Growth resistance and resilience of mixed silver fir and Norway spruce forests in central Europe: Contrasting responses to mild and severe droughts

Abstract Extreme droughts are expected to increase in frequency and severity in many regions of the world, threatening multiple ecosystem services provided by forests. Effective strategies to adapt forests to such droughts require comprehensive information on the effects and importance of the factors influencing forest resistance and resilience. We used a unique combination of inventory and dendrochronological data from a long‐term (>30 years) silvicultural experiment in mixed silver fir and Norway spruce mountain forests along a temperature and precipitation gradient in southwestern Germany. We aimed at examining the mechanisms and forest stand characteristics underpinning the resistance and resilience to past mild and severe droughts. We found that (i) fir benefited from mild droughts and showed higher resistance (i.e., lower growth loss during drought) and resilience (i.e., faster return to pre‐drought growth levels) than spruce to all droughts; (ii) species identity determined mild drought responses while species interactions and management‐related factors strongly influenced the responses to severe droughts; (iii) intraspecific and interspecific interactions had contrasting effects on the two species, with spruce being less resistant to severe droughts when exposed to interaction with fir and beech; (iv) higher values of residual stand basal area following thinning were associated with lower resistance and resilience to severe droughts; and (v) larger trees were resilient to mild drought events but highly vulnerable to severe droughts. Our study provides an analytical approach for examining the effects of different factors on individual tree‐ and stand‐level drought response. The forests investigated here were to a certain extent resilient to mild droughts, and even benefited from such conditions, but were strongly affected by severe droughts. Lastly, negative effects of severe droughts can be reduced through modifying species composition, tree size distribution and stand density in mixed silver fir‐Norway spruce forests.

: Tree-and stand-level variables tested to model resistance, resilience and recovery to drought.     Table S6: Linear mixed-effect models. Fit of tree-level resistance, recovery, and resilience as function of different variables (full models). Table S7: Linear mixed-effect models. Fit of stand-level resistance, recovery, and resilience as function of different variables (full models).           Appendix S1: Extended materials and methods information

Study sites
The shelterwood experiment (Weise, 1995) comprised three treatments differing in length of the regeneration period (20, fast, 35, medium, and 50 years, slow) and increment controls (stands maintained fully stocked by harvesting only 50% of the periodic increment every 5 years). The stands used in the experiment did not receive interventions in the 10 years preceding the beginning of the experiment (initiated between 1979 and 1981); the treatments were assigned to approximately 0.25 ha square plots. The three treatments were cut to 75% of the volume of a fully stocked stand at the time of the research installation. The interventions were planned at 5-year intervals in each treatment, according to the following scheme: Note that the fast treatment (20-year regeneration period, ended in the early 2000s) did not cover the entire period of analysis, and thus was not included in the analysis presented in this study.

Inventory and field data collection, and laboratory analysis
The diameter at breast height (DBH), height, live crown length, crown radii and leaf area of the trees for which these variables were not measured, were predicted from the sampled trees using the following equations (Forrester et al., 2019), for each plot and species: where DBHt is DBH at year t in cm, DBHt-1 is DBH of the previous year (t-1) in cm and β0 and β1 are fitted parameters. y = 1.3 + β0 e -β1 / DBH (Michajlov, 1952) ( 2) where y is total height in m or live crown length in m, DBH in cm and β0 and β1 are fitted parameters.
where KRA is crown radius in m, DBH in cm and β0 and β1 are fitted parameters.
Leaf area values were obtained using species-specific leaf area allometric equations (Forrester et al., 2017), where leaf area is predicted from DBH.

Statistical analyses
Twelve full models (2 levels: tree, stands; 2 drought groups: mild, severe; and 3 responses: resistance, recovery, resilience) were used to test different random structures to select the optimal random structure and, thus, type of model for analysis: random intercept to account for variability in the growth response to drought among trees within the same plot (tree-level models), and among plots within the same site (stand-level models); random intercept and slope, containing residual stand basal area as a fixed effect with a random slope and intercept; and no random term (Table S3). The restricted maximum likelihood method was used to evaluate the optimal random structure of the full models (      Slow -Medium (severe) 1.0000 1.0000 1.0000 Table S6: Summary of linear mixed-effect models. Fit of tree-level resistance, recovery, and resilience for mild (years 1984 and 1991) and severe drought events (years 2003 and 2011) as a function of different variables (full models). Sp = species (2 levels: fir, reference spruce); APAR = absorption of photosynthetically active radiation; NIratio fir = ratio of intensity of competition of fir to total intensity of competition; NIratio other = ratio of intensity of competition of other species (mainly beech) to total intensity of competition; BAstand = stand basal area; SPEI = SPEI of July at the time scale of 5 months; x = interaction; R 2 m = marginal R-squared (variance explained by the fixed factors); and R 2 c = conditional R-squared (variance explained by the fixed and random factors). Significance codes: '***' 0.001, '**' 0.01, '*' 0.05, '°' 0.1.  Table S7: Summary of linear regression models. Fit of stand-level resistance, recovery, and resilience for mild (years 1984 and 1991) and severe drought events (years 2003 and 2011) as a function of different variables (full models). APAR = absorption of photosynthetically active radiation; Shannon = Shannon diversity index; Ratiospruce = ratio of basal area of spruce to total stand basal area; BAstand = stand basal area; DBH = mean diameter at breast height (1.3 m height); Yrssince last = number of years since the last thinning; SPEI = SPEI of July at the time scale of 5 months; and R 2 adj = adjusted R-squared. Significance codes: '***' 0.001, '**' 0.01, '*' 0.05, '°' 0.1.  Figure S1: Tree stem density (N trees/ha) across treatments and sites since 1980. Vertical grey lines denote the years 1984years , 1991years , 2003years , and 2011: Correlation between SPEI and tree-ring chronologies using different time scales for the SPEI (2, 4, 5, and 6 months). No significant differences were found among the four SPEI in and between the months of June and July (repeated ANOVA tests, α > 0.05). Therefore, SPEI of July at the time scale of 5 months was selected because it covers the period of most radius increment for trees in the area (Dietrich et al., 2018). Correlation coefficients were calculated using the function dcc of the R package bootRes (Zang & Biondi, 2013). Individual tree-ring series were detrended by a smoothing spline, with 50% frequency response at 2/3 of series' length. Site chronologies were built using the Tukey's biweight robust mean with the function tbrm of the R package dplR (Bunn et al., 2014).   1984,1991,2003,2011. The different filling colors represent the probability associated to the density distribution (< 2.5%, 2.5-50%, 50-97.5%, > 97.5%).  1984,1991,2003,2011 are highlighted in yellow, orange, red and dark red, respectively. The different filling colors represent the probability associated to the density distribution (< 2.5%, 2.5-50%, 50-97.5%, > 97.5%).