cover 49