Mid-Infrared Spectroscopy as a Potential Tool for Reconstructing Lake Salinity

Abstract

Many aquatic ecosystems in Australia are impacted or threatened by salinisation; however, there is a paucity of records detailing the changes in salinity of individual water bodies that extend beyond a few decades. One way to overcome this issue is the use of inference models, which have typically been based on biological proxies. This pilot project investigates the potential for mid-infrared spectroscopy (MIRS) to provide an alternative method of reconstructing past salinity levels in Australian lakes. A small (19 lakes) calibration dataset was used to develop a MIRS-based lake water salinity inference model (measured vs. inferred salinity, based on leave-one-out cross-validation, R 2 = 0.64). This model and a previously published diatom-salinity model were both used to infer salinity levels in Tower Hill Lake in south-eastern Australia, over the last 60 years. Comparisons between these reconstructions and measured salinity data from Tower Hill Lake indicate that salinities inferred by the MIRS model more closely resembled the measured values than those produced using the diatom model, predominantly in terms of the actual values inferred, but also with regard to the trends observed. This supports the hypothesis that MIRS can provide a valuable new tool for reconstructing lake salinity.

Provenance discrimination of fine sediments by mid‐infrared spectroscopy: Calibration and application to fluvial palaeo‐environmental reconstruction

“…Furthermore, all spectral groups are characterized by absorbance peaks in the O to H stretching vibration region 3750 to 3450 cm −1 (Kaufhold et al ., ; Chukanov & Chervonnyi, ) associated with phyllosilicates, kaolinite (Van der Marel & Beutelspacher, ; Madejová, ) and illite (Pironon et al ., ; Palayangoda & Nguyen, ). Quartz SiO 2 related absorbance peaks are observed in the Si to O stretching vibrations at the specific ranges of 1990 cm −1 , 1878 cm −1 , 1040 cm −1 and 800 cm −1 (Mattesson & Herron, ; Bertaux et al ., ; Ramasamy et al ., ; Palayangoda & Nguyen, ; Sivakumar et al ., ; Cunningham et al ., ). The main characteristic absorbance peaks at the end of the mid‐infrared region (702 to 450 cm −1 ), in particular at 540 cm −1 , 650 cm −1 and 700 cm −1 , are influenced by SiO molecular vibrations (Rosén et al ., ) associated with quartz silica (Terra et al ., ).…”

“…Discriminant function 1 shows that discrimination between Rhine and Ill/Vosges samples is influenced by wavenumbers 3722 cm −1 , 3562 cm −1 and 3434 cm −1 , indicative for phyllosilicates such as kaolinite, illite and smectite (Janik et al ., ; Madejová, ; Alaoui et al ., ; Palayangoda & Nguyen, ). Minor coefficients of organic matter at 2874 cm −1 and 1594 cm −1 (Janik et al ., ; McCarty et al ., ; Rosén et al ., ; Reeves III, ; Liu et al ., ), carbonates at 1482 cm −1 and 874 cm −1 (Adamu, ; Palayangoda & Nguyen, ), as well as quartz at 1002 cm −1 (Cunningham et al ., ), also influence the model. Discriminant function 2 shows that discrimination between the Ill and Vosges samples is predominantly influenced by different proportions of phyllosilicates and tectosilicates.…”

“…Although mid‐infrared spectroscopy (MIRS) measurements are more time‐consuming, the spectral information obtained is richer than for NIR measurements and provides more accurate results (Janik et al ., ; Viscarra Rossel et al ., ), in particular for total organic carbon determination (Reeves III et al ., ; Reeves, ; Bellon‐Maurel & McBratney, ). Furthermore, MIRS has been applied successfully to sediment analysis to quantitatively infer mineral contents (Mattesson & Herron, ; Kaufhold et al ., ; Hahn et al ., ), total organic and inorganic carbon contents (Vogel et al ., ; Rosén et al ., ; Hahn et al ., ; Liu et al ., ; Veerasingam & Venkatachalapathy, ), metal contents (Moros et al ., ), organic matter (OM) properties (Alaoui et al ., ) and lake salinity (Cunningham et al ., ). Mid‐infrared spectroscopy was also used to qualitatively determine the origin of suspended sediment (Hillier, ) as well as to classify and quantify source contributions, using chemometric techniques (Poulenard et al ., , ; Evrard et al ., ; Vercruysse & Grabowski, ).…”