Advanced X-ray CT scanning can boost tree ring research for earth system sciences. (31st July 2019)

• Record Type: Journal Article
• Authors: Van den Bulcke, Jan; Boone, Marijn A; Dhaene, Jelle; Van Loo, Denis; Van Hoorebeke, Luc; Boone, Matthieu N; Wyffels, Francis; Beeckman, Hans; Van Acker, Joris; De Mil, Tom
• Is Part Of: Annals of botany. Volume 124:Number 5(2019)
• Page Start: 837
• Page End: 847
• Publication Date: 2019-07-31
• Subjects: X-ray CT -- computed tomography -- tree ring analysis -- multiscale imaging -- earth system sciences -- increment cores -- wood traits -- densitometry -- deep learning -- scanner simulation; Botany -- Periodicals; 580
• DOI: 10.1093/aob/mcz126
• Languages: English
• ISSNs: 0305-7364

Abstract

Abstract: Background and Aims: Tree rings, as archives of the past and biosensors of the present, offer unique opportunities to study influences of the fluctuating environment over decades to centuries. As such, tree-ring-based wood traits are capital input for global vegetation models. To contribute to earth system sciences, however, sufficient spatial coverage is required of detailed individual-based measurements, necessitating large amounts of data. X-ray computed tomography (CT) scanning is one of the few techniques that can deliver such data sets. Methods: Increment cores of four different temperate tree species were scanned with a state-of-the-art X-ray CT system at resolutions ranging from 60 μm down to 4.5 μm, with an additional scan at a resolution of 0.8 μm of a splinter-sized sample using a second X-ray CT system to highlight the potential of cell-level scanning. Calibration-free densitometry, based on full scanner simulation of a third X-ray CT system, is illustrated on increment cores of a tropical tree species. Key Results: We show how multiscale scanning offers unprecedented potential for mapping tree rings and wood traits without sample manipulation and with limited operator intervention. Custom-designed sample holders enable simultaneous scanning of multiple increment cores at resolutions sufficient for tree ring analysis and densitometry as well as single core scanning enabling quantitative wood anatomy, thereby approaching the conventional thin section approach. Standardized X-ray CT volumes are, furthermore, ideal input imagery for automated pipelines with neural-based learning for tree ring detection and measurements of wood traits. Conclusions: Advanced X-ray CT scanning for high-throughput processing of increment cores is within reach, generating pith-to-bark ring width series, density profiles and wood trait data. This would allow contribution to large-scale monitoring and modelling efforts with sufficient global coverage.