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Evaluating impacts of hydroclimatic extremes on water use efficiency and carbon use efficiency of northern ecosystems

Karkare, Vaishnavi Prashant LU (2025) In Student thesis series INES NGEM01 20251
Dept of Physical Geography and Ecosystem Science
Abstract
Climate change intensifies extreme weather events, especially droughts, with severe consequences to the functional integrity of terrestrial high-latitude ecosystems. As essential global water and carbon balance regulators, these sensitive ecosystems respond to increased warming and altered hydrology with modulated resource use efficiencies. This study aimed to investigate the impacts of various hydroclimatic drivers on ecosystem Water Use Efficiency (WUE) and Carbon use Ecosystem (CUE) across five distinct vegetation types in northern latitudes (deciduous broadleaf forests, evergreen needleleaf forests, grasslands, open shrublands, and permanent wetlands) from 2001 to 2020. Using flux data from FLUXNET2015 and AMERIFLUX with monthly SPEI... (More)
Climate change intensifies extreme weather events, especially droughts, with severe consequences to the functional integrity of terrestrial high-latitude ecosystems. As essential global water and carbon balance regulators, these sensitive ecosystems respond to increased warming and altered hydrology with modulated resource use efficiencies. This study aimed to investigate the impacts of various hydroclimatic drivers on ecosystem Water Use Efficiency (WUE) and Carbon use Ecosystem (CUE) across five distinct vegetation types in northern latitudes (deciduous broadleaf forests, evergreen needleleaf forests, grasslands, open shrublands, and permanent wetlands) from 2001 to 2020. Using flux data from FLUXNET2015 and AMERIFLUX with monthly SPEI for drought characterisation, a machine learning technique—Random Forest, was employed to capture complex, non-linear relationships.
The results indicate a concerning increase in drought frequency and severity in the high latitudes from 2016 onwards. While both WUE and CUE generally exhibited higher median values under dry conditions across most vegetation types, reflecting physiological adaptation, their linear sensitivity to SPEI was consistently weak, highlighting the importance of multiple interacting drivers. RF models demonstrated overall robust predictive performance, especially for CUE, revealing that the influence of climate variables on efficiencies was highly vegetation- and moisture-condition-specific. Vapor Pressure Deficit (VPD) consistently emerged as a key negative driver, particularly for forest WUE and CUE. At the same time, Air Temperature (TA), Soil Temperature (TS), and Shortwave Radiation (SW) showed varying importance depending on the vegetation type and moisture regime. These findings underline the non-linear complexity of high-latitude ecosystem responses to climate change, emphasising the critical need for biome-specific assessments to project their future role in global biogeochemical cycles accurately. (Less)
Please use this url to cite or link to this publication:
author
Karkare, Vaishnavi Prashant LU
supervisor
organization
course
NGEM01 20251
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Physical geography, Ecosystem analysis, Water Use Efficiency, Carbon Use Efficiency, Northern ecosystems, Random Forest model, Drought
publication/series
Student thesis series INES
report number
737
language
English
id
9205977
date added to LUP
2025-06-27 11:40:13
date last changed
2025-06-27 11:40:13
@misc{9205977,
  abstract     = {{Climate change intensifies extreme weather events, especially droughts, with severe consequences to the functional integrity of terrestrial high-latitude ecosystems. As essential global water and carbon balance regulators, these sensitive ecosystems respond to increased warming and altered hydrology with modulated resource use efficiencies. This study aimed to investigate the impacts of various hydroclimatic drivers on ecosystem Water Use Efficiency (WUE) and Carbon use Ecosystem (CUE) across five distinct vegetation types in northern latitudes (deciduous broadleaf forests, evergreen needleleaf forests, grasslands, open shrublands, and permanent wetlands) from 2001 to 2020. Using flux data from FLUXNET2015 and AMERIFLUX with monthly SPEI for drought characterisation, a machine learning technique—Random Forest, was employed to capture complex, non-linear relationships.
The results indicate a concerning increase in drought frequency and severity in the high latitudes from 2016 onwards. While both WUE and CUE generally exhibited higher median values under dry conditions across most vegetation types, reflecting physiological adaptation, their linear sensitivity to SPEI was consistently weak, highlighting the importance of multiple interacting drivers. RF models demonstrated overall robust predictive performance, especially for CUE, revealing that the influence of climate variables on efficiencies was highly vegetation- and moisture-condition-specific. Vapor Pressure Deficit (VPD) consistently emerged as a key negative driver, particularly for forest WUE and CUE. At the same time, Air Temperature (TA), Soil Temperature (TS), and Shortwave Radiation (SW) showed varying importance depending on the vegetation type and moisture regime. These findings underline the non-linear complexity of high-latitude ecosystem responses to climate change, emphasising the critical need for biome-specific assessments to project their future role in global biogeochemical cycles accurately.}},
  author       = {{Karkare, Vaishnavi Prashant}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Student thesis series INES}},
  title        = {{Evaluating impacts of hydroclimatic extremes on water use efficiency and carbon use efficiency of northern ecosystems}},
  year         = {{2025}},
}