Linking variability of tree water use and growth with species resilience to environmental changes

Christoforos Pappas,Patrick Fonti,Richard L Peters

doi:10.1111/ecog.04968

Abstract

Tree growth is an indicator of tree vitality and its temporal variability is linked to species resilience to environmental changes. Second‐order statistics that quantify the cross‐scale temporal variability of ecophysiological time series (statistical memory) could provide novel insights into species resilience. Species with high statistical memory in their tree growth may be more affected by disturbances, resulting in lower overall resilience and higher vulnerability to environmental changes. Here, we assessed the statistical memory, as quantified with the decay in standard deviation with increasing time scale, in tree water use and growth of co‐occurring European larch Larix decidua and Norway spruce Picea abies along an elevational gradient in the Swiss Alps using measurements of stem radius changes, sap flow and tree‐ring widths. Local‐scale interspecific differences between the two conifers were further explored at the European scale using data from the International Tree‐Ring Data Bank. Across the analysed elevational gradient, tree water use showed steeper variability decay with increasing time scale than tree growth, with no significant interspecific differences, highlighting stronger statistical memory in tree growth processes. Moreover, Norway spruce displayed slower decay in growth variability with increasing time scale (higher statistical memory) than European larch; a pattern that was also consistent at the European scale. The higher statistical memory in tree growth of Norway spruce in comparison to European larch is indicative of lower resilience of the former in comparison to the latter, and could potentially explain the occurrence of European larch at higher elevations at the Alpine treeline. Single metrics of resilience cannot often summarize the multifaceted aspects of ecosystem functioning, thus, second‐order statistics that quantify the strength of statistical memory in ecophysiological time series could complement existing resilience indicators, facilitating the assessment of how environmental changes impact forest growth trajectories and ecosystem services.

Highlights

Tree water use and growth are intrinsically coupled processes that define tree performance and affect terrestrial biogeochemical cycles across spatiotemporal scales
(Fig. 5). 3d) and Growing season WHSFD (Fig. 3g) diurnal fluctuations in WHSRF showed a consistent sinusoidal pattern: during night-time there was an increase in stem radius and water storage, as a result of lower vapour pressure deficit (VPD) and transpiration rates; during day-time there was a decrease in stem radius and depletion of stem water storage as result of higher transpiration rates and atmospheric demand in comparison to root water supply (Zweifel et al 2001, King et al 2013, Pappas et al 2018)
While tree water use and growth are intrinsically coupled processes (Fatichi et al 2015, Steppe et al 2015, Venturas et al 2017) our analysis revealed that their temporal variability exhibits different decay patterns as we move from shortto longer time scales

Summary

Introduction

Tree water use and growth are intrinsically coupled processes that define tree performance and affect terrestrial biogeochemical cycles across spatiotemporal scales. Apart from direct impact on the terrestrial carbon cycle (Huntzinger et al 2017, Le Quéré et al 2018, Fatichi et al 2019), affects several other biochemical and biophysical processes and trigger local, regional and global scale climate feedbacks (Bonan 2008, Friedlingstein 2015). Most of the continuous ecophysiological measurements (e.g. with high frequency sap flow sensors or stem dendrometers) have been performed on relatively short time scales spanning few growing seasons, making it difficult to assess long-term variability in the underlying processes. Scrutinizing the variability of ecophysiological processes across a continuum (e.g. hourly to decadal variability) rather than individual time scales (daily, annual, etc.) could shed light on vegetation resilience to environmental changes

Methods

Results

Conclusion