Diurnal temperature regimes drive seedling distribution at an abrupt treeline

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Jessie L. Sheldon and Miroslav Kummel, Environmental Science, Colorado College, Colorado Springs, CO

Background/Question/Methods
While it is generally accepted that temperature determines the approximate altitude of treeline, drivers of fine-scale treeline dynamics are poorly understood. Within treeline literature, there is an underlying assumption that sheltering from trees is beneficial for seedlings, initiating a positive feedback loop. However, sheltering can potentially create both hospitable and hostile microclimates. In this study, we examined the relationship between microclimate and seedling distribution at an abrupt treeline on Pikes Peak, Colorado and ask two main questions: (1) How do trees modify their surrounding microclimate, and (2) how do these microclimates impact seedling establishment? To explore these questions, we analyzed daytime and nighttime thermal images of treeline. The drone thermal images were taken during the growing season before sunrise and at solar noon in August 2017, and then processed into orthomosaics (pixel size of 9 cm and 10 cm, respectively). All seedlings were mapped with 20 cm precision in an approximately 160mx130m study area in June 2017. Supporting 3D tree canopy structures were derived from 2019 drone images. We first analyzed the spatial distribution of surface temperature with respect to the treeline spatial structure, followed by seedling density with respect to ground temperatures.
Results/Conclusions
We found that the microclimate temperature variations surrounding trees are defined by three factors: (1) the obstruction of boundary layer airflow, which leads to eddy-like isolated pockets of air that exhibit exaggerated diurnal temperatures (2) long wave radiation from trees, primarily a nighttime phenomenon that warms a certain radius on the ground below a tree, and (3) shade, which accounts for most of the daytime temperature lows. These three competing mechanisms interact with each other, resulting in a mosaic of variable ground temperatures adjacent to trees. Between these variable microclimates, seedlings exhibited distinct temperature preferences, with the highest density at both moderate daytime and nighttime temperatures, and an explicit avoidance of both daytime and nighttime high and low temperatures. When the temperature raster is divided into 12 equal temperature classes, and seedling density is compared between the classes, the best fit for both the daytime and nighttime datasets were third degree polynomials (Daytime: adjusted R2= 0.70, F(3,8)= 9.458, p=0.005, Nighttime: adjusted R2=0.58, F(3,8)=6.043, p=0.019). An analysis using a relative distribution estimate function (Rhohat) in spatstats package in R corroborated these findings.