QUANTITATIVE ESTIMATION OF SURFACE OCEAN PRODUCTIVITY AND BOTTOM WATER OXYGEN CONCENTRATION USING BENTHIC FORAMINIFERA

Quantitative estimation of surface ocean productivity and bottom water oxygen concentration with benthic foraminifera was attempted using 70 samples from equatorial and North Pacific surface sediments. These sa mples come from a well defined depth range in the ocean, between 2200 and 3200 m, so that depth related factors do not interfere with the es timation. Samples were selected so that foraminifera were well preserv ed in the sediments and temperature and salinity were nearly uniform ( T = 1.5 degrees C; S = 34.6 parts per thousand). The sample set was al so assembled so as to minimize the correlation often seen between surf ace ocean productivity and bottom water oxygen values (r(2) = 0.23 for prediction purposes in this case). This procedure reduced the chances of spurious results due to correlations between the environmental var iables. The samples encompass a range of productivities from about 25 to >300 gC m(-2) yr(-1), and a bottom water oxygen range from 1.8 to 3 .5 ml/L. Benthic foraminiferal assemblages were quantified using the > 62 mu m fraction of the sediments and 46 taxon categories. MANOVA mult ivariate regression was used to project the faunal matrix onto the two environmental dimensions using published values for productivity and bottom water oxygen to calibrate this operation. The success of this r egression was measured with the multivariate r(2) which was 0.98 for t he productivity dimension and 0.96 for the oxygen dimension. These hig h coefficients indicate that both environmental variables are strongly imbedded in the faunal data matrix. Analysis of the beta regression c oefficients shows that the environmental signals are carried by groups of taxa which are consistent with previous work characterizing benthi c foraminiferal responses to productivity and bottom water oxygen. The results of this study suggest that benthic foraminiferal assemblages can be used for quantitative reconstruction of surface ocean productiv ity and bottom water oxygen concentrations if suitable surface sedimen t calibration data sets are developed and appropriate means for detect ing no-analog samples are found.