Assessment of resource partitioning in pollinators at a particular place can be used to conserve plant communities by minimizing their inter-specific competition. Current study was conducted to investigate the occurrence of this phenomenon among plant communities under sub-tropical conditions for the first time in Pakistan. We considered the entire available flowering plant and floral visitor communities in the study area-Lal Suhanra forest of Bahawalpur, Pakistan- along with different variations among them based on morphology, color and symmetry (functional groups) i.e. four functional groups among insects and nine among plants. Weekly floral visitor censuses were conducted during spring season -from the first week of March to the fourth week of May 2018. Thirty individuals of each plant species -in bloom- were observed for floral visitors in each census. Plant species with different floral shapes, colors and symmetry did not show any significant resource partitioning. The Non-metric multidimensional scaling analysis followed by one-way ANOSIM test showed non- significant differences among all the pair of floral shapes, colors (except white and yellow) and symmetry (R-value < 0.168). However, SIMPER test suggested that flies were the most common group that contributed more towards within group similarities of different floral shapes (19 to 21% similarity), colors (16 to 30%) and symmetry (19%) followed by long-tongue bees i.e. 14 to 21%, 9 to 19% and 18%, respectively. Our results suggest that plant communities under sub-tropical conditions of Pakistan exhibit a generalist pollination system with no significant resource partitioning in pollinator species. Therefore, plant communities may have high competition for pollinator species which exhibits fewer implications of species loss on overall pollination process. Our study provides the basis for understanding the partitioning of pollinator guilds under sub-tropical conditions. Future studies should focus on functional traits in more detail at the community and the population scales for their possible impact on resource partitioning.