Automated Author ProfileSprau, Philipp
Ludwig-Maximilians-Universität München
Sprau, Philipp
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: 3.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
1: Numerous studies over the past decade have reported correlations between elevated levels of anthropogenic noise and a rise in the minimum frequency of acoustic signals of animals living in noisy habitats. This pattern appears to be occurring globally, and higher pitched signals have been hypothesized to be adaptive changes that reduce masking by low-frequency traffic noise. However, the sound analysis methods most often used in these studies are prone to measurement errors that can result in false positives. In addition, the commonly used method of measuring frequencies visually from spectrograms might also lead to observer-expectancy biases that could exacerbate measurement errors. 2: We conducted an experiment to (a) quantify the size and type of errors that result from “eye-balling” frequency measurements with cursors placed manually on spectrograms of signals recorded in noise and no-noise conditions, and (b) to test whether observer expectations lead to significant errors in frequency measurements. We asked 54 volunteers, blind to the true intention of our study, to visually measure the minimum frequency of a variety of natural and synthesized bird sounds, recorded either in noise, or no-noise conditions. Test subjects were either informed or uninformed about the hypothesized results of the measurements. 3: Our results demonstrate that inappropriate methodology in acoustic analysis can yield false positives with effect sizes as large, or even larger, than those reported in published studies. In addition to these measurement artefacts, psychological observer biases also led to false positives – when observers expected signals to have higher minimum frequencies in noise, they measured significantly higher minimum frequencies than uninformed observers, who had not been primed with any expectation. 4: The use of improper analysis methods in bioacoustics can lead to the publication of spurious results. We discuss alternative methods that yield unbiased frequency measures and we caution that it is imperative for researchers to familiarize themselves both with the functions and limitations of their sound analysis programs.. In addition, observer expectancy biases are a potential source of error not only in the field of bioacoustics, but in any situation where measurements can be influenced by human subjectivity.
Authors
- Brumm, Henrik ;
- Zollinger, Sue Anne ;
- Niemelä, Petri T. ;
- Sprau, Philipp
Optimal life-history decisions are shaped by prevailing environmental conditions. In the context of urbanization, environmental differences between urban and rural areas are known to vary across a multitude of axes. The relative roles of specific axes and whether they explain variation in avian life histories between forest and city populations have not often been studied empirically. This study comprehensively views urbanization from a multidimensional environmental perspective. For each of 13 nest box plots of a common passerine bird (the great tit Parus major), we quantified temperature, humidity, light, and noise, and subsequently assessed direct versus indirect effects of each environmental axis on components of annual reproductive success by applying a path analytical framework. All quantified environmental axes, and life-history traits, showed substantial repeatable variation between the plots. Forest and city plots differed tremendously in temperature, humidity, and light. We were able to attribute among-population variation in life history to variation in these environmental effects. However, the simple dichotomy between forest and city populations explained the data best. Birds in the city laid earlier, which indirectly resulted in smaller clutches, and their offspring fledged in poorer condition, compared to conspecifics in forests. Those differences persisted after controlling for temperature, humidity, light, and noise, which implies that they were shaped by other factors than the ones quantified in this study. In summary, our findings question the common interpretation that differences between forest and city areas relate to specific environmental axes that covary with urbanization, especially in in lieu of quantitative measurements.
Authors
- Sprau, Philipp ;
- Mouchet, Alexia ;
- Dingemanse, Niels J.