Optimal stomatal behaviour around the world

Lin, Yan Shih; Medlyn, Belinda E.; Duursma, Remko A.; Prentice, Iain Colin; Wang, Han; Baig, Sofia; Eamus, Derek; Dios, Víctor Resco de; Mitchell, Patrick J.; Ellsworth, David S.; Beeck, Maarten Op de; Wallin, Göran; Uddling, Johan; Tarvainen, Lasse; Linderson, M. L.; Cernusak, Lucas A.; Nippert, Jesse B.; Ocheltree, Troy W.; Tissue, David T.; Martin‐StPaul, Nicolas; Rogers, Alistair; Warren, Jeffrey M.; Angelis, Paolo De; Hikosaka, Kouki; Han, Qingmin; Onoda, Yusuke; Gimeno, Teresa E.; Barton, Craig V. M.; Bennie, Jonathan; Bonal, Damien; Bosc, Alexandre; Löw, Markus; Macinins-Ng, Cate; Rey, Ana; Rowland, Lucy; Setterfield, Samantha A.; Tausz‐Posch, Sabine; Zaragoza‐Castells, Joana; Broadmeadow, M. S. J.; Drake, John E.; Freeman, Michael L.; Ghannoum, Oula; Hutley, Lindsay B.; Kelly, Jeff W. G.; Kikuzawa, Kihachiro; Kolari, Pasi; Koyama, Kohei; Limousin, Jean Marc; Meir, Patrick; Costa, Antonio; Mikkelsen, Teis Nørgaard; Salinas, Norma; Sun, Wei; Wingate, Lisa

doi:10.1038/nclimate2550

Cited by 470 publications

(560 citation statements)

References 30 publications

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“…The values for g 1 , g 1M , and l have been shown to vary severalfold across plant species, communities, and biomes (Lloyd and Farquhar, 1994;Baldocchi and Xu, 2005;Lin et al, 2015). The range of c i /c a is more conservative , but within these narrow limits, there is a systematic global trend toward lower c i /c a (increased water-use efficiency) with lower mean annual precipitation, as indicated by lower D 13 C (Diefendorf et al, 2010).…”

Section: Stomata In Global Models: Empirical and Optimization Approacmentioning

confidence: 99%

“…A similar approach has been taken with CABLE, in which a single value of g 1L is applied Kala et al, 2015). CABLE also has been implemented with Equation 3 for g w and assigning g 1M values according to the plant functional types in Lin et al (2015). It is relatively straightforward to apply this approach also to CLM.…”

Section: Stomata In Global Models: Empirical and Optimization Approacmentioning

confidence: 99%

“…Global trends in leaf gas-exchange capacity and water-use efficiency. Each data point is an individual leaf-level measurement from raw data compiled by Lin et al (2015). A, Global nonlinear relationship between CO 2 assimilation rate (A) and stomatal conductance to water vapor (g w ) for 276 species with C3 photosynthesis from all major biomes.…”

Section: Leaf-scale Simulationsmentioning

confidence: 99%

“…C, Mean g 1 values obtained by fitting the BB model (Eq. 1, assuming g 0 = 0 and c s % c a , as in Lin et al, 2015) to subsets of the data from Lin et al (2015), representing C3 plants (as in A) and C4 plants from a temperate semiarid biome. Data sampled are for the relative humidity (H) range 0.1 to 0.9.…”

Section: Leaf-scale Simulationsmentioning

confidence: 99%

“…When g 1M is reduced to 2.8 (kPa) 0.5 in MED and Kala et al, 2015) and in the CLM4.5 simulations in Figures 9 and 10 below. These values are based on those given by Lin et al (2015) but differ slightly in some cases. Equivalent approximate values are derived from g 1M for l, g 1 , and mean c i /c a using Equations 4, 5, and 9 (25°C, H = 0.8, G* = 40 mmol mol 21 ).…”

Section: Leaf-scale Simulationsmentioning

confidence: 99%

See 4 more Smart Citations

Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models

et al. 2017

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Section: Stomata In Global Models: Empirical and Optimization Approacmentioning

confidence: 99%

Section: Stomata In Global Models: Empirical and Optimization Approacmentioning

confidence: 99%

Section: Leaf-scale Simulationsmentioning

confidence: 99%

Section: Leaf-scale Simulationsmentioning

confidence: 99%

Section: Leaf-scale Simulationsmentioning

confidence: 99%

See 3 more Smart Citations

Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models

et al. 2017

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Evaluating stomatal models and their atmospheric drought response in a land surface scheme: A multibiome analysis

2015

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Stomatal conductance (gs) is a key variable in Earth system models as it regulates the transfer of carbon and water between the terrestrial biosphere and the lower atmosphere. Various approaches have been developed that aim for a simple representation of stomatal regulation applicable at the global scale. These models differ, among others, in their response to atmospheric humidity, which induces stomatal closure in a dry atmosphere. In this study, we compared the widely used empirical Ball-Berry and Leuning stomatal conductance models to an alternative empirical approach, an optimization-based approach, and a semimechanistic hydraulic model. We evaluated these models using evapotranspiration (ET) and gross primary productivity (GPP) observations derived from eddy covariance measurements at 56 sites across multiple biomes and climatic conditions. The different models were embedded in the land surface model JSBACH. Differences in performance across plant functional types or climatic conditions were small, partly owing to the large variations in the observational data. The models yielded comparable results at low to moderate atmospheric drought but diverged under dry atmospheric conditions, where models with a low sensitivity to air humidity tended to overestimate gs. The Ball-Berry model gave the best fit to the data for most biomes and climatic conditions, but all evaluated approaches have proven adequate for use in land surface models. Our findings further encourage future efforts toward a vegetation-type-specific parameterization of gs to improve the modeling of coupled terrestrial carbon and water dynamics

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Canopy and physiological controls of GPP during drought and heat wave

Zhang

Xiao

Zhou

et al. 2016

Geophysical Research Letters

100

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Vegetation indices (VIs) derived from satellite reflectance measurements are often used as proxies of canopy activity to evaluate the impacts of drought and heat wave on gross primary production (GPP) through production efficiency models. However, GPP is also regulated by physiological processes that cannot be directly detected using reflectance measurements. This study analyzes the co‐limitation of canopy and plant physiology (represented by VIs and climate anomalies, respectively) on GPP during the 2003 European summer drought and heat wave for 15 Euroflux sites. During the entire drought period, spatial pattern of GPP anomalies can be quantified by relative changes in VIs. We also find that GPP sensitivity to relative canopy changes is higher for nonforest ecosystems (1.81 ± 0.32%GPP/%enhanced vegetation index), while GPP sensitivity to physiological changes is higher for forest ecosystems (−0.18 ± 0.05 g C m−2 d−1/hPa). A conceptual model is further built to better illustrate the canopy and physiological controls on GPP during drought periods.

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Optimal stomatal behaviour around the world

Cited by 470 publications

References 30 publications

Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models

Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models

Evaluating stomatal models and their atmospheric drought response in a land surface scheme: A multibiome analysis

Canopy and physiological controls of GPP during drought and heat wave

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