Multiscale analysis of palynological records: new possibilities

• Published in: Community ecology 2006-01, Vol.7 (1), p.53-67
• Main Authors: Orlóci, L., Pillar, V. D., Anand, M.
• Format: Article
• Language: English
• Subjects: Acceleration; air temperature; Climate change; Composition; Correlogram; Crater lakes; ecology; Formation; global warming; Paleoclimatology; Palynology; Pattern; Pollen; Sediments; semiarid zones; Shrubs; Spectra; Stability; Statistics; Synchronicity; Taxa; Temperature; terminology; time series analysis; Trajectory; Vegetation; Velocity; Vostok
• ISSN: 1585-8553; 1588-2756
• DOI: 10.1556/ComEc.7.2006.1.6

Palynological records helped to illuminate the past, but we show the take can be made much sharper when statistical analysis recognises the records' scale dependence. The latter is an unavoidable consequence of site selection, sediment sampling, and the samples' arrangement into time series by dating. To make provision for this in statistical analysis, scale has to be incorporated as one of the intrinsic variables. But by incorporating scale, the analysis will render the outcome not to be a single conclusion, the usual case in conventional statistics, but a multitude of conclusions each regarding the same set of response and forcing variables and each as valid at its own scale as any of the other conclusions at theirs. Thus, the central question for a usable Statistics is this: how to incorporate scale into the analysis and still have a unique conclusion. We address the methodological aspects and illustrate them by worked examples. We use 14 sites scattered across the globe. Interestingly, the analysis of these brought forth hitherto hidden aspects of the temporal synchronicity of change in palynological composition and concomitant atmospheric temperature oscillations that should greatly interest Ecology, as one critique put it, in the age of Global Change. The examples testify to a conceptual advance in laying open a very basic principle: the synchronicity's statistically strong formation specificity, dominantly positive (in frequency terms) for climate warming at sites in the currently humid, micro- and mesothermal zones, and negative in the currently arid and semi-arid zones. Our paper begins with an introduction to the terminology of multiscale analysis in Ecology, followed by data sources, the method we call canonical serial scaling, and objectives. A detailed discussion of data properties with special attention to error sources in palynology is provided. The method components discussed include the scalars of compositional transition and synchronicity, error dampening, stabilisation of the synchronicity scalar and its sign distribution, analysis of time shifted series, the use of deviation graphs, and pointers to help detect hotspots and other characteristic points of change on the time axis.