Standardising bee sampling: A systematic review of pan trapping and associated floral surveys.

The use of coloured pan traps (bee bowls, Moericke traps) for sampling bees (and other pollinators) has continuously increased over the last two decades. Although a number of methodological studies and conceptual frameworks offer guidance on standardised sampling, pan trap setups vary widely in characteristics even when optimised for capturing bees. Moreover, some uncertainty persists as to how local flower abundance and diversity influence sampling. We systematically reviewed peer-reviewed studies that used pan traps for bee collection and that were listed in the Web of Science core collection. To gauge methodological variation, we identified a set of relevant methodological criteria and assessed the studies accordingly. For obtaining evidence that pan trap samples and floral environment around traps are correlated, we screened the relevant studies for such correlations. While some aspects of pan trapping (e.g., trap coloration and elevation) were similar in the majority of studies, other aspects varied considerably (e.g., trap volume/diameter and sampling duration). Few studies used floral abundance and/or diversity as an explanatory variable in their analyses of bee samples. Among these studies, we found a considerable variation in key aspects of floral survey methods, such as time and space between vegetation surveys and pan trap sampling, abundance measures (quantitative, semi-quantitative and presence-absence), and processing of raw data prior to analysis. Often studies did not find any correlation between the floral environment and bee samples. Reported correlations varied markedly across studies, even within groups of studies applying a similar method or analysing a similar group of bees. Our synthesis helps to identify key issues of further standardisation of pan trap methodology and of associated floral surveys. In addition to the few aspects that have been standardised over the past decades, we suggest methodological direction for future research using pan traps as a better standardised method for the collection of wild bees. We encourage further studies to illuminate if and how varying floral resources around traps bias bee samples from pan traps. More generally, our synthesis shows that trapping methodologies should be reviewed regularly when their use increases to ensure standardisation.

Fragmentation of nest and foraging habitat affects time budgets of solitary bees, their fitness and pollination services, depending on traits: Results from an individual-based model.

Solitary bees are important but declining wild pollinators. During daily foraging in agricultural landscapes, they encounter a mosaic of patches with nest and foraging habitat and unsuitable matrix. It is insufficiently clear how spatial allocation of nesting and foraging resources and foraging traits of bees affect their daily foraging performance. We investigated potential brood cell construction (as proxy of fitness), number of visited flowers, foraging habitat visitation and foraging distance (pollination proxies) with the model SOLBEE (simulating pollen transport by solitary bees, tested and validated in an earlier study), for landscapes varying in landscape fragmentation and spatial allocation of nesting and foraging resources. Simulated bees varied in body size and nesting preference. We aimed to understand effects of landscape fragmentation and bee traits on bee fitness and the pollination services bees provide, as well as interactions between them, and the general consequences it has to our understanding of the system. This broad scope gives multiple key results. 1) Body size determines fitness more than landscape fragmentation, with large bees building fewer brood cells. High pollen requirements for large bees and the related high time budgets for visiting many flowers may not compensate for faster flight speeds and short handling times on flowers, giving them overall a disadvantage compared to small bees. 2) Nest preference does affect distribution of bees over the landscape, with cavity-nesting bees being restricted to nesting along field edges, which inevitably leads to performance reductions. Fragmentation mitigates this for cavity-nesting bees through increased edge habitat. 3) Landscape fragmentation alone had a relatively small effect on all responses. Instead, the local ratio of nest to foraging habitat affected bee fitness positively through reduced local competition. The spatial coverage of pollination increases steeply in response to this ratio for all bee sizes. The nest to foraging habitat ratio, a strong habitat proxy incorporating fragmentation could be a promising and practical measure for comparing landscape suitability for pollinators. 4) The number of flower visits was hardly affected by resource allocation, but predominantly by bee size. 5) In landscapes with the highest visitation coverage, bees flew least far, suggesting that these pollination proxies are subject to a trade-off between either longer pollen transport distances or a better pollination coverage, linked to how nests are distributed over the landscape rather than being affected by bee size.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.