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

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.

Why trees grow at night

“…Radial stem growth was associated with high mean SWP (−6 to −65 kPa) and low mean VPD (0.11–0.24 kPa, Table S2 ), emphasizing the commonly known negative influence of dry air and soil on growth processes (Zweifel et␣al ., 2006 ; Pappas et␣al ., 2020 ). However, these daily mean values did not account for diel dynamics and they did not reflect how differently SWP and VPD were generally related to stem growth at an hourly resolution (Figs 3 , 4 ).…”

“…However, the ranking of species along the linear regression line between time of day of maximum growth and the annual number of hours with growth was at least partly explainable by the respective SWP and VPD ranges for growth (Table S2 ). The drier the average site conditions where a species occurred, the fewer hours with growth were measured, which is consistent with the generally known limitation of growth by drought (McDowell & Sevanto, 2010 ; Korner, 2015 ; Pappas et␣al ., 2020 ). This was especially true for the two most extreme species in our study, Abies alba (growing mostly under humid conditions) and Quercus pubescens (growing under driest conditions).…”

“…Meanwhile, the zero‐growth approach has become widely accepted and applied (Dietrich & Kahmen, 2019 ; Schafer et␣al ., 2019 ; Eitel et␣al ., 2020 ; Güney et␣al ., 2020 ; Lamacque et␣al ., 2020 ; Pappas et␣al ., 2020 ; Sellier & Segura, 2020 ). Accordingly, growth is defined as the radial stem increase above a previously reached stem radial maximum (Fig.…”

Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest

“…Thus, tree radius varies daily because of transpiration‐induced changes in water storage and potential in the stem (Perämäki et al., 2001). We used the shift in the diurnal cycle of tree trunk radii to indicate the onset of transpiration in the spring (King et al., 2013; Pappas, Peters, & Fonti, 2020; Sevanto et al., 2006).…”

TreeNet–The Biological Drought and Growth Indicator Network

“…Increased growth was only observed in the driest parts of Switzerland (Figure 1) at this time of the season (Figure 6), e.g., in the inner alpine valleys in the southwest of the country (Valais). Considering the generally delayed growth response of trees to changing environmental conditions (Ogle et al, 2015;Zweifel and Sterck, 2018;Kannenberg et al, 2019;Bastos et al, 2020;Bose et al, 2020;Pappas et al, 2020;Zweifel et al, 2020;Fang et al, 2021), a uniform rapid growth response to wet conditions was not expected. However, trees growing normally under most droughtstressed conditions appeared to benefit more immediately in terms of an above-average growth performance.…”