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Supplementary material 1 from: Yemshanov D, Koch F, Ducey M, Haack R, Siltanen M, Wilson K (2013) Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker's perspective. NeoBiota 18: 193-218. https://doi.org/10.3897/neobiota.18.4002
Risk of out-of-state (out-of-province) locations to be the source of forest pests transported in firewood carried by campers. The risk rank values are based on the delineation of nested non-dominant sets via the first-degree stochastic dominance rule (FSD). The ranks close to 1.0 denote the highest risk of pest arrival and the ranks close to 0 denote the lowest risk. (doi: 10.3897/neobiota.18.4002.app1) File format: Adobe PDF File (pdf).:
Supplementary material 1 from: Spafford R, Lortie C, Butterfield B (2013) A systematic review of arthropod community diversity in association with invasive plants. NeoBiota 16: 81-102. https://doi.org/10.3897/neobiota.16.4190
Supplementary material 1 from: Spafford R, Lortie C, Butterfield B (2013) A systematic review of arthropod community diversity in association with invasive plants. NeoBiota 16: 81-102. https://doi.org/10.3897/neobiota.16.4190
Supplementary material 1 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 1 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 2 from: Spafford R, Lortie C, Butterfield B (2013) A systematic review of arthropod community diversity in association with invasive plants. NeoBiota 16: 81-102. https://doi.org/10.3897/neobiota.16.4190
Supplementary material 2 from: Spafford R, Lortie C, Butterfield B (2013) A systematic review of arthropod community diversity in association with invasive plants. NeoBiota 16: 81-102. https://doi.org/10.3897/neobiota.16.4190
Supplementary material 4 from: Yemshanov D, Koch F, Ducey M, Haack R, Siltanen M, Wilson K (2013) Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker's perspective. NeoBiota 18: 193-218. https://doi.org/10.3897/neobiota.18.4002
Summary of differences between risk rank classes, 0–0.05, 0.05–0.25, 0.25–0.5, 0.5–0.75, 0.75–0.95 and 0.95–1 in the delineations based on the FSD and SSD rules. (doi: 10.3897/neobiota.18.4002.app4) File format: Adobe PDF File (pdf).:
R code and associated data for: A review of riverine ecosystem service quantification: research gaps and recommendations
<p>This publication contains the R code and associated data used in the Journal of Applied Ecology publication entitled "A review of riverine ecosystem service quantification: research gaps and recommendations". </p>
Data and R script for 'Early-life begging effort reduces adult body mass but strengthens behavioural defence of the rate of energy intake in European starlings (Sturnus vulgaris)'
<p>Data files and R script for Dunn et al. "Early-life begging effort reduces adult body mass but strengthens behavioural defence of the rate of energy intake in European starlings (<em>Sturnus vulgaris</em>)"</p> <p>Includes a single R script that produces all the analyses in the paper. The script makes use of three different .csv data files.</p>
Figure 3: ExaminationDB: (a) E-R Model, (b) Relational Model
<p>In order to explain how the methodology works, we analyze step by step,<br> a simple mapping on a database sample named ExaminationDB.</p>
R code and data for: How much is enough? Minimum sample sizes in community ecology
<p>minimum_sample_sizes_code.R includes the complete set of instructions used to carry out the analyses in the related manuscript, plus save the computed data files and generate the text figures. data_files.tar.gz includes all of the files generated by the R code.</p>
F I G U R E A 2 in Reproductive biology of the electric lanternfish Electrona risso (Myctophidae) and the bigscale fishes Melamphaes polylepis and Scopelogadus mizolepis (Melamphaidae)
F I G U R E A 2 Scopelogadus mizolepis ovarian development. Reproductive phases based on Table 1. Macroscopic development of female gonads (left panels) and histological cross-sections of ovaries (right panels). CA, cortical alveoli oocyte; GVM, germinal vesicle migration oocyte; nu, nucleus; PG, primary growth oocyte; Vtg1–3, primary to tertiary vitellogenic oocyte; yg, yolk granules; yv, yolk vesicle. Photography by A. Knorrn.
F I G U R E 2 in Reproductive biology of the electric lanternfish Electrona risso (Myctophidae) and the bigscale fishes Melamphaes polylepis and Scopelogadus mizolepis (Melamphaidae)
F I G U R E 2 Length–frequency distributions of (a) Electrona risso, (b) Melamphaes polylepis, and (c) Scopelogadus mizolepis by sex (upper panels, females; lower panels, males).
Рис. 1. Рисуночный кΛюч ΑΛя опреΑеΛения виΑов роΑа Ethmolaimus de Man, 1880: A, C, E, G, I, K, M, O, Q, S, U, W — гоΛова самца; B, D, F, H, J, L, N, P, R, T, V, X — заΑний конец теΛа самца; Y — гоΛова самки; Z — заΑний конец теΛа самки Fig. 1. Pictorial key to the species of the genus Ethmolaimus de Man, 1880: A, C, E, G, I, K, M, O, Q, S, U, W — head of male; B, D, F, H, J, L, N, P, R, T, V, X — posterior body end of male; Y — head of female; Z — posterior body end of female in Morphological review of the genus Ethmolaimus de Man 1880 (Nematoda, Chromadorida)
Рис. 1. Рисуночный кΛюч ΑΛя опреΑеΛения виΑов роΑа Ethmolaimus de Man, 1880: A, C, E, G, I, K, M, O, Q, S, U, W — гоΛова самца; B, D, F, H, J, L, N, P, R, T, V, X — заΑний конец теΛа самца; Y — гоΛова самки; Z — заΑний конец теΛа самки Fig. 1. Pictorial key to the species of the genus Ethmolaimus de Man, 1880: A, C, E, G, I, K, M, O, Q, S, U, W — head of male; B, D, F, H, J, L, N, P, R, T, V, X — posterior body end of male; Y — head of female; Z — posterior body end of female
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>
Data from: hespdiv: an R package for spatially constrained, hierarchical and contiguous regionalization in palaeobiogeography
<p>This is data for the '"hespdiv": an R package for spatially constrained, hierarchical, and contiguous regionalization in palaeobiogeography' paper. It contains datasets used, their metada, dataset processing scripts, a list of references to data contributors, and R files containing some of the results presented in the paper.</p>
R code for differential gene expression and enrichment analyses
<p>The information about the magnitude of differences in thermal plasticity both between and within populations, as well as identification of the underlying molecular mechanisms are key to understanding the evolution of thermal plasticity. In particular, genes underlying variation in the physiological response to temperature can provide raw material for selection acting on plastic traits. Using RNAseq, we investigate the transcriptional response to temperature in males and females from bulb mite populations selected for the increased frequency of one of two discrete male morphs (fighter- and scrambler-selected populations) that differ in relative fitness depending on temperature. We show that different mechanisms underlie the divergence in thermal response between fighter- and scrambler-selected populations at decreased vs. increased temperatures. Temperature decrease to 18°C was associated with higher transcriptomic plasticity of males with more elaborate armaments, as indicated by a significant selection-by-temperature interaction effect on the expression of 40 genes, 38 of which were upregulated in fighter-selected populations in response to temperature decrease. In response to 28°C, no selection-by-temperature interaction in gene expression was detected. Hence, differences in phenotypic response to temperature increase likely depended on genes associated with their distinct morph-specific thermal tolerance. Selection on males also drove gene expression patterns in females. These patterns could be associated with temperature-dependent fitness differences between females from fighter- vs. scrambler-selected populations reported in previous studies. Our study shows that selection for divergent male sexually selected morphologies and behaviors has the potential to drive divergence in metabolic pathways underlying plastic response to temperature in both sexes.</p>
R code for: Following regulation, imidacloprid persists and flupyradifurone increases in non-target wildlife
<p>After regulation of pesticides, determination of their persistence in the environment is an important indicator of effectiveness of these measures. We quantified concentrations of two types of systemic insecticides: neonicotinoids (imidacloprid, acetamiprid, clothianidin, thiacloprid, and thiamethoxam) and butenolides (flupyradifurone), in off-crop non-target media of hummingbird cloacal fluid, honey bee (<em>Apis mellifera</em>) nectar and honey, and wildflowers before and after regulation of imidacloprid on highbush blueberries in Canada in April 2021. We found that mean total pesticide load increased in hummingbird cloacal fluid, nectar, and flower samples following imidacloprid regulation. On average, we did not find evidence of a decrease in imidacloprid concentrations after regulation. However, there were some decreases, some increases and other cases with no changes in imidacloprid levels depending on the specific media, time point of sampling and site type. At the same time, we found an overall increase in flupyradifurone, acetamiprid, thiamethoxam and thiacloprid, but no change in clothianidin concentrations. In particular, flupyradifurone concentrations observed in biota sampled near to agricultural areas increased by 2-fold in honey bee nectar, 7-fold in hummingbird cloacal fluid, and 8-fold in flowers after the 2021 imidacloprid regulation. The highest residue detected in this study was flupyradifurone at 665 ng/mL (PPB) in honey bee nectar. Mean total pesticide loads were highest in honey samples (84 ± 10 PPB) followed by nectar (56 ± 7 PPB), then hummingbird cloacal fluid (1.8 ± 0.5 PPB), and least, flowers (0.51 ± 0.06 PPB). Our results highlight that limited regulation of imidacloprid does not immediately reduce residue concentrations while other systemic insecticides, possibly replacement compounds, concurrently increase in wildlife.</p>
DataSet & R code used for the analysis of "Mechanisms of mobbing call recognition: Exploring featural decoding in great tits"
<p>Data and R code used in a playback experiment exploring the mechanisms of mobbing call recognition in the great tit, Parus major. Accepted in Animal Behaviour (2024). </p> <p>This experiment aimed at testing the hypothesis of simple featural interpretation in the great tit (i.e., the fact that receivers can focus on specific acoustic features rather than complete note recognition). </p> <p>The experiment is organised with two parts: first, we test the response of great tits to artificial calls that possess either none or all of the characteristics present in their own calls (and shared with other Parids), and compare their level of response to natural mobbing calls. </p> <p>As the 'complete' treatment triggered the same level fo response than the natural calls, we then create artifical calls with only one of the four features used to create our artifical mobbing calls (large frequency range, low frequency, noise and harmonics). </p> <p> </p> <p>More information can be obtained by contacting Ambre SALIS (salis.ambre87[at]gmail.com)</p>
23E. Rhinella margaritifera. Male.Triunfo, Bolivar.This population could represent R in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
23E. Rhinella margaritifera. Male.Triunfo, Bolivar.This population could represent R. martyi. Photo: César Barrio-Amorós.
FIGURES 37-43. Paranysson oscari R in A Revision of the Genus Paranysson Guérin-Méneville, 1844 (Hymenoptera: Crabronidae)
FIGURES 37-43. Paranysson oscari R. Turner. (37) Female clypeus and mandible; (38) Male clypeus and mandible; (39) Female clypeus and mandibular base in lateral oblique view; (40) Female hindcoxa with spine; (41) Male palpi; (42) Gastral apex of male in dorsal view (arrow shows lateral carina of tergum VI); (43) Male genitalia in dorsal view (arrow shows lateral process of penis valve).
Fig. 2 Infected R in Isolation of infectious Theileria parva sporozoites secreted by infected Rhipicephalus appendiculatus ticks into an in vitro tick feeding system
Fig. 2 Infected R. appendiculatus adult ticks feeding on a silicone membrane. a A representation of adult ticks attached to a silicone membrane. b Detection of tick salivary gland infected with T. parva via p104 PCR. Amplicons were visualized in 2% agarose gel
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.