https://researchdata.se/en/catalogue Search results en Here is presented all data and code used in the article "Strong diel variation in the activity of insect taxa sampled by Malaise traps" by Viktor Gårdman, Emme McDonald & Tomas Roslin. The sampling of insects through Malaise traps was conducted by the authors. 24 malaise traps were erected in a boreal forest in central Sweden (Lat. 60.024855, long. 17.751336) and emptied every second hour, with the exception of night (samplng events during night = 22:00, 02:00, 06:00) for five consecutive days between 14-19th of July 2022. The sampling design is described in further detail in the article (Fig. 1B). Insects were identified to taxonomic Family for Diptera, Coleoptera, and Hymenoptera, except for the superfamilies of Chalcidoidea and Cynipoidea (Hymenoptera). Chalcidoids and Cynipoids were only identified to the superfamily level, due to difficulties in assigning lower taxonomic levels without risking misidentification. Hemiptera was divided into taxonomic families for Heteroptera, and into suborders for Auchenorrhyncha and Sternorrhyncha. To simplify identification of a large group with similar morphology, all microlepidopteras were grouped as such with no further identification. Furthermore, to speed up the identification task, all insects not belonging to Diptera, Hymenoptera, Coleoptera, Lepidoptera or Hemiptera were identified to Order alone. The HRS_SpeciesData file contains information about each captured individual across all taxa for each 2 hour sampling interval during the five days of sampling. Dates are given as DD/M. TrapID refers to which of the 24 traps used the individual was found in. Time is given in hh:mm and refers to the time of sampling, Time_con refers to time in only hh, and time_Num shows time of day as a fraction between 0 (00:00) and 1 (23:59). The superfamily belonging for each taxon used is given. Note that for taxa were only taxonomic Order or Suborders are given, the superfamily column refers to this Order or Suborder. The HRS_EnviData file contains information about how many individual were captured at each timestep for the 17 most common taxa (appearing as >49 individuals or in >19 timesteps), along with weather covariates for each timestep. The weather covariates are average values from the five half hour measurements per sampling period (expect for 22:00-02:00 and 02:00-06:00 where n=9). The taxonomic columns follow the same principle as in HRS_SpeciesData, with an additional column of taxonomic Order. Times and date also follow the same principle as in HRS_SpeciesData. ID is a unique mix of Date and time, given as DDHH (Date, Hour). The emptying of trap at 20:00 on the 15h would have ID 1520. Temperature is given in degrees Celsius (°C), wind speed in m/s, cloud cover as a fraction between 0 (no cloud) and 1 (complete cloud cover), rain in mm, wind direction in cardinal directions, and relative humidity in %. Data on weather covariates was provided by the Swedish Transport Administration (https://www.trafikverket.se/) from weather station 327 Björklinge (Lat. 60.05042, long. 17.62149). All code was created using R version 4.4.0 and is presented through Rmarkdown Fri, 05 Dec 2025 12:45:22 GMT https://researchdata.se/en/catalogue/dataset/2025-211 https://researchdata.se/en/catalogue/dataset/2025-211 Swedish University of Agricultural Sciences Viktor Gårdman Emme McDonald Tomas Roslin Data of chemical compounds extracted from honey bee (Apis mellifera) brood in a varroa resistant and varroa susceptible population. Samples were taken 0, 6, 12, 18, 24, and 36 hours after brood capping by immersing pupae in pentane for 10 minutes. 6 hives from each population were used, and 3 replicates were taken per hive per time point. The FAME column was calculated by adding Methyl Palmitate, Linoloate, and Stearate together, while the FAEE columb was calculateed by adding Ethyl Palmitate, Linoloate, and Stearate together. Samples were analyzed using gas chromatography. R version 4.4.0 and RStudio version 1.4.1.748 were used to analyze the data. All packages and their version is listed in the attached R script. Data files included: Scaramella_et_al_2024_Contrast.tsv: 16 rows × 12 columns Scaramella_et_al_2024_Data.tsv: 210 rows × 14 columns Mon, 24 Jun 2024 13:15:10 GMT https://researchdata.se/en/catalogue/dataset/2024-173 https://researchdata.se/en/catalogue/dataset/2024-173 Swedish University of Agricultural Sciences Nicholas Scaramella Barbara Locke This study makes part of the research project GINFRA – green rights-of-way infrastructure for biodiversity and ecosystem services. The aim of the project was to quantify whether linear infrastructure habitats (road verges and power-line corridors) support biodiversity by assessing the influence of the area of these habitats in the landscape, their contribution to landscape connectivity and population persistence. The linked data was collected by surveying bumblebee queens during the spring and late summer in 20 sites in Uppland, Sweden. The sites were paired such that half of them had a high flowering plant diversity in the road verge and a gradient in traffic intensity from ~100 to ~6000 vehicles per day, and the other half had a similar gradient in traffic intensity but low flowering plant diversity in the road verge (i.e. regular grass dominated road verges). The surveyor walked a 2 km transect (1 km in each side of the road) and recorded all dead and alive bumblebee queens. The data set consists of 403 observations. Each observation corresponds to an observed bumblebee queen, whether they were found dead or alive and what behaviour they presented when observed. The data was gathered in 4 visits, 2 in spring and 2 in the late summer. Weather information is also present in the dataset, as well as information regarding the average width of the road verge. The data file Queen_mortality_and_behaviour.csv contains 403 rows and 12 columns. See the general description and the documentation file for more information. Thu, 30 Jun 2022 13:58:00 GMT https://researchdata.se/en/catalogue/dataset/2022-50-1 https://researchdata.se/en/catalogue/dataset/2022-50-1 Swedish University of Agricultural Sciences Juliana Dániel-Ferreira Åsa Berggren Riccardo Bommarco Jörgen Wissman Erik Öckinger The data set was collected in Uppsala Sweden between 2019 and 2021. Hives were established using varroa resistant queens from Oslo, Norway (n = 3), Gotland Sweden, (n = 5), and Avignon, France (n = 4), with a varroa susceptible population from Uppsala, Sweden (n = 5) as control. All hives were located at the SLU Lövsta research station (GPS Coordinates: 59° 50’ 2.544”N, 17° 48’ 47.447”E). Varroa destructor mite reproductive success was measured on frames with adult honeybee workers exposed to, and excluded from access to honeybee larvae. Excluders were added directly after brood capping, and frames were dissected nine days later. Cell caps were removed using a scalpel with the pupae and mite families carefully removed from the cell using forceps and a fine paint brush. Mite reproductive success calculated by counting successful reproduction attempts, which was defined as a mite that successfully produced one male, and at least one female offspring. If a mite did not meet this requirement, it was considered a failed reproduction attempt and the reason for failure was documented. All data was analyzed in R version 4.0.1 using R Studio 1.3.959. A linear mixed-effect model was used with mite reproductive success as the response variable, population origin and excluder treatment as independent variables, with colony and year as random effect variables to compare treatments within each population as well as fecundity. Least-square means of the model were used to compare treatments between individual populations. Scaramella_et_al_2023_Data.tsv - Data set consists of 34 rows and 21 columns. Colony demographics, and designated treatment are listed. All data collected are count data and are explained in more detail in read me file. R script used in analysis is attached. It is split into two sections, with the first being used for statistical analysis, and the second used for plot creations used in the paper. Sections defined by title SECTION 1 - ANALYSIS and SECTION 2 - PLOTs The output Scaramella_et_al_2023_Analysis_Code_log.txt and plot file Rplots.pdf can, provided that the script is in the same directory as the data files and needed R packages are installed (see sessionInfo.txt), be reproduced by running: Rscript Scaramella_et_al_2023_Analysis_Code.R > \ Scaramella_et_al_2023_Analysis_Code_log.txt Scaramella_et_al_2023_Bar_Graph_Data.tsv - Data set consisting of 8 rows & 5 columns. Colony demographics, and designated treatment are listed. All data generated from the count data in Scaramella_et_al_2023_Data.tsv and are explained in more detail in read me file. Scaramella_et_al_2023_Stacked_Bar_Graph_Data.tsv - Data set consisting of 102 rows & 8 columns. Colony demographics, and designated treatment are listed. All data is Scaramella_et_al_2023_Data.tsv restructured to include reason failed as a column. The data is explained in more detail in read me file. Thu, 01 Jun 2023 11:09:57 GMT https://researchdata.se/en/catalogue/dataset/2023-79-1 https://researchdata.se/en/catalogue/dataset/2023-79-1 Swedish University of Agricultural Sciences Nicholas Scaramella Ashley Burke Melissa Oddie Barbara Locke The aim of this study was to investigate how short- and long-tongued bees (bumblebees and honeybees) affect seed production in different cultivars of red clover, focusing on tetraploid cultivars. The study includes two experiments. In the first one, data were collected from field trials at six different sites (belonging to Lantmännen) distributed in southern and northern Sweden over two years. The data from this experiment include seed yield, seed set, abundance of short- and long-tongued bees and seed-eating weevils, and plant traits (flower head density and number of florets per flower head) from one diploid and three tetraploid red clover cultivars. The second experiment was a cage study where seed yield from tetraploid red clover was evaluated from cages with different densities of the short-tongued bumblebee Bombus terrestris, and compared with seed yield from an open plot adjacent to the cages. This study was conducted in farmers' fields in southern and northern Sweden over two years. Wed, 11 Mar 2026 08:17:06 GMT https://researchdata.se/en/catalogue/dataset/2026-28 https://researchdata.se/en/catalogue/dataset/2026-28 Swedish University of Agricultural Sciences Kajsa Svensson Veronika Hederström Ida Valentin Sara Lindholm Linda Öhlund Mattias C. Larsson Åsa Lankinen This data set comprises the species richness of vascular plants, butterflies and bumblebees in linear infrastructure habitats (road verges and power lines) and the historical and present grassland cover in a 2 km buffer surrounding each habitat. The main purpose of this data set is to investigate if older linear infrastructure habitats sustain a higher richness of vascular plants and pollinators, and to study if the surrounding grassland habitat in the landscape from the past or the present has an influence on the contemporary species richness. The data also contains the species richness of grassland specialist vascular plants and butterflies, which is a subset from the total richness of the respective groups. The data on plants and pollinators was assessed during fieldwork in 2016. The data on grassland cover was calculated using the Swedish National Land Cover Data (NMD, Nationella marktäckedata) for the contemporary grassland, and a digitized Swedish Economic Map from the 1950s. The dataset consists of 112 rows and 15 columns, excluding headers. Each row contains information for one studied habitat (112 in total). The columns contain information on the studied 'Landscape' and 'Habitat' within the landscape, the coordinates of the transect in each habitat ('Start_X', 'Start_Y', 'End_X', End_Y'), information on the time since habitat establishment ('FirstAppearance') and the surrouding grassland cover in the past and present ('1950s_Grassland' and '2017_Grassland', respectively), and the continuously existing grassland ('Continuous_Grassland'). Furthermore, it contains information on the species richness of all vascular plants ('PL_rich_all') and grassland specialist vascular plants ('PL_rich_spec'), all butterflies ('BF_rich_all') and grassland specialist butterflies ('BF_rich_spec'), and bumblebees ('BB_rich'). For further explanation on the information and how it was assessed, please see the README file. Tue, 31 Jan 2023 10:00:07 GMT https://researchdata.se/en/catalogue/dataset/2022-246-1 https://researchdata.se/en/catalogue/dataset/2022-246-1 Swedish University of Agricultural Sciences Svenja Horstmann Most research on the biology of the western honey bee (Apis mellifera) focuses on the worker bees, but knowledge about drones is lacking despite their important role in mating with a virgin queen. Available information about their ecology and behavior are mainly based on direct observations in need of intensive experience and knowledge about honey bees. Only two recent studies conducted in France and Argentina have monitored drones continuously, but on the scale of a single observation hive or during a short time period only. Therefore, studies that have continuously monitored drone flight activity during the whole mating season are still lacking. Further, we are not aware of any studies that have compared the ecology and behavior of drones between different subspecies of Apis mellifera. Besides the aim of analysing the ecology and behavior of drones in spring and summer in Sweden, where the climate poses challenging conditions for honey bees, the objective of this project was to compare the native, but threatened, subspecies Apis mellifera mellifera (Mel) with the hybrid ’Buckfast’ (Apis mellifera x, Buck). In Sweden, the latter is most commonly used in beekeeping today. Activity data at the entrance of the hives was collected with the use of Radio Frequency Identification (RFID) technology at two different apiaries with 8 colonies each. RFID technology enables the continuous monitoring of bees tagged with a microchip on their thorax. Hereby, only newborn drones with a maximum age of 3 days were tagged. Further, drones’ activity and behavior at the entrance of the hive was studied from video recordings. Weather parameters were measured by weather stations installed within the apiaries, enabling a direct analysis of the activity in relation to weather conditions (temperature, wind speed, rain, humidity). Wed, 14 Feb 2024 14:58:09 GMT https://researchdata.se/en/catalogue/dataset/2023-211 https://researchdata.se/en/catalogue/dataset/2023-211 University of Skövde Finja Schaumann We studied the effects of undersowing oats with a mixture of three annual clovers species across different aspects of cropping system multi-functionality using 26 observation plots in a paired field design with 13 fields. We investigated 16 below-and above-ground ecosystem service indicators related to soil mineral nitrogen, arable weed control, pollination, disease and pest pressures, natural pest control and crop yield. We measured each of the 16 ecosystem service indicators in an intercropped and in a control treatment with identical management. Some indicators were measured before and after the experiment in both treatments to assess the magnitude of change by the treatment. For further information, see methods in the publication Boetzl et al. (2023) Undersowing oats with clovers supports pollinators and suppresses arable weeds without reducing yields. Journal of Applied Ecology. The data in the 'combined_dataset.csv' file have information on different ecosystem service indicators collected in 13 fields ('field_ID') and two treatments per field (intercropped and control). 27 rows. The 16 ecosystem service indicators contained are: soil mineral nitrogen (before and after the experiment), arable weed cover, arable weed biomass, granivorous carabid beetle density, flower cover, pollinator density, root disease severity (before and after the experiment), root-feeding nematode density (before and after the experiment), cereal leaf beetle damage, predatory nematode density (before and after the experiment), predatory carabid beetle density, staphylinid beetle density, spider density, predation rates on the soil level, oat yield and oat yield nitrogen content. Additionally, the biomass of undersown clovers in the intercropped treatment, the area covered by the intercropped treatment, the field size and the arable land cover in 1 km radius around the oat field are stated. Mon, 16 Jan 2023 15:23:13 GMT https://researchdata.se/en/catalogue/dataset/2022-258-1 https://researchdata.se/en/catalogue/dataset/2022-258-1 Swedish University of Agricultural Sciences Fabian Boetzl Ola Lundin This data set comprises the flower density and abundance, richness and evenness of wild bees and butterflies in 37 road verges in Skåne county in southern Sweden, as well as information about the respective road verge width, traffic intensity in the adjacent road, mowing frequency, habitat quality and exact location. It is a crossed study design, allowing to separate the effects of road verge classification (valuable or regular) from the effects of mowing frequency (mowing once or twice) through the following four combinations: Valuable and mowed once, valuable and mowed twice, regular and mowed twice, regular and mowed once. Within each combination, there is a gradient in traffic intensity comparable between combinations. The data on plants and pollinators was assessed during fieldwork in 2021 and 2022. The data on traffic intensity and habitat quality was derived from the national road database: https://nvdb2012.trafikverket.se/. To get information about land cover we used the National Land Cover Database from the Swedish Environmental Protection Agency: https://metadatakatalogen.naturvardsverket.se/metadatakatalogen/GetMetaDataById?id=8853721d-a466-4c01-afcc-9eae57b17b39 To select landscapes without meadows and pastures of high nature value within 350m of the study sites we used the TUVA database from the Swedish Board of Agriculture: https://etjanst.sjv.se/tuvaut/ To select road verges, we used the environmental and infrastructure data from the national road database NVDB from Trafikverket: https://nvdb2012.trafikverket.se/ The data set consists of 37 rows and 361 columns, excluding headers. Each row contains information for one studied road verge (37 in total). The columns contain information on the unique identifier of each road verge (‘SiteID’), the coordinates of the middle of the 200 m long transect in each road verge (‘N’, ‘E’), road verge quality (‘RV_Quality’), mowing frequency (‘Mowed’), mean width of the road verge (‘VergeWidthMean’), traffic intensity (‘TI’), flower density (‘Flow_Dens’), butterfly abundance, richness and evenness (‘BF_Abun’, ‘BF_Rich’, ‘BF_Even’), wild bee abundance, richness and evenness (‘WB_Abun’, ‘WB_Rich’, ‘WB_Even’), and vascular plant richness (‘Vasc_Rich’). The columns P-IN contain the frequency of each vascular plant species observed in our study, with the species name as column header. The columns IO-JU contain the abundance of butterfly species observed in our study, with the species name as column header. The columns JV-MW contain the abundance of wild bee species observed in our study, with the species name as column header. For further explanation on the information and how it was assessed, please see the README file. Mon, 13 May 2024 11:46:45 GMT https://researchdata.se/en/catalogue/dataset/2024-22 https://researchdata.se/en/catalogue/dataset/2024-22 Swedish University of Agricultural Sciences Svenja Horstmann Alistair G. Auffret Lina Herbertsson Björn K. Klatt Sophie Müller Erik Öckinger Phenotypic plant data and herbivory intensity data from eight Solanum dulcamara populations in four habitats, and arthropod data from five of these populations collected in pan straps and sticky traps. The phenotypic plant data include measures on growth and reproduction. Herbivory data include measures on lost leaf area. Arthropod data are divided into different taxa. Thu, 03 Sep 2026 12:19:13 GMT https://researchdata.se/en/catalogue/dataset/2026-144 https://researchdata.se/en/catalogue/dataset/2026-144 Swedish University of Agricultural Sciences Åsa Lankinen Kristin Aleklett