Among-tree variability and feedback effects result in different growth responses to climate change at the upper treeline in the Swiss Alps

Upper treeline ecotones are important life form boundaries and particularly sensitive to a warming climate. Changes in growth conditions at these ecotones have wide‐ranging implications for the provision of ecosystem services in densely populated mountain regions like the European Alps. We quantify climate effects on short‐ and long‐term tree growth responses, focusing on among‐tree variability and potential feedback effects. Although among‐tree variability is thought to be substantial, it has not been considered systematically yet in studies on growth–climate relationships. We compiled tree‐ring data including almost 600 trees of major treeline species (Larix decidua, Picea abies, Pinus cembra, and Pinus mugo) from three climate regions of the Swiss Alps. We further acquired tree size distribution data using unmanned aerial vehicles. To account for among‐tree variability, we employed information‐theoretic model selections based on linear mixed‐effects models (LMMs) with flexible choice of monthly temperature effects on growth. We isolated long‐term trends in ring‐width indices (RWI) in interaction with elevation. The LMMs revealed substantial amounts of previously unquantified among‐tree variability, indicating different strategies of single trees regarding when and to what extent to invest assimilates into growth. Furthermore, the LMMs indicated strongly positive temperature effects on growth during short summer periods across all species, and significant contributions of fall (L. decidua) and current year's spring (L. decidua, P. abies). In the longer term, all species showed consistently positive RWI trends at highest elevations, but different patterns with decreasing elevation. L. decidua exhibited even negative RWI trends compared to the highest treeline sites, whereas P. abies, P. cembra, and P. mugo showed steeper or flatter trends with decreasing elevation. This does not only reflect effects of ameliorated climate conditions on tree growth over time, but also reveals first signs of long‐suspected negative and positive feedback of climate change on stand dynamics at treeline.

Quantifying the effects of drought on abrupt growth decreases of major tree species in Switzerland

Drought entails important effects on tree physiology, which may result in short‐ to long‐term radial growth decreases. While the majority of studies have focused on annual drought‐related variability of growth, relatively little is known about sustained growth decreases following drought years. We apply a statistical framework to identify climatic factors that induce abrupt growth decreases and may eventually result in tree mortality. We used tree‐ring data from almost 500 standing dead trees and 200 living trees in eight sites of the Swiss network of strict forest reserves, including four of the most important Central European tree species (Abies alba, Picea abies, Fagus sylvatica and Quercus spp.). First, to assess short‐term growth responses to drought under various climate and site conditions, we calculated correlations and linear mixed‐effects models between ring‐width indices (RWIs) and drought based on the Standardized Precipitation Evapotranspiration Index (SPEI). Second, to quantify drought effects on abrupt growth decreases, we applied distributed lag nonlinear models (DLNMs), which account for both delayed effects and the nonlinear relationship between the SPEI and the occurrence of abrupt growth decreases. Positive correlations between RWIs and the SPEI indicated short‐term growth responses of all species, particularly at arid sites. Results of the DLNMs revealed species‐specific growth responses to drought. For Quercus spp., abrupt growth decreases were more likely to occur several years following severe drought, whereas for P. abies, A. alba, and F. sylvatica abrupt growth decreases started frequently immediately in the drought year. We conclude that the statistical framework allows for quantifying the effects of drought intensity on the probability of abrupt growth decreases, which ultimately contributes to an improved understanding of climate impacts on forest community dynamics.

The influence of sampling design on tree-ring-based quantification of forest growth

Tree-rings offer one of the few possibilities to empirically quantify and reconstruct forest growth dynamics over years to millennia. Contemporaneously with the growing scientific community employing tree-ring parameters, recent research has suggested that commonly applied sampling designs (i.e. how and which trees are selected for dendrochronological sampling) may introduce considerable biases in quantifications of forest responses to environmental change. To date, a systematic assessment of the consequences of sampling design on dendroecological and-climatological conclusions has not yet been performed. Here, we investigate potential biases by sampling a large population of trees and replicating diverse sampling designs. This is achieved by retroactively subsetting the population and specifically testing for biases emerging for climate reconstruction, growth response to climate variability, long-term growth trends, and quantification of forest productivity. We find that commonly applied sampling designs can impart systematic biases of varying magnitude to any type of tree-ring-based investigations, independent of the total number of samples considered. Quantifications of forest growth and productivity are particularly susceptible to biases, whereas growth responses to short-term climate variability are less affected by the choice of sampling design. The world's most frequently applied sampling design, focusing on dominant trees only, can bias absolute growth rates by up to 459% and trends in excess of 200%. Our findings challenge paradigms, where a subset of samples is typically considered to be representative for the entire population. The only two sampling strategies meeting the requirements for all types of investigations are the (i) sampling of all individuals within a fixed area; and (ii) fully randomized selection of trees. This result advertises the consistent implementation of a widely applicable sampling design to simultaneously reduce uncertainties in tree-ring-based quantifications of forest growth and increase the comparability of datasets beyond individual studies, investigators, laboratories, and geographical boundaries.