Evidence map›Paper›PMID 24661098›Full record

ArticlePlant, cell & environment2014

A fully integrated isoprenoid emissions model coupling emissions to photosynthetic characteristics.

Rüdiger Grote, Catherine Morfopoulos, Ülo Niinemets, Zhihong Sun, Trevor F Keenan, Federica Pacifico, Tim Butler

Abstract read
In one paragraph

Article in Plant, cell & environment, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rüdiger GroteInstitute for Advanced Sustainability Studies (IASS), Berliner Str. 130, Potsdam, 14467, Germany; Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU), Kreuzeckbahnstraße 19, Garmisch-Partenkirchen, 82467, Germany.
Catherine Morfopoulos
Ülo Niinemets
Zhihong Sun
Trevor F Keenan
Federica Pacifico
Tim Butler

Funding

European Research Council 322603
6 · The paper itself

Abstract

The lack of a mechanistic basis has hampered modelling isoprene emission responses to environmental drivers, in particular the simulation of isoprene emissions under different CO₂ concentrations. Here, we advance previous semi-mechanistic model formulations by introducing a model that explicitly links electron availability for other purpose than carbon assimilation (or available energy for secondary metabolism processes; supply-constraint) and enzyme activity (capacity-constraint) to emissions. We furthermore investigate the sensitivity of the model to variations in photosynthetic and emission-specific parameters. By comparing species-specific simulations with experimental data, we demonstrate that differences in photosynthetic characteristics can explain inter-species differences in emissions. Interestingly, the seasonal development of emissions could also be explained to some degree by the change in energy supply from photosynthesis throughout the season. In addition, we show that the principal responses are not limited to isoprene but can be formulated to describe the emission of other light-dependent volatile species. The proposed model is suitable for implementation into regional and global models, particularly those that already provide species-specific photosynthesis estimates.

Indexed as

Models, TheoreticalPlant Physiological PhenomenaButadienesCarbon DioxideComputer SimulationEnvironmentHemiterpenesLightPentanesPhotosynthesisPlant LeavesSecondary MetabolismSpecies SpecificityButadienesCarbon DioxideHemiterpenesisoprenePentanesbiogenic emission modellingenvironmental sensitivitymodel evaluationphotosynthetic electron transport.

Identifiers

PMID24661098
PMCPMC4415481

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.