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A model approach to project the start of egg laying of Great Tit (Parus major L.) in response to climate change

Overview of attention for article published in International Journal of Biometeorology, May 2012
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Title
A model approach to project the start of egg laying of Great Tit (Parus major L.) in response to climate change
Published in
International Journal of Biometeorology, May 2012
DOI 10.1007/s00484-012-0553-7
Pubmed ID
Authors

Frank-M. Chmielewski, Klaus Blümel, Carina Scherbaum-Heberer, Bettina Koppmann-Rumpf, Karl-Heinz Schmidt

Abstract

The aim of this study was to select a phenological model that is able to calculate the beginning of egg laying of Great Tit (Parus major) for both current and future climate conditions. Four models (M1-M4) were optimised on long-term phenological observations from the Ecological Research Centre Schlüchtern (Hessen/Germany). Model M1 was a common thermal time model that accumulates growing degree days (GDD) on an optimised starting date t (1). Since egg laying of Great Tit is influenced not only by air temperature but also by photoperiod, model M1 was extended by a daylength term to give M2. The other two models, M3 and M4, correspond to M1 and M2, but t (1) was intentionally set to 1 January, in order to consider already rising temperatures at the beginning of the year. A comparison of the four models led to following results: model M1 had a relatively high root mean square error at verification (RMSE(ver)) of more than 4 days and can be used only to calculate the start of egg laying for current climate conditions because of the relatively late starting date for GDD calculation. The model failed completely if the starting date was set to 1 January (M3). Consideration of a daylength term in models M2 and M4 improved the performance of both models strongly (RMSE(ver) of only 3 days or less), increased the credibility of parameter estimation, and was a precondition to calculate reliable projections in the timing of egg laying in birds for the future. These results confirm that the start of egg laying of Great Tit is influenced not only by air temperature, but also by photoperiod. Although models M2 and M4 both provide comparably good results for current climate conditions, we recommend model M4-with a starting date of temperature accumulation on 1 January-for calculating possible future shifts in the commencement of egg laying. Our regional projections in the start of egg laying, based on five regional climate models (RCMs: REMO-UBA, ECHAM5-CLM, HadCM3-CLM, WETTREG-0, WETTREG-1, GHG emission scenario A1B), indicate that in the near future (2011-2040) no significant change will take place. However, in the mid- (2041-2070) and long-term (2071-2100) range the beginning of egg laying could be advanced significantly by up to 11 days on average of all five RCMs. This result corresponds to the already observed shift in the timing of egg laying by about 1 week, due mainly to an abrupt increase in air temperature at the end of the 1980s by 1.2 K between April and May. The use of five regional climate scenarios additionally allowed to estimate uncertainties among the RCMs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 23%
Student > Master 5 16%
Professor 4 13%
Student > Bachelor 3 10%
Student > Ph. D. Student 3 10%
Other 5 16%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 42%
Environmental Science 6 19%
Earth and Planetary Sciences 3 10%
Biochemistry, Genetics and Molecular Biology 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 1 3%
Unknown 6 19%
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 17 February 2013.
All research outputs
#17,062,731
of 25,074,338 outputs
Outputs from International Journal of Biometeorology
#1,061
of 1,377 outputs
Outputs of similar age
#110,221
of 168,913 outputs
Outputs of similar age from International Journal of Biometeorology
#8
of 8 outputs
Altmetric has tracked 25,074,338 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,377 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
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