https://researchdata.se/en/catalogue Search results en Occurrences in this dataset on Swedish Insects have been identified from specimens collected from for the Swedish Malaise Project (SMTP), an inventory funded by the Swedish Species Information Centre (ArtDatabanken). These records comprise the foundation for recent estimates on the size and composition of the Swedish insect fauna, published herein as sample-based datasets. Wed, 13 May 2020 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/gbif-sweden-10-15468-87hk5a https://researchdata.se/en/catalogue/dataset/gbif-sweden-10-15468-87hk5a Station Linné Dave Karlsson Fredrik Ronquist 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 We studied the effects of different landscape parameters on three spatial scales on the densities of pest flea beetles and crop damage at the cotyledon stage in 56 spring oilseed rape fields across five years. The landscape parameters investigated include the cover of non-crop habitats (forests and pastures) as potential overwintering sites, the distance to winter oilseed rape fields in the same year, the distance to spring oilseed rape fields in the preceding year, the landscape level crop diversity in the previous year and the edge-density in the surrounding landscapes. Flea beetles (Coleoptera, Alticinae) were collected with four pitfall traps in one observation plot established in each field and counts represent total catches for all four traps and sampling intervals combined. Crop damage was assessed in 10 or 16 (depending on the year) 0.5 m x 0.5 m squares per observation plot following the crop damage categories in Ekbom & Kuusk (2005), https://res.slu.se/id/publ/7184, at the end of cotyledon stage (~ BBCH 14). Values represent the average crop damage per observation plot. Landscape parameters were extracted from the official land-use maps provided by Lantmäteriet (Terrängkartan) at three radii (500 m, 1000 m and 2000 m) around the centre of the observation plots. For further information on the detailed methodology, see methods in the publication Boetzl et al. (2023) Spatiotemporal isolation of oilseed rape fields reduces insect pest pressure and crop damage. Journal of Applied Ecology. The data in the 'combined_dataset.csv' file have information on flea beetles and crop damages recorded in 56 fields ('site_ID') and landscape parameters in the landscapes surrounding these fields at three spatial scales. 169 rows. The landscape parameters investigated include the cover of non-crop habitats (forests and pastures) as potential overwintering sites, the distance to winter oilseed rape fields in the same year, the distance to spring oilseed rape fields in the preceding year, the landscape level crop diversity in the previous year and the edge-density in the surrounding landscapes. Flea beetles (Coleoptera, Alticinae) were collected with four pitfall traps in each plot in each field and counts represent total catches for all four traps and sampling intervals combined. Fri, 21 Apr 2023 14:31:56 GMT https://researchdata.se/en/catalogue/dataset/2023-77-1 https://researchdata.se/en/catalogue/dataset/2023-77-1 Swedish University of Agricultural Sciences Fabian Bötzl Ola Lundin The aim of our study was to disentangle the effects of the urban heat island (microclimate) and urbanization onto saproxylic beetle species. Besides dead wood, hollow trees serve as important habitat for saproxylic organisms. To study the saproxylic beetle fauna in a standardized way, we used wood mould boxes, which resemble hollow trees. The datasets describe the microclimatic temperatures in and around mulm boxes, and the sampled saproxylic beetle species in the boxes. For the temperature measurement, temperature loggers were attached in the wood mould of each box, on the wall inside each box, and on a tree next to each box. In total, we had 10 boxes in six different study cities, which where placed along an urbanization gradient. The temperature loggers measured from April-September 2022. The beetle sampling took place in 2020, where two pitfall traps were placed into each box, and thus, beetles were sampled from April-September 2020. Climate_data: This file describes the mean microclimatic temperature on plot level measured in and around wood mould boxes from mid April until mid September 2022. It contains 12 columns and 112 rows. City: 6 study cities (1: Linköping, 2: Motala, 3: Lund, 4: Göteborg, 5: Örebro, 6: Uppsala) Plot: Each city contains of 10 plots, where the wood mould boxes have been placed. Due to lost boxes, this number can vary between cities. Canopy openness: Canopy openness in [%] Logger location: 3 logger types per plot measuring microclimatic temperature (1: inside wood mould in boxes, 2: inside boxes, 3: outside boxes). Due to lost loggers, this this number can vary between plots. Distance to city center: Distance from plot to city center in [m] Number of hollow trees: Number of hollow trees in a 20 m radius around the boxes Urban forest cover_3000: Amount of urban forest in a 3000 m radius around the boxes Urban forest cover_1000: Amount of urban forest in a 1000 m radius around the boxes Urban forest cover_500: Amount of urban forest in a 500 m radius around the boxes Urban forest cover_100: Amount of urban forest in a 100 m radius around the boxes Urban structures_3000: Amount of urban structures in a 3000 m radius around the boxes Urban structures_1000: Amount of urban structures in a 1000 m radius around the boxes Urban structures_500: Amount of urban structures in a 500 m radius around the boxes Urban structures_100: Amount of urban structures in a 100 m radius around the boxes Regional climate 2022: Mean temperature per study city from April-September 2022 from SMHI Microclimate: Mean microclimatic temperature per logger across the season April-September 2022 Species_data: This file describes the number and abundance of sampled species per box. It contains 17 columns and 112 rows. Abundance: Total number of sampled saproxylic beetle individuals Species richness: Number of sampled saproxylic beetle species Microclimate: Mean microclimatic temperature across the three logger locations per plot Regional climate 2019: Mean temperature per study city from April-September 2019 from SMHI Species_data_cti: This file describes the community temperature index per box. It contains 14 columns and 112 rows. CTI: Community temperature index [°C] Wed, 17 Jan 2024 09:58:13 GMT https://researchdata.se/en/catalogue/dataset/2023-186 https://researchdata.se/en/catalogue/dataset/2023-186 Swedish University of Agricultural Sciences Anika Gossmann Ájtte Museum is one of the museums in Sweden that actively works with the collection and preservation of natural history material. The purpose of the collection is to build a special collection with the overall heading: "nature of the mountains". The collected material includes birds, mammals, fish, fungi, minerals, rocks and botanicals. The material constituting the Natural history collections are donated by private persons, the police (“state wildlife”) and other museums and institutions. In addition, the museum also conducts its own active collection activities. Currently, the museum holds over 19,000 natural history objects in its database /collection. The collections are searchable in the museum common database: http://collections.ajtte.com/ and thus accessible to researchers, students and other interested but also useful for educational purposes. The collections are stored in climate-controlled archives so that they can be preserved in a safe and secure way for the future. Our goal is that these unique collections will come to attention of the special interest researcher and be a resource to taxonomic and morphological studies on the species of Northern Sweden. The insect collections are the largest part of the natural history collections of Ájtte museum, with more than 14,500 specimens, mainly including beetles and butterflies with a northern provenance. The beetles (Coleoptera) of this collection were donated by Sven-Erik Nilsson’s estate (2003). The butterflies (Lepidoptera) are from the Jokkmokk area and consists of approximately 1 200 specimens belonging to 400 different species, and was donated by Roger Engelmark (Professor Emeritus, University of Umeå). The museum's collection of reindeers (Rangifer tarandus) is very extensive, perhaps the world's largest. The collection consists of osteological material with over 1 000 skulls, with antlers and jaws from both adult and young animals of both sexes. This well-documented material of reindeer has been collected from the whole Swedish range of distribution. The collection was previous held by the Swedish Museum of Natural History, but in 2010 it was taken over by Ájtte museum. The material was collected by the researcher Folke Skuncke during the middle of the 19th century. Thu, 14 Nov 2013 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/gbif-sweden-10-15468-eoika6 https://researchdata.se/en/catalogue/dataset/gbif-sweden-10-15468-eoika6 GBIF Sweden Göran Sjöberg Dataset used to infer the phylogeny of Dytiscidae in Bergsten et al (2025) "Whole Genome Shotgun Phylogenomics Resolve the Diving Beetle Tree of Life" in Systematic Entomology. Included files: - aa-baits-macse-trees_nov_concat.faa.gz (30M) Amino-acid sequence data in fasta format. Gzip-compressed. - aa-baits-macse-trees_nov_concat.partitions.gz (48K) Gene-partion definitions in plain text format. Gzip-compressed. - ortho.aa.tsv.gz (40K) Tab-separated translation table between TC-V9-V7 ortholog definitions. Gzip-compressed. - README.md (8K) Readme-file, plain text format. -MANIFEST.txt Manifest file listing file content in this item, plain text format. Abstract of original article: Diving beetles (Dytiscidae) are important generalist predators in freshwater ecosystems that have been around since the Jurassic. Previous phylogenetic studies have identified a largely stable set of monophyletic named groups (subfamilies, tribes and subtribes), however backbone relationships among these have remained elusive. Here we use whole-genome sequencing to reconstruct the phylogeny of Dytiscidae. We mine de novo assemblies and combine them with others available from transcriptome studies of Adephaga to compile a dataset of 149 taxa and 5364 orthologous genes. Species tree and concatenated maximum likelihood methods provide largely congruent results resolving in agreement all but two inter-subfamily nodes. All eleven subfamilies are monophyletic supporting previous results, possibly also all tribes but Hydroporini is recovered as paraphyletic with weak support and monophyly of Dytiscini is method dependent. One large clade includes eight of eleven subfamilies (excluding Laccophilinae, Lancetinae and Coptotominae). Matinae is sister to Hydrodytinae + Hydroporinae in contrast with previous studies that have hypothesized Matinae as sister to the remaining Dytiscidae. Copelatinae belong in a clade with Cybistrinae, Dytiscinae, Agabinae and Colymbetinae. Strongly confirmed sister-group relationships of subfamilies include Cybistrinae + Dytiscinae, Agabinae + Colymbetinae, Lancetinae + Coptotominae, and Hydrodytinae + Hydroporinae. Remaining problems include resolving with confidence the basal ingroup trichotomy and relationships between tribes in Hydroporinae. Resolution of tribes in Dytiscinae is affected by methodological inconsistencies. Platynectini, new tribe, is described and Hydrotrupini redefined within subfamily Agabinae. This study is a step forward towards completely resolving the backbone phylogeny of Dytiscidae which we hope will stimulate further work on remaining challenges. DNA extraction Specimen DNAs were extracted using Qiagen DNEasy or Puregene kits (Valencia, California, USA) using the animal tissue protocols. Library preparation DNA extractions of 14 samples were prepared with Chromium Genome kit to generate linked reads with 10X Genomics technology. The 14-sample library was sequenced on 8 lanes of Illumina HiSeqX using a 2x151 bp setup and the 'HiSeq X SBS' chemistry. 12 of the 14 samples were re-sequenced in a second run with identical run parameters as the previous but on 6 lanes and the assembly for these 12 samples are based on merging the data from run 1 and 2. Illumina libraries were prepared for an additional 62 samples following Prum et al. (2015). In short, a Covaris ultrasonicator was used to fragment extracted DNA to a size range of 200-700bp. Using a Beckman-Coulter Biomek FXp liquid-handling robot, we performed blunt-end repair followed by size selection to 200-400 using SPRI select beads (Beckman-Coulter Inc.; 0.9x ratio of bead to sample volume). Adapters containing sample-specific indexes were also ligated (for details, see Prum et al. 2015). After assessing DNA concentration using Qubit, we pooled libraries equally in groups of ~16, and verified library quality using qPCR. Initial sequencing took place on an Illumina NovaSeq6000 S2 flow cell (shared with 38 other samples), with the PE150bp protocol and dual 8bp indexing. After assessing sequencing coverage from this initial run, we re-pooled the libraries (to optimize coverage uniformity) and collected additional reads (same protocol) on a portion of an S4 flow cell. The re-pooling/re-sequencing process was repeated twice more using SP flow cells. De novo assembly For samples prepared using 10X Genomics, draft de novo assemblies were generated using supernova v.2.1.1 with non-default parameters "--nopreflight" and "--accept-extreme-coverage" (Weisenfeld, et al. 2017). For remaining samples, processed reads from the four sequenced lanes were concatenated and used as input for Abyss v2.2 in paired-end mode. After testing several k-mer sizes, we decided to use a k-mer size of 48 based on the quality of resulting alignments and appropriate length of resulting contigs (N50). We also set Abyss to run using a Bloom filter size to 100G with three hash functions (-H argument) and a k-mer count threshold of 3 (-kc). Extraction of orthologous gene dataset We used three previous transcriptome-based studies focusing on Coleoptera (McKenna, et al. 2019), Dytiscoidea (Vasilikopoulos, et al. 2019) or Neuropterida (Vasilikopoulos, et al. 2020) (see ReadMe file) to assemble an orthologous gene dataset. Each orthologous gene is identified by an OrthoDB code and we used OrthoDB V.10 and a translation table to match the codes between OrthoDB V.7 (McKenna, et al. 2019) (Vasilikopoulos, et al. 2020) and V.9 (Vasilikopoulos, et al. 2019) (see ortho.aa.tsv.gz).The matching and merging of the datasets resulted in 6,413 preliminary reference genes. The exon-capture study of Adephaga (Vasilikopoulos, et al. 2021) is a subset of Vasilikopoulous et al. (2019) since it targeted 651 of the 3,085 genes in the latter study and the 651 genes from the Adephaga terminals were downloaded, matched and included as well. The amino-acid alignments from the published data were subsequently used as baits when extracting corresponding regions from the new genome assemblies (scaffolds files). The gene extraction was made using the ALiBaSeq workflow v1.2 (Knyshov, et al. 2021). The workflow performs sequence extraction based on a local alignment search. We used tblastn v2.12.0+ (Camacho, et al. 2009) with an E-value set to 1e-10, and ALiBaSeq run with alibaseqPy3.py -x a -f M -b blast_results -t assemblies -e 1e-10 --is --amalgamate-hits --ac tdna-tdna. The combined nucleotide data set was translated to amino-acids and aligned using the program suite MACSE v10.02 (Ranwez, et al. 2011). This process included multiple sequence alignment with MAFFT v7.271 (Katoh, et al. 2002), at both nucleotide and amino-acid level, and both pre- and post-alignment filtering steps using HMMCleaner v1.8.VR2 (Di Franco, et al. 2019), where longer indel regions, shorter isolated codons, and frameshifts are identified and masked, as well as trimming alignments at the ends. Alignment and filtering The gene files were aligned with MAFFT v7.453 (option --auto). The multiple sequence alignment was then filtered using BMGE v1.12 (Criscuolo and Gribaldo 2010) with default settings. Maximum likelihood phylogenies were then estimated using RAxML-NG v1.1.0 (Kozlov, et al. 2019) with a fixed substitution model (LG+G8+F) (Yang 1994, Le and Gascuel 2008). These trees were used together with the multiple sequence alignment as input to TreeShrink v1.3.9 (Mai and Mirarab 2018) (with default settings), which can filter sequences based on whether a terminal appears as an outlier in a tree as determined by its branch length. The resulting, filtered alignment (5,364 genes, 825,452 aa positions, 149 terminals, aa file: aa-baits-macse-trees_nov_concat.faa, gene partition file: aa-baits-macse-trees_nov_concat.partitions) was then re-aligned with MAFFT, and subjected to a new tree inference with RAxML-NG, this time with automatic selection of the substitution model using ModelTest-NG v.0.2.0 (Darriba, et al. 2019). The final set of gene trees was used as input to ASTRAL-III v5.6.3 (Zhang, et al. 2018) and the concatenated dataset used for maximum likelihood analysis with IQ-TREE v2.1.2 (Nguyen, et al. 2015). See original paper and its supplementary information for further details on analyses and data sources. Mon, 28 Apr 2025 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-17044-scilifelab-28868468 https://researchdata.se/en/catalogue/dataset/doi-10-17044-scilifelab-28868468 Swedish Museum of Natural History Johannes Bergsten Johan Nylander Oscar Ospina Alan Lemmon Kelly Miller 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 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 Original data for Molander et al: p-Mentha-1,3-dien-9-ol: A novel aggregation-sex pheromone for monitoring longhorn beetles (Cerambycidae) in Eurasia and North America Longhorn beetles (Cerambycidae) are a diverse family of beetles with considerable impact as forest pests and vectors of pathogens, as well as being important components of forest food webs and ecosystem functionality. In recent years, numerous cerambycid pheromones have been identified, revealing some broad general patterns in functionality in terms of sex or aggregation- sex pheromones in different subfamilies, and different types of compounds characterizing the pheromones of various cerambycid taxa. Here, we include supplementary and original data regarding the identification of the aggregation- sex pheromones of the Eurasian longhorn beetle Aromia moschata moschata (L.) (Cerambycinae; tribe Callichromatini) and the North American species Holopleura marginata LeConte (Cerambycinae; Holopleurini). This is part of an ongoing effort to extend the taxonomic coverage of identified cerambycid pheromones, and to expand the prospects for cerambycid monitoring into the study of biodiversity and ecosystem services. Both species were found to use the novel pheromone compound p-mentha-1,3-dien-9-ol, which also attracted significant numbers of the longhorn beetle Xestoleptura crassipes (LeConte) (Lepturinae; Lepturini) in trials in California. p-Mentha-1,3-dien-9-ol represents a class of pheromone compounds novel to both tribes (Callichromatini and Holopleurini), further increasing the chemical space of identified pheromones within the subfamily Cerambycinae. This compound is also noteworthy because it represents an entirely different chemical class of pheromones than the monoepoxide (E)-2-cis-6,7-epoxynonenal previously reported as an aggregation-sex pheromone for the invasive Asian congener Aromia bungii (Faldermann). Original data from field trapping studies of catches of different species to different lures tested in the study. Aromia moschata trapping: Field trapping trials were performed at Revingehed near Lake Krankesjön, at 20 different field trapping sites (replicates) identified only by numbers 1-20. Treatments compared comprised two different baits: Dienol (p-Mentha-1,3-dien-9-ol dissolved in isopropanol) and Control (isopropanol only). Table columns: Year, Set date, Emptying date, Ordinal date, Trap site, Treatment (Dienol or Control), Total catch, Catch males, Catch females. Holopleura marginata trapping (and other species): Field trapping trials were performed at four different sites in northern California: 1) Slaughterhouse Ravine, Magalia, Butte Co. (Magalia), 2) Rattlesnake Creek at Forest Road 27N12 (Rattle), 3) Junction Forest Roads 27N06 and 27N12Y (Rd27), 4) Whispering Pines Pet Clinic property, Magalia, Butte Co. (Whisp). Treatments compared comprised four different bait types with active components dissolved in isopropanol: Dienol (p-Mentha-1,3-dien-9-ol), Alcohol (2-(4-methylphenyl)-1-propanol = p-cymen-9-ol), 1:1 blend of the former, and Control (isopropanol). Mon, 02 May 2022 14:13:33 GMT https://researchdata.se/en/catalogue/dataset/2022-56-1 https://researchdata.se/en/catalogue/dataset/2022-56-1 Swedish University of Agricultural Sciences Mattias Larsson Jocelyn Millar 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 2020 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 and Svealand excluding Gotland and 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. 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 2012) 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 use for the damage inventory was 25 m, the area which was included for the described site. Other parts of the plot were not included in the inventory. The inventory only includes trees with fresh infestations (season 0) from infestations of 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 653 rows with 30 column, at tree level of 621 rows with 16 columns. The content and scope of the inventory has been developed in consultation with Swedish Forest Agency. References: Grafström, A., Lundström, N., & Schelin, L. (2012). 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: Is the tree dead or alive? Position of tree – standing, wind-felled, stump 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). An English version of the National Forest Inventory field instruction is available for year 2021 only, which is why this is included here. Mon, 29 Sep 2025 13:02:35 GMT https://researchdata.se/en/catalogue/dataset/2025-168 https://researchdata.se/en/catalogue/dataset/2025-168 Swedish University of Agricultural Sciences Sören Wulff Cornelia Roberge