title: The influence of sampling design on tree-ring-based quantification of forest growth.
abstract: 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.
authors.affiliation: Swiss Federal Research Institute WSL, Zürcherstrasse 111, Birmensdorf, CH-8903, Switzerland.
authors.forename: Christoph
authors.initials: C
authors.lastname: Nehrbass-Ahles
authors.forename: Flurin
authors.initials: F
authors.lastname: Babst
authors.forename: Stefan
authors.initials: S
authors.lastname: Klesse
authors.forename: Magdalena
authors.initials: M
authors.lastname: Nötzli
authors.forename: Olivier
authors.initials: O
authors.lastname: Bouriaud
authors.forename: Raphael
authors.initials: R
authors.lastname: Neukom
authors.forename: Matthias
authors.initials: M
authors.lastname: Dobbertin
authors.forename: David
authors.initials: D
authors.lastname: Frank
mesh_terms: D057231:Climate Change; D065928:Forests; D018547:Plant Stems / Q000033:anatomy & histology*; D012107:Research Design; D015983:Selection Bias; D013557:Switzerland; D014197:Trees / Q000033:anatomy & histology / Q000254:growth & development*
keywords: CO2 fertilization; carbon cycle; climate reconstruction; climate response; forest productivity; growth trends; sampling bias; tree-rings