Fourier transform infrared (FTIR) spectroscopy enables chemical analysis of pollen samples for plant phenotyping to study plant–environment interactions, such as influence of climate change or pathogens. However, current approach, such as microspectroscopy and attenuated total reflection spectroscopy, does not allow for high-throughput protocols. This study at hand suggests a new spectroscopic method for high-throughput characterization of pollen. Samples were measured as thin films of pollen fragments using a Bruker FTIR spectrometer with a high-throughput eXTension (HTS-XT) unit employing 384-well plates. In total, 146 pollen samples, belonging to 31 different pollen species of Fagaceae and Betulaceae and collected during three consecutive years (2012–2014) at locations in Croatia, Germany and Norway, were analysed. Critical steps in the sample preparation and measurement, such as variabilities between technical replicates, between microplates and between spectrometers, were studied. Measurement variations due to sample preparation, microplate holders and instrumentation were low, and thus allowed differentiation of samples with respect to phylogeny and biogeography. The spectral variability for a range of Fagales species (Fagus, Quercus, Betula, Corylus, Alnus and Ostrya) showed high-species-specific differences in pollen's chemical composition due to either location or year. Statistically significant inter-annual and locational differences in the pollen spectra indicate that pollen chemical composition has high phenotypic plasticity and is influenced by local climate conditions. The variations in composition are connected to lipids, proteins, carbohydrates and sporopollenins that play crucial roles in cold and desiccation tolerance, protection against UV radiation and as material and energy reserves. The results of this study demonstrate the value of high-throughput FTIR approach for the systematic collection of data on ecosystems. The novel FTIR approach offers fast, reliable and economical screening of large number of samples by semi-automated methodology. The high-throughput approach could provide crucial understanding on plant–climate interactions with respect to biochemical variation within genera, species and populations.