Data set used in publication titled: All the light we cannot see: Climate manipulations leave short and long-term imprints in spectral reflectance of trees

Abstract

Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant-environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming, and drought affect spectra. To address this gap, we used an open-air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal-temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400-2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid-season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long- and short-time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near-infrared and shortwave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g. indices and traits) improves inferences about plant-environment relationships, which is particularly important in times of unprecedented climate change.