https://researchdata.se/en/catalogue Search results en From May until September 2020, micro- and macroclimatic temperature were measured along a 1200 km latitudinal gradient in Sweden. Microclimatic temperature was measured hourly under the bark of spruce logs, while macroclimatic temperature refers to measured air temperature 1.3 m above the ground at the same study sites. From April until September 2021, saproxylic beetles were collected at these study sites. The data set "boreal_forest_climate_data" contains 12 columns and 88 rows. Block: six different study sites are distributed from southern (1) to northern Sweden (6). Plot: five study plots that contains one study site. Block 1: Plot 11-15 Block 2: Plot 6-10 Block 3: 16-20 Block 4: 21-25 Block 5: 1-5 Block 6: 26-30 Shade: three different shade level at one plot. 1: sun-exposed, 2: intermediately shaded and 3: fully-shaded. Mikro- and makrotemp: mean temperatures per Block, plot and shade. CTI: community temperature index per Block, plot, and shade. Bark: Remaining bark at every spruce log. Diameter: Diameter of the spruce logs. Regional climate: Average temperature measured by nearby weather stations for every block over the period from May-September 1990-2020 in °C. Aspect: Aspect in degrees of every plot. Species richness: Species richness per Block, plot, and shade. Totalab: Abundance per Block, plot, and shade. Dataset "specieslist_xylo" contains 6 columns and 3460 rows. Log: 15 Spruce logs distributed over different shade levels on every plot. Spruce logs 1,4,7,10 and 13 on shade level 1; spruce logs 2,5,8,11 and 14 on shade level 2 and spruce logs 3,6,9,12, and 15 on shade level 3. Sampling_date: Date, when beetle species were collected. Species: Name of saproxylic beetle species found in each spruce log. Number: Number of each species found in each spruce log. STI: Species temperature index for every beetle species. Tue, 20 May 2025 13:06:08 GMT https://researchdata.se/en/catalogue/dataset/2023-8-1 https://researchdata.se/en/catalogue/dataset/2023-8-1 Swedish University of Agricultural Sciences Anika Gossmann Thomas Ranius Martin Schroeder Erik Öckinger Ly Lindman This folder contains all data and code used in the article "The potential of semiochemical blends to monitor saproxylic beetle communities" by Viktor Gårdman, Bo Aulin, Mikael A. Molander, & Mats Jonsell. The data stems from sampling of saproxylic beetles using crosstraps baited with one of three different pheromone blends between 2017-2023 (excluding 2022) at three different harbors in southern Sweden: Gothenburg (57.7017° N, 11.9479° E), Mönsterås (57.0416° N, 16.4431° E) and Norrköping (58.5877° N, 16.1924° E). Individual counts of all recorded species of saproxylic weevils (Curculionidae) (including barkbeetles (Scolytinae)), long-horned beetles (Cerambycidae), and jewel beetles (Buprestidae) are provided per month, year, harbor, blend and number of traps used. The data collection has been conducted by the Swedish Board of Agriculture with the aim to survey the potential entry of woodboring pests through timber import to Swedish harbors. Identification of beetles has been done by experts at the Swedish University of Agricultural Sciences. All data files are .csv files. Note that more types of pheromone blends or other attractants have been used in other traps at the same sites, and that more sites have been monitored throughout years. The data here is only from consistently used sites and blends between 2017-2023. For the complete dataset on catches of beetles across all sampling sites and baits, please refer to the Swedish Board of Agriculture (https://jordbruksverket.se/). The SpeciesMatrix contains raw counts of individuals sampled per species and month, year, harbor, and blend. The number of traps used at each occasion is also given. Data on tree host preferences (file 'TreeHost') for the sampled species was extracted from the Swedish Species Information Center (SLU ArtDatabanken, https://artfakta.se/). The GLMM_Species_Modified folder contains individual .csv files of counts for each species deemed suitable for individual analysis per harbor, year, month, and blend. The number of traps used for every occasion is also given. These files have further has modified to remove excess zeros. To avoid zero-inflation, any years, harbors, or baits with zero findings for each species have been removed. These are the files used to run the GLMM models. The SSOS file contains all records of saproxylic weevils, bark beetles, long-horned beetles, and jewel beetles found in the publicly available records in the Swedish Species Observations System (SSOS = "Artportalen", https://www.artportalen.se/) in a 10x10km square around each harbor between 2017-2023. All analyses were conducted using R version 4.4.0 and the code is presented through Rmarkdown. Wed, 15 Oct 2025 12:36:17 GMT https://researchdata.se/en/catalogue/dataset/2025-91 https://researchdata.se/en/catalogue/dataset/2025-91 Swedish University of Agricultural Sciences Viktor Gårdman Bo Aulin Mikael Molander Mats Jonsell 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 Capture data of bark beetles from experiment with combination of different lures Fri, 27 Feb 2026 14:28:51 GMT https://researchdata.se/en/catalogue/dataset/2026-77 https://researchdata.se/en/catalogue/dataset/2026-77 Linnaeus University Andreas Svensson Rikard Unelius Fredrik Schlyter Anton Hubner Suresh Ganji The shared data contain information on predator-prey interaction metrics such as the vulnerability of certain prey, as well as the trophic redundancy of predators in these networks. Further, the datasets contain species richnesses and abundance of Carabid predators, herbivores, soil fauna. Include data files are: Data_submission_BetaDiv_community.csv, 19 rows × 8 columns Data_submission_BetaDiv_dietTurnover.csv, 124 rows × 7 columns Data_submission_analysisI_and_II.csv, 171 rows × 8 columns Data_submission_analysisIII.csv, 19 rows × 30 columns Besides diet based metrics, the file "Data_submission_analysisIII.csv" contains arthropod community sampling data (pitfall, soil extraction, sweep netting), whereas the file "Data_submission_analysisI_and_II.csv" only contains information on Carabids diets, and the individual that were subject to gut content analysis. Based on these individuals, both the turnover in the communities per se ("Data_submission_BetaDiv_community.csv), as well as their diet turnover was assessed (" Data_submission_BetaDiv_dietTurnover.csv"). See the READme files for more information. Tue, 30 Apr 2024 11:06:01 GMT https://researchdata.se/en/catalogue/dataset/2024-17 https://researchdata.se/en/catalogue/dataset/2024-17 Swedish University of Agricultural Sciences Janina Heinen Riccardo Bommarco The data was collected to determine the role of habitat use and non-trophic predator-predator interactions on food-web dynamics. We developed four dynamic food-web models - with vs without habitat use and non-trophic predator interactions - and fit the models to the data. We used mesocosm experiments in the greenhouse, combining all combinations of 0, 1 or 2 predator species with 1 or 2 prey species (33 combinations in total, each with 6 replicates). aphid_counts (1734R × 6C) and pred_counts (180R × 8C): Aphid populations were counted on days 2, 4, 6 and 8, while predator populations were counted on day 8. Aphid populations in treatments with no predator were also counted on day 0, and some treatments with Coccinella septempunctata were counted on day 1 and 3 as well. Initial predator populations were 10 Pardosa, 2 C. septempunctata, 20 O. majusculus, or 20 Bembidion. Where the treatment only contained one predator, these numbers were doubled (i.e. 4 C. septempunctata). 150 aphids were added to each mesocosm on day -2 (i.e. two days before predators were added). This was either 150 of one aphid species or 75 of each aphid species. body_masses_raw (44R x 5C): This data set contains body mass measurements for each species in our experiment. Some species were weighed multiple at a time because of their small size. The columns contain name of the species measured ("Species"), mass of the measured individual(s) in grams ("Mass (g)"), the number of individuals that were weighed together ("Number of individuals"), the per capita mass of those weighed in that group ("Per capita Mass (mg)"), and the average per capita mass for the species, in mg ("Avg species per capita mass (mg)"). aphid_hab_use_by_replicate ( 97R x 5C) and pred_hab_use_by_replicate (985R x 5C): This dataset contains the habitat use of each aphid and predator species. The cage was divided into four areas - walls (and roof), ground, barley, and beans and we recorded the number of individuals located in each area. If an individual moved during counting it was assigned half to each habitat it was in. Aphid habitat use was recorded on days 2 and 6 of the 8 day experiment, while predators were recorded every day (or multiple times a day for Coccinella septempunctata, because we had so few individuals. Wed, 23 Nov 2022 06:48:02 GMT https://researchdata.se/en/catalogue/dataset/2022-40-1 https://researchdata.se/en/catalogue/dataset/2022-40-1 Swedish University of Agricultural Sciences Kate Wootton Inventories of forest damage are carried out within the Swedish University of Agricultural Sciences (SLU) Forests programme. An annual monitoring of the most important sources of forest damage is carried out by the Swedish National Forest inventory (NFI). Although the Swedish NFI is an objective and uniform inventory of forest damage in Swedish forests at national and regional scales, less common or less widespread occurrences of forests pests and pathogens are difficult to survey solely through large-scale monitoring programmes. There is a need for complementary inventories to facilitate timely delivery of relevant information. Thus Target-tailored forest damage inventories (TFDI) aiming at providing data for operational decisions making at local level, and linked to specific damage events were introduced. TFDI’s are developed to give rapid response to requested information of specific damage outbreaks. The TFDIs are carried out in limited and concentrated samples, with flexible but robust methods and design. The data collected in the TFDI shall also be of such quality that it can be useful in research. During 2013 TFDI carried out a sample inventory of the volume Norway spruce (Picea abies) damage by bark beetles, Four-eyed spruce bark beetle (Polygrapus poligraphus) and/or European spruce bark beetle (Ips typographus) in older spruce forest in the county of Västernorrland. The inventory included both standing and wind-felled trees. The purpose of the inventory was to estimate the volume Norway spruce damage by the given bark beetles, but also to highlight geographical distribution and the appearance of the damage in different forest sites. The inventory was stratified by an objective sample of all the National Forest Inventory permanent sample plots in the county of Västernorrland. Included plots within the sample was older thinning forest and final felling mature forest consisting of at least 7/10 spruce and a lesser proportion of forest with lesser share of spruce or younger thinning forest. The radii of sample plots use for the damage inventory was 25 m. Diameter at breast height was measured on damage trees and wind-felled trees. Diameter on stump from cut trees with fresh damage was measured. Furthermore species of bark beetle and age of damage was recorded. The inventory was carried out in the same way as in 2011 and 2012, but with the addition that damaged wind-felled trees were included. During 2013 also the variable Edge time was introduced, i. e. when a stand edge within 25 m from plot center occurred. In total 93 plots and 330 trees and 118 wind-felled trees was measured. Some assessed and used variables: At sample plot level: Plot area measured The proportion of spruce at the sample plot Maturity class At tree level: Is the tree dead or alive? Position of tree – standing, wind thrown, stump Diameter at breast height Which species of bark beetle has attacked the tree? Which season did the damage occur? Tree volume At wind-felled tree level: Diameter at breast height Is the tree infested by bark beetle? Which species of bark beetle has attacked the tree? Which season did the tree fell? Tree volume See the document "Data_description" for more detailed information. As additional documentation, field instructions for the inventories are also provided, both for the specific inventory and for the National Forest Inventory (NFI). An English version of the National Forest Inventory field instruction is available for year 2021 only, which is why this is included here. Mon, 03 Feb 2025 14:33:44 GMT https://researchdata.se/en/catalogue/dataset/2024-626 https://researchdata.se/en/catalogue/dataset/2024-626 Swedish University of Agricultural Sciences Sören Wulff Cornelia Roberge Inventories of forest damage are carried out within the Swedish University of Agricultural Sciences (SLU) Forests programme. An annual monitoring of the most important sources of forest damage is carried out by the Swedish National Forest inventory (NFI). Although the Swedish NFI is an objective and uniform inventory of forest damage in Swedish forests at national and regional scales, less common or less widespread occurrences of forests pests and pathogens are difficult to survey solely through large-scale monitoring programmes. There is a need for complementary inventories to facilitate timely delivery of relevant information. Thus Target-tailored forest damage inventories (TFDI) aiming at providing data for operational decisions making at local level, and linked to specific damage events were introduced. TFDI’s are developed to give rapid response to requested information of specific damage outbreaks. The TFDI’s are carried out in limited and concentrated samples, with flexible but robust methods and design. The data collected in the TFDI shall also be of such quality that it can be useful in research. During 2012 TFDI carried out a sample inventory of the volume Norway spruce (Picea abies) damage by bark beetles, Four-eyed spruce bark beetle (Polygrapus poligraphus) and/or European spruce bark beetle (Ips typographus) in older spruce forest in the county of Västernorrland. The purpose of the inventory was to estimate the volume Norway spruce damage by the given bark beetles, but also to highlight geographical distribution and the appearance of the damage in different forest sites. The inventory was stratified by an objective sample of all the National Forest Inventory permanent sample plots in the county of Västernorrland. Included plots within the sample was older thinning forest and final felling mature forest consisting of at least 7/10 spruce and a lesser proportion of forest with lesser share of spruce or younger thinning forest. The radii of sample plots use for the damage inventory was 25 m. Diameter at breast height was measured on damage trees and wind-felled trees. Diameter on stump from cut trees with fresh damage was measured. Furthermore species of bark beetle and age of damage was recorded. The inventory was carried out in the same way as in 2011, but with the addition that damaged wind-felled trees and stumps from cut damaged trees were included. In total 87 plots and 194 trees was measured. Some assessed and used variables At sample plot level: Plot area measured The proportion of spruce at the sample plot Maturity class At tree level: Is the tree dead or alive? Position of tree – standing, wind thrown, stump Diameter at breast height Which specie of bark beetle has attacked the tree? Which season did the damage occur? Tree volume See the document "Data_description" for more detailed information. As additional documentation, field instructions for the inventories are also provided. Tue, 10 Dec 2024 08:14:07 GMT https://researchdata.se/en/catalogue/dataset/2024-509 https://researchdata.se/en/catalogue/dataset/2024-509 Swedish University of Agricultural Sciences Sören Wulff Cornelia Roberge Inventories of forest damage are carried out within the Swedish University of Agricultural Sciences (SLU) Forests programme. An annual monitoring of the most important sources of forest damage is carried out by the Swedish National Forest inventory (NFI). Although the Swedish NFI is an objective and uniform inventory of forest damage in Swedish forests at national and regional scales, less common or less widespread occurrences of forests pests and pathogens are difficult to survey solely through large-scale monitoring programmes. There is a need for complementary inventories to facilitate timely delivery of relevant information. Thus Target-tailored forest damage inventories (TFDI) aiming at providing data for operational decisions making at local level, and linked to specific damage events were introduced. TFDI’s are developed to give rapid response to requested information of specific damage outbreaks. The TFDIs are carried out in limited and concentrated samples, with flexible but robust methods and design. The data collected in the TFDI shall also be of such quality that it can be useful in research. During 2014 TFDI carried out a sample inventory of the volume Norway spruce (Picea abies) damage by bark beetles, Four-eyed spruce bark beetle (Polygrapus poligraphus) and/or European spruce bark beetle (Ips typographus) in older spruce forest in the county of Västernorrland and in eastern Jämtland (township of Bräcke, Ragunda and Östersund). The reason for the geographical expansion in 2014 including Jämtland compare to the previous years was due to the severe winter storms in 2013, which felled a large amount of forest. The inventory included both standing and wind-felled trees. The purpose of the inventory was to estimate the volume Norway spruce damage by the given bark beetles, but also to highlight geographical distribution and the appearance of the damage in different forest sites. The inventory was stratified by an objective sample of all the National Forest Inventory permanent sample plots in the county of Västernorrland and eastern Jämtland. Included plots within the sample was all older thinning forest and final felling mature forest consisting of at least 7/10 proportion of spruce and 25 % of forest in the same stage consisting of 3 to 6/10 proportion of spruce and 10 % of younger thinning forest consisting of a least 3/10 proportion of spruce. The radii of sample plots use for the damage inventory was 25 m. Diameter at breast height was measured on damage trees and wind-felled trees. Diameter on stump from cut trees with fresh damage was measured. Furthermore species of bark beetle and age of damage was recorded. Height and volume are estimated only for trees infested during present (0) season. The inventory was carried out in the same way as in 2011, 2012 and 2013. Wind-felled trees were included as in 2013 which comprises both wind-felled trees newly infested (season 0) with bark beetles and fresh wind-felled trees not infested with bark beetle. The dataset consist at plot level of 183 rows with 23 column, at tree level of 610 rows with 12 columns and at wind-felled tree level of 302 rows with 12 columns. Some assessed and used variables: At sample plot level: Plot area measured The proportion of spruce at the sample plot Maturity class At tree level: Is the tree dead or alive? Position of tree – standing, stump Diameter at breast height Which species of bark beetle has attacked the tree? Which season did the damage occur? Tree volume At wind-felled tree level: Diameter at breast height Is the tree infested by bark beetle? Which species of bark beetle has attacked the tree? Which season did the tree fell? Tree volume See the document "Data_description" for more detailed information. As additional documentation, field instructions for the inventories are also provided, both for the specific inventory and for the National Forest Inventory (NFI). An English version of the National Forest Inventory field instruction is available for year 2021 only, which is why this is included here. Wed, 19 Mar 2025 07:48:16 GMT https://researchdata.se/en/catalogue/dataset/2025-67 https://researchdata.se/en/catalogue/dataset/2025-67 Swedish University of Agricultural Sciences Sören Wulff Cornelia Roberge Inventories of forest damage are carried out within the Swedish University of Agricultural Sciences (SLU) Forests programme. An annual monitoring of the most important sources of forest damage is carried out by the Swedish National Forest inventory (NFI). Although the Swedish NFI is an objective and uniform inventory of forest damage in Swedish forests at national and regional scales, less common or less widespread occurrences of forests pests and pathogens are difficult to survey solely through large-scale monitoring programmes. There is a need for complementary inventories to facilitate timely delivery of relevant information. Thus Target-tailored forest damage inventories (TFDI) aiming at providing data for operational decisions making at local level, and linked to specific damage events were introduced. TFDI’s are developed to give rapid response to requested information of specific damage outbreaks. The TFDIs are carried out in limited and concentrated samples, with flexible but robust methods and design. The data collected in the TFDI shall also be of such quality that it can be useful in research. During 2021 TFDI carried out a sample inventory of the volume Norway spruce (Picea abies) damage by European spruce bark beetle (Ips typographus) in older spruce forest in the region of Götaland excluding Gotland and Svealand excluding Dalarna. This as a follow-up to the extremely hot and dry summer in 2018, which resulted in many drought stressed spruce trees that favored the spruce bark beetle. The spruce bark beetle populations, which were already high before, increased rapidly and have in recent years caused extensive damage to spruce in Götaland och Svealand. This year´s inventory is a follow-up to the inventory carried out in 2020. The inventory includes both standing infested trees as well as infested wind-felled trees and stumps from felled infested trees. The purpose of the inventory was to estimate the volume Norway spruce damage by the given bark beetles, but also to highlight geographical distribution and the appearance of the damage in different forest sites. The results from the inventory should be available for decisions making basis in forestry managements. The inventory was stratified by an objective sample of all the National Forest Inventory permanent sample plots in Götaland and Svealand. Included plots within the sample was all older thinning forest and final felling mature forest consisting of at least 7/10 proportion of spruce. For the selection of plots LPM (local pivotal method, Grafström et al) is used where the selection was spread based on the geographical position and the spruce volume of the sample plots. The radii of sample plots used for the damage inventory was 20 m, the area which was included for the described site. This means that the inventoried area was smaller than during the 2020 inventory, when the radius was 25 m. Other parts of the plot were not included in the inventory. The inventory in 2021 includes both trees with fresh infestations (season 0) and trees infested last year (season 1) by the spruce bark beetle. Diameter at breast height was measured on damage trees and wind-felled trees. Diameter on stump from cut trees with fresh damage was measured. The dataset consist at plot level of 711 rows with 28 column, at tree level (season 0) of 399 rows with 16 columns and at tree level (season 1) of 270 rows with 12 columns. Data on inventory date has been lost. The content and scope of the inventory has been developed in consultation with Swedish Forest Agency. References: Grafström, A., Lundström, N., & Schelin, L. Spatially Balanced Sampling through the Pivotal Method. Biometrics, 68(2), 514-520. Retrieved December 1, 2020, from https://doi.org/10.1111/j.1541-0420.2011.01699.x Some assessed and used variables: At sample plot level: Plot area measured The proportion of spruce at the sample plot Maturity class Number of infested trees Logging Sanitation At tree level season 0: Is the tree dead or alive? Position of tree – standing, wind-felled, stump Diameter at breast height Tree volume At tree level season 1: Diameter at breast height Tree volume See the document "Data_description" for more detailed information. As additional documentation, field instructions for the inventories are also provided, both for the specific inventory and for the National Forest Inventory (NFI). Fri, 07 Nov 2025 13:30:50 GMT https://researchdata.se/en/catalogue/dataset/2025-282 https://researchdata.se/en/catalogue/dataset/2025-282 Swedish University of Agricultural Sciences Sören Wulff Cornelia Roberge