Faculty of AgriSciences

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https://scholar.sun.ac.za/handle/10019.1/9

The Faculty of AgriSciences at Stellenbosch University (SU) is held in high esteem at national and international levels for the quality of its training and research and also as consultant in the agricultural and forestry industry.

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Browsing Faculty of AgriSciences by browse.metadata.advisor "Abdel-Rahman, Elfatih"

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    Landscape characteristics and honeybee colony integrity: A case study of Mwingi, eastern Kenya
    (Stellenbosch : Stellenbosch University, 2020-12) Ochungo, Pamela Aor; Veldtman, Ruan; Abdel-Rahman, Elfatih; Landmann, Tobias; Muli, Eliud; Stellenbosch University. Faculty of AgriSciences. Dept. of Conservation Ecology and Entomology.
    ENGLISH ABSTRACT: Honeybees (Apis mellifera) are highly efficient crop pollinators, providing valuable ecosystem services through pollination in diverse environments globally. However, honeybee populations are in decline and habitat loss and fragmentation, pests and parasites and nutritional deficiencies are emerging as some of the most important factors contributing to this decline, consequently threatening food security and rural communities’ livelihoods. Therefore, monitoring the interconnected effects of landscape fragmentation, pollen diversity, honeybee pests’ and honeybees’ colony strength is a fundamental component of their conservation as well as safeguarding continued ecosystem services. In Kenya, where the study is carried , there have been no investigations specifically addressing these linkages mainly because until recently, there has been unavailability of freely available moderate to high resolution landscape fragmentation maps. As such, the overall goal of this study was to quantify landscape fragmentation, and to investigate its effect on honeybee colony strength, pollen diversity and protein content and Varroa destructor mite occurrence in a semi-arid region located in the eastern part of Kenya. Using Sentinel-1A SAR and Sentinel-2A optical remote sensing systems, the first part of this study examined the use of a random forest machine learning algorithm to map fine-scaled and under-represented landscape elements representing honeybee habitats in six study sites (apiaries) specifically selected based on varying landscape degradation levels. The results indicated that the fused SAR and optical imagery had the highest overall accuracy for mapping the spatially explicit honeybee habitats and thereafter, fragmentation metrics relating to landscape composition and configuration were derived from this fused combination, within a 3 km buffer radius of each apiary. Landscape fragmentation metrics derived from the fused SAR and optical imageries were thereafter linked with honeybee colony strength parameters. Results of zero inflated negative binomial regression with mixed effects indicated that lower complexity of patch geometries represented by Fractal Dimension and reduced proportions of croplands were most influential at local foraging scales (1 km) from the apiary, while higher proportions of woody vegetation and hedges resulted in higher colony strength at longer distances from the apiary (2.5 km). Moreover, honeybees in moderately degraded landscapes displayed the most consistently strong colonies throughout the study period. In the third part of the study, pollen diversity and protein content were examined across the six apiaries. Results showed that pollen diversity was highest in moderately degraded landscapes while protein content in pollen did not vary by location but varied by seasonality. In the final part of the study, Varroa destructor mite did not have any effect on honeybee colony strength parameters, except for eggs. However, lower complexity of patch shapes and greater landscape homogeneity represented by the Shannon diversity index were highly influential on Varroa destructor mite occurrence. The overall study shows that landscape fragmentation influences honeybee colony strength, pollen diversity and Varroa destructor mite occurrence. These results can be used to inform hive placement for maximal colony strength and hive productivity. However, the study was conducted in only six apiaries and recommendations regarding validation at larger numbers of replicates are made.