Predation in Ground-Nesting Birds: an Experimental Study Using Natural Egg-Color Variation

We tested the hypothesis that cryptically colored eggs would suffer less predation than conspicuous eggs in the ground-nesting red-legged partridge, Alectoris rufa. We used A. rufa as a model species because it has a wide range of natural egg colors, the eggs are widely available from breeding farms, and nests are easily mimicked because they are scrapes containing no vegetation. The study was conducted in the spring of 2001 in forest and fallow fields of central Spain in Castilla La Mancha, Ciudad Real. We used 384 clutches of natural eggs that were white, white spotted, brown, or brown spotted. Within clutches, eggs were consistent in color and size; among clutches, color differences were distributed across habitats. Clutches were checked once after 2 wk of exposure. Cryptic coloration had a survival advantage that was dependent on the local suite of predators. Rodent predation was nonselective with respect to clutch color; however, avian predation was significantly higher for conspicuous clutches. In addition, there was an interaction of landscape and egg color for avian predation. In forest landscapes, the clutches with highest survival were brown spotted, whereas in fallow landscapes, brown and brown spotted clutches had higher survival than white and white potted clutches. Thus, both the predator suite and the landscape had significant effects on the value of cryptic egg coloration. Our study is relevant for conservationists and managers in charge of restocking programs in hunting areas. The release of other partridge species or their hybrids could result in hybridization with wild partridges, potentially leading to nonoptimal clutch pigmentation and reduced survival of the native species. We therefore recommend that local authorities, managers, and conservationists be cautious with the use of alien species and hybrids and release only autochthonous species of partridges within their natural ranges.

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.