Evidence map›Paper›PMID 32985502›Full record

ArticleScientific data2020

Vegetation traits of pre-Alpine grasslands in southern Germany.

Anne Schucknecht, Alexander Krämer, Sarah Asam, Abraham Mejia-Aguilar, Noelia Garcia-Franco, Max A Schuchardt, Anke Jentsch, Ralf Kiese

Abstract readDataset
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning.International journal of applied earth observation and geoinformation : ITC journal · 2022
    Article
  2. Article
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

8 authors.

Anne SchucknechtKarlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research - Atmospheric Environmental Research (IMK-IFU), Garmisch-Partenkirchen, Germany. anne.schucknecht@kit.edu.
Alexander KrämerWWL Umweltplanung und Geoinformatik GbR, Bad Krozingen, Germany.
Sarah AsamGerman Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, Germany.
Abraham Mejia-AguilarEurac Research, Center for Sensing Solutions, Bolzano, Italy.
Noelia Garcia-FrancoTechnical University of Munich, TUM School of Life Sciences Weihenstephan, Chair of Soil Science, Freising, Germany.
Max A SchuchardtUniversity of Bayreuth, Bayreuth Center of Ecology and Environmental Research (Bayceer), Chair of Disturbance Ecology, Bayreuth, Germany.
Anke JentschUniversity of Bayreuth, Bayreuth Center of Ecology and Environmental Research (Bayceer), Chair of Disturbance Ecology, Bayreuth, Germany.ORCID http://orcid.org/0000-0002-2345-8300
Ralf KieseKarlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research - Atmospheric Environmental Research (IMK-IFU), Garmisch-Partenkirchen, Germany.

Funding

Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 031B0027ABundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 031B0027BBundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 031B0027EBundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 031B0516CBundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 031B0516FEC | European Regional Development Fund (Europski Fond za Regionalni Razvoj) ERDF1094
6 · The paper itself

Abstract

The data set contains information on aboveground vegetation traits of > 100 georeferenced locations within ten temperate pre-Alpine grassland plots in southern Germany. The grasslands were sampled in April 2018 for the following traits: bulk canopy height; weight of fresh and dry biomass; dry weight percentage of the plant functional types (PFT) non-green vegetation, legumes, non-leguminous forbs, and graminoids; total green area index (GAI) and PFT-specific GAI; plant water content; plant carbon and nitrogen content (community values and PFT-specific values); as well as leaf mass per area (LMA) of PFT. In addition, a species specific inventory of the plots was conducted in June 2020 and provides plot-level information on grassland type and plant species composition. The data set was obtained within the framework of the SUSALPS project ("Sustainable use of alpine and pre-alpine grassland soils in a changing climate"; https://www.susalps.de/ ) to provide in-situ data for the calibration and validation of remote sensing based models to estimate grassland traits.

Indexed as

BiomassGrasslandPlantsCarbonGermanyNitrogenSoilCarbonNitrogenSoil

Identifiers

PMID32985502
PMCPMC7522989

What OpenQuestion holds

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Registered trials

None linked

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.