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Sukumar, R.

Publications and source records attributed to Sukumar, R..

2 recordsLinked to original sources

Climate change and the migration of a pastoralist people c.3500 cal. years BP inferred from palaeofire and lipid biomarker records in the montane Western Ghats, India

Human migration in response to climate change during the Holocene has been recorded in many regions of the world. The Todas are a pastoralist people who are believed to have colonized the higher elevations (>2000 m asl) of the Nilgiris in the Western Ghats, India, not earlier than about 2000 cal. yr BP. Vegetation shifts in response to changing climate in tropical montane forest-grassland mosaic of the Ghats have been well documented using stable carbon isotopes and pollen profiles; however, there have been no corresponding investigations of human presence and activity at the highest elevations. We used a number of other proxies to infer the human ecology of this montane region. Radiocarbon dated (~22,000 cal. BP to the present) peat samples from the Sandynallah basin (2200m asl, Nilgiri hills, Tamil Nadu State) were used to reconstruct fire history, animal abundance, and human presence since the Last Glacial Maximum (LGM). While the macro-charcoal record indicates fires at the LGM, macro- and micro-charcoal counts indicate intense fire at ~3500 cal. yr BP, coprophilous fungal spores indicate a large population of herbivorous mammals, and steroid biomarkers indicate human faecal remains for the first time. This period is also characterized by dry arid conditions and dominant grassy vegetation as inferred from n-alkane signatures. We thus infer that a pastoralist people, most likely the Todas, migrated to the highest elevations of the Western Ghats along with their buffalo herds in response to prolonged or abrupt climate change in peninsular India, about 3500 cal. yr BP or at least 1500 years prior to what historical accounts assume.

ecology

Improving prediction and assessment of global wildfires using neural networks

Fires determine vegetation patterns, impact human societies, and provide complex feedbacks into the global climate system. Empirical and process-based models differ in their scale and mechanistic assumptions, giving divergent predictions of fire drivers and extent. Especially, the role of anthropogenic drivers remains less understood. Taking a data-driven approach, we use an artificial neural network to learn region-specific relationships between fire and its socio-environmental drivers across the globe. As a result, our models achieve higher predictability than previously reported, with global spatial correlation of 0.92, temporal correlation of 0.76, interannual correlation of 0.69, and grid-cell level correlation of 0.6, between predicted and observed burned area. Our analysis reveals universal global patterns in fire-climate interactions, coupled with strong regional differences in fire-human relationships. Given the current socio-anthropogenic conditions, Equatorial Asia, southern Africa, and Australia show a strong sensitivity of fire extent to temperature whereas northern Africa shows a strong negative sensitivity. Overall, forests and shrublands, show a stronger sensitivity of burned area to temperature compared to savannas, potentially weakening their status as carbon sinks under future climate-change scenarios.

ecology