Skip to main content
SpringerLink
Log in

Extracting a Common Signal in Tree Ring Widths with a Semi-parametric Bayesian Hierarchical Model

  • Published:
Journal of Agricultural, Biological and Environmental Statistics Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  • Barefoot, A., Woodhouse, L., Hafley, W., and Wilson, E. (1974). Developing a dendrochronology for Winchester England. Journal of the Institute of Wood Science, 6:34–40.

    Google Scholar 

  • Berliner, L., Wikle, C., Cressie, N (2000). Long-lead prediction of Pacific SSTs via Bayesian Dynamic Modeling. J. Climate, 13:3953–3968.

    Article  Google Scholar 

  • Berliner, L.M. (2011). Discussion of: A statistical analysis of multiple temperature proxies : Are reconstructions of surface temperatures over the last 1000 years reliable ? Annals of Applied Statistics, 5(1):45–46.

    Article  MathSciNet  MATH  Google Scholar 

  • Boreux, J.-J., Naveau, P., Guin, O., Perreault, L., and Bernier, J. (2009). Extracting a common high frequency signal from Northern Quebec black spruce tree-rings with a Bayesian hierarchical model. Climate of the Past. 5(4):607–613.

    Article  Google Scholar 

  • Buckley, B. (2009). Encyclopedia of Paleoclimatology and Ancient Environments. Encyclopedia of Earth Sciences Series, chapter Dating, dendrochronology. Dordrecht, Netherlands: Springer, 2009.

    Google Scholar 

  • Christiansen, B., Schmith, T., Thejll, P., and Surrogate, A., (2009). Ensemble Study of Climate Reconstruction Methods: Stochasticity and Robustness. J. Climate, 22:951–976.

    Article  Google Scholar 

  • Cook, E., (1990). Methods of Dendrochronology: Applications in the Environmental Sciences, chapter A conceptual linear aggregate model for tree rings, pages 98-104. Kluwer Academic Publ., Dordrecht.

    Book  Google Scholar 

  • Cook, E., and Kairikukstis, L. (1990). Methods of dendrochronology : applications in the environmental sciences / edited by E.R. Cook and L.A. Kairiukstis. Kluwer Academic Publishers, Dordrecht, Netherlands, Boston.

  • Cook, E., and Peters., K., (1981). The smoothing spline : a new approach to standardizing forest interior Tree-Ring Width series for dendroclimatic studies, Tree-ring Bulletin, 41:45–53.

    Google Scholar 

  • Cook, E. R., Briffa, K. R., Shiyatov, S., and Mazepa, V. (1990). Treering standardization and growth-trend estimation, in Methods of Dendrochronology: Applications in the Environmental Sciences, edited by E. R. Cook and L. A. Kairiukstis. Kluwer Acad.

  • Cook, E. R., Meko, M. D., Stahle, D. W., and Cleaveland, M. K. (1999). Drought reconstructions for the continental United States. J. Clim, 12:145–1162.

    Google Scholar 

  • Craigmile, P., and Rajaratnam, B. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):88–90, 5.

    Article  MathSciNet  MATH  Google Scholar 

  • Cressie, N., and Tingley, M. P. (2010). Comment: Hierarchical statistical modeling for paleoclimate reconstruction. Journal of the American Statistical Association, 105(491):895–900.

    Article  MathSciNet  Google Scholar 

  • Cressie, N., and Wikle, C. (2011). Statistics for Spatio-Temporal Data. Wiley.

  • Davis, R. A., and Liu, J. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Annals of Applied Statistics, 5(1):52–55.

    Article  MathSciNet  MATH  Google Scholar 

  • de Boor, C. (1978). A practical Guide to Splines. Applied Mathematical Sciences.

  • Douglass, A. (1920). Evidence of climatic effects in the annual rings of trees. Ecology, 1:24–32.

    Article  Google Scholar 

  • Douglass, A. (1936). Climatic Cycles and Tree-growth. Carnegie Institution of Washington publication, 289(3).

  • Esper, J., Schweingruber, F. H., and Winiger, M, (2002). 1300 years of climatic history for Western Central Asia inferred from tree-rings. The Holocene, 12:267–277.

    Article  Google Scholar 

  • Eubank, R. (1999). Nonparametric regression and spline smoothing. Marcel Dekker.

  • Evans, M., Reichert, B., Kaplan, A., Anchukaitis, K., Vaganov, E., Hughes, M., and Cane. M. (2006) A forward modeling approach to paleoclimatic interpretation of tree-ring data. J. Geophys. Res, 111.

  • Evans, M.,Tolwinski-Ward, S., Thompson, D., and Anchukaitis, K. (2013). Application of proxy system modeling in high resolution paleoclimatology. Quaternary Science Reviews, 76:6–28.

    Article  Google Scholar 

  • Fan, J., and Gijbels, I. (1996). Local Polynomial Modelling and its Applications. Chapman and Hall.

  • Fang, K., Gou, X., Peters, K., Li, J., and Zhang, F. (2010). Removing biological trends from tree-ring series: testing modified Hugershoff curves. Tree-ring research, 66(1):51–59.

    Article  Google Scholar 

  • Fritts, H., Mosimann, J., and Bottorff, C., (1969). A Revised Computer Program for standardizing Tree-Ring Series. Tree-Ring Bulletin, 29:15–20.

    Google Scholar 

  • Gavin A. Schmidt, Mann, M.E., and Rutherford, S. D. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Annals of Applied Statistics, 5(1):65–70.

    Article  MathSciNet  MATH  Google Scholar 

  • Gelman, A., Carlin, J., Stern, H., and Rubin, D. (2003) Bayesian Data Analysis. Chapman and Hall, 2nd edition.

  • Gornitz, V., editor (2009). Encyclopedia of Paleoclimatology and Ancient Environments. Encyclopedia of Earth Sciences Series. Dordrecht, Netherlands: Springer.

    Google Scholar 

  • Guiot, J. (1987). Methods of dendrochronology - 1, chapter Standardization and selection of the chronologies by the ARMA analysis. International Institute for Applied Systems Analysis, Laxenburg, Austria and Polish Academy of Sciences-System Research Insti- tute, Warsaw, Poland.

  • Haran, M., and Urban, N, M, (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Annals of Applied Statistics, 5(1):61–64.

    Article  MathSciNet  MATH  Google Scholar 

  • Haslett, J., Salter-Townshend, M., Wilson, S; P., Bhattacharya, S., Whiley, M., Allen, J. R. M., Huntley, B., and Mitchell, J. F. G. (2006). Bayesian palaeoclimate reconstruction. J. R. Statist. Soc. A, 169, Part 3, pp.(3):1–36.

  • Hastie, T., and Tibshirani, R. (1990) Generalized additive models. Chapman and Hall, London.

    MATH  Google Scholar 

  • Hastie, T., and Tibshirani, R., (2000). Bayesian Backfitting. Statistical Science, 15(3):196-223.

    Article  MathSciNet  MATH  Google Scholar 

  • Holmström, L. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):71–75.

    Article  MathSciNet  MATH  Google Scholar 

  • Hooten, M., and Wikle, C. (2007). Shifts in the spatio-temporal growth dynamics of shortleaf pine. Environmental and Ecological Statistics, 14(3):207–227.

    Article  MathSciNet  Google Scholar 

  • Kaplan, A. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):47–51.

    Article  MathSciNet  MATH  Google Scholar 

  • Kimeldorf, G., and Wahba, G. (1970). A correspondence between Bayesian estimation of stochastic processes and smoothing by splines. The Annals of Mathematical Statistics, 41:495–502.

    Article  MathSciNet  MATH  Google Scholar 

  • Li, B., Nychka, D. W., and Ammann, C. M. (2010a). Rejoinder: Hierarchical statistical modeling for paleoclimate reconstruction. Journal of the American Statistical Associa-ion, 105(491):910–911.

    Article  MATH  Google Scholar 

  • Li, B., Nychka, D. W., and Ammann, C. M. (2010b). The value of multiproxy reconstruction of past climate. Journal of the American Statistical Association, 105(491):883–895.

    Article  MathSciNet  MATH  Google Scholar 

  • McIntyre, S., and McKitrick, R. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Annals of Applied Statistics, 5(1):56–60.

    Article  MathSciNet  MATH  Google Scholar 

  • McShane, B. B., and Wyner, A. J. (2011a). Rejoinder of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Annals of Applied Statistics, 5(1):99–123.

    Article  MathSciNet  MATH  Google Scholar 

  • McShane, B. B., and Wyner, A. J.,(2011b). A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?. Annals of Applied Statistics, 5(1):5–44.

    Article  MathSciNet  MATH  Google Scholar 

  • Melvin, T.M., and Briffa, K.R., (2008). A “signal-free” approach to dendroclimatic standardisation. Dendrochronologia, 26:71–86.

    Article  Google Scholar 

  • Nicault, A., Guiot, J., Edouard, J., and Brewer, S., (2010). Preserving long-term fluctuations in standardisation of tree-ring series by the adaptative regional growth curve (ARGC). Dendrochronologia, 28(1):1–12s.

    Article  Google Scholar 

  • Nicault, A., Rathgeber, C., Tessier, L., and Thomas, A., (2001).Observations sur la mise en place du cerne chez le pin d’Alep (Pinus halepensis Mill.) : confrontation entre les mesures de croissance radiale, de densité et les facteurs climatiques. Annals of forest science, 58:769–784.

    Article  Google Scholar 

  • Nychka, D., and Li, B., (2011). Spurious predictions with random time series: The Lasso in the context of paleoclimatic reconstructions. Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):80–82.

    Article  MathSciNet  MATH  Google Scholar 

  • Reinsch, C., (1967). Smoothing by spline functions. Numer. Math., 10:138–177.

    Article  MathSciNet  MATH  Google Scholar 

  • Rougier, J., (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1) 96–98.

    Article  MathSciNet  MATH  Google Scholar 

  • Sahu, S. K., Gelfand, A. E., and Holland, D. M. (2007). High-resolution space-time ozone modeling for assessing trends. Journal of the American Statistical Association, pages 1–14.

  • Schliep, E., Cooley, D., Sain, S.R., Hoeting, J.A. (2010). A Comparison Study of Extreme Precipitation from Six Different Regional Climate Models via Spatial Hierarchical Modeling. Extremes, 13:219–239.

    Article  MathSciNet  MATH  Google Scholar 

  • Smerdon, J. E. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):76–79.

    Article  MathSciNet  MATH  Google Scholar 

  • Smith, R. L. (2010a). Comment: Hierarchical statistical modeling for paleoclimate reconstruction. Journal of the American Statistical Association, 105(491):905–910.

    Article  MathSciNet  Google Scholar 

  • Smith, R. L. (2010b). Understanding sensitivities in paleoclimatic reconstructions. Annals of Applied Statistics.

  • Tebaldi, C., Smith R. L., and Sanso, B, (2010). BAYESIAN STATISTICS 9, chapter Characterizing Uncertainty of Future Climate Change Projections Using Hierarchical Bayesian Models. Oxford University Press,. Oxford University Press.

    Google Scholar 

  • Tingley, M.P., Craigmile, P.F., Haran, M., LI, B., Mannshardt, E., and Rajaratnam, B. (2012). Piecing together the past: statistical insights into paleoclimatic reconstructions. Quaternary Science Reviews, pp. 35:1–22.

  • Tingley, M. P., and Huybers, P. (2010). A Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time. Part 1: Development and applications to paleoclimate reconstruction problems. Journal of Climate, 23(10):2759–2781.

    Article  Google Scholar 

  • Tingley, M.P., and Huybers, P. (2013). Recent temperature extremes at high northern latitudes unprecedented in the past 600 years. Nature, 496:201–205.

    Article  Google Scholar 

  • Tingley, M. P. (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):83–87.

    Article  MathSciNet  MATH  Google Scholar 

  • Wahba, G., (1978). Improper priors, spline smoothing and the problem of guarding against model errors in regression. Journal of the Royal Statistical Society, 40(3):364–372.

    MathSciNet  MATH  Google Scholar 

  • Wahl, E., Schoelzel, C., Williams, J., and Tigrek, S. (2010). Comment: Hierarchical statistical modeling for paleoclimate reconstruction. Journal of the American Statistical Association, 105(491):900–905.

    Article  MathSciNet  MATH  Google Scholar 

  • Wahl, E. R., and Ammann, C. M., (2011). Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable? Annals of Applied Statistics, 5(1):91–95.

    Article  MathSciNet  MATH  Google Scholar 

  • Wand, M., and Jones, M., (1995). Kernel smoothing. Chapman and Hall, 1995.

  • Werner, J. P., and Tingley, M. P., (2015). Technical Note: Probabilistically constraining proxy age-depth models within a Bayesian hierarchical reconstruction model. Climate of the Past, 11:533–545s.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratoire de Sciences du Climat et de l’Environnement, IPSL-CNRS, Gif-sur-Yvette, France

    Ophélie Guin & Philippe Naveau

  2. University of Liège, Arlon, Belgium

    Jean-Jacques Boreux

Authors
  1. Ophélie Guin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Philippe Naveau
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jean-Jacques Boreux
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ophélie Guin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guin, O., Naveau, P. & Boreux, JJ. Extracting a Common Signal in Tree Ring Widths with a Semi-parametric Bayesian Hierarchical Model. JABES 23, 550–565 (2018). https://doi.org/10.1007/s13253-018-0330-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13253-018-0330-0

Keywords

Search

Navigation