Using parallel factor analysis modeling (PARAFAC) and self-organizing maps to track senescence-induced patterns in leaf litter leachate

As trees undergo autumnal processes such as resorption, senescence, and leaf abscission, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams changes. However, little research has investigated how the fluorescent DOM (FDOM) changes throughout the autumn and how this differs inter- and intraspecifically. Two of the major impacts of global climate change on forested ecosystems include altering phenology and causing forest community species and subspecies composition restructuring. We examined changes in FDOM in leachate from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and yellow poplar (Liriodendron tulipifera L.) leaves from Maryland throughout three different phenophases: green, senescing, and freshly abscissed. Beech leaves from Maryland and Rhode Island have previously been identified as belonging to the same distinct genetic cluster and beech trees from Vermont and the study site in North Carolina from the other. FDOM in samples was characterized using excitation-emission matrices (EEMs) and a six-component parallel factor analysis (PARAFAC) model was created to identify components. Self-organizing maps (SOMs) were used to visualize variation and patterns in the PARAFAC component proportions of the leachate samples. Phenophase and species had the greatest influence on determining where a sample mapped on the SOM when compared to genetic clusters and geographic origin. Throughout senescence, FDOM from all the trees transitioned from more protein-like components to more humic-like ones. Percent greenness of the sampled leaves and the proportion of the tyrosine-like component 1 were found to significantly differ between the two genetic beech clusters. This suggests possible differences in photosynthesis and resorption between the two genetic clusters of beech. The use of SOMs to visualize differences in patterns of senescence between the different species and genetic populations proved to be useful in ways that other multivariate analysis techniques lack.