Abstract

In order to use counts of active animals to estimate population parameters (abundance, sex ratio, age structure), we need to understand the factors that bias such counts. For many taxa, the main problems involve behavioural differences among age/sex classes, and the effects of local conditions on activity levels. A unique opportunity to quantify such effects on snakes occurs on Shedao, a small island in the Bohai Sea off north-eastern China. The island contains an extraordinary density of endemic pit-vipers ( Gloydius shedaoensis), that feed primarily on migrating passerine birds. Over an 8-year period we walked the same 540-m path on 936 mornings during bird-migration periods, counted all pit-vipers within a 3-m-wide transect, and recorded the animals’ sex and age class (adult vs juvenile). Total numbers of snakes averaged 40.6 per survey (0.31 per m): thus, the data set contains 37,980 records of sightings of snakes. The total numbers and the composition (sex ratio, age structure) of snakes seen in a morning differed among segments of the path, differed between seasons (spring versus autumn), differed with time within each season, and were influenced by weather conditions (temperature, wind speed, relative humidity). For example, more snakes were seen on days that were hot, with little wind. The proportion of juvenile snakes in the sample decreased on hot, dry, windy days. Sex ratios shifted with time and air temperature. Interactions between these factors were also significant. Overall, census conditions (date, weather) had more influence on total numbers of snakes seen than on age structure or sex ratio in the samples. However, visual censuses strongly under-represented the proportion of adult (vs juvenile) snakes, and the numbers of male compared to female snakes. These analyses provide a strong cautionary message for researchers who use census data to infer underlying demographic traits. At the same time, they show that census data can be informative about abundance and demography as long as one understands the nature and magnitude of biases introduced by conditions prevailing during data aquisition.

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