The relative performance of sampling methods for native bees: an empirical test and review of the literature

Kit S Prendergast,Philip W Bateman,Myles H M Menz,Kingsley W Dixon

doi:10.1002/ecs2.3076

Abstract

AbstractMany bee species are declining globally, but to detect trends and monitor bee assemblages, robust sampling methods are required. Numerous sampling methods are used, but a critical review of their relative effectiveness is lacking. Moreover, evidence suggests the relative effectiveness of sampling methods depends on habitat, yet efficacy in urban areas has yet to be evaluated. This study compared the bee community documented using observational records, targeted netting, mobile gardens, pan traps (blue and yellow), vane traps (blue and yellow), and trap‐nests. The comparative surveys of native bees and honeybees were undertaken in an urbanized region of the southwest Australian biodiversity hot spot. The outcomes of the study were then compared to a synthesis based on a comprehensive literature review of studies where two or more bee sampling methods were conducted. Observational records far exceeded all other methods in terms of abundance of bees recorded, but were unable to distinguish finer taxonomic levels. Of methods that captured individuals, thereby permitting taxonomic identification, targeted sweep netting vastly outperformed the passive sampling methods, yielding a total of 1324 individuals, representing 131 taxonomic units—even when deployed over a shorter duration. The relative effectiveness of each method differed according to taxon. From the analysis of the literature, there was high variability in relative effectiveness of methods, but targeted sweep netting and blue vane traps tended to be most effective, in accordance with results from this study. However, results from the present study differed from most previous studies in the extremely low catch rates in pan traps. Species using trap‐nests represented only a subset of all potential cavity‐nesters, and their relative abundances in the trap‐nests differed from those in the field. Mobile gardens were relatively ineffective at attracting bees. For urbanized habitat within this biodiversity hot spot, targeted sweep netting is indispensable for obtaining a comprehensive indication of native bee assemblages; passive sampling methods alone recorded only a small fraction of the native bee community. Overall, a combination of methods should be used for sampling bee communities, as each has their own biases, and certain taxa were well represented in some methods, but poorly represented in others.

Highlights

In many regions, bees are important pollinators of a large number of native and agricultural plant species (Tepedino 1979, Klein et al 2007, Potts et al 2016)
When standardized to approximate an equal sampling duration to the other methods (3 h), blue vane traps caught a comparable number of bees to pan (Table 2)
Pan traps are widely used, are easy to deploy, and can collect large numbers of specimens in certain habitats in the Northern Hemisphere, they were found to be insufficient at sampling native bee communities in this study in an urbanized region of the southwest Western Australian biodiversity hot spot

Summary

Introduction

Bees are important pollinators of a large number of native and agricultural plant species (Tepedino 1979, Klein et al 2007, Potts et al 2016). Bees are declining across the globe due to a number of often interacting threats, including habitat loss, degradation, and fragmentation due to agricultural and urban expansion, disease, pesticides, and climate change (Goulson et al 2015, Potts et al 2016). A number of methods for sampling bees have been developed, each with their own benefits and limitations, including sampling effort, skill required, taxonomic and functional group biases, and cost of implementation (Table 1). The sampling method used may be biased toward bees of a particular lineage or functional group, meaning that the appropriate sampling method varies depending on the taxonomic group or question at hand (Gonzalez et al 2016, Sircom et al 2018, McCravy et al 2019)

Methods

Results

Discussion

Conclusion