The G. ruber is a symbiont-bearing mixed layer and oligotrophic species of planktic foraminifera that lives in the upper ~ 30 m of the Ocean water column where the environment is composed of high light availability and low turbidity (Feldmeijer et al., 2014; Mulitza et al., 2003; Gast et al., 2000; Govil et al., 2022). The δ18O of foraminiferal shells captured the temperature and δ18O of seawater at which the oxygen isotope fractionations occurred between the foraminiferal shell and seawater (Emiliani, 1954; Labeyrie et al., 1992). The δ18O of foraminiferal shells also depends on the global ice volume, salinity and change in the evaporation precipitation budget (Hilbrecht & Thierstein, 1996; Govil and Naidu 2010). The G. ruber calcified in the upper 30 m water column and inhaled all the isotopic signatures in the shell (Bé and Tolderlund 1971; Fairbanks et al., 1980). This dependence of foraminiferal shell δ18O on the isotopic composition of palaeo-seawater is utilized to understand the paleoceanographic and paleoclimatic studies to interpret and track past marine conditions (Schiebel and Hemleben 2017). The higher value of δ18OG.ruber in the glacial period represents a dry and colder climate. It further indicates the weak Indian summer monsoon (or strong Indian winter monsoon) and increases the ice volume in the polar areas. In contrast, the lower value in the interglacial period represents a more robust summer monsoon and low salinity in the present study area (Figs. 3 and 4). Previous study from the Japan Sea (East Sea) also reported that the East Asian summer monsoon was most intense during MIS 5e, MIS 7, MIS 9, and MIS 11 (Gallagher et al., 2018). A recent study from the western Arabian Sea up to 172 ka also reported the strong Indian summer monsoon during the inter-glacial periods (Khan et al., 2023). Indian summer monsoon (ISM) variability is driven by a combination of northern hemisphere insolation and ice volume via latent heat distribution from the southern subtropical Indian Ocean (Clemens et al., 2008, 2010). The ISM maxima are linked with Global ice volume minima. On the other hand, the glacial ISM achieves a minimum and starts to rise before the global ice volume reaches its maximum (Zhisheng et al., 2011). The δ18OG.ruber signature from WEIO shows increased sea surface temperature, and precipitations during MIS 11, MIS 5, and MIS 1 show more and similar lower values (Figs. 3 and 4) related to the strong Indian summer monsoon. Thus, it can be further inferred that these interglacial periods have similar solar insolation intensities that concur with the Indian summer monsoon (ISM). Interestingly, the value with more positive excursion during MIS 10 suggests more cooling than MIS 2. However, in mid-MIS 10 and mid-MIS 2, the value becomes lower; it was inferred that there was a sub-cycle of warming during these intense glacial periods in the WEIO, as was mentioned earlier in previous study (Govil et al., 2011). The different cooling patterns and warm sub-cycles in MIS 10 and MIS 2 would be the effect of IOD, equatorial westerly wind and ENSO in the WEIO. However, interestingly, the other two glacial periods, MIS 8, and MIS 6, show a low and different colling pattern than MIS 10 and MIS 2. During MIS 8, colling was increased, but warming signals were attained at a boundary of MIS 8 to 7. Meanwhile, MIS 6 shows an overall colling pattern throughout the period. It may be inferred that MIS 10 and MIS 2 show the intensity of the northeast monsoon (winter), weakening the SWM. More evaporation in MIS 10 and MIS 2 also documents that the evaporation-precipitation budget in the WEIO was positive and the intense cloud cover (Fig. 3). Intense evaporation with colling subject to more cloud cover and movement of ITCZ towards the southward of the Indian Ocean. The peaks in δ18Ovalue and more negative excursion align with the Northern Hemisphere summer (June–August) insolation (NHSI) variation on a ∼23-kyr cycle associated with the precession of the Earth’s orbit (Cai et al., 2015; Gupta et al., 2011; Tiwari et al., 2011; Ramesh et al., 2010; Sinha et al., 2007).
The planktonic foraminifera δ13C is widely used for surface water paleoproductivity, indicating proxy in the Ocean (Berger et al., 1978; Penaud et al., 2010; El Frihmat et al., 2015). The carbon isotope composition of planktonic foraminifera shell records the local bicarbonate 13C/12C variations if the shell was deposited in equilibrium (Broecker, 1971). It was reported in the previous study that the surface water of the Ocean is enriched in 13C fractionation (Craig, 1970; Kroopnick et al., 1970). The removal of 12C by the phytoplankton and the degree of 13C enrichment is related to the biomass in the surface water. The higher δ13C values in the planktonic foraminifer decipher higher surface productivity because the primary producer utilizes 12C through photosynthesis, hence increasing 13C left in the surface water and hence enrichment in 13C (Penaud et al., 2010; Broecker, 1971). In our record, the lowest δ13C value is observed during the early MIS 6 to late MIS 7 (~ 130–240 ka), revealing the lowest productivity in these periods over the past ~ 412 ka. Phytoplankton did not bloom this time, and the 12C value did not separate from the reservoir and decreased the δ13C value. In contrast, MIS 9, MIS 5, and MIS 3 − 1 show higher productivity due to an increase in δ13C value (Fig. 3). In this record, the all-glacial periods show lower (early MIS 10; MIS 6, and MIS 4) or moderate (MIS8 and MIS 2) productivity, but mid-MIS 10 shows a higher value like mid-MIS 9 (most of the higher δ13C value) (Fig. 3). The dissolved inorganic carbon δ13C value of the surface Ocean (planktic foraminifera) was found to be high due to high photosynthesis rate (12C sequestered in phytoplankton), and a lower value was observed in the deep ocean (using benthic foraminifera proxy) (Shackleton et al., 1992; Broecker, 1982; Berger and Vincent, 1986). So, the variation in the vertical gradient in the surface and sub-surface δ 13C value reveals the upwelling/vertical mixing or circulation change in the area (Curry and Oppo, 2005). The lowest productivity between MIS 7 and MIS 6 is frequently attributed to the neutral IOD and low photosynthesis due to less phytoplankton bloom. In contrast, the higher productivity in the mid-MIS 10, MIS 9, and moderate productivity in the MIS 5, MIS 3 reveal that strong photosynthesis due to higher phytoplankton bloom (nutrient rich water) in the WEIO.
The western equatorial Indian Ocean has surface hydrodynamics variations depending on the Pacific and Atlantic oceans through teleconnection and thermohaline circulations. Here, we compare δ18OG. ruber record of core VM29045-PC (WEIO) to five δ18O records from different Indian, Atlantic, and Pacific Ocean basins, namely, Southeast Atlantic Ocean (64PE-174P13) (Scussolini and Peeters 2013), Andaman Sea (NGHP-01-17) (Gebregiorgis et al., 2018), western Pacific warm pool (KX97322-4) (Zhang et al., 2021), Southern Agulhas bank (MD96-2080) (Rau et al., 2002), and Eastern equatorial Indian Ocean (ODP 121-757C) (Boltan et al., 2013) (Fig. 4). All these δ18O records are synchronous with our δ18O of VM29045-PC and have a similar well-recognized glacial-interglacial cycle, representing global SST and ice volume variability in the past. The present study's core location is also affected by some regional and Global Ocean teleconnections such as IOD and ENSO. Therefore, in our records, the quantitative value of δ18O differs from other basin δ18O records. In our records, the δ18O values representing the MIS10 and MIS 2 are much cooler. The most exciting finding in our records is that the cooling intensities of MIS 8 and MIS 6 are different and much weaker than other records (Fig. 4). The possible mechanism behind the different cooling patterns could be regional cooling or because of IOD and equatorial westerly wind during the MIS 10 and MIS 2 (Fig. 4). Equatorial Indian Ocean surface and subsurface temperature variability also corelated with ENSO, were investigated in the output of an Ocean general circulation model (OGCM) forced with surface flux observations. The subsurface dipole exhibits little correlation with ENSO, but the surface dipole is highly connected with ENSO (Shinoda et al., 2004). Other studies also reveal that glacial periods MIS 10 and MIS 2 reflected similar cooling intensities (Rau et al., 2002; Scussolini and Peeters 2013; Boltan et al., 2013; Zhang et al., 2021) The most interesting finding in our records is that the cooling intensities of MIS 8 and MIS 6 are different and much weaker than the other records. The little lower δ18OG.rubervalues were observed during MIS 8 and MIS 6 revealing that it may have happened due to increased freshwater runoff and SST. The positive IOD conditions increase the SST and rainfall in the western equatorial Indian Ocean (Saji et al., 1999; Webster et al., 1999; Schott & McCreary, 2001; Ashok et al., 2001; Li et al., 2003). Our δ13CG.ruber records show lower value corresponded to a decrease in productivity (Penaud et al., 2010; Azharuddin et al., 2017; Khan et al., 2022) in the present study area during the MIS 8 and MIS 6, which also supported this mechanism.
The Indonesian through flow from the western WPWP reaches up to the western equatorial Indian Ocean via the propagation of equatorial waves (Lee et al., 2015; Makarim et al., 2019). So, the surface hydrographic variations could have little similarity in the δ18O records between WPWP and WEIO. Therefore, our records match synchronously with the WPWP records during the glacial-interglacial boundary but do not match within the glacial-interglacial cycle (Fig. 4). The present study core lies within the western DMI region. Hence, IOD directly affects this area (Saji et al., 1999; webster et al 1999) rather than ITF, suggesting that present data shows different patterns and values within the glacial-interglacial cycle. The comparison of the present study with Southern Agulhas Bank and Southeast Atlantic Ocean helps to understand how western Equatorial surface hydrography variability affects the intensity of Agulhas current and Atlantic Niño. The western equatorial SST warming also influences the SST anomaly in the Southeast Atlantic Ocean through the atmospheric bridge and cross-basin impact, initiating the Atlantic Niño (Zhang and Han 2021). South Indian Subtropical Surface Antarctic Intermediate Water mainly feeds up the Agulhas current. However, some remnants contribute from the Red Sea and Tropical Indian Ocean surface Water into the Agulhas retroflection region (Valentine et al.,1993). In our records, the δ18OG.ruber value within the glacial-interglacial cycle shows a similar pattern with the SEA and Agulhas Bank records (Scussolini and Peeters 2013; Rau et al., 2002). It reveals that western equatorial warming and cooling during positive and negative IOD conditions affect the Agulhas current intensity, respectively. However, understanding the complex interaction between IOD, Agulhas, and Atlantic Niño is crucial for predicting climate variability, but it is still in the preliminary stage. Further research will be needed on this mechanism and developing essential strategies for global climate change.