The following is a description of the approach to sampling design and data collection for the themes covered to the baseline report.
Sampling design and data collection in wetlands was planned to cover the indicators that were identified, namely; vegetation cover, acreage, plant species richness and composition. The methodology has been discussed according to key indicators.
Vegetation cover and Acreage
To determine changes in wetland acreage and vegetation cover, remote sensing techniques were used. This involved satellite image acquisition, processing and production of maps which were analyzed to ascertain changes in wetland acreage and vegetation cover. Land cover maps were produced showing satellite image details of 2010 on the ground to level of 50 meters. These provided details of what was to be verified by the field team on ground and showed cover types which included forests, farmlands, wetlands, grasslands, open water and built up areas in the Albertine Graben.
Ground truthing was undertaken to verify the maps generated from the satellite imagery. The information was recorded using data sheets. Hotspots for future monitoring were identified based on sensitivity of the wetland system, critical values/ecosystem services and threats to the systems. GPS coordinates of areas visited were registered and any changes noted on the ground were described.
Catch Assessment Surveys (CAS) were conducted to generate information on fish landed per fishing unit (vessel, gear and crew).
CAS landing sites were selected using a two-stage stratified sampling design according to the Standard Operating Procedures (SOPs) for CAS adopted by the Lake Victoria Fisheries Organization (LVFO, 2005). Within each district, a sample of primary sampling units (PSUs), that is, the fish landing sites were first selected from the sampling frame. At each PSU, stratified samples of Secondary Sampling Units (SSUs) – the Vessel and gear type, were randomly selected for fish catch sampling. Eighteen (18) landing sites representing 23% of all the 78 landing sites on Lake Albertand 26 representing 21% of the 126 fish landing sites on Albert Nile were sampled (Appendix 2). Standard CAS data forms (Appendix 3) were used to record fish catch data.
Fourty-three (43) CAS sampling landing sites were selected from a sampling frame of 204 landing sites recorded during frame survey of 2012 on Lake Albert and Albert Nile (NaFiRRI, 2012). In each of the landing sites in the riparian districts visited, fish catch data was recorded by species, vessel and gear type at each of the landing sites. The sample area constituted of Lake Albert and the 220 km stretch of Albert Nile to the Uganda – South Sudan border.
Data on large mammals was collected by Uganda Wildlife Authority (UWA) in partnership with Wildlife Conservation Society (WCS). Aerial surveys, ground counts and Randomised Block Design (RBD) were used. Aerial surveys involved systematic reconnaissance flights along transects at 2.5 x 2.5km. During these flights, the spatial location and all observable mammals are recorded. The generated data was analysed to produce distribution maps. Since many parts of the park had dense vegetation, it was hard to accurately account for all the mammals that occur in the area. Additional surveys were, therefore, carried out using camera traps in Murchison Falls National Park (MFNP), Kabwoya Wildlife Reserve (KWR), and Bugungu Wildlife Reserve (BWR) in 2014/2015 to beef up animal counts with particular interest to capture rarely observed species.
It is not always easy to survey small mammals due to their size and elusiveness. Methods, therefore, varied with the type of small mammals being surveyed.
Shrews and Rodents
The Sherman traps were used to capture rodents and shrews, using a bait that comprised of a mixture of peanut butter, maize flour, margarine and bananas. The trapping protocol used traps laid along line transects that maximized the habitat variation in each survey area. To enhance the chances of capturing animals, traps were specifically placed at locations with feeding signs, runways and against or beneath logs and areas with a good amount of low vegetation cover. All trap locations were marked with flagging tape and a GPS coordinate were also recorded.
Bats were sampled using mist nets, searching for roosts, and using an acoustic bat detector that can record micro-chiropteran activity. Sampling of bats was constrained by the location of sampling sites and the safety of the field team at night. As a result not every site sampled for shrews and rodents was sampled for bats as well.
Birds were sampled using point counts at 250 m intervals along each transect visited and the habitat of each point was noted. Additional points were placed in rare habitats in the vicinity of the sample site. The latter would include feeding sites for migratory waders and small wetlands.
Amphibian and reptile surveys
Reptiles and amphibians were surveyed in each of the main habitat types of the park. Visual Encounter Surveys (VES) were used to document the presence of amphibians and reptiles. A sample was taken from an individual animal of each species encountered.
- VES was carried out within 100m2 quadrats of homogenous habitat. Each quadrat was surveyed for 30 minutes. Quadrats were selected to include large old trees with consistent leaf litter around the roots.
- Opportunistic VES was used to detect the presence of diurnal amphibians and reptiles. A 30 minutes’ walk was conducted during day and night within a uniform area of habitat and any amphibian or reptile encountered was recorded.
Plant plots were measured at 250m intervals along the transect. Standard nested circular plots were used at all sites in the Albertine Rift (AR). Small herbs were recorded in a circle of 2m radius; trees from 2.5-10cm DBH (Diameter at Breast Height), lianas (>1cm diameter) and shrubs are recorded in 10m radius plots; and trees > 10cm DBH are recorded in 20m radius plots. A representative sample was taken of every species identified in the field so that checks could be made on species identification later. The GPS coordinates, the slope and canopy cover measurements were recorded at every plot and habitat using a standard form (Appendix).
Fertile plant specimens (flower/fruit), where possible, or otherwise non-fertile specimens of all plant species detected were collected. The specimens were pressed and dried using portable plant driers developed by WCS for field surveys and later identified at Makerere University Herbarium. In addition, for each specimen a GPS reading and field notes on habitat and characteristics were recorded.
Information was recorded using remote sensing, analysing current and past satellite imagery in particular Landsat. The processes were carried out as described in the following sections:
Acquisition and preparation of satellite imagery
(R) and verified using Google Earth. Ground truthing was undertaken as well.
Classification and Legend development
The National Biomass Study (NBS) 2014 classification which consists of 13 major land cover classes (Table 2) with substrata for each class was used. The substrata indicate the woody biomass and bush content of the class. It also has a sub-type for soil water (Table 3).
Table 2 General Translation between NBS and Land Cover Classification System (LCCS):
|NBS Code||NBS Classification||Description|
|1||Broad leaved plantations||Broad leaved trees|
|2||Coniferous plantation||Needle leaved trees|
|3||Tropical High Forest well stocked||Closed multi-storied high trees|
|4||Tropical high forest low stock||Open high trees|
|5||Woodland||Closed trees, Open trees, generally open trees, very open trees, woody areas|
|6||Bush||Closed, Open or very open shrubs|
|7||Grassland||Graminoids and herbaceous areas|
|8||Wetland||Permanently wet Graminoids and herbaceous Areas|
|9||Small scale farmland||Shrub and herbaceous crops on small fields|
|10||Commercial farmland||Shrub or herbaceous crops on Medium or large size fields|
|11||Built up area||Artificial surfaces- urban, airport, refugee camp|
|12||Open Water||Standing and flowing water, and water dams|
|13||Impediments||Bare soil and bare rocks, quarry, snow|
Table: Water Seasonality in NBS and LCCS :
|Soil water seasonality||NBS Code||LCCS Code|
Physical and Chemical Environment
Data collection covered stations and sites identified through a reconnaissance exercise. The reconnaissance generated issues through field visits to the oil and gas exploration areas in the Graben which informed the development of a basic water quality monitoring network. Sampling was undertaken at various points on lakes Albert, George and Edward and on rivers, and ground water sources mainly boreholes. In -situ measurements were taken, macro zoobenthos on rivers and water samples collected and delivered to Entebbe Reference Laboratory for further analysis. A total number of 52 water samples were collected for laboratory analysis for physio-chemical and heavy metal parameters.
Soil and plant samples were collected from Exploration Area 1, 2, 3 from the following areas; Tangi camp; JOBI 1, JOBI 3, JOBI 4, JOBI EAST 2, JOBI EAST 6, well locations that are all north of the Victoria Nile in Nwoya District. NGIRI 2, GUNYA and Nsoga well sites and Bugungu waste consolidation area in Buliisa District, and Bugomaand Nyamasiga Waste Treatment and Disposal site in Hoima District.
Sampling procedure – Soil
Soil samples were systematically collected from points along transects running in the direction of water flow and parallel to areas where drilling pads were located or parallel to waste consolidation areas. To assess the distribution of different elements down the soil profile the soil samples were collected from 0 – 30, and 30 – 60 cm intervals. The 0 – 30 cm horizon is used to determine the soil suitability for plant growth because most plant roots are found in it. The sampling points were geo-referenced for future monitoring.
Sampling procedure – Plants
Plant samples were systematically collected from selected points where soil samples are collected.
Soil samples were air-dried and ground to pass a 2 mm sieve and analyzed for pH, organic matter, total nitrogen (N), total and available phosphorus (P), extractable calcium (Ca), magnesium (Mg), sodium (Na), copper (Cu), zinc (Zn), iron (Fe) and manganese (Mn), and textural class [sand, clay and silt] at the Soils and Plant Tissue Analytical Laboratory at National Agricultural Research Laboratories (NARL) of the National Agricultural Research Organization (NARO) at Kawanda. The electro-conductivity is used to assess the soil salinity that is the availability of excess sodium in the soil. Analysis for extractable mercury (Hg), chromium and lead (Pb) were carried out at the Soils Laboratory, Faculty of Agriculture, Makerere University and the Government Chemist. Analysis was done using standard methods by Walkley and Black 1934, that is Soil pH (1:2.5 soil: water ratio), soil organic matter (SOM) and available Phosphorus and exchangeable Potassium measured in a single Mehlich-3 extract and buffered at pH 2.5 (Mehlich, 1984). Soil texture was determined by the hydrometer method by Bouyoucos, 1936.
Plant samples were dried in an oven at 70ºC, ground to pass a 0.5mm sieve and analyzed for total nitrogen (N), total phosphorus (P), extractable calcium (Ca), magnesium (Mg), copper (Cu), zinc (Zn), iron (Fe) and manganese (Mn) at the Soils and Plant Tissue Analytical Laboratory at National Agricultural Research Laboratories (NARL) of the National Agricultural Research Organization (NARO) at Kawanda.
Field observations were made for any sign of sheet, rill and gully erosion in the areas due to vegetation removal. Furthermore observations were also made on termite activities.
The data collection exercise was undertaken in collaboration with the District Environment Officers. The main focus was on the following departments in line with the VECs: Education, Health, Environment and Natural Resources, Production, Community Development, Commerce, Water, Works, Energy and Culture. Other sectors consulted were the private sector, local leaders, religious leaders, schools and community members.
Data was collected in different ways;
- Tailored questionnaires that were designed and distributed to targeted Heads of Department in the Local Governments and other officials for the available secondary data.
- Consultative interviews/Focus Group Discussions (FGDs) using tailored Interview Guides, targeting selected adults: responses and comments from the respondents were documented and analysed as additional information that could not be collected using the questionnaires.
- The Uganda National Household Survey (UBOS-UNHS 2012/2013) was used as a key
source of information whose data was analysed and compilation, providing aggregated data at the Albertine Graben level.
- Literature review of available secondary data.
- Observations: still photos were taken using cameras while others obtained to enhance records and data collected.
- Global Position System (GPS) equipment was used to map the respective locations and produce maps for the respective locations.
- Raw data obtained from the field was analysed to ensure consistence within the survey tools and methodology findings as well ensuring quality data. Statistics were generated using statistical packages and methods.
Business & Management
Monitoring was done using environmental indicators (Appendix). These were information
tools that informed and helped in understanding the status and threats on our natural resources.
Information was compiled through literature review, remote sensing and field data collection. Interviews were conducted with institutions and individuals knowledgeable about the subject matter including government agencies, civil society organizations, private sector and individualising the Albertine graben.
Data on fish production and commercial value of the fisheries of Lake Albert and Albert Nile system was collected during the Catch Assessment Survey (CAS) and covered 78 landing sites along the Lake Albert and Albert Nile. The information was collected by the National Fisheries Resources Research Institute (NAFIRRI) in collaboration with the Department of Fisheries Resources (DFR), Local Government staff (FOs) and BMU members at selected landing sites on Lake Albert (18 landing sites from Ntoroko, Kibale, Hoima, Buliisa, Nebbi districts) and Albert Nile (26 landing sites from Nebbi, Arua, Adjumani and Moyo districts) representing 23% of all the 78 landing sites on the Ugandan part of Lake Albert and 26 (21%) of the 126 fish landing sites on Albert Nile were sampled in November 2013 and July 2014. In each sampling, a total of 1280 and 768 boat days in 2013 and 2014 respectively were sampled on both Lake Albert and Albert Nile for a period of 10 days in each sampling, namely; Nebbi – 6,Buliisa-14, Hoima- 36, Kibaale -7 and Ntoroko- 7. The full list of landing sites can be found in Appendix.
A survey was done to establish baseline data on the number of fish caught per landing site. The survey stretched from Moyo and Adjumani Districts along the Albert Nile to the south of Lake Albert. The total fish catches were estimated using the mean fish catch rates and the May 2012 Frame survey data as a rising factor. For each effort group, the Boat activity coefficient i.e. the probability that a fishing craft of each craft-gear type would be active on any day during the month, was estimated as the mean number of days the boats in each effort group fished in the week preceding the sampling day divided by the number of days in a week. The total catch of each effort group was then estimated. The mean fish catch rates (kg boat-1 day-1) were estimated for each effort group by species.
Remote Sensing was used to locate sites where construction materials are extracted. They were mapped using satellite images and Google Earth and later validated by ground truthing. Remote sensing and GIS were used to determine location and extent of areas under agriculture as well as those under forests.
Data was collected on some of the tourism facilities that are found in the Albertine Graben. Data collected was on the protected area, where it is found, the company or firm, running the concession and the investor in the facility. More Data was also collected on the year in which it was established but also on the capacity of the facility. (The capacity is the number of persons the facility can comfortably accommodate).