Tracing the history

Tracing the history of climatic and anthropogenic influence on the Banni Grassland, Kachchh, Gujarat – A multi proxy approach. [/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.12.2″ custom_padding=”0|0px|0|0px|false|false” make_fullwidth=”on”][et_pb_column type=”2_3″ _builder_version=”3.12.2″ parallax=”off” parallax_method=”on”][et_pb_text _builder_version=”3.12.2″]

Presented by
Anusree A.S.
Anusree A.S., Jayashree Ratnam, Mahesh Sankaran

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The Banni landscape is one of Asia’s largest tropical grasslands and has for thousands of years supported large populations of people and livestock. This study aims to understand the historic dynamics of this unique ecosystem in response to various drivers of vegetation change, which is particularly important in the context of present day scenarios of changing climatic, edaphic, grazing and fire regimes, to all of which this system is very sensitive.


A lake sediment core (of ~1.5 m depth) collected from the Banni grassland was radio carbon dated to determine the age of sediment, and the core (Chachi) was analysed to reconstruct past vegetation, climate, herbivore abundance and fire events based on pollen (Bennett & Willis 2001), stable isotopes of carbon and oxygen (West et al.2006), coprophilous fungal spores (Baker et al., 2013) and charcoal (Stevenson & Harberle, 2005) respectively.


The sediment dated back to ~ 4482 years before present (ybp). Isotope and pollen analysis show that there is a shift from mesic to arid conditions ~2500 ybp with aridity peaking at ~2000 ybp. After ~2000 ybp, there is a slight shift back to mesic conditions until ~1500 ybp following which the system has remained arid. Fungal spores and charcoal density have gradually increased from ~3782 ybp, suggesting an increase in anthropogenic activities in the ecosystem since then.


This study provides insights about past trends and causes of vegetation change in the Banni and it provides relevant inputs to make predictions regarding vegetation responses to current drivers in the landscape and the future directions of ecosystem changes. A high resolution study of more cores will be helpful to make informed decisions for the sustainable management of ecosystem.

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