In:
The Condor, Oxford University Press (OUP)
Abstract:
Examination of population trends for raptors is a research priority, especially given recent concern for their conservation status. Road counts—in which raptors are counted from a motorized vehicle moving along the ground—might be an effective method to expand the monitoring of raptor populations and estimation of trends. Here, we review past methods used to perform road counts of raptors and present revised recommendations to aid collaboration, data transfer, and interpretation of results across monitoring programs. We performed a standardized keyword search of online literature databases to obtain 148 past road count studies. The number of studies employing road counts increased per year since the 1970s. Most of these studies occurred in North America. The times of day during which road counts were conducted ranged from sunrise to sunset, and maximum speeds ranged from 10 to 113 km hr–1. The number of observers ranged from 1 (the driver) to 5. Most (93) of the studies used unlimited-width transects and fixed-width transects ranging from 0.02 to 2.50 km wide. Sixteen percent of studies calculated or corrected for the probability of detection. Such broad variation in the methodology used during road counts, coupled with infrequent correction for detection, hampers the interpretation of results across road survey programs. We suggest that road count practitioners should emphasize the collection of data, such as speed, number of observers, and distance to observed raptors, which would allow for the calculation of detection-corrected estimates. Such correction would likely improve trend estimation. Recent technology, including mobile apps, allows researchers to collect such data relatively easily, conducting their own studies while contributing to a broader raptor monitoring initiative. Road counts will likely become more useful as statistical analysis of road count data improves and researchers pool their data in a global effort to monitor raptors.
Type of Medium:
Online Resource
ISSN:
0010-5422
,
1938-5129
DOI:
10.1093/ornithapp/duaa061
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2021
detail.hit.zdb_id:
215921-1
detail.hit.zdb_id:
2066173-3
SSG:
12
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