A Machine Learning Approach To Analyzing The Relationship Between Temperatures And Multi-Proxy Tree-Ring Records

Machine learning (ML) is a widely unexplored field in dendroclimatology, but it is a powerful tool that might improve the accuracy of climate reconstructions. In this paper, different ML algorithms are compared to climate reconstruction from tree-ring proxies. The algorithms considered are multiple linear regression (MLR), artificial neural networks (ANN), model trees (MT), bagging of model trees (BMT), and random forests of regression trees (RF). April-May mean temperature at a Quercus robur stand in Slovenia is predicted with mean vessel area (MVA, correlation coefficient with April-May mean temperature, r = 0.70, p 0.05 (ns)) chronologies. The predictive performance of ML algorithms was estimated by 3-fold cross-validation repeated 100 times. In both spring and summer temperature models, BMT performed best respectively in 62% and 52% of the 100 repetitions. The second-best method was ANN. Although BMT gave the best validation results, the differences in the models' performances were minor. We therefore recommend always comparing different ML regression techniques and selecting the optimal one for applications in dendroclimatology.This item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at [email protected]

Stable Isotopic Evidence for the Widespread Presence of Oxygen Containing Chemical Linkages between alpha-Cellulose and Lignin in Poaceae (Gramineae) Grass Leaves

The chemical linkage between alpha-cellulose and lignin in plant cell walls has long been a controversial topic and crucial to devising effective strategies for sustainable biomass and bioenergy utilization. In this new contribution, we surveyed 80 Poaceae (Gramineae) species grown in tropical Hainan Island (China) to test the hypothesis that the presence of oxygen-containing chemical linkage in Poaceae species is widespread. Our innovative natural abundance oxygen isotopic analysis allowed us to infer that more than 1/3 of the species investigated has chemical (ether) linkages between alpha-cellulose and lignin in their leaf cell walls, with a species-specific 2-89 oxygen-containing bonds for every 1000 glucose units. However, the presence of such linkage appears to be phylogeny-dependent. On average, species of C-3 photosynthetic mode are found to have more extensive oxygen-containing linkages than those of C-4 photosynthetic mode. Our finding challenges the conventional view that no chemical bonds between alpha-cellulose and lignin are present in higher plant cell walls and calls for new strategies for further understanding of the chemical linkage between the two major constituents of cell walls. This is especially important in the context of renewed and growing interests in biomass, bioenergy, and plant cell wall structure studies