Nisa Karimi, Ph.D.
Assistant Scientist
Africa and Madagascar Department
Research Interests
• Flora of continental Africa and Madagascar
• Mechanisms of plant diversification
• Pollination ecology and plant-pollinator interactions
Applying Pollination Syndromes to Malagasy Flora. Karimi is an Assistant Scientist in the Africa and Madagascar department, her research explores mechanisms of species diversification in the flora of Africa and Madagascar. Highly resilient ecosystems are dependent on a complex web of life and individual species’ long-term survival is dependent on an ecosystem's integrity. Pollination networks, or plant-pollinator mutualistic interactions, are an essential building block that shapes ecosystem communities. While the value of documenting these networks is known, there is very limited data on these interactions, particularly in regions of the world that are experiencing some of the greatest biodiversity losses, such as Madagascar. The best approach to documenting pollination networks is via direct observational studies (personal observations, camera trapping), although this can be quite challenging. As an alternative means to document preliminary pollination networks within a given plant community, it might be possible to assign species’ pollination syndromes. Pollination syndromes are a suite of floral traits (i.e. shape, size, color, scent) that have co-evolved across distantly related lineages due to the same selective pressures of specific pollinators. For example, bat pollinated species have flowers that are often white, “musky” in scent, open at night, and have large reproductive parts. For this project, we propose using herbarium specimens and existing scientific literature to assign classic pollination syndromes to numerous species, all co-occurring at a single site in Madagascar, to construct initial pollination networks. The student involved in this project will extract herbarium records from the Tropicos MBG’s database (https://www.tropicos.org/home) for a specific site of interest in Madagascar and filter records based on the presence of reproductive parts (i.e., flowers). The student will collect information from the specimens on flower size, color, and shape. For each species, literature reviews will also be conducted to confirm or add to the data collected from the specimens and gather any known pollination information. Finally, statistical analyses will be conducted in R to visualize species’ clustering in morphological space based on similar traits and to help classify species without pollination information to putative pollinators. It is possible for the student participating in this project to receive co-authorship on a publication resulting from this work.