Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series

• Published in: Ecology and evolution Vol. 10; no. 14; pp. 7419 - 7430
• Main Authors: Czyż, Ewa A., Guillén Escribà, Carla, Wulf, Hendrik, Tedder, Andrew, Schuman, Meredith C., Schneider, Fabian D., Schaepman, Michael E.
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01-07-2020; John Wiley and Sons Inc; Wiley
• Subjects: Biodiversity; Biodiversity loss; Climate change; Deoxyribonucleic acid; DNA; Environmental changes; Fagus sylvatica; Forests; Genetic diversity; Genetic structure; Genetic testing; Genetics; Genotype & phenotype; Hypotheses; Imaging; imaging spectroscopy; Information processing; intraspecific variation; Moisture content; Monitoring; Original Research; partial least squares regression; Phenols; Phylogenetics; Pigments; Plant diversity; Population; Population genetics; Population studies; Reflectance; Regression analysis; Remote sensing; Sampling; Seasonal variations; Spectra; Spectroscopy; Statistical analysis; Taxonomy; temperate forest; Temperate forests; Time series; Trees; Water content; Switzerland; population genetics; temperate forest; partial least squares regression; imaging spectroscopy; intraspecific variation
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.6469

The growing pace of environmental change has increased the need for large‐scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.
We used multi‐annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.
We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full‐analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.
This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.
Declining intraspecific genetic variation is likely a critical factor in biodiversity loss. In this study, we demonstrated the high potential of airborne imaging spectroscopy to access information about intraspecific genetic variation in a systematic and spatially continuous manner.