Abstract
Radial stem size changes, measured with automated dendrometers at intra-daily resolution, offer great potential to link environmental conditions with tree physiology at the seasonal scale. Such measurements need to be time-aligned, cleaned of outliers and shifts, gap-filled and analysed for reversible (water-related) and irreversible (growth-related) fractions to obtain physiologically meaningful data. Therefore, comprehensive tools are needed for reproducible data processing and analytics of dendrometer data. Here we present a transparent method, compiled in the R package treenetproc, to turn raw dendrometer data into clean, physiologically interpretable information, i.e., stem growth, tree water deficit, growth phenological phases, mean daily shrinkage and their respective timings. The removal of errors is facilitated by additional functions and supported with graphical visualizations. To ensure reproducible data handling, the processing parameters and induced changes to the raw data are documented in the output and, thus, are a step towards a standardized processing of automatically measured stem radius time series. We discuss examples, such as the seasonality of growth or the dependence of growth on atmospheric and soil drought. The presented growth and water-related physiological variables at high temporal resolution offer novel physiological insights into the seasonally varying responses of trees to changing environmental conditions.
Highlights
Tree water use and wood growth are closely coupled processes and jointly define a tree’s physiology on a daily to seasonal time scale
The cleaned and gap-filled data are used to compute time series of tree water deficit and annually accumulated growth, which are reported in the output data frame (Table S3)
The questions range from “when do trees grow?”, and “what are speciesspecific differences?” to “what is the impact of drought on tree water relations and growth performance?” (Figures 5 and 6)
Summary
Tree water use and wood growth are closely coupled processes and jointly define a tree’s physiology on a daily to seasonal time scale. Growth phenology and radial increment from dendrometer measurements are not without pitfalls (i.e., stem shrinkage preventing appropriate detection of growth start and end; [29]), they provide a promising and cost-effective method to derive such proxies at sub-daily resolutions Realizing this potential requires reproducible and user-friendly ways of data processing being able to separate water-related from growth-related dynamics. Treenetproc provides a standardised and flexible calculation of critical phenological growth phases such as the beginning and end of stem growth within the growing season It calculates the timing and rate of change of different phases of stem shrinkage and expansion and provides a variety of ways to better contextualise dendrometer data to changing environmental conditions [4]. It is consistent with the necessary evolution from an annual to an intra-annual focus of tree-specific water and carbon-related responses to environmental change [11]
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