EGU23-257, updated on 22 Feb 2023
https://doi.org/10.5194/egusphere-egu23-257
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessment of the Long-term Temporal Resilience of the Indian Terrestrial Ecosystems: Insights into the Country-scale Drivers

Abhishek Chakraborty1, Sekhar Muddu1,2, and Lakshminarayana Rao3
Abhishek Chakraborty et al.
  • 1Interdisciplinary Centre for Water Research (ICWaR), Indian Institute of Science Bangalore, Bengaluru, Karnataka, India
  • 2Department of Civil Engineering, Indian Institute of Science Bangalore, Bengaluru, Karnataka, India
  • 3Centre for Sustainable Technologies, Indian Institute of Science Bangalore, Bengaluru, Karnataka, India

The knowledge of the long-term resilience of Indian terrestrial ecosystems is essential in the background of massive land-use conversion to croplands, intensification of irrigation, and the enhanced climate change signals over the past few decades. Previous assessments of Indian ecosystem resilience were limited by a smaller temporal span, lack of consideration for the sub-annual ecosystem transitions, and non-aridity-based stressors of the loss of resilience of ecosystems (Sharma and Goyal, 2017, Glob Chang Biol; Kumar and Sharma, 2023, J Environ Manage). This study aims towards a comprehensive understanding of the resilience of Indian terrestrial ecosystems through monthly scale assessment considering the driving role of the stressors in a standalone and compound manner.

The study utilizes ecosystem water use efficiency (WUE) as a state variable to assess the resilience of Indian ecosystems. WUE, produced from the FLUXCOM RS+METEO gross primary productivity (GPP) and evapotranspiration (ET) datasets at a monthly scale (WUEe=GPP/ET) from 1950 to 2010 (Jung et al., 2019, Sci Data; Tramontana et al., 2016, Biogeosciences), is a metric to quantify the strength of the coupling between terrestrial water and carbon cycles. Further lag-1 autocorrelation time series (AC(1)) is produced by evaluating the Kendall tau correlations for each pixel's residual component of the decomposed time series of WUE (excluding the impacts of trends and seasonal cycles). Such higher-order statistical assessments have been used earlier to quantify the loss of resilience (Smith et al., 2022, Nat Clim Change; Boulton et al., 2022, Nat Clim Change). We conduct the AC(1) analysis for resilience for India's six homogeneous meteorological regions, the eight major river basins, and the biome scale. We further consider the impacts of different forms of aridity on the loss of resilience: atmospheric aridity, hydrological aridity, and soil moisture aridity, individually and in a compound pattern. We also assess the loss of resilience at a seasonal scale (winter, summer, monsoon, post-monsoon) for the two major anthropogenic influences on Indian ecosystems: intensity of irrigation and groundwater fluctuations. This study attempts at a holistic understanding of the loss of resilience through its quantification and impacts of drivers, which could help the policymakers to identify the hotspots of loss of resilience and the significant perturbations to the resilience of Indian terrestrial ecosystems.

How to cite: Chakraborty, A., Muddu, S., and Rao, L.: Assessment of the Long-term Temporal Resilience of the Indian Terrestrial Ecosystems: Insights into the Country-scale Drivers, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-257, https://doi.org/10.5194/egusphere-egu23-257, 2023.