Medicinal plants are vital sources of easily accessible remedy used in the countryside healthcare system. This study aimed to find and make record of plants that are used for medicinal therapy by three communities living in Cherangani Hills. So far no single study has documented medicinal plants as a whole in the area. Ethnobotanical data were obtained through interviewing informants using semi-structured questionnaires and extracting information from journals and books. Descriptive statistical analysis was applied to describe the data. Overall 296 plant species from 80 families and 191 genera were identified. Asteraceae family was the most dominant, representing 10.7% of the total plant species recorded. Roots (35.9%) represented the most commonly used parts of the plant. The commonly used method of preparation was decoction (54.9%). The reported diseases were classified into 14 diverse ailment groups out of the 81 health conditions on their underlying user reports. Rural communities in Cherangani Hills are rich sources of plants with medicinal properties. Therapeutic uses of the compiled plants provide basic information that can aid scientists to conduct additional research dedicated to conservation of species and pharmacological studies of species with the greatest significance.

Globally, food and medicinal plants have been documented, but their use patterns are poorly understood. Useful plants are non-random subsets of flora, prioritizing certain taxa. This study evaluates orders and families prioritized for medicine and food in Kenya, using three statistical models: Regression, Binomial, and Bayesian approaches. An extensive literature search was conducted to gather information on indigenous flora, medicinal and food plants. Regression residuals, obtained using LlNEST linear regression function, were used to quantify if taxa had unexpectedly high number of useful species relative to the overall proportion in the flora. Bayesian analysis, performed using BETA.INV function, was used to obtain superior and inferior 95% probability credible intervals for the whole flora and for all taxa. To test for the significance of individual taxa departure from the expected number, binomial analysis using BINOMDIST function was performed to obtain p-values for all taxa. The three models identified 14 positive outlier medicinal orders, all with significant values (p < 0.05). Fabales had the highest (66.16) regression residuals, while Sapindales had the highest (1.1605) R-value. Thirty-eight positive outlier medicinal families were identified; 34 were significant outliers (p < 0.05). Rutaceae (1.6808) had the highest R-value, while Fabaceae had the highest regression residuals (63.2). Sixteen positive outlier food orders were recovered; 13 were significant outliers (p < 0.05). Gentianales (45.27) had the highest regression residuals, while Sapindales (2.3654) had the highest R-value. Forty-two positive outlier food families were recovered by the three models; 30 were significant outliers (p < 0.05). Anacardiaceae (5.163) had the highest R-value, while Fabaceae had the highest (28.72) regression residuals. This study presents important medicinal and food taxa in Kenya, and adds useful data for global comparisons.

Aeollanthus repens, native to East Africa, thrives in seasonally dry tropical biomes and boasts qualities ideal for both ornamental and ground cover purposes. However, despite its potential, its current resistance levels remain uncertain. Assessing its adaptability could offer valuable insights for its wider adoption and utilization. In this study, researchers employed 3-month-old cuttings of A. repens, subjecting them to six distinct environments by manipulating the temperature (25/20 °C and 35/30 °C) and soil moisture levels (100%, 20%, and 40%). Their leaf physiological and photosynthetic indices were assessed at intervals of 5, 10, and 15 days following exposure to stress. The findings unveiled that exposure to prolonged moisture, elevated temperatures, or a combination of both led to an increase in osmoregulatory substances in the leaves. This increase was accompanied by heightened enzyme activity and an increased intercellular carbon dioxide concentration, followed by a subsequent decline. Additionally, chlorophyll content, net photosynthetic rate, stomatal conductance, and transpiration rate exhibited a decreasing trend over time. Through a comprehensive assessment of stress tolerance utilizing a composite affiliation function value index, the study concluded that A. repens exhibits optimal growth in a certain high-temperature environments and demonstrates substantial resistance to waterlogging, drought, and simultaneous high-temperature stress. However, the resilience of A. repens appears to diminish under the compounded stresses of high temperature and drought.