Land Cover Sampling Biases Associated with Roadside Bird Surveys

Abstract

Roadside surveys such as the Breeding Bird Survey (BBS) are widely used to assess the relative abundance of bird populations. The accuracy of roadside surveys depends on the extent to which surveys from roads represent the entire region under study. We quantified roadside land cover sampling bias in Tennessee, USA, by comparing land cover proportions near roads to proportions of the surrounding region. Roadside surveys gave a biased estimate of patterns across the region because some land cover types were over-or underrepresented near roads. These biases changed over time, introducing varying levels of distortion into the data. We constructed simulated population trends for five bird species of management interest based on these measured roadside sampling biases and on field data on bird abundance. These simulations indicated that roadside surveys may give overly negative assessments of the population trends of early successional birds and of synanthropic birds, but not of late-successional birds. Because roadside surveys are the primary source of avian population trend information in North America, we conclude that these surveys should be corrected for roadside land cover sampling bias. In addition, current recommendations about the need to create more early successional habitat for birds may need reassessment in the light of the undersampling of this habitat by roads. RÉSUMÉ. Les programmes de dénombrement d'oiseaux tels que le Recensement des oiseaux nicheurs sont fréquemment utilisés pour estimer l'abondance relative des populations d'oiseaux. La précision des dénombrements effectués le long des routes dépend de la réprésentativité des types de milieux échantillonnés par rapport à leur proportion relative dans la région. Nous avons quantifié le biais existant dans l'échantillonnage des milieux situés en bordure de routes au Tennessee, É-U, en comparant les proportions représentées par chacun de ces types de milieux près des routes vs dans l'ensemble de la région. L'échantillonnage en bordure de routes a résulté en un échantillon biaisé des patrons à l'échelle de la région : certains types de milieux étaient sous-représentés ou surreprésentés près des routes. Les biais changeaient dans le temps, ce qui introduit un degré variable de distorsion dans les données. À l'aide de ces données sur le biais d'échantillonnage le long des routes et de données sur l'abondance d'oiseaux, nous avons simulé les fluctuations de populations de cinq espèces d'un intérêt particulier pour l'aménagement. Ces simulations ont indiqué que les dénombrements le long des routes peuvent résulter en une impression faussement négative des tendances des populations des espèces de début de succession et des espèces synanthropiques, tandis que les résultats sont fiables pour les espèces de fin de succession. Puisque les dénombrements effectués le long des routes constituent la principale source d'information sur les tendances des populations d'oiseaux en Amérique du Nord, nous concluons que ces dénombrements devraient être corrigés pour les bi...

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

“…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.…”

“…First, our study implies that there is a risk of inaccurate status assessment for boreal forest birds. Simulations by Harris and Haskell (2007) suggest that habitat and disturbance biases can cause substantial misrepresentation of rates of population change, with one simulation suggesting underestimation of a population increase by 2.57% y -1 . Bias in that range could be sufficient to substantially change species status assessments.…”

“…In addition, several systematic changes in spatial distribution of habitats occur in the boreal forest (e.g., increasing proportion of coniferous trees toward the treeline) that could interact with spatial distribution of effort. Simulation studies have shown that land cover sampling biases can introduce biases in both estimated status and trend (Harris and Haskell 2007). Furthermore, bias in representing landscape change along BBS routes could result in biased population trend estimates (O'Connor et al 2000).…”

Understanding the value of imperfect science from national estimates of bird mortality from window collisions

“…Yet avian abundance can be related to smaller scale habitats along roads or large-scale habitats surrounding the point count station at the landscape level. For example, accounting for habitat edges and narrow right-of-way roadside clearings may be helpful important when controlling for roadside bias (Harris and Haskell 2007). Furthermore, roadside bias has been found to be more prevalent along wider roads (Hutto et al 1995).…”

“…For example, Western Meadowlarks are counted more often at survey points along roads due to their tendency to sing from fence posts (Rotenberry and Knick 1995). Similarly, there is a propensity of habitat edges along roadsides (Harris and Haskell 2007) and bird attracted to edges may be counted more frequently along roadside than off-road areas (Hutto et al 1995).…”