Climate and Vegetation Drivers of Terrestrial Carbon Fluxes: A Global Data Synthesis

Chen, Shutao; Zou, Jianwen; Hu, Zhenghua; Lu, Yanyu

doi:10.1007/s00376-019-8194-y

Cited by 27 publications

(27 citation statements)

References 79 publications

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“…Mallick et al (2018) showed that vegetation control on evapotranspiration was stronger in arid ecosystems compared with the mesic ecosystems. Similar results were found for dry and wet Amazonian forest (Costa et al, 2010;Mallick et al, 2016) and dry and wet grassland (De Kauwe et al, 2017). Ferguson et al (2012) studied landatmosphere coupling of fluxes, which includes the effect of vegetation as well as other factors such as soil wetness, soil texture, and surface temperature.…”

Section: Introductionsupporting

confidence: 62%

Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

et al. 2020

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Abstract. Vegetation regulates the exchange of water, energy, and carbon fluxes between the land and the atmosphere. This regulation of surface fluxes differs with vegetation type and climate, but the effect of vegetation on surface fluxes is not well understood. A better knowledge of how and when vegetation influences surface fluxes could improve climate models and the extrapolation of ground-based water, energy, and carbon fluxes. We aim to study the link between vegetation and surface fluxes by combining the yearly average MODIS leaf area index (LAI) with flux tower measurements of water (latent heat), energy (sensible heat), and carbon (gross primary productivity and net ecosystem exchange). We show that the correlation of the LAI with water and energy fluxes depends on the vegetation type and aridity. Under water-limited conditions, the link between the LAI and the water and energy fluxes is strong, which is in line with a strong stomatal or vegetation control found in earlier studies. In energy-limited forest we found no link between the LAI and water and energy fluxes. In contrast to water and energy fluxes, we found a strong spatial correlation between the LAI and gross primary productivity that was independent of vegetation type and aridity. This study provides insight into the link between vegetation and surface fluxes. It indicates that for modelling or extrapolating surface fluxes, the LAI can be useful in savanna and grassland, but it is only of limited use in deciduous broadleaf forest and evergreen needleleaf forest to model variability in water and energy fluxes.

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Section: Introductionsupporting

confidence: 62%

Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

et al. 2020

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“…Other studies however found a weak link between LAI and GPP for annual time scales (Law et al, 2002). The link between NEE and LAI was less strong as for GPP, which is in agreement with results of Chen et al (2019). NEE is the sum of carbon uptake by the vegetation (GPP) and carbon loss by ecosystem respiration.…”

Section: Discussionsupporting

confidence: 90%

“…Zooming out from stomatal to canopy scale, there are several other ways in which vegetation influences surface fluxes. Soil and crown mutual shadowing and deep ground water uptake by vegetation influence the latent heat flux whereas soil moisture influences ecosystem respiration and thereby carbon exchange (Chen et al, 2019;Schmitt et al, 2010). The large-scale vegetation control of ecosystem fluxes has been shown by different data or modelling studies and depends on climate and vegetation type (Williams et al, 2012;Xu et al, 2013;Wagle et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Examining the link between vegetation leaf area and land-atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

Dijke¹,

Mallick²,

Schlerf³

et al. 2020

Preprint

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<p><strong>Abstract.</strong> Vegetation regulates the exchange of water, energy, and carbon fluxes between the land and the atmosphere. This regulation of surface fluxes differs with vegetation type and climate, but the effect of vegetation on surface fluxes is not well understood. A better knowledge of how and when vegetation influences surface fluxes could improve climate models and the extrapolation of ground-based water, energy, and carbon fluxes. We aim to study the large-scale link between vegetation and surface fluxes by combining MODIS leaf area index with flux tower measurements of water (latent heat), energy (sensible heat), and carbon (gross primary productivity and net ecosystem exchange). We show that the correlation between leaf area index and water and energy fluxes depends on vegetation and aridity. In water-limited conditions, the link between vegetation and water and energy fluxes is strong, which is in line with a strong stomatal or vegetation control found in earlier studies. In energy-limited forest we found no vegetation control on water and energy fluxes. In contrast to water and energy fluxes, we found a strong correlation between leaf area index and gross primary productivity that was independent of vegetation type and aridity index. This study provides insight in the large-scale link between vegetation and surface fluxes. The study indicates that for modelling or extrapolating large-scale surface fluxes, LAI can be useful in savanna and grassland, but only of limited use in deciduous broadleaf forest and evergreen needleleaf forest.</p>

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“…Site B is an uneven-aged dense forest stand, and the mean dominant tree height is approximately 29 m (Table 1). Since tree height can be used as a proxy of gross primary production (GPP), the high SR rate in site B could be attributed to high GPP [9,29,66,77,78,79], which can provide substrates for root and microbial respiration through photosynthesis [66,80]. This finding is confirmed by LMMs and correlation test evidencing a significant positive relation between SR ref and mean dominated tree height, therefore indicating that, after removing the effect of temperature, productivity results in one of the main factors affecting SR.…”

Section: Discussionmentioning

confidence: 99%

Soil respiration variation along an altitudinal gradient in Italian Alps: Disentangling forest structure and temperature effects

Badraghi

Ventura

Polo

et al. 2021

Preprint

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To understand the main determinants of soil respiration (SR), we investigated the changes of soil respiration and soil physicochemical properties, including soil carbon (C) and nitrogen (N), root C and N, litter C and N, soil bulk densities and soil pH at five forest sites, along an elevation/temperature gradient (404 to 2101 m a.s.l) in Northern Italy, where confounding factors such as aspect and soil parent material are minimized, but an ample variation in forest structure and composition is present. Our result indicated that SR rates increased with temperature in all sites, and about 55% - 76% of SR was explained by temperature. Annual cumulative SR, ranging between 0.65 and 1.40 kg C m-2 yr-1, declined along the elevation gradient, while temperature sensitivity (Q10) of SR increased with elevation. However, a high SR rate (1.27 kg C m-2 yr-1) and low Q10 were recorded in the old conifer forest stand at 1731 m a.s.l., characterized by a complex structure and high productivity, introducing nonlinearity in the relations with elevation and temperature. Reference SR at the temperature of 10°C (SRref) was not related to elevation. A significant linear negative relationship was found for bulk density with elevation. On the contrary, soil C, soil N, root C, root N, pH and litter mass were better fitted by nonlinear relations with elevation. However, it was not possible to confirm a significant correlation of SR with these parameters once the effect of temperature has been removed (SRref). These results show how the main factor affecting SR in forest ecosystems along this Alpine elevation gradient is temperature, but its regulating role can be strongly influenced by site biological characteristics, particularly vegetation type and structure. This study also confirms that high elevation sites are rich in C stored in the soil and also more sensitive to climate change, being prone to high carbon losses as CO2. Conversely, forest ecosystems with a complex structure, with high SRref and moderate Q10, can be more resilient.

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Climate and Vegetation Drivers of Terrestrial Carbon Fluxes: A Global Data Synthesis

Cited by 27 publications

References 79 publications

Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

Examining the link between vegetation leaf area and land-atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

Soil respiration variation along an altitudinal gradient in Italian Alps: Disentangling forest structure and temperature effects

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