Automated Author ProfileCepák, Jaroslav
Natural History Museum Prague
Cepák, Jaroslav
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.0 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Ongoing climate changes represent a major determinant of demographic processes in many organisms worldwide. Birds, and especially long-distance migrants, are particularly sensitive to such changes. To better understand these impacts on long-distance migrants’ breeding productivity, we tested three hypotheses focused on (i) the shape of the relationships with different climate variables, including previously rarely tested quadratic responses, and on regional differences in these relationships predicted by (ii) mean climatic conditions and (iii) by the rate of climate change in respective regions ranging from Spain to Finland. We calculated breeding productivity from constant effort ringing sites from 11 European countries covering 34 degrees of latitude, and extracted temperature- and precipitation-related climate variables from E-OBS and NASA MODIS datasets. To test our hypotheses, we fitted GLMM and Bayesian meta-analytic models. We revealed hump-shaped responses of productivity to temperature, growing degree-days, green-up onset date, and precipitation anomaly, and negative responses to intense and prolonged rains across the regions. The effects of March temperature and April growing degree-days were more negative in cold than in warm regions, except that one with the highest accumulated heat, whereas increasing June precipitation anomalies were associated with higher productivity in both dry and wet regions. The rate of climate warming was unrelated to productivity responses to climate. The influence of climate on bird productivity proved to be frequently non-linear, as expected by ecological theory. To explain the differences between regions, the rate of climate change is less important than regional interannual variability in climate (which is predicted to increase), but this may change with the progression of climate change in the future. Productivity declines in long-distance migratory songbirds are particularly expected if out-of-norm water excess increases in frequency or strength.
Authors
- Hanzelka, Jan ;
- Telenský, Tomáš ;
- Koleček, Jaroslav ;
- Procházka, Petr ;
- Robinson, Robert A. ;
- Baltà, Oriol ;
- Cepák, Jaroslav ;
- Gargallo, Gabriel ;
- Henry, Pierre-Yves ;
- Henshaw, Ian ;
- van der Jeugd, Henk ;
- Karcza, Zsolt ;
- Lehikoinen, Petteri ;
- Meister, Bert ;
- Nebot, Arantza Leal ;
- Piha, Markus ;
- Thorup, Kasper ;
- Tøttrup, Anders P. ;
- Reif, Jiří