A simple method to estimate capture height biases at landbird banding stations: opportunities and limitations
Data files
Nov 07, 2023 version files 59.15 KB
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height.binomial.txt
130 B
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README.md
2.11 KB
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TattoniLaBarbera2023.csv
56.91 KB
Abstract
Mist-nets are one of the most important tools for the capture of wild birds in ornithological research. The probability of capturing birds may vary by net height, which may drive capture biases. Such biases are rarely estimated, likely because of the relatively high cost and effort associated with constructing and operating elevated mist-net rigs where multiple mist-nets are stacked above one another. Therefore, a low-cost and -effort method to collect capture height data may allow broader investigation and better accounting of potential bias in existing banding protocols. Here, we investigate whether recording net panel of capture (with net panels indicating capture height, e.g., “upper panel”) in ground-level mist-nets provides sufficient information to estimate capture height biases and compare these estimations to those obtained with traditional elevated mist-net rigs. Of the 29 taxa analyzed, we detected elevated capture biases for 11 (37.9%) and ground-level capture biases for seven (24.1%). When compared to estimates derived from elevated mist-net rigs at the same study site, we found high agreement with ground-level biases (75.0%) and low agreement with elevated biases (23.1%). These results suggest panel height of ground-level nets is a reliable method to estimate ground-level biases; however, scale of sampling may influence elevated biases, particularly for species that center their activity at the mid-story. Recording panel height may be quickly integrated into a station’s processing protocols and broader application may improve our understanding of these biases.
README: A simple method to estimate capture height biases at landbird banding stations: opportunities and limitations
https://doi.org/10.5061/dryad.zw3r228f4
Description of the data and file structure
The csv file "TattoniLaBarbera2023.csv" contains all the data required to recreate the analyses in this paper. There are four fields: id, species_code, and net_panel, and height. Fields in our dataset not relevant/required for the analyses in this paper have been removed from this publicly available dataset. Individuals who wish to access the full dataset should contact the San Francisco Bay Bird Observatory Landbird Program (klabarbera@sfbbo.org).
Field Descriptions:
- id: this is a unique numeric identifier for every banded bird in our dataset
- species_code: four letter code that abbreviates the English name for each species. These codes come from the USGS Bird Banding Lab and can be found here.
- net_panel: indicates the net panel that a bird was captured in from a standard four-paneled mist-net. L = lower, LM = lower-middle, UM = upper-middle, and U = upper.
- height: binary indicator variable for the binomial analysis where x = 1 was assigned to lower and lower-middle panel captures and x = 0 was assigned to upper-middle and upper panel captures.
The text file "height.binomial.txt" is the model written in the BUGS language for the analysis. There are two data inputs needed to run this model: n and x. n is the total number of individuals in a species, and x is the height variable from the CSV file. This model can be run using the R script described below.
Sharing/Access information
Contact the San Francisco Bay Bird Observatory Landbird Program (klabarbera@sfbbo.org) for further data information.
Code/Software
The file "TattoniLaBarbera2023.R" contains all the code needed to recreate the analyses presented in this paper. Make sure the txt file of the BUGS model exists in your working directory. Contact D. Julian Tattoni (davidtattoni@gmail.com or jtattoni@ucdavis.edu for questions on code usage).