Leaf Area Index (the one-sided area of leaves/area of ground) is an important variable for quantifying vegetation in ecology and climate modeling. A major focus of my research is to add this important variable to the field of paleoecology. With the ability to quantify vegetation structure in deep time, we can begin to address many outstanding questions in paleoecology.
My method for reconstructing LAI thus far has been to track epidermal cell morphology (cell area and degree of undulation) of non-grass phytoliths across an LAI gradient in Costa Rica (see this paper published in Science Magazine). This idea is based on the well known differences between sun leaves and shade leaves whereby shade leaves have larger and more undulated epidermal cells than leaves exposed to more sunlight (sun leaves). This pattern of leaf morphology was first described by German botanists in the late 1800’s and has been studied by many botanists ever since.
In forested environments (high LAI), there should be more shade leaves, hence larger and more undulated epidermal phytoliths in the soil than in open habitats (low LAI). To test this idea, my field assistant Melanie Conner and I collected >200 surface soil samples in a diversity of Costa Rican habitats including wet tropical forest, dry tropical forest, shrublands, and grasslands.
Undergraduate Aiden Loesser extracted phytoliths from the modern soils in the Strömberg Paleobotany and Paleoecology Lab and we photographed and measured them. When we compared the phytolith morphology data to our field based measurements of LAI from hemispherical photographs, we found that LAI is highly correlated with both cell size and cell shape and that LAI can be predicted based on these characters with confidence. This means that we now have a phytolith-based method for determining LAI in the fossil record using the same type of phytoliths which are commonly found in fossil samples. We call LAI values predicted from our statistical model “rLAI” meaning “reconstructed LAI”.
A short video of this research