Novel approaches to sampling pollinators in whole landscapes: a lesson for landscape-wide biodiversity monitoring

Abstract

Context Biodiversity monitoring programs require fast, reliable and cost-effective methods for biodiversity assessment in landscapes. Sampling pollinators across entire landscapes is challenging, as trapping needs to cover many habitat types. Objectives We developed and tested a landscapewide sampling design for pollinators. We assessed the predictability and stability of pollinator biodiversity estimates in agricultural landscapes, and tested how estimates were affected by sampled habitat, landscape composition and spatial scale. Methods We sampled pollinators using pan traps at 250 locations in 10 replicated landscapes measuring 1 9 1 km and calculated bee richness predictions based on different sample sizes. Traps were placed regularly in each landscape, sampling each habitat proportionally to its area. Landscapes contained semi-natural habitats, crop fields and forests and differed in the amount of a mass-flowering crop (oilseed rape). Results Regular sampling reflected local habitat amount. Compared with cereal fields, significantly more pollinators occurred in oilseed rape, and fewer in forests. Sampling in only one habitat type led to biased estimates of landscape-wide bee species richness, even when sample size was increased. The spatial scale of best predictions depended on the sampled habitat. Species richness was overestimated when sampling was limited to semi-natural habitats and underestimated in oilseed rape fields. Precision increased with the number of sampling points per landscape. Conclusions To study landscape-wide pollinator biodiversity, we suggest to sample multiple sites per landscape in a broad range of resource-providing habitat types, with sample sizes proportional to habitat amount. Our approach will also be useful for biodiversity monitoring programs in general. Keywords Apidae Á Bees Á Bumblebees Á Wild bee Á Regular sampling design Á Grid-based sampling Á Biodiversity monitoring Á Ecological indicators Á Insect decline Á Community ecology Christoph Scherber and Tatiane Beduschi contributed equally to this work.

Species–habitat networks elucidate landscape effects on habitat specialisation of natural enemies and pollinators

“…Pollinators were sampled with yellow pan traps for 3 days each month in April, May, June and August of 2011 (12 days in total). In each sampling site, one trap was placed at vegetation height across the 10 landscapes (Scherber et al ., 2019). Collected specimens of wild bees (Hymenoptera: Apoidea) and hoverflies (Diptera: Syrphidae) were sent to specialists for identification to the species level by morphological traits (Table ).…”

Land‐sharing/‐sparing connectivity landscapes for ecosystem services and biodiversity conservation

“…We envisage that land‐sharing/‐sparing landscapes with high spatial connectivity (Figure ) allow combining biodiversity conservation with multifunctional ecosystems. From an ecological point of view, landscape design may be guided by studies on landscape‐wide biodiversity monitoring, spillover of species and associated ecosystem services between habitats and landscape elements (Kormann et al, ; Scherber, Beduschi, & Tscharntke, ; Tschumi et al, ; Woodcock et al, ). On regional scales, graph theory provides an analytical framework for identifying areas of low and high landscape connectivity as well as those habitats or landscape elements that facilitate metacommunity dynamics and thus population persistence (Urban & Keitt, ).…”

The landscape ecology of pollination

“…Further, to date, little is known about whether the effects of land-cover changes on pollinator communities are context-dependent. Scherber et al (2019) tested a grid-based method to sample pollinators across entire agricultural landscapes that varied in the proportion of oil-seed rape, a common mass-flowering crop. Using 250 trap locations, distributed across 10 landscapes and sampled over 2 years, they report that restricting sampling to one or a few habitat types only can strongly bias estimates of landscape-wide species richness.…”