AmeriFlux: Its Impact on our understanding of the ‘breathing of the biosphere’, after 25 years

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 348, P. 109929 - 109929

Published: Feb. 16, 2024

Language: Английский

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Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 917, P. 170532 - 170532

Published: Jan. 29, 2024

Language: Английский

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Revisiting vegetation activity of Mongolian Plateau using multiple remote sensing datasets

Agricultural and Forest Meteorology, Journal Year: 2023, Volume and Issue: 341, P. 109649 - 109649

Published: Aug. 3, 2023

Language: Английский

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Differential phenological responses of plant functional types to the temporal repackaging of precipitation in a semiarid grassland

Plant and Soil, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 28, 2025

Language: Английский

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Diversity of evapotranspiration and water use efficiency for complex ecosystems in the Horqin Sandy Land

CATENA, Journal Year: 2025, Volume and Issue: 252, P. 108890 - 108890

Published: March 6, 2025

Language: Английский

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Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

Journal of Advances in Modeling Earth Systems, Journal Year: 2025, Volume and Issue: 17(3)

Published: March 1, 2025

Abstract Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring (C) fluxes in rangelands are challenging due to the considerable spatial temporal variability tied rangeland C dynamics as well limited data availability. We developed Rangeland Carbon Tracking Management (RCTM) system track long‐term changes by leveraging remote sensing inputs variable sets with algorithms representing terrestrial C‐cycle processes. Bayesian calibration was conducted using quality‐controlled flux obtained from 61 Ameriflux NEON tower sites Western Midwestern US parameterize model according dominant vegetation classes (perennial and/or annual grass, grass‐shrub mixture, grass‐tree mixture). The resulting RCTM produced higher accuracy for estimating cumulative gross primary productivity (GPP) ( R 2 > 0.6, RMSE <390 g m −2 ) relative net exchange of CO (NEE) 0.4, <180 ). Model performance varied season type. captured = 0.6 when validated against measurements across 13 sites. simulations indicated slightly enhanced during past decade, is mainly driven an increase precipitation. Future efforts refine will benefit network‐based biomass, fluxes, stocks.

Language: Английский

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Interannual variability and trends of gross primary production and transpiration in savannas and grasslands from 2000 to 2021

Frontiers of Earth Science, Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

Language: Английский

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Vegetation factors and atmospheric dryness regulate the dynamics of ecosystem water use efficiency in a temperate semiarid shrubland

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 639, P. 131644 - 131644

Published: July 4, 2024

Language: Английский

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Coexistence of vascular plants and biocrusts under changing climates and their influence on ecosystem carbon fluxes

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 360, P. 110298 - 110298

Published: Nov. 13, 2024

Language: Английский

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Coupling Remote Sensing with a Process Model for the Simulation of Rangeland Carbon Dynamics

Authorea (Authorea), Journal Year: 2024, Volume and Issue: unknown

Published: April 9, 2024

Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring (C) fluxes in rangelands are challenging due to the considerable spatial temporal variability tied rangeland C dynamics, as well limited data availability. We developed a Rangeland Carbon Tracking Management (RCTM) system track long-term changes by leveraging remote sensing inputs variable datasets with algorithms representing terrestrial C-cycle processes. Bayesian calibration was conducted using quality-controlled flux obtained from 61 Ameriflux NEON tower sites Western Midwestern U.S. rangelands, parameterize model according dominant vegetation classes (perennial and/or annual grass, grass-shrub mixture, grass-tree mixture). The resulting RCTM produced higher accuracy for estimating cumulative gross primary productivity (GPP) (R2 > 0.6, RMSE < 390 g m-2) than net exchange of CO2 (NEE) 0.4, 180 m-2), captured surface R2 = 0.6 when validated against measurements across 13 sites. Our simulations indicated slightly enhanced during past decade, is mainly driven an increase precipitation. Regression analysis identified slope, texture, climate factors main controls on model-predicted sequestration rate. Future efforts refine will benefit network-based biomass, fluxes, stocks.

Language: Английский

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