A Field Evaluation of the Time-of-Detection Method to Estimate Population Size and Density for Aural Avian Point Counts

The time-of-detection method for aural avian point counts is a new method of estimating abundance, allowing for uncertain probability of detection. The method has been specifically designed to allow for variation in singing rates of birds. It involves dividing the time interval of the point count into several subintervals and recording the detection history of the subintervals when each bird sings. The method can be viewed as generating data equivalent to closed capture–recapture information. The method is different from the distance and multiple-observer methods in that it is not required that all the birds sing during the point count. As this method is new and there is some concern as to how well individual birds can be followed, we carried out a field test of the method using simulated known populations of singing birds, using a laptop computer to send signals to audio stations distributed around a point. The system mimics actual aural avian point counts, but also allows us to know the size and spatial distribution of the populations we are sampling. Fifty 8-min point counts (broken into four 2-min intervals) using eight species of birds were simulated. Singing rate of an individual bird of a species was simulated following a Markovian process (singing bouts followed by periods of silence), which we felt was more realistic than a truly random process. The main emphasis of our paper is to compare results from species singing at (high and low) homogenous rates per interval with those singing at (high and low) heterogeneous rates. Population size was estimated accurately for the species simulated, with a high homogeneous probability of singing. Populations of simulated species with lower but homogeneous singing probabilities were somewhat underestimated. Populations of species simulated with heterogeneous singing probabilities were substantially underestimated. Underestimation was caused by both the very low detection probabilities of all distant individuals and by individuals with low singing rates also having very low detection probabilities.

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.