Color pan traps often catch less when there are more flowers around

When assessing changes in populations of species, it is essential that the methods used to collect data have some level of precision and preferably also good accuracy. One commonly used method to collect pollinators is colour pan traps, but this method has been suggested to be biased by the abundance of surrounding flowers. The present study evaluated the relationship between pan trap catches and the frequency of flowers on small (25 m2) and large (2–6 ha) spatial scales. If pan traps work well, one should assume a positive relationship, that is, more insects caught when they have more food. However, in contrast, we found that catches in pan traps were often negatively affected by flower frequency. Among the six taxa evaluated, the negative bias was largest in Vespoidea and Lepturinae, while there was no bias in solitary Apoidea (Cetoniidae, Syrphidae and social Apoidea were intermediate). Furthermore, red flowers seemed to contribute most to the negative bias. There was also a tendency that the negative bias differed within the flight season and that it was higher when considering the large spatial scale compared to the small one. To conclude, pan trap catches may suffer from a negative bias due to surrounding flower frequency and color. The occurrence and magnitude of the negative bias were context and taxon dependent, and therefore difficult to adjust for. Thus, pan traps seem less suited to evaluate differences between sites and the effect of restoration, when gradients in flower density are large. Instead, it seems better suited to monitor population changes within sites, and when gradients are small. Colour pan traps are often recommended for pollinator monitoring. We report that pan trap catches may suffer from a negative bias due to surrounding flower frequency and color. The occurrence and magnitude of the negative bias were context and taxon dependent, and therefore difficult to adjust for. Thus, pan traps seem less suited when gradients in flower density are large. Instead, it seems better suited to monitor population changes within sites, and when gradients are small.