Informace o publikaci
Application of RCS and signal-free RCS to tree-ring width and maximum latewood density data
Autoři | |
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Rok publikování | 2024 |
Druh | Článek v odborném periodiku |
Fakulta / Pracoviště MU | |
Citace | |
www | https://www.sciencedirect.com/science/article/pii/S1125786524000420 |
Doi | http://dx.doi.org/10.1016/j.dendro.2024.126205 |
Klíčová slova | Maximum latewood density; Temperature; Tree -ring width; Scandinavia |
Popis | Dendroclimatic research faces the challenge of selecting appropriate detrending methods for retaining lowfrequency signals in temperature reconstructions. Among the numerous methods available to dendrochronologists, regional curve standardisation (RCS) and the signal-free approach in combination with RCS (SF-RCS) are increasingly used to preserve the full spectrum of temperature variance in tree-ring data. Here, we apply RCS and SF-RCS to tree-ring width (TRW) and maximum latewood density (MXD) datasets composed of only living and combined living and relict trees from northern Scandinavia. Whereas RCS and SF-RCS produce highly similar chronologies when applied to composite (living-plus-relict) datasets, particularly for MXD, both methods fail to establish chronologies coherent with regional temperature trends when applied to living-tree datasets. Additional tests including pruning of well-replicated living-tree datasets, to approximate the heterogenous agestructure of composite datasets, reveal improved results and coherent trends in MXD. While this demonstrates the applicability of joint detrending and pruning techniques to retain meaningful low-frequency variance in living-tree MXD chronologies, similar improvements were not achieved with TRW, likely because of the much stronger age-trend inherent to this widely used proxy. Further tests with other tree species and in alpine environments are needed to verify these findings. However, such assessments require an adjustment of tree-ring sampling protocols to increase replication to 50+ trees per site including old and young individuals to facilitate data pruning. |