Dryland Organic Farming Partially Offsets 
Negative Effects of Highly Simplified 
Agricultural Landscapes on Forbs, Bees, 
and Bee-Flower Networks
Authors: Subodh Adhikari, Laura A. Burkle, Kevin M. 
O’Neill, David K. Weaver, Casey M. Delphia, Fabian 
D. Menalled 
This is a pre-copyedited, author-produced PDF of an article accepted for publication in 
Environmental Entomology following peer review. The version of record, see below citation, is 
available online at: https://dx.doi.org/10.1093/ee/nvz056.
Adhikari, Subodh, Laura A. Burkle, Kevin M O'Neill, Casey M. Delphia, David K. Weaver, and 
Fabian D. Menalled. "Dryland Organic Farming Partially Offsets Negative Effects of Highly 
Simplified Agricultural Landscapes on Forbs, Bees, and Bee-Flower Networks." Environmental 
Entomology48 , no. 4 (August 2019): 826-835. DOI:10.1093/ee/nvz056.
Made available through Montana State University’s ScholarWorks 
scholarworks.montana.edu 
Title: 
Dryland organic farming partially offsets negative effects of highly-simplified agricultural 
landscapes on forbs, bees, and bee-flower networks 
Authors: 
Subodh Adhikariabǂ, Laura A. Burklec, Kevin M. O’Neilla, David K. Weavera, Casey M. Delphiaac, 
Fabian D. Menalleda 
Authors’ institutional affiliation: 
a Department of Land Resources and Environmental Sciences, Montana State University, P.O. Box 
173120, Bozeman, MT 59717-3120, USA 
b Department of Entomology, Plant Pathology and Nematology 875 Perimeter Drive MS 2329 
Moscow, ID 83844-2329 (current address) 
c Department of Ecology, Montana State University, P.O. Box 173460, Bozeman, MT 59717-3460, 
USA 
ǂ Correspondence to: subodh.adhikari1@gmail.com 
Running title: 
Farming system effects on forbs and bees 
Key words 
Dryland conventional farming, natural habitat, Northern Great Plains, small-and large-bodied 
bees, wild bees 
Page 1 of 33 
Abstract 
Industrialized farming practices result in simplified agricultural landscapes, reduced biodiversity, 
and degraded species-interaction networks. Thus far, most research assessing the combined 
effects of farming systems and landscape complexity on beneficial insects has been conducted in 
relatively diversified and mesic systems and may not represent the large-scale, monoculture-
based dryland agriculture that dominates many regions worldwide. Specifically, the effects of 
farming systems on forbs, bees, and their interactions is poorly understood in highly-simplified 
dryland landscapes such as those in the Northern Great Plains, USA, an area globally important 
for conventional and organic small grain, pulse, forage, and oilseed production. During a 3-year 
(2013-2015) study, we assessed (i) the effects of dryland no-till conventional and tilled organic 
farming on forbs, bees, and bee-flower networks, and (ii) the relationship between natural habitat 
and bee abundance. Flower density and richness were greater in tilled organic fields than in no-
till conventional fields, and forb community composition differed between farming systems. We 
observed high bee diversity (109 taxa) in this highly-simplified landscape, and bee abundance, 
richness, and community composition were similar between systems. Compared with tilled 
organic fields, bee-flower interactions in no-till conventional fields were poorly connected, 
suggesting these systems maintain relatively impoverished plant-pollinator networks. Natural 
habitat (11% of the landscape) did not affect small-bodied bee abundance in either farming 
system, but positively affected large-bodied bees within 2000 m of crop field centers. In highly-
simplified agricultural landscapes, dryland organic farming and no-till conventional farming 
together support relatively high bee diversity, presumably because dryland organic farming 
enhances floral resources and bee-flower networks, and no-till management in conventional 
farming provides undisturbed ground-nesting habitats for wild bees.  
Page 2 of 33 
Introduction 
While modern industrialized crop production systems provide valuable agronomic and economic 
benefits to humankind, they are also major drivers of declines in local and regional biodiversity. 
For example, bees (Hymenoptera: Apoidea, Apiformes) provide billions of dollars of pollination 
services to crops globally, but a suite of direct and indirect anthropogenic stressors, including 
agricultural intensification, reduction of floral resources, landscape simplification, pesticide 
toxicity, and exposure to parasites and pathogens, are driving their declines (Goulson et al. 
2015). Declines in bee abundance and diversity, in turn, influence bee-flower networks (e.g., 
Burkle et al. 2013), negatively impacting ecosystem functioning and food security (Gallai et al. 
2009, Vanbergen 2013).  
Organic farming relies on frequent crop rotation and a lack of synthetic off-farm inputs such as 
herbicides, resulting in greater weed abundance and diversity (Menalled et al 2001, Hole et al. 
2005). Changes in weed abundance and composition could positively influence beneficial 
insects, including bees (Nicholls and Altieri 2013), via plant-mediated bottom-up effects 
(Scherber et al. 2010). Studies conducted in drylands of the Northern Great Plains (NGP), a key 
agricultural region of small grain, pulse, and oilseed crop production, have also shown higher 
weed abundance and diversity in organic systems compared to conventional ones (Pollnac et al. 
2008). Nevertheless, how differing weed communities are associated with the abundance and 
diversity of bees and bee-flower networks across farming systems is unknown for this region. 
 Additionally, within crop fields, weedy forbs (i.e., broad-leaf plants) and mass-flowering crops 
(e.g., canola, Brassica napus L.) provide food resources to beneficial insects for a short time 
interval (Morandin and Winston 2006), but surrounding uncultivated natural habitats provide 
season-long food resources, nesting substrates and stable refugia (Landis et al. 2005, Requier 
Page 3 of 33 
2015). Studies conducted in diversified agroecosystems worldwide have shown positive effects 
of natural habitat on farmland biodiversity (Rader et al. 2014), bee pollinators (Kennedy et al. 
2013, Boscolo et al. 2017), and pollination networks (Moreira et al. 2015). However, the 
relationship between natural habitat and farmland biodiversity is poorly understood in the highly-
simplified dryland landscapes. that rank high in net productivity and help meet the global food 
demand (Millennium Ecosystem Assessment 2005). Hence, understanding biodiversity and its 
functioning in drylands is key to supporting future crop production and food security, 
particularly because these ecosystems are projected to increase and occupy 48% of the global 
land surface by 2025 due to climate change (Huang et al. 2016).  
Farming systems and amount of natural habitat in agricultural landscapes influence bee 
communities (Holzschuh et al. 2007) and pollination (Nicholson et al. 2017), but the effects 
largely depend on landscape scale and complexity (Steffan-Dewenter et al. 2002). For instance, 
Holzschuh et al. (2007) found that, when compared to conventional fields, the effect of organic 
farming on bee diversity was stronger in simplified landscapes than in complex landscapes. 
Similarly, Nicholson et al. (2017) found that intensive farm management (i.e., large grain crop 
area and high pesticide use) exacerbates the negative effects of limited natural habitat on bee 
communities and pollination.  
The effects of percent natural habitat on bee communities may vary as a function of species-
specific bee body sizes (Benjamin et al. 2014, Forrest et al. 2015). The foraging ranges of small-
bodied (intertegular width < 2.25 mm) bees are generally limited to a radius of less than 500 m 
from their nests (Gathmann and Tscharntke 2002, Greenleaf et al. 2007; but see Castilla et al. 
2017). This limitation may make small-bodied bees more vulnerable to the impact of landscape 
simplification (Jauker et al. 2013, Benjamin et al. 2014) when compared to large-bodied 
Page 4 of 33 
(intertegular width ≥ 2.25 mm) bees with larger flight capacities and foraging ranges (Westphal 
et al. 2006, Greenleaf et al. 2007).  
Theoretically, a simplified agricultural landscape with limited natural habitat such as in the NGP 
should have stronger negative effects on small-bodied bees than on large-bodied bees (De Palma 
et al. 2015; but see Forrest et al. 2015). Hence, in highly-simplified landscapes, lower 
abundances of small-bodied bees are expected compared to abundances of large-bodied bees, but 
there is currently no empirical evidence testing this expectation. Previous studies on the 
interacting effects of farming system and amount of natural habitat on bee communities have 
mainly been conducted in relatively diversified and mesic agroecosystems and are lacking for 
highly-simplified dryland agricultural landscapes. Further, to our knowledge, no study has 
formally assessed the joint impact of farming systems and percent natural habitat on forbs, bees, 
and bee-flower networks in highly-simplified dryland agricultural landscapes.  
To address these knowledge gaps, we tested the effects of no-till conventional vs. tilled organic 
farming on forbs, bees, and bee-flower networks in a three-year, on-farm study in drylands of the 
NGP. We also assessed how the percentage of natural habitat within various distances from crop 
fields might mediate the effects of farming system on the abundances of small- and large-bodied 
bees. We hypothesized that: (i) because of the higher crop rotation and avoidance of synthetic 
herbicides, organically-managed tilled wheat fields (hereafter, organic system) would have 
greater forb flower density and species richness, and different forb community composition than 
chemically-managed no-till wheat fields (hereafter, conventional system), (ii) greater floral 
density and species richness in organic fields would be associated with differences in bee 
community composition and dispersion, and positively correlated with the abundance and 
diversity of bees and the complexity of bee-flower networks, and (iii) percentage natural habitat 
Page 5 of 33 
would be positively associated with the abundances of both small- and large-bodied bees, but the 
association would be stronger for small-bodied bees than for large-bodied bees, especially in 
conventional fields.  
Materials and methods 
Site description and cropping history 
We conducted this three-year, on-farm study in conventional and organic wheat fields near Big 
Sandy, Montana, USA (Fig. 1; 48.036N, 110.014W; elevation 960 m). Located in an important 
dryland, small-grain producing region in the NGP, the Big Sandy area is relatively dry (i.e., the 
94-year mean annual precipitation is 325 mm) and hot (i.e., mean annual minimum and
maximum temperatures are -1.2C and 14.8C; see details in Adhikari et al., 2018). In each year 
from 2013 to 2015, we selected three conventionally-managed, no-till spring wheat (Triticum 
aestivum L.) and three adjacent organically-managed tilled “Kamut” wheat (Triticum turgidum, 
ssp. turanicum McKey) fields (Fig. 1). While conventionally managed farms follow no-till 
practices in this region, tillage is commonly used in organic farms to terminate cover crops, 
control weeds, and prepare for plantation. Different fields were chosen each year for a total of 18 
fields, ranging from 25 ha to 70 ha and separated by a minimum of 500 m (see details of 
cropping history for each field in Adhikari et al. 2018 and Adhikari and Menalled 2018).  
Forb and bee community sampling 
Each year, we established a randomly-oriented, 55-m transect within each field, located at least 
150 m from any field border. At three randomly selected points along this main transect, we 
established three perpendicular 25-m, sub-transects at each field. Each year, on three dates with 
Page 6 of 33 
one each in June, July, and August, we quantified forb communities by visually estimating 
percent cover by species within a 0.5 × 1 m quadrat placed perpendicular to each sub-transect at 
every 1 m interval. Additionally, we estimated flower density by counting open flowers per 
individual forb plant within each quadrat. The naturally short growing season of the study area 
and logistical constraints precluded us from obtaining samples outside the June to August period. 
On the same dates on which we sampled forb communities, we also assessed bee communities 
using pan traps (250 ml), one of the most efficient methods of sampling pollinator communities 
passively (Westphal et al. 2008, Lebuhn et al. 2013). We used blue, yellow, and white traps (i.e., 
cups) filled with diluted soapy water to break the surface tension; these colors are effective at 
passively capturing diverse bee groups (Lebuhn et al. 2013). We alternated traps (securely 
hanging on polyvinyl chloride poles) of each color, placing them 5 m apart at crop canopy height 
along the main transects described above (n = 12 pan traps per transect). After 24 hours in the 
field, bees were collected from traps and stored in a freezer until they could be processed. As 
above, seasonal and logistic constraints determined our sampling efforts. 
Bees were identified using taxonomic keys, identification guides, and experts (Table S1). Eighty-
five of 109 bee taxa were identified to species, while the remaining 24 were identified to 
subgenus only (mainly Lasioglossum (Dialictus) spp.) or morphospecies. Using digital calipers, 
we also measured intertegular width of up to 10 randomly-chosen bees of each species and used 
this variable as a proxy of overall bee body size and potential foraging distance (Greenleaf et al. 
2007). 
Bee-flower networks 
To assess the impact of farming system on bee-flower interactions, we walked each of the 25-m 
Page 7 of 33 
sub-transects used to evaluate forb communities for 20 minutes and recorded the identity and 
frequency of bees visiting flowers within 1 m of each sub-transect. Each year, we performed 
these observations three times between June and August (once each month; 54 h total). All 
observations were conducted between 0800 and 1625 h under sunny, warm (mean temperature: 
29 ± 0.3°C, n = 231), and calm-breeze (mean wind speed: 5 ± 0.2 m s-1, n = 231) conditions. 
During the observations, we collected all flower visiting bees using an insect net for later 
identification. In the rare cases (<10%) when it was not possible to capture bees during 
observations, we identified them to the lowest possible taxonomic level on the wing (usually 
genus).  
Percent natural habitat and its relationship to small- and large-bodied bee abundance 
For each field, we acquired cloud-free Landsat-8 images (30 × 30 m resolution) from the United 
States Geological Survey and used ArcGIS 10.2 to analyze the images. Using ArcMap and V-
LATE 2.0 beta (Vector-based Landscape Analysis Tools Extension), we classified the areas of 
land use types (“cropland,” “natural habitat,” “water,” and “others”) and calculated the percent 
natural habitat (all uncultivated semi-natural lands with forbs and grasses such as roadside 
margins, and grasslands with frequent grazing or non-grazing) within four concentric circles of 
250 m, 500 m, 1000 m, and 2000 m radii from the center of each sampled field. We chose these 
radii, following Steffan-Dewenter et al. (2002), to determine the spatial scales at which percent 
natural habitat influences bee abundance. Additionally, we used ground observation, Google 
Earth, and USDA-National Agriculture Imagery Program to crosscheck the land use types.  
Data analyses 
Page 8 of 33 
After pooling data from all transects at each field, we first calculated forb flower density, bee 
abundance, species richness, and species evenness (following Pielou’s evenness; Pielou 1966). 
We selected the most representative response variables to include in our analyses, after 
determining whether such variables were strongly correlated (rp > 0.6; Table S2).  
After removing strongly corelated variables (such as forb diversity and bee diversity), to test the 
effect of farming system on forb flower density, forb species richness, bee abundance, and bee 
species richness (i.e., for count data), we used generalized linear mixed-effects models (“glmer”) 
with Poisson distributions. Diagnostic plots such as residual plots were used to check if the 
models met the assumptions of homogeneity of variance. Similarly, we used linear mixed-effect 
models (“lmer”) to test the effects of farming system on forb and bee species evenness. 
Diagnostic plots such as QQ plots and residual plots were used to check if the models met the 
assumptions of normality and homogeneity of variance, and response variables were log-
transformed as required. In all models, farming system was treated as a fixed effect while year 
and field were treated as random effects, with month nested within field, and field nested in year. 
The effects of conventional and organic farming on forb and bee community composition were 
assessed using Permutational Multivariate Analysis of Variance (PERMANOVA) on a Bray-
Curtis dissimilarity matrix (Bray and Curtis 1957) and visualized with Non-metric 
Multidimensional Scaling (NMDS) ordination. Also, PERMANOVA was used to assess any 
temporal shift or seasonal variation (i.e., across sampling months) in forb and bee communities. 
Community dispersion (β-diversity) between conventional and organic systems as well as among 
months was tested using the “betadisper” function. After the “adonis” test of PERMANOVA, if 
significant, we did post-hoc tests using “pairwise.perm.manova” function and reported the false 
discovery rate adjusted p-value (Hervé 2017). Following significant PERMANOVAs, we used 
Page 9 of 33 
“simper” to determine which species contributed the most to the observed dissimilarity in 
community composition between farming systems or among months (Oksanen et al. 2016). We 
identified indicator species for both farming systems and for all months using “IndVal” (Cáceres 
and Legendre 2009), a procedure to detect key species in a particular site based on their relative 
abundance (specificity) and relative frequency (fidelity) (Dufrêne and Legendre 1997).  
Rare bee-flower interactions in conventional fields (see Results) precluded quantitative analysis 
of the effects of farming system on network characteristics. 
To compare the proportion of natural habitat surrounding conventional and organic fields within 
the circles with 500 m, 1000 m, and 2000 m radii described above, we utilized generalized linear 
mixed models - automatic differentiation model builder (“glmmADMB”) with beta distribution 
(Skaug et al. 2016). However, we did not include the 250 m radius in our analysis because the 
majority of crop fields (14 out of 18 fields) had 0% natural habitat within this radius. To evaluate 
the effects of percent natural habitat on large- and small-bodied bee abundances and following 
Benjamin et al. (2014), all sampled bees were divided into “large-bodied” (intertegular width ≥ 
2.5 mm) bees and “small-bodied” (intertegular width < 2.5 mm) bees. Using generalized mixed-
effects models (“glmer”), we tested the effect of percent natural habitat within a 500 m, 1000 m, 
or 2000 m radius from the center of each field on large- and small-bodied bee abundances. In the 
mixed-effects models, percent natural habitat, farming system, and their interaction (natural 
habitat × farming system) were treated as a fixed effect while field was treated as a random 
effect. To determine whether the effects of percent natural habitat on small- and large-bodied 
bees were stronger in conventional fields than in organic fields, we calculated marginal R2 
(variance explained by fixed factors alone) and conditional R2 (variance explained by fixed and 
random factors) from mixed-effect models (Nakagawa and Schielzeth 2013), using “MuMIn”. 
Page 10 of 33 
All statistical analyses and graphics were conducted with R 3.2.4 (R Core Team 2016). We used 
“lme4” (Bates et al. 2015), “glmmADMB” (Skaug et al. 2016), and “MuMIn” (Barton 2017) 
packages for mixed-effect models. Multivariate analyses, PERMANOVA post-hoc tests, and 
ordination graphics were conducted using “vegan” (Oksanen et al. 2017), and 
“RVAideMemoire” (Hervé 2017) packages. We produced all other graphics using the “ggplot2” 
(Wickham 2009) and ‘sciplot’ (Morales 2017) packages. 
Results 
Forb communities 
Over the 3-year period of our study, we recorded 38 forb species, primarily non-native 
agricultural weeds. Of these, we observed 14 species in the conventional fields and 37 in the 
organic fields (Table S3). Flower density was 385% greater in organic fields than in 
conventional fields (Table 1). Forb species richness was 248% greater in organic fields than in 
conventional fields (Table 1). However, there was no effect of farming system on forb species 
evenness (Table 1).  
Forb community composition differed between farming systems (Fig. 2; pseudo-F 2 1, 16 = 6.9; r = 
0.30; P = 0.001). Also, forb community dispersion was greater across conventional fields than 
across organic fields (F1, 16 = 35.2; P ≤ 0.001). There was no temporal shift in forb community 
composition (pseudo-F 2 2, 51 = 0.28; r = 0.01; P = 0.311) through the growing season (June, July, 
and August) in both farming systems. Together, Thlaspi arvense L., Salsola kali L., Carthamus 
tinctorius L., Polygonum convolvulus L., Pisum sativum L., Chenopodium album L., Medicago 
sativa L., and Amaranthus retroflexus L. contributed 72% to the observed dissimilarity in forb 
community composition between farming systems. These species were more abundant in organic 
Page 11 of 33 
fields, and five of them were absent from conventional fields. Indicator species analysis did not 
reveal any forb associated with either system.  
Bee communities 
We collected a total of 8,710 bee specimens, representing at least 109 species, 25 genera, and 
five families (Andrenidae, Apidae, Colletidae, Halictidae, and Megachilidae) from the pan 
traps (Table S4). Of the bees collected in our samples, all but 12 specimens (10 Apis mellifera 
and 2 Bombus impatiens) were wild (i.e., non-managed) bees (Table S4). The five most 
abundant bee taxa for both conventional and organic systems were Lasioglossum (Dialictus) 
spp., Agapostemon texanus Cresson, Eucera hamata (Bradley), Agapostemon femoratus 
Crawford, and Agapostemon virescens (F.). Bee intertegular widths ranged from an average of 
0.7 ± 0.1 mm (Perdita fallax Cockerell) to 5.9 ± 0.4 mm (Bombus nevadensis Cresson). 
Approximately 81% of the bee taxa were ground nesting bees, representing 98.6% of the total 
individuals captured (Table S4). Approximately 79% of the total capture were small-bodied bees 
(intertegular widths < 2.5 mm). 
We did not detect any differences between conventional and organic systems in bee abundance, 
species richness, or evenness (Table 2). Across years, we observed no differences in overall bee 
community composition between conventional and organic fields (pseudo-F1, 52 = 1.35; r2 = 0.03; 
P = 0.168). However, bee community composition differed between farming systems in August 
(Fig. 3; pseudo-F 2 4, 48 = 2.2; r = 0.27; P = 0.001), with Lasioglossum (Dialictus) spp., Melissodes 
agilis Cresson, Melissodes pallidisignatus Cockerell, Halictus ligatus Say, and Melissodes 
lupinus Cresson contributing 75% of the total observed dissimilarity. In August, M. 
pallidisignatus was indicative of conventional farming, whereas Andrena sp.1 and Anthidium 
Page 12 of 33 
porterae Cockerell were indicative of organic farming in (Table S5); all three taxa being ground-
nesting bee species. Across fields, we observed a temporal shift in bee community composition 
(Fig. 3; pseudo-F 2 2, 51 = 7.75; r = 0.23; P = 0.001) over the growing season, with sampling 
months different from each other (P = 0.001, for all pairwise combinations). Twenty bee species 
were characteristic in June, two species were characteristic in July, and four species (all 
Melissodes) were characteristic in August (Table S5).  
Bee-flower networks 
Forbs and bee-forb interactions were so rare in conventional fields that bee-flower networks 
either could not be quantified, or they were extremely simplified (i.e., single forb species visited 
by a single bee taxon) (Fig. 4). In contrast, bee-flower interactions were more often observed in 
organic fields, hence the bee-flower networks were more complex (Fig. 4). Only six bee species 
(six individuals) were observed in the bee-flower networks of conventional fields over the three 
years, whereas 21 bee species (104 individuals) were recorded in organic fields. Because of its 
dominance in the landscape, Medicago sativa was the plant species most frequently visited by 
bees in both systems, and the unidentified Halictus spp. were observed on more plant species 
than any other bee taxa. 
Percent natural habitat and its relationship to small- and large-bodied bee abundance 
Since the landscape was primarily occupied by cropland, it had a low proportion of natural 
habitat (11 ± 2.2% within 2000 m or 7± 2.6% within 1000 m of field centers; Fig. 1; Table S6). 
Percent natural habitat within 500 m and 1000 m from the center of the conventional fields was 
greater than those of the organic fields, but this difference was marginal within 2000 m (Table 
3).  
Page 13 of 33 
Percent natural habitat did not affect small-bodied bee abundance in either farming system for 
any of the analyzed distances from the field center (Fig. 5a-c; 500 m: F1, 16 = 0.27; P = 0.610, 
1000 m: F1, 16 = 0.21; P = 0.650, and 2000 m: F1, 16 = 2.23; P = 0.150). Similarly, we found no 
effect of percent natural habitat on large-bodied bee abundance in either farming system in the 
500 m radius (Fig.5d; F1, 16 = 0.15; P = 0.720) or in the 1000 m radius (Fig. 5e; F1, 16 = 2.5; P = 
0.141). However, percent natural habitat within the 2000 m radius positively related to large-
bodied bee abundance (Fig. 5f; F1, 16 = 11; P = 0.004) in both conventional and organic fields; 
and the effect of natural habitat on large-bodied bee abundance was similar between 
conventional (conditional R2 = 0.93, marginal R2 = 0.46) and organic (conditional R2 = 0.93, 
marginal R2 = 0.41) fields. 
Discussion 
Prior to this study, little was known about wild bees and bee-flower networks in highly-
simplified agricultural landscapes in dryland settings, like those that dominate the NGP. 
Although we found that organic fields supported greater forb flower density and species richness 
and more complex bee-flower networks, we observed no differences in bee abundance or 
richness from pan traps between organic and conventional fields. However, despite very limited 
natural habitat, there was surprisingly high bee diversity in both systems. Overall, our findings 
suggest that in highly-simplified dryland agricultural landscapes, the abundance and richness of 
flowers in organic farming enhances bee-flower interactions. 
Forb communities 
Consistent with Pollnac et al. (2008), organic fields had greater forb flower density and species 
richness than conventional fields, which likely provided food resources to beneficial insects, 
Page 14 of 33 
influenced forb-insect interactions, and supported biodiversity and ecosystem services (Jordan 
and Vatovec 2004, DiTommaso et al. 2016). The observed differences in forb communities could 
result from the different ecological filters imposed by the two studied farming systems (Smith et 
al. 2015). Specifically, the continuous use of selective herbicides in conventional small grain 
fields excludes dicotyledonous species (Grossmann 2009), ultimately reducing floral resources 
for pollinators (Nicholls and Altieri 2013, Adhikari et al. 2019). Also, in agreement with 
Menalled et al. (2001), we found greater temporal variability in forb community composition in 
conventional fields than in organic fields, suggesting greater stability of resources for bees in 
organic fields. 
Bee communities  
While previous studies demonstrated that organic farming supports greater floral and bee 
diversity than conventional farming (Holzschuh et al. 2007), we failed to detect differences in the 
assessed bee community metrics between farming systems. One possible explanation is that 
while plant species are strongly affected by farming system at the within-field scale, mobile 
species like bees respond at larger scales with home ranges exceeding field size (Gabriel et al. 
2010; but see Benjamin et al. 2014). For example, since the increased soil disturbance due to 
tillage in organic fields may reduce the habitat suitability for ground-nesting solitary (Shuler et 
al. 2005) and social (Williams et al. 2010) bees, these species may prefer un-tilled conventional 
fields for nesting and the adjacent flower-rich organic fields for foraging. However, our study 
found no differences in ground nesting bee abundance and diversity between no-till conventional 
and tilled organic fields, possibly because a vast majority of the bees in this system were solitary 
(vs. social and semi-social; Michener 2007, Table S1) and less sensitive to the disturbances 
imposed by tillage, compared with social bees (Williams et al. 2010). This hypothesis deserves 
Page 15 of 33 
further consideration but assessing landscape-scale bee habitat use was beyond the scope of this 
study. Second, pan traps may have served as ‘magnets’ by luring bees that were flying through 
the fields searching for forage. This magnetic effect might be stronger (1) in landscapes with a 
low proportion of natural habitats, (2) in conventional fields with less floral resources, and (3) 
for bees with nests within the foraging range of pan traps. Hence, pan trap sampling may not 
allow us to distinguish resident or explicitly foraging bees from those flying further afield (but 
see Westphal et al. 2008).  
Conventional and organic fields had surprisingly high bee diversity, given the extensive 
monoculture-based dryland cereal grains system (i.e., wind-pollinated) of the studied area, the 
limited abundance of natural habitat, and the consistently windy conditions that may have 
reduced bee movement. Though we lacked information from simplified dryland agricultural 
landscapes, other studies of bee communities done in natural and semi-natural systems in 
Montana have revealed similar or lower bee diversity. For example, Fultz (2005) reported 119 
species of bees at the Tenderfoot National Experimental Forest in central Montana, whereas 
Pearce et al. (2012) found 48 species in south-central Montana on a floristically-diverse 
wildflower seed farm surrounded by natural and diversified agricultural areas. It is possible that 
rapid drainage in the sandy soil of the NGP landscape allows ground-nesting bees to thrive (Cane 
1991), and the mosaic of weed-free no-till conventional fields and weedy but tilled organic fields 
that exist in the studied area provides required nesting habitat and resources to support diverse 
bee assemblages.  
Bee community composition did not differ between the two farming systems in June or July but 
did in August when Melissodes pallidisignatus was more abundant in conventional fields while 
Andrena sp.1 and Anthidium porterae were associated with organic fields. There are limited 
Page 16 of 33 
studies on the biology, ecology, or phenology of these species, so it is not clear why these 
species were unequally distributed across systems. For example, M. pallidisignatus is reported to 
prefer sandy soil for nesting and is known as an oligolege (collecting pollen from a limited set of 
genera) in Asteraceae (Thorp and Chemsak 1964). But, Asteraceae were rare in the conventional 
fields and soil structure was not noticeably different between these dryland conventional and 
organic fields (Adhikari, Pers. Obs.). Similarly, the biology of Andrena sp. 1 (or, Andrena 
genus) and A. porterae is largely unknown, but are likely ground nesters, with oligolectic to 
polylectic habits (Gonzalez and Griswold 2013, Ascher and Pickering 2014). Association of 
these bees with organic fields could be due to the availability and diversity of floral resources. 
Bee-flower networks 
Due to low forb flower density and richness in conventional fields, we recorded fewer bee-
flower interactions and less connected bee-flower networks compared to those in organic fields. 
Our results are partly consistent with Kehinde and Samways (2014), who compared insect-
flower networks between conventional and organic vineyards in South Africa, where the higher 
number of interactions in organic vineyards was due to their greater forb abundance. Power and 
Stout (2011) also found more connected and “larger” insect-flower networks in Irish organic 
dairy farms with greater floral and bee abundance than in conventional farms. Yet, compared 
with networks observed in more botanically diverse and mesic systems (Power and Stout 2011, 
Kehinde and Samways 2014, Tucker and Rehan 2017), bee-flower networks in the organic fields 
we assessed were far less connected, suggesting that highly-simplified dryland agricultural 
landscapes maintain relatively impoverished bee-flower networks, despite the high diversity of 
bee taxa.  
Page 17 of 33 
Percent natural habitat and its relationship to small- and large-bodied bee abundance 
Previous studies assessing bee abundance and diversity in farmlands have been primarily 
conducted in diversified systems and heterogeneous landscapes (Kennedy et al. 2013, Boscolo et 
al. 2017) with more mesic settings, and little knowledge existed about how percent natural 
habitat impacts bee communities in highly-simplified dryland landscapes. The studied fields had 
only 11% natural habitat within 2000 m of their centers (or only 7± 2.6% within 1000 m). 
However, Morandin and Winston (2006) reported that 30% of the land within 750 m of field 
edges in Alberta, Canada is required to remain uncultivated to sustain pollinators and maximize 
Brassica napus L. production. This suggests that the natural habitats in the studied, resource-
constrained dryland system are too limited to be the sole support of pollinators.  
In both farming systems, the abundances of small-bodied bees were not related to natural habitat 
at either field or landscape scales, probably because these bees had short foraging ranges 
(Benjamin et al. 2014) that prevented them from moving across habitat boundaries. Studies have 
shown that the foraging range of small-bodied bees is limited to less than 500 m from their nests 
(Gathmann and Tscharntke 2002, Greenleaf et al. 2007) and can be as low as 90 m (Wright et al. 
2015; but see Castilla et al. 2017). These studies also suggested that with a short-distance flight 
capacity, small bees are confined near field edges making them more vulnerable to the impact of 
dryland landscape simplification (Jauker et al. 2013). In our study, most of the sampled bees 
(79%) were small-bodied and were collected at the centers of large conventional and organic 
fields. How these bees are sustained in the center of large, resource-constrained fields with little 
nearby natural habitat is unknown and requires further research.  
Page 18 of 33 
By contrast, the abundances of large-bodied bees increased with increasing natural habitat 2000 
m from crop-field centers in both farming systems. These results agree with previous research 
showing that large-bodied bees, due to their greater foraging range, respond positively to 
increases in natural habitat (Westphal et al. 2006, Greenleaf et al. 2007). Large-bodied bees in 
the highly-simplified dryland landscape of the NGP may have become adapted to fly greater 
distances, as they have shown extreme foraging plasticity to visit consistent floral patches in the 
landscape (Jha and Kremen 2012). Even though, there were differences in the amount of natural 
habitat between organic and conventional fields within 500 m and 1000m of their centers, natural 
habit was not significantly different at the scale of 2000 m. Also, due to extremely limited 
natural habitat, the biological impacts of these differences could be negligible in the smaller 
spatial scales, particularly for the large-bodied bees with longer foraging distances (Steffan-
Dewenter et al. 2002). 
Conclusions 
This study indicates that in a highly-simplified dryland agricultural landscape, the greater forb 
flower density and richness of organic fields was associated with more connected bee-flower 
networks when compared to conventional fields. However, both farming systems contained 
equally high bee diversity. Our results raise questions about how such diverse bee communities 
can be sustained in highly-simplified and seemingly depauperate dryland agricultural landscapes. 
For instance, the extent to which the simple bee-flower networks observed could be resilient in 
the face of agricultural intensification and climate change is largely unknown. Overall, our 
results suggest that practicing organic methods in the drylands of the NGP and intermixing 
natural habitat with crop fields may help to maintain or improve bee-flower network complexity 
and potentially better sustain these bee communities. 
Page 19 of 33 
Acknowledgements 
This work was supported by the USDA-National Institute of Food and Agriculture [grant 
numbers MONB00314 and MONB00128]. We thank all conventional and organic farmers for 
providing their farms to conduct our research. S. McKenzie, N. Ranabhat, S. Johnson, M. Nixon, 
C. Welch, A. Adhikari, and K. Crisp are thankful for their assistance in data collection and T.
Griswold, S. Burrows, M. Orr, Z. Portman, H. Ikerd, and K. Wright for their help in bee 
identification. The authors declare no conflicts of interest. 
Appendix A. Supplementary data 
Supplementary data associated with this article can be found, in the online version, at…… 
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Figure legends 
Figure 1: Study area in Big Sandy, MT, USA. (a) All 18-field shown (9 conventional: red 
triangles and 9 organic: blue filled circles). (b) Example of highly-simplified 
agricultural landscape in the Northern Great Plains. The picture was taken in 2015 
during field sampling at one of the organic wheat fields. (c) Percent cropland, semi-
natural habitat, other, and water (mean ± SE) within each of the four circles across all 
conventional and organic fields combined. 
Figure 2: Non-metric multidimensional scaling ordination of forb communities observed in 
conventional and organic wheat fields. Dotted ellipses encircle communities in 2013, 
dashed ellipses encircle communities in 2014, and solid ellipses encircle communities 
in 2015. Each point represents a conventional (red) or organic field (blue).  
Figure 3: Non-metric multidimensional scaling ordination of bee communities observed across 
June, July and August in conventional (red triangle) and organic (blue filled circles) 
fields. Dotted ellipses encircle communities in June, dashed ellipses encircle 
communities in July, and solid ellipses encircle communities in August. Due to the non-
significant effects of year, values were pooled across three years (2013-2015). Each 
point represents a month at each field across three years. 
Figure 4: Comparison of bee-flower networks between conventional and organic wheat fields 
across three years. The top yellow horizontal bars represent bee taxa and the bottom 
green horizontal bars represent forb species. Black lines connecting bee taxa and forb 
species represent interaction links (visits) and the thickness of these lines corresponds 
Page 29 of 33 
to the frequency of interactions. To show general patterns between bee and forb 
species, all observation data were pooled across months and fields. 
Figure 5: (a-c) Small bee (< 2.5 mm intertegular width) and (d-f) large bee (≥ 2.5 mm 
intertegular width) abundance versus percent natural habitat within 500 m, 1000 m, and 
2000 m (* = P < 0.05). Circles were drawn from the centers of each conventional and 
organic wheat field, where transects were established to trap bees. Shaded bands around 
lines are the 95% confidence interval.  
Table legends 
Table 1: Floral density, species richness, and evenness in conventional and organic fields 
between 2013 and 2015 in Big Sandy, MT. Values were pooled across three years. 
Significant P-values (P ≤ 0.05) are bolded. 
Table 2: Bee abundance, species richness, and evenness in conventional and organic fields 
collected between 2013 and 2015 at Big Sandy, MT. Values were pooled across three 
years. Significant P-values (P ≤ 0.05) are bolded. 
Table 3: Percent natural habitat within 500 m, 1000 m, and 2000 m from the centers of 
conventional and organic fields in Big Sandy, MT. Significant P-values (P ≤ 0.05) are 
bolded. 
Page 30 of 33 
Table 1: 
Variables Conventional Organic Analysis 
Mean ± SE Mean ± SE DF F-statistic P value 
Floral density 88 ±83 426 ± 128 1,16 16.8 <0.001 
Richness 9.8 ± 2.1 34 ± 3.0 1,16 44.3 <0.001 
Evenness 0.57 ± 0.1 0.65 ± 0.03 1,16 0.69 0.420 
Page 31 of 33 
Table 2: 
Variables Conventional Organic Analysis 
Mean ± SE Mean ± SE DF F-statistic P value 
Abundance 158 ± 31 165 ± 33 1,16 0.56 0.47 
Richness 25 ± 2 27 ± 3 1,16 0.19 0.67 
Evenness 0.85 ± 0.02 0.80 ± 0.02 1,16 3.55 0.08 
Page 32 of 33 
Table 3: 
Distance from Conventional Organic Analysis 
the field centers Mean ± SE Mean ± SE DF (n) χ2 - statistic P value 
500 m 4.9 ± 1.8% 1.3 ± 0.9% 1 (18) 4.5 0.040 
1000 m 9.9 ± 1.5% 4.7 ± 2.2 % 1 (18) 10.6 0.001 
2000 m 13.1 ± 2.2% 8.6 ± 2.4% 1 (18) 3.04 0.080 
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