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Testing the Landscape Reconstruction Algorithm for spatially explicit reconstruction of vegetation in northern Michigan and Wisconsin

Published online by Cambridge University Press:  20 January 2017

Shinya Sugita ,
Tim Parshall ,
Randy Calcote  and
Karen Walker
Shinya Sugita*
Affiliation:
Institute of Ecology, Tallinn University, Uus-Sadama 5, 10120 Tallinn, Estonia
Tim Parshall
Affiliation:
Department of Biology, Westfield State College, 577 Western Avenue, Westfield, MA 01086-1630, USA
Randy Calcote
Affiliation:
Limnological Research Center, University of Minnesota, 219 Pillsbury Hall, 310 Pillsbury Dr. SE, Minneapolis, MN 55455, USA
Karen Walker
Affiliation:
Montana Natural Heritage Program, 1515 East Sixth Ave, Helena, MT 59620-1800, USA
*
*Corresponding author. Fax: +1 372 6199801. E-mail addresses: sugita@tlu.ee (S. Sugita), tparshall@wsc.ma.edu (T. Parshall), calco001@umn.edu (R. Calcote), kwalker@mt.gov (K.Walker).
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Abstract

The Landscape Reconstruction Algorithm (LRA) overcomes some of the fundamental problems in pollen analysis for quantitative reconstruction of vegetation. LRA first uses the REVEALS model to estimate regional vegetation using pollen data from large sites and then the LOVE model to estimate vegetation composition within the relevant source area of pollen (RSAP) at small sites by subtracting the background pollen estimated from the regional vegetation composition. This study tests LRA using training data from forest hollows in northern Michigan (35 sites) and northwestern Wisconsin (43 sites). In northern Michigan, surface pollen from 152-ha and 332-ha lakes is used for REVEALS. Because of the lack of pollen data from large lakes in northwestern Wisconsin, we use pollen from 21 hollows randomly selected from the 43 sites for REVEALS. RSAP indirectly estimated by LRA is comparable to the expected value in each region. A regression analysis and permutation test validate that the LRA-based vegetation reconstruction is significantly more accurate than pollen percentages alone in both regions. Even though the site selection in northwestern Wisconsin is not ideal, the results are robust. The LRA is a significant step forward in quantitative reconstruction of vegetation.

Keywords

Pollen analysisLandscape Reconstruction AlgorithmREVEALSLOVERelevant source area of pollenQuantitative reconstruction of vegetation

Information

Type
Research Article
Information
Quaternary Research , Volume 74 , Issue 2 , September 2010 , pp. 289 - 300
Copyright
University of Washington

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References

Andersen, S.T. The relative pollen productivity and pollen representation of North European trees, and correction factors for tree pollen spectra. Danmarks Geologiske Undersøgelse II, (1970). 99 RÆKKE. No. 96 Google Scholar
Anderson, N.J., Bugmann, H., Dearing, J.A., and Gaillard, M.-J. Linking palaeoenvironmental data and models to understand the past and to predict the future. Trends in Ecology & Evolution 21, (2006). 696–704.Google Scholar
Bradshaw, R.H.W. Quantitative reconstruction of local woodland vegetation using pollen analysis from a small basin in Norfolk, England. Journal of Ecology 69, (1981). 941–955.Google Scholar
Bradshaw, R.H.W., and Webb, T.I.I.I. Relationships between contemporary pollen and vegetation data from Wisconsin and Michigan, USA. Ecology 66, (1985). 721–737.Google Scholar
Broström, A., Sugita, S., and Gaillard, M.-J. Pollen productivity estimates for the reconstruction of past vegetation cover in the cultural landscape of southern Sweden. Holocene 14, (2004). 368–381.Google Scholar
Broström, A., Sugita, S., Gaillard, M.-J., and Pilesjö, P. Estimating spatial scale of pollen dispersal in the cultural landscape of southern Sweden. Holocene 15, (2005). 252–262.CrossRefGoogle Scholar
Broström, A., Nielsen, A.B., Gaillard, M.-J., Hjelle, K., Mazier, F., Binney, H., Bunting, M.J., Fyfe, R., Meltsov, V., Poska, A., Räsänen, S., Soepboer, W., von Stedingk, H., Suutari, H., and Sugita, S. Pollen productive estimates of key European plant taxa for quantitative reconstruction of vegetation: a review. Vegetation History and Archaeobotany 17, (2008). 461–478.Google Scholar
Bunting, M.J., and Middleton, D. Modelling pollen dispersal and deposition using HUMPOL software, including simulating windroses and irregular lakes. Review of Palaeobotany and Palynology 134, (2005). 185–196.Google Scholar
Bunting, M.J., Gaillard, M.J., Sugita, S., Middleton, R., and Broström, A. Vegetation structure and pollen source area. Holocene 14, (2004). 651–660.Google Scholar
Bunting, M.J., Armitage, R., Binney, H.A., and Waller, M. Estimates of relative pollen productivity and relevant source area of pollen for major tree taxa in two Norfolk (UK) woodlands. Holocene 15, (2005). 459–465.Google Scholar
Bunting, M.J., Twiddle, C.L., and Middleton, R. Reconstructing past vegetation in mountain areas from pollen data: application of pollen dispersal and deposition. Palaeogeography, Palaeoclimatology, Palaeoecology 259, (2008). 77–91.Google Scholar
Calcote, R. Pollen source area and pollen productivity: evidence from forest hollows. Journal of Ecology 83, (1995). 591–602.Google Scholar
Calcote, R. Identifying forest stand types using pollen from forest hollows. Holocene 8, (1998). 423–432.Google Scholar
Davis, M.B. On the theory of pollen analysis. American Journal of Science 261, (1963). 897–912.Google Scholar
Davis, M.B. Palynology after Y2K — understanding the source area of pollen in sediments. Annual Review of Earth and Planetary Sciences 28, (2000). 1–18.Google Scholar
Davis, J.C. Statistics and Data Analysis in Geology. 3rd Edition (2002). John Wiley & Sons, New York.Google Scholar
Davis, M.B., Sugita, S., Calcote, R.R., Ferrari, J.B., and Frelich, L.E. Historical development of alternative communities in a hemlock-hardwood forest in northern Michigan, USA. Edwards, P.J., May, R., and Webb, N.R. Large-scale Ecology and Conservation Biology. (1994). Blackwell Scientific Publications, Oxford. 19–39.Google Scholar
Davis, M.B., Calcote, R.R., Sugita, S., and Takahara, H. Patchy invasion and the origin of a hemlock-hardwood forest mosaic. Ecology 79, (1998). 2641–2659.Google Scholar
Dilworth, J.R., and Bell, J.F. Variable Probability Sampling — Variable Plot and Three-P. (1982). Oregon State University Book Stores Inc., Corvallis.Google Scholar
Duffin, K., and Bunting, M.J. Relative pollen productivity and fall speed estimates for southern African savanna taxa. Vegetation History and Archaeobotany 17, (2008). 507–525.Google Scholar
Efron, B., and Tibshirani, R.J. An Introduction to the Bootstrap. (1998). Chapman & Hall/CRC, Boca Raton.Google Scholar
Faegri, K., and Iversen, J. Textbook of Pollen Analysis. (1989). John Wiley & Sons, Chichester.Google Scholar
Gaillard, M.-J., Sugita, S., Bunting, M.J., Middleton, R., Broström, A., Caseldine, C., Giesecke, T., Hellman, S.E.V., Hicks, S., Hjelle, K., Langdon, C., Nielsen, A.B., Poska, A., von Stedingk, H., and Veski, S. The use of modeling and simulation approach in reconstructing past landscapes from fossil pollen data: a review and results from the POLLANDCAL network. Vegetation History and Archaeobotany 17, (2008). 419–444.Google Scholar
Gaillard, M.-J., Sugita, S., Mazier, F., Kaplan, J.O., Trodman, A.-K., Broström, A., Hickler, T., Kjellström, E., Kuneš, P., Olofsson, J., Smith, B., and Strandberg, G. Holocene land-cover reconstruction for studies on land cover-climate feedbacks. Climate of the Past Discussions 6, (2010). 307–346.Google Scholar
Hellman, S., Gaillard, M.-J., Broström, A., and Sugita, S. The REVEALS model, a new tool to estimate past regional plant abundance from pollen data in large lakes: validation in southern Sweden. Journal of Quaternary Science 23, (2008). 21–42.Google Scholar
Hellman, S.E.V., Gaillard, M.-J., Broström, A., and Sugita, S. Effects of the sampling design and selection of parameter values on pollen-based quantitative reconstructions of regional vegetation: a case study in southern Sweden using the REVEALS model. Vegetation History and Archaeobotany 17, (2008). 445–459.Google Scholar
Hellman, S., Bunting, M.J., and Gaillard, M.-J. Relevant source area of pollen in patchy cultural landscapes and signals of anthropogenic landscape disturbance in the pollen record: a simulation approach. Review of Palaeobotany and Palynology 153, (2009). 245–258.CrossRefGoogle Scholar
Hellman, S., Gaillard, M.-J., Bunting, J.M., and Mazier, F. Estimating the relevant source area of pollen in the past cultural landscapes of southern Sweden — a forward modelling approach. Review of Palaeobotany and Palynology 153, (2009). 259–271.Google Scholar
Hickler, T., Smith, B., Sykes, M.T., Davis, M.B., Sugita, S., and Walker, K. Using a generalized vegetation model to simulate vegetation dynamics in northeastern USA. Ecology 85, (2004). 519–530.Google Scholar
Hicks, S. The use of annual arboreal pollen deposition values for delimiting tree-lines in the landscape and exploring models of pollen dispersal. Review of Palaeobotany and Palynology 117, (2001). 1–29.Google Scholar
Hjelle, K.L. Herb pollen representation in surface moss samples from mown meadows and pastures in western Norway. Vegetation History and Archaeobotany 7, (1998). 79–96.CrossRefGoogle Scholar
Huusko, A., and Hicks, S. Conifer pollen abundance provides a proxy for summer temperature: evidence from the latitudinal forest limit in Finland. Journal of Quaternary Science 24, (2009). 522–528.Google Scholar
Jackson, S.T., and Williams, J.W. Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow?. Annual Review of Earth and Planetary Sciences 32, (2004). 495–537.Google Scholar
Jackson, S.T., Futyma, R.P., and Wilcox, D.A. A paleoecological test of a classical hydrosere in the Lake Michigan dunes. Ecology 69, (1988). 928–936.Google Scholar
Jacobson, G.L. Jr., and Bradshaw, R.H.W. The selection of sites for paleovegetational studies. Quaternary Research 16, (1981). 80–96.CrossRefGoogle Scholar
Janssen, C.R. A post-glacial pollen diagram from a small Typha swamp in northwestern Minnesota, interpreted from pollen indicators and surface samples. Ecological Monographs 37, (1967). 145–172.Google Scholar
Janssen, C.R. The palaeoecology of plant communities in the Dommel Valley, North Brabant, Netherlands. Journal of Ecology 60, (1972). 411–437.Google Scholar
Janssen, C.R. Local and regional pollen deposition. Birks, H.J.B., and West, R.G. Quaternary Plant Ecology. (1973). Blackwell Scientific Publications, Oxford. 30–43.Google Scholar
Mazier, F., Brostöm, A., Sugita, S., Vittoz, P., Gaillard, M.-J., and Buttler, A. Pollen productivity estimates and relevant source area for selected plant taxa in a pasture woodland of Jura Mountains (Switzerland). Vegetation History and Archaeobotany 17, (2008). 479–496.Google Scholar
Middleton, R., and Bunting, M.J. MOSAIC v1.1: landscape scenario creation software for simulation of pollen dispersal and deposition. Review of Palaeobotany and Palynology 132, (2004). 61–66.Google Scholar
Mossiman, J.E. Statistical methods for the pollen analyst: multinomial and negative multinomial techniques. Kummel, B., and Raup, D. Handbook of Paleontological Techniques. (1965). W.H. Freeman, San Francisco/London. 636–675.Google Scholar
Nielsen, A.B. Modelling pollen sedimentation in Danish lakes around AD 1800 — an attempt to validate the POLLSCAPE model. Journal of Biogeography 31, (2004). 1693–1709.Google Scholar
Nielsen, A.B., and Sugita, S. Estimating relevant source area of pollen for small Danish lakes around AD 1800. Holocene 15, (2005). 1006–1020.Google Scholar
Overpeck, J.T., Webb, T., and Prentice, I.C. Quantitative interpretation of fossil pollen spectra: dissimilarity coefficients and the method of modern analogs. Quaternary Research 23, (1985). 87–108.Google Scholar
Parshall, T. Late Holocene stand-scale invasion by hemlock (Tsuga canadensis) at its western range limit. Ecology 83, (2002). 1386–1398.Google Scholar
Parshall, T., and Calcote, R. Effect of pollen from regional vegetation on stand-scale forest reconstruction. Holocene 11, (2001). 81–87.Google Scholar
Pastor, J., and Broschart, M. The spatial pattern of a northern conifer-hardwood landscape. Landscape Ecology 4, (1990). 55–68.Google Scholar
Prentice, I.C. Multidimensional scaling as a research tool in Quaternary palynology: a review of theory and methods. Review of Palaeobotany and Palynology 31, (1980). 71–104.Google Scholar
Prentice, I.C. Pollen representation, source area, and basin size: toward a unified theory of pollen analysis. Quaternary Research 23, (1985). 76–86.Google Scholar
Prentice, I.C. Records of vegetation in time and space: the principles of pollen analysis. Huntley, B., Webb, T. III Vegetation History. (1988). Kluwer Academic Publishers, Dordrecht. 17–42.Google Scholar
Prentice, I.C., and Jolly, D. Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa. Journal of Biogeography 27, (2000). 507–519.CrossRefGoogle Scholar
Prentice, I.C., and Parsons, R.W. Maximum likelihood linear calibration of pollen spectra in terms of forest composition. Biometrics 39, (1983). 1051–1057.Google Scholar
Prentice, I.C., Webb, T. III Pollen percentages, tree abundances and the Fagerlind effect. Journal of Quaternary Science 1, (1986). 35–43.Google Scholar
Press, W.H., Teukolsky, S.A., Vetterling, W.T., and Flannery, B.P. Numerical Recipes in C: The Art of Scientific Computing. (1992). Cambridge University Press, New York.Google Scholar
Räsänen, S., Suutari, H., and Nielsen, A.B. A step further towards quantitative reconstruction of past vegetation in Fennoscandian boreal forests: pollen productivity estimates for six dominant taxa. Review of Palaeobotany and Palynology 146, (2007). 208–220.CrossRefGoogle Scholar
Richie, J.C., and Yarranton, G.A. The late-Quaternary history of the boreal forest of central Canada, based on standard pollen stratigraphy and principal component analysis. Journal of Ecology 66, (1978). 199–212.Google Scholar
Siegel, S., Castellan, N.J. Jr. Nonparametric Statistics for the Behavioral Sciences. (1988). McGraw-Hill Book Company, New York.Google Scholar
Soepboer, W., Sugita, S., Lotter, A.F., van Leeuwen, J.F.N., and van der Knaap, W.O. Pollen productivity estimates for quantitative reconstruction of vegetation cover on the Swiss Plateau. Holocene 17, (2007). 65–78.Google Scholar
Soepboer, W., Vervoort, J.M., Sugita, S., and Lotter, A.F. Evaluating Swiss pollen productivity estimates using a simulation approach. Vegetation History and Archaeobotany 17, (2008). 497–506.Google Scholar
Soepboer, W., Sugita, S., and Lotter, A.F. Regional vegetation-cover changes on the Swiss Plateau during the past two millennia: a pollen-based reconstrcution using the REVEALS model. Quaternary Science Reviews 29, (2010). 472–483.Google Scholar
Sokal, R.R., and Rohlf, F.J. Biometry. 2nd Edition (1981). W.H. Freeman and Company, New York.Google Scholar
Sugita, S. A model of pollen source area for an entire lake surface. Quaternary Research 39, (1993). 239–244.Google Scholar
Sugita, S. Pollen representation of vegetation in Quaternary sediments: theory and method in patchy vegetation. Journal of Ecology 82, (1994). 881–897.Google Scholar
Sugita, S. Modelling pollen representation of vegetation. Palaeoclimate Research, Academy of Sciences and Literature, Mainz 27, (1998). 1–15.Google Scholar
Sugita, S. Theory of quantitative reconstruction of vegetation. I: pollen from large sites REVEALS regional vegetation. Holocene 17, (2007). 229–241.Google Scholar
Sugita, S. Theory of quantitative reconstruction of vegetation. II: all you need is LOVE. Holocene 17, (2007). 243–257.Google Scholar
Sugita, S. POLLSCAPE Model. Elias, S.A. Encyclopedia of Quaternary Science. (2007). Elsevier, Amsterdam. 2561–2570.Google Scholar
Sugita, S., MacDonald, G.M., and Larsen, C.P.S. Reconstruction of fire disturbance and forest succession from fossil pollen in lake sediments: potential and limitations. Clark, J.S., Cachier, H., Goldammer, J.G., and Stocks, B. Sediment Records of Biomass Burning and Global Change. (1997). Springer, Berlin. 387–412.Google Scholar
Sugita, S., Gaillard, M.-J., and Broström, A. Landscape openness and pollen records: a simulation approach. Holocene 9, (1999). 409–421.Google Scholar
Sugita, S., Parshall, T., and Calcote, R. Detecting differences in vegetation among paired sites using pollen records. Holocene 16, (2006). 1123–1135.Google Scholar
Sugita, S., Gaillard, M.-J., Hellman, S.E.V., and Broström, A. Model-based reconstruction of vegetation and landscape using fossil pollen. Posluschny, A., Lambers, K., and Herzog, I. Layers of Perception: Proceedings of the 35th International Conference on Computer Applications and Quantitative Methods in Archaeology (CAA), Berlin, Germany, April 2–6, 2007. (2008). Dr. Rudolf Habelt GmbH, Bonn. 385–391.Google Scholar
Sugita, S., Hicks, S., and Sormunen, H. Absolute pollen productivity and pollen-vegetation relationships in northern Finland. Journal of Quaternary Science 25, (2010). 724–736.Google Scholar
von Stedingk, H., Fyfe, R.M., and Allard, A. Pollen productivity estimates from the forest-tundra ecotone in west-central Sweden: implications for vegetation reconstruction at the limit of the boreal forest. Holocene 18, (2008). 323–332.Google Scholar
Wahl, E.R. A general framework for determining cutoff values to select pollen analogs with dissimilarity metrics in the modern analog technique. Review of Palaeobotany and Palynology 128, (2004). 263–280.Google Scholar
Webb, T.I.I.I., Howe, S.E., Bradshaw, R.H.W., and Heide, K.M. Estimating plant abundances from pollen percentages: the use of regression analysis. Review of Palaeobotany and Palynology 34, (1981). 269–300.Google Scholar