Global Patterns of Vegetation Response to Short-Term Surface Water Availability

Terrestrial vegetation response to surface water availability is important for land-atmosphere interactions. However, the current understanding of how the vegetation responds to surface water remains limited since the physical processes happening within the biosphere and hydrosphere are highly coupl...

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Veröffentlicht in:IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.8273-8286
Hauptverfasser: He, Qing, Lu, Hui, Yang, Kun, Zhen, Ling, Yue, Siyu, Li, Yishan, Entekhabi, Dara
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container_title IEEE journal of selected topics in applied earth observations and remote sensing
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creator He, Qing
Lu, Hui
Yang, Kun
Zhen, Ling
Yue, Siyu
Li, Yishan
Entekhabi, Dara
description Terrestrial vegetation response to surface water availability is important for land-atmosphere interactions. However, the current understanding of how the vegetation responds to surface water remains limited since the physical processes happening within the biosphere and hydrosphere are highly coupled. It is even more difficult to measure such interactions for the processes related to surface soil moisture (SSM)-the central variable that interacts the most intimately with vegetation-since the observations of SSM are often scarce and uneven. Here, we use the satellite observations of vegetation optical depth (VOD) and SSM to map the response time scales of vegetation to surface water anomalies. We use the stability theory to derive vegetation memory time ({{{\bf \tau }}_{{{\bf ReS}}}) to reveal the global pattern of vegetation memory to surface water anomalies. That is, the time vegetation takes to return back to its equilibrium when an anomaly dissipates to a certain level (e.g., the e-folding level). We also estimate the plant reactive time ({{{\bf \tau }}_{{{\bf ReA}}})-the time when impacts of surface anomaly reach its peak to evaluate the overall resilience of terrestrial vegetation to surface water anomalies. The results show that {{{\bf \tau }}_{{{\bf ReS}}} tends to be longer in herbaceous biomes, whereas {{{\bf \tau }}_{{{\bf ReA}}} is longer in biomes with tree cover. Such anticorrelation of {{{\bf \tau }}_{{{\bf ReS}}} and {{{\bf \tau }}_{{{\bf ReA}}} indicates that the herbaceous biomes may be more vulnerable to surface water perturbations during climate extremes. Our study provides a global quantification on vegetation-soil moisture feedbacks-enabling comparison with earth system models.
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However, the current understanding of how the vegetation responds to surface water remains limited since the physical processes happening within the biosphere and hydrosphere are highly coupled. It is even more difficult to measure such interactions for the processes related to surface soil moisture (SSM)-the central variable that interacts the most intimately with vegetation-since the observations of SSM are often scarce and uneven. Here, we use the satellite observations of vegetation optical depth (VOD) and SSM to map the response time scales of vegetation to surface water anomalies. We use the stability theory to derive vegetation memory time (<inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula>) to reveal the global pattern of vegetation memory to surface water anomalies. That is, the time vegetation takes to return back to its equilibrium when an anomaly dissipates to a certain level (e.g., the e-folding level). We also estimate the plant reactive time (<inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula>)-the time when impacts of surface anomaly reach its peak to evaluate the overall resilience of terrestrial vegetation to surface water anomalies. The results show that <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula> tends to be longer in herbaceous biomes, whereas <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula> is longer in biomes with tree cover. Such anticorrelation of <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula> indicates that the herbaceous biomes may be more vulnerable to surface water perturbations during climate extremes. 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We also estimate the plant reactive time (<inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula>)-the time when impacts of surface anomaly reach its peak to evaluate the overall resilience of terrestrial vegetation to surface water anomalies. The results show that <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula> tends to be longer in herbaceous biomes, whereas <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula> is longer in biomes with tree cover. Such anticorrelation of <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula> indicates that the herbaceous biomes may be more vulnerable to surface water perturbations during climate extremes. 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However, the current understanding of how the vegetation responds to surface water remains limited since the physical processes happening within the biosphere and hydrosphere are highly coupled. It is even more difficult to measure such interactions for the processes related to surface soil moisture (SSM)-the central variable that interacts the most intimately with vegetation-since the observations of SSM are often scarce and uneven. Here, we use the satellite observations of vegetation optical depth (VOD) and SSM to map the response time scales of vegetation to surface water anomalies. We use the stability theory to derive vegetation memory time (<inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula>) to reveal the global pattern of vegetation memory to surface water anomalies. That is, the time vegetation takes to return back to its equilibrium when an anomaly dissipates to a certain level (e.g., the e-folding level). We also estimate the plant reactive time (<inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula>)-the time when impacts of surface anomaly reach its peak to evaluate the overall resilience of terrestrial vegetation to surface water anomalies. The results show that <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula> tends to be longer in herbaceous biomes, whereas <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula> is longer in biomes with tree cover. Such anticorrelation of <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReS}}}</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">{{{\bf \tau }}_{{{\bf ReA}}}</tex-math></inline-formula> indicates that the herbaceous biomes may be more vulnerable to surface water perturbations during climate extremes. 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subjects Anomalies
Atmospheric models
Availability
Biosphere
Couplings
Ecosystems
Hydrosphere
Meteorology
Optical analysis
Optical thickness
Perturbation
Perturbation methods
Remote sensing
Resilience
Response time
Satellite observation
Soil
soil measurements
Soil moisture
Soil surfaces
Stability
Surface stability
Surface treatment
Surface water
Surface water availability
Vegetation
Vegetation mapping
Water availability
title Global Patterns of Vegetation Response to Short-Term Surface Water Availability
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