Mobile Incubation in Waved Albatross (Phoebastria irrorata): Associated Hatching Failure and Artificial Mitigation

Waved albatrosses often relocate their eggs during incubation by placing the egg between the tarsi and shuffling forward. This behavior frequently results in eggs becoming lodged between rocks, accounting for at least 10%, and perhaps as much as 80%, of breeding failures. Because albatross populations worldwide are currently threatened, artificial means of augmenting reproductive success may be necessary to mitigate losses caused by anthropogenic effects. We characterize the frequency and extent of egg movement; test several hypotheses related to microhabitat, timing, and incubation location to explain the behavior; and investigate the utility of repositioning lodged eggs in a location in which breeding birds might resume incubation. Egg rescue increased both the likelihood of continued incubation as well as the hatching rate in our experiment, and provides an efficient, low-cost management option for this species.

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.