Leaf physiognomy records the Miocene intensification of the South Asia Monsoon

Bhatia, Harshita; Srivastava, Gaurav; Spicer, R. A.; Farnsworth, Alex; Spicer, T.E.V.; Mehrotra, R.C.; Paudayal, Khum N. and Valdes, Paul (2021). Leaf physiognomy records the Miocene intensification of the South Asia Monsoon. Global and Planetary Change, 196, article no. 103365.

DOI: https://doi.org/10.1016/j.gloplacha.2020.103365

Abstract

Our understanding regarding the onset and development of the modern South Asia monsoon (SAM) is still incomplete due to its complex nature and differing views about its relationship with major orographic features such as the Himalaya and Tibetan Plateau. Climate data derived from some terrestrial and marine sediments from the Neogene suggests the onset and intensification of the SAM to a near-modern state occurred during the Miocene, while modelling and other terrestrial proxies point to a much earlier origin for the proto-East Asia monsoon (EAM) and proto-SAM. Angiosperm leaves, particularly dicot leaves, provide a good indication of prevailing climatic conditions as a result of key adaptations in their leaf structure. Here we use Climate Leaf Analysis Multivariate Program (CLAMP) in conjunction with general circulation models to decode the Lower (~13–11 Ma) and Middle (9.5–6.8 Ma) Siwalik climate signal inherent in the physiognomy of fossil leaves. The reconstructed climate data indicates that the Middle Siwalik was warmer and wetter than the Lower Siwalik, particularly in the cooler part the year. The leaf physiognomy of Lower and Middle Siwalik assemblages is indistinguishable to that of the modern leaf assemblages, which are influenced by today's SAM climate. This shows that the SAM was already well established as an independent domain during the late middle Miocene (~13–11 Ma) and has remained nearly the same from the perspective of leaf adaptations since then. A quantitative monsoon intensity index indicates an intensified monsoon during the late Miocene (9.5–6.8 Ma), a finding replicated by climate modelling.

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