ISS observations offer insights into plant function

Stavros, E. Natasha; Schimel, David; Pavlick, Ryan; Serbin, Shawn P.; Swann, Abigail L. S.; Duncanson, Laura; Fisher, Joshua B.; Fassnacht, Fabian Ewald; Ustin, Susan L.; Dubayah, R.; Schweiger, Anna K.; Wennberg, P. O.

doi:10.1038/s41559-017-0194

Cited by 116 publications

(109 citation statements)

References 12 publications

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“…AVIRIS, Serbin et al ., ), and the suite of current and planned space‐borne platforms (e.g. EnMAP, Guanter et al ., ; HISUI, Stavros et al ., ; Surface Biology and Geology mission, National Academies of Sciences E, Medicine, ). Imaging spectroscopy, if successful in capturing V c,max25 –age relationships at canopy scales, will greatly advance our capability to monitor and mechanistically understand V c,max25 variability across both space and time, providing critically important datasets to parameterize and evaluate ESMs.…”

Section: Discussionmentioning

confidence: 99%

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Rogers

Albert

et al. 2019

New Phytologist

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Summary Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (Vc,max) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting Vc,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of Vc,max was tested. Vc,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict Vc,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts Vc,max of mature leaves in Panamanian tropical forests (R2 = 0.90). However, this single‐age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for Vc,max and leaf age enabled construction of the Vc,max–age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in Vc,max, assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize Vc,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models.

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Section: Discussionmentioning

confidence: 99%

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Rogers

Albert

et al. 2019

New Phytologist

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“…unprecedented insights into canopy structure and the vertical distribution of aboveground biomass, even in the most challenging tropical and dense temperate forests (Stavros et al, 2017). unprecedented insights into canopy structure and the vertical distribution of aboveground biomass, even in the most challenging tropical and dense temperate forests (Stavros et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Canopy height explains species richness in the largest clade of Neotropical lianas

Meyer

Diniz‐Filho

Lohmann

et al. 2019

Global Ecol Biogeogr

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Aim Tall and structurally complex forests can provide ample habitat and niche space for climbing plants, supporting high liana species richness. We test to what extent canopy height (as a proxy of 3‐D habitat structure), climate and soil interact to determine species richness in the largest clade of Neotropical lianas. We expect that the effect of canopy height on species richness is higher for lianas from closed tropical rain forests compared to riparian and savanna habitats. Location Neotropics. Time period Present. Major taxa studied Tribe Bignonieae (Bignoniaceae). Methods We used structural equation models to evaluate direct and indirect effects of canopy height, climate (temperature, precipitation and precipitation seasonality), and soil (cation exchange capacity and soil types) on overall Bignonieae species richness (339 liana species), as well as on species richness of lianas from forest, riparian and savanna habitats, respectively. We further performed multiple regression models with Moran's eigenvector maps to account for spatial autocorrelation. Results Canopy height was a key driver of liana species richness, in addition to climate and soil. Species richness of forest lianas showed a strong positive relationship with canopy height whereas the relationship was less pronounced for riparian species. Richness of savanna species decreased with increasing canopy height. Climate also explained a substantial proportion of variation in liana species richness whereas soil variables showed little explanatory power. Main conclusions The relationship between canopy height and liana species richness differs among habitats. While forest and riparian lianas benefit from tall and complex habitats that provide physical support to reach the canopy to escape low light availability in the understorey, high light availability in open habitats and an increased risk of embolism of conductive vessels for lianas with long stems living in areas with high seasonality might explain the inverse relationship between species richness and canopy height in savannas.

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“…LUE cannot be directly observed, but can be approximated by measuring changes in fAPAR and GPP. It follows then that satellite LAI and/or fAPAR estimates could be combined with independent records of vegetation production derived from satellite VOD and/or SIF to directly constrain LUE (Stavros et al ., ; Fischer et al ., ).…”

Section: Satellite Observations Can Constrain Direct and Indirect Effmentioning

confidence: 99%

Constraining estimates of terrestrial carbon uptake: new opportunities using long‐term satellite observations and data assimilation

et al. 2019

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Summary The response of terrestrial carbon uptake to increasing atmospheric [CO2], that is the CO2 fertilization effect (CFE), remains a key area of uncertainty in carbon cycle science. Here we provide a perspective on how satellite observations could be better used to understand and constrain CFE. We then highlight data assimilation (DA) as an effective way to reconcile different satellite datasets and systematically constrain carbon uptake trends in Earth System Models. As a proof‐of‐concept, we show that joint DA of multiple independent satellite datasets reduced model ensemble error by better constraining unobservable processes and variables, including those directly impacted by CFE. DA of multiple satellite datasets offers a powerful technique that could improve understanding of CFE and enable more accurate forecasts of terrestrial carbon uptake.

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ISS observations offer insights into plant function

Cited by 116 publications

References 12 publications

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Canopy height explains species richness in the largest clade of Neotropical lianas

Constraining estimates of terrestrial carbon uptake: new opportunities using long‐term satellite observations and data assimilation

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