@article{UYANAHEWAGE_Halwatura_Seneviratne_2022, title={Plant selection matrix for classifying elephant forage plants in Sri Lanka using metadata: A Cluster and Classification -and- Regression Tree Approach}, volume={4}, url={https://journal.slaas.lk/index.php/JSLAAS/article/view/7}, DOI={10.5281/zenodo.7498120}, abstractNote={<p>The elephant, the largest terrestrial herbivore in the world, requires a higher amount of plant material for survival. The degradation and shrinking of forests on the island resulted due to anthropogenic activities, drive to deplete the habitats and niches of elephants migrating towards new habitats and food sources. Identifying the preferences of plant species is imperative in enhancing habitat enrichment endeavours to mitigate Human-Elephant Conflict (HEC). There was a scarcity of in-depth knowledge available on the feeding behavior and dietary patterns of Asian elephants grazing on rangelands and secondary forests. The work carried out on the elephant forage, in general, indicated that most of the Sri Lankan elephants preferred grasses over the other plants, the preferences vary with the seasonal availability of forage plants during dry/wet seasons. The establishment of forages could be considered one of the remedial measures for wildlife conservation. The objective of the study was to develop a plant selection matrix using plants and ecological characters from metadata analyzed using Cluster analysis (CA) and, Classification and Regression Tree (CART). CA produced three clusters at 80% phenon level and characterized by plant height (p < 0.05), soil pH (p < 0.05) and habitat type (p < 0.05). CART recognized the type of lifecycle, soil type and method of pollination as decisive features.  Both cluster and classification and regression tree analyses identified the important character /character state that helped to group elephant forage. These characters were used to construct a forage plant section matrix for identifying proficient forge plants with minimum effort.</p>}, number={1}, journal={Journal of the Sri Lanka Association for the Advancement of Science}, author={UYANAHEWAGE, DILINI and Halwatura, Rangika Umesh and Seneviratne, Somaratne}, year={2022}, month={Dec.}, pages={22–39} }