Automated Author ProfileRaby, Graham D.
University of Windsor
Raby, Graham D.
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: 2.2 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Aquatic chemical ecology is an important and growing field of research that involves understanding how organisms perceive and respond to chemical cues in their environment. Research assessing the preference or avoidance of a water source containing specific chemical cues has increased in popularity in recent years, and a variety of methods have been described in the scientific literature. Two-current choice flumes have seen the greatest increase in popularity, perhaps because of their potential to address the broadest range of research questions. Here, we review the literature on two-current choice flumes and show that there is a clear absence of standardized methodologies that make comparisons across studies difficult. Some of the main issues include turbulent flows that cause mixing of cues, inappropriate size of choice arenas for the animals, short experiments with stressed animals, failure to report how experiment and researcher biases were eliminated, general underreporting of methodological details, underutilization of collected data and inappropriate data analyses. In this review, we present best practice guidelines on how to build, test and use two-current choice flumes to measure the behavioural responses of aquatic animals to chemical cues, and provide blueprints for flume construction. The guidelines include steps that can be taken to avoid problems commonly encountered when using two-current choice flumes and analysing the resulting data. This review provides a set of standards that should be followed to ensure data quality, transparency and replicability in future studies in this field.
Authors
- Jutfelt, Fredrik ;
- Sundin, Josefin ;
- Raby, Graham D. ;
- Krång, Anna-Sara ;
- Clark, Timothy D.