Assessing the Eco-hydro-meteorological Variables Influencing the Carbon Exchange Phenomenon of Pine-dominated Ecosystem of Himalaya
Abstract
The great Himalayas is a rich hotspot of biodiversity, enormously susceptible to extreme natural hazards and anthropogenic interventions. Such a fragile region allows the development of multiple ecosystems according to varying topography and terrain. Nowadays, the ecosystems of the Himalayas are experiencing recurrent extreme weather events, which are drastically impacting the structure, function, and dynamics of present ecosystems. These temporary and permanent changes disturb the carbon cycle, due to which the amount of Net Ecosystem Exchange (NEE) varies spatiotemporally. The short-duration fluctuations in ecohydrological variables significantly perturb the weekly NEE amount. To this end, the present study examines the NEE variations of the natural and dense Himalayan ecosystems, which are not well explored at a sub-daily scale due to limited data availability. Here, we investigate the influence of eco-hydro-meteorological variables on NEE for a Pine-dominated ecosystem (Pinus roxburghii) in the Western Himalayans. We studied the observed half-hourly temporal resolution flux tower data of 104 weeks starting from December 2014 to November 2016. We observed that the sub-daily scale variability of NEE contributes 20-40% to weekly variability. We applied a transfer entropy-based process network approach with a maximum memory of six hours to understand sub-daily scale processes. We generated the process networks of consistent causal links on a seasonal scale. Irrespective of the season, the eco-hydro-meteorological variables such as Net Solar Radiation, Air Temperature, Relative Humidity, and Sensible Heat flux have a substantial impact on the NEE and Ecosystem Respiration (RE) at a sub-daily scale. The network does not show the direct causal link from Precipitation to NEE and RE within a sub-daily scale. Precipitation does not immediately influence the deep-rooted Pine forests; however, it is a strong contributing variable at higher memory. At the same time, the analysis conducted for the networks of wet and dry weeks of Precipitation demonstrates that the moisture-stressed dry periods contain more causal connections from hydrometeorological variables to NEE.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H32N1096K
- Keywords:
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- Ecohydrology;
- Pine ecosystem;
- Himalayan;
- Process networks;
- Transfer entropy