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How sensitive are estimates of carbon fixation in agricultural models to input data?

Overview of attention for article published in Carbon Balance and Management, February 2012
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Title
How sensitive are estimates of carbon fixation in agricultural models to input data?
Published in
Carbon Balance and Management, February 2012
DOI 10.1186/1750-0680-7-3
Pubmed ID
Authors

Markus Tum, Franziska Strauss, Ian McCallum, Kurt Günther, Erwin Schmid

Abstract

Process based vegetation models are central to understand the hydrological and carbon cycle. To achieve useful results at regional to global scales, such models require various input data from a wide range of earth observations. Since the geographical extent of these datasets varies from local to global scale, data quality and validity is of major interest when they are chosen for use. It is important to assess the effect of different input datasets in terms of quality to model outputs. In this article, we reflect on both: the uncertainty in input data and the reliability of model results. For our case study analysis we selected the Marchfeld region in Austria. We used independent meteorological datasets from the Central Institute for Meteorology and Geodynamics and the European Centre for Medium-Range Weather Forecasts (ECMWF). Land cover / land use information was taken from the GLC2000 and the CORINE 2000 products.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Germany 1 5%
Unknown 20 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 32%
Researcher 4 18%
Student > Master 3 14%
Student > Doctoral Student 2 9%
Student > Bachelor 2 9%
Other 3 14%
Unknown 1 5%
Readers by discipline Count As %
Earth and Planetary Sciences 6 27%
Environmental Science 3 14%
Agricultural and Biological Sciences 3 14%
Computer Science 2 9%
Engineering 2 9%
Other 5 23%
Unknown 1 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 February 2012.
All research outputs
#15,241,801
of 22,662,201 outputs
Outputs from Carbon Balance and Management
#170
of 236 outputs
Outputs of similar age
#163,554
of 247,240 outputs
Outputs of similar age from Carbon Balance and Management
#5
of 9 outputs
Altmetric has tracked 22,662,201 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 236 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 247,240 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.