Abstract

Regional differences in tree growth can be used to approximate the geographical provenance of ring-width series (‘dendro-provenancing’). This method relies on cross-dated ring-width series (reference chronologies) that are thought to represent the radial growth signal of trees in a given region. Reference chronologies are often established from ring-width series of living tree populations. Frequently, they are too short to allow for investigating the provenance of historical wood. Thus, references are extended by ring-width series from buildings and art-historical objects that exhibit best matching growth patterns with the living tree references. Yet, series from other provenances may erroneously be included. Thereby the local or regional growth signal of the references is progressively contaminated, but this has received little attention to date. I investigate this contamination risk using a simulation approach that allows for generating pseudo site chronologies that preserve the relevant statistical properties of the real site chronologies. While the exact provenance of historical wood is unknown, for simulated ring-width series the provenance is unambiguous. Hence, pseudo reference chronologies may be established while monitoring the signal mixture. Specifically, 15 site chronologies of Norway spruce (Picea abies (L.) H. Karst.) from northeastern Switzerland were used to generate 15 pseudo site growth signals that span 1000 years. The simulation demonstrates that quasi uncontaminated references can be established in ideal circumstances for the study area. However, the thresholds for the similarity in between-series correlation must be very high. Even then, contaminated pseudo references occurred in rare cases during the simulation. Yet, elevation-specific pseudo references were established with lower thresholds. Simulation currently offers the only approach for assessing the contamination risk of reference chronologies, and it allows for elucidating the conditions under which acceptable levels of contamination can be guaranteed. Therefore, the present approach paves the way towards a practical simulation tool for dendro-provenancing.

Highlights

  • Dendrochronology is used in many scientific disciplines, e.g. in Forestry, Climatology and Ecology [1]

  • Dendro-provenancing goes beyond the dating of wooden objects and capitalizes on regional differences in tree growth that originate from regional differences in climatic and site conditions

  • The number of PREF-Constructor runs executed per simulation repetition was very low

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Summary

Introduction

Dendrochronology (most commonly, the study of tree-ring width) is used in many scientific disciplines, e.g. in Forestry, Climatology and Ecology [1]. Dendro-provenancing goes beyond the dating of wooden objects and capitalizes on regional differences in tree growth that originate from regional differences in climatic and site conditions. Dendro-provenancing is based on the comparison of candidate ring-width series from historical objects of unknown provenance to a framework of local reference chronologies. The reference chronologies are established from cross-dated samples of ring-width measurements that are thought to represent local tree-growth. The location of the provenance is approximated by the geographical area in which best matches between the ring-width patterns of a candidate series and the reference chronologies are found [16]. Best matches are determined statistically using the same methods as for the (cross-)dating of ringwidth series [17, 18]

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