Excavation and Radiocarbon dating
A 1 m ² pit (SQA) was opened near to the entrance of the cave where the slope flattened. The pit location was chosen for its central location near the opening with optimal light and where prehistoric habitation activity was most likely to be focused. SQ A was hand excavated with trowel and hand shovels in 5 cm intervals (spits) within stratigraphic layers down to bedrock (Spits A1-A9). When a burial was encountered in the east baulk this was extended at the eastern side of SQ A with another 100 x 50 cm pit (SQ B) for the purposes of accessing the complete burial feature for excavation. SQ B was also excavated in 5 cm spits down to the top of the burial (spits B1–B6). When the top of the burial was exposed in both SQ A and B, the excavation was further extended into the southeast baulk using spades to expose it in the burial extension area. Once the discrete burial feature was exposed fully in plan, the burial was excavated separately in two 5 cm spits removing sediment and exposing the human skeletal remains in situ using brushes, fine wooden skewers and small trowels to reveal the burial position and associated artefacts.
All excavation units, features, and in situ charcoal, shell and artefacts were recorded in 3D using a Leica TS09 total station. Charcoal was also collected from the section walls. These sections were hand drawn on graph paper and digitized later. Charcoal was also recovered in situ during excavation as well as during sieving and sorting. All material from SQ A (spits 1–9), SQ B (spits 1–6) and from the burial feature was first dry sieved through a 1.5 mm mesh and then bagged by spit and feature for transport to the beach where it was further wet sieved through another 1.5 mm mesh. The material from above the burial extension was discarded without sieving due to time constraints. All retrieved material was then dried and sorted into the following categories: bone, shell, lithics, charcoal, seeds, pottery, ochre, shell artefacts.
In situ marine shell and charcoal were dated at the Australian National University Radiocarbon Dating Centre (95) and Waikato Radiocarbon dating laboratory. All dates were calibrated in OxCal 4.4, using IntCal20 (96) and Marine20 (97), to 95.4% confidence interval (SI Table 1). These radiocarbon dates were put into an age depth depositional model within OxCal 4.4 (98). The age depth model assumes a Poisson (or random) accumulation of sediment (99), calculated from the available age data by averaging the model over many values of k (100). The model interpolation rate was set to a single date per spit, and the unit of depth used was in centimeters (cm). For charcoal dates, we applied the Charcoal Plus t-type Outlier Model with a prior outlier probability of 10%, which is specifically designed to account for the inbuilt age of charcoal, while also allowing for some stratigraphic movement in an archaeological context (101–102).
Mortuary practices
Mortuary practice reconstructions used standard data collection methods in the field (103–105) and centered on the anatomical composition of human skeletal material and their spatial distribution in relation to grave goods to reconstruct the initial internment conditions (body position, manipulation) through visual aspects of the burials in plan (photographs and drawings). Once the skeletal material was exposed and carefully cleaned of loose sediment, the burials were photographed in situ with datum points plotted in 3D at critical points on the skull, long bones, hands and feet. Both burials were in exceptionally fragile condition, the bones were soft and flaking so excavation and lifting had to be completed with care. Once recorded elements were individually lifted by hand and placed into bags with bubble wrap and stored in plastic containers for transport for study at the archaeology department laboratory in Universitas Gadjah Mada (UGM), Jogjakarta. Biological characteristics consisting of age, sex, stature, biological affinity, and pathological history are difficult to assess due to the poor condition of these individuals, which are also covered in concreted carbonate. They were assessed using standard bioarchaeological methods (103) and will be reported in a future publication.
Faunal analyses
The vertebrate and invertebrate remains were further sorted in the UGM lab by broad taxonomic group for further designation into the lowest taxonomic level possible whether that be order, family, genus or species. Identification and quantification methods followed (1). In most cases identification could only be made to class, order or family level due to limited reference materials available at UGM. Vertebrates were quantified by Number of Identified Specimens Present (NISP) and weight (g). In the case of invertebrates, previously identified archaeological reference specimens were available at the department of archaeology at UGM for comparison with the RM2 material. Molluscs were quantified by Minimum Number of Individuals (MNI) using a non-recurring element for each taxon.
Diversity and evenness values were calculated for mollusc MNI by taxa using PAST4 software (106) to determine changes in foraging strategies, whereby diversity or richness (NTAXA) calculates number of taxa exploited and evenness indices including Simpsons, Shannon-Wiener H, Equitability e, and Equitability J, calculate relative abundance of taxa being exploited to detect changes in foraging strategies (50, 107). The higher the evenness value the less diverse the assemblage and the more generalist the foraging strategy, conversely the lower the evenness score the greater the focus of foraging on fewer taxa suggesting a more specialized strategy.
Stable carbon (δ13C), oxygen (δ18O) isotope analysis
Two human teeth, one from each burial, were selected for stable carbon and oxygen isotope analysis. Stable carbon and oxygen isotope analyses of human and faunal tooth enamel has proven an effective method for reconstructing Pleistocene-Holocene human subsistence in Wallacea. In tropical regions, δ13C analysis can be used to distinguish reliance on C3 resources, which dominate woodland and forests settings and include crops such as rice, versus C4 resources, which are commonly tropical grasses including crops such as millet (108–111). Plants and animals feeding on plants, in closed canopy forest also have lower δ13C than other C3 plants growing in more open areas thanks to the ‘canopy effect’ (112). Higher δ13C in marine producers than all C3 terrestrial plants (113–114) facilitates distinction of marine versus terrestrial C3 consumers (115). While consumption of marine and C4 resources can lead to overlapping δ13C, the provision of a detailed faunal baseline and contextual information can tease these factors apart (48). δ18O analysis of tooth enamel provides additional mammalian information about imbibed water and consumed food. δ18O analysis has also been argued to distinguish terrestrial from marine consumers (116), though this is not currently evident for Wallacean contexts (48).
Air-abrasion was used to clean the selected teeth and remove adhering external material. A diamond-tipped drill was used to obtain 8 milligrams of enamel powder from the full length of the buccal surface of the tooth, representing the entire period of enamel formation. Samples were washed in 1.5% sodium hypochlorite for 60 minutes, followed by three rinses in purified H2O and centrifuging, before 0.1M acetic acid was added for 10 minutes, followed by another three rinses in purified H2O. Samples were subsequently lyophilized for 24 hours. 100% phosphoric acid was added to the samples with the gases evolved being measured for δ13C and δ18O using a Thermo Gas Bench 2 connected to a Thermo Delta V Advantage Mass Spectrometer at the Max Planck Institute for the Science of Human History, Jena, Germany. δ13C and δ18O values were compared against International Standards (IAEA-603 (δ13C = 2.5; δ18O = -2.4); IAEA-CO-8 (δ13C = -5.8; δ18O = -22.7); USGS44 (δ13C = -42.2) and in-house standard (MERCK (δ13C = -41.3; δ18O = -14.4). Replicate analysis of MERCK standards suggests that machine measurement error is c. ± 0.1‰ for δ13C and ± 0.2‰ for δ18O. Overall measurement precision was based on repeat extracts from a bovid tooth enamel standard (n = 20, ± 0.2‰ for δ13C and ± 0.3‰).
Strontium (87Sr/86Sr) isotope analysis
Strontium isotope analysis has been used to assess the mobility and migration patterns of prehistoric humans around the world (117–120), but little work has focused on applying this method in Island Southeast Asia. The method is based on the premise that rocks display variable 87Sr/86Sr depending on their type, age, and original rubidium (Rb) content. Mineral weathering and erosion of the underlying bedrock, airborne dust (loess), sea-spray, atmospheric deposition, groundwater, and stream water are major contributors to the strontium in soil (121–123). As a result of these processes the biologically available 87Sr/86Sr of the soil may vary from the 87Sr/86Sr of the underlying bedrock (124–125). Human tooth enamel is resistant to diagenetic alteration in the burial environment. Strontium purified from enamel should be representative of the biogenic strontium available during the time of tooth mineralization (117, –126–127). The 87Sr/86Sr ratio of tooth enamel reflects the bioavailable strontium isotope signature of the food and drink a person consumed during the time of tooth mineralization (121).
For radiogenic strontium isotope analysis, two 10–20 mg enamel samples from the same teeth used for the above analyses were prepared and analysed at the class-10, ultra-clean laboratory at the Centre for Trace Element Analysis, Department of Geology, University of Otago, Dunedin, New Zealand. Prior to transferring to the clean lab, the enamel was cleaned through abrasion with a sonicated Dremel® reinforced diamond cutting wheel to remove possible surface contaminants. Any additional adhering materials, such as organic matter or dentin, were also removed. Samples were then transferred to the clean lab and weighed in clean Perfluoroalkoxy alkanes (PFA) vials (Savillex, Eden Prairie, Minnesota, USA) and digested in 2 ml of 3M HNO3 overnight at 110°C. Samples were then evaporated between 4–8 hours at 110°C. After evaporation, dried samples were dissolved in 2 ml of 3M HNO3 and subsampled to determine strontium concentration. Strontium was purified manually using established processes of column chemistry (117, 128). Only a single elution was necessary and the sample was evaporated, reconstituted in 2% HNO3, subsampled for strontium concentration analysis, and then 87Sr/86Sr was measured using a Nu Plasma-HR MC-ICP-MS instrument (Nu Instruments Ltd., UK). Data were normalized using repeated measurement of two in-house lab references, NIST SRM 987 and HPS, that bracketed every six samples to monitor the accuracy and reproducibility of the measurements. The in-house, long-term reference value for NIST SRM 987 is 0.71025 ± 0.00002 (2 SD, n > 200) and for HPS it is 0.70762 ± 0.00003 (2 SD, n = 189). Any instrumental mass fractionation present was corrected using repeated measurement of 86Sr/88Sr, expected to be 0.1194. Procedural blanks were run with each batch of 48 samples and all yielded negligible Sr levels of < 250 pg.
Peptide analysis
Enamel peptide preparation followed established methods (129). First the enamel was washed in 3% H2O2 for 30 seconds and quenched in MilliQ H2O for 30 seconds. The enamel chip was then conditioned in 60µL of 5% (vol/vol) HCl for 2 minutes. The HCL conditioning solution was removed and discarded. Another 60µL of 5% (vol/vol) HCl was added to the enamel chip and incubated for 2 minutes for peptide extraction. The HCl extraction solution containing the peptides was then recovered and centrifuged for 5 min at 20,000 rpm to remove any particulates. The extracted peptides were then purified by solid phase extraction on a ZipTip with 0.6 µL C18 resin (Millipore) essentially following the manufacturer’s instructions. In brief, after rinsing of the C18 resin in pure acetonitrile (ACN), the ZipTip was equilibrated in 0.1% formic acid (FA) in water before loading the sample of extracted peptides. The bound peptides were then washed on-tip with 0.1% formic acid (FA) in water and eluted in 60% ACN, 0.1% formic acid (FA) in water. The eluate was dried using a centrifugal vacuum concentrator and stored as dried samples at -80°C.
For peptide analysis by untargeted liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) samples were reconstituted in 20 µL of 5% ACN, 0.1% FA in water of which 5 µL were loaded into an Ultimate 3000 nano-flow uHPLC system inline coupled to a LTQ-Orbitrap mass spectrometer (Thermo Scientific). Peptides were separated on a 75 µm ID silica emitter tip column that was in-house packed with Aeris 2.6 µm PEPTIDE XB-C18 100 Å bead material (Phenomenex) on a length of 20 cm. The LC gradient between mobile phase A (0.1% formic acid in water) and mobile phase B (0.1% formic acid in 90% aqueous ACN) was developed from 5% B to 25% B over 13 min followed by an increase to 40% B over 3 min. and 90% B over 2 min. at a flow rate of 300 nl/min. The LTQ-Orbitrap mass spectrometer was operated in an untargeted data acquisition mode. The precursor ion scan was performed in a m/z window of 400 to 2000 at a resolution of 60,000. The precursor ion scan was followed by 9 data-dependent collision-induced dissociation (CID) fragment ion spectrum acquisitions, of which the first three scans were set up as semi-targeted acquisitions of pre-specified precursor masses if present in the precursor ion scan at a threshold intensity of at least 5000 counts. The following 6 CID acquisitions were set up as data-dependent scans of the 6 most intense ions. The peptide targets included in the precursor ion list were three peptidoforms of the AMELY encoded amelogenin isoform (SMIRPPY at m/z 432.23, SMOXIRPPY at m/z 440.22 and SMOXIRPPYS at m/z 483.74), one peptide specific for the AMELX encoded isoform (SIRPPYPSY at m/z 540.28) and one peptide common to both isoforms (MPLPPHPGHPGYINF at m/z 837.42).
Raw data were analysed by both software-assisted sequence database searches and manual spectrum interpretation. The Proteome Discoverer software (version 2.5, Thermo Scientific) was used for sequence assignment using the Sequest HT program to search the human reference and UniProt amino acid sequence databases. Enzyme cleavage was set to non-specific and methionine oxidation was included as a variable modification. Precursor and fragment ion intensities (area under the curve) were extracted manually using the Qual Browser program of the Xcalibur software package (version 2.0.7, Thermo Scientific).
Based on the results of the untargeted data acquisition approach, a fully targeted high resolution multiple reaction monitoring assay was set up for further confirmation of the presence of the AMELY isoform using a 5600 + Triple Time-Of-Flight mass spectrometer coupled to nano-flow liquid chromatography (AB Sciex). Sample loading and LC conditions were the same as for the untargeted approach. The following precursor ions of selected peptide sequences were targeted. AMELY-specific: SMIRPPY, SMOXIRPPY, and SMOXIRPPYS; AMELX-specific: SIRPPYPSY, YEVLTPLK; present in both AMELY and AMELX: LPPHPGHPGYINF. Data were analysed with the Skyline software (version 21.2.0, https://skyline.ms/project/home/begin.view?).
Artefacts
Stone artefacts were identified by raw material with flakes, flake fragments, cores and flaked pieces counted using the total number of stone flaked artifacts [TNA] and the minimum number of flakes [MNF] (130). Heat damage was present on some stone artefacts and identified by the presence of crazing, potlids and crenulated surfaces. Pottery was counted by NISP and weight and assessed for form and decoration. Shell artefacts were counted, weighed, photographed and recorded by taxa and evidence of use-wear and/or manufacture.
Obsidian Geochemistry
Obsidian artefacts were analysed semi-quantitatively by portable X-Ray Fluorescence analysis (pXRF), a Bruker Tracer III-SD was employed. Manufacturer recommended settings were used of 40 keV and 42 mA using a 0.1524 mm Cu, 0.0254 mm Ti and 0.3048 mm Al filter in the X-Ray path and a 60 s live-time count at 145 FWHM. The raw counts of the pXRF were calibrated using 40 international standards provided by MURR (131). Each artefact was analysed at two spots. Element concentrations of manganese (Mn), iron (Fe), zinc (Zn), gallium (Ga), thorium (Th), rubidium (Rb), strontium (Sr), yttrium (Y), zirconium (Zr), and niobium (Nb) were calculated. Elemental concentrations were compared to six known obsidian sources in ISEA, four obsidian source regions in the Western Pacific and two identified sources in the Lesser Sunda Islands which are only known by artefact occurrences at sites (Group 1 and 2) (26–29). Discriminant Analysis (LDA) in the PAST4 software was used for comparison (106).
Geochemical analysis of 31 obsidian flakes was conducted. Discriminant function analysis (LDA) and bi-plots of the elemental composition of each artefact against the reference samples were used and the statistical analysis unambiguously sourced all samples to the Group 1 source (Fig. 11). The initial LDA of Mn, Rb, Sr, Y, Zr and Nb was successful insofar that 98% of all sources could be excluded as a possible origin. Only the sources of Uliang Bundoc on Luzon, Philippines, and Group 1 obsidian, assumed to be located in the Lesser Sunda Islands, match the geochemistry of the samples. Unfortunately, these two sources plot closely together and an unambiguous sourcing by LDA alone was not possible. However, additional analysis by bi-plots of selected elemental compositions revealed that the Uliang Bundoc source is not a good match for the RM2 samples. Sr and Nb were selected to investigate the differences between Uliang Bundoc and Group 1 (Fig. 11). Uliang Bundoc has significantly lower values in both Sr and Nb, and can be excluded as possible origin of the artefacts.