4 research outputs found
Understanding climate change effects on the potential distribution of an important pollinator species, Ceratina moerenhouti (Apidae: Ceratinini), in the Eastern Afromontane biodiversity hotspot, Kenya
Monitoring key pollinator taxa such as the genus Ceratina requires precise near real-time predictions to facilitate
better surveillance. The potential habitat suitability of Ceratina moerenhouti was predicted in the Eastern Afromontane
biodiversity hotspot (EABH) in Kenya using presence-only data, to identify their potential distribution
and vulnerability due to climate change. Bioclimatic, edaphic, terrain, land surface temperature, and land use
and land cover (LULC) variables were used as predictors. Three machine learning techniques, together with their
ensemble model, were evaluated on their suitability to predict current and future (the shared socioeconomic
pathways (SSPs), i.e., SSP245 and SSP585) habitat suitability. Predictors were subjected to variable selection
using the variance inflation factor resulting in a few (n = 9) optimum variables. The area under the curve (AUC)
and true skill statistic (TSS) were used for the accuracy assessment of the modeling outputs. The results indicated
that 30% and 10% of the EABH in Murang’a and Taita Taveta counties are currently suitable for C. moerenhouti
occurrence, respectively. However, future projections show a ±5% decrease in C. moerenhouti habitats in the two
counties. Further, the ensemble model harnessed the algorithm differences while the random forest had the
highest individual predictive power (AUC = 0.97; TSS = 0.96). Clay content, LULC, and the slope were the most
relevant variables together with temperature and precipitation. Integrating multi-source data in predicting
suitable habitats improves model prediction capacity. This study can be used to support the maintenance of
flowering plant communities around agricultural areas to improve pollination services
Spatial modelling of invasive species distribution in water-limited environments using remotely sensed data and climatic scenarios in the Heuningnes catchment, South Africa
>Magister Scientiae - MScThe occurrence and spread of Invasive Alien Plants (IAPs) is a threat to global water resources and natural ecosystems due to high water use rates. With the current climate change projections and their ability to survive extreme environmental conditions, these species pose a huge threat to grazing resources, water availability and ecosystems in general. Routine monitoring and understanding their distribution and potential vulnerable areas is fundamental as it provides the requisite baseline information to guide clearing efforts and other related management and rehabilitation initiatives
Understanding Striga occurrence and risk under changing climatic conditions across different agroecological farming systems at local and regional scales122
Philosophiae Doctor - PhDThe invasion by Striga in most cereal crop fields in Africa has posed an acute threat to food security and socioeconomic integrity. Consequently, numerous technological and research developments have been made to minimize and even control the Striga impacts on crop production. So far, efforts to control Striga have primarily focused on the manipulation of the genetics of the host crops, as well as understanding the phenological and physiological traits, along with the chemical composition of the weed