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Transcriptomic analysis of deceptively pollinated Arum maculatum (Araceae) reveals association between terpene synthase expression in floral trap chamber and species-specific pollinator attraction
<p>A compressed folder containing the R script and input files required to replicate the results in our manuscript entitled "Transcriptomic analysis of deceptively pollinated <em>Arum maculatum</em> (Araceae) reveals association between terpene synthase expression in floral trap chamber and species-specific pollinator attraction".</p> <p>Note: Raw Illumina sequencing files associated with this study have been uploaded to NCBI SRA, under the BioProject accession PRJNA856436.</p> <p><strong>ABSTRACT</strong></p> <p>Deceptive pollination often involves volatile organic compound (VOC) emissions that mislead insects into performing non-rewarding pollination. Among deceptively pollinated plants, <em>Arum maculatum</em> is particularly well-known for its potent dung-like VOC emissions and specialized floral chamber, which traps pollinators – mainly <em>Psychoda phalaenoides</em>and <em>P. grisescens</em> – overnight. However, little is known about the genes underlying the production of many <em>A. maculatum</em>VOCs, and their influence on variation in pollinator attraction rates. Therefore, we performed <em>de novo</em> transcriptome sequencing of <em>A. maculatum</em> appendix and male floret tissue collected during- and post-anthesis, from ten natural populations across Europe. These RNA-seq data were paired with GC-MS analyses of floral scent composition and pollinator data collected from the same inflorescences. Differential expression analyses revealed candidate transcripts in appendix tissue linked to malodourous VOCs including indole, <em>p</em>-cresol, and 2-heptanone. Additionally, we found that terpene synthase expression in male floret tissue during anthesis significantly covaried with sex- and species-specific attraction of <em>Psychoda phalaenoides</em> and <em>P.</em> <em>grisescens</em>. Taken together, our results provide the first insights into molecular mechanisms underlying pollinator attraction patterns in <em>A. maculatum</em>, and highlight floral chamber sesquiterpene (<em>e.g.</em>bicyclogermacrene) synthases as interesting candidate genes for further study.</p>
Catches of numerous insect species in Rothamsted 160W light trap at Devonport, Tasmania, 1992-2019
<p>These data derive from decades of near-continuous (1992 - 2019, apart from 2008 and 2009) operation of a 160W Rothamsted-design light trap at Stony Rise Centre, Devonport, Tasmania, Australia. Stony Rise was the last of several long term, continuous trapping sites operated over this period by the Tasmanian state agricultural agency, currently known as the Department of Natural Resources and Environment Tasmania.</p> <p>The light was normally operated every night, with all individuals of selected taxa counted. There were 5433 trapping events covering 7897 nights including 4167 single-night events, 502 two-night events, 516 three-night events and 165 four-night events. The remaining 83 events were variously 5-14 nights duration. There were 194 sporadic nights when the trap malfunctioned, which is about 2.5% of 7897 nights in the main trapping periods. The trap did not operate for extended periods (3-6 months) in early 1996, early 1998, all of 2007, all of 2008, all of 2009, early 2010 and late 2015. Enumeration of catches ceased on 6 February 2019. A total of 222,146 specimens were identified and enumerated for the data set.</p> <p><strong>Dataset</strong></p> <p>The initial focus of the trapping was on Noctuidae and insect species of economic importance for Tasmanian agriculture. The taxa selected for identification and counts grew from 104 taxa in 1992 to 273 taxa in 2019. Consequently, absence of some species from early samples should not be considered to indicate absence of these species. During periods in which any species was included in counts, a record is always included for the species in question, with a count of zero if no individuals were detected. During periods in which the species was not included in counts, no record is included for the species and period in question. Hence zero counts can always be considered to represent true absence within the sample of identified insects.</p> <p>An explanation of the survey work leading to this dataset and an overview of species included was published in Hill, L., 2013b, Long-term light trap data from Tasmania, Australia, Plant Protection Quarterly Vol.28(1) (<a href="https://www.researchgate.net/publication/274700470_Long-term_light_trap_data_from_Tasmania_Australia">https://www.researchgate.net/publication/274700470_Long-term_light_trap_data_from_Tasmania_Australia</a>).</p> <p>The bibliography lists publications derived from analysis of these data.</p> <p><strong>Purpose</strong></p> <p>The focus was on prognosis of Persectania ewingii Westwood, southern armyworm and several other noctuid pests such as Helicoverpa punctigera (Wallengren), native budworm and Agrotis species, true cutworms, which were all subsequently shown to undertake substantial annual immigration from mainland Australia to Tasmania across Bass Strait (Drake et al. 1981, Hill 1993, Hill 2007a). The reliability of using light trap catches to forecast larval outbreaks of southern armyworm was determined empirically since 1953 (Hill, L. 2013c). A history of forecasting outbreaks of the southern armyworm, Persectania ewingii (Lepidoptera: Noctuidae) in Tasmania. Plant Protection Quarterly Vol.28(1), 15-21. Many frequent or infrequent vagrant Lepidoptera and other taxa were detected and the status of some of these was asserted in scientific publications (Hill 2011a, 2012a, 2013d, 2014, 2015, 2016a, 2016b, 2017). Sex ratio data for 38 species of Noctuidae was collected but is not provided in this dataset. Data from similar traps at other Tasmanian sites, back to 1953 for a few species, as described by Hill (2013c) is held variously in hardcopy format by the Department of Natural Resources and Environment Tasmania. It is available on request.</p> <p><strong>Temporal scope</strong></p> <p>January 1, 1992 - February 6, 2019</p> <p><strong>Geographic scope</strong></p> <p>Stony Rise Centre, Devonport, Tasmania, Australia </p> <p><strong>Taxonomic scope</strong></p> <p>227 species or higher taxa of Lepidoptera, representing about 30 families. 7 taxa of Coleoptera, representing 2 families. 6 taxa of Diptera representing 6 families. 12 taxa of Hemiptera representing 6 families. 3 taxa of Hymenoptera representing 1 family. 16 taxa of Neuroptera representing 5 families. 1 taxon of Blattodea. 1 taxon of Orthoptera.</p> <p><strong>Methodology</strong></p> <p><em>Study extent</em></p> <p>The light trap was installed at Stony Rise Centre (government offices), 1 Rundle Street, Devonport, Tasmania (146.32 E, 41.18 S).</p> <p><em>Sampling</em></p> <p>The trap was similar to the Rothamsted-design traps operated in the United Kingdom, consisting of a clear glass or Perspex, truncated pyramid of 52 cm square base, 22 cm height and 12 cm top aperture surrounding a square, glass funnel of slightly lesser height with 20 cm top aperture and 4 cm bottom aperture. This was mounted on a wooden base-board about 1.3 m above ground under a ridged, steel roof. A 160 W mercury vapour bulb was suspended within the funnel from the ceiling of the roof cavity, in which a clock switch was fitted. Clearance between the top aperture of the funnel and the ceiling of the roof was about 4 cm. The catch was collected into a single 10 cm square glass jar with a plaster of Paris floor bearing tetrachlorethane killing fluid and with a 9 cm orifice screwed to the underside of the baseboard. This jar contained a piece of crumpled paper towel to reduce rubbing of specimens. In December 2015 the trap was rebuilt in stainless steel to the same dimensions and using the original collection pyramid and funnel. The clock switch was replaced by a light sensitive switch.</p> <p><em>Quality control</em></p> <p>Only selected insect species were sorted and identified, counted and written into a data file. Some insects were only sorted and counted using supraspecific ranks. The range of included species grew over the period. Records for each interval exclude taxa which were not sorted or identified during the period in question. Hence zero counts indicate absence of the insects concerned during a trapping period.</p> <p><em>Method steps</em></p> <ol> <li> <p>In the study, all individual records of selected target insect species were collected, identified to species level and counted yielding qualitative (species) and quantitative (number of individuals within each species) data for the entire study period. The recorded taxa are listed in taxon.csv in this dataset, along with summary information on the first and last events during which the taxon was monitored, the number of events in which the taxon could have been detected, the actual number in which it was detected, the total number of individuals detected, and the number of individuals detected in each year from 1992 to 2019 and in each month of the year.</p> </li> <li> <p>All handling and identification of material was carried out consistently throughout the entire period by the same researcher.</p> </li> <li> <p>Over 9000 specimens in several hundred taxa from this light trap are preserved in the Tasmanian Agricultural Insect Collection, Hobart, Tasmania (<a href="https://collections.ala.org.au/public/show/co131">https://collections.ala.org.au/public/show/co131</a>). Note specimen records are not included in this dataset. Images of representative specimens of most recorded taxa are included in the image subfolder and listed in image.csv. For insects identified only to genus or higher, it should not be assumed that all records over the period matched the species illustrated.</p> </li> <li> <p>The data were prepared for publication as a Darwin Core sampling event dataset via a series of transformations within Excel and comprises the following CSV files: event.csv (Darwin Core sampling event records) and occurrence.csv (Darwin Core occurrence records linked to event.csv by eventID). Two other CSV files are included but not mapped through the Darwin Core Archive meta.xml. First, image.csv lists images of example specimens of many of the taxa recorded in the dataset. These images are included in the image folder. Secondly, taxon.csv summarises the taxa referenced within occurrence.csv, cross-references the images as associatedMedia and provides summary counts for the number of individuals of each taxon recorded in each year of the study and in each calendar month through the period.</p> </li> </ol> <p><strong>Bibliography</strong></p> <ol> <li> <p>Drake et al. 1981. Insect migration across Bass Strait during spring: a radar study. Bulletin of Entomological Research 71, 449-66. https://doi.org/10.1017/S0007485300008476</p> </li> <li> <p>Hill 1993. Colour in adult Helicoverpa punctigera Wallengren (Lepidoptera: Noctuidae) as an indicator of migratory origin. Journal of the Australian Entomological Society 32, 145-51. https://doi.org/10.1111/j.1440-6055.1993.tb00563.x</p> </li> <li> <p>Hill 2007a. Agrotis (Lepidoptera: Noctuidae) species in Tasmania including montane, summer aestivation of the bogong moth, Agrotis infusa (Boisduval, 1832). Victorian Entomologist 37(1), 3-9. https://www.researchgate.net/publication/274700557</p> </li> <li> <p>Hill 2007b. The chevron cutworm, Diarsia intermixta in Tasmania. Victorian Entomologist 37(5), 68-76. https://www.researchgate.net/publication/274700503</p> </li> <li> <p>Hill 2011a. The Pacific damsel bug, Nabis kinbergii in Tasmania. Victorian Entomologist 41(5), 99-107. https://www.researchgate.net/publication/274700561</p> </li> <li> <p>Hill 2011b. The heliotrope moth, Utetheisa pulchelloides in Tasmania. Victoria Entomologist 41(4), 69-73. https://www.researchgate.net/publication/274700401</p> </li> <li> <p>Hill 2011c. Continual migration across Bass Strait? Victorian Entomologist 41(6), 117-22. https://www.researchgate.net/publication/274700626.</p> </li> <li> <p>Hill 2012a. Cabbage-centre grub Hellula hydralis, not resident in Tasmania. Plant Protection Quarterly 27(3), 91-100. https://www.researchgate.net/publication/274700462</p> </li> <li> <p>Hill 2012b. The brown lacewing, Micromus tasmaniae in Tasmania: Part 1. Victorian Entomologist 42(5), 94-101. https://www.researchgate.net/publication/274700563.</p> </li> <li> <p>Hill 2012c. The brown lacewing, Micromus tasmaniae in Tasmania: Part 2. Victorian Entomologist 42(6), 115-20. https://www.researchgate.net/publication/274700504</p> </li> <li> <p>Hill 2013a. A history of forecasting outbreaks of the southern armyworm, Persectania ewingii (Lepidoptera: Noctuidae) in Tasmania. Plant Protection Quarterly Vol.28(1), 15-21. https://www.researchgate.net/publication/274700550</p> </li> <li> <p>Hill 2013b. Long-term light trap data from Tasmania, Australia. Plant Protection Quarterly Vol.28(1), 22-27. https://www.researchgate.net/publication/274700470.</p> </li> <li> <p>Hill 2013c. The common armyworm, Mythimna convecta (Walker) (Noctuidae:Lepidoptera), a seasonal resident in Tasmania. Plant Protection Quarterly Vol.28(4), 114-119. https://www.researchgate.net/publication/274700391</p> </li> <li> <p>Hill 2013d. Earias moths, rare vagrants in Tasmania. Victorian Entomologist 43(2), 40-43. https://www.researchgate.net/publication/274700577.</p> </li> <li> <p>Hill 2013e. Australia painted lady butterflies light-trapped in Tasmania. Victorian Entomologist 43(4), 76-81. https://www.researchgate.net/publication/274700637</p> </li> <li> <p>Hill 2013f. The satin moth, Thalaina selenaea in Tasmania. Victorian Entomologist 43(5), 106-111. https://www.researchgate.net/publication/274700628</p> </li> <li> <p>Hill 2014. Lesser armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), a vagrant moth in Tasmania. Plant Protection Quarterly Vol.29(4), 131-142. https://www.researchgate.net/publication/274700387</p> </li> <li> <p>Hill 2015. Eggfruit caterpillar, Sceliodes cordalis (Doubleday) (Lepidoptera: Pyralidae), a vagrant moth and indicator for likelihood of Queensland fruit fly establishment in Tasmania? Plant Protection Quarterly Vol.30(1), 27-39. https://www.researchgate.net/publication/311950878.</p> </li> <li> <p>Hill 2016a. An extreme rain event brings two vagrant moths to Tasmania. Victorian Entomologist 46(4), 88-89. https://www.researchgate.net/publication/311951473.</p> </li> <li> <p>Hill 2016b. Meyrickella ruptellus (Noctuidae: Hypeninae), a rare vagrant in Tasmania. Victorian Entomologist 46(3), 60-66. https://www.researchgate.net/publication/311950973</p> </li> <li> <p>Hill 2017. Migration of green mirid, Creontiades dilutus (Stål) and residence of potato bug, Closterotomus norwegicus (Gmelin) in Tasmania (Hemiptera: Miridae: Mirinae: Mirini). Crop Protection 96(2017), 211-220. https://doi.org/10.1016/j.cropro.2017.02.006</p> </li> </ol>
Dataset to "Hydrogen induced trap states in TiO2 probed by resonant X-ray photoemission"
<p>Dataset to "Hydrogen induced trap states in TiO2 probed by resonant X-ray photoemission" as published in Proceedings of the International Conference on X-Ray Lasers 2020</p>
Data from: Pitcher geometry facilitates extrinsically powered 'springboard trapping' in carnivorous Nepenthes gracilis pitcher plants
<div> <p>Carnivorous pitcher plants capture insects in cup-shaped leaves that function as motionless pitfall traps. <em>Nepenthes gracilis</em>, evolved a unique 'springboard' trapping mechanism that exploits the impact energy of falling raindrops to actuate a fast pivoting motion of the canopy-like pitcher lid. We superimposed multiple computerized micro-tomography images of the same pitcher to reveal distinct deformation patterns in lid-trapping <em>N. gracilis</em> and closely related pitfall-trapping <em>N. rafflesiana</em>. We found prominent differences between downward and upward lid displacement in <em>N. gracilis </em>only. Downward displacement was characterised by bending in two distinct deformation zones while upward displacement was accomplished by evenly distributed straightening of the entire upper rear section of the pitcher. This suggests an anisotropic impact response, which may help to maximize initial jerk forces for prey capture, as well as the subsequent damping of the oscillation. Our results point to a key role of pitcher geometry for effective 'springboard' trapping in <em>N. gracilis</em>.</p> </div>
Yellow Glue Paper Traps Dataset
<p>Color images are captured by pheromone traps installed at multiple locations in a field with vegetable crops (tomato) at Volos, Greece by a commercial provider of pheromone-based pest control solutions. The pheromone attracted the pest of interest into the trap where they became stuck to the adhesive surface. A digital camera (Svpro 13MP, sensor: Sony 1/3” IMX213) was used to capture the trapped insects. The resolution of images taken was 3840x2160. The working distance was set to 20 cm based on the camera specifications, in order to obtain a large enough field of view to capture the whole adhesive board trap. Using that equipment, 225 images were captured in indoor and outdoor conditions and chosen to represent the insect variability. </p> <p>For image annotation, Roboflow was used. The annotation process aims to label the location and class of the insect pests in the image. Roboflow was chosen because it can generate various annotations formats for different object detection models. The whole process was carried out by an experienced entomologist. Two insects were labelled, whiteflies, and black aphids. In total 5904 insect instances were labelled, out of which 2431 are whiteflies and 3473 are black aphids. Note that there are 26.24 annotations per image at average across the two classes.</p> <p>For validating the Yellow Glue Paper Traps Dataset, we split the whole images into training and validation subsets. In total, the dataset was split into 180 images for training and 45 for validation with 80-20% proportion. The split was chosen so as to keep a similar ratio and the classes which would ensure same distribution to training and validation subsets. The insect count in each subset can be seen in the following table:</p> <table align="center"> <caption>Dataset splits insect counts</caption> <thead> <tr> <th scope="col"><strong>Dataset split</strong></th> <th scope="col"><strong>Images</strong></th> <th scope="col"><strong>Insect Instances</strong></th> <th scope="col"><strong>Whiteflies</strong></th> <th scope="col"><strong>Black Aphids</strong></th> </tr> </thead> <tbody> <tr> <td>Training</td> <td>180</td> <td>4773</td> <td>1926</td> <td>2847</td> </tr> <tr> <td>Validation</td> <td>45</td> <td>1131</td> <td>505</td> <td>626</td> </tr> <tr> <td>Total</td> <td>225</td> <td>5904</td> <td>2431</td> <td>3473</td> </tr> </tbody> </table> <p> </p>
Fig. 1 in Yearly and seasonal changes in species composition of hornets (Hymenoptera: Vespidae) caught with bait traps on the Sea of Japan coast
Fig. 1. Yearly changes in the species composition of hornets in Sakata Park (A) and campus of Niigata University (B).
Data for "High-accuracy determination of Paul-trap stability parameters for electric-quadrupole-shift prediction", J. Appl. Phys. 132, 124401 (2022)
<p>Data required to reproduce the key results in: "High-accuracy determination of Paul-trap stability parameters for electric-quadrupole-shift prediction", J. Appl. Phys. <strong>132</strong>, 124401 (2022). <a href="https://doi.org/10.1063/5.0106633">https://doi.org/10.1063/5.0106633</a></p> <ul> <li>The file "sec_freq.dat" contains measured secular frequencies, the rf frequency, the applied bias voltages, and the MJD of the measurement: <ul> <li>Figures 4-5 use rows 31-33 of this data.</li> <li>Figure 6 uses all data corresponding to -1.1e-3 < <em>a</em><sub>x</sub> < -0.6e-3.</li> <li>Figure 7(a) uses all the data.</li> </ul> </li> <li>The file "data2021-12-21_MJD.txt" contains the secular frequency data used to derive Eq. (16) and plot Figure 8.</li> <li>The file "RF_monitor_rectifier_1d.txt" contains the rectified monitor voltage used in Figure 8.</li> <li>The file "Temperature_108_1d.txt" contains the helical-resonator temperature used in Figure 8.</li> <li>The file "Fig9_EQS.dat" contains the measured electric quadrupole shift (EQS) used for Figure 9.</li> <li>The file "interleavedEQS.dat" contains the data from the interleaved EQS measurement used to determine a lower value of 1070 for the cancellation factor.</li> </ul>
Data from: Protection status, human disturbance, snow cover and trapping drive density of a declining wolverine population in the Canadian Rocky Mountains
<p>Protected areas are important in species conservation, but high rates of human-caused mortality outside their borders and increasing popularity for recreation can negatively affect wildlife populations. We quantified wolverine (<em>Gulo gulo</em>) population trends from 2011 to 2020 in >14 000 km2 protected and non-protected habitat in southwestern Canada. We conducted wolverine and multi-species surveys using non-invasive DNA and remote camera-based methods. We developed Bayesian integrated models combining spatial capture-recapture data of marked and unmarked individuals with occupancy data. Wolverine density and occupancy declined by 39 percent, with an annual population growth rate of 0.925. Density within protected areas was 3 times higher than outside and declined between 2011 (3.6 wolverines/1000 km2) and 2020 (2.1 wolverines/1000 km2). Wolverine density and detection probability increased with snow cover and decreased near development. Detection probability also decreased with human recreational activity. The annual harvest rate of 13% was above the maximum sustainable rate. We conclude that humans negatively affected the population through direct mortality, sub-lethal effects and habitat impacts. Our study exemplifies the need to monitor population trends for species at risk – within and between protected areas - as steep declines can occur unnoticed if key conservation concerns are not identified and addressed.</p>
Data and code for article "Nature reserve customized method of photo and video camera traps materials processing using two-stage neural network approach"
<p><strong>DESCRIPTION</strong> 📓</p> <p>"data" folder directory contains the datasets for classification and detection. </p> <ol> <li>The detection dataset has <strong>YOLOv5 format</strong> and contains three classes <strong>[tigers, leopards, empty]</strong>. The class empty is about <strong>10%</strong> of the total data. The leopard and tiger classes contain <strong>3500</strong> images each. The entire amount of data for the detection task is <strong>7600</strong> images.</li> <li>The classification dataset contains two classes <strong>[tigers, leopards]</strong>. Images for classification are cropped images from the detection task using bounding boxes. Each class has <strong>3500</strong> images</li> </ol> <p> </p> <p>The "weights" folder contains pretrained models for classification and detection tasks. </p> <ul> <li>The detector weights were pre-trained on <strong>231k</strong> images from camera traps located throughout Russia.</li> <li>The classifier weights were pre-trained on <strong>416k</strong> images that were cropped with <strong>bounding boxes</strong> from photographs for the detection task. Some of the images for the classification task were taken from the <strong>Internet</strong>. The classifiers were trained for <strong>29 classes</strong>.</li> <li>You can also find folder <strong>tigers_vs_leopards</strong> in both the detection and classification directory, where there are weights that have been trained on a part of the camera trap images available at the link below.</li> </ul> <p><em>Classification weights</em></p> <ol> <li>EfficientNetv2-M</li> <li><strong>ResNeSt-101e</strong> (🚀 RECOMMENDED)</li> <li>ResNet-101d</li> <li>ReXnet-100</li> <li>SeResNet-152d</li> </ol> <p><em>Detection weights</em></p> <ol> <li>YOLOR-W6-1280</li> <li>YOLOX-X-640</li> <li>YOLOv5-X-640</li> <li>YOLOv5-X-1280</li> <li>YOLOv5-M6-1280</li> <li><strong>YOLOv5-L6-1280</strong> (🚀 RECOMMENDED)</li> </ol> <p>Read README.md file for more details</p>
Simulation Data & R scripts for: "Introducing recurrent events analyses to assess species interactions based on camera trap data: a comparison with time-to-first-event approaches"
<p><strong>Files descriptions:</strong></p> <p>All csv files refer to results from the different models (PAMM, AARs, Linear models, MRPPs) on each iteration of the simulation. One row being one iteration. <br>"results_perfect_detection.csv" refers to the results from the first simulation part with all the observations.<br>"results_imperfect_detection.csv" refers to the results from the first simulation part with randomly thinned observations to mimick imperfect detection.</p> <p>ID_run: identified of the iteration (N: number of sites, D_AB: duration of the effect of A on B, D_BA: duration of the effect of B on A, AB: effect of A on B, BA: effect of B on A, Se: seed number of the iteration).<br>PAMM30: p-value of the PAMM running on the 30-days survey.<br>PAMM7: p-value of the PAMM running on the 7-days survey.<br>AAR1: ratio value for the Avoidance-Attraction-Ratio calculating AB/BA.<br>AAR2: ratio value for the Avoidance-Attraction-Ratio calculating BAB/BB.<br>Harmsen_P: p-value from the linear model with interaction Species1*Species2 from Harmsen et al. (2009).<br>Niedballa_P: p-value from the linear model comparing AB to BA (Niedballa et al. 2021).<br>Karanth_permA: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species A (Karanth et al. 2017).<br>MurphyAB_permA: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>MurphyBA_permA: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>Karanth_permB: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species B (Karanth et al. 2017).<br>MurphyAB_permB: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br>MurphyBA_permB: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br> </p> <p>"results_int_dir_perf_det.csv" refers to the results from the second simulation part, with all the observations.<br>"results_int_dir_imperf_det.csv" refers to the results from the second simulation part, with randomly thinned observations to mimick imperfect detection.<br>ID_run: identified of the iteration (N: number of sites, D_AB: duration of the effect of A on B, D_BA: duration of the effect of B on A, AB: effect of A on B, BA: effect of B on A, Se: seed number of the iteration).<br>p_pamm7_AB: p-value of the PAMM running on the 7-days survey testing for the effect of A on B.<br>p_pamm7_AB: p-value of the PAMM running on the 7-days survey testing for the effect of B on A.<br>AAR1: ratio value for the Avoidance-Attraction-Ratio calculating AB/BA.<br>AAR2_BAB: ratio value for the Avoidance-Attraction-Ratio calculating BAB/BB.<br>AAR2_ABA: ratio value for the Avoidance-Attraction-Ratio calculating ABA/AA.<br>Harmsen_P: p-value from the linear model with interaction Species1*Species2 from Harmsen et al. (2009).<br>Niedballa_P: p-value from the linear model comparing AB to BA (Niedballa et al. 2021).<br>Karanth_permA: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species A (Karanth et al. 2017).<br>MurphyAB_permA: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>MurphyBA_permA: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>Karanth_permB: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species B (Karanth et al. 2017).<br>MurphyAB_permB: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br>MurphyBA_permB: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br> </p> <p><strong>Scripts files description:</strong><br>1_Functions: R script containing the functions:<br> - MRPP from Karanth et al. (2017) adapted here for time efficiency.<br> - MRPP from Murphy et al. (2021) adapted here for time efficiency.<br> - Version of the ct_to_recurrent() function from the recurrent package adapted to process parallized on the simulation datasets.<br> - The simulation() function used to simulate two species observations with reciprocal effect on each other.<br>2_Simulations: R script containing the parameters definitions for all iterations (for the two parts of the simulations), the simulation paralellization and the random thinning mimicking imperfect detection.<br>3_Approaches comparison: R script containing the fit of the different models tested on the simulated data.<br>3_1_Real data comparison: R script containing the fit of the different models tested on the real data example from Murphy et al. 2021.<br>4_Graphs: R script containing the code for plotting results from the simulation part and appendices.<br>5_1_Appendix - Check for similarity between codes for Karanth et al 2017 method: R script containing Karanth et al. (2017) and Murphy et al. (2021) codes lines and the adapted version for time-efficiency matter and a comparison to verify similarity of results.<br>5_2_Appendix - Multi-response procedure permutation difference: R script containing R code to test for difference of the MRPPs approaches according to the species on which permutation are done.</p>
Figure 2 in Field Capture of Male Melon Flies, Bactrocera cucurbitae (Coquillett), in Jackson Traps Baited with Cue-Lure Versus Raspberry Ketone Formate in Hawaii
Figure 2. Number of B. cucurbitae males captured in Jackson traps baited with cue-lure (CL) liquid (●) versus raspberry ketone formate (RKF) liquid (○) at four study sites on Oahu, Hawaii. At each site, 15 traps of each treatment were operated 1 day per week over 6 consecutive weeks. Symbols represent means (+ 1 SE, n = 15).
Figure 1 in Field Capture of Male Melon Flies, Bactrocera cucurbitae (Coquillett), in Jackson Traps Baited with Cue-Lure Versus Raspberry Ketone Formate in Hawaii
Figure 1. Number of B. cucurbitae males captured in Jackson traps baited with cue-lure (CL) liquid (●) versus raspberry ketone formate (RKF) plugs (○) at four study sites on Oahu, Hawaii. At each site, 15 traps of each treatment were operated 1 day per week over 6 consecutive weeks. Symbols represent means (+ 1 SE, n = 15).
Figure 1 in Testing the Temporal Limits of Lures and Toxicants for Trapping Fruit Flies (Diptera: Tephritidae): Additional Weathering Studies of Solid Bactrocera and Zeugodacus Male Lures and Associated Insecticidal Strips
Figure 1. Captures of Zeugodacus cucurbitae males in Jackson traps containing toxicants of variable age deployed at Aloun Farm, Oahu, Hawaii. The lures were fresh in all traps and were prepared in Hawaii at the start of the test. Two fresh toxicants were included: naled in liquid CL (bar labelled L) and a DDVP strip with a CL plug (bar labelled P). The DDVP strips weathered in Arizona and Florida were tested during the same 1-day period (December 9–10, 2015). Values represent means (+ 1 SE); 12 traps were deployed per treatment. Bars marked by different letters were significantly different (Student-Newman-Keuls multiple comparisons test).
Figure 5 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains
Figure 5. Mean crayfish counts by size (cm) class across twelve trap types with standard error bars.
Figure 2 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains
Figure 2. Six standard, base trap types used in this study; a = Steel silver Gee Minnow trap, b = Vinyl coated black Promar Minnow trap, c = Mountain Restoration Trust custom design pyramid trap, d = Collapsible red square mesh Promar 501 trap, e = Colapsible cylindrical black mesh Promar 503 trap, and f = Mountain Restoration Trust custom PVC tube/refuge traps. Specific modifications to these traps to create the 12 types tested are provided in Table 1.
Figure 1 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains
Figure 1. Placement of traps compared in study in Las Virgenes Creek within Malibu Creek State Park. Inset shows specific study location within a regional context. Section locations were selected based on their representativeness of habitat types occurring over the entire reach (i.e. amount of riffle, runs and pools being comparable) and presence of suitable habitat for trap placement and visual observance of crayfish, tadpoles and native chub.
Figure 7 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains
Figure 7. Mean catches by stream habitat type. Differences in mean catches between stream Pools vs. Runs was evaluated using Wilcoxon rank-sum tests. * P-value <0.05.
Figure 3 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains
Figure 3. Mean catch per trap type with standard errors. Letters indicate significantly different mean counts within groups.
Figure 6 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains
Figure 6. Mean chub counts by size class across twelve trap types with standard error bars. Size classes include small as ≤ 60mm, medium as 61–89 mm, and large as 89–150mm as described by O'Brien et al. (2011).
Fig. 2 in Effect of the height and distribution pattern of pheromone-baited traps on the capture of Scyphophorus acupunctatus (Coleoptera: Dryophthoridae) on blue agave (Asparagales: Asparagaceae)
Fig. 2. Mean (+ SE) numbers and sex ratios of Scyphophorus acupunctatus weevils captured per trap with various distribution pattern of traps in the field. Treatments with similar letters are not significantly different (Tukey's test, a = 0.05).
ScienceDex guides
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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.