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References

The methods dplPy implements come from the published dendrochronology literature and from four established software tools. The works below are those cited across the dplPy source; each function's docstring names the specific reference(s) behind it, and the API Reference surfaces those docstrings directly.

Fundamentals

Two foundational texts underpin the field and the methods dplPy implements:

  • Fritts, H.C. (1976). Tree Rings and Climate. Academic Press, New York.
  • Cook, E.R., Kairiukstis, L.A. (eds.) (1990). Methods of Dendrochronology: Applications in the Environmental Sciences. Springer, Dordrecht, Netherlands.

Software heritage

  • DPL — Holmes, R.L. (1983). Dendrochronology Program Library. Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ, USA. (the original FORTRAN library)
  • dplR — Bunn, A.G. (2008). A dendrochronology program library in R (dplR). Dendrochronologia 26(2), 115–124.
    Bunn, A.G. (2010). Statistical and visual crossdating in R using the dplR library. Dendrochronologia 28(4), 251–258.
  • COFECHA — Holmes, R.L. (1983). Computer-assisted quality control in tree-ring dating and measurement. Tree-Ring Bulletin 43, 69–78.
  • ARSTAN — Cook, E.R. (1985). A time series analysis approach to tree ring standardization. PhD dissertation, University of Arizona.
    Cook, E.R., Krusic, P.J., Peters, K., Holmes, R.L. (2017). Program ARSTAN: autoregressive tree-ring standardization program. Tree-Ring Laboratory of Lamont-Doherty Earth Observatory.
  • CRUST — Melvin, T.M., Briffa, K.R. (2014). CRUST: Software for the implementation of Regional Chronology Standardisation: Part 1. Signal-free RCS. Dendrochronologia 32(1), 7–20.
    Melvin, T. M., & Briffa, K. R. (2014). CRUST: Software for the implementation of Regional Chronology Standardisation: Part 2. Further RCS options and recommendations. Dendrochronologia, 32(4), 343–356.

Detrending & standardization

  • Cook, E.R., 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.
  • Cook, E.R., Peters, K. (1997). Calculating unbiased tree-ring indices for the study of climatic and environmental change. The Holocene 7(3), 361–370.
  • Melvin, T.M. (2004). Historical growth rates and changing climatic sensitivity of boreal conifers. PhD thesis, University of East Anglia.
  • Melvin, T.M., Briffa, K.R., Nicolussi, K., Grabner, M. (2007). Time-varying- response smoothing. Dendrochronologia 25(1), 65–69.
  • Melvin, T.M., Briffa, K.R. (2008). A "signal-free" approach to dendroclimatic standardisation. Dendrochronologia 26(2), 71–86.
  • Melvin, T.M., Briffa, K.R. (2014). CRUST: Software for the implementation of Regional Chronology Standardisation: Part 1. Signal-free RCS. Dendrochronologia 32(1), 7–20.
  • Melvin, T. M., & Briffa, K. R. (2014). CRUST: Software for the implementation of Regional Chronology Standardisation: Part 2. Further RCS options and recommendations. Dendrochronologia, 32(4), 343–356.

Canopy disturbance

  • Lorimer, C.G., Frelich, L.E. (1989). A methodology for estimating canopy disturbance frequency and intensity in dense temperate forests. Canadian Journal of Forest Research 19(5), 651–663. (radial-growth averaging)
  • Druckenbrod, D.L., Cook, E.R., Pederson, N., Martin-Benito, D. (2024). Detecting and removing the effects of canopy disturbances from tree-ring chronologies with an age-dependent spline. Dendrochronologia 85, 126195.

Superposed epoch analysis

  • Rao, M.P., Cook, E.R., Cook, B.I., Anchukaitis, K.J., D'Arrigo, R.D., Krusic, P.J., LeGrande, A.N. (2019). A double bootstrap approach to Superposed Epoch Analysis to evaluate response uncertainty. Dendrochronologia 55, 119-124.
  • Adams, J.B., Mann, M.E., Ammann, C.M. (2003). Proxy evidence for an El Nino-like response to volcanic forcing. Nature 426, 274-278. (block bootstrap)

Moving correlation

  • Gershunov, A., Schneider, N., Barnett, T. (2001). Low-frequency modulation of the ENSO-Indian monsoon rainfall relationship: signal or noise? Journal of Climate 14, 2486-2492. (the variability test and the surrogate approach)
  • Gelman, A., Stern, H. (2006). The difference between "significant" and "not significant" is not itself statistically significant. The American Statistician 60(4), 328-331. (why moving_corr shows estimates and uncertainty, not a grid of per-window significance)
  • Zang, C., Biondi, F. (2014). treeclim: an R package for the numerical calibration of proxy-climate relationships. Ecography 38(4), 431-436. (the moving-correlation / moving-response convention)
  • Slutzky, E. (1937). The summation of random causes as the source of cyclic processes. Econometrica 5(2), 105-146. (why overlapping windows manufacture low-frequency wobble)
  • Livezey, R.E., Chen, W.Y. (1983). Statistical field significance and its determination by Monte Carlo techniques. Monthly Weather Review 111(1), 46-59. (the grid-level field-significance test for the season grid)
  • Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B 57(1), 289-300. (the per-season FDR annotation)
  • Crameri, F. (2018). Scientific colour maps. Zenodo, doi:10.5281/zenodo.1243862.
    Crameri, F., Shephard, G.E., Heron, P.J. (2020). The misuse of colour in science communication. Nature Communications 11, 5444. (the perceptually-uniform, colourblind-safe maps used in the grid figures)

Chronology & signal strength

  • Wigley, T.M.L., Briffa, K.R., Jones, P.D. (1984). On the average value of correlated time series, with applications in dendroclimatology and hydrometeorology. Journal of Climate and Applied Meteorology 23, 201–213. (EPS, SSS, SNR)
  • Osborn, T.J., Briffa, K.R., Jones, P.D. (1997). Adjusting variance for sample-size in tree-ring chronologies and other regional-mean timeseries. Dendrochronologia 15, 89–99. (variance stabilization)
  • Cook, E.R., Pederson, N. (2011). Uncertainty, emergence, and statistics in dendrochronology. In: Dendroclimatology (Developments in Paleoenvironmental Research 11), Springer, 77–112. (effective signal, SNR)
  • Frank, D., Esper, J., Cook, E.R. (2006). On Variance Adjustments in Tree-Ring Chronology Development, Tree Rings in Archaeology, Climatology and Ecology (TRACE), 4, 56–66. (variance stabilization)
  • Frank, D., Esper, J., & Cook, E. R. (2007). Adjustment for proxy number and coherence in a large-scale temperature reconstruction. Geophysical Research Letters, 34(16). (variance stabilization)
  • Buras, A. (2017). A comment on the expressed population signal. Dendrochronologia 44, 130–132. (SSS vs EPS)

Crossdating

  • Baillie, M.G.L., Pilcher, J.R. (1973). A simple cross-dating program for tree-ring research. Tree-Ring Bulletin 33, 7–14. (the t statistic)
  • Wigley, T.M.L., Jones, P.D., Briffa, K.R. (1987). Cross-dating methods in dendrochronology. Journal of Archaeological Science 14(1), 51–64.
  • Fowler, A.M., Bridge, M.C. (2017). Empirically-determined statistical significance of the Baillie and Pilcher (1973) t statistic for British Isles oak. Dendrochronologia 42, 51–55.
  • Wilson, R. (2026). Multi-parameter crossdating for sub-fossil and historical samples. Dendrochronologia 96, 126485.
  • Visser, R.M. (2021). On the similarity of tree-ring patterns: Assessing the influence of semi-synchronous growth changes on the Gleichläufigkeitskoeffizient for big tree-ring data sets, Archaeometry, 63(1), 204–215.

Statistics & indices

  • Bunn, A. G., Jansma, E., Korpela, M., Westfall, R. D., & Baldwin, J. (2013). Using simulations and data to evaluate mean sensitivity (ζ) as a useful statistic in dendrochronology. Dendrochronologia, 31(3), 250–254.
  • Biondi, F., Qeadan, F. (2008). Inequality in paleorecords. Ecology 89(4), 1056–1067. (Gini coefficient; mean-sensitivity treatment)

Climate response & reconstruction

  • Cook, E.R., Briffa, K.R., Jones, P.D. (1994). Spatial regression methods in dendroclimatology: a review and comparison of two techniques. International Journal of Climatology 14(4), 379–402. (the OSR / PCR method behind pcreg)
  • Meko, D.M., Touchan, R., Anchukaitis, K.J. (2011). Seascorr: A MATLAB program for identifying the seasonal climate signal in an annual tree-ring time series. Computers & Geosciences 37(9), 1234–1241. (the method behind seascorr)
  • Fritts, H.C., Blasing, T.J., Hayden, B.P., Kutzbach, J.E. (1971). Multivariate techniques for specifying tree-growth and climate relationships and for reconstructing anomalies in paleoclimate. Journal of Applied Meteorology 10(5), 845–864. (the response function behind climate_response)
  • Guiot, J. (1991). The bootstrapped response function. Tree-Ring Bulletin 51, 39–41. (bootstrapping the response-function coefficients and the PVP component criterion)
  • Biondi, F., Waikul, K. (2004). DENDROCLIM2002: A C++ program for statistical calibration of climate signals in tree-ring chronologies. Computers & Geosciences 30(3), 303–311. (the moving/bootstrapped correlation- and response-function program climate_response follows)
  • Dixon, P.M. (2001). Bootstrap resampling. In: The Encyclopedia of Environmetrics, Wiley, New York. (the percentile significance method for the resampling bootstraps)
  • Politis, D.N., Romano, J.P. (1994). The stationary bootstrap. Journal of the American Statistical Association 89(428), 1303–1313. (the boot="stationary" block resampler)
  • Politis, D.N., White, H. (2004). Automatic block-length selection for the dependent bootstrap. Econometric Reviews 23(1), 53–70; with the correction by Patton, A., Politis, D.N., White, H. (2009), Econometric Reviews 28(4), 372–375. (the automatic stationary-bootstrap block length)
  • Percival, D.B., Constantine, W.L.B. (2006). Exact simulation of Gaussian time series from nonparametric spectral estimates with application to bootstrapping. Statistics and Computing 16(1), 25–35. (the exact spectral simulation behind boot="exact")
  • Fritts, H.C. (1976). Tree Rings and Climate. Academic Press. (reduction of error and the verification/validation statistics)
  • Oreskes, N., Shrader-Frechette, K., Belitz, K. (1994). Verification, validation, and confirmation of numerical models in the Earth sciences. Science 263(5147), 641–646. (why dplPy says "validation", not "verification")

Citing dplPy

dplPy is developed by the OpenDendro group. If you use it in published work, please cite the software using its archived Zenodo record, and also cite the specific method reference(s) named in the docstrings of the functions you relied on (e.g. Osborn et al. 1997 and Frank et al. 2006 for variance stabilization, Cook 1985 / ARSTAN for chron_ars).

The software has a concept DOI that always resolves to the latest release:

10.5281/zenodo.22695105

Each release also has its own version DOI on Zenodo, so you can cite the exact version you used. A suggested citation (adjust the version and year to the release you used):

Anchukaitis, K. J., Ale, I., Bunn, A. G., Swetnam, T. L., & Cook, E. R. (2026). dplPy: Dendrochronology Program Library for Python (version 0.7.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.22695105

In BibTeX:

@software{dplpy,
  author  = {Anchukaitis, Kevin J. and Ale, Ifeoluwa and Bunn, Andrew G. and
             Swetnam, Tyson Lee and Cook, Edward R.},
  title   = {dplPy: Dendrochronology Program Library for Python},
  year    = {2026},
  version = {0.7.0},
  doi     = {10.5281/zenodo.22695105},
  url     = {https://opendendro.github.io/dplPy}
}

The repository ships a CITATION.cff, so GitHub's "Cite this repository" button gives the current APA and BibTeX entries automatically, and always reflects the latest authors, version, and DOI.