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Enregistrement W2909054580 · doi:10.1111/gcb.14565

Solar‐induced chlorophyll fluorescence exhibits a universal relationship with gross primary productivity across a wide variety of biomes

2019· letter· en· W2909054580 sur OpenAlexaff
Jingfeng Xiao, Xing Li, Binbin He, M. Altaf Arain, Jason Beringer, Ankur R. Desai, Carmen Emmel, David Y. Hollinger, Alisa Krasnova, Ivan Mammarella, Steffen M. Noe, Penélope Serrano-Ortíz, Camilo Rey‐Sánchez, Adrian V. Rocha, Andrej Varlagin

Notice bibliographique

RevueGlobal Change Biology · 2019
Typeletter
Langueen
DomaineEnvironmental Science
ThématiqueAtmospheric and Environmental Gas Dynamics
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésBiomeEddy covariancePrimary productionProductivityAtmospheric sciencesPhotosynthesisChlorophyll fluorescenceEnvironmental sciencePrimary productivityCarbon cycleFlux (metallurgy)MonsoonEcosystemPhysicsEcologyBotanyBiologyMeteorologyChemistry

Résumé

récupéré en direct d'OpenAlex

In our recent study in Global Change Biology (Li et al., 2018), we examined the relationship between solar-induced chlorophyll fluorescence (SIF) measured from the Orbiting Carbon Observatory-2 (OCO-2) and gross primary productivity (GPP) derived from eddy covariance flux towers across the globe, and we discovered that there is a nearly universal relationship between SIF and GPP across a wide variety of biomes. This finding reveals the tremendous potential of SIF for accurately mapping terrestrial photosynthesis globally. In our recent study in Global Change Biology (Li et al., 2018), we examined the relationship between solar-induced chlorophyll fluorescence (SIF) measured from the Orbiting Carbon Observatory-2 (OCO-2) and gross primary productivity (GPP) derived from eddy covariance flux towers across the globe, and we discovered that there is a nearly universal relationship between SIF and GPP across a wide variety of biomes. This finding reveals the tremendous potential of SIF for accurately mapping terrestrial photosynthesis globally. In a letter to the Editor, Zhang, Zhang, Joiner, and Migliavacca (2018) argued that different viewing zenith angles (VZA) of the OCO-2 instrument could impact the SIF-GPP relationship revealed by our recent study. We need to clarify four over- or misinterpretations. In the letter, Zhang et al. (2018) first explained the measurement modes of OCO-2 (i.e., nadir, glint, and target) and called for attention to the effects of VZA (Frankenberg et al., 2014; He, Chen, Liu, Mo, & Joiner, 2017) on SIF magnitude. We recognized the effects of viewing geometries and also demonstrated that with all observations from 64 sites grouped together, there was no significant difference in the mean SIF between the nadir mode and the combined modes (glint/target) (Li et al., 2018). We combined SIF data from all observation modes to examine the universality of the SIF-GPP relationship among eight biomes (Li et al., 2018). In the Letter to the Editor, Zhang et al. (2018) argued that our nearly universal relationship may be complicated by the fact that the three observation modes have different viewing geometries. At an individual site, the observation modes could lead to slightly different slopes. Here we re-examined how the SIF-GPP relationship varies among biomes using the same data as used in our study (Li et al., 2018) but with the SIF observations acquired in the nadir mode only. Our new analysis shows that a nearly universal SIF-GPP relationship among the eight biomes still exists (Figure 1). Although there are view angle effects that require further investigation and may be site specific, our grouped global results appear to be robust regardless of the inclusion or exclusion of observations acquired in the target and/or glint mode. Our study showed that with all data from 64 sites grouped together, there is no significant difference in the slope of the SIF-GPP relationship between nadir and the combined modes (glint/target) (Li et al., 2018). In the letter, Zhang et al. (2018) lumped observations from a number of sites together and found a significant difference between target and nadir (or glint) but not between nadir and glint. The SIF-GPP relationship solely based on observations with high VZA indeed could be different from that based on observations with low VZA as revealed in our earlier study (Li, Xiao, & He, 2018). Observations by the target mode only accounted for a small fraction of the OCO-2 observations and therefore we combined glint and target observations and compared the slopes between nadir and the combined modes (Li et al., 2018). Finally, Zhang et al. (2018) suggested that the slopes could vary significantly among individual sites if a linear fit was forced through the origin following Sun et al. (2017). There is no evidence that the true SIF-GPP relationship at the ecosystem scale should pass through the origin although fitting a model without an intercept is mathematically feasible. Nevertheless, here we revisited the SIF-GPP relationship for each of the eight biomes (Li et al., 2018) using a linear fit without an intercept (Figure 2). Our new analysis clearly shows that there is a universal SIF-GPP relationship across the eight biomes. It is important to recognize that the SIF-GPP relationship at the biome level could be different from that at the site level, particularly given the representativeness of an individual site and a very limited number of observations available at each site. Viewing geometries of the OCO-2 instrument could influence the SIF-GPP relationship at individual sites but do not alter the near universality of the relationship between SIF and GPP across a wide variety of biomes found in our study (Li et al., 2018). This analysis contributes to projects funded by the National Aeronautics and Space Administration (NASA) (Grant No. NNX16AG61G and NNX14AJ18G).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,051
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,024
Tête enseignante GPT0,233
Écart entre enseignants0,210 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations50
Publié2019
Routes d'admission1
Résumé présentoui

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