Jianning Le

Reconstructing paleoenvironment by transfer function: Model evaluation with simulated data

Abstract This study examines Imbrie and Kipps transfer function method (IKM) of estimating past sea surface temperature (SST) using simulated biological species abundance data ( Imbrie and Kipp, 1971 ). We test the effects on SST estimation of (1) the number of factors in calibration, (2) regression types, (3) counting errors, (4) calibration ranges, and (5) sub-surface species. When the number of factors is too small, the residuals of SST estimates show highly cyclic patterns in full range calibration, and the IKM largely overestimates SST at low temperature range and underestimates SST at high temperature range. The simulations also demonstrate that curvilinear equations are more sensitive to noise associated with faunal counting than linear equations because of the power and crossproduct terms, although curvilinear equations usually achieve a higher accuracy in full range calibrations. The use of a minor factor may greatly increase accuracy in certain regions by accounting for local ecological phenomena. In general, the IKM, if used with caution, is a robust working method as demonstrated by its wide usage thanks to the restraint imposed by regression methodology. The experiments have also shown that regional linear calibrations achieve higher accuracy in the relevant region by overcoming the inadequacy of full range linear equations and the sensitivity of curvilinear equations, provided that the region is sufficient to fully cover past variations in terms of both species abundances and the SST to be estimated. This study also provides a method to evaluate the contribution of individual species to SST estimates in the IKM. One may also quantitatively evaluate the effect on SST estimation of the inclusion of those species that respond to environmental variables other than SST in an equation which is aimed to estimate SST. In such an equation, the variations in other environmental variables will be apparently manifested as changes in SST, the amount of which depends on: (1) the weight of those species on the equation, and (2) the degree of non-analog condition in the sample for which SST is to be estimated.