Summary Data collection on interactions between organisms and their environment has traditionally been conducted by on‐site human observations, a time‐consuming enterprise that could explain the shortage of around‐the‐clock observations of free‐ranging wild animals. In this paper, I outline a time‐efficient procedure to collect data on flower‐visiting animals. The objectives were, first, to model diel activity rhythms by using cosine‐based mixed‐effects regression models (cosinor method) on data from an established automatic video monitoring system and, secondly, to test the use of a cheap off‐the‐shelf digital camera modified for automated monitoring of flower visitors. Two different model systems were studied: foraging bumblebees visiting focal white clovers, monitored around‐the‐clock (193 h) to model diel activity; and honeybees visiting thistles, monitored over a shorter period (5 h) to test the applicability and reliability of a new method for monitoring pollinators. The data were automatically entered and processed using R‐scripts after manual filtering of the images, obviating the need for manual data entry prior to analysis. For diel activity in bumblebees, the model that gave the best fit included the 24‐h fundamental period and one harmonic, a 12‐h period to modulate the signal, together with temperature. The bumblebees were exclusive diurnal, with activity starting about 5 h after sunrise, peaking sharply in the afternoon and ending about 1 h before sunset. In addition to time of day, activity also increased with temperature. The off‐the‐shelf digital camera, Canon PowerShot®, with motion detection script, was triggered by every flower‐visiting honeybee. In addition to recorded visitor frequency and visitor duration, it enabled high‐resolution images, which could be important for species identification. Automatic camera recording is advantageous for close‐up monitoring, compared with continuous video recording, because the latter demands more time and effort in reviewing the material. It could be used to study a range of different species such as pollinators, on‐plant behaviour of herbivorous animals, cavity dwellers or cavity breeders. Moreover, the procedures for automatic data entry, data processing and statistical analysis for modelling diel activity rhythms could have great relevance for researchers using other types of camera monitoring systems operating 24 h per day.

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Documenting species interactions is a time consuming enterprise, in particular for rare interaction events and interactions taking place at night. Pollinators foraging on orchids have traditionally been monitored by discovering pollen vectors on collected insects, recording traces left by moths on the orchid, direct observations and recently by continuous video monitoring. Direct observations in the wild of orchids with low visitation rates is time demanding. In the present study I monitored greater butterfly-orchids (Platanthera chlorantha), by using a event triggered video monitoring system. A total of 23 nights of monitoring were conducted, whereas only 6 nights had visits by one moth species, namely the pine hawk-moth (Hyloicus pinastri). The total numbers of pine hawk-moths registered were 18. In addition to species identification, the video recordings also enabled detection of pollinaria on the pine hawk-moths. Most of the pine hawk-moth visits took place around midnight. The visit lasted on average for 38.0 sec and the average number of flowers visited was 9.6. In future studies, this video system could give more details on interactions between orchids and insects and even link it to environmental factors (e.g. varying weather conditions).

In this study we used a portable event-triggered video surveillance system for monitoring flower-visiting bumblebees. The system consist of mini digital recorder (mini-DVR) with a video motion detection (VMD) sensor which detects changes in the image captured by the camera, the intruder triggers the recording immediately. The sensitivity and the detection area are adjustable, which may prevent unwanted recordings. To our best knowledge this is the first study using VMD sensor to monitor flower-visiting insects. Observation of flower-visiting insects has traditionally been monitored by direct observations, which is time demanding, or by continuous video monitoring, which demands a great effort in reviewing the material. A total of 98.5 monitoring hours were conducted. For the mini-DVR with VMD, a total of 35 min were spent reviewing the recordings to locate 75 pollinators, which means ca. 0.35 sec reviewing per monitoring hr. Most pollinators in the order Hymenoptera were identified to species or group level, some were only classified to family (Apidae) or genus (Bombus). The use of the video monitoring system described in the present paper could result in a more efficient data sampling and reveal new knowledge to pollination ecology (e.g. species identification and pollinating behaviour). download supplementary video