The Importance of Agriculture-Dominated Landscapes and Lack of Field Border Effect for Early-Succession Songbird Nest Success

In recent decades, many early-succession songbird species have experienced severe and widespread declines, which often are related to habitat destruction. Field borders create additional or enhance existing early-succession habitat on farmland. However, field border shape and the landscape context surrounding farms may influence the effectiveness of field borders in contributing to the stabilization or increase of early-succession bird populations. We examined the influence of linear and nonlinear field borders on farms in landscapes dominated by either agriculture or forests on nest success and Brown-headed Cowbird (Molothrus ater) brood parasitism of Indigo Bunting (Passerina cyanea) and Blue Grosbeak (Passerina caerulea) nests combined. Field border establishment did not affect nest survival probability and brood parasitism frequency of Indigo Bunting and Blue Grosbeak nests. Indigo Bunting/Blue Grosbeak nest success probability was more than twice as high in agriculture-dominated landscapes (39%) than in forested landscapes (17%), and brood parasitism frequency was high (33%) but did not differ between landscapes. Edges in agriculture-dominated landscapes can be higher-quality habitats for early-succession birds than edges in forest-dominated landscapes, but our field border treatments did not enhance nest success for these birds on farms in either landscape.

Detectability of migrating raptors and its effect on bias and precision of trend estimates

Annual counts of migrating raptors at fixed observation points are a widespread practice, and changes in numbers counted over time, adjusted for survey effort, are commonly used as indices of trends in population size. Unmodeled year-to-year variation in detectability may introduce bias, reduce precision of trend estimates, and reduce power to detect trends. We conducted dependent double-observer surveys at the annual fall raptor migration count at Lucky Peak, Idaho, in 2009 and 2010 and applied Huggins closed-capture removal models and information-theoretic model selection to determine the relative importance of factors affecting detectability. The most parsimonious model included effects of observer team identity, distance, species, and day of the season. We then simulated 30 years of counts with heterogeneous individual detectability, a population decline (λ = 0.964), and unexplained random variation in the number of available birds. Imperfect detectability did not bias trend estimation, and increased the time required to achieve 80% power by less than 11%. Results suggested that availability is a greater source of variance in annual counts than detectability; thus, efforts to account for availability would improve the monitoring value of migration counts. According to our models, long-term trends in observer efficiency or migratory flight distance may introduce substantial bias to trend estimates. Estimating detectability with a novel count protocol like our double-observer method is just one potential means of controlling such effects. The traditional approach of modeling the effects of covariates and adjusting the index may also be effective if ancillary data is collected consistently.