DOI: 10.5061/dryad.h9w0vt4s4
title: Data from: Biogeographical patterns in the seasonality of bird collisions with aircraft

description: Bird collisions with aircraft pose a serious threat to human safety.
 However, broad-scale patterns in how bird strikes might vary through space
 and time have yet to be fully understood. Here, we conducted a
 biogeographical study of bird strikes to answer two questions: (1) Are
 bird strikes higher at certain times of the year in the Northern and
 Southern Hemispheres? and (2) Is seasonality in bird strikes more
 prominent in the Northern Hemisphere than in the Southern Hemisphere? We
 collated data on monthly bird strikes from 122 airports across the globe
 and used circular statistics to test for hemispherical asymmetries in the
 circular mean and variance in bird strikes. Results showed that annual
 peaks in bird strikes occurred between late summer to autumn seasons, and
 as a result, they occurred at opposite times of year in the northern and
 southern hemispheres. Results also showed that bird strikes were more
 seasonal in the Northern Hemisphere than the Southern Hemisphere, where
 strikes tended to occur more consistently throughout the year. 
 Practical implications Overall results indicate that avian collisions with
 aircraft show strong biogeographic patterning, concomitant with global
 patterns in bird breeding seasons and migration tendencies.
description: We focused on bird strikes instead of all wildlife strikes since
 birds strikes have resulted in considerably more human fatalities (Avisure
 2024), thus posing a larger threat to human safety than strikes with other
 groups. We searched the Google Web, Google Scholar, and Web of Science
 search engines for data on monthly bird strikes at airports using the
 keywords ‘bird strike’ with ‘airport’, ‘seasonal’, ‘monthly’ and ‘annual’.
 The language settings allowed for search results in any language. We
 included sources that reported bird strikes in each calendar month over a
 minimum of 12 months at individual airports. The data availability ranged
 from one year to 20 years (Table S1). Monthly data from studies conducted
 over multiple years were averaged for each month among years prior to
 analyses. Apart from online sources, data for Wellington Airport were
 obtained via personal communication with airport personnel. Studies that
 reported either yearly bird strikes for individual airports, or monthly
 bird strikes for entire countries did not match the spatial and/or
 temporal resolution of this study and hence were not included. Data on
 strikes with non-avian species (bats, non-volant mammals, reptiles) were
 also not included. We restricted our data sources to those available via
 web search for logistical reasons (except for the Wellington data, to
 which we had access prior to commencing the study).
 Given that time is a ‘non-linear’ variable, we used circular
 statistics to analyze the data (Berens 2009). In this instance, the circle
 is used to represent one cycle (i.e. one calendar year), and we analyze
 the timing of an event within this cycle (i.e. occurrences of high bird
 strikes, see Jammalamadaka and Sengupta 2001). Seasonality in bird strikes
 was assessed using the temporal scale of months of the year. Each month
 occupied 30° on the circular plot starting with January by convention and
 going clockwise. The monthly strike frequency data were visualized using
 circular plots called rose diagrams (circular frequency distributions).
 Seasons were classified generally as December-January-February being
 boreal winter and austral summer, March-April-May being boreal spring and
 austral autumn, June-July-August being boreal summer and austral winter,
 and September-October-November being boreal autumn and austral
 spring. For some airports, bird strikes were reported
 as number of strikes in each month, while others used ‘strike rates’
 (typically strikes/10,000 flight movements) accounting for aircraft
 movements. We converted the strike frequencies to angles (in degrees)
 prior to analyses using the <em>circular</em> package in R to
 make them comparable across airports (Agostinelli and Lund 2022, R Core
 Team 2022). For each airport, we calculated two metrics to characterize
 the annual distribution of bird strikes: 1) angle of mean vector (in
 degrees, 0°-360°), a measure of central tendency, to identify the time of
 year with overall high bird strikes (referred to in this study as timing
 of ‘peak strikes’), and 2) circular standard deviation, a measure of
 dispersion of the bird strikes around the mean (as per Ting et al. 2008).
 These values were then used to calculate the overall angles of mean vector
 and circular standard deviations to identify the month with the highest
 bird strikes for the Northern and Southern Hemispheres. The angle of the
 mean vector represents the timing of peak strikes for each airport and
 corresponds to the direction of the vector arrow on the circular plot.
 Circular standard deviation represents the spread of the strikes around
 the mean, and is inversely related to the length of the vector (see Wright
 and Calderon 1995, Ting et al. 2008). A high circular standard deviation
 would indicate that the strikes are more dispersed around the mean, while
 a low circular standard deviation would indicate that strikes are less
 dispersed around the mean, and thus, more seasonal. To
 answer the first question of whether bird strikes were higher at certain
 times of the year, we used the angles of mean vector for each airport to
 calculate the overall angles of mean vector and circular standard
 deviations for the Northern and Southern Hemispheres. The month of peak
 bird strikes for each hemisphere was determined by back-calculating the
 angle of mean vector to the corresponding month (January for values
 between 0° and 30°, February between 30° and 60°, and so on). Rayleigh’s
 Test of Uniformity was conducted to assess if the strikes were uniformly
 distributed throughout the year for each hemisphere. The means of the
 distributions of strikes in both hemispheres were compared using
 Watson-William’s Test of Homogeneity of Means (see Pewsey et al.
 2013). To answer the second question of whether the
 annual spread of bird strikes differed between hemispheres, we conducted
 linear regression analyses to assess the relationship of circular standard
 deviations at individual airports with latitude in both hemispheres.
 Additionally, we conducted Welch’s t-test on the circular standard
 deviations between hemispheres to test for overall hemispherical
 differences in annual dispersions of strikes. Analyses and visualizations
 were conducted in the R environment using <em>circular</em>
 and <em>ggplot2</em> packages, respectively (Wickham 2016,
 Agostinelli and Lund 2022, R Core Team 2022).
description: # Biogeographical patterns in bird collisions with aircraft
 [https://doi.org/10.5061/dryad.h9w0vt4s4](https://doi.org/10.5061/dryad.h9w0vt4s4) This dataset contains previously published data on bird strikes at airports around the world. Data sources are listed below. ## Description of the data and file structure In the .csv file attached, the monthly bird strikes for each location are provided along with the coordinates, duration of study, angles of mean vector, circular standard deviations and data sources. ## Sharing/Access information Data was derived from the following sources: * Aas, C. K., Bentz. P. G., & Stenman, O. (2003). The Nordic Bird Strike Advisory Group – A Short Presentation. Bird Strike Committee Europe. [https://canadianbirdstrike.ca/wp-content/uploads/2018/02/Aas_et_al_2003_0.pdf](https://canadianbirdstrike.ca/wp-content/uploads/2018/02/Aas_et_al_2003_0.pdf) * Anagnostopoulos, A. (2003). Bird strike risk assessment for Athens International Airport. Management report, Environmental Department, Aviation Services Division, Athens International Airport. Athens, Greece. [http://www.aerohabitat.eu/uploads/media/BIRDSTRIKE_RISK_ASSESSMENT.pdf](http://www.aerohabitat.eu/uploads/media/BIRDSTRIKE_RISK_ASSESSMENT.pdf) * Arshad, S., Malik, A. M., & Hussain, I. (2019). Wildlife hazard and airports, an empirical analysis of bird strikes at Benazir International Airport, Islamabad, Pakistan. Pakistan Journal of Agricultural Research, 32(4), 572-578. [http://dx.doi.org/10.17582/journal.pjar/2019/32.4.572.578](http://dx.doi.org/10.17582/journal.pjar/2019/32.4.572.578) * Australian Transport Safety Bureau (ATSB). (2008). An analysis of Australian birdstrike occurrences 2002 to 2006. ATSB Transport Safety Investigation Report, Aviation Research and Analysis Report AR-2008-027. Australian Transport Safety Bureau, Canberra, ACT, Australia. * Chilvers, B. L., Ryan, C. J., & Hickling, G. J. (1997). Factors affecting pilot-reported bird-strike rates at Christchurch International Airport, New Zealand. New Zealand Journal of Zoology, 24(1), 1-7. [https://doi.org/10.1080/03014223.1997.9518100](https://doi.org/10.1080/03014223.1997.9518100) * Dukiya, J. J., & Gahlot, V. (2013). An evaluation of the effects of bird strikes on flight safety operations at international airport. International Journal for Traffic and Transport Engineering, 3(1), 16-33. [http://dx.doi.org/10.7708/ijtte.2013.3(1).02](http://dx.doi.org/10.7708/ijtte.2013.3\(1\).02) * Federal Aviation Administration Wildlife Strike Database, 2023. Available online: [https://wildlife.faa.gov/home](https://wildlife.faa.gov/home) (accessed on 5th May 2023) * Froneman, A., & van Rooyen, M. (2003). The successful implementation of a border collie bird scaring program at Durban International Airport, South Africa. Proceedings of the international bird strike committee, Warsaw, Poland, 5-9. * Fu, Q., Wang, N., Shen, M., Song, N., & Yan, H. (2016). A study of the site selection of a civil airport based on the risk of bird strikes: The case of Dalian, China. Journal of Air Transport Management, 54, 17-30. [https://doi.org/10.1016/j.jairtraman.2016.03.016](https://doi.org/10.1016/j.jairtraman.2016.03.016) * Owino, A., Biwott, N., & Amutete, G. (2004). Bird strike incidents involving Kenya Airways flights at three Kenyan Airports, 1991-2001. African Journal of Ecology, 42, 122-128. [https://doi.org/10.1111/j.1365-2028.2004.00507.x](https://doi.org/10.1111/j.1365-2028.2004.00507.x) * Rebello, B. (2015). Bird Strike Prevention Part 2. B.Sc. Thesis, Worcester Polytechnic Institute. * Soldatini, C., Gerogalas, V., Torricelli, P., & Albores-Tatajas, Y. V. (2010). An ecological approach to birdstrike risk analysis. European Journal of Wildlife Research, 56, 623-632. [https://doi.org/10.1007/s10344-009-0359-z](https://doi.org/10.1007/s10344-009-0359-z) * Tan, A., Searing, G., & Keng, W.L. (2010). A Risk-based approach towards setting wildlife strike alert levels. 2nd Meeting of the International Bird Strike Committee, Cairns (Australia). IBSC29_WP02.pdf (worldbirdstrike.com) * Yohannes, E., Bekele, A., & Woldu, Z. (2000). Bird strike incidence at Addis Ababa Bole International Airport. SINET: Ethiopian Journal of Science, 23(2), 215-229. [https://doi.org/10.4314/sinet.v23i2.18167](https://doi.org/10.4314/sinet.v23i2.18167) ## Code/Software Data were analyzed using the 'circular' package in R software.