CHAPTER 3: DISTRIBUTION, HABITAT USE, AND ABUNDANCE OF
3.3 Methodology
The study was conducted in Waterberg National Park which is situated in the Otjozonjupa Region in northern Namibia, 280 km north of Windhoek and 68 km south east of
Otjiwarongo (20°25'S, 17°13'E; Figure 3.1).
44
Figure 3.1. Waterberg National Park and the different vegetation types for in the park.
Source: (Jankowitz1983).
The WPN is 49 km long from south west to north east, and 8-16 km wide. It is 40,500 ha in size, with 40,000 ha on the plateau and 500 ha in the foot hills. The plateau arises from 1550 to 1850 m above sea level and between 100 to 300 m above the surrounding plain. The periphery of the plateau forms almost vertical cliffs, up to 300m high. The top of the plateau is made up of aeolianite (lithified dunes) of the Etjo Formation, which is ca. 200 million years old. The sandstone is covered with Kalahari sand (Hegenberger, 1990). There are no permanent water courses or pans. The water is pumped from the canal which runs across north central parts of the country from the Berg Aukas and Kombat mines where it is than diverted to the seven waterpoints in WNP (Figure 3.1), and is available throughout the year.
The vegetation falls into the broad-leaf woodlands which are typical of the sandveld of eastern and north-eastern parts of Namibia (Mendelsohn et al. 2009). Three main vegetation communities within this park have been recognized, with a fourth one occurring on rocky substrates: Terminalia sericea-Melhania acuminate covering 42% of the park, Terminalia sericea-Blepharis integrifolia covering 16% of the park, Terminalia sericea-Thesium megalocarpum covering 11% of the park, and the rock community Peltophorum africanum
45
which covers 27% of the park (Jankowitz,1983). Over 500 flowering plants and 140 lichen species were recorded in the Waterberg N. P. Common trees include Acacia ataxacantha, Burkea africana, Combretum collinum, C. psidioides, Dichrostachys cinerea, Grewia flavescens and G.retinervis, Philenoptera nelsii, Ochna pulchra, Peltophorum africanum, Terminalia sericea and Ziziphus mucronata. Common grass species are Andropogon schirensis, Brachiaria nigropedata, Digitaria seriata, Eragrostis jeffreysii, E. pallens, E rigidior and Panicum kalaharense (Jankowitz&Venter1987; Mendelsohnet al. 2009).
The plateau is divided into 6 burning blocks, each of which is burnt every 6-8 years The Waterberg Plateau Park falls into the ‘Hot Steppe’ climatic zone. The mean temperature is above 18°C. More than 90% of the rainfall occurs from October-March. Average annual rainfall at Onjoka (below the plateau) is 450.2 ±75.4 mm (Mendelsohn et al. 2009). The total rainfall for Waterberg N. P. in the year 2015 was 142.7mm, of which less than half of that occurred in the months January to March with no rain in April, whereas in the year 2016 Waterberg National Park received a total of 404.4mm in rainfall, of which most of the years rain occurred in the months January, February, March and April (Figure 3.2).
Figure 3.2. Rainfall of Waterberg N. P. for the years 2015 and 2016. Total rainfall for 2015 was 142.7mm and 404.4m in 2016. Source:
(Sasscalweathernet.org/station_datasheet_we.php).
0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0
0.0 5.0 10.0 15.0 20.0 25.0 30.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
(mm)
(℃)
Month
Rainfall (2015) Rainfall (2016)
Average Temperature (2015) Average Temperature (2016)
46 3.3.2 Data Collection
Data were collected using road counts during three months of Namibia’s wet season starting in February to April of both 2015 and 2016, whereas the data for dry season were collected during the months of June to August for both years. A Toyota truck was used to drive along the transects, at a speed between 15-20km/hour. The sampling was started every day at 06:00am, with the odometer set to 0 at the starting point. Animals where observed from the vehicle by two individuals using binoculars. Observed animals were recorded using Global Positioning System (GPS) to plot the coordinates of the observation spot, and distance was estimated between 0 and 100m using a Nikon ACULON laser range finder for accuracy of identifying the sexes of the observed animals (0 if the observation was on the road). Coordinates of the seven (7) waterpoints were collected in order to determine animal vegetation preferences and estimate the distance between each point of observation and the nearest waterpoint. The total distance of transect covered per day varied between 50 and 70km. We avoided recounting of the animals by not returning along the same transects. Data of rhino occurrence are omitted from this study, merely because of the current poaching threats in Namibia.
3.3.3 Processing of GIS data
ArcGIS 10.x software was used to process the coordinates of the observed animals. A total of 52 attribute fields were added to the existing attributes for species observed in 2015 and 2016 representing wet and dry seasons respectively. Data were then populated/entered for each point of observation. Different symbols were used to represent the wet and dry season on the map, the observed points were then labelled according to the total number of species observed. The vegetation was categorized based on each vegetation type and displayed using a unique color ramp representing the different vegetation types. A transparency of 50% was applied on each vegetation color, in order to aid visualization of other overlaid data.
3.3.4 Statistical analyses
Data on habitat preference and habitat were not normally distributed but met the assumptions of Chi-square test for association using IBM SPSS version 20. Non-parametric Chi-square tests of association were, therefore, performed to determine if a particular animal species is associated with certain habitat or not (symbolizing usage or preference) and in which season (dry or wet) across the years 2015 and 2016. Secondly, one-way analyses of variance (ANOVAs) followed by post-hoc using Duncan’s multiple range test at 5 % significant level
47
tests were conducted to ascertain if the average distances to the water point differ among different species, seasons, years and season by species interactions, after testing for normality.
Lastly, animal densities for 2015–2016 were estimated using line distance methodology, implemented in the software Distance 7.2 (Kiffner et al. 2017). The model fitted five different detection functions to the data (Thomas et al. 2010; Kiffner et al. 2017). The conventional detection models (all with cosine expansion) describe detectability as a function of perpendicular distance: uniform, half-normal, negative exponential, and hazard rate. Half- normal key, k(y) = Exp(-y**2/(2*A(1)**2)), where k is number of sample and A is the i-th parameter in the estimated probability function Based on the Akaike’s information criterion (AIC) score of each model and the visual fit of the detection function near the transect line and goodness-of-fit statistics, we selected the best-fitting detection model for species and used this model to estimate and species densities (Kiffner et al. 2017).