Global invasion by manicatum (Linnaeus) (: ): assessing potential distribution in and beyond

James P. Strange, Jonathan B. Koch, Victor H. Gonzalez, Lindsay Nemelka & Terry Griswold

Biological Invasions

ISSN 1387-3547 Volume 13 Number 9

Biol Invasions (2011) 13:2115-2133 DOI 10.1007/s10530-011-0030-y

1 23 Author's personal copy

Biol Invasions (2011) 13:2115–2133 DOI 10.1007/s10530-011-0030-y

ORIGINAL PAPER

Global invasion by (Linnaeus) (Hymenoptera: Megachilidae): assessing potential distribution in North America and beyond

James P. Strange • Jonathan B. Koch • Victor H. Gonzalez • Lindsay Nemelka • Terry Griswold

Received: 8 July 2010 / Accepted: 20 May 2011 / Published online: 22 June 2011 Ó Springer Science+Business Media B.V. (outside the USA) 2011

Abstract The wool carder , Anthidium manica- model predicted a much broader distribution of A. tum, is the most widely distributed unmanaged bee in manicatum (214% increase); whereas, the South the world. It was unintentionally introduced to North American model predicted a narrower distribution America in the late 1960s from , and subse- (88% decrease). The poor predictive power of the quently, into , New Zealand and the latter model in estimating suitable habitats in the . We provide information on the local invasive South American range of A. manicatum distribution, seasonal abundance and sex ratio of suggests that the bee may still be limited by the A.manicatum from samples collected in an intensive bioclimatic constraints associated with a novel envi- two-year survey across Utah, USA. Anthidium man- ronment. Estimates of niche similarity (D) between icatum was detected in 10 of the 29 Utah counties, the native and invasive models find that the North largely in urban and suburban settings. Combining America bioclimatic niche is more similar to the presence-only and MaxEnt background data from bioclimatic niche of the native model (D = 0.78), literature, museum databases and new records from whereas the bioclimatic niche of the South America Utah, we constructed three species distribution mod- invasion is relatively dissimilar (D = 0.69). We els to examine the potential distribution of A. manic- discuss the naturalization of A. manicatum in North atum in its native Eurasian range as well as invaded America, possibly through punctuated dispersal, the ranges of North and South America. The A. manic- probability of suitable habitats across the globe and atum model based on locality and background data the synanthropy exhibited by this invasive species. from the species’ native range predicted 50% of the invasive records associated with high habitat suit- Keywords Anthidium manicatum Á Invasion ability (HS C 0.90). The invasive North American dynamics Á Species distribution modeling Á Synanthropy Á MaxEnt background data

J. P. Strange (&) Á J. B. Koch Á V. H. Gonzalez Á T. Griswold USDA-ARS Pollinating - Biology, Management and Systematics Laboratory, Utah State University, Introduction 261 BNR, Logan, UT 84322-5310, USA e-mail: [email protected] (Hymenoptera: ) are among the most important of many flowering plants J. B. Koch Á L. Nemelka Biology Department, Utah State University, including agricultural crops through which they 5305 Old Main Hill, Logan, UT 84322-5305, USA contribute an estimated one in three bites of food 123 Author's personal copy

2116 J. P. Strange et al. consumed by humans (Buchmann and Nabhan 1996). manicatum (Linnaeus), is a solitary bee in the family While several bee species have been intentionally Megachilidae that has been unintentionally introduced transported around the globe for pollination services into several regions of the world, and has recently [e.g., A. mellifera L., B. terrestris L., M. rotundata shown rapid expansion in its non-native geographic (Fabricius)], many other species across multiple distribution (Smith 1991; Miller et al. 2002; Hoebeke families are finding their ways into novel environ- and Wheeler 2005; Maier 2005; Zavortink and Shanks ments through accidental and indirect introductions 2008; Gibbs and Sheffield 2009). Females and males [e.g., M. sculpturalis Smith, A. oblongatum (Illiger), of A. manicatum, like many other anthidiines, are H. hyalinatus (Smith)]. There is growing concern that conspicuous because of their black and yellow-striped the shuffling of bee pollinators across habitats may abdomen and robust body form. In its invasive range facilitate the spread of novel bee pathogens (Goka males can be distinguished from native anthidiines by et al. 2001; Goulson 2004; Colla et al. 2006) and the distinctive series of protruding spines on the provoke competitive interactions with native bees for posterior segments of their abdomen (Fig. 1). Males floral resources and habitat (Roubik 1980; Goulson are territorial and aggressively defend mating sites 2003; Schmid-Hempel et al. 2007). While the from intruders by employing the abdominal spines to Africanized invasion of the New World break or disable the intruders’ wings during aerial may be the most dramatic example of the unintended battery (Pechuman 1967; Wirtz et al. 1992). Male A. consequences of bee movement (Roubik 1980), focus manicatum do not discriminate between conspecific has not been placed on the impacts of invasions by and heterospecific intruders and are often seen unintentionally introduced bees, nor have the under- patrolling flowers and attacking other bees that enter lying factors that facilitate their range expansion been into their territory (Kurtak 1973; Severinghaus et al. studied. 1981). This behavior is of particular interest because To date, most research has focused on the impacts some bees, particularly bumble bees, have been of managed bees on native bee communities documented to be deterred from foraging by A. (reviewed in Goulson 2003), while virtually nothing manicatum (Pechuman 1967; Comba et al. 1999). is known about the ecological ramifications of unin- Because of their distinctive body form and aggressive tentionally introduced bees (but see Severinghaus behavior A. manicatum are easily recognizable inhab- et al. 1981). The wool carder bee, Anthidium itants of residential gardens and are widely reported

Fig. 1 Anthidium manicatum (#). Dorsal view of abdominal spines (right) used in aerial battery 123 Author's personal copy

Global invasion by Anthidium manicatum (Linnaeus) 2117 on internet identification sites such as ‘‘Bug Guide’’ the bioclimatic profile associated with its native and ‘‘Discover Life’’, where pictures of the bees are distribution. posted along with location and date of sighting. Alternatively, the distribution of A. manicatum The native distribution of A. manicatum spans may be related to nesting behavior or foraging diet most of Europe, western and coastal North (Comba et al. 1999; Corbet et al. 2001). Anthidium Africa. Anthidium manicatum was first observed in manicatum often nests in holes and cavities in wood or North America in 1963 in Ithaca, New York (Jaycox hollowed stems of plants, thus, facilitating dispersal 1967). Initial range expansion by A. manicatum was (Kurtak 1973). Female A. manicatum card fibers off of apparently not rapid; it was subsequently documented the leaves and stems of plants such as wooly hedge from Ontario, Canada in 1991 (Smith 1991), and nettle ( byzantina K. Koch) and use the Pennsylvania in 1996 (Miller et al. 2002; Hoebeke material to line nest cells in cavities (Mu¨ller et al. and Wheeler 2005). However, since 1996 A. manic- 1996). The host-plants associated with the carding atum detection has increased dramatically; it is now behavior of A. manicatum seem to be restricted to the well documented throughout the eastern USA (e.g., family , whereas and foraging Miller et al. 2002; Matteson et al. 2008; Tonietto and occurs on a greater array of plants, primarily plants in Ascher 2008), and most recently in California the family’s Lamiaceae, Fabaceae and Scrophularia- (Zavortink and Shanks 2008), Colorado, Idaho and ceae (Kurtak 1973, reviewed in Zavortink and Shanks western Canada (Gibbs and Sheffield 2009). In less 2008). However, it is still unknown to what extent than 50 years A. manicatum has dispersed across A. manicatum will utilize novel plants for nest- North America, primarily documented in major urban building or larval provisions in invaded environments, areas. Concurrently, it has colonized large portions of or whether the species range is limited by the presence southern , Peru, Suriname, , Para- of introduced European plant species. guay, , New Zealand, and the Canary Islands During 2007 and 2008 the Utah Department of (Hoebeke and Wheeler 2005; Gibbs and Sheffield Agriculture and Food (UDAF) conducted a statewide 2009), making it the most widely distributed Anthi- monitoring and eradication program of the invasive dium in the world and the most widespread unman- Japanese beetle (Popillia japonica Newman Coleop- aged bee species. Records of A. manicatum from tera: Scarabaeidae) in response to beetle detections in central Asia are known from the 1960s (Wu 2005), Orem, Utah, USA. The network of baited beetle traps but it is unclear if these records are due to a recent deployed throughout the state, particularly concen- range expansion, or are from poorly documented trating on populated areas, resulted in large captures areas of their native range. of non-target insects. These unintentionally trapped Despite the widespread distribution of A. manic- insects, termed ‘‘by-catch’’, were primarily composed atum, little is known about the invasive potential of of Coleoptera, Lepidoptera and Hymenoptera (espe- this bee to colonize new areas. As recently as 2009 cially bees) (the authors, pers. obs.). Anthidium A. manicatum was called ‘‘adventive’’ (Gibbs and manicatum was found among the by-catch, providing Sheffield 2009), indicating that it was newly colo- an opportunity to survey from large portions of Utah. nizing and not yet well established in North America. Here we report on the distribution, seasonal While the bee occupies a large and diverse habitat in abundance and sex ratio of A. manicatum in Utah. its native range including Europe, western Asia and We also construct three models of A. manicatum North Africa, the species initially seemed to be potential distribution based on a suite of proximal restricted in North America to northeastern USA and bioclimatic variables. The first model reflects the eastern Canada. As such, it is arguable that the locality records associated with the native Eurasian bioclimatic profiles of both the native and invasive range of A. manicatum, whereas the latter two models range are relatively similar. However, the more reflect the invasive locality records associated with recent records of A. manicatum in South America North and South America. We then assess several of and western North America argue for a broader range the bioclimatic variables used in these models and of habitat than previously suspected. Given that compare them with the bioclimatic profile associated A. manicatum is found in a diverse range of habitats with locality records compiled from the Utah study, worldwide, we hypothesize that it is not limited by the largest regional survey of A. manicatum outside 123 Author's personal copy

2118 J. P. Strange et al. its native range. Finally, we compare the model of densities of JBT were located throughout Utah in A. manicatum based on native locality records to the the rest of the 29 counties. models based on their invasive ranges using niche JBT were emptied biweekly by state inspectors, by- similarity indices and discuss this species’ ability to catch was collected into labeled plastic bags (Whirl– colonize novel environments. pakÒ) and sent to the United States Department of Agriculture- Agricultural Research Service- Pollinat- ing Insects Research Unit (PIRU) in Logan, Utah. Each Methods two-week period from a JBT at a site is hereafter termed a trapping period. The trapping season in 2008 Trap protocol and seasonal abundance data was shortened by 20 days to reduce the amount of bumble bee (Bombus) queens that were being killed as Tre´ce´ Japanese Beetle TrapsÒ (JBT) were set by-catch. Traps were placed approximately two weeks throughout the state of Utah (Fig. 2a) from April to later in the spring and retrieved a week earlier in the fall November, 2007 (147 trap days) and May through of 2008, thus, fewer samples were taken in June and no September, 2008 (127 trap days) as part of the UDAF data are available for November 2008. The JBT Japanese beetle monitoring and eradication program. contents were sorted at PIRU and all bees in the genus Approximately 3,250 JBT locations were distributed Anthidium were pinned, labeled and identified to throughout the state of Utah, with high trap density in species. In addition to JBT specimens, net collections areas known to be infested with Japanese beetles. The of A. manicatum were conducted in 2009 in Cache highest concentration of JBT was within the popu- County, to verify the presence of the bee in an area with lated corridor of Utah along Interstate 15, known as low JBT density. JBT locations and collection dates the Wasatch Front (Fig. 2b); however, lower provided by UDAF personnel were entered into the US

Fig. 2 Anthidium manicatum distribution in Utah, USA. represent JBT with no A. manicatum detected. Gray circles Background collection effort summary (a) of all bees reported indicate bee surveys associated with the NPID, with size of in the US National Pollinating Database (NPID) since circle proportional to survey effort. Underlying gray-scale in 1999 and (b) map inset of A. manicatum detected in Tre´ce´ (b) represents human population density, where darker colors Japanese Beetle TrapsÒ (JBT) during 2007 and 2008 along the indicate highly urban areas (ESRI 2008). The cross-hatched Wasatch Front in Utah, USA. White crosses represent polygon in both figures represents the Great Salt Lake A. manicatum detection using JBT and white triangles 123 Author's personal copy

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National Pollinating Insect Database (NPID) (US Table 1 General information about A. manicatum caught in NPID 2011) housed at PIRU and the number of female Japanese Beetle Traps in Utah, USA in 2007 and 2008 and male A. manicatum were recorded for each 2007 2008 trapping event. These data were used to determine the seasonal abundance and sex ratio of A. manicatum Trap days 147 127 in Utah. Total bees 194 197 Bees/day 1.32 1.55 Locality records and covariate selection Number males 76 114 Number females 118 83 Using locality records from literature, museum dat- Month abases [i.e., Global Biodiversity Information Facility June 92 4a (GBIF; http://www.gbif.org/)] and the specimens July 42 86 from the JBT in Utah, we compiled a total of 281 Aug 26 53 unique locality records of A. manicatum from its Sept 5 36 native range and 119 locality records outside of its Oct 27 16 native range (Table 1;‘‘Appendix’’). In addition, we Nov 2 0a used records from Discover Life (Ascher and County Pickering 2011) and Iowa State University’s online Box Elder 1 0 insect identification repository Bug Guide (Bartlett Cache* 0 Obs. 2011), but only if specimens could be unambiguously Davisb 24 35 identified from the pictures posted online. Collection Juab 0 2 locations of specimen records extracted from NPID Salt Lake 42 57 were georeferenced using Google Earth (http://www. Sanpete 1 0 earth.google.com/). We excluded specimens with Summit 1 0 questionable identifications and all records used in Utah 111 80 this study were verified by published works or Wasatch 2 5 through personal communication. To reduce geo- Weber 13 17 graphic bias from the Utah occurrence records of * Anthidium manicatum observed and net collected in 2008 A. manicatum, only one randomly selected occur- and 2009 at multiple locations in Cache County including rence record from each county in Utah was utilized in several in Logan, the most populous city in the county the final model. a Two male A. manicatum collected in Davis County had Nineteen bioclimatic variables (Hijmans et al. unspecified dates and thus, are omitted from the monthly 2005) were initially considered in modeling the summary, but included in the total and County summary distribution of A. manicatum. These biologically b Trapping period in 2008 was mid-June to mid-October thus, meaningful variables have proven useful in predicting fewer bees were collected in June 2008 and no bees were collected in November 2008 because of the truncated trapping the distribution of many different organisms, includ- period ing bees (e.g., Gonzalez et al. 2010). Bioclimatic variables were downloaded from the WorldClim database (http://www.worldclim.org/) at a spatial bioclimatic variables. However, when combining all resolution of 1 km2 and processed using Arc-GIS 9.3 occurrence records of A. manicatum in both the (ESRI 2008). native and invasive range we were able to reduce the To reduce multicollinearity in the variables we initial set of 19 variables to 10. We ran models on calculated multiple pair wise correlation coefficient both the reduced variable set and on the full set of 19 values (Pearson correlation coefficient, r) using variables. We did not detect any qualitative differ- occurrence records from both the native and invasive ences in model performance or prediction and range of A. manicatum. From each set of highly therefore present the models based on the reduced correlated variables (|r| [ 0.75) we retained only one variable set. The bioclimatic variables retained in the variable for the final model. In the native data set we final models are as follows: mean temperature diurnal could not find any significant correlations across the range, temperature annual range, mean temperature 123 Author's personal copy

2120 J. P. Strange et al. of wettest quarter, mean temperature of driest quarter, geographic extent of museum and publication locality mean temperature of warmest quarter, precipitation records of A. manicatum, we utilized GBIF to collect seasonality, precipitation of wettest quarter, precipi- spatially biased background data (see ‘‘Appendix’’ for tation of driest quarter, precipitation of warmest a summary of data sources). We searched GBIF for quarter and precipitation of coldest quarter. Like georeferenced localities of confamilial bees to A. man- many other bee species, these are proximal variables icatum (Megachilidae) in Europe, North America and related to the bioclimatic profile associated their South America regardless of genus or species. Back- foraging resources (i.e., nectar and pollen availability ground locality records retrieved from GBIF were from flowering plants) and nesting habitats. For a full limited to a maximum convex polygon (MCP) con- discussion of the bioclimatic variables see Hijmans structed with A. manicatum locality records across all et al. (2005). three continents and were calculated using the open- source software program Geospatial Modeling Envi- Modeling procedure and validation ronment (Spatial Ecology LLC 2010). These MCPs also limited the geographic extent of the models To estimate the distribution of A. manicatum across constructed using MaxEnt. its native and invasive ranges, we employed the Three A. manicatum models were constructed: a species distribution modeling program MaxEnt v 3.3 native model, a North American invasive model and a (Phillips et al. 2006). MaxEnt estimates relative South American invasive model. The native model was habitat suitability (HS), between 0 and 1, where trained on the bioclimatic variables associated with values closer to 0 suggest low HS and values closer to locality (l = 281) and background (b = 4,016) data 1 suggest high HS. The estimation of HS is based on within the MCP native distribution of A. manicatum. the conditional density of covariates associated with The native model was subsequently projected onto the presence sites and the unconditional density of full geographic extent of the Europe, North America covariates associated with the study area (Elith and South America, the latter two representing et al. 2011). Unlike traditional SDM methods that A. manicatum’s invasive range. The North American require both presence and absence data, MaxEnt only invasive model estimated HS based on North Amer- requires presence data (Phillips et al. 2006). In lieu of ican locality (l = 72) and background (b = 3,415) absence, MaxEnt relies on background data across data, whereas the South American invasive model the study area to make the estimation of HS. This estimates HS based on South American locality feature of MaxEnt is advantageous when true absence (l = 47) and background (b = 267) data. The limited is unknown or confounded by a low detection background data set associated with the latter continent frequency or species phenology (Elith et al. 2006). is a relic of the poor collection and digitization effort of A major property of the MaxEnt modeling program South American Megachilidae (Appendix). This nar- is the assumption of an unbiased distribution of locality row approach was also performed to accommodate for records (Phillips et al. 2006). However, as museum the bioclimatic dissimilarity between the two invaded records of specimens are usually biased towards roads ranges of A. manicatum. Both invasive models were and urban areas, it is critical to account for collection then projected onto the respective continent to estimate bias when assigning background data for model HS associated with the bioclimatic profile A. manic- construction. While models with spatially biased atum in novel environments. As the spatial resolution locality records may perform well, it is likely that the of the bioclimatic variables utilized in the MaxEnt model is estimating collection bias, rather than HS models represent 1 km2, multiple locality records that (Elith et al. 2011). In the MaxEnt framework, several fell within a grid pixel were removed from both approaches have been suggested to reduce spatial bias presence and background locality records for all in models, including spatial filtering and biased grid models constructed. files of presence data (Phillips et al. 2009; Veloz 2009). MaxEnt models were fitted using default settings of An alternative method includes the assignment of prevalence, feature type, logistic output (constrains HS equally biased background data in model construction estimates between 0 and 1) and regularization (Phillips (Elith et al. 2011), and will be used in our modeling et al. 2006) across 100 replicates, with the exception of approach. To account for both the spatial bias and the South American invasive model (40 replicates). 123 Author's personal copy

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The reduced replicate set of the South American individuals of A. manicatum were recorded (1.32 invasive model reflects the limited locality and back- bees/trap-day) from 106 JBT trapping events ground data set associated with South American (Table 1). In 2008, 197 individuals (1.55 bees/trap- A. manicatum and Megachilidae data, respectively. day) were detected in 156 JBT trapping events. Each replicate was assessed using tenfold cross-valida- Females were more frequently collected than males tion to estimate predictive performance of held out data. in 2007, whereas males were more common in 2008 The built in area under the curve (AUC) statistic in in contrast with observations in the native range MaxEnt is reported to assess the overall accuracy of a which show a distinct female biased sex ratio (Wirtz model replicate, where values above 0.5 suggest that the et al. 1988). However, when pooled across both years models performed better than random (Fielding and Bell the sex ratio was about 1:1. 1997). The final models and respective AUC test The seasonal abundance of A. manicatum adults in statistic represent the average of the model replicates. Utah is at least 5 months long, lasting from June to October (Table 1). Anthidium manicatum was detected Bioclimatic niche similarity metrics as late as November 2007 indicating that individuals were active within the 2 weeks period prior to that date To estimate the similarity of HS associated with the based on JBT deployment and collection times. bioclimatic profiles of native and invasive models, Females and males appear in the earliest sample period Schoener’s metric for niche overlap (D) was calcu- and both were detected in traps throughout the season. lated (reviewed in Warren et al. 2008). This metric In 2007, June had the highest capture of A. manicatum constrains estimates of niche overlap between 0 and (n = 92) and in 2008 July had the highest capture 1, where values closer to 1 suggest high niche overlap (n = 86). The JBT were not located at all of the same and values closer to 0 suggest low niche overlap. To sites in both years, but many cities have multiple assess niche similarity between projections of the specimen records from both years (e.g., Brigham City, native and invasive models in North and South Ogden, Orem, Provo, Salt Lake City) indicating America, 10,000 random points were drawn from the established populations along the Wasatch Front continental extents and aggregated with the respec- (Fig. 2b). Furthermore, despite the numerous sampling tive raster grids using ArcGIS 9.3. The open-source efforts across the state of Utah within the past 10 years, statistical software package R v2.9.2 (R Development A. manicatum was never detected in intensive bee Core Team 2009) was utilized for the Pearson’s surveys in wild lands (Fig. 2a). correlation coefficient analysis, to construct box plots to visualize the bioclimatic variables and for the Potential distribution estimation of bioclimatic niche similarity. The A. manicatum native model performed well

(AUCtrain = 0.76, AUCtest = 0.69 ± 0.16), predict- Results ing 71 and 19% of the known A. manicatum localities associated with HS C 0.90 in North (Fig. 3a) and Distribution and seasonal abundance of A. South America (Fig. 4a), respectively. As expected, manicatum in Utah the North American invasive model predicted a much wider range of HS (Fig. 3b), whereas the South The present study surveyed by-catch from 3,250 JBT American invasive model surprisingly predicted a throughout Utah (Fig. 2a) over a 2 year period. Utah, much narrower range of HS (Fig. 4b). Based on the Salt Lake and Davis Counties, in descending order, AUC statistic of model performance, the North had the highest number of records; however, those American invasive model predicted the distribution counties also had the highest density of traps in the of A. manicatum exceptionally well (AUCTrain = state and the number of trapped individuals is not 0.96; AUCTest = 0.94 ± 0.07), estimating HS C adjusted for trap density. Over the 2 year period, 0.90 for 85% of the A. manicatum locality records. A. manicatum was detected in nine counties using However, the South American invasive model did not

JBT and in a tenth county (Cache) by net collection in perform as well (AUCTrain = 0.81; AUCTest = 2008 and 2009 (Fig. 2a; Table 1). In 2007, 194 0.67 ± 0.25), but is arguably better than a random 123 Author's personal copy

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bioclimatic niche of the native and invasive models of North America are more similar (D = 0.78) than the bioclimatic niche on South America (D = 0.69). In the latter scenario, the lack of niche similarity is not surprising considering its subtropical bioclimatic profile and prediction capabilities. A comparison of the bioclimatic profile associated with the native and invasive distributions of A. man- icatum reveals interesting departures and patterns in both precipitation (Fig. 5) and temperature tolerances of the species (Fig. 6). For example, the bioclimatic variable precipitation seasonality (Fig. 5a) shows greater variability when associated to locality records of A. manicatum in the invasive distribution relative to the native distribution. Also, the precipitation of the warmest quarter associated with the invasive distribution of A. manicatum (Fig. 5b) is more varied than in the native distribution, particularly where the bee has invaded regions that receive higher precip- itation than the native distribution. The greater range of precipitation values observed in both precipitation seasonality and precipitation of warmest quarter Fig. 3 North American A. manicatum probable distribution associated with individuals captured in the Southern and historic collection effort. The probable distribution Hemisphere (i.e., Brazil, Argentina and Chile) sug- (underlying gray-scale) of A. manicatum is estimated by aggregating bioclimatic variables associated with (a) locality gest that A. manicatum is not deterred by environ- records exclusive to its native distribution and (b) pooled ments with heavy precipitation or in regions where locality records from its native and invasive range. White the seasonality of precipitation differs from the native crosses represent A. manicatum detection. Underlying gray- distribution. The pattern of less variability and scale for both models represents habitat suitability (HS) with darker colors indicating higher HS generally drier conditions is observed in the three other precipitation variables, precipitation of driest quarter (Fig. 5c), precipitation of wettest quarter model (AUC C 0.50). It did not estimate any invasive (Fig. 5d) and precipitation of coldest quarter records to be associated with HS C 0.90, but rather (Fig. 5e). While we observe a narrower range of estimated 34% of the records to be associated with HS precipitation values associated with locality records between 0.70 and 0.80. At a threshold of HS C 0.90, in the Utah portion of its distribution, these values fall the native A. manicatum model estimates distributions well within the variability observed in both A. man- of 6.7 9 106 km2 in North America whereas the icatum’s native and invasive distributions. invasive models estimates distributions of 2.1 9 107 Although locality records representing invasive km2, a 214% increase. In South America the native A. A. manicatum show dramatic variability in their manicatum model estimates a distribution of precipitation bioclimatic profile, it seems that tem- 8.0 9 106 km2, whereas the invasive model estimate perature is less variable across both its native and a distribution of 9.4 9 105 km2, an 88% decrease. The invasive distributions. For example in both the invasive models estimate the potential distribution in temperature annual range (Fig. 6a) and mean tem- North America to be much broader in scope, encom- perature of driest quarter (Fig. 6b) we detect no passing most of the contiguous USA and southern qualitative differences among the locality records Canada (Fig. 3b), whereas the South American associated with the native and invasive distributions distribution is much more limited to coastal regions of A. manicatum. In fact, mean temperature of driest (Fig. 4b). Finally, based on Schoener’s D of niche quarter has more variance in the native distribution similarity, a comparison of the A. manicatum than in the invasive distribution. However, when 123 Author's personal copy

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Fig. 4 South American A. manicatum probable distribution and historic collection effort. The probable distribution of A. manicatum is estimated by aggregating bioclimatic variables associated with (a) locality records exclusive to its native distribution and (b) pooled locality records from its native and invasive range. White crosses represent A. manicatum detection. Underlying gray-scale for both models represents habitat suitability (HS) with darker colors indicating higher HS

comparing the temperature variables associated with and Ascher 2008; Zavortink and Shanks 2008; Gibbs its bioclimatic profile in Utah, it appears that and Sheffield 2009). The number of A. manicatum A. manicatum is able to tolerate more temperature specimens detected in the survey accounted for about extremes than would be suggested by its native 1/3 of the total number of anthidiine specimens distribution (Fig. 6c–e), and there seems to be collected from JBT, far exceeding the combined qualitative differences when comparing locality number of specimens of the other eight native records associated with mean temperature of wettest Anthidium. In Utah County, where JBT were most quarter (Fig. 6d). From the assessment of these two dense, 78 A. manicatum individuals were detected at temperature-related bioclimatic variables it seems dozens of sites, primarily in urban areas, indicating a that A. manicatum may not be limited by temperature well established population. The presence of the bee in its invasive distribution. Moreover, it is also in less urban areas, where limited numbers of traps possible that A. manicatum has not been detected in were deployed, is not well known. However, multiple areas where temperature related variables depart from individuals at several locations have been observed the currently known bioclimatic profile of the spec- and collected in Cache County where traps failed to imens compiled in this study. detect the bee. Not surprisingly, the North American invasive model estimates broad HS in the invaded range Discussion (Fig. 3b), possibly over predicting invasive distribu- tion. Conversely, the South American invasive model The present Utah survey not only explores the was unable to predict high HS for known occurrence breadth of the A. manicatum invasion into more arid records (Fig. 4b), further suggesting that the model is regions of the USA, but also the depth of the pattern. not effective at predicting invasive distribution. Since accidental introduction to New York prior to Unlike similar studies of invasiveness (e.g., 1963 (Kurtak 1973), the species has colonized a large Broennimann and Guisan 2008; Steiner et al. 2008), territory in North America. However, the full inva- pooling native and invasive A. manicatum locality sive potential of this species is only now being data did not improve model predictions. Thus, our realized as new records are documented throughout analysis represents a narrow geographic approach in the USA and Canada (Matteson et al. 2008; Tonietto modeling the invasive potential of A. manicatum.By 123 Author's personal copy

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Fig. 5 Boxplot comparisons of precipitation related bioclimatic space inhabited by A. manicatum in their invasive (I), native (N) and Utah (U) distributions. Precipitation amounts are reported in mm precipitation

Fig. 6 Boxplot comparisons of temperature related bioclimatic space inhabited by A. manicatum in their invasive (I), native (N) and Utah (U) distributions. Temperatures are reported in °C

limiting the geographic extent of the invasive models Intermountain West in the USA (Fig. 3a). Further- to separate continents, we were able to better estimate more, the poor predictive capability of the South known occurrences. This may be due to the nature of American invasive model suggests that the distribu- the background data utilized (Elith et al. 2011), which tion of A. manicatum may not be necessarily guided is narrower in distribution, or may be a relic of the by bioclimatic variables, but rather by the availability bioclimatic variability associated with the invasive of floral resources found in urban gardens (Kurtak distributions (Figs. 5 and 6). 1973), or by microclimates generated from changes Anthidium manicatum is naturalized in environ- in land use. While we think that the present invasion ments not predicted by the native model, such as the models are a conservative estimate for future 123 Author's personal copy

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A. manicatum colonization, it provides a theoretical of offspring reared in P. deltoides cotton is not structure on which to base future surveys. Our study known. contributes to the growing body of literature utilizing Recent surveys in natural and agricultural land- a SDM approach to predict the invasive potential of a scapes conducted by the authors have not yielded species, facilitating discussion on the mechanism specimens of A. manicatum. To date, all records in behind bioclimatic niche flexibility or conservatism western North America are restricted to residential (Fitzpatrick et al. 2007; Warren et al. 2008;Ro¨dder and commercial gardens, further suggesting synan- and Lo¨tters 2009). thropy (Jaycox 1966; Severinghaus et al. 1981; The naturalization of A. manicatum in apparently Matteson et al. 2008; Zavortink and Shanks 2008). non-suitable environments poses interesting biological Several species of hedge nettles (Stachys) are native questions. For example, are there physiological or to the USA, but none of them have been documented behavioral adaptations that allow this species to thrive as hosts for A. manicatum. In New York urban in new environments? In the invaded regions of Utah, gardens, Matteson et al. (2008) found A. manicatum temperatures fall below -20°C in the winter, and on in 44% of the gardens surveyed whereas A. oblong- average can be colder than the temperatures associated atum (Illiger), another adventive anthidiine bee, was with the native range of A. manicatum (Fig. 6d). only present in 5.6%. Synanthropy of A. manicatum Additionally, this region is characterized by lower may be dependent on non-native ornamental plants precipitation than the native range (Fig. 6a–e). These for forage and/or nesting substrate (especially drastic changes in temperature and moisture could S. byzantina), thus, limiting expansion to areas with directly affect the metabolic processes of the insect. gardens containing appropriate floral mixes. However, our data indicate that this species tends to The exact mechanism of A. manicatum transport is occur in urban settlements (Fig. 3b), where tempera- not yet known. However, it appears to be rapidly tures are usually warmer than rural areas, and irrigation colonizing distant environments through punctuated provides moisture during dry summers. We suspect dispersal (Davis and Thompson 2000). As docu- that human modified landscapes might facilitate their mented with many other organisms (e.g., Davis and survival in otherwise marginal or unsuitable habitats Thompson 2000 and references therein), A. manica- and that the most predictive bioclimatic variables in the tum could be transported by humans across long models, temperature and precipitation, may not reflect distances via nursery stock of ornamental plants. This the actual values. Interestingly, the seasonal activity of would not be surprising considering their wood A. manicatum adults in Utah, lasting from June to nesting behavior (Kurtak 1973; Severinghaus et al. October, seems longer than that reported in Germany 1981; Wirtz et al. 1992). Further research on the by Wirtz et al. (1992) where bees survived only to nesting biology and dietary requirements of this August, perhaps a factor of the warmer summer climate species is warranted to determine if invasion of wild in Utah (Fig. 6b,c). lands is possible. Based on its rapid colonization, Anthidium manicatum may exploit new plant especially in major urban settlements, and male resources for nectar, pollen or nest materials that aggressive behavior, we propose that A. manicatum enable it to inhabit novel environments. In France and should no longer be considered adventive, but should Germany, the diet of A. manicatum is restricted to be referred to as invasive (Colautti and MacIsaac about 25 plants, nearly all in Fabaceae, Lamiaceae 2004). Beyond the semantic change, the invasion of and Scrophulariaceae (Wirtz et al. 1992). In New A. manicatum may have repercussions in western York, Kurtak (1973) found that 37 plant species, most North America where 32 native Anthidium bees exist of which are non-native ornamentals, were used as and may be adversely affected by the presence of this food, and only five species were used for nesting territorial and aggressive species. material. Notably, while the primary plant utilized for nesting substrate was the introduced S. byzantina, Acknowledgments We thank Daniel Downey, Clint Burfitt females also used the pubescence of Populus delto- and the staff at the Utah Department of Agriculture and Food for providing us access to the trap by-catch and critical ides Bartram ex Marsh (Salicaceae) seeds, indicating information on trap locations and trapping protocols. We thank that they will use at least some native plant materials Leah Lewis and Joyce Knoblett for assistance in sorting by- for nesting purposes. However, the survival success catch from JBT. We thank Harold Ikerd and Daniel Young for 123 Author's personal copy

2126 J. P. Strange et al. specimen preparation and curation. Molly Rightmyer and Appendix Samuel Rivera provided critical reviews on an earlier version of this manuscript. We thank Matthew Fitzpatrick for editorial assistance, Janani Kalidasan and an anonymous reviewer for See Table 2. providing invaluable suggestions that greatly improved our analysis and discussion.

Table 2 Background and locality online data source summary of A. manicatum Source Institution URL Data Type

GBIF Agricultural research council’s http://data.gbif.org/datasets/resource/11946 Megachilidae background biosystematics division GBIF O¨ kostation (Freiburg) http://data.gbif.org/datasets/resource/2750 Megachilidae background GBIF BioFokus http://data.gbif.org/datasets/resource/8066 Megachilidae background GBIF Artenvielfalt am Eich- http://data.gbif.org/datasets/resource/11328 Megachilidae background Gimbsheimer Altrhein GBIF Artenvielfalt am Schlern http://data.gbif.org/datasets/resource/8055 Megachilidae background GBIF Artenvielfalt auf der Weide— http://data.gbif.org/datasets/resource/2697 Megachilidae background GEO-Hauptveranstaltung in Crawinkel GBIF Australian museum provider for http://data.gbif.org/datasets/resource/9105 Megachilidae background OZCAM GBIF Balkon (Norderstedt) http://data.gbif.org/datasets/resource/3048 Megachilidae background GBIF Bee specimens http://data.gbif.org/datasets/resource/1941 Megachilidae background GBIF Bees of Canada/Gschwendtner http://data.gbif.org/datasets/resource/1942 Megachilidae background property collection GBIF Bees of Canada/Joker’s hill http://data.gbif.org/datasets/resource/1947 Megachilidae background collection GBIF Bees of Ireland http://data.gbif.org/datasets/resource/10809 Megachilidae background GBIF Bees, wasps and ants recording http://data.gbif.org/datasets/resource/12037 Megachilidae background society—Bees, wasps and ants recording society—Trial dataset GBIF Biodiversidad de Costa Rica http://data.gbif.org/datasets/resource/333 Megachilidae background GBIF Biological and palaeontological http://data.gbif.org/datasets/resource/8107 Megachilidae background collection and observation data MNHNL GBIF Biologiezentrum Linz http://data.gbif.org/datasets/resource/1104 Megachilidae background GBIF Biologische station im Kreis http://data.gbif.org/datasets/resource/2703 Megachilidae background Wesel GBIF Biospha¨renpark Wienerwald— http://data.gbif.org/datasets/resource/8971 Megachilidae background Pfaffsa¨tten GBIF Biospha¨renpark Wienerwald— http://data.gbif.org/datasets/resource/3392 Megachilidae background Wiener Steinhofgru¨nde GBIF Biotope in Rheine—Aktion 350 http://data.gbif.org/datasets/resource/9001 Megachilidae background GBIF Bristol regional environmental http://data.gbif.org/datasets/resource/11926 Megachilidae background records centre—BRERC October 2009 GBIF Bugs (GBIF-SE: Artdatabanken) http://data.gbif.org/datasets/resource/1154 Megachilidae background GBIF BUND—Dassower see (Lu¨beck/ http://data.gbif.org/datasets/resource/2707 Megachilidae background Dassow) GBIF CNIN/Abejas de Me´xico/Apoidea http://data.gbif.org/datasets/resource/8394 Megachilidae background

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Table 2 continued Source Institution URL Data Type

GBIF Colec¸a˜o de Abelhas do Museu de http://data.gbif.org/datasets/resource/2003 Megachilidae background Cieˆncias e Tecnologia da PUCRS GBIF Colec¸a˜o de Entomologia do http://data.gbif.org/datasets/resource/2004 Megachilidae background Laborato´rio de Biologia Vegetal GBIF Colec¸a˜o de Entomologia do http://data.gbif.org/datasets/resource/12105 Megachilidae background Laborato´rio de Biologia Vegetal GBIF Colec¸a˜o Entomolo´gica do Depto. http://data.gbif.org/datasets/resource/2001 Megachilidae background de Sistema´tica e Ecologia GBIF Colec¸a˜o Entomolo´gica Moure e http://data.gbif.org/datasets/resource/2000 Megachilidae background Costa GBIF Colec¸a˜oEntomolo´gica Paulo http://data.gbif.org/datasets/resource/1997 Megachilidae background Nogueira-Neto—IB/USP GBIF Colec¸a˜o Entomolo´gica Pe. Jesus http://data.gbif.org/datasets/resource/1998 Megachilidae background Santiago Moure (Hymenoptera) GBIF Coleccio´n del Departamento de http://data.gbif.org/datasets/resource/8081 Megachilidae background Biologı´a (Zoologı´a) de la Universidad de La Laguna GBIF Corantioquia http://data.gbif.org/datasets/resource/8101 Megachilidae background GBIF Countryside council for Wales— http://data.gbif.org/datasets/resource/932 Megachilidae background UK biodiversity action plan invertebrate data for Wales GBIF Countryside council for wales— http://data.gbif.org/datasets/resource/11890 Megachilidae background welsh invertebrate database (WID) GBIF Department of freswater http://data.gbif.org/datasets/resource/11947 Megachilidae background invertebrates, makana biodiversity centre, Albany museum, Grahamstown GBIF Dorset environmental records http://data.gbif.org/datasets/resource/11862 Megachilidae background centre–Dorset SSSI species records 1952–2004 (Natural ) GBIF EcoRecord—Natural England’s http://data.gbif.org/datasets/resource/11819 Megachilidae background scientific files GBIF EcoRecord—wildlife trust for http://data.gbif.org/datasets/resource/11888 Megachilidae background Birmingham and the Black Country surveys GBIF EDIT—ATBI in Mercantour/Alpi http://data.gbif.org/datasets/resource/7949 Megachilidae background Marittime (France/Italy) GBIF Entomology collection http://data.gbif.org/datasets/resource/7911 Megachilidae background GBIF Fo¨hrenried (Fronreute und Baindt) http://data.gbif.org/datasets/resource/2970 Megachilidae background GBIF FFH-Gebiet ‘‘Calwer Heckenga¨u’’ http://data.gbif.org/datasets/resource/3373 Megachilidae background GBIF Finnish entomological database: http://data.gbif.org/datasets/resource/8239 Megachilidae background Hymenoptera GBIF Freiburger GEO-Tag der http://data.gbif.org/datasets/resource/8969 Megachilidae background Artenvielfalt GBIF Freigela¨nde Naturschutzscheune http://data.gbif.org/datasets/resource/2845 Megachilidae background Reinheimer Teich (Kreis Darmstadt-Dieburg)

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Table 2 continued Source Institution URL Data Type

GBIF GEO biodiversity day http://data.gbif.org/datasets/resource/1094 Megachilidae background GBIF GEO Hauptveranstaltung Tirol http://data.gbif.org/datasets/resource/2662 Megachilidae background (Innsbruck) GBIF GEO-Hauptveranstaltung (Insel http://data.gbif.org/datasets/resource/2704 Megachilidae background Vilm) GBIF GEO-Hauptveranstaltung (NLP http://data.gbif.org/datasets/resource/2643 Megachilidae background Harz/Hochharz) GBIF GEO-Hauptveranstaltung in http://data.gbif.org/datasets/resource/8974 Megachilidae background ‘‘wildtierland’’ GBIF GEO-Tag der Artenvielfalt http://data.gbif.org/datasets/resource/2783 Megachilidae background Hornwiesen-Grundschule GBIF Gieselbachtal Fulda-Harmerz http://data.gbif.org/datasets/resource/3100 Megachilidae background GBIF Gravel master thesis/Chubut http://data.gbif.org/datasets/resource/1943 Megachilidae background Argentina GBIF Gunma museum of natural history http://data.gbif.org/datasets/resource/8020 Megachilidae background insect specimen GBIF Gurgltal (Tarrenz) http://data.gbif.org/datasets/resource/2727 Megachilidae background GBIF Highland biological recording http://data.gbif.org/datasets/resource/11867 Megachilidae background group—HBRG insects dataset GBIF Hymenoptera collection of the http://data.gbif.org/datasets/resource/8080 Megachilidae background finnish museum of natural history GBIF Hymenopteran specimen database http://data.gbif.org/datasets/resource/611 Megachilidae background of Osaka museum of natural history GBIF Ibaraki nature museum, arthropoda http://data.gbif.org/datasets/resource/1814 Megachilidae background collection GBIF Illinois natural history survey http://data.gbif.org/datasets/resource/225 Megachilidae background GBIF Innenstadt Go¨ttingen—Natur http://data.gbif.org/datasets/resource/2851 Megachilidae background Zuhause GBIF Insect (MNHM-IN) http://data.gbif.org/datasets/resource/11470 Megachilidae background GBIF Insects http://data.gbif.org/datasets/resource/625 Megachilidae background GBIF Insekten http://data.gbif.org/datasets/resource/3292 Megachilidae background GBIF Instituto de Ciencias Naturales http://data.gbif.org/datasets/resource/2559 Megachilidae background GBIF Inventaire national du Patrimoine http://data.gbif.org/datasets/resource/2620 Megachilidae background naturel (INPN) GBIF Isartal Dingolfing http://data.gbif.org/datasets/resource/3117 Megachilidae background GBIF Knerer collection/Gschwendtner http://data.gbif.org/datasets/resource/1945 Megachilidae background property GBIF LaBoOb02 http://data.gbif.org/datasets/resource/2629 Megachilidae background GBIF Laborato´rio de Ecologia e http://data.gbif.org/datasets/resource/2002 Megachilidae background Biogeografia de Insetos da Caatinga GBIF Landschaftspflegehof (Berlin) http://data.gbif.org/datasets/resource/2656 Megachilidae background GBIF Langes Tannen http://data.gbif.org/datasets/resource/2682 Megachilidae background GBIF Lillachtal mit Kalktuffquelle bei http://data.gbif.org/datasets/resource/3002 Megachilidae background Weissenohe

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Table 2 continued Source Institution URL Data Type

GBIF Lothian wildlife information http://data.gbif.org/datasets/resource/856 Megachilidae background centre—Lothian wildlife information centre secret garden survey GBIF Merseyside BioBank—Merseyside http://data.gbif.org/datasets/resource/11893 Megachilidae background environmental advisory service dataset GBIF Missouri botanical garden http://data.gbif.org/datasets/resource/12084 Megachilidae background GBIF Mokpo museum of natural history http://data.gbif.org/datasets/resource/568 Megachilidae background insect GBIF Morandin PhD thesis/La Crete http://data.gbif.org/datasets/resource/1946 Megachilidae background Alberta GBIF Museum Victoria provider for http://data.gbif.org/datasets/resource/9107 Megachilidae background OZCAM GBIF NABU Naturschutzhof Netttetal http://data.gbif.org/datasets/resource/2759 Megachilidae background (Sassenfeld) e. V. GBIF National system of protected areas http://data.gbif.org/datasets/resource/8248 Megachilidae background in poland—animals GBIF National trust—Anglesey Abbey http://data.gbif.org/datasets/resource/11780 Megachilidae background wildlife species data held by the national trust GBIF National trust—hatfield forest http://data.gbif.org/datasets/resource/11874 Megachilidae background species data held by the national trust GBIF National trust—Ickworth species http://data.gbif.org/datasets/resource/11821 Megachilidae background data held by the national trust GBIF National trust—Wicken Fen nature http://data.gbif.org/datasets/resource/11873 Megachilidae background reserve species data held by the national trust GBIF National trust for Scotland http://data.gbif.org/datasets/resource/11841 Megachilidae background (staff)—NE Scotland NTS properties species records GBIF Natural England—invertebrate site http://data.gbif.org/datasets/resource/944 Megachilidae background register—England GBIF Natural history museum rotterdam http://data.gbif.org/datasets/resource/693 Megachilidae background GBIF Naturhistorisches Museum Mainz http://data.gbif.org/datasets/resource/12678 Megachilidae background Zoological Collection GBIF Naturschutzgebiet Bausenberg http://data.gbif.org/datasets/resource/2657 Megachilidae background GBIF Naturschutzgebiet Bausenberg http://data.gbif.org/datasets/resource/2674 Megachilidae background (Niederzissen) GBIF Neckartalsu¨dhang (Horb) http://data.gbif.org/datasets/resource/2680 Megachilidae background GBIF Packer collection/Madagascar http://data.gbif.org/datasets/resource/1948 Megachilidae background GBIF Paleobiology database http://data.gbif.org/datasets/resource/563 Megachilidae background GBIF Peabody entomology DiGIR http://data.gbif.org/datasets/resource/8138 Megachilidae background service GBIF Philosophenwald und Wieseckaue http://data.gbif.org/datasets/resource/2690 Megachilidae background in GieA˜ Y¨ en GBIF Rapid assessment program (RAP) http://data.gbif.org/datasets/resource/8076 Megachilidae background biodiversity survey database

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Table 2 continued Source Institution URL Data Type

GBIF Ratti master thesis/Fraser Valley, http://data.gbif.org/datasets/resource/1944 Megachilidae background British Columbia GBIF Rohrmeistereiplateau und http://data.gbif.org/datasets/resource/3382 Megachilidae background angrenzendes Gebiet GBIF Royal horticultural society http://data.gbif.org/datasets/resource/11879 Megachilidae background GBIF Rund um das LUGY http://data.gbif.org/datasets/resource/3022 Megachilidae background GBIF Schlern—(Bozen) http://data.gbif.org/datasets/resource/2661 Megachilidae background GBIF Schulgela¨nde Hans-Carossa- http://data.gbif.org/datasets/resource/3235 Megachilidae background gymnasium (Berlin) GBIF Schulhof Sandhofenschule http://data.gbif.org/datasets/resource/3045 Megachilidae background (Mannheim) GBIF Scottish wildlife trust— http://data.gbif.org/datasets/resource/11903 Megachilidae background commissioned surveys and staff surveys and reports for SWT reserves GBIF Shropshire ecological data http://data.gbif.org/datasets/resource/11906 Megachilidae background network—Shropshire ecological data network database GBIF South African museum collection http://data.gbif.org/datasets/resource/11952 Megachilidae background GBIF South East Wales biodiversity http://data.gbif.org/datasets/resource/12702 Megachilidae background records centre—CCW regional data: South East Wales non- sensitive species records GBIF Stadtpark Sulzbach-Rosenberg http://data.gbif.org/datasets/resource/2800 Megachilidae background GBIF Staffordshire ecological record— http://data.gbif.org/datasets/resource/11913 Megachilidae background SER Site-based surveys GBIF Staffordshire ecological record— http://data.gbif.org/datasets/resource/11912 Megachilidae background SER species-based surveys GBIF Steinbruch Mainz-Weisenau, 3. http://data.gbif.org/datasets/resource/3135 Megachilidae background Jahr GBIF Streuobstwiese RSG (Cham) http://data.gbif.org/datasets/resource/2637 Megachilidae background GBIF Suffolk biological records http://data.gbif.org/datasets/resource/11927 Megachilidae background centre—Suffolk biological records centre (SBRC) dataset GBIF Teich Berlin Wuhlheide http://data.gbif.org/datasets/resource/2853 Megachilidae background GBIF Thames valley environmental http://data.gbif.org/datasets/resource/11895 Megachilidae background records centre—local wildlife site surveys Oxfordshire GBIF The Norwegian species http://data.gbif.org/datasets/resource/11833 Megachilidae background observation service— invertebrates GBIF Trockenrasen und Buchenwald in http://data.gbif.org/datasets/resource/2723 Megachilidae background der Umgebung der Jugendherberge Bad Blankenburg GBIF Truppenu¨bungsplatz http://data.gbif.org/datasets/resource/2965 Megachilidae background Panzerkaserne Bo¨blingen GBIF Tullie house museum—Tullie http://data.gbif.org/datasets/resource/11900 Megachilidae background house museum natural history collections

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Table 2 continued Source Institution URL Data Type

GBIF Tullie house museum—Tullie http://data.gbif.org/datasets/resource/11917 Megachilidae background house museum. Invertebrate records other than Lepidoptera. Pre-2009 for Cumbria GBIF University of Alberta museums http://data.gbif.org/datasets/resource/2618 Megachilidae background entomology collection GBIF Unna-Mu¨hlhausen Wiesen http://data.gbif.org/datasets/resource/2865 Megachilidae background GBIF Unser Schulgela¨nde http://data.gbif.org/datasets/resource/2714 Megachilidae background GBIF USDA-ARS bee biology and http://data.gbif.org/datasets/resource/1904 Megachilidae background systematics laboratory GBIF Wald und Wiese am Buchwald http://data.gbif.org/datasets/resource/2676 Megachilidae background GBIF Wiesen am Treffpunkt Freizeit http://data.gbif.org/datasets/resource/3487 Megachilidae background GBIF Wiesen-Wa¨lder-Wasser um http://data.gbif.org/datasets/resource/3500 Megachilidae background Dansenberg, Biospha¨renreservat Pfa¨lzerwald GBIF ZFMK Hymenoptera collection http://data.gbif.org/datasets/resource/1840 Megachilidae background GBIF Biologiezentrum Linz http://data.gbif.org/datasets/resource/1104 A. manicatum Oberoesterreich GBIF Entomology collection http://data.gbif.org/datasets/resource/7911 A. manicatum GBIF EUNIS http://data.gbif.org/datasets/resource/198 A. manicatum GBIF Colec¸a˜o de Abelhas do Museu de http://data.gbif.org/datasets/resource/2003 A. manicatum Cieˆncias e Tecnologia da PUCRS GBIF ZFMK Hymenoptera collection http://data.gbif.org/datasets/resource/1840 A. manicatum GBIF Insects collection of the Ghent http://data.gbif.org/datasets/resource/1938 A. manicatum University zoology museum GBIF Colec¸a˜o Entomolo´gica Pe. Jesus http://data.gbif.org/datasets/resource/1998 A. manicatum Santiago Moure (Hymenoptera) GBIF University of Ghent—zoology http://data.gbif.org/datasets/resource/2625 A. manicatum museum—invertebratacollectie GBIF Hymenoptera collection of the http://data.gbif.org/datasets/resource/8080 A. manicatum finnish museum of natural history GBIF Colec¸a˜o Entomolo´gica Paulo http://data.gbif.org/datasets/resource/1997 A. manicatum Nogueira-Neto—IB/USP GBIF USDA-ARS Bee biology and http://data.gbif.org/datasets/resource/1904 A. manicatum systematics laboratory GBIF Coleccio´n del Departamento de http://data.gbif.org/datasets/resource/8081 A. manicatum Biologia Animal (Zoologia) de la Universidad de La Laguna GBIF Bees of Canada/Gschwendtner http://data.gbif.org/datasets/resource/1942 A. manicatum property collection GBIF Biologiezentrum Linz http://data.gbif.org/datasets/resource/1104 A. manicatum GBIF Inventaire national du Patrimoine http://data.gbif.org/datasets/resource/2620 A. manicatum naturel (INPN) GBIF O¨ kostation (Freiburg) http://data.gbif.org/datasets/resource/2750 A. manicatum GBIF Ratti master thesis/Fraser Valley, http://data.gbif.org/datasets/resource/1944 A. manicatum British Columbia

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Table 2 continued Source Institution URL Data Type

GBIF Bees, wasps and ants recording http://data.gbif.org/datasets/resource/934 A. manicatum society—bees, wasps and ants recording society—trial dataset GBIF Highland biological recording http://data.gbif.org/datasets/resource/954 A. manicatum group—HBRG hymenoptera dataset GBIF Natural England—invertebrate site http://data.gbif.org/datasets/resource/944 A. manicatum register—England GBIF Naturschutzgebiet Bausenberg http://data.gbif.org/datasets/resource/2657 A. manicatum GBIF Artenvielfalt auf der Weide— http://data.gbif.org/datasets/resource/2697 A. manicatum GEO-Hauptveranstaltung in Crawinkel GBIF Rund um das LUGY http://data.gbif.org/datasets/resource/3022 A. manicatum GBIF NABU Naturschutzhof Netttetal http://data.gbif.org/datasets/resource/2759 A. manicatum (Sassenfeld) e. V. GBIF Unna-Mu¨hlhausen Wiesen http://data.gbif.org/datasets/resource/2865 A. manicatum GBIF Innenstadt Go¨ttingen—Natur http://data.gbif.org/datasets/resource/2851 A. manicatum Zuhause GBIF Bugs (GBIF-SE: Artdatabanken) http://data.gbif.org/datasets/resource/1154 A. manicatum GBIF Finnish entomological database: http://data.gbif.org/datasets/resource/8239 A. manicatum hymenoptera BugGuide University of Iowa Bug Guide http://bugguide.net/index.php?q=search& A. manicatum keys=anthidium?manicatum& search=Search Discover life Discover life http://www.discoverlife.org/mp/ A. manicatum 20m?kind=Anthidium?manicatum GBIF Global biodiversity information facility

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