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*Corresponding author: 

Email: twesigyeck@yahoo.com, +256 782 353 775  https://dx.doi.org/10.4314/eajbcs.v3i1.5S  

 

 

Assessment of Vegetation in Murchison Falls National Park Five Years after the Completion of 

Oil and Gas Exploration 

 

Hindrah Akisiimire1, William Tinzaara2,  Keneth Tumwebaze3 and Charles K.Twesigye1*, 

1Department of Biological Sciences, Kyambogo University, P.O. Box 1, Kyambogo, Kampala, Uganda 
2Department of Agricultural Production, Kyambogo University, P.O. Box 1, Kyambogo, Kampala, 

Uganda 

3Department of Environment Management, College of Agricultural and Environmental Sciences, 

Makerere University, P.O. Box 7062, Kampala, Uganda 

 

 

KEYWORDS:  

Biodiversity hotspot;  

Ecological restoration;  

Plant species diversity;  

Uganda 

 

 

 

 

 

 

 

 

 

 

 

 

ABSTRACT 

Uganda discovered petroleum deposits in commercially viable quantities in 2006. Most 

areas such as Murchison Falls National Park (MFNP) where petroleum has been 

discovered overlap with wildlife and nature conservation with high biodiversity and 

sensitive ecosystems. This study sought to study the vegetation frequency index, relative 

abundance and diversity in former oil pads five years after the completion of oil and gas 

exploration in MFNP. We counted all observed plant species following a systematic 

random sampling technique using a (1mx1m) quadrat for herbs, (5mx5m) quadrat for 

shrubs, and (10mx10m) quadrat for trees. Data was collected using a 60m line transect to 

record the identified plant species. The study used a total of eight quadrats per transect and 

the total number of transects were 32. A quadrat was placed every after 7m along the line 

transect in and outside the oil pads. Each transect begun from the center (placard) of the 

oil pad going in directions of center to north, center to south, center to east, and center to 

west. This was carried out for purposes of replication and the same procedure was carried 

out for the control area. The same procedure was conducted at a frequency of wet (4 th-30th 

April 2019) and dry (1st-30th June 2019) seasons. The counted data was later transformed 

and analyzed using t-statistical tests and chi- square tests in SPSS version 20 software. 

The study recorded uniform and non-uniform plant species and the mean vegetation 

diversity of 1.9±0.06 in oil pads and 1.71±0.12 in control areas. The study identified 31 

different plant species, and among these, seven plant species were recorded in oil pads, 

eight in control areas. The results of vegetation relative abundance and diversity between 

oil pads and control areas were generally similar. However, the study observed some plant 

species such as Desert date (Balanites aegyptiaca) in control areas that were completely 

absent in oil pads. Further studies focusing on edaphic assessments, soil chemical, and 

biological analysis to better understand the impacts of oil exploration in the protected area 

are recommended. 

 

INTRODUCTION 

Oil was first discovered in western Uganda in 

the 1870s, but commercially viable oil was only 

confirmed in 2006 (Rwakakamba and Lukwago, 

2013). Approximately 2.5 billion barrels of 

commercially viable oil of $2 billion worth in 

annual revenue for twenty years (Shepherd, 

East African Journal of Biophysical and Computational Sciences 

Journal homepage : https://journals.hu.edu.et/hu-journals/index.php/eajbcs 
  

Hawassa University

College of Natural & Computational Sciences

Year 2021

Volume xx No xx

 
Research article

mailto:twesigyeck@yahoo.com
https://dx.doi.org/10.4314/eajbcs.v3i1.5S


East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

44 
 

2013) was discovered under the Ugandan 

portion of the Albertine Rift in 2006. This 

would make Uganda the fifth largest oil 

producer in Africa (Vokes, 2012). The 

government of Uganda went ahead in the early 

2000s and licensed the exploration of oil 

prospects in the country. The government made 

agreements with oil companies which include 

Dominion Uganda Ltd, Tullow Oil plc, Heritage 

Oil and Gas Ltd and Neptune Petroleum Uganda 

Limited (NEMA, 2009). These companies 

discovered oil quantities in the Albertine Rift 

and along the boundary of Uganda and 

Democratic Republic of Congo (DRC). Uganda 

hosts a number of protected areas including the 

Queen Elizabeth National Park, Rwenzori 

Mountains National Park (both are World 

Heritage Sites), Kibaale, Semlikiand Murchison 

Falls National Parks, plus Toro-Semliki and 

Kabwoya wildlife reserves (USAID, 2007). 

Seven of the ten national parks and over 20 

forest reserves are located in the Albertine Rift. 

The Albertine Rift provides ecosystem services 

such as tourism, water systems through lakes, 

rivers and wetlands. It also supports people by 

providing a source of livelihoods via forests, 

wetlands, minerals and fertile soils. 

Global economic development and demand for 

energy have led to an expansion in oil and gas 

exploration, and oil and gas reserves in many 

cases overlap with protected areas and 

biodiversity Hot spots (Harfoot et al., 2018). For 

example, the Albertine Rift is a known hotspot 

of mammals, birds and plant species in Uganda. 

The wildlife law in Uganda allows exploration 

and extraction of oil under protected areas, 

provided that the impacts to the environment are 

minimized and where possible the natural 

habitat is restored after extraction. Initial 

drilling was promising, and it expanded from 

the Kabwoya Wildlife Reserve to other sites 

around Lake Albert including Murchison Falls 

National Park (MFNP). Uganda, Gabon and the 

Democratic Republic of the Congo are some of 

the African regions where oil exploration has 

occurred in protected areas (Coghlan, 2014; 

Dowhaniuk et al., 2018). 

Human activities in a national park can lead to 

habitat loss from an increasing and expanding 

human population which is the greatest threat to 

a wide diversity of species (Brooks et al., 2002). 

Further causes of habitat loss can be recreation 

and transportation which may have an array of 

immediate and long-term impacts on species 

within wilderness parks (Trombulak and 

Frissell, 2000). Kityo (2011) also noted that 

other potential impacts due to increased human 

presence and traffic would include increased 

incidents of road kills, soil spills (an oil or fuel 

spill) on site which would result into an 

ecological disaster, destroying wildlife grazing 

rangelands and wildlife. Clearing of vegetation 

along seismic lines and pipelines can fragment 

habitat and alter predator–prey interactions 

(Borasin et al., 2002). Construction of drill 

pads, new roads and fences results into habitat 

loss and exacerbates fragmentation (UWA, 

2012). Additionally, improved access to remote 

areas can increase poaching and the oil spills 

can have devastating effects on entire 

ecosystems (Johnson, 2007; Rwakakamba et al., 

2014). Northrup and Wittemyer (2013) pointed 

out energy development impacts on wildlife as 

pollution, removal of vegetation for roads and 

oil pads, increased poacher access, altered 

animal migration and foraging habits. Oil and 

natural gas development poses heavy threats and 

dangers towards environmental conservation 

and the health and safety of the earth’s 

biodiversity (Ericson, 2014). Increased road 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

45 
 

traffic due to mining can also threaten protected 

areas due to increased access to biodiverse 

regions (Laurance et al., 2009), causing drastic 

change to land cover due to large human 

migration into areas with low human population 

density (Wilkie and Carpenter, 1999; Wilkie et 

al., 2000; Laurance et al., 2014).  

From an ecological perspective, development 

can cause large-scale and novel alterations to 

ecosystems, resulting in habitat loss and 

fragmentation (Leu et al., 2008; McDonald et 

al., 2009) that strongly impact terrestrial 

wildlife populations and their ecosystems. The 

most important and large-scale cause of habitat 

fragmentation is the expansion and 

intensification of human land use (Burgess and 

Sharpe, 1981). Habitat fragmentation has three 

major components, namely loss of the original 

habitat, reduction in habitat patch size, and 

increasing isolation of habitat patches, all of 

which contribute to a decline in biological 

diversity within the original habitat (Wilcox and 

Murphy, 1985). 

Oil extraction has shown to put biodiversity 

conservation at risk, as exemplified in the Niger 

Delta, where oil spills and gas flaring have 

damaged biodiversity, destroyed mangrove 

forests, contaminated beaches, coated birds, 

endangered fish hatcheries, and disrupted food 

webs (Ugochukwu and Ertel 2008).Human 

disturbances from oil and gas activities affect 

wildlife at different levels. It may affect the 

structure, composition, and distribution of 

wildlife populations on a landscape level 

(Wassenaar, 2005; Vistnes and Nellemann, 

2008). Various studies have indicated that 

wildlife displacement is a result of disturbance. 

For example, in the US state of Virginia, 

reclaimed coal mines had fewer salamanders 

(Corrozino, 2009). In the state of Montana, elk 

continued to avoid a drill pad even after drilling 

was completed (Dyke and Klein, 1996). The 

state of California registered lower bird species 

richness and abundance four years after the 

restoration of flood control structures (Pattern 

and Rotenberry, 1998). Wyoming State in the 

US experienced the displacement of elks for 2 

weeks during the seismic surveys (Gillin, 1989). 

Land-use changes and degradation of 

ecosystems by humans are the biggest global 

threats to biodiversity and ecosystem services 

(Foley et al., 2005; Hooper et al., 2012). 

Oil exploration and production has various 

phases ranging from seismic surveys, 

exploratory drilling which confirms the 

existence or absence and quantities of 

hydrocarbon reservoirs. This is followed by 

appraisal drilling whose intention is to know if 

the reservoir is economically viable for 

development. This is followed by development 

and production, and the final stage is 

decommissioning (Kasimbazi, 2012). In some 

cases, this is followed by restoring the site to 

environmentally sound conditions. It is achieved 

by implementing measures to motivate site re-

vegetation and constant monitoring of the site 

after closure. For the case of MFNP, all drill 

pads and pad access roads north of the Nile 

were restored upon completion of appraisal 

drilling in early 2014 (Fuda, 2018). Restoration 

involved removal of all equipment and murram 

(a laterite soil used for building roads in East 

Africa) at the site, scarification of subsoil, 

reinstatement of topsoil and translocation of 

native grasses from nearby areas to the 

decommissioned access road and pad footprint 

(Total E&P Uganda, 2013). There was no 

reforestation of native trees or shrubs, which 

caused in restored sites being more profoundly 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

46 
 

dominated by grasses, in relative to surrounding 

areas. Thus this study sought to assess the status 

of vegetation of the former oil pads post 

exploration stage. We were able to achieve that 

by studying the vegetation composition in 

former oil pads by comparing it with sites that 

are presumed to have never gone through 

anthropogenic disturbances.  

MATERIALS AND METHODS 

Study Area 

Murchison Falls National Park (MFNP) is 

located in the northwestern region of Uganda 

and the study area is in the northern part of the 

park which is the main tourism circuit area. The 

study sites were located in Exploration Area 1 

and they included Jobi 4 with a coordinate of 2 
o20ˈ09.5 ̎N, 31 o29ˈ52.4 ̎E and Jobi East 7 

having a coordinate of 2o20ˈ45.4 ̎ N, 

31o32ˈ26.8  ̎ E (Figure 1). The study area 

consists mainly of mosaic grassland, dense 

borassus woodland, open borassus woodland; 

open woodland, wooded grassland and 

bush/shrub. The park’s topography is rolling, 

reaching a maximum elevation of 1,291 m at 

Rabongo Hill in the south east of the park, and 

the lowest elevation of 619 m at Lake Albert on 

the rift valley floor in the west. The park is hot 

with mean minimum temperature of 22°C and 

maxima of 29°C all year round. The eastern part 

of the park is wetter than the western part; 

Chobe to the East receives around 1,500 mm 

whilst Paraa receives about 1,100 mm per year. 

Murchison Falls National Park has two rainy 

seasons, from mid-March to mid-June, and from 

August to November (UWA 2001). The two 

exploration sites were drilled and restored by 

replanting of vegetation at different time periods 

(Table 1). Control areas were outside the 

selected oil pads within the same location. 

Restoration involved removal of all equipment 

and murram (a laterite soil used for building 

roads in East Africa) at the site, scarification of 

subsoil, reinstatement of topsoil and 

translocation of native grasses from nearby 

areas to the decommissioned access road and 

pad footprint (Total & Uganda, 2013). There 

was no replanting of native trees or shrubs, 

which caused in restored sites being more 

heavily dominated by grasses, in relative to 

surrounding areas  

 

Table 1: Time period of exploration and restoration of the study sites 

Exploration Site Drilled Restoration completed by 

Jobi 4 March- April 2013 June 2013 

Jobi East 7 July- August 2013 May 2014. 

 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

47 
 

 

Figure 1: Location of study sites in Murchison Falls National Park in northwest Uganda 

Research Design  

The study used quantitative research designs 

which involved purposive sampling to select the 

exploration sites and control areas. This was on 

basis of easy accessibility, the cost involved in 

travelling, time available, and sites must be 

under the mandate of Uganda Wildlife 

Authority. The oil pad sites under the study 

were selected based on the fact that they must 

be somewhat a habitat to the mammals in the 

park. The control area sites were selected based 

on the assumption that they had the same 

environmental conditions as the oil pads (Jobi 4 

and Jobi East 7) and had never gone through 

any human disturbance. The control areas were 

located 120m away from the oil pad sites. Plant 

counts were replicated for both wet (April 2019) 

and dry (June 2019) seasons in and outside the 

oil pads. The study conducted replicated counts 

along transect lines as one of the sampling 

principles to ensure that difference in encounter 

rate (number of objects detected per unit survey 

effort) can be sufficiently estimated. All transect 

lines were replicated following similar 

randomization scheme to give all locations in 

the study area a known, non‐zero probability of 

being covered by a transect (Figure 2). The 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

48 

study used a dichotomous key to identify the 

plants during the study. Identification of the 

plants was made at the sites without carrying 

samples to herbarium because it would be 

tedious. Moreover, the research permit issued to 

us to conduct research in a protected area does 

not permit carrying plant species outside the 

park. One of the research assistants involved 

during data collection was a qualified botanist 

experienced in plant identification, which made 

plant identification easy.  

 

 

Figure 2:(A) is the 1x1m quadrat used to count plants along a transect, (B) is the placard bearing 

the oil pad name, time of drilling and restoration, (C) is the borehole that once supplied water to 

the oil pad camp. 

Data Collection 

Plant species counts were conducted in and 

outside the former oil pad sites using 

observation and recording method. A systematic 

random sampling technique (Greig-Smith, 

1983) was followed by using a 1 x 1m quadrat 

for herbs, 5 x 5m quadrat for shrubs, and 

(10x10m) quadrat for trees. Data was collected 

following a 60m line transect to record the 

identified plant species. A quadrat was placed 

every after 7m along the line transect in and 

outside the oil pads. In total 8 quadrats x 4 line 

transects were followed for the sites under the 

study. Each transect begun from the center 

(placard) of the oil pad going in directions of 

center to north, center to south, center to east, 

and center to west. This was carried out for the 

purposes of replication in order to get the true 

representation of each site and the same 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

49 

procedure was carried out for the control area. 

The same procedure was conducted at a 

frequency of wet (4th-30th April 2019) and dry 

(1st-30th June 2019) seasons. It should be noted 

that the study intentionally measured vegetation 

frequency index, vegetation relative abundance 

and vegetation diversity but did not put in to 

account the relative cover of the observed plant 

species due to the limited time and resources 

that were available for the study. The study was 

primarily concerned with the uniformity and 

composition of the plant communities as a 

whole not the nature of plants and coverage 

across the sites under the study. 

Data Analysis 

Vegetation Frequency Index 

The vegetation frequency index was determined 

using Equation 1. The obtained frequency 

indices were analyzed using Raunkier’s law of 

frequency (1962), which is often used to study 

the homogeneity or uniformity of plant species 

in an area. 

𝐹𝐼 = {
𝑁𝑜. 𝑜𝑓 𝑢𝑛𝑖𝑡𝑠 𝑖𝑛 𝑤ℎ𝑖𝑐ℎ 𝑡ℎ𝑒 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑜𝑐𝑐𝑢𝑟𝑒𝑑

𝑇𝑜𝑡𝑎𝑙 𝑛𝑜. 𝑜𝑓 𝑢𝑛𝑖𝑡𝑠 𝑠𝑡𝑢𝑑𝑖𝑒𝑑
} 𝑥 100 … … (1) 

This law of frequency assumes bimodality 

occurrences to describe vegetation abundance 

per unit area, which assumes that species are, 

either present or absent. In Raunkiaer’s law, 

species are categorized in levels/classes based 

on frequency as: level A (0-20%); B (21-40%); 

C (41-60%;) D (61-80%); and E (80-100%). 

The normal frequency ratio is valuable in 

several kinds of studies in testing the 

homogeneity of the vegetation in a given area. 

Frequency levels are interpreted as 

A>B<C>D<E; In general, the higher class E has 

greater homogeneity/uniformity of the 

vegetation. The most essential point being that 

class E should be larger than class D with 

greater number of species in class E than in D. 

Class A means the plant species under study are 

very scarce, B means occasional presence, C 

means infrequent presence, D means frequent 

presence and E means abundant or very 

numerous presences of the plant species under 

the study.  

Vegetation Relative Abundance 

The vegetation relative abundance (RA) was 

determined by employing Equation 2, where A 

refers to the observed individual plant species. 

𝑅𝐴

= {
𝑇𝑜𝑡𝑎𝑙 𝑛𝑜. 𝑜𝑓 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝐴

𝑇𝑜𝑡𝑎𝑙 𝑛𝑜. 𝑜𝑓 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 𝑜𝑓 𝑎𝑙𝑙 𝑠 ㅳ 搠𝑐𝑖𝑒𝑠 𝑟𝑒𝑐𝑜𝑟𝑑𝑒𝑑
𝑥 100} (2) 

However, the study compiled mean vegetation 

abundance of each plant species observed to 

compare the mean values using t statistical tests. 

Mean vegetation relative abundance (𝜇) was 

computed by summing up the total number of 

each plant species (x) observed divided by the 

total number of quadrats used in the study 

(Equation 3). 

𝜇 =
𝑆𝑢𝑚 𝑜𝑓 𝑝𝑙𝑎𝑛𝑡 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑥

𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑞𝑢𝑎𝑑𝑟𝑎𝑡𝑠
… … … … … … … … . … . . … … (3) 

All data sorting and computing was conducted 

using Microsoft excel sheets before being 

transferred to SPSS software for further t-

statistical tests. 

Vegetation Diversity 

Vegetation diversity was computed using 

Shannon Weiner diversity index (H) that was 

determined by Equation (4). The corresponding 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

50 

H Max values and equitability values were 

calculated as well as to help make scientific 

conclusions of the collected data. Calculations 

were determined using Microsoft Word Excel 

2010 before exporting it to SPSS version 20 for 

t - statistical analysis. Vegetation relative 

abundance and diversity between oil pads and 

control areas were analyzed using t statistical 

tests in SPSS version 20 at p=0.05 significance 

level. 

𝐻 = ∑ p𝒾 ln p𝒾 … … … … … … … … . … … … … . … … … … … … … (4)

s

i=1

 

In the Shannon index, p is the proportion (n/N); 

of individuals of one particular species present 

(n) divided by the total number of individuals 

present (N), ln is the natural logarism, Σ is the 

sum of the calculations, and s is the number of 

species. H max values are determined when 

each group has the same frequency referred to 

as maximum diversity possible [log(x)]. 

Shannon equitability value or Evenness (E) was 

also determined using Equation (5). 

𝐸 =
𝐻

𝐻𝑚𝑎𝑥
… … … … … … … … … … … … … … … … … … … … … . (5) 

Where H= Shannon-Weiner diversity index, 

Hmax = ln(s) and S = total number of species in 

the sample. 

RESULTS 

Vegetation frequency index per transect 

The frequency index analysis from the study 

shows that some plant species are more uniform 

than others (Table 2). The plant species that 

were observed to be uniform in both oil pads 

and control areas include Thatching grass 

(Hyparrhenia hirta), Cat's tail drop seed 

(Sporobolus pyramidalis), Nut grass (Cyperus 

rotundus) and Wandering jew (Commelina 

benghalensis). Plant species which are more 

uniform in oil pads than control areas include 

Garden signal grass (Urochloa panicoides), 

Hippo grass (Vossia cuspidate), Creeping wood-

sorrel (Oxalis corniculata), Star grass (Cynodon 

dactylon), Goats weed (Ageratum conyzoides), 

Devil horsewhip (Achyranthes aspera), Pickerel 

weed (Pontederia cantata), Tick berry (Lantana 

camara), Wait a bit thorn (Acacia mellifera), 

White thorn acacia tree (Vachellia constricta), 

and Candle bush (Senna alata). However, some 

plant species were recorded to be less uniform 

in oil pads than control areas and they include 

Feathered chloris (Chloris virgate), Bur bristled 

grass (Setaria verticillata), Desert date 

(Balanites aegyptiaca), Hoket horn (Arisonia 

abyssinica), Garden pink-sorrel (Oxalis 

latifolia), Borassus palm tree (Palmyra palm), 

Edible canna (Canna eduls), Guatemala 

(Tripsacum laxum), Sticking weed (Acacia 

okidetalia), Treedax daisy (Tridax procumbens), 

and Whistling acacia (Acacia hoki). Other 

recorded plant species in the study had similar 

uniformity in oil pads and control areas and they 

include Finger grass (Digitaria eriantha), 

Fibrous drop seed (Sporobolus stafianus), Nandi 

grass (Cetera ancient), Wild canny lilly flower 

(Canna indical), and Baboon apple (Annona 

glabra). 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

51 

 

Table 2: Frequency Index, Frequency Classes, and Vegetation Relative Abundance of the observed plant species per transect 

in oil pads and control areas. 
Observed Plant Species Scientific Name OP-FI FC CA-FI FC OP-VRA CA-VRA Sig. Value 

Thatching grass  Hyparrhenia hirta 100 E 87.5 E 103.8±30.6 169.6±47.8 * 

Cat's tail drop seed Sporobolus pyramidalis 100 E 87.5 E 95.8±20.1 148.1±41.8 * 

Nut grass  Cyperus rotundus 100 E 100 E 42.3±9.8 95.5±20.0 * 

Wandering jew Commelina benghalensis 100 E 100 E 48.6±10.2 58±8.5 * 

Feathered chloris Chloris virgata 12.5 A 50 C 9.8±4.9 57.5±28.1 * 

Bur bristled grass  Setaria verticillata 0 A 12.5 A 0±0 0.75±0.74 *** 

Desert date  Balanites aegyptiaca 0 A 37.5 B 0±0 9.8±8.9 *** 

Hoket horn  Arisonia abyssinica 0 A 12.5 A 0±0 2.8±2.7 ** 

Candle bush  Senna alata 12.5 A 0 A 4.1±4.1 0±0 *** 

Garden signal grass  Urochloa panicoides 50 C 0 A 1.4±1.4 0±0 ** 

Hippo grass  Vossia cuspidata 50 C 0 A 7.8±3.1 0±0 *** 

Creeping wood-sorrel  Oxalis corniculata 50 C 37.5 B 18.6±11.6 14.6±8.0 NS 

Finger grass  Digitaria eriantha 50 C 50 C 17.4±8.9 9.8±4.0 NS 

Garden pink-sorrel  Oxalis latifolia 50 C 75 D 15.3±8.4 9.8±4.5 NS 

Star grass  Cynodon dactylon 87.5 E 75 D 14.5±5.5 13.4±4.2 NS 

Fibrous drop seed Sporobolus stafianus 25 B 37.5 B 11.1±8.9 14.1±10.4 NS 

Whitethorn acacia tree Vachellia constricta 37.5 B 12.5 A 0.9±0.4 0.9±0.9 NS 

Baboon apple Annona glabra 25 B 12.5 A 0.9±0.6 10.6±10.6 NS 

Borassus palm tree Palmyra palm 12.5 A 50 C 0.3±0.2 2.6±1.5 NS 

Goats weed  Ageratum conyzoides 62.5 D 25 B 8±3.7 0.9±0.7 NS 

Nandi grass  Cetera ancient 12.5 A 12.5 A 0.6±0.6 1.5±1.5 NS 

Wild canny lilly flower Canna indical 50 C 50 C 4.6±2.1 5.5±2.2 NS 

Devil horsewhip  Achyranthes aspera 12.5 A 0 A 0.3±0.2 0±0 NS 

Edible canna  Canna eduls 0 A 12.5 A 0±0 0.4±0.4 NS 

Guatemala Tripsacum laxum 0 A 12.5 A 0±0 0.3±0.2 NS 

Pickerel weed  Pontederia cantata 12.5 A 0 A 2.8±2.7 0±0 NS 

Sticking weed  Acacia okidetalia 0 A 12.5 A 0±0 0.1±0.1 NS 

Tick berry  Lantana camara 12.5 A 0 A 2.9±2.9 0±0 NS 

Treedax daisy  Tridax procumbens 0 A 12.5 A 0±0 2±1.9 NS 

Wait a bit thorn  Acacia mellifera 37.5 B 0 A 0.8±0.4 0±0 NS 

Whistling acacia  Acacia hoki 0 A 25 B 0±0 3±2.0 NS 
OP = Oil Pads, CA = Control Areas, FI = Vegetation Frequency Index / Percentage Frequency, FC = Raunkiaer’s Frequency Classes, A = (0-20%), B = (21-40%), C = (41-60%), D = (61-80%), E = 

(81-100%), Raunkiaer’s Formula A>B>C<D<E, OP-VRA = Oil Pad Vegetation Relative Abundance, CA-VRA = Control Area Vegetation Relative Abundance, Sig.Value = Significant Value, NS= Non 

Significant difference, *(p<0.05), **(p<0.01), ***(p<0.001), Total number of quadrats per transect= 8, Total number of  transects in oil pads = 16, Total number of transects in  control areas = 16 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

52 

 

Vegetation relative abundance per transect  

The vegetation relative abundance in oil pads 

has no significant difference from the vegetation 

relative abundance in control areas (t= -1.946, 

d.f=30, p=0.061). However, the results show 

that there were some plant species that were 

significantly more abundant in control areas 

than in the oil pads (Table 2) which include 

Thatching grass (Hyparrhenia hirta), Cat's tail 

drop seed (Sporobolus pyramidalis), Nut grass 

(Cyperus rotundus), Wandering Jew 

(Commelina benghalensis), Feathered chloris 

(Chloris virgate), Bur bristled grass (Setaria 

verticillata), Desert date (Balanites aegyptiaca), 

and Hoket horn (Arisonia abyssinica). On the 

other hand, some recorded plant species were 

more significantly abundant in oil pads than 

control areas and they include Candle bush 

(Senna alata), Garden signal grass (Urochloa 

panicoides), and Hippo grass (Vossia 

cuspidata).  

 

Table 3: Plant species recorded per transect in oil pads and control areas 

Species Common Name Scientific Name Type of Plant Oil Pads Control Areas 

Baboon apple Annonaglabra Shrub + + 

Borassus palm tree Palmyra palm Tree + + 

Bur bristled grass Seteriaverticullata Grass - + 

Candle bush Sennaalata Tree + - 

Cat's tail drop seed Sporoboluspyramidalis Grass + + 

Creeping wood-sorrel Oxalis corniculata Grass + + 

Desert date Balanites aegyptiaca Shrub - + 

Devil horsewhip Achyranthesaspera Shrub + - 

Edible canna Canna eduls Shrub - + 

Feathered chloris Chlorisvirgata Grass + + 

Fibrous drop seed Sporobolusstafianus Grass + + 

Finger grass Digitariaeriantha Grass + + 

Garden Pink-sorrel Oxalis latifolia Grass + + 

Garden signal grass Urochbapanicoides Grass + - 

Goatsweed Ageratum conyzoides Grass + + 

Guntamala Tribsacumlaxom Grass - + 

Hippo grass Vossiacuspidata) Grass + - 

Hokes horn Harrisoniaabyssinica Grass - + 

Nandi grass Cetera ancient Grass + + 

Nut grass Cyperusrotundus Grass + + 

Pickerel weed Pontederia cantata Grass + - 

Star grass Cynodondactylon Grass + + 

Sticking weed Acacia okidetalia Grass - + 

Thatching grass HyparrheniaHirta Grass + + 

Tick berry Lantana Camara Grass + - 

Treedax daisy Tridaxprocumbens Grass - + 

Wait a bit thorn Acacia mellifera Shrub + - 

Wandering jew Commelinabenghalensis Grass + + 

Whitethorn acacia tree Vachelliaconstricta Tree + + 

Whistling acacia  Acacia hoki Tree - + 

Wild canna lilly flower Canna indical Shrub + + 

Total number of plant species present  23 24 

+ = Plant species present, - = Plant species absent, OP = Oil Pads, CA = Control Areas, Total number of quadrats per 

transect= 8, Total number of transects in oil pads = 16, Total number of transects in control areas = 16 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

53 

 

The study also recorded a non-significant 

difference in the vegetation relative abundance 

of some plant species between oil pads and 

control areas which include Creeping wood-

sorrel (Oxalis corniculata), Finger grass 

(Digitaria eriantha), Garden Pink-sorrel (Oxalis 

latifolia), Star Grass (Cynodon dactylon), 

Fibrous drop seed (Sporobolus stafianus), 

Whitethorn acacia tree (Vachellia constricta), 

Baboon apple (Annona glabra), Borassus palm 

tree (Palmyra palm), Goats weed (Ageratum 

conyzoides), Nandi grass (Cetera ancient), Wild 

canny lilly flower (Canna indical), Devil 

horsewhip (Achyranthes aspera), Edible canna 

(Canna eduls), Guatemala (Tripsacum laxum), 

Pickerel weed (Pontederia cantata), Sticking 

weed (Acacia okidetalia), Tick berry (Lantana 

camara), Treedax daisy (Tridax procumbens), 

Wait a bit thorn (Acacia mellifera), and 

Whistling acacia (Acacia hoki). 

Observed plant species per transect 

A total of 16 various grass plant species, 4 shrub 

plant species and 3 tree species were recorded in 

oil pads whilst a total number of 17 grasses, 4 

shrubs, and 3 trees were recorded in control 

areas. Some of the observed plant species were 

recorded in both oil pads and control areas, 

while others were in either of the two sites 

(Table 3). However, the total number of plant 

species recorded in oil pads were not 

significantly different from the ones recorded in 

control areas (2= 8.29, d.f=1, p > 0.05). 

Vegetation diversity per transect  

The results of Shannon Weiner vegetation index 

per transect at both oil pads and control areas 

are presented in table 4. The results show a 

relatively higher mean vegetation diversity per 

transect at oil pads (1.9±0.058) compared to at 

control areas (1.71±0.120). The study results 

show a non-significant difference in the 

vegetation diversity between the former oil pads 

and control areas (t= 2.114, d.f =7, p=0.072). 

This indicates that there are no habitat variations 

post oil and gas exploration. The results indicate 

a non-significant difference between the 

vegetation species equitability between oil pads 

and control areas (t = 2.118, d.f=7, p =0.072). 

The mean equitability of vegetation per transect 

in oil pads and control areas is 0.80±0.014 and 

0.75±0.029, respectively 

 

Table 4: Vegetation diversity at oil pads and control areas 

OPT  H value H max E value CAT H value H max E value 

Jobi4 ET 2.05 2.48 0.83 CA1 ET 1.83 2.20 0.83 

Jobi4 ST 2.16 2.56 0.84 CA1 ST 2.47 2.71 0.91 

Jobi4 WT 1.89 2.40 0.79 CA1 WT 1.42 1.95 0.73 

Jobi4 NT 1.78 2.20 0.81 CA1 NT 1.38 2.08 0.66 

JE7 ST 1.61 2.20 0.73 CA2 ST 1.63 2.30 0.71 

JE7 WT 1.93 2.40 0.81 CA2 WT 1.63 2.20 0.74 

JE7 NT 1.91 2.48 0.77 CA2 NT 1.60 2.40 0.67 

JE7 ET 1.86 2.20 0.85 CA2 ET 1.72 2.20 0.78 
OPT=Oil Pad Transect, CAT=Control Area Transect, JE7 = Jobi East 7, H value- Shannon Weiner vegetation index, H max= Maximum 

species’, E value= Species’ equitability. ET=East transect, ST= South transect, WT= West transect, NT= North transect, CA1= Control 

area 1, CA2= Control area 2,Total number of quadrats per transect= 8, Total number of transects in oil pads = 16, Total number of 

transects in control areas = 16 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

54 

 

DISCUSSION 

Frequency Index (FI) of vegetation 

Results from the vegetation frequency index 

were analyzed by Raunkiaer's law of frequency 

(1962) recorded the uniformity or non-

uniformity of plant species in the study area. 

Uniform vegetation signified stable community 

whilst non-uniformity may suggest a disturbed 

vegetation community. The study recorded a 

number of plant species which were more 

uniform in control areas than in oil pads. This 

may suggest that these plant species are more 

abundant in control areas than oil pads. 

However, it should be noted that distribution of 

frequencies "depends on the number of 

quadrats, the size of the quadrats, and on the 

Index of Diversity of the population." Unless all 

of these factors are considered, the distribution 

of frequencies in classes is not meaningful 

(Williams, 1950). Another challenge with this 

methodology of vegetation assessment is that 

the dissemination of species in the frequency 

classes differs with the size of sample. The 

results are highly influenced by the composition 

of the total population in terms of numbers of 

individuals per species.  

Vegetation Relative Abundance  

The study recorded a non-significant difference 

in the vegetation relative abundance between oil 

pads and control areas. The findings are not in 

line with Lee et al. (2013) who suggested that 

species richness and total vegetation cover 

(Fiori and Zalba, 2003) may decrease in 

response to road construction and natural 

resource extraction. The results reveal that the 

plant communities have been able to recover 

from the human disturbances caused by oil 

exploration. This is not in line with the report by 

Forbes et al. (2001), which suggested that there 

is a general slow recovery of plant communities 

from human disturbances, and other physical 

impacts of development for decades or 

centuries.  

Some of the recorded plant species were more 

abundant in control areas than former oil pads. 

The findings are similar to those of Simmers 

and Galatowitsch (2010) which suggest that, in 

semi-arid environments, habitats heavily 

disturbed by anthropogenic activities often have 

lower species richness compared with 

undisturbed areas. However, the timeline for 

recovery may vary by taxa and level of 

disturbance (Nichols and Nichols, 2003; Walker 

and Moral 2003). This could be an explanation 

why some plant species were abundant in oil 

pads than control areas. Encounters of more 

abundant plant species in former oil pads is 

contrary to the findings by Prinsloo et al. (2011) 

which suggested that oil and gas development 

leads to decrease in vegetation cover. The study 

recorded some plant species which were more 

abundant in former oil pads than control areas 

and this is similar to Larson et al. (2001), whose 

findings indicate that reclaimed sites tend to 

have a higher abundance of species. This is 

because reclamation introduces new plants and 

offers moist and humid soil‐water which are 

better conditions than reference sites. This 

causes the reclaimed oil pads to have greater 

richness and higher abundance of the introduced 

plants. 

Vegetation diversity 

The study recorded a non-significant difference 

in the vegetation diversity between oil pads and 

control areas. This is similar to Lupardus et al. 



East Afr. J. Biophys. Comput. Sci. (2022), Vol. 3, No. 1, 43-57 
 

55 

 

(2020) whose findings did not detect significant 

differences in species richness of recovering 

grasslands between reference and reclaimed 

well pads. However, the current study findings 

of no significant difference were contrary to 

findings by Edwards et al. (2014) which noted 

that mining infrastructure fragments and 

degrades natural habitat through the creation of 

roads. Another study conducted by Cui et al. 

(2009) and Janz et al. (2019) found out that 

disturbances can have immediate and persistent 

or long‐lasting effects with slow recovery times 

on vegetation. The results are also contrary to 

UNEP (1997), Epstein and Selber (2002), 

Kumpula et al. (2011),  OGP/IPIECA (2011) 

and Kamara et al. (2019) whose findings 

indicated that natural resource extraction of oil 

and gas exploration had well documented 

impacts on wildlife as well as vegetation. The 

fact that the vegetation diversity in oil pads is 

similar to that in control areas is a good 

indicator that the habitats for mammals has been 

fully restored.  

CONCLUSIONS 

In general, the results of the current study 

revealed that the vegetation at the former oil 

pads has been fully restored. The oil exploration 

has not generally changed vegetation in the 

protected area. The oil pads are recovering at a 

steady rate given there is no observable 

difference of the vegetation relative abundance 

and diversity between oil pads and control areas. 

Based on these findings, oil companies should 

always do baseline studies before any 

development activities are carried out. The 

findings can serve as a benchmark for 

restoration once oil activities are complete. 

Moreover, further research studies are 

recommended in the former oil pads about 

edaphic assessments, soil chemical, and 

biological properties analysis. The studies 

would provide information to better understand 

if exploration altered the quality of soil in any 

way and also provide better guidance for further 

development phases of oil and gas in the park. 

Acknowledgements 

The authors are grateful to Uganda Wildlife 

Authority (UWA) for giving us access to 

Murchison Falls National Park to conduct this 

study. We also extend our appreciation to the 

UWA staff in the park who made our work 

easier by giving us all the necessary assistance 

needed. We wish to acknowledge the great 

support of Dr. Sylivia Nalubwama and Mr. 

Kitimbo Herbert for the valuable guidance, 

technical support, generosity and direct 

collaboration during this study. 

Author Contributions 

HA, CKT and WT conceived and designed the 

study; HA and KT conducted the research; HA 

and WT analyzed the data; HA and CKT wrote 

the paper. All the authors (HA, CKT, WT and 

KT) reviewed and approved the paper for 

submission. 

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