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In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1–3.2 days decade−1) compared to the spring (0.9–1.5 days decade−1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling.

Phenology is the study of recurring biological events and how they are affected by interannual variations in climate. Phenology has a direct effect on the annual productivity of forest ecosystems because it determines the length of the growing season and physiological activity. Longer growing seasons tend to have positive effects on forest ecosystem productivity in areas not limited by water, in others, longer growing seasons could amplify water stress and have a net negative effect on forest productivity. This dissertation entails three studies that investigate how forest phenology responds to changing environmental conditions. Each of the projects utilizes high-frequency measurements of forest phenology across different forest types to address knowledge gaps and better understand how forests cope with a changing climate. The first chapter investigates how the phenology of aboveground tree growth varies along an elevation gradient in the semi-arid southwestern United States (US). The timing of growth in these semi-arid ecosystems showed high variability among years, particularly at low elevations, indicating growth phenology in water-limited ecosystems is more variable than temperate forest ecosystems not limited by water. The second chapter utilizes digital repeat photography to extract phenology dates and model future changes in spring and fall transition dates in temperate deciduous forests in the eastern US. The models suggested season length will be more affected in the fall in response to future climate change than spring, but spring will have a larger positive effect on the forest productivity. The third chapter investigates the link between low temporal resolution tree growth measurements (i.e., annual tree rings) and high-resolution forest carbon uptake measurements (i.e., net ecosystem productivity) to identify potential lags in allocation of carbon to structural aboveground biomass. Lags in allocation of previous year carbon uptake to structural growth were detected at half of the sites studied, suggesting trees use stored carbon from previous years, but the role of stored carbohydrates for growth may not be as important in slow growing ecosystems due to other limitations on growth. By using multiple different sites in each of the outlined chapters, forest phenology was shown to respond strongly to the seasonality of most limiting factors. Phenology of forest ecosystems in the southwestern US had stronger links to water limitation, while the phenology of northeastern US was more strongly temperature limited. The widespread linkage of phenology to temperature in the literature suggests water-limitation is an undervalued driver of phenological change across the US, and globally.

Carbon (C) storage and accumulation in forests is of growing importance as climate change focuses our attention on rising greenhouse gas emissions. In 2012, we measured total ecosystem C pools (including live vegetation, dead wood, and soils) in two unmanaged, mixed-species stands in central Maine, USA. The stands are adjacent to one another and serve as references against which silvicultural treatments can be compared. The soil parent material of the stands was different (marine sediments versus glacial till), which provided an ideal opportunity to compare C stocks between these stands. We used tree ring analysis and repeated forest inventories to estimate tree and dead wood recruitment patterns and past disturbance severity. Site quality influenced C trajectories through its influence on tree species composition, which in turn strongly determined stand susceptibility to insect outbreaks. In 2012, total ecosystem C stocks were 196.3 ± 9.6 Mg ha–1 (mean ± SD) in the stand on soils derived from marine sediments and 247.0 ± 17.7 Mg ha–1 in the stand on soils derived from glacial till. Differences in average total ecosystem C stocks were primarily driven by the live tree C pool. Despite the occurrence of several partial disturbance events from 1954 to 2012, live tree C stocks increased over time in both stands. Average C accumulation in recruited dead wood was also positive, indicating that aboveground biomass served as a C sink. Our results can be used to inform decisions related to C objectives in unmanaged stands of similar species composition and soils.

This study examined climate—tree growth relationships of a G2 globally rare Pinus rigida (Pitch Pine) barren located at the species' northern range limit in Acadia National Park, ME. Our tree-ring chronologies spanned the period 1804–2014 CE and included 50 dated tree-ring series from 33 trees. We found significant (P < 0.05) positive correlations in all chronologies between each year's tree growth and previous October through April temperature, as well as with August precipitation. Additionally, we found negative correlations between our chronologies and previous July precipitation. Moving interval correlation analysis showed temporal instability of all climate—growth relationships except for April temperature and August precipitation for the total width and latewood chronologies. Our results corroborate previous findings that suggest tree species at their northern range limit respond positively to winter temperature. We posit warmer winter temperatures and enhanced late-summer precipitation indicate a maritime influence that positively influenced radial growth at our site.