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Article

Variable Transect Method Outperformed in Sampling Hymenopteran Flower Visitors in Brassica campestris L. var. toria Ecosystem

by
Arup Kumar Sarma
1,*,
Borsha Neog
2,
Mukul Kumar Deka
3,
Alin Carabet
4 and
Ramona Stef
4,*
1
AAU-Zonal Research Station, Shillongani, Assam Agricultural University, Nagaon 782002, Assam, India
2
Department of Statistics, Assam Agricultural University, Jorhat 785013, Assam, India
3
Department of Entomology, Assam Agricultural University, Jorhat 785013, Assam, India
4
Faculty of Agriculture, University of Life Sciences “King Mihai I” from Timisoara, Calea Aradului 119, 300645 Timisoara, Romania
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(6), 1281; https://doi.org/10.3390/agronomy15061281
Submission received: 9 February 2025 / Revised: 10 April 2025 / Accepted: 20 May 2025 / Published: 23 May 2025
(This article belongs to the Special Issue Pests, Pesticides, Pollinators and Sustainable Farming)
Browse Figures
Versions Notes

Abstract

:
Brassica campestris L. var. toria, a major oilseed crop cultivated in India, is primarily an entomophilic species. Hymenopteran flower-visiting species provide important ecological services like pollination or pest control in Brassica crops. In this context, a study was conducted during 2015–2017 in three localities in Assam, a state in northeast India that falls under two global biodiversity hotspots—Indo–Burma and Himalayan—to bring data on the diversity of hymenopteran flower visitors of toria crops by using multiple sampling techniques and to compare the efficiency of these techniques. Altogether, nine sampling treatments were used. To assess the sampling effectiveness of the different treatments, the data from the two cropping periods of toria in each locality were analysed cumulatively and comparatively. Variable transect outperformed the other sampling methods with the highest number of hymenopteran flower visitor species recorded in toria crops at 54, representing 84.4% of the total number of species, and was followed by standard transect (34 species, 53.1%), elevated yellow trap (22 species, 34.4%), and observation plot (21 species, 32.8%). However, the importance of multiple sampling methods in this diversity study was noticed; one method alone could not sample all the species recorded. The cluster of traps and netting with transect walks was proven to be complementary and considered useful for future research studies in the upstream basin of the Burhidihing River of Assam, India.

1. Introduction

Thirty-five percent of the global production of crops, including at least 800 cultivated plants, depends on animal pollination [1,2]. Pollinators play a crucial role in flowering plant reproduction and in the production of most fruits and vegetables; without the assistance of these pollinators, most plants could not reproduce [3,4,5]. The importance of pollinators has also been reported from an economic point of view, so that in 2009, the economic benefit was EUR 153 billion and represented 9.5% of the world’s agricultural economic production [6,7]. In 2016, a report by IPBES [8] estimated that pollinators annually determine an added value of USD 235–577 billion to global food production.
Previous statements show that animal-mediated pollination represents one of the most important biotic interactions in terrestrial ecosystems, being essential both for their functioning and for the conservation of biodiversity [7].
In terrestrial ecosystems, plant pollination can also be accomplished by abiotic factors, such as wind and water [9]. The most widespread types of pollination are anemophilic and entomophilic. Anemophilic pollination predominates in dense plant communities such as grasslands and forests [10], while insect pollination is dominant in areas of high biodiversity [11].
Brassica campestris L. var. toria is an important oilseed crop that requires insect pollinators to ensure its reproductive success [12]. The pollination of Brassica campestris var. toria is mainly entomophilic, being an attractive crop for insects and providing abundant pollen and nectar [13,14], although there are indications of a secondary contribution of anemophilous pollination under specific climatic conditions [15]. Brassica campestris L. is a xenogamous species, almost self-sterile, and produces more seeds when cross-pollination occurs [16,17]. The yield of this crop is strongly influenced by the abundance and diversity of floral visitors [17]. According to Brittain et al. [18], pollinating insects determine an annual production increase of 580 million tons in oilseed plants, and this statement is also endorsed by subsequent studies by Bandenes-Perez et al. and Woodcock et al. [17,19]. The quality and quantity of Brassica campestris L. var. toria production is influenced by the diversity and abundance of floral visitors, which in turn depend on the structure and composition of the local pollinator community [20,21,22,23,24]. In the success of pollination of agricultural crops, in addition to the diversity and abundance of floral visitors, it is important to know the functional differences between species in facilitating pollination [19,25]. Studies conducted to date support that pollination with significant economic impact is carried out by a relatively small number of species [19,26,27,28]. Therefore, the stable and efficient pollination of agricultural crops in different climatic and ecological contexts is ensured by the functional diversity of pollinators [18,29].
In the ecosystem of Brassica campestris var. toria, the main entomophilic species belongs to the orders Hymenoptera and Diptera due to their efficiency in pollen transport [30]. An important role in the pollination of agroecosystems is played by wild pollinators, which provide essential pollination services and represent a natural biological reserve, offering protection and compensation in the case of decline in pollinator communities due to pests and diseases [31].
The species-level identification of pollinators is extremely important, especially of hymenopterans, as they show differences in feeding behaviour and floral preferences [32]. Understanding the specific relationships between plants and pollinators is essential in developing effective conservation strategies and sustainable agricultural management [33].
Studies regarding the pollinators in the Brassica campestris var. toria agroecosystem using different sampling methods have been conducted by Sarma et al., Taba et al., Westphal et al., Potts et al., and Sarma et al. [14,15,34,35,36,37,38,39,40]. The sampling methods used by researchers for pollinating insects of Brassica campestris var. toria included direct observation, manual capture by sweep nets, coloured traps, Malaise traps, etc. The data present in the literature indicate that for a comprehensive understanding of ecological relationships involved in the reproduction process of Brassica campestris var. toria, it is mandatory to combine multiple sampling methods [38].
Methods for sampling pollinator ecological assemblages seek to be efficient, repeatable, and representative; there is a concern that common methods have their limits in terms of revealing species function and so have less value for comparative studies [39].
The sampling methods frequently used in ecosystems and agroecosystems are coloured pan traps, Malaise traps, and direct observations (transects).
Malaise traps are recommended for biodiversity studies due to their ability to capture a wide range of flying insects, rare and hard to detect species, over a long period of time [40,41]. The use of these traps offers the advantage of continuous sampling without researcher interventions, generating a lot of data about biodiversity. However, these traps also have several disadvantages, such as high costs, and the setup and capture of non-pollinator insects require additional effort for sorting and specimen identification, leading to further increased costs [39,40,41].
The method of direct observation (transect) provides data on pollinator behaviour, floral preferences, and interactions between species [42]. Walking transects can have different sizes, from 100 m × 1 m to 250 m × 4 m, and are completed in 20 to 50 min. These are considered variable when the position and direction of the transects are randomly selected during sampling or are fixed/standard when the same point is visited repeatedly during monitoring [43]. However, the term “variable” is interpreted differently by Westphal et al. [34] and Nielsen et al. [44]: both use the term for a second transect performed in a 1 ha area, where the researcher can move freely among flower patches for about 30 min. This has the significant advantage of allowing for a detailed assessment of insects’ behaviour in their natural habitat, providing data on flower visit frequency and the specific preferences of pollinators [39]. The disadvantage of this method is determined by a long observation time and the involvement required from researchers, which can introduce subjectivity in observations and affect the results [40].
The most used sampling method is represented by the use of coloured pan traps filled with soapy water [45,46,47], whether accompanied or not by collecting flowers with a net [48]. When comparing the two methods, even though they were found to capture similar richness and abundance, the assemblages differed, particularly in relation to aspects of pollination function [39]. The frequent use of coloured traps relies on low costs, ease of use, and reproducibility, and can cover large areas simultaneously [49]. One disadvantage of pan traps is that they do not offer behavioural data with respect to insect–plant interactions [50]. The selection of the sampling method represents an important and necessary component in determining relevant species in an area [44]; otherwise, the collected specimens do not represent the groups of insects present in an ecosystem or the rare collection of a group of insects, which is due to the lack of an efficient collecting technique for this group [51]. The use of a variety of pan colours has been advocated by Gollan et al. [52] for sampling overall bee biodiversity, but specific colours may be more effective when targeting certain groups or species [50]. A literature review that compares six sampling methods (Malaise traps, pan traps, bait, sweep nets, timed observations, and aspirators) for bee species populations found little consensus regarding which method would be most reliable for sampling multiple species in tropical forests and agroecosystems [53]. The complementary use of several techniques allows for the minimising of individual limits and ensures a proper picture of a pollinator community [45]. Moreover, a key area for future pollination research is to more deeply understand the roles played by the full complement of pollinators [54,55].
Published research highlights the existence of pressures on pollinator communities, so their effective identification is becoming increasingly important. Pollinator diversity and abundance are affected by habitat degradation, excessive pesticide use, climate change, and land use change [56,57,58]. Studies by Landanverde-Gonzalez et al. [7] show that in traditional, low-intensity milpa agriculture in tropical Mexico, pan traps and transect walk methods of sampling were found to be similarly efficient for pollinator diversity analyses, although each collected different components of the bee community, emphasising the fact that bee species richness and abundance were negatively corelated with the area of chili crops due to agricultural intensification while being positively related to the amount of forest cover. Millard et al. [59] highlight that the selection of sampling methods is essential in biodiversity studies and recommend the use of standardised and complementary methods in ecosystems affected by anthropogenic activities.
Although there are many studies on pollinator diversity and decline, there is a lack of research that comparatively evaluates the efficiency of sampling methods in agroecosystems, especially in India. Therefore, this present study aimed to compare the effectiveness of nine methods used for species monitoring of hymenopteran floral visitors of Brassica campestris L. var. toria crops under the particular conditions of the Assam state area in India in order to select the methods with the greatest potential to be used in Hymenoptera biodiversity-related studies.

2. Materials and Methods

This study was conducted in October 2015-March 2016 and October 2016-March 2017 in the state of Assam in India in an area that is within two global biodiversity hotspots: Indo–Burma and the Himalayas [38].

2.1. Study Area

Dibrugarh District is in the Oriental region near the border of the Palearctic region. This study was conducted in farmers’ fields in three villages, viz., Jajimukh (GPS: N 27°17′12.3″; E 94°50′09.0″, recorded using GPS Map Camera mobile app for Android), Lejai Panimirigaon (GPS: N 27°17′06.9″; E 94°47′08.5″), and Kutuha-Bhagamur (GPS: N 27°16′49.6″; E 94°49′58.0″) in Dibrugarh District of the Upper Brahmaputra Valley Zone (UBVZ) of Assam, India. The localities where the study was carried out are located near the Burhidihing River, which is prone to flooding during the monsoon season.
The study area is characterised by a humid subtropical climate and is influenced by southwest monsoons, with an annual mean precipitation of 2518.3 mm [60]. Climate conditions vary accordingly to the three seasons: summer (March–May—characterised by a mean temperature of 26–38 °C, with reduced precipitations), monsoon (June–September—mean temperature from 25 °C to 32 °C, with abundant precipitation—mean of 1731.6 mm/season), and winter (October–February—mean temperature 6–25 °C, with low level of precipitations (42.2 mm mean/season)) [60].
The Brassica campestris var. toria crop ranks first in both area and production among oilseed crops grown in Assam, and is grown on hundreds of hectares near the Burhidihing River. For this present study, all sampling sites were selected in Brassica campestris var. toria crop fields positioned on both banks of the Burhidihing River. The distance between the experimental fields did not exceed 3 km. No managed honeybee colonies were available in the selected villages. No insecticide was applied to the crops at any stage.

2.2. The Agroecosystem of Brassica campestris var. toria

In 2015, two sampling sites were selected in each locality, one with Brassica campestris var. toria crops sown in mid-October and one with Brassica campestris var. toria sown at the beginning of December. In 2016, all sites were set up in the same areas selected the previous year.

2.2.1. Normal Cropping Period for Brassica campestris var. toria

The crop variety that was sown in mid-October was TS 36, produced and recommended by the Agricultural University of Assam, Jorhat, India [61]. The TS 36 variety has a vegetation period of 90–95 days and is suitable for late sowing from 15 October to 15 November. This variety can be cultivated after rice, normally achieving yields up to 1200 kg/ha, and is tolerant to drought stress [62]. This cropping system of Brassica campestris var. toria is common in hundreds of hectares in the uplands near the Burhidihing River. The peak flowering period was between mid-November and mid-January.

2.2.2. Late Cropping Period for Brassica campestris var. toria

The crop variety that was sown in the first week of December was TS-67 [62]. It needs 90–95 days to reach maturity, medium height, and a small number of primary brunches, and exerts a high production capability up to 1000–1200 kg/ha when sown in an optimal period and up to 700–800 kg/ha when sown up to the first week of December [61]. This variety is well known for its capacity to attract pollinator insects due to the high quantity of nectar and pollen production [38].
The TS-67 variety was sown after the rice harvest in the first week of December. The peak flowering period was from mid-January to mid-March.

2.3. Sampling Methodology

2.3.1. Period of Observation and Field Data Collection

Pollinator data collection in the Brassica campestris var. toria ecosystem was performed eight times at one-week intervals at each site during the crop flowering period.

2.3.2. Methods and Sampling Design

The methodology and sampling design were adapted from those described by Belavadi and Ganeshaiah [63], Nielsen et al. [44], and Westphal et al. [34] as follows:

Ground Bowl Traps (GBTs)

At each study site, 30 coloured bee bowls in clusters of three colours (yellow, white, and blue) at ground level at 15 m intervals were used by following the methodology of Belavadi and Ganeshaiah [63].

Elevated Bowl Traps (EBTs)

In each of the six experimental sites, 30 bowl traps were set up in 10 clusters separated by 15 m. Each cluster contained three bowl traps (white, yellow, and blue). These colours accounted for the different colour preferences among bee species, increasing the efficiency of the trap clusters in attracting bees [45,47]. Each trap was filled with 200 mL of water and a few drops of liquid detergent. The pan traps were mounted on a pole at the vegetation height and left active for 48 h during each of the eight rounds of sampling conducted in a cropping period.
For both EBT and GBT sampling, the same bowl type with a 16 cm inner diameter x 7 cm inner depth was used.

Observation Plots (OP)

In each study site, ten rectangular (1 m × 2 m) observation plots were randomly established and marked. Direct observations at each plot lasted 6 min. Each observed hymenopteran species was collected with a sweeping net for further identification. Plot observations were randomised at each visit to ensure data accuracy.

Standardised Transect Walks (ST)

A permanently marked 250 m-long and 4 m-wide corridor (transect) was divided into 10 plots, each 25 m long, and used for the standardised transect walk. The sub-plots were marked permanently with a bamboo stick before crop flowering. Each sub-plot was surveyed for 5 min, during which all hymenopteran species visiting the toria flowers were collected by netting and preserved for further identification.
The methods described in Section 2.3.1 and Section 2.3.2 were performed at each experimental site on a 1 ha plot delimited inside the greater crop surface.

Variable Transect Walks (VT)

For this method, an adjacent 1 ha plot was selected, located in the same crop for each experimental site. These plots were surveyed by slowly walking around on variable line transects for 30 min, while all specimens of flower visitors observed were collected by netting.
Sampling in the case of OP, ST, and VT methods was performed randomly, at different intervals of the day (from 10 a.m. to 4 p.m.) with favourable weather conditions (temperature above 15 °C, no rain, no wind, and cloud cover of less than 50%).
Altogether, the nine sampling methods, considered here as treatments (T1 to T9), were T1—YTG (yellow trap in the ground); T2—BTG (blue trap in the ground); T3—WTG (white trap in the ground); T4—YTE (yellow trap elevated to canopy); T5—BTE (blue trap elevated to canopy); T6—WTE (white trap elevated to canopy); T-7—OP (observation plot); T8—ST (standardised transect walk) and T9—VT (variable transect walk).
The samples consisted of hymenopteran specimens collected at every site, and treatments at various sampling moments were stored in ethanol, transferred to a laboratory, and further processed for taxonomic segregation.

2.4. Statistical Analysis of Data

The efficiency of each sampling method was evaluated based on the number of species of flower visitors sampled. To assess the sampling effectiveness of the different methods, the data from the two cropping periods were analysed cumulatively and comparatively using SPSS software (version 20). To compare the mean differences between treatments, Tukey’s HSD test was used. ANOVA was performed to assess differences in the efficiency of the seven non-transect sampling methods, while a t-test was performed for the two transect methods. For the comparison of non-transect methods (YTG, BTG, WTG, YTE, BTE, WTE, and OP), the Kruskal–Wallis test was applied as a non-parametric method used when there are more than two independent groups.

3. Results

Efficiency of All Sampling Methods

Overall, the species of hymenopteran floral visitors in the Brassica campestris var. toria agroecosystem collected during the study period were classified into nine families: Apidae (fifteen species), Halictidae (nine species), Vespidae (eighteen species), Megachilidae (eight species), Crabronidae (five species), Andrenidae (two species), Sphecidae (four species), Scoliidae (two species) and Colletidae (one species), totalling 64 species (Table 1).
The families Vespidae (eighteen species), Apidae (fifteen species), and Halictidae (nine species) recorded the highest species richness. Colletidae, Scoliidae, and Sphecidae families were present in the toria crop in a small number of species (Table 1).
The results regarding the use of sampling methods for hymenopteran flower visitors in toria crops varied in terms of the number of species caught (Table 1). Treatment 9 (VT) was found to be the most efficient method of sampling, with the highest number of species recorded, 54,—84.4% of the total number of species caught. It can be noted that VT was the only method by which all the pollinator species belonging to Andrenidae, Scoliidae, and Colletidae were collected. In terms of the number of species recorded per sampling method, treatment 9 (VT) was followed by treatment 8 (ST) (with 34 species), treatment 4 (YTE) (22 species), and treatment 7 (OP) (21 species). Notably, these four methods also had higher trends of catching Vespidae and Apidae—the dominant families of Hymenoptera in the toria crop ecosystem. For other families, viz., Megachilidae, Halictidae, and Andrenidae, the extent of catches recorded by two non-transect methods, treatment 4 (YTE) and treatment 7 (OP), was also relatively high.
The proportionate comparisons among different hymenopteran families across the sampling methods can be perceived from Figure 1 (radar chart), while the data dispersion and variation among sampling methods are highlighted in Figure 2 (box plot).
The radar chart provides a comparative visualisation of the species richness of the nine Hymenoptera families across data from different sampling treatments. This graphical representation highlights clear differences in hymenopteran family distribution and suggests variation in detection efficiency among sampling methods.
Among all families, Apidae exhibits the highest representation across most treatments, particularly in VT and ST, and the elevated values recorded in these treatments indicate that these methods are particularly effective in capturing the dominant pollinator group.
Vespidae also shows a pronounced peak in the VT transect, suggesting that the method might be more sensitive to detecting fast-moving or aggressive taxa. Similarly, Halictidae (a family often composed of smaller, ground-nesting bees) was detected in a moderate number of species in VT and ST but much less so in other sampling treatments, further supporting the higher efficacy of these two methods for detecting a wider array of taxa.
In contrast, families such as Andrenidae, Megachilidae, Colletidae, and Crabronidae appear in lower species richness across all treatments, potentially indicating their low natural abundance in the study area. This underrepresentation may also reflect habitat preferences or nesting behaviours that are less compatible with the sampling techniques used.
Analysing the boxplot from Figure 2, showing central tendencies of dispersion but also extreme values, it can be observed that the hymenopteran species caught in toria crops exhibits a numerical variation for each method. The use of transect methods showed the highest variation in the number of species collected, suggesting a higher capacity for collecting a wide range of entomofauna diversity. The use of treatment 9 (VT) has recorded very significant differences; out of a total of sixteen species, the species richness reached a mean of six species, suggesting a high capturing potential but with highly variable values from one plot to another.
Assessing treatment 5 (BTE) and treatment 2 (BTG) with respect to floral visitors captured in the toria agroecosystem, the data highlighted the stability of the results regarding the number of species caught but showed lower results in terms of species richness. Treatment 4 (YTE) and treatment 7 (OP) offered balanced results regarding hymenopteran species diversity.
A comparative analysis (Kruskal–Wallis test) of the nine treatments highlighted that there are significant differences regarding sampling methods used to capture hymenopteran species (Table 2). The number of collected species in treatment 9 (VT) was very significantly higher than the number of species collected by some passive (non-transect) methods like treatment 2 (BTG) (p-adj. = 0.031), treatment 5 (blue elevated traps—BTE) (p-adj. = 0.025), and treatment 6 (white elevated traps—WTE) (p-adj. = 0.032). These significant differences between treatment 9 (VT) (64.83) and treatment 2 (BTG) (28.78) and treatment 6 (WTE) (29.56) are also highlighted in Figure 3.
In a comparison of the VT method with the active sampling method (ST, standardised transect; OP, observation plots), no significant differences were recorded, suggesting that these methods provide similar results over diversity.
a. Efficiency of non-transect sampling methods
The efficiency of non-transect methods (treatments 1 to 7) showed highly significant differences in each cropping period (Table 3 (a)), as well as at their pooled mean level (Table 3 (b)).
Table 3 (a) shows that the number of collected species, using the non-transect sampling method, is more sensitive in the late-drilled toria crop, with the only exception being recorded when the YTE method was used (8.19—normally drilled toria crop; 8.16—late-drilled toria crop).
The mean number of the collected species in normally drilled toria plots varied between 2.36 in treatment 6 (WTE) and 8.35 in treatment 7 (OP). The results were almost similar in the case of plots with toria drilled in a later period, and the mean number of recorded species varied between 2.64 (treatment 5, BTE) and 8.85 (treatment 7, OP). Non-transect sampling methods YTG (4.63 species), BTG (4.23 species), and WTG (4.14 species) showed a medium efficiency in collecting the crop visitor species (normal or late crops) in Brassica campestris var. toria.
The mean sampling record per site was higher in Kutuha village as compared to the other two locations (Table 3 (b)). Treatment 7 (OP) outperformed the other non-transect methods at all three locations; however, the results in the case of treatment 4 (YTE) were statistically similar to those registered in treatment 7 (OP) when comparing the mean number of hymenopteran flower visitor species calculated for all locations.
b. Efficiency of transect methods of sampling
In each of the cropping periods and also in their pooled mean level, the number of species caught in both treatments with transect methods (treatment 8—ST, and treatment 9—VT) had significant differences between the three locations of the study (Table 4 (a)). The mean sampling record of hymenopteran flower visitor species numbers per site was significantly higher in Kutuha village (35.8) when compared to that in Panimirigaon (33.33) and very significantly higher compared to that recorded in Jajimukh (32.3).
Based on a t-test, it can be seen that the performance of VT was superior to ST in both the cropping periods individually as well as at their pooled mean level; highly significant differences between the number of hymenopteran flower visitor species were observed between them (Table 4 (b)).
In the normal cropping period, the efficiency of transect methods in terms of the hymenopteran flower visitor species caught was found to be higher than that of pan traps (Figure 4). The comparison of the nine sampling methods through confidence intervals (CI 95%) reveals that methods VT (T9) and ST (T8) recorded the highest values, showing a high variability as well.
Non-transect methods, BTG (T2), WTG (T3), BTE (T5), and WTE (T6), exhibited the lowest values in species collecting from toria crops, presenting thinner trust intervals and endorsing more accurate evaluations.
Using the nine sampling methods in the late-drilled period of toria cropping proved that their efficiency does not change, the ranking being similar to the one obtained in a normally drilled period of the crop (Figure 5). Transect methods VT (T9) and ST (T8) collected the highest number of hymenopteran flower visitor species, followed by OP (T7) and YTE (T4). Using the methods of coloured traps placed on the ground (T1, T2, T3) and elevated ones (T5, T6), a low number of hymenopteran flower visitor species were captured.

4. Discussion

In the context in which Assam is part of two global biodiversity hotspots (Indo–Burma and the Himalayas), Brassica campestris var. toria being the main agricultural crop in the region, its productivity significantly depends on the efficiency of pollinator species. The main aim of this study was to complement previous knowledge [38] with reference data regarding the efficiency of various sampling methods for hymenopteran floral visitor species.

4.1. Diversity of Floral Visitors Based on Sampling Methods

In Brassica campestris var. toria (drilled in the optimal and later period), in all experimental sites dedicated to the study in three localities (Jajimukh, Panimirigaon, and Kutuha) using nine sampling methods, a very large number of hymenopteran floral visitor species were caught. The 64 species were assigned to nine Hymenoptera families (Apidae, Andrenidae, Megachilidae, Vespidae, Scoliidae, Halictidae, Crabronidae, Colletidae, and Sphecidae) (Table 1).
Active methods like VT (variable transect), ST (standardised transect walk), and OP (direct observations) proved to be the most effective, and through their use, important pollinators belonging to the Apidae and Halictidae families were collected (Table 1). The results align with those reported by Popic et al. and Roulston et al. [39,48]. As a group, the species of Apidae and Halictidae were detected in all the sampling methods, which indicates that species of these families visit multiple strata of crop plant vegetation.
Even though the number of species belonging to Vespidae was relatively larger (Table 1), most of them are predatory in habit and some species can alter the pollination dynamics; thus, vespids are less efficient as pollinators in toria crops as compared to many species of other families such as Apidae and Megachilidae since bees are considered important pollinators globally [64].
By using the OP method in the Brassica campestris var. toria ecosystem, we succeeded in collecting 32.8% of species belonging to seven families (Apidae, Andrenidae, Megachilidae, Vespidae, Halictidae, Crabronidae, and Sphecidae) out of the nine recorded.
By using the YTE method, we recorded the presence of 34.4% of toria crop hymenopteran floral visitor species belonging to six families (Apidae, Andrenidae, Megachilidae, Vespidae, Halictidae, and Crabronidae), while the use of passive methods placed at a ground level, BTE and WTE, recorded a very low percentage (9.4% and 10.9%, respectively) of the total toria hymenopteran floral visitor species (Table 1). YPT efficacy is also confirmed by studies conducted by Sounders and Luck [49], who found that this method caught the most pollinator insects across a great variety of habitats, although not all of the analysed ones, and concluded that pan trap colour attractiveness depends largely on habitat.
Therefore, the ability to sample more pollination-efficient species, as observed in YTE and OP, may increase the efficiency of the entire sampling module if these two are included along with VT and ST. These significant differences are supported by Figure 2 and Figure 5, as well as Table 3 (a). Although transect methods (VT, ST) proved to be superior in collecting hymenopteran floral visitor species in a Brassica campestris var. toria ecosystem, some studies indicate that standardised methods may exclude essential pollinating species [65,66]. Likewise, traps installed at ground level, viz., YTG, BTG, and WTG, could sample some ground-dwelling species, even though their overall sampling efficiency is less (10.9–18.8%). The coloured traps placed at ground level (YTG, BTG, WTG) proved to be attractive for species belonging to the Halictidae family, but these were not efficient in capturing species belonging to the Colletidae family. Similar results were reported by Droege et al. [67], who also reported a taxonomic bias related to colour.
Therefore, ground traps may be complementary to other methods. In some small farms of Asian farmers, where non-crop vegetation and hedges are frequently present between two adjacent crop fields of small acreage, there are heterogeneous and homogeneous areas within the same crop landscape. In such a situation, the combination of complementary methods would always perform better.

4.2. Comparative Efficiency of Transect and Non-Transect Sampling Methods

The comparative analyses of transect sampling methods (VT and ST) and non-transect (OP, YTG, BTG, WTG, YTE, BTE, and WTE) revealed significant differences in their capacity to capture the diversity of hymenopteran floral visitor species in toria agroecosystem conditions in Assam.
Transect methods proved to be superior in capturing the number of species compared to non-transect methods across all three sites in both toria crops (normal cropping period and late cropping period) (Figure 4 and Figure 5). Variable transect (VT), due to its flexibility, exhibits the most efficient active method, followed by direct observation (OP) and standard transect (ST). We found that VT had higher sampling records than ST. This may be due to the larger transecting area covered under VT treatment. We consider that species records in both ST and VT may be increased proportionately with pollinator diversity of a locality by intensifying the netting with proper temporal randomisation, particularly for annual crops with a shorter blooming period. Such flexibility in sampling intensity based on scientists’ particular goals and specific knowledge about local diversity of pollinators has also been suggested in the case of traps by Shapiro et al. [65].
Analysing comparatively the efficiency of transect methods in toria crops drilled in regular and late periods, it was observed that their superiority was maintained, indicating a consistency regarding collecting the hymenopteran flower visitors. Temporal variations of species richness between two cropping periods under multiple sampling methods are a researchable issue.
Among the non-transect methods, the highest mean number of hymenopteran flower visitor species record was observed in OP followed by YTE (Table 3 (a)). The flower visitors responded poorly to other non-transect methods. Here lies the importance of incorporating the transect methods in a sampling module. Although non-transect methods YTG, BTG, WTG, BTE, and WTE constantly yielded lower results in terms of the number of hymenopteran flower visitor species, their complementary role cannot be ignored as they can provide more complete coverage of functional diversity.
Westphal et al. [34] recommend pan traps for pollinator monitoring schemes to provide reliable results when operated by many surveyors in different habitats, regions, and years, and also consider the transect walks and observation plots as the main methods in more detailed studies on plant–pollinator interactions. Despite its wide use in sampling pollinator diversity, the influence of colour on pan trap efficiency is not so clear; accordingly, the blue, yellow, and white pan traps are considered complementary in sampling the Hymenoptera community [66].
Transect methods have been shown to be remarkably superior to the non-transect ones in terms of sampling records. However, being contributory, both are required for such sampling studies, as discussed in the above sections. Multiple sampling methods have also been suggested in some recent studies [68,69].
The combination of transect methods with some selected passive methods (like OP and YTE) seems to be an optimal strategy for a broader characterisation of pollinator communities.
The results of this study highlight that variable transect (VT) recorded the highest values in the detection of floral visitor species, maintaining its efficiency even in cases where non-transect methods (YTG, BTG, WTG, YTE, BTE, and WTE) tend to fail in fully capturing local diversity.
The superiority of transect methods to pan traps is also supported by studies conducted by Berglund and Milberg [70] and by other subsequent research [71].
They claim that pan traps underestimate the number of species and individuals belonging to the Apidea family and overestimate Lepturinae and Cetoniidae. Similar differences were reported in studies performed by Cane et al. [46] and Roulston et al. [48] (2007), highlighting the limits of pan traps in fully characterising the bee fauna. Differences between passive and active methods, in terms of species abundance and the composition of collected bees, were also reported by Gibbs et al. [72] and McCravy and Ruholl [73].

4.3. Influence of Trap Colour and Position on Sampling Efficiency

Colour is one of the most important attractants for many flower-visiting insects, and their preferences for a specific colour is an important source of bias that needs to be considered in pan trap surveys [74].
Our data clearly indicate that the majority of the species sampled by pan traps had an affinity towards yellow (Table 2). Saunders and Luck [49] have also reported higher trap records in yellow pan traps. In our study, YTG had failed to trap some of the top surface visitors, which led to a lower sampling rate than YTE. On the other hand, possibly because of the affinity of some ground-dwelling and sub-surface species towards blue and white, the trap record in BTG and WTG was significantly superior to same-coloured elevated traps. This model of chromatic selection based on vertical layers was also documented by Nuttman et al. [75], underlining the fact that colour preferences vary among taxons, affecting feeding behaviour and activity level in a vegetal canopy. However, no colour was consistently found to be preferred if both placement positions (i.e., ground and elevated) were considered. Such facts have also been reported in some previous works, which emphasise that one colour cannot be considered more attractive than others when targeting a wide range of taxa in different ecological contexts [40,66,76]. The species diversity might be improved through (i) the simultaneous use of pan traps of different colours, which has been suggested for surveys targeting a wide range of taxa [47,74,77], or (ii) by increasing the number of traps based on particular goals and specific knowledge about local bee diversity, as reported by Shapiro et al. [65].

4.4. Implications for Future Research and Conservation

As this present study took place near the Palearctic border, a higher number of Palearctic species may be recorded by similar diversity studies in localities in the upstream basin of the Burhidihing River. Identifying those wild pollinators may open new research avenues in relation to their conservation and colonisation for harnessing their pollination services in crop ecosystems of the Oriental region. The conservation of wild pollinators to support the toria production of small and marginal farmers in India and other Asian countries is an important issue. This is highlighted by Zou et al. [78] in smallholder oilseed farming systems of China. There is also the future scope of a study focusing on temporal dynamics, as demonstrated by Ludewig et al. [79] and Casiá-Achjé [80]. Millard et al. [59] and Tsang et al. [81] have demonstrated the impact of land use changes on biodiversity, particularly in human-modified areas like agricultural landscapes, and emphasised the effects of land use change on insect diversity at multiple scales.
A multisampling study on bee assemblage conducted in the traditional slash-and-burn agriculture (milpa) of the Yucatan Peninsula of Mexico (part of Mesoamerica, which is considered an important biodiversity hotspot), revealed that bee diversity was highest in forested areas and lower in cropped land; although, surprisingly, chilli pollination was enhanced by surrounding fallow, gardens, and pasture but reduced by surrounding forest cover [7]. Such studies on pollinator assemblage with due correlation with the surrounding fallow, non-crop plant community are another topic of interest in toria crop ecosystems in Assam state in India.

5. Conclusions

Overall, the data demonstrate that VT, followed by ST, consistently yielded higher species richness across diverse hymenopteran families, reinforcing their utility as core sampling methods for monitoring flower visitor diversity in toria crops. Their ability to capture both dominant and moderately represented taxa suggests that these methods may offer a more comprehensive assessment of the pollinator community structure, but this study reveals that no method alone is adequate to sample the whole hymenopteran flower visitor diversity, including pollinator species in toria crop ecosystems. The most deployed method of sampling, i.e., coloured pan traps filled with soapy water, failed to justify its efficiency as the sole method of sampling. Another conclusion was that active methods (VT, ST, and OP) exerted a higher efficacy in capturing a higher number of species belonging to Apidae and Halictidae. The YTE method proved to be the most effective passive method for capturing flower visitors in toria crops. On the other hand, the lowest efficiency in catching hymenopterans was shown by blue-coloured traps.
A cluster of coloured pan traps and netting with transect walk were found to be complementary to each other; hence, both transect and non-transect methods as a module should be used in order to record a wider species composition in toria crop ecosystems. Such a complementary combination of sampling techniques will be particularly useful in areas with rich flower visitor diversity, with implications for long-term monitoring and conservation planning.
Such modules will also be fruitful for benchmark surveys to see the depletion of pollinator species richness, if any, due to climate change over time. In continuation of this present study, there is the scope of identifying wild Palearctic hymenopteran pollinators in the upstream basin of the Burhidihing River of Assam, India, which may open new research avenues on their conservation and colonisation for harnessing their pollination services in crop ecosystems in the Oriental region.

Author Contributions

Conceptualisation, A.K.S., B.N. and M.K.D.; methodology, A.K.S., B.N. and M.K.D.; formal analysis, B.N. and A.K.S.; investigation, A.K.S.; resources, A.K.S. and M.K.D.; writing—original draft preparation, A.K.S. and R.S.; writing—review and editing, A.K.S., A.C. and R.S.; funding acquisition, A.C. and R.S. This work is part of the doctoral research program of the first author. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

This article is based on the PhD research work of the first author; no raw data will be shared.

Acknowledgments

The authors are highly indebted to Neil Anderson, Former Researcher-cum-Project leader, Department of Biosciences, University of Oslo, Norway, for his encouragement to take up the field research and for sharing the methodology of the sampling techniques. The farmers who allowed us to conduct research work in their crop fields and provided accommodation during the field studies are duly acknowledged. The authors are also thankful to the scientists of (i) the National Bureau of Agricultural Insect Resource, Bengaluru, India, and (ii) the University of Agricultural Science, Bengaluru, India, for the taxonomic identification of the insects.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Klein, A.M.; Vaissiere, B.E.; Cane, J.H.; Steffan-Dewenter, I.; Cunningham, S.A.; Kremen, C.; Tscharntke, T. Importance of pollinators in changing landscapes for world crops. Proc. R. Soc. B 2007, 274, 303–313. [Google Scholar] [CrossRef] [PubMed]
  2. Nicholls, C.; Altieri, M. Plant biodiversity enhances bees and other insect pollinators in agro-ecosystems: A review. Agron. Sustain. Dev 2013, 33, 257–274. [Google Scholar] [CrossRef]
  3. Mcgregor, S.E. Insect Pollination of Cultivated Crop Plants; USDA/ARS Agriculture Handbook 496; Agricultural Research Service, US Department of Agriculture: Washington, DC, USA, 1976; p. 139.
  4. Tepedino, V.J. The importance of bees and other insect pollinators in maintaining floral species composition. Great Basin Nat. Mem. 1979, 3, 17. [Google Scholar]
  5. Free, J.B. Insect Pollination of Crops; Academic Press: London, UK, 1993; p. 684. [Google Scholar]
  6. Gallai, N.; Salles, J.M.; Settele, J.; Vaissiere, B.E. Economic valuation of the vulnerability of world agriculture confronted with pollinator decline. Ecol. Econ. 2009, 68, 810–821. [Google Scholar] [CrossRef]
  7. Landaverde-González, P.; Quezada-Euán, J.J.G.; Theodorou, P.; Murray, T.E.; Husemann, M.; Ayala, R.; Moo-Valle, H.; Vandame, R.; Paxton, R.J. Sweat bees on hot chilies: Provision of pollination services by native bees in traditional slash-and-burn agriculture in the Yucatán Peninsula of tropical Mexico. J. Appl. Ecol. 2017, 54, 1814–1824. [Google Scholar] [CrossRef]
  8. Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. The Assessment Report on Pollinators, Pollination and Food Production; IPBES Secretariat: Bonn, Germany, 2016; Available online: https://ipbes.net (accessed on 3 March 2025).
  9. Faegri, K.; Van Der Pijl, L. Principales of Pollination Ecology, 3rd ed.; Elsevier: Amsterdam, The Netherlands, 2013; p. 256. [Google Scholar]
  10. Klein, A.M.; Steffan-Dewenter, I.; Tscharntke, T. Pollination of Coffea canephora in relation to local and regional agroforestry management. Oecologia 2003, 134, 607–615. [Google Scholar] [CrossRef]
  11. Culley, T.M.; Weller, S.G.; Sakai, A.K. The evolution of wind pollination in angiosperms. Trends Ecol. Evol. 2002, 17, 361–369. [Google Scholar] [CrossRef]
  12. Abrol, D.P. Pollination Biology: Biodiversity Conservation and Agricultural Production; Springer: Dordrecht, The Netherlands, 2012; p. 792. [Google Scholar]
  13. Stanley, J.; Sah, K.; Subbanna, A.R.N.S. How efficient is the Asian honey bee, Apis cerana in pollinating mustard, Brassica campestris var. toria? Pollination behavior, pollinator efficiency, pollinator requirements and impact of pollination. J. Agric. Res. 2017, 56, 439–451. [Google Scholar] [CrossRef]
  14. Sarma, A.K.; Chauhan, J.S. Pollinator diversity in Brassica crops and significance of pollinators in improving productivity: A review. J. Agric. Res. 2015, 1, 35–40. [Google Scholar]
  15. Taba, N.; Sharma, P.; Devadas, V.S.; Hazarika, G.N.; Monlai, S. Performance of Toria (Brassica campestris L.) Varieties under Namsai Conditions. Int. J. Curr. Microbiol. Appl. Sci. 2020, 9, 2101–2103. [Google Scholar]
  16. Williams, I.H. The pollination requirements of swede rape (Brassica napus L.) and of turnip rape (Brassica campestris L.). J. Agric. Sci. 1978, 91, 343–348. [Google Scholar] [CrossRef]
  17. Badenes-Pérez, F.R. Benefits of Insect Pollination in Brassicaceae: A Meta-Analysis of Self-Compatible and Self-Incompatible Crop Species. Agriculture 2022, 12, 446. [Google Scholar] [CrossRef]
  18. Brittain, C.; Kremen, C.; Klein, A.M. Biodiversity buffers pollination from changes in environmental conditions. Glob. Chang. Biol. 2013, 19, 540–547. [Google Scholar] [CrossRef]
  19. Woodcock, B.A.; Garratt, M.P.D.; Powney, G.D.; Shaw, R.F.; Osborne, J.L.; Soroka, J.; Lindström, S.A.M.; Stanley, D.; Ouvrard, P.; Edwards, M.E.; et al. Meta-Analysis Reveals That Pollinator Functional Diversity and Abundance Enhance Crop Pollination and Yield. Nat. Commun. 2019, 10, 1481. [Google Scholar] [CrossRef] [PubMed]
  20. Rader, R.; Howlett, B.G.; Cunningham, S.A.; Westcott, D.A.; Newstrom-Lloyd, L.E.; Walker, M.K.; Teulon, D.A.J.; Edwards, W. Alternative Pollinator Taxa Are Equally Efficient but Not as Effective as the Honeybee in a Mass Flowering Crop. J. Appl. Ecol. 2009, 46, 1080–1087. [Google Scholar] [CrossRef]
  21. Junqueira, C.N.; Pereira, R.A.S.; da Silva, R.C.; Alves Cardoso Kobal, R.O.; Araújo, T.N.; Prato, A.; Pedrosa, J.; Martínez-Martínez, C.A.; Castrillon, K.P.; Felício, D.T.; et al. Do Apis and Non-Apis Bees Provide a Similar Contribution to Crop Production with Different Levels of Pollination Dependency? A Review Using Meta-Analysis. Ecol. Entomol. 2021, 47, 76–83. [Google Scholar] [CrossRef]
  22. Garibaldi, L.A.; Steffan-Dewenter, I.; Winfree, R.; Aizen, M.A.; Bommarco, R.; Cunningham, S.A.; Kremen, C.; Carvalheiro, L.G.; Harder, L.D.; Afik, O.; et al. Wild Pollinators Enhance Fruit Set of Crops Regardless of Honey Bee Abundance. Science 2013, 339, 1608–1611. [Google Scholar] [CrossRef]
  23. Rader, R.; Bartomeus, I.; Garibaldi, L.A.; Garratt, M.P.D.; Howlett, B.G.; Winfree, R.; Cunningham, S.A.; Mayfield, M.M.; Arthur, A.D.; Andersson, G.K.S.; et al. Non-Bee Insects Are Important Contributors to Global Crop Pollination. Proc. Natl. Acad. Sci. USA 2016, 113, 146–151. [Google Scholar] [CrossRef]
  24. Földesi, R.; Howlett, B.G.; Grass, I.; Batáry, P. Larger Pollinators Deposit More Pollen on Stigmas across Multiple Plant Species—A Meta-Analysis. J. Appl. Ecol. 2021, 58, 699–707. [Google Scholar] [CrossRef]
  25. Rader, R.; Howlett, B.G.; Cunningham, S.A.; Westcott, D.A.; Edwards, W. Spatial and temporal variation in pollinator effectiveness: Do unmanaged insects provide consistent pollination services to mass flowering crops? J. Appl. Ecol. 2012, 49, 126–134. [Google Scholar] [CrossRef]
  26. Kleijn, D.; Winfree, R.; Bartomeus, I.; Carvalheiro, L.G.; Henry, M.; Isaacs, R.; Klein, A.-M.; Kremen, C.; M’Gonigle, L.K.; Rader, R.; et al. Delivery of crop pollination services is an insufficient argument for wild pollinator conservation. Nat. Commun. 2015, 6, 7414. [Google Scholar] [CrossRef]
  27. Winfree, R.; Fox, W.; Williams, J.; Reilly, N.M.; Cariveau, J.R.D.P. Abundance of common species, not species richness, drives delivery of a realworld ecosystem service. Ecol. Lett. 2015, 18, 626–635. [Google Scholar] [CrossRef] [PubMed]
  28. Winfree, R.; Reilly, J.R.; Bartomeus, I.; Cariveau, D.P.; Williams, N.M.; Gibbs, J. Species turnover promotes the importance of bee diversity for crop pollination at regional scales. Science 2018, 359, 791–793. [Google Scholar] [CrossRef] [PubMed]
  29. Oliver, T.H.; Heard, M.S.; Isaac, N.J.B.; Roy, D.B.; Procter, D.; Eigenbrod, F.; Freckleton, R.; Hector, A.; Orme, C.D.L.; Petchey, O.L.; et al. Biodiversity and Resilience of Ecosystem Functions. Trends Ecol. Evol. 2015, 30, 673–684. [Google Scholar] [CrossRef] [PubMed]
  30. Jauker, F.; Bondarenko, B.; Becker, H.C.; Steffan-Dewenter, I. Pollination efficiency of wild bees and hoverflies provided to oilseed rape. Agric. For. Entomol. 2012, 14, 81–87. [Google Scholar] [CrossRef]
  31. Vaissiere, B.E.; Breno, M.F.; Barbara, G.H. Protocol to Detect and Assess Pollination Deficits in Crops: A Handbook for Its Use; FAO, UN: Rome, Italy, 2011; pp. 1–70. [Google Scholar]
  32. Wood, T.J.; Holland, J.M.; Goulson, D. Providing foraging resources for solitary bees on farmland: Current schemes for pollinators benefit a limited suite of species. J. Appl. Ecol. 2016, 54, 323–333. [Google Scholar] [CrossRef]
  33. Thompson, A.; Frenzel, M.; Schweiger, O.; Musche, M.; Groth, T.; Roberts, S.P.M.; Kuhlmann, M.; Knight, T.M. Pollinator sampling methods influence community patterns assessments by capturing species with different traits and at different abundances. Ecol. Indic. 2021, 132, 108284. [Google Scholar] [CrossRef]
  34. Westphal, C.; Bommarco, R.; Carre, G.; Lamborn, E.; Morison, N.; Petanidou, T.; Potts, S.G.; Roberts, S.P.M.; Szentgyo Rgyi, H.; Tscheulin, T.; et al. Measuring bee biodiversity in different European habitats and bio-geographical regions. Ecol. Monogr. 2008, 78, 653–671. [Google Scholar] [CrossRef]
  35. Potts, S.G.; Petanidou, T.; Roberts, S.; O’Toole, C.; Hulbert, A.; Willmer, P. Assessing pollinator biodiversity: Standardized methods for monitoring. J. Appl. Ecol. 2008, 45, 9–14. [Google Scholar]
  36. Potts, S.G.; Vulliamy, B.; Roberts, S.; O’toole, C.; Dafni, A.; Ne’eman, G.; Willmer, P. Role of nesting resources in organising diverse bee communities in a mediterranean landscape. Ecol. Entomol. 2005, 30, 78–85. [Google Scholar] [CrossRef]
  37. Hutchinson, L.A.; Oliver, T.H.; Breeze, T.D.; O’Connor, R.S.; Potts, S.G.; Roberts, S.P.M.; Garratt, M.P.D. Inventorying and monitoring crop pollinating bees: Evaluating the effectiveness of common sampling methods. Insects Conserv. Divers. 2022, 15, 299–311. [Google Scholar] [CrossRef]
  38. Sarma, A.K.; Deka, M.K.; Neog, B. Species richness of Hymenopteran flower visitors in Brassica campestris var. toria in Assam, India: A comparison of five sampling methods. AtaXE 2024, 70, 314–328. [Google Scholar] [CrossRef]
  39. Popic, T.J.; Davila, Y.C.; Wardle, G.M. Evaluation of common method for sampling invertebrate pollinator assemblages: Net samplings outperform Pan traps. PLoS ONE 2013, 8, e66665. [Google Scholar] [CrossRef] [PubMed]
  40. Campbell, J.W.; Hanula, J.L. Efficiency of Malaise traps and coloured pan traps for collecting flower visiting insects from three forested ecosystems. J. Insect Conserv. 2007, 11, 399–408. [Google Scholar] [CrossRef]
  41. Geroff, R.K.; Gibbs, J.; McCravy, K.W. Assessing bee (Hymenoptera: Apoidea) diversity of an Illinois restored tallgrass prairie: Methodology and conservation considerations. J. Insect Conserv. 2014, 18, 951–964. [Google Scholar] [CrossRef]
  42. Biesmeijer, J.C.; Roberts, S.P.M.; Reemer, M.; Ohlemüller, R.; Edwards, M.; Peeters, T.; Kunin, W.E. Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 2006, 313, 351–354. [Google Scholar] [CrossRef]
  43. Giovanetti, M.; Albertazzi, S.; Flaminio, S.; Ranalli, R.; Bortolotti, L.; Quaranta, M. Pollination in Agroecosystems: A Review of the Conceptual Framework with a View to Sound Monitoring. Land 2021, 10, 540. [Google Scholar] [CrossRef]
  44. Nielsen, A.; Steffan-Dewenter, I.; Westphal, C.; Messinger, O.; Potts, S.G.; Roberts, S.P.M.; Settele, J.; Szentgyörgyi, H.; Vaissière, B.E.; Vaitis, M.; et al. Assessing bee species richness in two Mediterranean communities: Importance of habitat type and sampling techniques. Ecol. Res. 2011, 26, 969–983. [Google Scholar] [CrossRef]
  45. Leong, J.M.; Thorp, R.W. Colour-coded sampling: Pan trap colour preferences oligolectic and non-oligolectic bees associated with a vernal pool plant. Ecol. Entomol. 1999, 24, 329–335. [Google Scholar] [CrossRef]
  46. Cane, J.H.; Minckley, R.L.; Kervin, R.J. Sampling bees (Hymenoptera: Apiformes) for pollinator community studies: Pitfalls of pan trapping. J. Kans. Entomol. Soc. 2000, 73, 225–231. Available online: http://www.jstor.org/stable/25085973 (accessed on 5 March 2025).
  47. Toler, T.R.; Evans, E.W.; Tepedino, V.J. Pan-trapping for Bee (Hymenoptera: Apiformes) in Utah’s West Desert: The importance of colour diversity. Pan-Pac Entomol. 2005, 81, 103–113. [Google Scholar]
  48. Roulston, T.H.; Smith, S.A.; Brewster, A.L. A comparison of Pan Trap and Intensive Net Sampling Techniques for documenting a bee (Hymenoptera: Apiformes) Fauna. J. Kans. Entomol. Soc. 2007, 80, 179–181. [Google Scholar] [CrossRef]
  49. Saunders, M.E.; Luck, G.W. Pan trap catches of pollinator insects vary with habitat. Aus. J. Entomol. 2013, 52, 106–113. [Google Scholar] [CrossRef]
  50. Lebuhn, G.; Droege, S.; Connor, E.F.; Gemmill-Herren, B.; Potts, S.G.; Minckley, R.L.; Griswold, T.; Jean, R.; Kula, E.; Roubik, E.W.; et al. Detecting insect pollinator declines on regional and global scales. Conserv. Biol. 2013, 27, 113–120. [Google Scholar] [CrossRef] [PubMed]
  51. Aguiar, A.P.; Sharkov, A. Blue Pan Traps for collecting Stephanidae (Hymenoptera). J. Hymenopt. Res. 1997, 6, 422–423. [Google Scholar]
  52. Gollan, J.R.; Ashcroft, M.B.; Batley, M. Comparison of yellow and white pan traps in surveys of bee fauna in New South Wales, Australia (Hymenoptera: Apoidea: Anthophila). Aust. J. Entomol. 2011, 50, 174–178. [Google Scholar] [CrossRef]
  53. Prado, S.G.; Ngo, H.T.; Florez, J.A.; Collazo, J.A. Sampling bees in tropical forests and agroecosystems: A review. J. Insect Conserv. 2017, 21, 753–770. [Google Scholar] [CrossRef]
  54. Mayer, C.; Adler, L.; Armbruster, W.S.; Dafni, A.; Eardle, C.; Huan, S.Q.; Kevan, P.G.; Ollerton, J.; Packer, L.; Ssymank, A.; et al. Pollination ecology in the 21st century: Key questions for future research. J. Pollinat. Ecol. 2011, 3, 8–23. [Google Scholar] [CrossRef]
  55. Ollerton, J.; Winfree, R.; Tarrant, S. How many flowering plants are pollinated by animals? Oikos 2011, 120, 321–326. [Google Scholar] [CrossRef]
  56. Scheper, J.; Reemer, M.; van Kats, R.; Ozinga, W.A.; van der Linden, G.T.J.; Schaminée, J.H.J.; Siepel, H.; Kleijn, D. Museum specimens reveal loss of pollen host plants as key factor driving wild bee decline in The Netherlands. Proc. Natl. Acad. Sci. USA 2014, 111, 17552–17557. [Google Scholar] [CrossRef]
  57. Winfree, R.; Aguilar, R.; Vázquez, D.P.; LeBuhn, G.; Aizen, M.A. A meta-analysis of bees’ responses to anthropogenic disturbance. Ecology 2009, 90, 2068–2076. [Google Scholar] [CrossRef] [PubMed]
  58. Newbold, T.; Hudson, L.N.; Hill, S.L.L.; Contu, S.; Lysenko, I.; Senior, R.A.; Börger, L.; Bennett, D.J.; Choimes, A.; Collen, B.; et al. Global effects of land use on local terrestrial biodiversity. Nature 2015, 520, 45–50. [Google Scholar] [CrossRef] [PubMed]
  59. Millard, J.; Outhwaite, C.L.; Kinnersley, R.; Freeman, R.; Gregory, R.D.; Adedoja, O.; Gavini, S.; Kioko, E.; Kuhlmann, M.; Ollerton, J.; et al. Global effects of land-use intensity on local pollinator biodiversity. Nat. Commun. 2021, 12, 2902. [Google Scholar] [CrossRef] [PubMed]
  60. Regional Meteorological Department, Kolkata. 2020. Available online: https://mausam.imd.gov.in/kolkata/ (accessed on 6 March 2025).
  61. Thakuria, C. Yield assessment of Indian mustard variety NRCHB101 with toria varieties TS 36 and TS 38 in Dibrugarh district of Assam. Pharma Innov. J. 2023, 12, 1502–1503. [Google Scholar]
  62. Deka, B.C.; Parisa, D.; Singha, A.K.; Siangshai, R.; Massar, D.A. (Eds.) Impact of Technologies on Oilseeds Production in North Eastern Region; ICAR-Agricultural Technology Application Research Institute (ATARI): Zone-VII: Umiam, Meghalaya, India, 2018; p. 28. [Google Scholar]
  63. Belavadi, V.V.; Ganeshaiah, K.N. Insect Pollination Manual; Indian Council of Agricultural Research: New Delhi, India, 2013; pp. 1–44. [Google Scholar]
  64. Willmer, P. Pollination and Floral Ecology; Princeton University Press: Princeton, NJ, USA, 2011; pp. 1–832. [Google Scholar]
  65. Shapiro, L.H.; Tepedino, V.J.; Minckley, R.L. Bowling for bees: Optimal sample number for “bee bowl” sampling transects. J. Insect Conserv. 2014, 18, 1105–1113. [Google Scholar] [CrossRef]
  66. Moreira, E.F.; Silva Santos, R.L.S.; Penna, U.L.; Coca, C.A.; Oliveira, F.F.; Blandina Felipe Viana, B.F. Are pan traps colors complementary to sample community of potential pollinator insects? J. Insect Conserv. 2016, 20, 583–596. [Google Scholar] [CrossRef]
  67. Droege, S.; Tepedino, V.J.; LeBuhn, G.; Link, W.; Minckley, R.L.; Chen, Q.; Conrad, C. Spatial scale and sampling interval effects on abundance and species richness of native bees. Biol. Conserv. 2010, 143, 1068–1074. [Google Scholar]
  68. Rogers, S.R.; Tarpy, D.R.; Burrack, H.J. Bee Species Diversity Enhances Productivity and Stability in a Perennial Crop. PLoS ONE 2014, 9, e97307. [Google Scholar] [CrossRef]
  69. Devi, M.; Sharma, H.K.; Thakur, R.K.; Bhardwaj, S.K.; Rana, K.; Thakur, M.; Ram, B. Diversity of insect pollinators in reference to seed set of mustard (Brassica juncea L.). Int. J. Curr. Microbiol. Appl. Sci. 2017, 6, 2131–2144. [Google Scholar] [CrossRef]
  70. Berglund, H.L.; Milberg, P. Sampling of fower-visiting insects: Poor correspondence between the catches of colour pan−trap and sweep netting. Eur. J. Entomol. 2019, 116, 425–431. [Google Scholar] [CrossRef]
  71. Lezzeri, M.; Lozano, V.; Brundu, G.; Floris, I.; Pusceddu, M.; Quaranta, M.; Satta, A. Standardized transect walks outperform pan traps in assessing wild bee community in a Mediterranean protected area (Asinara National Park, Italy). Biodivers. Conserv. 2024, 33, 2329–2344. [Google Scholar] [CrossRef]
  72. Gibbs, J.; Joshi, N.K.; Wilson, J.K.; Rothwell, N.L.; Powers, K.; Haas, M.; Gut, L.; Biddinger, D.J.; Isaacs, R. Does passive sampling accurately reflect the bee (Apoidea:Anthophila) communities pollinating apple and sour cherry orchards? Environ. Entomol. 2017, 46, 579–588. [Google Scholar] [CrossRef] [PubMed]
  73. McCravy, K.W.; Ruholl, J.D. Bee (Hymenoptera: Apoidea) diversity and sampling methodology in a Midwestern USA deciduous forest. Insects 2017, 8, 81. [Google Scholar] [CrossRef] [PubMed]
  74. Vrdoljak, S.M.; Samways, M.J. Optimising coloured pan traps to survey flower visiting insects. J. Insect Conserv. 2012, 16, 345–354. [Google Scholar] [CrossRef]
  75. Nuttman, C.V.; Otieno, M.; Kwapong, P.K.; Combey, R.; Willmer, P.; Potts, S.G. The utility of aerial pan-trapping for assessing insect pollinators across vertical strata. J. Kans. Entomol. Soc. 2011, 84, 260–270. [Google Scholar] [CrossRef]
  76. Grundel, R.; Frohnapple, K.J.; Jean, R.P.; Pavlovic, N.B. Effectiveness of bowl trapping and netting for inventory of a bee community. Environ. Entomol. 2011, 40, 374–380. [Google Scholar] [CrossRef]
  77. Kirk, W.D.J. Ecologically selective coloured traps. Ecol. Entomol. 1984, 9, 35–41. [Google Scholar] [CrossRef]
  78. Zou, Y.; Xiao, H.; Felix, J.J.; Bianchi, A.; Jauker, F.; Luo, S.; Werf, W. Wild pollinators enhance oilseed rape yield in small-holder farming systems in China. BMC Ecol. 2017, 17, 6. [Google Scholar] [CrossRef]
  79. Ludewig, M.J.; Landaverde-González, P.; Götz, K.P.; Chmielewski, F.-M. Initial assessment to understand the effect of air temperature on bees as floral visitors in urban orchards. J. Insect Conserv. 2023, 27, 1013–1022. [Google Scholar] [CrossRef]
  80. Casiá-Ajché, Q.B.; Escobedo-Kenefic, N.; Escobar-González, D.; Cardona, E.; Mejía-Coroy, A.; Morales-Siná, J.; Enríquez, E.; Landaverde-González, P. Unveiling the effects of land use and intra-seasonal variation on bee and plant diversity and their ecological interactions in vegetation surrounding coffee plantations. Front. Bee Sci. 2024, 2, 1408854. [Google Scholar] [CrossRef]
  81. Tsang, T.P.; De Santis, A.A.; Armas-Quiñonez, G.; Ascher, J.S.; Ávila-Gómez, E.S.; Báldi, A.; Ballare, K.; Balzan, M.V.; Banaszak-Cibicka, W.; Bänsch, S.; et al. Land use change consistently reduces α-but not β-and γ-diversity of bees. Glob. Chang. Biol. 2025, 31, e70006. [Google Scholar] [CrossRef] [PubMed]
Agronomy 15 01281 g001
Figure 1. Radar chart showing the proportionate comparisons among different hymenopteran families across nine sampling methods.
Figure 1. Radar chart showing the proportionate comparisons among different hymenopteran families across nine sampling methods.
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Agronomy 15 01281 g002
Figure 2. Boxplot showing the data dispersion and variation among the nine sampling methods.
Figure 2. Boxplot showing the data dispersion and variation among the nine sampling methods.
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Agronomy 15 01281 g003
Figure 3. Ranking representation of used sampling methods of hymenopteran species in Brassica campestris var. toria crops.
Figure 3. Ranking representation of used sampling methods of hymenopteran species in Brassica campestris var. toria crops.
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Agronomy 15 01281 g004
Figure 4. Error bar graphs on the efficiency of nine sampling methods (T1–T9) in a normal cropping period of toria crops.
Figure 4. Error bar graphs on the efficiency of nine sampling methods (T1–T9) in a normal cropping period of toria crops.
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Agronomy 15 01281 g005
Figure 5. Error bar graphs on the efficiency of nine sampling methods (T1–T9) in a late cropping period of toria crops.
Figure 5. Error bar graphs on the efficiency of nine sampling methods (T1–T9) in a late cropping period of toria crops.
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Table 1. The number of species of hymenopteran flower visitors sampled using different methods in toria ecosystem of Assam, India (2015–2017).
Table 1. The number of species of hymenopteran flower visitors sampled using different methods in toria ecosystem of Assam, India (2015–2017).
Sl. No.FamilyTotal No. of Species SampledNo. of Species Sampled by Different Sampling Techniques
YTG
(T1)		BTG
(T2)		WTG
(T3)		YTE
(T4)		BTE
(T5)		WTE
(T6)		OP
(T7)		ST
(T8)		VT
(T9)
1Apidae155
(33.3)		3
(20.0)		4
(26.7)		8 (53.3)3
(20.0)		4
(26.7)		7
(46.7)		10
(66.7)		13
(86.7)
2Andrenidae021
(50.0)		1
(50.0)		1
(50.0)		1 (50.0)--1
(50.0)		1
(50.0)		2
(100.0)
3Megachilidae081
(12.5)		--4 (50.0)-1
(12.5)		3
(37.5)		5
(62.5)		7
(87.5)
4Vespidae18---3 (18.8)--3
(18.8)		8
(44.4)		16
(88.9)
5Scoliidae02-------1
(50.0)		2
(100.0)
6Halictidae094
(44.4)		3
(33.3)		3
(33.3)		5 (55.6)2 (22.2)2
(22.2)		5
(55.6)		5
(55.6)		7
(77.8)
7Crabronidae051
(20.0)		-1
(20.0)		1 (20.0)1 (20.0)-1
(20.0)		3
(60.0)		4
(80.0)
8Colletidae01--------1
(100.0)
9Sphecidae04------1
(25.0)		-3
(75.0)
Total 64120709220607213454
% species sampled18.810.914.134.49.410.932.853.184.4
% deviation from mean (=19.1)−37.2−63.4−52.9+15.2−68.6−63.4+9.9+78.0+182.7
* Value within parentheses is the percentage of species of the corresponding family as sampled by the method under test.
Table 2. Pairwise comparison of sampling methods used to collect hymenopterans in Brassica campestris var. toria agroecosystem (Kruskal–Wallis test).
Table 2. Pairwise comparison of sampling methods used to collect hymenopterans in Brassica campestris var. toria agroecosystem (Kruskal–Wallis test).
Pair 1–Pair 2Test StatisticStd. ErrorStd. Test StatisticSig.Adj. Sig.
BTG–VT−35.33310.617−3.3280.0010.031
BTE–VT−36.05610.617−3.3960.0010.025
WTE–VT−35.27810.617−3.3230.0010.032
WTG–VT−31.77810.617−2.9930.0030.099
YTG–VT−27.66710.617−2.6060.0090.330
BTE–ST−24.27810.617−2.2870.0220.800
WTE–ST−23.50010.617−2.2130.0270.967
BTG–ST−23.55610.617−2.2190.0270.954
WTG–ST−20.00010.617−1.8840.0601.000
YTE–VT−19.16710.617−1.8050.0711.000
BTE–OP−18.61110.617−1.7530.0801.000
BTG–OP−17.88910.617−1.6850.0921.000
WTE–OP−17.83310.617−1.6800.0931.000
OP–VT−17.44410.617−1.6430.1001.000
BTE–YTE16.88910.6171.5910.1121.000
BTG–YTE−16.16710.617−1.5230.1281.000
WTE–YTE16.11110.6171.5170.1291.000
YTG–ST−15.88910.617−1.4970.1351.000
WTG–OP−14.33310.617−1.3500.1771.000
WTG–YTE−12.61110.617−1.1880.2351.000
ST–VT−11.77810.617−1.1090.2671.000
YTG–OP−10.22210.617−0.9630.3361.000
YTG–YTE−8.50010.617−0.8010.4231.000
BTE–YTG8.38910.6170.7900.4291.000
BTG–YTG7.66710.6170.7220.4701.000
WTE–YTG7.61110.6170.7170.4731.000
YTE–ST−7.38910.617−0.6960.4861.000
OP–ST−5.66710.617−0.5340.5941.000
BTE–WTG4.27810.6170.4030.6871.000
WTG–YTG4.11110.6170.3870.6991.000
BTG–WTG−3.55610.617−0.3350.7381.000
WTE–WTG3.50010.6170.3300.7421.000
YTE–OP−1.72210.617−0.1620.8711.000
BTE–WTE−0.77810.617−0.0730.9421.000
BTE–BTG0.72210.6170.0680.9461.000
BTG–WTE−0.05610.617−0.0050.9961.000
Table 3. a. Number of hymenopteran flower visitor species recorded in different non-transect sampling methods at every site by cropping period and toria variety. b. Mean number of hymenopteran flower visitor species recorded by non-transect sampling methods, depending on site location.
Table 3. a. Number of hymenopteran flower visitor species recorded in different non-transect sampling methods at every site by cropping period and toria variety. b. Mean number of hymenopteran flower visitor species recorded by non-transect sampling methods, depending on site location.
a
Treatment (Sampling Method)Normal Cropping Period (TS 36 Variety)Late Cropping Period (TS 67 Variety)
JajimukhPanimirigaonKutuhaMeanJajimukhPanimirigaonKutuhaMean
Treatment 1 (YTG)4.014.134.514.21 b4.814.284.814.63 c
Treatment 2 (BTG)3.493.733.933.72 c4.124.214.354.23 d
Treatment 3 (WTG)3.513.533.883.64 c4.073.974.384.14 d
Treatment 4 (YTE)7.657.889.038.19 a7.497.989.008.16 b
Treatment 5 (BTE)2.192.382.502.36 d2.502.592.842.64 e
Treatment 6 (WTE)2.192.462.612.42 d2.462.712.832.67 e
Treatment 7 (OP)7.768.119.208.35 a8.138.589.848.85 a
Site Mean4.40 c4.60 b5.09 a4.704.80 b4.90 b5.44 a5.05
Deviation (%) from OM (4.88)(−) 9.84(−) 5.74(+) 4.30(−) 3.69(−) 1.64(+) 0.41(+) 11.48(+) 3.28
b
Treatment
(Sampling Method)		JajimukhPanimirigaonKutuhaMean
Treatment 1 (YTG)4.414.214.664.43 b
Treatment 2 (BTG)3.803.974.143.97 bc
Treatment 3 (WTG)3.793.754.133.89 c
Treatment 4 (YTE)7.577.939.028.17 a
Treatment 5 (BTE)2.352.492.672.50 d
Treatment 6 (WTE)2.332.592.722.55 d
Treatment 7 (OP)7.958.359.528.61 a
Mean4.604.755.27OM = 4.88
Deviation (%) from OM(−) 5.74(−) 2.66(+) 7.99-
a: Tabulated data correspond to mean values of eight assessments taken in two crops of normal and two crops of late cropping periods per locality. OM: overall mean; i.e., mean of all data under all treatments recorded in three locations in all cropping periods (=4.88). Values in mean column superscripted with different letters are statistically significantly different at p = 0.01 according to Tukey’s test (SPSS 20). b: Tabulated data are pooled between the mean of normal and late cropping periods in different locations, observed in eight evaluations. Mean values superscripted with different letters are significantly different at p = 0.01. Values in mean column superscripted with different letters are statistically significantly different at p = 0.01 according to the Tukey HSD test (SPSS 20).
Table 4. a. Mean number of hymenopteran flower visitor species recorded by transect methods in two cropping periods of toria in three different locations of Assam, India. b. Number of hymenopteran flower visitor species sampled by transect methods in toria crops.
Table 4. a. Mean number of hymenopteran flower visitor species recorded by transect methods in two cropping periods of toria in three different locations of Assam, India. b. Number of hymenopteran flower visitor species sampled by transect methods in toria crops.
a
LocationsNormal Cropping PeriodLate Cropping PeriodPooled Mean
(over Cropping Periods)
T8
ST		T9
VT		MeanT8
ST		T9
VT		Mean
Jajimukh24.7538.0031.38 c26.7539.6933.22 b32.30 c
Panimirigaon25.6939.7532.72 b27.6940.1933.94 b33.33 b
Kutuha27.4342.5635.00 a29.2341.0635.15 a35.08 a
Mean25.9640.1033.0327.8940.3134.1033.57
b
TreatmentsNormal Cropping PeriodLate Cropping PeriodMean
T8 (ST)25.9627.8926.93
T9 (VT)40.1040.3140.21
Mean33.0334.1033.57
t-test3.408 **2.767 **11.585 **
a: Mean values in a column superscripted with the same letters do not differ significantly according to LSD (p = 0.01) and Tukey (SPSS 20) tests. b: Tabulated data (columns 2 and 3) are the mean of eight observations of three locations for 2 years. ** Significantly different at 1% level of significance.
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Sarma, A.K.; Neog, B.; Deka, M.K.; Carabet, A.; Stef, R. Variable Transect Method Outperformed in Sampling Hymenopteran Flower Visitors in Brassica campestris L. var. toria Ecosystem. Agronomy 2025, 15, 1281. https://doi.org/10.3390/agronomy15061281

AMA Style

Sarma AK, Neog B, Deka MK, Carabet A, Stef R. Variable Transect Method Outperformed in Sampling Hymenopteran Flower Visitors in Brassica campestris L. var. toria Ecosystem. Agronomy. 2025; 15(6):1281. https://doi.org/10.3390/agronomy15061281

Chicago/Turabian Style

Sarma, Arup Kumar, Borsha Neog, Mukul Kumar Deka, Alin Carabet, and Ramona Stef. 2025. "Variable Transect Method Outperformed in Sampling Hymenopteran Flower Visitors in Brassica campestris L. var. toria Ecosystem" Agronomy 15, no. 6: 1281. https://doi.org/10.3390/agronomy15061281

APA Style

Sarma, A. K., Neog, B., Deka, M. K., Carabet, A., & Stef, R. (2025). Variable Transect Method Outperformed in Sampling Hymenopteran Flower Visitors in Brassica campestris L. var. toria Ecosystem. Agronomy, 15(6), 1281. https://doi.org/10.3390/agronomy15061281

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