• Open Access

Temperature effects on pitfall catches of epigeal arthropods: a model and method for bias correction


Correspondence author. E-mail: saska@vurv.cz


  1. Carabids and other epigeal arthropods make important contributions to biodiversity, food webs and biocontrol of invertebrate pests and weeds. Pitfall trapping is widely used for sampling carabid populations, but this technique yields biased estimates of abundance (‘activity-density’) because individual activity – which is affected by climatic factors – affects the rate of catch. To date, the impact of temperature on pitfall catches, while suspected to be large, has not been quantified, and no method is available to account for it. This lack of knowledge and the unavailability of a method for bias correction affect the confidence that can be placed on results of ecological field studies based on pitfall data.
  2. Here, we develop a simple model for the effect of temperature, assuming a constant proportional change in the rate of catch per °C change in temperature, r, consistent with an exponential Q10 response to temperature. We fit this model to 38 time series of pitfall catches and accompanying temperature records from the literature, using first differences and other detrending methods to account for seasonality. We use meta-analysis to assess consistency of the estimated parameter r among studies.
  3. The mean rate of increase in total catch across data sets was 0·0863 ± 0·0058 per °C of maximum temperature and 0·0497 ± 0·0107 per °C of minimum temperature. Multiple regression analyses of 19 data sets showed that temperature is the key climatic variable affecting total catch. Relationships between temperature and catch were also identified at species level. Correction for temperature bias had substantial effects on seasonal trends of carabid catches.
  4. Synthesis and Applications. The effect of temperature on pitfall catches is shown here to be substantial and worthy of consideration when interpreting results of pitfall trapping. The exponential model can be used both for effect estimation and for bias correction of observed data. Correcting for temperature-related trapping bias is straightforward and enables population estimates to be more comparable. It may thus improve data interpretation in ecological, conservation and monitoring studies, and assist in better management and conservation of habitats and ecosystem services. Nevertheless, field ecologists should remain vigilant for other sources of bias.