非表示:
キーワード:
dispersion, distribution, food availability, resource selection, species abundance, vegetation plot
要旨:
Characteristics of food availability and distribution are key components of a species'
ecology. Objective ecological surveying used in animal behavior research does not
consider aspects of selection by the consumer and therefore may produce imprecise
measures of availability. We propose a method to integrate ecological sampling of an
animal's environment into existing behavioral data collection systems by using the
consumer as the surveyor. Here, we evaluate the consumer-centric method (CCM)
of assessing resource availability for its ability to measure food resource abundance,
distribution, and dispersion. This method catalogs feeding locations observed during
behavioral observation and uses aggregated data to characterize these ecological
metrics. We evaluated the CCM relative to traditional vegetation plot surveying
using accumulated feeding locations across 3 years visited by a tropical frugivore, the
bonobo (Pan paniscus), and compared it with data derived from over 200 vegetation
plots across their 50 km2+ home ranges. We demonstrate that food species abundance
estimates derived from the CCM are comparable to those derived from traditional
vegetation plot sampling in less than 2 years of data collection, and agreement improved
when accounting for aspects of consumer selectivity in objective vegetation plot
sampling (e.g., tree size minima). Density correlated between CCM and plot-derived
estimates and was relatively insensitive to home range inclusion and other species
characteristics, however, it was sensitive to sampling frequency. Agreement between
the methods in relative distribution of resources performed better across species than
expected by chance, although measures of dispersion correlated poorly. Once tested
in other systems, the CCM may provide a robust measure of food availability for use
in relative food availability indices and can be incorporated into existing observational
data collection. The CCM has an advantage over traditional sampling methods as it
incorporates sampling biases relevant to the consumer, thereby serving as a promising
method for animal behavioral research
