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Free keywords:
Electrical conductivity - Salinity - Calibration data set - CCA - Weighted averaging partial least squares regression (WA-PLS) - Transfer function - Ostracoda - Near East
DDC:
550 - Earth sciences
Abstract:
Surface sediments, water samples and environmental data from 37 lakes, ponds and streams in Israel were analysed to determine the main variables controlling ostracod species distributions. Multivariate statistical analysis revealed that the greatest amounts of variation in the distribution of the ostracod taxa among the 37 water bodies were explained by the host water δD value (12.9%), water temperature (11.0%), mean January air temperature (10.5%), electrical conductivity (9.5%), and the Mg and NO3 concentrations (7.8 and 7.1%, ion concentrations as % of the anions or cations). A supplementary data set comprising ostracod species composition and electrical conductivity readings for 24 water bodies was available from previous research and was merged with the 37 samples data set to develop an ostracod-based transfer function for the reconstruction of electrical conductivities. A weighted averaging partial least squares regression (WA-PLS) provided the best results with a relatively high coefficient of determination (r 2) between measured and inferred electrical conductivity values of 0.73, a root mean square error of prediction of 0.13 (13.4% of gradient length) and a maximum bias of 0.24 (23.9% of gradient length), as assessed by leave-one-out cross-validation based on 56 water bodies. The application of the EC transfer function onto (sub)fossil ostracod assemblages from Holocene and early to mid Pleistocene lake sediments provided EC values consistent with other proxies and demonstrated that Quaternary ostracod assemblages from subaqueous sediments can now be used to trace the hydrological history of water bodies in the Near East. A better understanding of past hydrological conditions in response to the natural climate variability is crucial in regions that face restricted water resources and rising demands in times of rapid climate and environmental change.
