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.

Shifts in resident bird communities associated with cloud forest patch size in Central Veracruz, Mexico

Avian communities in cloud forests have high levels of endemism and are at major risk given the accelerated rate of habitat fragmentation. Nevertheless, the response of these communities to changes in fragment size remains poorly understood. We evaluated species richness, bird community density, community composition, and dominance as indicators of the response to fragment size in a fragmented cloud forest landscape in central Veracruz, Mexico. Medium-sized fragments had statistically higher than expected species richness and more even communities, which may be a reflection of the intermediate disturbance hypothesis, in which medium-sized fragments are exploited by both forest and disturbance-associated species. Bird density also reached higher values in medium-sized fragments, which may indicate a carrying capacity in this habitat. However, large cloud forest fragments had a distinct taxonomic and functional composition, attributable to an increased number of understory insectivore species and canopy frugivores. By comparison, omnivorous species associated with human-altered habitats were more abundant in smaller fragments. Hence, although medium-sized cloud forest fragments had higher species richness and high bird density, large forest tracts maintained a distinct avian community composition, particularly of insectivorous and frugivorous species. Furthermore, the underlying response to fragmentation can only be properly addressed when contrasting several community attributes, such as richness, density, composition, and species dominance. Therefore, cloud forest conservation should aim to preserve the remaining large forest fragments to maintain comprehensive avian communities and avoid local extinctions.