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Tree Health Conditions (mortality, damage, disease, bark beetles) in Fuel Reduction Treatments Located Near Communities in Interior Alaska and the Cook Inlet Region of Alaska - Observations from July-August 2023
This dataset contains tree-, transect-, and site-level observations of forest stands at sites that received a fuel reduction treatment. Tree-level observations include species, diameter, living status, damage, disease, and bark beetle presence. Transect-level observations include level of coarse woody debris and bark beetle presence. Sites are categorized by region (recent/ongoing spruce beetle oubreak or endemic spruce beetle population levels) and treatment type (hand-thinned or mechanincally felled and masticated). These observations are from July-August 2023. Sites are located near communities in Interior Alaska and the Cook Inlet Region.
Data from: Functional structure of European forest beetle communities is enhanced by rare species
<p>From article abstract:</p> <p><a href="https://doi.org/10.1016/j.biocon.2022.109491">https://doi.org/10.1016/j.biocon.2022.109491</a></p> <p><strong>ABSTRACT</strong></p> <p>Biodiverse communities have been shown to sustain high levels of multifunctionality and thus a loss of species likely negatively impacts ecosystem functions. For most taxa, however, the roles of individual species are poorly known. Rare species, often the most likely to go extinct, may have unique traits leading to unique functional roles. Alternatively, rare species may be functionally redundant, such that their loss would not disrupt ecosystem functions. We quantified the functional role of rare species by using capture records of wood-living (saproxylic) beetle species, combined with recent databases of their morphological and ecological traits, from three regions in central and northern Europe. Using a rarity index based on species’ local abundance, geographic range, and habitat breadth, we used local and regional species removal simulations to examine the contributions of both the rarest and the most common beetle species to three measures of community functional structure: functional richness, functional specialization, and functional originality. In both regional species pools and local communities, all three of these measures declined more rapidly when rare species were removed than under common (or random) species removal scenarios. These consistent patterns across scales and among several forest types give evidence that rare species provide unique functional contributions, and that their loss may disproportionately impact ecosystem functions. This implies that conservation measures targeting rare and endangered species, such as preserving intact forests with dead wood and mature trees, can provide broader ecosystem-level benefits. Experimental research linking functional structure to ecosystem processes should be prioritized to increase our understanding of the functional consequences of species loss and to develop more effective conservation strategies.</p> <p> </p> <p><strong>DATASET DESCRIPTION</strong></p> <p>This dataset includes a) beetle capture information and b) beetle trait information from three countries: 1) Norway, 2) Finland, and 3) Germany. </p> <p> </p> <p><strong>FILES</strong></p> <p><strong>readme.txt</strong> -- this has the information from this description section</p> <p><strong>Norway_traits.csv</strong>, <strong>Finland_traits.csv</strong>, <strong>Germany_traits.csv</strong> -- these are the trait files, including all species</p> <p><strong>Norway_sites.species.csv</strong>, <strong>Finland_sites.species.csv</strong>, <strong>Germany_sites.species.csv</strong> -- this has species (rows) by sites (columns); values are the number of beetles caught (for number of traps, dates, and other site covariates, see related dataset: <a href="https://doi.org/10.5061/dryad.tmpg4f50b">https://doi.org/10.5061/dryad.tmpg4f50b</a> and manuscript: <a href="https://doi.org/10.1111/jbi.14272">https://doi.org/10.1111/jbi.14272</a>). Species names follow GBIF taxonomic backbone.</p> <p><strong>Traits_METADATA.csv</strong> -- this has information on all the fields in the trait data</p> <p> </p>
Bonanza Creek Experimental Forest Beetles Per Trap Beginning in 1975 - Kruse (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-bnz/504/7. The abstract below was extracted from the Level 0 data package and is included for context: This is a more detailed datafile then the previous method of reporting found in the datafile: Bonanza Creek Experimental Forest Bark Beetle Per Trap 1Begining in 1975 - Werner. Starting 2010 it contains counts of all woodboring insects and bark beetles caught in the pheromone baited traps, and retains information at the individual sample level.
Annotated checklist of the beetles of Abeti Soprani, a silver fir forest of Central Italy
<p>The checklist contains 179 species of beetles which belong to 48 families. The species were collected during a field study carried out in the years 2012 and 2013 and aimed at describing the beetles of the area. The collection methods consisted in window flight traps and emergence traps. The study area, named Abeti Soprani, is a silver fir (<em>Abies alba</em>) forest located in the Central Apennines.</p> <p>The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, geographic position, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015). </p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a></p> <p>Investigations on spatial patterns and diversity have been based on this dataset and published (Parisi et al. 2016, 2020).</p> <p>The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p>
Annotated checklist of the beetles of chestnut agroforestry systems in Aspromonte, Southern Italy
<p>The checklist contains 255 species of beetles which belong to 49 families. The species were collected during a field study carried out in the years 2017 and aimed at describing the community of beetles. The collection methods consisted of window flight traps. The study area included 3 sites, two coppice stands, young and mature (38.180221 N, 15.784308 E), and a traditional fruit orchard (38.06018 N, 15.781616 E), located in the Italian Southern Apennines on the borders of the Aspromonte National Park.</p> <p>The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, locality, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015). </p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a></p> <p>The Diversity of saproxylic beetle communities have been analysed and published (Parisi et al. 2020).</p> <p>The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p>
Annotated checklist of the beetles of beech forests in Matese National Park, Central Italy
<p>The checklist contains 165 species of beetles which belong to 37 families. The species were collected during a field study carried out in the year 2018 and aimed at describing the community of beetles. The collection methods consisted of window flight traps. The study activities were carried out in four distinct beech forest stands based on their altitude (High and Low) and exposure (South and North) and located in the Italian Central Apennines. The sites are included in the Natura 2000 site IT 7222287 “La Gallinola - Monte Miletto - Monti del Matese” and Matese National Park.</p> <p>The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, geographic position, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015). </p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a></p> <p>The discovery of a new species of beetle (Elateridae) for the Italian fauna was based on this dataset (Parisi et al., 2020).</p> <p>The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p>
Annotated checklist of the beetles of three beech forests in Gran Sasso National Park, Central Italy
<p>The checklist contains 163 species of beetles which belong to 36 families. The species were collected during a field study carried out in the years 2013 and 2016 and aimed at describing the community of beetles. The collection methods consisted of window flight traps and emergence traps. The study area included 3 beech forest sites, named Prati di Tivo (42.5096 N, 13.5679 E), Venacquaro (42.4988 N, 13.5139 E) and Incodara (42.5123 N, 13.4735 E) located in the Italian Central Apennines. The sites are included in the Natura 2000 site IT7110202 “Gran Sasso”.</p> <p>The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, locality, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015). </p> <p>The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a></p> <p>Investigations on stand structure and forest biodiversity (Sabatini et al. 2016) and faunistic analysis (Zanetti and Parisi 2019) have been based on this dataset.</p> <p>The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.</p>
Data from: Choosy beetles: how host trees and southern boreal forest naturalness may determine dead wood beetle communities
<p>See methods section of paper for detailed information on dataset and sources; briefly, these .csv files includes numbers of each beetle species captured at all sites used in the project, as well as information about each site and about each species.</p> <p> </p> <p>Data from:</p> <p><strong>Choosy beetles: how host trees and southern boreal forest naturalness may determine dead wood beetle communitie</strong><strong>s</strong></p> <p>Ryan C. Burner, Tone Birkemoe, Jörg G. Stephan, Lukas Drag, Jörg Muller, Otso Ovakainen, Mária Potterf, Olav Skarpaas, Tord Snall, Anne Sverdrup-Thygeson</p> <p>Forest Ecology and Management, 2021</p> <p> </p> <p>From abstract of paper:</p> <p>Wood-living beetles make up a large proportion of forest biodiversity, and contribute to important ecosystem services, including decomposition. Beetle communities in managed southern boreal forests are less species rich than in natural and near-natural forest stands. In addition, many beetle species rely primarily on specific tree species. Yet, the associations between individual beetle species, forest management category, and tree species are seldom quantified, even for red-listed beetles. We compiled a beetle capture dataset from flight intercept traps placed in Norway spruce (<em>Picea abies</em>), oak (<em>Quercus sp.</em>), and Eurasian aspen (<em>Populus tremulae</em>) trees in 413 sites in mature managed forest, near-natural forest, and clear-cuts in southeastern Norway. We used joint species distribution models to estimate the strength of associations for 368 saproxylic beetle species (including 20 vulnerable, endangered, or critical red-listed species) for each forest management category and tree species. Tree species on which traps were mounted had the largest effect on beetle communities; oaks had the most highly associated beetle species, including most of the red-listed species, followed by Norway spruce and Eurasian aspen. Most beetle species were more likely to be captured in near-natural than in mature managed forest. Our estimated associations were compatible – for many species – with categorical classifications found in several existing databases of saproxylic beetle preferences. These quantitative beetle-habitat associations will improve future analyses that have typically relied on categorical classifications. Our results highlight the need to prioritize conservation of near-natural forests and oak trees in Scandinavia to protect the habitat of many red-listed species in particular. Furthermore, we underline the importance of carefully considering the species of trees on which traps are mounted in order to representatively sample beetle communities in forest stands.</p>
Agonum sordidum, Fig_6 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum sordidum,</p> <p>Fig_6 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum rugicolle, Fig_5 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum rugicolle,</p> <p>Fig_5 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum_nigrum, Fig_4 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum_nigrum,</p> <p>Fig_4 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum_mesostictum, Fig_2 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum_mesostictum,</p> <p>Fig_2 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum monachum syriacum, Fig_3 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum monachum syriacum,</p> <p>Fig_3 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p>
Agonum_marginatum, Fig_1 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.
<p>New version as *png</p> <p>Agonum_marginatum,</p> <p>Fig_1 from Assmann et al. (2021) The ground beetle tribe Platynini Bonelli, 1810 (Coleoptera, Carabidae) in the southern Levant: dichotomous and interactive identification tools, ecological traits, and distribution.</p> <p> </p>
Ground beetle (Coleoptera:Carabidae) species composition of three forests in the Netherlands
<p>During this research the carabid fauna assemblage of two forests, the Amsterdamse Bos and Purmerendse Bos, was determined. Throughout the forests series (locations within the forests) were chosen to place pitfall traps. Each series consisted of five plastic cups that were dug into the soil in such a way that they were flush with the surface. Each cup was located five meters away from the subsequent one. The cups were filled with formaldehyde (diluted water 1: 10) as conservative and a small amount of soap in order to decrease water tension and thus let the organisms submerge. Afterwards the trap was covered with a wooden plate attached onto the soil with nails to protect it from rain and damage. The plates were covered up with plant material as camouflage. A small opening in between the soil and the plate was left so there was space for soil fauna to crawl into the cup (Picture 1). Because carabids are often dispersed throughout an area in small populations instead of being homologous spread (Raino & Niemelä, 2003) a diversity of locations was chosen. Therefore biotic and abiotic conditions were recorded (soil, light invasion, litter and dominant vegetation) to select the most diverse sites. </p> <p>Nine series in the Amsterdamse Bos and eleven series in the Purmerendse Bos were placed. These forests were sampled for a time span of 63 days. When traps were emptied the formaldehyde was refreshed. After the third time all of the traps were removed and holes filled up with soil. </p> <p>The content of emptied traps was washed with water and afterwards the ground beetles were selected and preserved in 95% ethanol. The ground beetles found were identified by making use of “De Loopkevers van Nederland & Vlaanderen” by Boeken, Desender, Drost, van Gijzen, Koese, Muilwijk, Turin & Vermeulen (2002. </p> <p>For each series the quantity of caught individuals was recorded. From the Eyserbos, data collected by supervisor B. Brugge in the years from 2012 to 2014 was used for analysis; during this research the same catching methods were used but the time scale was different. For four years, five series of pitfall traps were placed for one week halfway of June thus for a total of 28 days. Data of the species composition and the ecological characteristics and classification of the three forests was collected. Following classifications and ecological characters of the species that were used for analysis were documented: the status of the species in the Netherlands, Belgium, Denmark and Luxemburg, the status of the species in the Netherlands, the distribution in the Netherlands, how important the species’ population in the Netherlands is in its distribution in Europe (so called I-species), which type of habitats a species can migrate through to spread to other habitat patches, the classification of the species by Lindroth (1969), the degree of eurytopicity of the species and the flight capabilities of the species. </p> <p>Data obtained can be found in the file:</p> <p><strong>201703-05_groundbeetle_species_composition_Eyserbos_AmsterdamseBos_and_PurmerendseBos.txt</strong></p> <p>The possible inputs for characteristics can be found in the file</p> <p><strong>201706_Legenda_data_groundbeetles_species_composition_Amsterdamse_and_Purmerendse_bos.txt</strong></p>
Bark Beetle Behavioral Response to 4-Allylanisole
<p><strong>Experiment 1: </strong>Experiment 1 was established in May 2018 and was a dose response study that evaluated the behavioral response of southern pine beetle (<em>Dendroctonus frontalis</em>), black turpentine beetle (<em>Dendroctonus terebrans</em>), and clerid predator beetles (<em>Thanasimus dubius</em>) to 4-allylanisole when combined with bark beetle pheromone components and a demonstrated host-produced synergist (<em>alpha</em>-pinene). </p> <p>This experiment contained four different collection dates, four sites in Oconee National Forest in Georgia, four traps per site, and four different treatments/lure combinations.</p> <p>Treatments: 1) Control with pheromone components (frontalin and brevicomin) + <em>alpha</em>-pinene; 2) pheromone components + <em>alpha</em>-pinene + low release rate of 4-allylanisole (4.8 mg/day) (LOW4AA); 3) pheromone components + <em>alpha</em>-pinene + medium release rate of 4-allylanisole (48 mg/day) (MED4AA); and 4) pheromone components + <em>alpha</em>-pinene + high release rate of 4-allylanisole (500 mg/day) (HIGH4AA).</p> <p>Variables in data include date of collection (Date), date of collection with dummy codes for each of the four collection times (Time), collection site (Site), trap number (Trap), lure combination (Treatment), number of southern pine beetle (SPB), number of black turpentine beetles (BTB), and number of clerid predator beetles (Clerids).</p> <p> </p> <p><strong>Experiment 2: </strong>Experiment 2 was established in April 2019 and was a dose response study that assessed the capacity of 4-allylanisole to influence beetle response when combined with attractive bark beetle pheromone components in the absence of other host-produced odors.</p> <p>This experiment contained four different collection dates, four sites in Oconee National Forest in Georgia, four traps per site, and four different treatments/lure combinations.</p> <p>Treatments: 1) Control with only pheromone components (frontalin and brevicomin); 2) pheromone components + low release rate of 4-allylanisole (4.8 mg/day) (LOW4AA); 3) pheromone components + medium release rate of 4-allylanisole (48 mg/day) (MED4AA); and 4) pheromone components + high release rate of 4-allylanisole (500 mg/day) (HIGH4AA).</p> <p>Variables in data include date of collection (Date), date of collection with dummy codes for each of the four collection times (Time), collection site (Site), trap number (Trap), lure combination (Treatment), number of southern pine beetle (SPB), number of black turpentine beetles (BTB), and number of clerid predator beetles (Clerids).</p> <p> </p> <p><strong>Experiment 3: </strong>Experiment 3 assessed the efficacy of 4-allylanisole to enhance the standard lure for <em>D. frontalis </em>and whether the presence of <em>alpha</em>- and <em>beta-</em>pinene and 4-allylanisole simultaneously enhances attraction over either host odor component when present singly<em>. </em></p> <p>Treatments: 1) pheromone components (frontaline and <em>endo</em>-brevicomin (A); 2) pheromone components + 4-allylanisole (B); 3) pheromone components + <em>alpha-/beta-</em>pinene (C); 4) pheromone components + <em>alpha-/beta-</em>pinene + 4-allylanisole (D); 5) pheromone components + turpentine sock (E); and 6) pheromone components + turpentine + 4-allylanisole (F).</p> <p>Variable in the data include date of collection (Date), time of collection which is a dummy code for each collection date (Time), number of days before collection (Days), site (Block), trap number (Trap), lure combination (Treatment), number of male southern pine beetles (Male), number of female southern pine beetles (Female), number of southern pine beetles (SPB), and number of clerid predator beetles.</p> <p> </p> <p>Questions regarding this data can be e-mailed to hmunro@uga.edu.</p>
Supplementary videos for "A second fossil species of the enigmatic rove beetle genus Charhyphus in Eocene Baltic amber, with implications on the morphology of the female genitalia (Coleoptera: Staphylinidae: Phloeocharinae)"
<p><strong>Original figures used in this study:</strong></p> <p>The holotype of <em>Charhyphus serratus </em>sp. nov. and four extant <em>Charhyphus </em>species.</p> <p> </p> <p><strong>Supplementary Videos 1–3:</strong></p> <p><strong>Supplementary Videos 1</strong> <em>Charhyphus serratus </em>sp. nov., 001 DUBC, holotype, habitus, movie of X-ray micro-CT volume renderings.</p> <p><strong>Supplementary Videos 2</strong> <em>Charhyphus serratus </em>sp. nov., 001 DUBC, holotype, habitus, movie of X-ray micro-CT volume renderings using different parameters from Supplementary Videos 1.</p> <p><strong>Supplementary Videos 3</strong> <em>Charhyphus serratus </em>sp. nov., 001 DUBC, holotype, female genitalia, movie of X-ray micro-CT volume renderings.</p>
Spreadsheet Template for Body Length Data for North American Beetles
<p>Body size data for North American beetles extracted from The Insects and Arachnids of Canada:</p> <p>Anderson, R.S., Peck, S.B., 1985. The insects and arachnids of Canada, Part 13. The Carrion Beetles of Canada and Alaska: Coleoptera: Silphidae and Agyrtidae. Research Branch Agriculture Canada Publication 1778: 1-121.</p> <p>Bright, D.E., 1976. The insects and arachnids of Canada, Part 2. The bark beetles of Canada and Alaska: Coleoptera: Scolytidae. Research Branch Agriculture Canada Publication 1576: 1-241. </p> <p>Bright, D.E., 1987. The insects and arachnids of Canada, Part 15. The Metallic Wood-boring Beetles of Canada and Alaska. Coleoptera: Buprestidae. Research Branch Agriculture Canada Publication 1810: 1-335.</p> <p>Bright, D.E., 1993. The insects and arachnids of Canada, Part 21. The Weevils of Canada and Alaska: Volume 1. Coleoptera: Curculionoidea, excluding Scolytidae and Curculionidae. Research Branch Agriculture Canada Publication 1882: 1-217.</p>
Data from "Resource pulses drive spatio-temporal dynamics of non-native bark beetles and wood borers"
<p>This is a compilation of datasets that were used for the publication entitled "Resource pulses drive spatio-temporal dynamics of non-native bark beetles and wood borers" by Eckehard G. BROCKERHOFF, Stephanie L. SOPOW, and Martin K.-F. BADER, published in the Journal of Applied Ecology, 'in press' in October 2024.</p> <p>Note: The date format is either (i) season (spring/summer/autumn/winter) plus a two-figure short form for the year (e.g., "autumn08" stands for autumn 2008), or (ii) just the year for an annual total in either four- or two-figure form in the file name (e.g., "reg2010sums.csv" or "reg10sums.csv" for the year 2010).</p> <p>1. File "mean_trap_catches.csv" = Data used for Fig. 1 - Mean trap catch data of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus over time in Kaingaroa forest stands 378 ("F2006"), 377 ("F2009"), and 383 ("F2010"). For further explanations see methods of Brockerhoff et al. (2024).</p> <p>2. File "reg2010sums.csv" = Data used for Fig. 2 - Year 2010, annual trap catches of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus indicating approximate dispersal distances between Pinus radiata stands. For details see caption of Fig. 2 in Brockerhoff et al. (2024).</p> <p>3. File "reg2010sums.csv" = Data used for Fig. 2 - Year 2011, annual trap catches of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus indicating approximate dispersal distances between Pinus radiata stands. For details see caption of Fig. 2 in Brockerhoff et al. (2024).</p> <p>4. File "reg2010sums.csv" = Data used for Fig. 2 - Year 2012, annual trap catches of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus indicating approximate dispersal distances between Pinus radiata stands. For details see caption of Fig. 2 in Brockerhoff et al. (2024).</p> <p>5. File "reg10sums.csv" = Data used for Fig. 3 - Year 2010, annual trap catches of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus indicating approximate dispersal distances between Pinus radiata stands. For details see caption of Fig. 3 in Brockerhoff et al. (2024).</p> <p>6. File "reg11sums.csv" = Data used for Fig. 3 - Year 2011, annual trap catches of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus indicating approximate dispersal distances between Pinus radiata stands. For details see caption of Fig. 3 in Brockerhoff et al. (2024).</p> <p>7. File "reg12sums.csv" = Data used for Fig. 3 - Year 2012, annual trap catches of Hylastes ater, Hylurgus ligniperda and Arhopalus ferus indicating approximate dispersal distances between Pinus radiata stands. For details see caption of Fig. 3 in Brockerhoff et al. (2024).</p> <p>8. File "hylu2010-fitted_dispersal_to_5km-Version_23May2024.csv" = Data shown in Fig. 4 - Extension of the prediction range to 5 km of Hylurgus ligniperda dispersal data, using a generalised additive mixed model (GAMM) with beta distributed errors and the default logarithmic link. For details see caption of Fig. 4 and methods in Brockerhoff et al. (2024).</p> <p> </p>
Backyard Beetles and Pollinators Dataset - EREN/NEON Flexible Learning Project
<p>This dataset comes from the EREN-NEON flexible learning project 'Backyard Beetles and Pollinators.' It can be used for teaching field, computational, or hybrid courses. The dataset is standardized, visual observations of insect plant visitors, identified to standard functional groups, to indirectly assess pollination and construct plant-pollinator interaction networks. Insects were identified to morphospecies in the field using reference images. We also collected information about the flowers the insects were observed on - including functional type information about the color, size, and type of flower - as well as cover. This information is part of an ongoing course-based undergraduate research project to both teach about plants, insects, and functional biodiversity in a flexible and inclusive way - while collaboratively assessing interaction networks across landscapes and time. </p> <p>To use the flexible lesson materials or join the collaboration, get more information here: https://erenweb.org/eren-neon-flexible-learning-projects/ Or contact the project lead, Dr. Stack Whitney, directly at kxwsbi [at] RIT [dot] edu. </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.