S26 An Investigation of the Impact of Temperature and Precipitation Patterns on the Phenology of Deciduous Trees in Maine

Sunday, 12 January 2025
Hall C (New Orleans Ernest N. Morial Convention Center)
Amber R Stokes, University of Delaware, Newark, DE; and T. Foisy

Handout (3.4 MB)

The timing of seasonal biological events has been shown to be changing on a global scale in response to meteorological and climate-related factors. Several studies have shown changes in phenology of various species in the state of Maine over time, including shifts in the timing of deciduous tree spring leaf out and autumn peak foliage, resulting in longer growing seasons. Although some studies have shown a strong correlation between temperature and deciduous tree phenology (Everill et al., 2014; Parmesan, 2007), results from other studies suggest variation was tied more closely to microclimate and year-to-year temperature changes (MacKenzie et al., 2018). This study looked at the changes in temperature and precipitation and their effects on the timing of spring leaf out dates and peak foliage dates in four, geographically separated Maine locations. A comparison between the first and last 15 years of historical average monthly temperature datasets shows increases at all locations between 0.4-4.4 degrees Fahrenheit in October and 1.2-3.3 degrees Fahrenheit in April, while comparisons of average monthly precipitation were variable, but showed increases in some locations. Spring leaf out dates were directly compared with average April temperatures between 1981-2023, where a positive trend was found for all locations, with warmer temperatures correlated with earlier leaf out dates. The limited availability of autumn peak foliage data made analysis difficult; no correlation was shown between increasing temperature and later peak foliage dates over the 9 year dataset that was available. In order to more clearly understand the possible effects of climate and meteorological factors on tree phenology in Maine in order to predict future patterns, additional sites should be studied within the state and the region, including the analysis of both direct and remote sensing data.
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