|Title||Stalagmites from western Thailand: preliminary investigations and challenges for palaeoenvironmental research|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Chawchai S, Liu G, Bissen R, Jankham K, Paisonjumlongsri W, Kanjanapayont P, Chutakositkanon V, Choowong M, Pailoplee S, Wang X|
Locating suitable caves and stalagmites for palaeoenvironmental and palaeoclimatic studies can be challenging. Isotopic geochemical analyses, albeit commonly performed for palaeoclimatic reconstruction, are also time consuming and costly. Therefore, petrographic and non-destructive morphological studies on speleothems are desirable to facilitate sample selection for further analysis. In this study, 20 caves were surveyed in Ban Rai district, Uthai Thani province in western Thailand. After external physical observations in the field, three stalagmite samples were collected from Tham Nam Cave to test their potential for palaeoclimatic research. Firstly, the stalagmites were scanned by X-ray computed tomography (CT scanning) and subsequently the CT images were compared with petrographic inspections. Columnar fabrics show the highest density, whereas closed and open dendritic fabrics have medium and the lowest densities, respectively. Layers near the top and bottom of the three stalagmites were dated by U-Th mass spectrometric techniques. All three samples were deposited between c.87 and c.105 ka ago; therefore, they are probably the oldest stalagmites that have been reported so far from mainland Southeast Asia. However, their physical features indicate that all the samples have suffered from postdepositional dissolution, and are unlikely to be suitable for palaeoclimatic research. The internal dissolution feature of stalagmites, however, cannot be identified by visual inspection of uncut samples. We hereby argue that CT images are useful to characterize stalagmite petrography, in particular fabric, porosity and density. Such features can be used to select the ideal plane of a stalagmite for sectioning, to maximize the chances of robust climatic reconstruction.