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  • Articles  (3)
  • 2015-2019  (3)
  • Canadian Journal of Forest Research. 2016; 46(3): 387-401. Published 2016 Mar 01. doi: 10.1139/cjfr-2015-0366.  (1)
  • Canadian Journal of Forest Research. 2019; 49(12): 1483-1492. Published 2019 Dec 01. doi: 10.1139/cjfr-2018-0525.  (1)
  • Journal of Climate. 2019; 32(24): 8713-8731. Published 2019 Dec 02. doi: 10.1175/jcli-d-19-0184.1.  (1)
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  • Articles  (3)
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  • 1
    Publication Date: 2019-12-01
    Description: This is the first study to generate and analyze the climate signal in blue intensity (BI) tree-ring chronologies from Alaska yellow-cedar (Callitropsis nootkatensis (D. Don) Oerst. ex D.P. Little). The latewood BI chronology shows a much stronger temperature sensitivity than ring width and can thus provide information on past climate. The well-replicated BI chronology exhibits a positive January–August mean maximum temperature signal for 1900–1975, after which it loses temperature sensitivity following the 1976–1977 shift in northeastern Pacific climate. The positive temperature response appears to recover and remains strong for the most recent decades, but the coming years will continue to test this observation. This temporary loss of temperature sensitivity from about 1976 to 1999 is not evident in ring width or in a change in forest health but is consistent with prior work linking cedar decline to warming. A confounding factor is the uncertain influence of a shift in color variation from the heartwood–sapwood boundary. Future expansion of the yellow-cedar BI network and further investigation of the influence of the heartwood–sapwood transitions in the BI signal will lead to a better understanding of the utility of this species as a climate proxy.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
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  • 2
    Publication Date: 2016-03-01
    Description: Nonclimatic disturbance events are an integral element in the history of forests. Although the identification of the occurrence and duration of such events may help to understand environmental history and landscape change, from a dendroclimatic perspective, disturbance can obscure the climate signal in tree rings. However, existing detrending methods are unable to remove disturbance trends without affecting the retention of long-term climate trends. Here, we address this issue by using a novel method for the detection and removal of disturbance events in tree-ring width data to assess their spatiotemporal occurrence in a network of Scots pine (Pinus sylvestris L.) trees from Scotland. Disturbance trends “superimposed” on the tree-ring record are removed before detrending and the climate signals in the precorrection and postcorrection chronologies are evaluated using regional climate data, proxy system model simulations, and maximum latewood density (MXD) data. Analysis of subregional chronologies from the West Highlands and the Cairngorms in the east reveals a higher intensity and more systematic disturbance history in the western subregion, likely a result of extensive timber exploitation. The method improves the climate signal in the two subregional chronologies, particularly in the more disturbed western sites. Our application of this method demonstrates that it is possible to minimise the effects of disturbance in tree-ring width chronologies to enhance the climate signal.
    Print ISSN: 0045-5067
    Electronic ISSN: 1208-6037
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
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  • 3
    Publication Date: 2019-12-02
    Description: Quantifying past climate variation and attributing its causes improves our understanding of the natural variability of the climate system. Tree-ring-based proxies have provided skillful and highly resolved reconstructions of temperature and hydroclimate of the last millennium. However, like all proxies, they are subject to uncertainties arising from varying data quality, coverage, and reconstruction methodology. Previous studies have suggested that biological-based memory processes could cause spectral biases in climate reconstructions. This study determines the effects of such biases on reconstructed temperature variability and the resultant implications for detection and attribution studies. We find that introducing persistent memory, reflecting the spectral properties of tree-ring data, can change the variability of pseudoproxy reconstructions compared to the surrogate climate and resolve certain model–proxy discrepancies. This is especially the case for proxies based on ring-width data. Such memory inflates the difference between the Medieval Climate Anomaly and the Little Ice Age and suppresses and extends the cooling in response to volcanic eruptions. When accounting for memory effects, climate model data can reproduce long-term cooling after volcanic eruptions, as seen in proxy reconstructions. Results of detection and attribution studies show that signals in reconstructions as well as residual unforced variability are consistent with those in climate models when the model fingerprints are adjusted to reflect autoregressive memory as found in tree rings.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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