Abstract
ABSTRACTWe present an expanded training set of salt‐marsh foraminifera for reconstructing Holocene relative sea‐level change from 12 sites in New Jersey that represent varied physiographic environments. Seven groups of foraminifera are recognized, including four high‐ or transitional‐marsh assemblages and a low‐salinity assemblage. A weighted‐averaging transfer function trained on this dataset was applied to a dated core from Barnegat Bay to reconstruct sea level with uncertainties of ± 14% of tidal range. We evaluate the transfer function using seven tests. (1) Leave‐one‐site‐out cross validation suggests that training sets of salt‐marsh foraminifera are robust to spatial autocorrelation caused by sampling along transects. (2) Segment‐wise analysis shows that the transfer function performs best at densely sampled elevations and overall estimates of model performance are over optimistic. (3) Dissimilarity and (4) non‐metric multi‐dimensional scaling evaluated the analogy between modern and core samples. The closest modern analogues for core samples were drawn from six sites demonstrating the necessity of a multi‐site training set. (5) Goodness‐of‐fit statistics assessed the validity of reconstructions. (6) The transfer function failed a test of significance because of the unusual properties of some cores selected for sea‐level reconstruction. (7) Agreement between reconstructed sea level and tide‐gauge measurements demonstrates the transfer function's utility. Copyright © 2013 John Wiley & Sons, Ltd.
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