Abstract
ContextBiodiversity 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.ObjectivesWe developed and tested a landscape-wide 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.MethodsWe sampled pollinators using pan traps at 250 locations in 10 replicated landscapes measuring 1 × 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).ResultsRegular 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.ConclusionsTo 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.
Highlights
In the context of recent reports on declines in pollinator biodiversity (Biesmeijer et al 2006; Potts et al 2010) and overall insect biomass (Hallmann et al 2017; Vogel 2017), the debate has opened up on what the main drivers of these declines could be
A potentially suitable approach involves sampling a range of habitat types on a large spatial scale, for example by (i) selectively sampling several habitat types (Tylianakis et al 2005; Holzschuh et al 2016), (ii) establishing transects with their length adapted to local habitat area at nested spatial scales (Gillespie et al 2017), or (iii) by establishing sampling grids covering several hectares or square kilometers
We demonstrated that the sampling design can affect the predictability of landscape-wide pollinator biodiversity estimates
Summary
In the context of recent reports on declines in pollinator biodiversity (Biesmeijer et al 2006; Potts et al 2010) and overall insect biomass (Hallmann et al 2017; Vogel 2017), the debate has opened up on what the main drivers of these declines could be. The study on insect declines by Hallmann et al (2017) has received criticism for focusing ‘‘only’’ on protected areas, while little is still known on pollinator abundance or richness on cropland or on larger spatial scales. While there is a staggering amount of separate studies for pollinators in individual habitat types (e.g. grassland, cropland, forest), almost nothing is yet known on pollinator abundance or even pollinator richness on a landscape-wide scale. In order to address these questions, and to properly design potential future monitoring programs, an adequate sampling design is needed that covers a large spatial scale (say, square kilometers). A potentially suitable approach involves sampling a range of habitat types on a large spatial scale, for example by (i) selectively sampling several habitat types (Tylianakis et al 2005; Holzschuh et al 2016), (ii) establishing transects with their length adapted to local habitat area at nested spatial scales (Gillespie et al 2017), or (iii) by establishing sampling grids covering several hectares or square kilometers (hereafter termed ‘‘landscape grid method’’; Fig. 1)
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