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Constitutive and induced phenolics and volatiles in Quercus pyrenaica

Cite this dataset

Galmán, Andrea et al. (2020). Constitutive and induced phenolics and volatiles in Quercus pyrenaica [Dataset]. Dryad.


With this dataset, we studied elevational gradients and their underlying climatic factors in constitutive and induced phenolics and volatile organic compounds in Oak trees. Oak defences were measured in leaves in a field study. 

The dataset includes data for 18 populations of Quercus pyrenaica spanning a 1300 m elevational gradient (from 370 to 1614 m) with their correspondence coordinates. In each population we sampled six saplings that were randomly assigned to one of two treatments: 1) herbivore inductionwith A. quercertorum larvae or 2) no induction (control). For each tree, we include an estimation of leaf-herbivory accounting for pre-treatment variation in natural herbivory as well as in the amount of experimentally-imposed damage by larvae.

For each tree, we quantified and identify volatile organic compounds. We report 75 individual compounds including monoterpenes, sesquiterpenes and other compounds of different nature. We also quantify and identify 40 phenolics that were classified as condensed tannins, hydrolysable tannins, lignins or flavonoids.

Finally, the dataset includes eight climatic variables extracted from worldClim for the coordinates of each population.


Phenolics were extracted from dry leaves using a methanolic extraction. For phenolics quantification, we used ultra-high performance
liquid-chromatography and a UV/VIS photodiode array detector. For phenolic identification, we used an ultraperformance liquid chromatography coupled with electrospray
ionization quadrupole time-of-flight mass spectrometry.

Volatile Organic Compounds (VOCs) were collected from bagged leaves and trapped on charcoal filter using air-sampling pumps. After collection, VOCs were eluted in dichloromethane. For VOCs quantification, we used gas chromatography (GC) coupled with a mass selective detector (MSD). For VOCs identification, we used Kovats
retention index from published work and the NIST Standard Reference Database.