Uneven Rates of Landscape Change as a Source of Bias in Roadside Wildlife Surveys

Abstract

Roadside survey data have been used frequently to assess species occurrence and population trends and to establish conservation priorities. However, most studies using such data assume that samples are representative of either the amount of habitat or its rate of change at larger spatial scales. We tested both of these assumptions for the Breeding Bird Survey (BBS) from 1974 to 2001 in New Brunswick, Canada. Our study focused on mature forest—a cover type that we predicted would be characterized by rapid change due to human activities and that is of high ecological importance. We also sought to determine whether land cover changes adjacent to BBS routes were related to bird population trends detected in BBS data. Within all 3 time periods examined (1970s, 1980s, and 1990s), the amount of mature forest adjacent to BBS routes was significantly lower than in surrounding 1° blocks of latitude and longitude. This could be problematic for studies that use roadside data to compare the relative abundance of species. On average, mature forest declined at a rate of‐1.5% per year over the 28‐year study period. We detected no significant difference in the rate of change between degree blocks and BBS routes over this time span. However, in the 1970s and 1980s, mature forest declined more rapidly in degree blocks (‐2.7%/yr) than adjacent to BBS routes (‐0.5/yr). We also found that the BBS trend for a mature forest‐associated species, blackburnian warbler (Dendroica fusca), was correlated with the trend in mature forest along BBS routes. This, combined with slower rates of mature forest change along routes in the 1970s and 1980s, suggests that BBS data may have underestimated population declines during this period. It is important that research be conducted to test for potential biases in roadside surveys caused by uneven rates of landscape change, particularly in regions characterized by rapid habitat alteration.

Biased representation of disturbance rates in the roadside sampling frame in boreal forests: implications for monitoring design

“…Furthermore, differences in geographic scales of comparison and units of measure make it difficult to directly compare the magnitude of bias between studies; thus, future work may benefit from reporting biases over multiple distance classes as we have done here. Despite scale differences, our results are generally of a magnitude similar to biases reported by Betts et al (2007) in New Brunswick (13.5%-22.5% bias) and biases of up to 30% in representing some cover types in the boreal forest (Matsuoka et al 2011). Similarly, Veech et al (2012) showed biased representation of some developed landcover classes in the 2%-6% range, which falls at the low range of overrepresentation of anthropogenic disturbances we describe.…”

“…Several previous studies have found variable bias in habitat representation and/or disturbance rates (Bart et al 1995, Keller and Scallan 1999, Lawler and O'Connor 2004, Betts et al 2007, Harris and Haskell 2007, Matsuouka et al 2011, Veech et al 2012. Our analyses suggested that bias was greatest in areas immediately along roadsides, which corresponds to work by Keller and Scallan (1999), who found a greater rate of increase in urban area along roadsides (0-200 m) than off-road areas (200-1600 m) in Maryland.…”

“…In contrast, several previous studies have described relatively low bias in habitat representation along BBS routes (Lawler andO'Connor 2004, Veech et al 2012). Across studies, biases appear to vary between physiographic regions and also appear to be dependent on scales of geographic analyses; studies that use smaller buffers such as ours and those by Keller and Scallan (1999) and Betts et al (2007) appear to be more likely to identify biases. Biologically, smaller scales are likely more relevant because the majority of boreal species are effectively detectable at distances below 120 m (Bart et al 1995, Matsuoka et al 2012.…”

“…A failure of the roadside sampling frame to accurately reflect disturbance rates over the population of interest would inherently result in biased trend estimates (e.g., Betts et al 2007) and potentially affect sample size requirements. Therefore, we examined biases in BBS representation of habitat disturbance in the boreal forest.…”

Potential benefits of augmenting road-based breeding bird surveys with autonomous recordings

“…However, there are concerns when BBS data are used to (1) generate population size estimates (e.g., Partners in Flight; Blancher et al 2013), because roads influence bird behavior (Matsuoka et al 2011) and sound transmission relative to forest interiors (Haché et al 2014, and (2) assess trends for species that are systematically arriving earlier than the June survey period creating declines in population size owing to a change in phenology, but not abundance (Inouye et al 2000, Parmesan 2007). The BBS in boreal Canada also suffers from a nonrandom distribution of routes, poor habitat representation (Matsuoka et al 2011), and biased representation of disturbance rates (Betts et al 2007, Machtans et al 2014, Van Wilgenburg et al 2015, Handel and Sauer 2017. The degree to which these add variance to the data and reduce power and precision is a concern.…”