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

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.

背景 生物多样性监测项目亟需快速、可靠且兼具成本效益的方法，以对各类景观开展生物多样性评估。对全景观尺度的传粉昆虫（pollinators）进行采样颇具挑战，因为诱捕工作需要覆盖多种生境类型。
研究目标 我们开发并测试了一套适用于全景观尺度的传粉昆虫采样方案。本研究评估了农业景观中传粉昆虫生物多样性估算结果的可预测性与稳定性，并检验了采样生境、景观组成以及空间尺度（spatial scale）对估算结果的影响。
研究方法 我们在10个重复设置的1×1km尺度景观内的250个采样点，使用色盘诱捕法（pan traps）采集传粉昆虫，并基于不同样本量计算蜂类物种丰富度（bee richness）的预测值。各景观内的诱捕装置均均匀布设，并按照各生境的面积比例进行采样。本次研究涉及的景观包含半自然生境、农田与森林，且在大面积开花作物——油菜（oilseed rape）的占比上存在差异。
研究结果 均匀采样可反映局部生境的占比情况。与谷类农田相比，油菜田中出现的传粉昆虫数量显著更多，森林中则更少。仅对单一生境类型进行采样，会导致全景观尺度蜂类物种丰富度的估算结果出现偏差，即便增加样本量亦无法改善这一问题。最佳预测的空间尺度取决于所采样的生境类型：当仅对半自然生境进行采样时，物种丰富度会被高估；而在油菜田采样时则会被低估。采样点密度越高，估算结果的精度也随之提升。
研究结论 针对全景观尺度的传粉昆虫生物多样性研究，我们建议在景观内覆盖多种能够提供资源的生境类型，并布设多个采样点，且样本量需与生境面积成比例。本研究提出的方法同样可推广至通用的生物多样性监测项目中。