Research Article |
Corresponding author: Jovana Bila Dubaić ( jovanabila@bio.bg.ac.rs ) Academic editor: Sven Bacher
© 2022 Jovana Bila Dubaić, Milan Plećaš, Jovana Raičević, Julia Lanner, Aleksandar Ćetković.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Bila Dubaić J, Plećaš M, Raičević J, Lanner J, Ćetković A (2022) Early-phase colonisation by introduced sculptured resin bee (Hymenoptera, Megachilidae, Megachile sculpturalis) revealed by local floral resource variability. NeoBiota 73: 57-85. https://doi.org/10.3897/neobiota.73.80343
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There is a growing interest to document and better understand patterns and processes involved in non-native bee introductions and subsequent colonisation of new areas worldwide. We studied the spread of the East Asian bee Megachile sculpturalis in Serbia and south-eastern Europe; the bee was earlier established in the USA (since 1994) and western Europe (since 2008). Its establishment in Serbia remained dubious throughout most of 2017–2019, following its first detection. We hereby report on its establishment and spreading, which were corroborated in 2019 under specific circumstances. Owing to an exceptionally poor blooming of Styphnolobium japonicum in 2019, we recorded a high activity density of M. sculpturalis concentrated on a scarce key food resource. We present a novel quantitative approach for an improved early detection of M. sculpturalis, based on the interplay between the bee local occurrence pattern and dynamics of key food-plant(s) availability. This approach seems particularly effective during the early-phase colonisation, at initially low population density of introduced bees. We address the importance of integration of the genuine plant usage patterns with context-specific bee assessment options in establishing effective monitoring. The improved understanding of M. sculpturalis local dynamics triggered the questions about possible origin(s) and modes of its dispersal east of the Alps. To explore the possible scenarios of M. sculpturalis introduction(s), we extended the study to a wider spatio-temporal context – the region of SE Europe (2015–2019). The two complementary study approaches (at local and regional scale) provided more comprehensive evidence of bee dispersal history and the detection patterns in varied recording contexts. Based on this two-scale approach, we suggest that a diffusive mode of M. sculpturalis introduction into Serbia now seems to be a more plausible scenario (than a long-distance jump). We argue that the integration of outcomes from the contrasting approaches (a systematic surveillance, based on plant resources and a broad-scale opportunistic recording) could be of great methodological relevance for the development of future monitoring protocols.
colonisation scenarios, invasive pollinators, monitoring, non-native bees, Serbia, south-eastern Europe, Styphnolobium japonicum
Amongst the continually growing number of introduced species being discovered around the world (
A growing number and geographical extent of alien bee introductions worldwide raise concerns regarding their potential to cause negative environmental impacts. Documented or predicted impacts include: decline of native bee populations through competition (for floral or nesting resources) or pathogen and parasite transmission, degradation of native flower-pollinator networks, reduced pollination of native and crop plants, facilitation of alien weeds and invasive plants (
Megachile sculpturalis
belongs to the subgenus Callomegachile Michener, which is distributed principally in the Old-World tropics (
The first confirmed establishment outside of M. sculpturalis native range was in 1994 in North Carolina, USA (
Following its remarkable non-native spreading, evidence was accumulated about sculptured resin bee interactions with numerous plant genera and families (
Despite a growing number of studies, a specified approach is still missing to quantify the sculptured resin bee distribution dynamics and population trends, its interactions with key plants and native bees and, hence, ultimately, to assess its invasive potential. As a first step, we need an effective approach for early detection and extended surveillance of its expansion. To address these questions, we explored the spatial relationships between bee activity patterns and local availability of key plant resources. We present the survey of the sculptured resin bee introduction in Serbia as an event-driven case study of an early-phase colonisation. Initially, the accidental encounter of a single specimen early in 2017 was interpreted as a likely long-distance chance dispersal of uncertain success (
The study of M. sculpturalis arrival and establishment in Serbia was mostly based on extensive fieldwork within the city of Belgrade, during the period of 2017–2019. The wider geographical and temporal context of this survey included principally the eastern Pannonian Plain, but we also considered the nearest known occurrences towards the west and east of this area (from Austria and Slovenia through the Crimean Peninsula), for the period of 2015–2019.
Belgrade is one of the largest cities in south-eastern Europe (Belgrade “proper” administrative-urbanistic core area is nearly 776 km2, population > 1.5 million), situated at the border between the two quite different geographical units: the predominantly hilly to mountainous Balkan Peninsula to the south and the vast lowlands of the Pannonian Plain to the north. It is positioned in a climatically transitional zone between the temperate-continental and the more steppic regime, with a relief spanning the altitude range of 65–506 m. The Belgrade area encompasses more than 50% of varied agricultural habitats as a matrix, with embedded mosaics of urban and rural habitats; two principal sections of Belgrade (the Balkan and the Pannonian – Fig.
Landscape/urbanistic zonation of the study area in Serbia (18×11 km), within Belgrade proper (light blue outline; sections separated by the red dotted-line): BUC – Balkan Urban Core; BMP – Balkan Mixed Periphery; PUC – Pannonian Urban Core; PSU – Pannonian Semi-Urban; PPU – Pannonian Peri-Urban.
The first record of M. sculpturalis, in early July 2017 (a single male), was an unexpected find within a routine monitoring of wild bee communities of selected urban habitats in the Belgrade area (
A the first specimen of Megachile sculpturalis (male), caught in Serbia in July 2017 B mass-foraging females detected in August 2019.
The second record of M. sculpturalis was also accidental. The summer of 2019 was characterised by an extreme failure in S. japonicum blooming (see details in Results); for this reason, this plant was excluded from our regular monitoring that year. Then, upon an unexpected detection of numerous sculptured resin bees on 2 August 2019, on a single S. japonicum tree (Fig.
On all locations with still-blooming trees, we conducted estimation of bees foraging on flowers, using binoculars where needed (for high crowns). Due to different situations amongst the sites as well as logistic constraints, the duration of work at each location varied from 1–50 minutes (mostly ranging 10–20, mean ~ 15.3 ± 10.7 SD). The estimation procedure was adjusted to varied levels of activity density: (a) at sites with lower activity (≤ 5 observable individuals), bees were usually not present continuously during the observation; here, we used timed counts to quantify the presence of foraging bees on a tree and, if the number of individuals was changing over the period of observation, we split the total time into intervals characterised by each recorded value (0–5); (b) when continuous and more vivid activity was observed (> 5 bees visible at any moment), 3–4 snapshot counts were made over the time spent on site, using two abundance classes: moderate (6–10) or high (11–20). We adapted the snapshot technique used in ornithology (
Simultaneously, we estimated the key floral resource to assess if its quantity, distribution and phenology affect the local differences in activity density and distribution of the bee population. We recorded the number of S. japonicum trees (hereafter NoT) and visually assessed their actual blooming status at each visited location: the number of trees that entered blooming in 2019 (hereafter NoT_iB), the share of inflorescences developed on each crown in bloom during 2019 (as a fraction of the fully-blooming crown; summed value interpreted as Total Floral Resource, hereafter TFR) and, finally, the actual share of flowers still in bloom on each crown at the moment when we made the observation (summed to Current Floral Resource, hereafter CFR). We continued to survey S. japonicum until early September, regardless of the ceased blooming (and no bee activity), to provide the spatial coverage of resource availability across the study area. For extended explanations and visual examples of these parameters, see in Suppl. material
All surveyed locations were primarily georeferenced in Google Earth Pro ver. 7.3.3.7786 (Google Inc. 2020) and further prepared as distribution maps in QGIS ver. 3.4 (
All values from field assessments were summed per defined sector. To calculate TFR, we summed individual values from each S. japonicum tree in bloom, expressed as a fraction of the whole crown, based on the estimated maximal extent of blooming attained during the summer of 2019. Similarly, we calculated CFR as a sum of estimated blooming fractions at the moment of assessment; this represents the actual extent of blooming of each crown within the sector. We recorded blooming fractions as percentage of the whole crown for each assessed tree and then summed the values in decimal form (e.g. blooming of 10% of one crown, 25% of another and 80% of a third gives the value of 1.15 “unit crowns” per sector; more details and visual examples for the calculation available in Suppl. material
We tested if various aspects of floral resource distribution and seasonal dynamics (i.e. change from TFR to CFR level of blooming) had a measurable effect on local differences in bee activity. We analysed the relationship between the bee activity density (BpM) and all measured parameters of the key floral resource (NoT, NoT_iB, TFR and CFR), calculated in S250 and S500 frameworks, with the Generalised Least Square (GLS) linear regression, to account for heteroscedasticity of errors. Additionally, we used GLS linear regression to analyse the relationship between BpM and TFR, CFR, percentage of TFR (TFR/NoT) and percentage of CFR (CFR/NoT), all averaged for each urbanistic zone. Analyses assumptions were tested by examination of residuals. Furthermore, we tried to establish if there were any local patterns in reduction of S. japonicum blooming (i.e. any possible differences caused by environmental effects that specifically vary with urbanistic gradients, using urbanistic zones as tentative proxies) and, if so, are the bees responding to these differences. Differences in NoT, NoT_iB, TFR, CFR and BpM between urbanistic zones were analysed by the Kruskal-Wallis test. All analyses were performed in R v.3.6.3 (
We compiled, from all available sources (Suppl. material
The compilation and mapping of records were conducted within a more extensive Europe-wide survey of M. sculpturalis distribution and expansion; preliminary results for the period of 2008–2019 were presented as series of summary phase-maps in
Following the first detection of M. sculpturalis in Belgrade (and Serbia), in July 2017, we confirmed the establishment of this species only in August 2019. Our recording was almost exclusively based on bees foraging on S. japonicum trees. The exceptions were the first detected specimen – a male collected on Trifolium repens and a single female observed around a Buddleja bush; both cases occurred in downtown parks with nearby present S. japonicum trees. We did not detect M. sculpturalis neither on Lavandula nor on Ballota during the 2017–2019 period, despite notable efforts.
Most of the metrics calculated within the S500 framework had non-significant values (see in Suppl. material
Results of the GLS linear regression models of the relationship of bee activity density (BpM) and variables NoT, NoT_iB, TFR and CFR (N = 16).
Model | Estimate | SE | t-value | p-value | |
---|---|---|---|---|---|
NoT | Intercept | 6.368 | 1.638 | 3.887 | 0.002* |
Variable | -0.144 | 0.854 | -1.644 | 0.122 | |
NoT_iB | Intercept | 6.092 | 2.001 | 3.045 | 0.008* |
Variable | -0.557 | 0.579 | -0.962 | 0.352 | |
TFR | Intercept | 3.459 | 2.689 | 1.286 | 0.219 |
Variable | 0.951 | 1.824 | 0.521 | 0.611 | |
CFR | Intercept | -0.154 | 1.858 | -0.089 | 0.935 |
Variable | 12.276 | 3.891 | 3.154 | 0.007* |
Distribution of A effective floral resources of S. japonicum, as surveyed in August 2019 (Current Floral Resource – CFR) and B respective metrics of M. sculpturalis activity density (Bees per Minute – BpM), both presented within the S250 framework (circular sectors – “landscapes” of r = 250 m; values shown in classes). Urbanistic zones (acronyms as in Fig.
Results of the GLS linear regression models of the relationship of bee activity density (BpM) and variables TFR, CFR, %TFR and %CFR, all averaged across each urbanistic zone (N = 5).
Model | Estimate | SE | t-value | p-value | |
---|---|---|---|---|---|
TFR | Intercept | 1.575 | 5.663 | 0.278 | 0.799 |
Variable | 3.121 | 4.184 | 0.745 | 0.509 | |
%TFR | Intercept | 0.568 | 2.388 | 0.238 | 0.827 |
Variable | 15.359 | 6.196 | 2.479 | 0.089 | |
CFR | Intercept | -2.492 | 0.909 | -2.741 | 0.071 |
Variable | 18.008 | 1.838 | 9.798 | 0.002* | |
%CFR | Intercept | 1.293 | 0.756 | 1.711 | 0.186 |
Variable | 30.223 | 3.981 | 7.592 | 0.005* |
Relationship between A BpM and CFR and B BpM and %CFR averaged across each urbanistic zone (BpM – Bees Per Minute; CFR – Current Floral Resource; %CFR – percentage of current floral resource).
Within the surveyed area (16×9 km was the approximate span of all visited S. japonicum locations; Fig.
The first record in Serbia (in 2017, in Belgrade) was amongst the earliest known, positioned so remotely to the east from the contemporary colonised areas in western Europe. By that time, the closest previous occurrences were from NE Hungary in 2015 (
We documented and analysed the widespread local occurrence of M. sculpturalis within the City of Belgrade, highlighting the early phase of its establishment in Serbia (2017–2019). This initially local case study provided a novel quantitative approach for assessing the bee activity in relation to floral resource availability, contributing to the framework for its early detection. Improved understanding of M. sculpturalis dynamic local patterns triggered an extension of the research scope to the wider, regional-scale context of this introduction – the colonisation within the E Pannonian Plain and SE Europe (2015–2019). The combined outcomes of two complementary approaches, one on local and another on regional scale, provide important elements for future monitoring protocols of this Asian bee.
Detection and monitoring of a newly-established species may be challenging before a substantial local population build-up is attained (
Within the sectors with detectable bee activity (CFR ≥ 0.1), we have found that the activity density (BpM) was solely affected and significantly related to the levels of currently available floral resources (CFR); this was shown at both sector/landscape scale and as averaged values across urbanistic zones defined in this study. We could neither detect any effects of other tested resource parameters (NoT, NoT_iB, TFR) on bee abundance and distribution patterns, nor of other possible environmental features that vary amongst the defined urbanistic zones. Arguably, the lack of significant effects may be, in part, ascribed to a high variability of key floral resources and/or to a small sample size (due to the limited surveying period). However, this may also indicate the ability of M. sculpturalis to efficiently trace available key food resources, owing to its size and expectedly strong flight capacity (
Noteworthy, even under dramatically reduced foraging opportunities on S. japonicum as the preferred food-plant, we could not detect the bee activity on alternative plants within the area. One such commonly available plant, Lavandula, is very frequently visited in the bee European range, second only to S. japonicum (cf.
Understanding of genuine plant usage patterns is important for improving M. sculpturalis early detectability, as well as for further monitoring of its population trends. The effect of concentration, herewith based specifically on a single key food plant, was crucial for this early mass recording. Without this effect, the initially slow population growth would translate into a prolonged accumulation of rare accidental records. For this reason, species detection in many areas commonly lags behind its actual establishment and expansion. Such detection patterns are documented elsewhere in Europe (cf.
Several studies urged for the establishment of monitoring programmes to track the expansion and evaluate possible impacts of this rapidly spreading alien bee (
Currently, we still lack an elaborate and comprehensive monitoring protocol – generally for any of the alien bee species worldwide. In this study, we propose a set of surveying routines and analytical approaches suitable for a structured assessment of plant resource availability, integrated with a standardised quantification of sculptured resin bee activity density. To build a functional monitoring approach, this working framework requires further testing and quantitative “calibration” of suggested procedures, under different environmental settings and varied modalities specific for each local or regional colonisation event. This should be based on extensive comparison of future assessment trials, taking into account the complicated interplay of resources: the co-occurrence of favourable plants (of different functional status: pollen or nectar-only sources), their varying phenologies and management regimes at different scales (from landscape through to regional), affected by varying environmental gradients (from urban to natural), while also considering particular establishment histories.
The first three occurrences of M. sculpturalis east of the Alps, as documented during 2015–2017 (NE Hungary, N Serbia and NE Austria), were remarkably distant from the contemporary W European range and also widely mutually separated across the Pannonian Plain (Suppl. material
From this wider perspective, a long-distance jump into Belgrade indeed seems as the most plausible scenario. The status of Belgrade (the capital city) and its position at important traffic junctions of several major routes from central and western Europe, makes it highly exposed to a large-scale transportation of diverse goods (Suppl. material
However, an in-depth consideration of two contrasting cases (Belgrade vs. E Pannonian) suggests that the alternative scenario of the colonisation of N Serbia is even more plausible; it is based primarily on a diffusive mode of spreading (
The recognition of one vs. another mode of dispersal, as well as the identification of a probable introduction and expansion pathway(s), may be severely difficult and often speculative, but nevertheless highly important for understanding the spatio-temporal patterns of each non-native colonisation (
Finally, we have shown that, contrary to common expectations (
Authors JBD, MP, JR and AĆ were partly supported through the long-term project funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia (# III43001: 2011–2019; # 451-03-68/2020-14/200178: 2020); JL was partly supported by a DOC Fellowship of the Austrian Academy of Sciences at the Institute of Integrative Nature Conservation Research at the University of Natural Resources and Life Sciences. We would like to express our gratitude to the editor and two anonymous reviewers for their detailed feedback and highly constructive suggestions which significantly improved our manuscript. We are thankful to Dr. Jasmina Krpo-Ćetković who critically read our manuscript and helped us during the revision process.
Megachile sculpturalis distribution through Europe for the period 2011–2019
Data type: map (.pdf file)
Explanation note: Summary visualisation of the Megachile sculpturalis distribution and spreading through Europe for the period 2011–2019, shown as series of tentative expansion phases.
Study area – Belgrade (Serbia): basic topography, biogeography, ecological patterns and urbanistic zonation
Data type: maps (.pdf file)
Explanation note: Study area – Belgrade (Serbia): basic topography, biogeography, ecological patterns (habitats, land-use, landscapes) and urbanistic zonation: (i) City of Belgrade: general features (Fig. S2.1); (ii) Zonation of Belgrade (version_01: survey in 2019; Fig. S2.2); (iii) Survey design and processing of geospatial framework (Fig. S2.3) (This is the PDF version of selected pages from the thematic project website (Ćetković et al. 2020), by: Centre for Bee Research of the Faculty of Biology, University of Belgrade (available also at: https://srbee.bio.bg.ac.rs/english/belgrade-general-features; https://srbee.bio.bg.ac.rs/english/m-sculpturalis-2019-survey; with occasional updates).
Quantitative survey of distribution and abundance parameters of M. sculpturalis and S. japonicum in the Belgrade area in August 2019
Data type: spreadsheet database (excel file)
Explanation note: Quantitative survey of distribution and abundance parameters of M. sculpturalis (BpM) and S. japonicum (NoT, NoT_iB, TFR, CFR) in the Belgrade area in August 2019: Tables S3.1–S3.4.
Records of M. sculpturalis from the broader SE European region (compiled for: 2015–2019)
Data type: database (excel file)
Explanation note: Table S4.1. Records of M. sculpturalis from the broader SE European region and the adjacent areas (compiled for: 2015–2019). Table S4.2. Published data sources used.
Results of statistical testing and distribution maps of estimated metrics
Data type: maps (.pdf file)
Explanation note: Belgrade area: results of statistical testing (Tables S5.1–S5.3) and distribution maps of estimated metrics (Figs S5.1–S5.2).