Leading indicators

Leading indicators of grassland to woodland transitions in a savanna ecosystem [/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
Amit Agrawal
Indian Institute Of Science
Amit Agrawal, Stephanie Eby, Andrew P. Dobson, Vishwesha Guttal


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Many ecosystems are susceptible to abrupt, often irreversible regime shifts, like the transition from savanna to desert that created the Sahara. Indication of such transition allows to prevent or mitigate adverse effects. Some indicators were already proposed based on mathematical ecological model but should be tested in real ecosystem. It is difficult to test these indicators, due to lack of a large space-time data and difficulties in performing field experiments.


To address this problem we took a ‘space-for-time-substitution’ approach by computing leading indicators of transitions from grassland to woodland states in the Serengeti-Mara ecosystem in Tanzania and Kenya.


We found that spatial indicators such as spatial variance, spatial skewness, spatial correlation and spatial discrete Fourier transform (DFT) at low frequencies all increased prior to a sharp decrease in grass cover. However, we found that the spatial metrics are most effective as early warning signals during the initial decline in grass cover and also after certain loss of grass cover such leading indicators are of no use.


Our results suggest that it may be possible to determine early warning signals of regime shifts based on spatial data. And also effectiveness of these leading indicators depend upon the current state of ecosystem. Possibly in future, these indicators will allow us to identify the regions at risk, and where conservation efforts should be focused

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