@article {SCHEIDEMAN:2017:1750-1938:408,
title = "Use of wildlife camera traps to aid in wildlife management planning at airports",
journal = "Journal of Airport Management",
parent_itemid = "infobike://hsp/cam",
publishercode ="hsp",
year = "2017",
volume = "11",
number = "4",
publication date ="2017-10-01T00:00:00",
pages = "408-419",
itemtype = "ARTICLE",
issn = "1750-1938",
eissn = "1750-1946",
url = "https://www.ingentaconnect.com/content/hsp/cam/2017/00000011/00000004/art00007",
keyword = "airport, aircraft, strike, camera, animal",
author = "SCHEIDEMAN, MATTHEW and REA, ROY and HESSE, GAYLE and SOONG, LAURA and GREEN, CUYLER and SAMPLE, CALEB and BOOTH, ANNIE",
abstract = "Wildlife incidents with aircraft cost airports and operators worldwide an average of US$1.28bn annually. In Canada, Airport Wildlife Management Plans (AWMPs) are designed to provide an outline of specific wildlife hazards at airports and recommend countermeasures to minimise
strike risk. Wildlife incident reports are a key component in the development of such plans. Here, wildlife incident reports were compiled and compared to data collected using newly-installed digital wildlife camera trap technology at the Prince George International Airport. Seven camera traps
were monitored for a total of 2,426 sampling days (9,228 camera days) between 2009 and 2016 and recorded a total of 3,046 animals within 16 different animal species/groups. Airport personnel recorded 4,640 animals and 23 different species/ groups during the same period. Camera traps recorded
almost five times as many animals (n = 2,525) on days when no wildlife incident reports were filed than days when wildlife incident reports were filed (n = 521) and camera traps recorded no images. Z-test for proportions analyses indicated that birds (ie flocks) were more commonly observed
and reported by airport personnel than were captured by camera traps, while mammals such as moose (Alces alces), black bears (Ursus americanus) and snowshoe hares (Lepus americanus) were more commonly recorded by camera traps. These findings suggest that data from camera traps can help in
the development of more informed AWMPs.",
}