Natural and Agricultural Sciences

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Browsing Natural and Agricultural Sciences by Advisor "Adelabu, Samuel"

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    Grass nutrients estimation as an indicator of rangeland quality using satellite remote sensing
    (University of the Free State, 2022) Mashiane, Katlego Kgabo; Adelabu, Samuel; Ramoelo, Abel
    South Africa's grasslands are known for their rich biodiversity, which makes for rangelands with expansive landscapes for grazing. Numerous studies have been conducted on how species variety and composition affect the sustainability and productivity of grasslands. The provision of ecosystem functions and services, mainly grazing for both domestic livestock and wild animals, is threatened by rapid biodiversity loss. Hence crucial to develop monitoring systems for biodiversity, especially considering the anticipated impacts of global environmental changes. Nutritionally sufficient grass swards strongly influence the distribution and abundance of grazing animals. Although estimates of crucial ecological and biodiversity indicators can be obtained from in situ and remote sensing data, remote sensing offers timely and cost-effective data that can be used for species monitoring. This study sought to measure essential biodiversity variables in GGHNP related to plant productivity and nutrient availability using in situ and remote sensing approaches. In addition, by estimating grass species nitrogen using remote sensing, the research intended to improve carrying capacity models and stocking rate in the park, thus ensuring efficient rangeland management. Assessments of species diversity and richness are pivotal for devising effective conservation strategies. These biodiversity metrics are good indicators of rangeland quality, health, and ecological response to disturbances. Data collected using in situ methods showed that species richness are virtually similar across the park under different richness of disturbance regime. However, species richness were higher at landscape richness than at the site richness. Albeit criticised for their use in conservation, species diversity metrics could be useful for measurements of rangeland quality. Due to its intolerance to harsh environmental circumstances, mountainous grassland vegetation is probably the most susceptible to environmental changes on a worldwide scale. Understanding the factors that influence species distribution in alpine grasslands will be crucial for identifying biodiversity and preserving it. This evident in that an increase in topo-edaphic variables negatively affects species richness, while slope and elevation showed an improvement of species richness. The influence of topography and other accompanying factors on species diversity is highlighted, emphasizing how topography affects species dispersion in mountainous grassland communities. Understanding the value of environmental conditions are to the geographical distribution of biodiversity has been the focus of the most active ecological research. The selection of appropriate modelling algorithms could be beneficial for gaining insights into biodiversity-environment relations. Non-parametric and parametric modelling frameworks were used to assess these relationships. Topographically controlled edaphic variables continued to be the most significant drivers of species richness and diversity in grassland plant communities in the park, despite higher prediction accuracies being attained using parametric models. Remote sensing permits rapid and inexpensive recording and assessment of vegetation over short to long-term periods at a local and global scales. This study sought to predict and model species richness and diversity in GGHNP. Near-infrared (NIR) was the most selected spectral interval for predicting species diversity, further ascertaining the efficiency of NIR in vegetation mapping. Grass species N (grass N) estimation is valueable for rangeland management because it determines their forage quality which has nutritional implications for grazing animals. I used remote sensing data to predict grass N in the park using Sentinel 2 Multi-Spectral Instrument (S2 MSI). The results showed red edge bands as the optimal bands for estimating grass N, which makes S2 MSI superior for modelling grass N throughout grass phenology and among seasons because of its multiple red edge bands. Grassland monitoring is imperative for both assessing global change impacts and the security of sustainable development goals. Grasslands serve as rangelands that supply forage for domestic and wild animals. Monitoring of forage quality and quantity is crucial for evaluating carrying capacity models and thus ensuring effective rangeland management. Plant species richness and species diversity are key indicators for plant primary productivity in rangelands and many other ecosystem health parameters. Due to the immensity of rangeland landscapes, remote sensing could be the effective technology for determining and keeping track of ecological parameters in grasslands.
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    Relationship among functional traits of wetland plants and climatic variables along an aridity gradient across the Highveld, South Africa
    (University of the Free State (Qwaqwa Campus), 2017-01) Mofutsanyana, Seadi Sefora; Sieben, Erwin; Adelabu, Samuel
    Wetlands are among the most threatened ecosystems in South Africa due to human activities such as changing land use. In addition to these threats, wetlands are now faced with the threat of climate change, which may affect their biota in the future. Therefore, South Africa needs locally relevant biological indicators to detect changes in wetland ecosystems that can be used in monitoring programmes for wetland vegetation. Plant functional traits are recognised as an effective tool that can be used to understand community assembly processes that determine the abundance and distribution of plant species and their response to climate change. The aim of the study was to determine whether plant functional traits change along an aridity gradient across the Highveld of South Africa. Functional traits of the dominant plant species were collected in the wetlands of the Highveld along a climatic gradient from dry in the west to mesic in the east. The measured traits include plant weight, rhizome internode length, shoot length, leaf nitrogen content (Leaf N) and specific leaf area (SLA). In the analysis canonical ordination techniques were applied to find the correlation between plant functional composition, non-climatic environmental variables and climatic variables. Community-averaged traits were calculated for all wetland vegetation plots and these were plotted against non-climatic environmental variables and climatic variables using the CANOCO program. Hierarchical Cluster Analysis (HCA) was carried out to delineate plant functional groups using the PC-Ord program. Plant functional groups were plotted against non-climatic environmental variables and climatic variables using CANOCO program. The distribution ranges of each plant functional group were mapped using Geographical Information System (ArcGIS). Principal Component Analysis (PCA) was carried out using the PC-Ord program to find the relationship between non-climatic environmental variables and climatic variables. The RDA results showed that the correlations between climatic variables and plant traits in general are not as strong as expected; plants seem to respond much more strongly to non-climatic environmental variables. This means that plants seem to respond much more directly to local factors that determine the wetland habitat and not directly to the climate itself. Nonetheless, it is still possible that these environmental conditions (wetness, inundation, nutrient content of the soil) may change as well in the scenario of climate change, but that would be considered as an indirect effect. The results revealed that plant weight and rhizome internode length are correlated with maximum temperature and evaporation. Species with high plant weight and long rhizome internode length represents species growing in dry areas on the western side of the study area. SLA, shoot length and leaf N are correlated with precipitation and minimum temperature. Species with high SLA, long shoot length and high leaf N are specifically those species growing in mesic areas on the eastern side of the study area. Wetland plant species in dry areas grow in wetlands that are exposed to high temperatures, high evaporation rates, low rainfall and high salinity. These species are short and have low SLA which they use as an adaptation to water stress. Wetland plant species in mesic areas grow in wetlands that are exposed to high rainfall and low temperatures. These species grow faster and are more productive. The functional classification resulted with six plant functional groups namely: tufted graminoids, leafless graminoids, rhizomatous graminoids, salt tolerant forbs, succulent shrubs and short trailing forbs and grasses. The tufted graminoids, leafless graminoids and rhizomatous graminoids are distributed in mesic areas and the succulent shrubs, salt tolerant forbs and short trailing forbs and grasses are distributed in dry areas. Changes in community composition will show how the wetland is responding to climatic variability and environmental change. This will provide an improved basis for monitoring the impacts of climate change on wetland vegetation.
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    Understanding the spatial distribution and factors responsible for cloven hooved foot and mouth disease spread in Umkhanyakude district, South Africa
    (University of the Free State, 2017-12) Dlamini, Khethiwe; Adelabu, Samuel; Mahasa, Pululu
    Recent global reports show a continual vulnerability of large livestock populations to transboundary diseases such as cloven hooved foot and mouth disease (FMD) in relation to our environments. Of a particular concern is the spatial distribution of disease occurrences and its association with risk factors. Domesticated animals such as cattle are at risk of contracting the highly contagious FMDV that manifests with different distribution of serotypes across the world. FMD serotypes i.e. South African territory (SAT 1, SAT2, SAT3) are restricted to South African countries. Despite the several reports of FMD in Umkhanyakude district, few reports have utilized GIS (Geographical information system) technology for mapping the environmental factors and the disease concerned. In Umkhanyakude, Jozini and Umhlabuyalingana shoulder the highest FMD burden. In the present study, GIS was used to map FMD occurrences and to identify geographic areas with on-going FMD occurrences for the study period (2011-2015). MCDA was carried out to determine factors with the major influence on the spread of FMD. Weights were then assigned into percentage from Oto 100% using an evaluation scale of 1 to 5, with 5 being extremely important, and 1 being of equal importance. Correlation analysis was carried out to determine the relationship between spatial occurrence of FMD and factors such as distance, herd size, rainfall, wind and temperature, correlation coefficient ranges from 1 to -1. Results revealed that there is a spatial relationship between FMD occurrences and factors concerned, areas with high vulnerability towards the spread of the disease were identified. Spatial distribution of the environmental factors, and vulnerability maps were derived to characterise the spatial pattern of FMD.