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Data from: Flattening the curve: approaching complete sampling for diverse beetle communities
<p><strong>DATA FROM:</strong></p> <p>Burner, R., J. Åstrom, T. Birkemoe, A. Sverdrup-Thygeson. 2021. Flattening the curve: approaching complete sampling for diverse beetle communities. <em>Insect Conservation and Diversity</em> <a href="https://doi.org/10.1111/icad.12540">https://doi.org/10.1111/icad.12540</a> </p> <p> </p> <p><strong>ACKNOWLEDGEMENTS</strong></p> <p>This research was funded by the Norwegian Environment Directorate as part of an ‘Agreement on monitoring hollow oaks and insects in hollow oaks’. The Norwegian University of Life Sciences (NMBU) workshop designed and produced the cross-pane flight intercept traps. Thanks to Sindre Ligaard for identifying the beetle species, and to Lindsay Burner, Ruben Roos, and Ross Wetherbee for assistance in the field. High-performance computing resources were provided by Frederick H. Sheldon and Louisiana State University (LSU HPC).</p> <p><strong>INFORMATION</strong></p> <p>This dataset contains all data necessary to reproduce the analysis in the resulting manuscript. Briefly, 110 insect traps were set for 3 months in a single forest stand in Ås, Norway in 2020. This dataset includes trap locations, number of individuals of each species captured in each trap, trap type, and forest covariates collected around the traps.</p> <p>For more detailed information see manuscript and README file.</p> <p>From abstract of manuscript:</p> <ol> <li>Insects are a hyper diverse and ecologically important group. Their high diversity, however, presents challenges in sampling methodology, because rare species are unreliably detected with low sampling effort. However, the relationship between effort and species detections, critical for effective monitoring and evaluation of population trends, is too seldom quantified.</li> <li>We sampled forest beetles for three months in a 4-ha stand of mixed deciduous forest in southeastern Norway using 110 flight intercept (four types) and Malaise traps, the highest trap density (29 traps/ha) that we have seen reported. We examined species accumulation curves to quantify the benefits of each additional trap, compared capture rates among several trap designs and trap emptying frequencies, and tested for spatial autocorrelation.</li> <li>In total we captured 566 beetle taxa (19,854 individuals) from 52 families, yet our species accumulation curve was only beginning to flatten. Trap types differed considerably in their effectiveness. Nevertheless, twenty of our most effective window traps detected 75% of all taxa in our dataset. We found no evidence of spatial correlation within the scale of the study (100 m radius), nor did trap-level forest covariates (5 m radius) explain much variation.</li> <li>This implies that low to moderate sampling effort dramatically underestimates species richness, but that a limited number of effective traps can nonetheless achieve relatively thorough sampling for some applications. Immediate trap surroundings and spacing appeared unimportant. But, insect ecologists should take particular care in selecting trap types and be cautious comparing studies that employed different trap types.</li> </ol> <p> </p>
Simulation result from "Simulating Bark Beetle Outbreak Dynamics and their Influence on Carbon Balance Estimates with ORCHIDEE r7791"
<p>Eight locations were selected which represent the range of climatic conditions within the distribution area of spruce in Europe (<em>Picea Abies</em> Karst L.) as shown in Table 4. Half-hourly weather data from the FLUXNET database <a href="https://www.zotero.org/google-docs/?ibBw15">(Pastorello et al., 2020)</a> for these locations were used to drive ORCHIDEE. Some of these locations (FON, SOR, HES, COL, WET) are not populated with spruce but all are located within the species distribution. For each location, a pure spruce stand was simulated and the available FLUXNET data was looped to simulate a 100-year period. The study did not investigate the effect of species mixture in the simulation experiments. Other inputs, including soil texture, pH and soil color were obtained from the USDA map derived from <a href="https://www.zotero.org/google-docs/?aaWPI6">Eswaran et al. (2003</a>), for the corresponding pixel.</p> <p>The amount of fresh breeding woody substrate inputs used by the bark beetles to breed was controlled by modifying the maximum wind speed of a windthrow event in ORCHIDEE. Seven wind speeds ranging between 19 m/s and 40 m/s were selected (Table 3). This range is justified by the observation that mean wind speeds below 19 m/s could not trigger a windthrow event in ORCHIDEE <a href="https://www.zotero.org/google-docs/?jEqNDm">(Chen et al., 2018)</a> while for wind speeds exceeding 40 m/s, more than 60% of the trees are uprooted, leaving too few living trees to trigger a bark beetle outbreak within the same pixel. </p> <p>To investigate the impact of windthrow intensity and background climate on bark beetle outbreaks, the study conducted a total of 56 [8 sites x 7 wind speed intensities] simulations as given in table 3. The same 56 simulations were also used to analyze the sensitivity of the carbon balance of spruce forests to windthrow intensity and background climate.</p> <p>Where most land surface models use a turnover time to simulate continuous mortality <a href="https://www.zotero.org/google-docs/?5jGfXF">(Thurner et al., 2014; Pugh et al., 2019)</a>, ecological reality is better described by abrupt mortality events. An idealized simulation experiment was used to qualify the impact of abrupt mortality on net biome productivity by changing from a framework in which mortality is approximated by a constant background mortality to a framework in which mortality occurs in abrupt, discrete events. To test the impact of a change in mortality framework two versions of ORCHIDEE were compared to create an idealized simulation experiment: (1) a version simulating mortality as a continuous process, labeled ”the continuous version”, and (2) the version capable of simulating abrupt mortality from windthrow and subsequent bark beetle outbreaks, labeled ”the abrupt version”. The effect of simulating abrupt mortality was evaluated over 20-, 50-, and 100-year time horizons.</p> <p>The effect of changing the framework of simulating mortality from continuous to abrupt was qualified on the basis of 112 simulations (8 sites x 7 wind speeds x 2 model versions) of 100 years each. The simulations with abrupt mortality were run first. Subsequently, the number of trees killed was quantified and used as a reference value for the continuous mortality set-up. This approach resulted in the same quantities of dead trees at the end of the simulation for both frameworks, which then differed only in the timing of the simulated mortality. This precaution is necessary to avoid comparing two different mortality regimes where the result would mainly be explained by the intensity of the mortality rather than by its underlying mechanisms. </p>
Blair et al. 2020: Machine learning identification of ground beetles (repackaging of occurrences published by the NEON Biorepository Data Portal)
Blair, J.; Weiser, M. D.; Kaspari, M.; Miller, M.; Siler, C.; Marshall, K. E. 2020. Robust and simplified machine learning identification of pitfall trap-collected ground beetles at the continental scale. Ecology and Evolution 10 (23): 13143-13153. https://doi.org/10.1002/ece3.6905 Additional NEON samples (not yet archived at the Biorepository) were used in this research: full list of occurrences used.
Identified invertebrate bycatch from beetle pitfall traps at SJER and SOAP, 2017 - 2018 (repackaging of occurrences published by the NEON Biorepository Data Portal)
California permit requirements necessitated a more thorough identification of beetle pitfall samples than is typical of this protocol. These invertebrate bycatch samples therefore have occurrence associations that indicate their contents in both the NEON Biorepository and main NEON data portals. See NEON prototype dataset 9bc959c-148b-aaad-aa35-2d0805327428 available here.
Bonanza Creek Experimental Forest Beetles Per Trap Beginning in 1975 - Kruse (Reformatted to a Darwin Core Archive)
This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/251/2, which 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.
Bonanza Creek Experimental Forest Beetle Population Counts
Defoliating insect population levels for the Bonanza Creeek Experimental Forest for the Summers of 2001 - Present. The datafile has trap types, species counts... This is a more detailed datafile then the previous method of reporting found in the datafile: Bonanza Creek Experimental Forest Defoliating Insect Population Levels Per Trap: 1975 - 2002
Bonanza Creek Experimental Forest Beetles Per Trap 1975-2012 - Werner
Bark beetle population levels were monitored at Bonanza Creek Experimental Forest, Fairbanks, Alaska, USA from 1976 to 2012. The per trap total insect count is archived in this dataset for three common tree-killing species of bark beetle in Interior Alaska.
Trapping system for longhorn beetles at the Coweeta Hydrologic Laboratory from 2000 to 2003
This was a pheromone trapping experiment for bark and wood boring beetles. The study attempts to develop an efficient trapping system for the detection and monitoring of exotic bark and wood boring beetles, particularly longhorn beetles (Cerambycidae). It was conducted from 12 May 2003 to 30 July 2003 in mature white pine stand with lots of tree mortality to southern pine beetle, Dendroctonus frontalis. There were four replicates of eight treatments set in RBD with four replicates at each of two sites. Treatments involved funnel traps baited with combinations of three common bark beetle pheromones: lanierone, ipsenol and ipsdienol. The objective is to use areas in the south with substantial populations of native beetles to develop a generic trap for large wood borers before attempting trials in areas such as China and Russia. Several types of intercept traps will be tested with various host compounds such as ethanol and alpha-pinene.
Herb coverage on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2001 to 2003
Percent cover of herb layer species was compared between beetle-impacted and non-beetle-impacted white pine plots in watershed 1.
Seedling regeneration density on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2001 to 2003
Seedling density was compared between beetle-impacted and non-beetle-impacted white pine plots on watershed 1.
Photosynthetically active radiation (PAR) on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2002 to 2003
Light availability (photosynthetically active radiation, PAR) was compared between beetle-impacted and non-beetle-impacted white pine plots watershed 1.
Percent soil moisture on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2002 to 2003
Soil moisture was compared between beetle-impacted and non-beetle-impacted white pine plots in watershed 1.
Supplementary materials (Allometry and fighting behaviour of a dimorphic stag beetle Cyclommatus miniszechi (Coleoptera: Lucanidae))
<p><strong>Supplementary Materials:</strong></p> <p><strong>Table S1.</strong> The morphological measurements of males of <em>Cyclommatus mniszechi</em> used for allometry analyses.</p> <p><strong>Table S2. </strong>The behavioural sequence data used for sequential analyses of size-matched contests in major males of <em>Cyclommatus mniszechi</em>.</p> <p><strong>Table S3. </strong>The behavioural sequence data used for sequential analyses of size-matched contests in minor males of <em>Cyclommatus mniszechi</em>.</p> <p><strong>Video S1.</strong> The behavioural sequence of males of <em>Cyclommatus mniszechi</em> in fighting contests under the laboratory setups. One of the opponents walked to the other and touched it (00:07), and then both of them displayed ‘defensive posture’ (00:08) after ‘touch’. Once both individuals approached each other, they accelerated antennation and raised their mandibles and prothoracic parts. The contest then progressed into ‘body raising’ (00:14). They then performed ‘attack’ and ‘push’ to each other several times and then escalated to ‘tussle’ (00:20) and interlocked their mandibles until one of the contestants was clamped (‘clamp1’) in the air by the other for a second and flipped (00:50). The winner dropped the loser and kept attacking and pushing the loser while the loser retreated and moved backwards (00:51).</p>
Fig. 29 in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 29. Current distribution of Streblopus van Lansberge, 1874 and the Old World groups with which it is believed to be more closely related plotted on an Upper Cretaceous palaeomap (~ 80 million years ago). Based particularly on the hypothesis in Tarasov & Génier (2015) that Streblopus is part of a clade otherwise composed uniquely of dung beetle lineages either exclusively distributed in Africa (Circellium, Chalconotus and Gyronotus) or with a distribution largely centred on that continent (Scarabaeini), and on the dating of the origin of the Scarabaeini as 71 million years ago (Gunter et al. 2016), we propose that the lineage that would eventually lead to Streblopus branched off from those groups in Africa some time between 95 and 71 million years ago, and that one of its descendent lineages (the only one living today) dispersed from its original continent to South America during the late Upper Cretaceous or the early Cenozoic. Since Africa and South America have not been connected by land since the Lower Cretaceous, the only way the ancestor of Streblopus could have reached South America was through transoceanic dispersal across the early South Atlantic. That dispersal probably happened by rafting on floating pieces of plants or other debris, as probably occurred with a large number of other organisms. Palaeomap modified from Scotese (2016); distribution area based on Balthasar (1963), Scholtz & Howden (1987), Davis et al. (2008) and our own results.
Fig. 14. Profemora. A‒B. Streblopus opatroides van Lansberge, 1874. A in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 14. Profemora. A‒B. Streblopus opatroides van Lansberge, 1874. A. ♂. B. ♀. C‒D. S. punctatus (Balthasar, 1938). C. ♂. D. ♀. Note the differences between the species and sexes in relation to the overall shape of the profemora and the presence of spurs on the anterior edge in males.
Fig. 12. Pronotum. A. Streblopus opatroides van Lansberge, 1874. B. S in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 12. Pronotum. A. Streblopus opatroides van Lansberge, 1874. B. S. punctatus (Balthasar, 1938). Note the differences in the umbilicate punctation and colour between the species.
Fig. 1. Streblopus opatroides van Lansberge, 1874. A‒B. Ordinary specimens, dorsal view. A in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 1. Streblopus opatroides van Lansberge, 1874. A‒B. Ordinary specimens, dorsal view. A. ♂. B. ♀. C‒D. Lectotype, ♂. C. Dorsal view. D. Attached labels.
Fig. 3 in Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)
Fig. 3. Streblopus punctatus (Balthasar, 1938). A‒B. Holotype, ♀. A. Dorsal view. B. Attached labels. C‒D. Ordinary specimens, dorsal view. C. ♂. D. ♀.
Figures 7–13. Jansenia myanmarensis Wiesner, 2004. 7 in Two new tiger beetle species (Coleoptera: Cicindelidae) from Myanmar and notes on another species. 151. Contribution towards the knowledge of the Cicindelidae
Figures 7–13. Jansenia myanmarensis Wiesner, 2004. 7) Habitus, male, scale = 5 mm. 8–9. Labrum, scale = 1 mm. 8) Male. 9) Female. 10–12. Left elytron, scale = 2 mm. 10) Male. 11) Female. 12) Paratype female. 13) Left lateral view of aedeagus, scale = 1 mm.
Figures 1–4. Fossil elateroids. 1 in Descriptions of two new elateroid beetles (Coleoptera: Eucnemidae, Elateridae) from Burmese amber
Figures 1–4. Fossil elateroids. 1) Cenomana clavata holotype, dorsal habitus. 2) Cenomana clavata holotype, ventral habitus. 3) Cretopityobius pankowskiorum holotype, dorsal habitus. 4) Cretopityobius pankowskiorum holotype, ventral habitus. (Scale: 1–4 = 1.0 mm)
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