Geography 607: Quantitative Methods in Paleoecology

Winter 2018

Class is held in Knight Library 41 Fridays, 11:00-1:40

Instructor: Dan Gavin (dgavin@uoregon.edu)
Office: 110 Condon Hall; Phone: 346-5787. 

Office Hours: 9:30 to 11:30 Thursdays, or by appointment, in Condon 110.

Class information and schedule

image to right: a CT-scan of a sediment core reveals sediment density at scales finer than one mm. The overlayed yellow line is a measure of density as shown by the CT number, or Hounsfield unit.

Class resources, organized by week

Please note that PDFs for all readings are available through canvas.uoregon.edu; all other materials are available here.

Quick links to [Week 1: Building site chronologies] [Week 2: Working with stratigraphical data] [Week 3: Peak over thresholds and changepoint detection] [Week 4: Assessing synchrony] [Week 5: Species range limits & times of extinction or immigration] [Week 6: Rates of change, zonation, and paleodiversity] [Week 7: Modern analogue techniques, Analog matching] [Week 8: Ordination and correspondence analysis] [Week 9: Climate transfer functions] [Week 10: Biogeographic analysis, geostatistics, time-slice mapping]

• Readings
  • Background wikipedia: Radiocarbon dating, and Calibration of radiocarbon dates.
  • Blaauw, M., and E. Heegaard. 2012. Estimation of age-depth relationships. Pages 379–413 Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer, Dordrecht.
  • Mathias Trachsel, and Richard J Telford. 2017. All age-depth models are wrong, but are getting better. The Holocene 27:860–869.
• Software
  • Calib: a Web-based and windows application for radiocarbon calibration.
    • Use the Windows program to obtain the complete calibrated distribution of a radiocarbon date.
  • OxCal: Another calibration program, with more advanced options.
  • CLAM: a program for classical fitting of age-depth relationships
    • Modified version of clam for fitting monotonic splines. See this web page.
    • Another modification of depth-age modeling uses a variable measured down-core in the sediment that is expected to vary with the sedimentation rate. For example, sediment may be composed of silt that is deposited rapidly in single large events, and organic matter that accumulates slowly. See Colombaroli and Gavin 2010 and Kelly et al. 2013. Software is in development.
  • Bacon Bayesian age-depth modeling, and the highly-cited paper describing the method.
  • The Bchron package for R provides easy radiocarbon calibration and another Bayesian age-depth modeling method. This Example code does the following:
    • Calibrate a date and obtain the calibrated probability distribution.
    • Develop a mean intensity chronology from a list of radiocarbon dates using a Gaussian Mixture model. Contrast this with simply summing the probability distributions of many radiocarbon dates.
• Introduction to R
  • Read parts 1 and 2 in the Introduction to R
  • Learn by doing: examine and use this short function.

• Case-study presenters: Geoffrey Johnson and Chantel Saban

• Readings. The Dunnette paper is used to illustrate 'superposed epoch analysis'. The Marlon paper is used to illustrate how to quantitatively combine many disparate types of data into a mean series.
• Maher, L. J., O. Heiri, and A. F. Lotter. 2012. Assessment of Uncertainties Associated with Palaeolimnological Laboratory Methods and Microfossil Analysis. Pages 143–166 in H. J. B. Birks, A. F. Lotter, S. Juggins, and J. P. Smol, editors. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer Netherlands, Dordrecht.
• Dunnette, P. V., P. E. Higuera, K. K. McLauchlan, K. M. Derr, C. E. Briles, and M. H. Keefe. 2014. Biogeochemical impacts of wildfires over four millennia in a Rocky Mountain subalpine watershed. New Phytologist 203:900–912.
• Marlon, J. R., P. J. Bartlein, C. Carcaillet, D. G. Gavin, S. P. Harrison, P. E. Higuera, F. Joos, M. J. Power, and I. C. Prentice. 2008. Climate and human influences on global biomass burning over the past two millennia. Nature Geoscience 1:697–702.
• Software. We will not use Tilia or rioja in class this week; this is only an introduction.
• Tilia. For managing and graphing paleontological data and metadata, especially stratigraphic data. You may download the free version and see how data is managed in the spreadsheets and forms. Data on the Neotoma Paleoecology Database is readable by Tilia.
• rioja. R package for plotting stratigraphical data, and for computing climate transfer functions (to be used later in class).
• Code for compositing time series into a mean chronology, as in Marlon et al. (2008). Analysis of the Global Charcoal Database. The R package paleofire performs the same analyses. We will run through the steps of the analysis but not implement it on new data.
• Code for running a superposed epoch analysis. To use this example, download and use this data file series.csv.
• The program PALYHELP.EXE in the INQUA file boutique does not seem to run on modern versions of Windows, but does work on the free program Dosbox. The equations for the functions in this program are in the Maher paper. In general, the INQUA file boutique is out-dated.

• Case-study presenters: Kate Hayes

• Readings
  • Higuera, P. E., D. G. Gavin, P. J. Bartlein, and D. J. Hallett. 2010. Peak detection in sediment-charcoal records: impacts of alternative data analysis methods on fire-history interpretations. International Journal of Wildland Fire 19:996.
  • Graham, R. W., S. Belmecheri, K. Choy, B. J. Culleton, L. J. Davies, D. Froese, P. D. Heintzman, C. Hritz, J. D. Kapp, L. A. Newsom, R. Rawcliffe, É. Saulnier-Talbot, B. Shapiro, Y. Wang, J. W. Williams, and M. J. Wooller. 2016. Timing and causes of mid-Holocene mammoth extinction on St. Paul Island, Alaska. Proceedings of the National Academy of Sciences 113:9310–9314.
• Software
  • CharAnalysis: a program for peak detection in sediment stratigraphies. Requires Matlab.
  • Detecting a change in the mean and/or variance.
    • An overview of the changepoint package.
    • The bcp Bayesian changepoint package is relatively simple to apply and produce an estimate of the probability of a change point at every location along a series. (see manual page for bcp).
    • The cusum function in the qcc quality control R package is designed to detect subtle changes in the mean of a time series.
    • The segmented R package for piecewise fitting of linear models. Here is an example of segmented regression applied to a time series data set. The example includes a method for interpolating to equal time intervals. It uses this .csv data file.

• Case-study presenters: Dan

• Readings
  • Blaauw, M., J. A. Christen, D. Mauquoy, J. van der Plicht, and K. D. Bennett. 2007. Testing the timing of radiocarbon-dated events between proxy archives. The Holocene 17:283–288.
  • Blaauw, M. 2012. Out of tune: the dangers of aligning proxy archives. Quaternary Science Reviews 36:38–49.
  • Gavin, D. G., F. S. Hu, K. Lertzman, and P. Corbett. 2006. Weak climatic control of stand-scale fire history during the late Holocene. Ecology 87:1722–1732.
• Software
  • K1D A desktop program for binary event analysis. R code is also available on the same web page.
  • Splancs an R package for space-time point processes.

• Case-study presenters: Lauren Hendricks (range limits) and Matt Napalitano (immigration)

• Estimating probability of arrival time from a calibration data set (modern pollen data):
  • Herring, E.M., D.G. Gavin, S.Z. Dobrowski, M. Fernandez, and F.S. Hu. 2018. Ecological history of a long-lived conifer in a disjunct population. Journal of Ecology 106:319–332.
• A series of papers on the topic of addressing time of extinction from a series of "sightings" (i.e., dates).
  • The original Poisson model:
    • Solow, A. R. 1993. Inferring extinction from sighting data. Ecology 74:962–964.
  • Revision that emphasizes the most recent intervals between sightings:
    • McInerny, G. J., D. L. Roberts, A. J. Davy, and P. J. Cribb. 2006. Significance of sighting rate in inferring extinction and threat. Conservation Biology 20:562–567.
  • A weighting applied to the time series of dates, so the intervals between the most recent dates influence the extinction estimate more than older dates (GRIWM method):
    • Bradshaw, C. J. A., A. Cooper, C. S. M. Turney, and B. W. Brook. 2012. Robust estimates of extinction time in the geological record. Quaternary Science Reviews 33:14–19.
  • A review of methods applied to simulated data, and introduction of bootstrapped estimates (BRIWM method):
    • Saltré, F., B.W. Brook, M. Rodríguez-Rey, A. Cooper, C. N. Johnson, C.S.M. Turney, and C.J.A. Bradshaw. 2015. Uncertainties in dating constrain model choice for inferring extinction time from fossil records. Quaternary Science Reviews 112:128–137.
• Software
  • Hurdle model example showing the analysis in Herring et al. 2018.
  • There is R code in the supplementary information for the Saltre paper.

• Case-study presenters: Yuan Fang

• Readings
  • pages: 358-365 and 369-372 in: Birks, H. J. B. 2012. Analysis of Stratigraphical Data. Pages 355–378 in H. J. B. Birks, A. F. Lotter, S. Juggins, and J. P. Smol, editors. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer Netherlands, Dordrecht.
  • pages 167-180. Legendre, P., and H. J. B. Birks. 2012. Clustering and Partitioning. Pages 167–200 in H. J. B. Birks, A. F. Lotter, S. Juggins, and J. P. Smol, editors. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer Netherlands, Dordrecht.
  • Colombaroli, D., M. Beckmann, W. O. van der Knaap, P. Curdy, and W. Tinner. 2013. Changes in biodiversity and vegetation composition in the central Swiss Alps during the transition from pristine forest to first farming. Diversity and Distributions 19:157–170.
    • A description of rarefaction.
    • Background: Knaap, W. O. van der. 2009. Estimating pollen diversity from pollen accumulation rates: a method to assess taxonomic richness in the landscape. The Holocene 19:159–163.
• Software
  • rioja: R package for stratigraphic data

• Case-study presenters: Holly and Ross

• Readings
  • Overpeck, J. T., R. S. Webb, and T. Webb. 1992. Mapping eastern North American vegetation change of the past 18 ka: No-analogs and the future. Geology 20:1071–1074.
  • Simpson, G. L. 2012. Analogue Methods in Palaeolimnology. Pages 495–522 in H. J. B. Birks, A. F. Lotter, S. Juggins, and J. P. Smol, editors. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer Netherlands, Dordrecht.
• Software
  • analogue: R package for analogue and weighted averaging for paleoecology.
  • vegan: R package for community ecology

• Case-study presenters: Schyler Reis

• Readings
  • Legendre, P., and H. J. B. Birks. 2012. From Classical to Canonical Ordination. Pages 201–248 in H. J. B. Birks, A. F. Lotter, S. Juggins, and J. P. Smol, editors. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer Netherlands, Dordrecht.
• Software
  • vegan: R package for community ecology

• Case-study presenters: Adrian

• Readings
  • Juggins, S., and H. J. B. Birks. 2012. Quantitative Environmental Reconstructions from Biological Data. Pages 431–494 in H. J. B. Birks, A. F. Lotter, S. Juggins, and J. P. Smol, editors. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques. Springer Netherlands, Dordrecht.
• Software
  • rioja: R package for stratigraphic data

• Case-study presenters: Weicheng and Jamila
• Blois, J. L., J. W. (Jack) Williams, E. C. Grimm, S. T. Jackson, and R. W. Graham. 2011. A methodological framework for assessing and reducing temporal uncertainty in paleovegetation mapping from late-Quaternary pollen records. Quaternary Science Reviews 30:1926–1939.