Melathopoulos, A. | bioRxiv Science

bioRxiv2025

Development and evaluation of a low-cost, automated camera trap for surveying bumble bee communities

Widespread declines in insect diversity and abundance underscore an urgent need for standardized, nonlethal monitoring methods for important pollinators such as bumble bees (Bombus spp.). Camera traps are widely used for non-intrusive, continuous surveys of large animals but have not yet been extensively adopted for monitoring insects. An automated camera trap system could improve current insect survey methods, which often rely on lethal traps or in-person observation. We developed an open-source, low-cost camera trap for monitoring wild insects and evaluated its performance relative to established sampling approaches. The system used a low-power microcomputer to collect time-lapse images on colored platforms. We trained whole-image and tiled deep-learning object detection models to detect insects in images captured by the traps. We found that tiled inference models significantly improved detection accuracy and outperformed human review. Bumble bee visitation was highest on platforms featuring a fluorescent bullseye pattern; adding a fluorescent coat to blue platforms increased visitation modestly. With continuous monitoring, the cameras recorded bumble bee visits during all daylight hours. Over 18 days, camera traps recorded six Bombus species, yielding community composition and diversity estimates comparable to those obtained by hand netting and blue vane traps. Using our observed data, we simulated the effect of deploying variable numbers of cameras at sites with distinct levels of diversity. Adding cameras substantially increased sampling completeness, particularly in species-rich communities. Our findings demonstrate that low-cost, automated camera traps paired with deep-learning image analysis can enable scalable, nonlethal studies of bumble bee diversity and behavior. Our work establishes a foundation for monitoring other diurnal insect communities.

ecology↗

bioRxiv2023

Systematic review of residual toxicity studies of pesticides to bees and comparison to language on pesticide labels using data from studies and the Environmental Protection Agency.

BACKGROUNDResidues of pesticides on crops can result in mortality to foraging bees. The likelihood of mortality can be mitigated by applying pesticides in the evening so that their residues dissipate by the following morning when bees resume foraging. The dissipation rates of different pesticides, or their residual toxicity, is captured in a public-facing database compiled by the U.S. Environmental Protection Agency (EPA), but the database includes only a fraction pesticides bees are likely to encounter in the environment. Pesticide applicators in the U.S. encounter a Pollinating Insect Hazard Statement on pesticide labels, which coarsely indicate which products dissipate over the course of an evening. There is reason to suspect that these statements may not align with residual toxicity data, given previous findings of significant misalignment from published data discovered on the acute toxicity section of the Pollinating Insect Hazard Statement. Without a complete database of residual toxicity estimates, however, it is not possible to determine whether the residual toxicity components of the Pollinating Insect Hazard Statement similarly diverge from published studies. RESULTSWe compiled 48 studies and calculated the residual time to 25% mortality (RT25) of each assay for three different bee species (Apis mellifera, Nomia melanderi, and Megachile rotundata). Our findings were compared to the EPA published database of RT25 values. Of the RT25 values that we could compare, we found that over 90% of the values support a similar conclusion to EPA: that the active ingredient has extended residual toxicity (i.e., residues cause greater than 25% mortality for eight hours or more). Next, we compared our values and the EPAs values to the Pollinating Insect Hazard Statement in the Environmental Hazards sections of 155 EPA registered product labels. Of these labels, a little less than a third (27%) presented their residual toxicity in a manner inconsistent with their calculated RT25 and current EPA labeling guidelines. Moreover, over a third (33%) of labels contained an active ingredient which was neither listed under EPAs RT25 database nor had a published study to estimate this value. CONCLUSIONResidual toxicity of pesticides is a key parameter used by pesticide applicators to reduce impacts of their applications to bees. We provide the first evidence that many pesticide labels may convey residual toxicity information to applicators that is not correct and could lead to bees being exposed to toxic residues on plants. We also show large gaps in the availability of contemporary residual toxicity study for many pesticides, suggesting either researchers should conduct studies to estimate RT25 values for these products, or EPA should make data from registrants more readily available. Finally, our analysis identified significant variation found between RT25 values among different bee species tested, and different formulations of the same active ingredient, suggesting these factors should be incorporated into future bee residual toxicity studies.

ecology↗