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zenodo40/100

Data and analyses for Perkowski et al. (2024) manuscript accepted to AoB Plants: "Symbiotic nitrogen fixation reduces belowground biomass carbon costs of nitrogen acquisition under low, but not high, nitrogen availability"

This repository contains data and scripts for analyses and plots in Perkowski et al. (2024), titled "Symbiotic nitrogen fixation reduces belowground biomass carbon costs of nitrogen acquisition under low, but not high, nitrogen availability". v2.0 updates code and scripts per reviewer comments and is the final release prior to manuscript proofing.

opencc-by-4.0Sep 2024View details →

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Data Echoes: Tracking Data Availability and Integrity in Software Engineering Research

This is the dataset of the report: Data Echoes: Tracking  Data Availability and Integrity in Software Engineering Research It contains the following information of all the papers from ASE, FSE, and ICSE in 2023: <ul> <li>Paper title</li> <li>Keyword</li> <li>Is the source data available and accessible in the paper?</li> <li>If the source data is not available, do the authors explain why?</li> <li>Hosting platforms</li> <li>Access mode</li> <li>License</li> <li>Is their experiment data reused from previous work, or newly generated specifically for this study, or combination of both? </li> <li>Do the authors change/modify their experiment data before experiment?</li> <li>What modifications do they perform?</li> <li>Does the link provide detailed instructions about how to replicate their paper?</li> <li>Does the link contains their complete experiment data, their source code or other materials that are necessary to replicate their experiments?</li> <li>What's the data format inside the link?</li> <li>What's the content of the link?</li> </ul>   We collect the data in a rush. If you want to use this dataset and find any errors, please contact us  ;-)   Our emails: <ul> <li>echo.xiangchen@gmail.com</li> <li>zhifengyao731@gmail.com</li> </ul>

opencc-by-4.0Sep 2024View details →

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Data from: Intraspecific correlations between growth and defense vary with resource availability and differ within- and among-populations

A paradigm in the plant defense literature is that defending against herbivores comes at a cost to growth, resulting in a growth-defense tradeoff. However, while there is strong evidence for growth-defense tradeoffs across species, evidence is mixed within species. Several mechanisms can account for this equivocal support within species, but teasing them apart requires examining growth-defense relationships both within and among populations, an approach seldom employed. We examined correlations between plant biomass (growth) and terpene production (defense) within and among populations of Monarda fistulosa, a perennial herb. We sampled populations from Montana and Wisconsin, regions that differ in resource availability characterized by different summer precipitation and associated abiotic conditions that influence plant productivity. We found negative, neutral, and positive growth-defense correlations, depending on the scale examined. Negative correlations occurred across populations originating from divergent regions, positive correlations occurred across populations originating from within the high-resource region, and neutral correlations were found within single populations. Collectively, these results challenge the general expectation of ubiquitous tradeoffs and support emerging views that resource availability (as it affects productivity) shapes the evolution of defense at different scales.

opencc-zeroJun 2021View details →

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Data from: Recovery of silver fir (Abies alba Mill.) seedlings from ungulate browsing mirrors soil nitrogen availability

Abies alba (Mill.) has a high potential for mitigating climate change in European mountain forests, yet, its natural regeneration is severely limited by ungulate browsing. Here, we simulated browsing in a common garden experiment to study growth and physiological traits, measured from bulk needles, using a randomized block design with two levels of browsing severity and seedlings originating from 19 populations across Switzerland. Genetic factors explained most variation in growth (on average, 51.5%) and physiological traits (10.2%) under control conditions, while heavy browsing considerably reduced the genetic effects on growth (to 30%), but doubled those on physiological traits related to C storage. While browsing reduced seedling height, it also lowered seedling water use efficiency (decreased δ13C) and increased their δ15N. Different populations reacted differently to browsing stress, and for seedling height, starch concentration and δ15N population differences appeared to be the result of natural selection. First, we found that populations originating from the warmest regions recovered the fastest from browsing stress, and they did so by mobilizing starch from their needles, which suggests a genetic underpinning for a growth-storage trade-off across populations. Second, we found that seedlings originating from mountain populations growing on steep slopes had a higher δ15N in the common garden than those originating from flat areas, indicating that they have been selected to grow on N poor, potentially drained, soils. This finding was corroborated by the fact that N concentration in adult needles was lower on steep slopes than on flat ground, strongly indicating that steep slopes are the most N poor environments. These results suggest that populations adapted to these N poor environments have a genetically based high N use efficiency, which could be necessary for their recover from ungulate browsing.

opencc-by-4.0Jul 2021View details →

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Fig. 1 in Currently available data on Borneo geometrid moths do not provide evidence for a Pleistocene rainforest refugium

Fig. 1. Sundaland during the Pleistocene. Lowered sea levels exposed much of the Sunda shelf, unifying Borneo, Sumatra, Java, Bali and the Malay Peninsula. Today's coastlines and country borders are shown for orientation. Dark grey areas denote hypothesized rainforest refugia (redrawn from Gathorney-Hardy et al., 2002). Stars indicate sampling locations in Borneo as used for this study; the southern-most location is Camp Foyle (see Appendix for details).

opencc-by-4.0Dec 2014View details →

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Data Availability Statements in the 2020 and 2021 scientific publications of Tampere University

For this dataset, scientific peer-reviewed articles by Tampere University researchers from the years 2020 and 2021 were extracted from the TUNICRIS. A random sample of 40 percent was taken from the listed 4,922 publications according to faculties and years. There were 2,085 analyzed articles, i.e. more than 42 percent of the total number.  To find Data Availability Statements, articles were opened one by one and searched for mentions of research data and its availability. For each article, it was written down whether DAS existed and where in the article it was located. From the contents of DAS, information about data availability, location, openness and possible restrictions on use was written down.  Dataset also includes information about the journals and publications taken from TUNICRIS.  The prevalence of DAS and data openness were examined in relation to different variables. Tampere University faculty information has been removed from the dataset.  Related slides: https://doi.org/10.5281/zenodo.7655892 Related article (in Finnish): Toikko, T., & Kylmälä, K. (2023). Tutkimusdatan saatavuustiedot tieteellisissä artikkeleissa: Raportti Data Availability Statementien käytöstä Tampereen yliopistossa. Informaatiotutkimus, 42(1-2), 31–50. https://doi.org/10.23978/inf.126098

opencc-by-4.0Jan 2023View details →

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Data from: Comparing winter versus summer deepwater dissolved oxygen depletion with the potential for cross-seasonal forecasting of deepwater oxygen availability

Depletion of deepwater dissolved oxygen (DO) in lakes has become increasingly prevalent and severe due to many external stressors, potentially threatening human-derived ecosystem services ranging from drinking water quality to fisheries. Using year-round, high-frequency DO data from 12 dimictic lakes, we compared three measures of deepwater DO depletion during winter and summer:  DO depletion rate, DO minimum, and hypoxia duration. Hypoxia (DO < 3 mg L-1) occurred in over half of the lakes and persisted an average of 83% longer in summer than in winter. While we found no difference in DO depletion rates between winter versus summer, these rates were strongly related to lake morphology in winter but water transparency and temperature in summer. Winter hypoxia duration was negatively related to summer hypoxia duration, suggesting potential utility for forecasting DO depletion in the subsequent summer. Spring mixing efficacy was strongly related to winter minimum DO saturation and hypoxia duration, and was also a strong predictor of summer minimum DO saturation and hypoxia duration. Hence, these cross-seasonal patterns suggest deepwater DO metrics can be used to forecast DO availability in subsequent seasons, modified by the relative importance of morphology, water transparency, and temperature. These findings can allow for improved, early management when DO is predicted to be critically low based on previous seasons’ DO measurements, which can work to minimize the negative consequences for water quality and fisheries health associated with severe DO depletion.

opencc-by-4.0May 2023View details →

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Data and Code Availability Stament for Halifa-Marín et al., 2023 (Environmental Research: Climate)

This file provides the R codes and datasets to reproduce the analyses made in the mentioned study, Halifa-Marín et al., 2023 (Environmental Research: Climate), and the supplementary material (figures).

opencc-by-4.0Jun 2023View details →

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Characterizing the Folding Transition State Ensembles in the Energy Landscape of an RNA Tetraloop - available data.

Trajectory file and scripts necessary to generate an ELViM [Oliveira, A. B.; Yang, H.; Whitford, P. C.; Leite, V. B. P. JCTC, 2019, 15, p.6482] projection of the conformational space for the GCAA tetraloop.

opencc-by-4.0Mar 2023View details →

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Data and code for "Turning tables: food availability shapes dynamic aggressive behaviour among asynchronously hatching siblings in red kites Milvus milvus"

Abstract Aggression represents the backbone of dominance acquisition in several animal societies, where the decision to interact is dictated by its relative cost. Among siblings, such costs are weighted in the light of inclusive fitness, but how this translates to aggression patterns in response to changing external and internal conditions remains unclear. Using a null-model-based approach, we investigate how day-to-day changes in food provisioning affect aggression networks and food allocation in growing red kite (Milvus milvus) nestlings, whose dominance rank is largely dictated by age. We show that older siblings, irrespective of age, change from targeting only close-aged peers (close-competitor pattern) when food provisioning is low, to uniformly attacking all other peers (downward heuristic pattern) as food conditions improve. While food allocation was generally skewed towards the older siblings, the youngest sibling in the nest increased its probability of accessing food as more was provisioned and as downward heuristic patterns became more prominent, suggesting that different aggression patterns allow for catch-up growth after periods of low food. Our results indicate that dynamic aggression patterns within the nest modulate environmental effects on juvenile development by influencing the process of dominance acquisition and potentially impacting the fledging body condition, with far-reaching fitness consequences.

opencc-by-4.0Jun 2023View details →

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Sources of prey availability data alter interpretation of outputs from prey choice null networks

Spider surveys Data collection was described previously by Cuff, Tercel, et al., (2022). This study pertains to a subset of those data, collected between 1st May and 9th July 2018 at 19 separate locations, for which paired sticky trap and vacuum sample data were collected (described below). Briefly, money spiders (Araneae: Linyphiidae) and wolf spiders (Araneae: Lycosidae) were visually located along transects in two adjacent barley fields at Burdons Farm, Wenvoe in South Wales (51°26'24.8"N, 3°16'17.9"W) and collected from webs and the ground. Transects were randomly distributed across the entire field. Along these transects, separate 4 m2 quadrats, at least 10 m apart, were searched and all observed linyphiids and lycosids were collected. Spiders were placed in 100 % ethanol using an aspirator, regularly changing meshing to limit potential cross-contamination. Linyphiids occupying webs were prioritised for collection, but ground-active spiders were also collected. Spiders were taken to Cardiff University, transferred to fresh ethanol and stored at -80 °C in 100 % ethanol until DNA extraction. Extraction, amplification and sequencing of DNA, and bioinformatic analysis is described by Cuff, Tercel, et al., (2022) and Drake et al., (2022), and is also detailed below. Extraction and high-throughput sequencing of spider gut DNA Given their prevalence in field collections, dietary analysis was carried out for the linyphiid genera Erigone, Tenuiphantes, Bathyphantes and Microlinyphia (Araneae: Linyphiidae), and the Lycosidae genus Pardosa. Spiders were transferred to and washed in fresh 100 % ethanol to reduce external contaminants prior to identification via morphological key (Roberts, 1993). Abdomens were removed from spiders and again transferred to and washed in fresh 100 % ethanol. DNA was extracted from the abdomens via Qiagen TissueLyser II and DNeasy Blood & Tissue Kit (Qiagen) as per the manufacturer protocol, but with an extended lysis time of 12 hours to account for the complex and branched gut system in spider abdomens (Krehenwinkel et al., 2017). For amplification of DNA, two primer pairs were used. BerenF-LuthienR (Cuff et al., 2021) amplified a broad range of invertebrates including spiders, and TelperionF-LaureR (Cuff et al., 2022), amplified a range of invertebrates but fewer spiders. Primers were labelled with unique 10 bp molecular identifier tags (MID-tags) so that each individual had a unique pairing of forward and reverse tags for identification of each spider post-sequencing. PCR reactions of 25 µl contained 12.5 µl Qiagen PCR Multiplex kit, 0.2 µmol (2.5 µl of 2 µM) of each primer and 5 µl template DNA. Reactions were carried out in the same thermocycler, optimised via temperature gradient, with an initial 15 minutes at 95 °C, 35 cycles of 95 °C for 30 seconds, the primer-specific annealing temperature for 90 seconds and 72 °C for 90 seconds, respectively, followed by a final extension at 72 °C for 10 minutes. BerenF-LuthienR and TelperionF-LaureR used annealing temperatures of 52 °C and 42 °C, respectively. Within each PCR 96-well plate, 12 negative controls (extraction and PCR), 2 blank controls and 2 positive controls were included (i.e. 80 samples per plate), based on Taberlet et al. (2018). Positive controls were mixtures of invertebrate DNA comprised of non-native Asiatic species in four different proportions and blanks were empty wells within each plate to identify tag-jumping into unused MID-tag combinations. PCR negative controls were DNase-free water treated identically to DNA samples. A negative control was present for each MID-tag to identify any contamination of primers. All PCR products were visualised in a 2 % agarose gel with SYBRSafe (Thermo Fisher Scientific, Paisley, UK) and placed in categories based on their relative brightness. The concentration of these brightness categories was quantified via Qubit dsDNA High-sensitivity Assay Kits (Thermo Fisher Scientific, Waltham, MA, USA) with at least three representatives of each category per plate. The PCR products were then proportionally pooled according to these concentrations. Each pool was cleaned via SPRIselect beads (Beckman Coulter, Brea, USA), with a left-side size selection using a 1:1 ratio (retaining ~300-1000 bp fragments). The concentration of the pooled DNA was then determined via Qubit dsDNA High-sensitivity Assay Kits and pooled together into one library per primer pair. Library preparation for Illumina sequencing was carried out on the cleaned libraries via NEXTflex Rapid DNA-Seq Kit (Bioo Scientific, Austin, USA) and samples were sequenced on an Illumina MiSeq via a V3 chip with 300-bp paired-end reads (expected capacity ≤25,000,000 reads). Bioinformatic analysis followed Drake et al. (2022). Bioinformatic analysis The Illumina run generated 11,165,405 and 10,959,010 reads for BerenF-LuthienR and TelperionF-LaureR, respectively, which were quality-checked and paired via FastP (Chen et al., 2018)  to retain only sequences of at least 200 bp with a quality threshold of 33, resulting in 10,561,874 and 9,355,112 paired reads. The paired reads were demultiplexed and assigned to their respective spider sample according to their MID-tags via the “trim.seqs” command in Mothur v1.39.5 (Schloss et al., 2009), leaving 7,854,610 and 7,437,929 reads with exact matches to the primer and MID-tags. Replicates were removed, and denoising and clustering to zero-radius operational taxonomic units (ZOTUs; clustered without % identity to avoid multiple species represented within a single operational taxonomic unit (OTU)) completed via Unoise3 in Usearch11 (Edgar, 2010). The resultant sequences were assigned a taxonomic identity from GenBank via BLASTn v2.7.1 (Camacho et al., 2009) using a 97 % identity threshold (Alberdi et al., 2017). The BLAST output was analysed in MEGAN v6.15.2 (Huson et al., 2016). Where the top BLAST hit, determined by lowest e-value, was resolved at a higher taxonomic level than species-level, the results were checked; where possibly erroneous entries were preventing species-level assignment (e.g., poorly resolved identifications on GenBank), finer resolution was assigned based on the next-closest match. Where ZOTUs were assigned the same taxon, these were aggregated. Data clean-up used the optimal minimum sequence copy thresholds identified by Drake et al. (2022). The maximum value for a ZOTU present in blank or negative controls was identified and subtracted from all read counts for that ZOTU to remove background contaminants. Simultaneously, known lab contaminants (e.g., German cockroach Blattella germanica), artefacts and errors of the sequencing process, unexpected reads in positive controls and positive control taxon reads in dietary samples were identified. These were calculated as a percentage of their respective sample’s read count and any read counts lower than the highest of these percentages for their respective sample were removed to eliminate additional instances of contamination. These thresholds were defined as 0.38 % and 0.39 % for BerenF-LuthienR and TelperionF-LaureR, respectively. The data from the two libraries (i.e., from each primer pair) were then aggregated together by sample and aggregated again by taxon. Non-target taxa (e.g., fungi) and instances in which predator DNA was amplified (i.e., ZOTUs with high read counts matching the individual’s morphological identity) were removed.  The resultant sequencing read counts were converted into relative proportions (all values made to sum to one within each sample) and a mean value across the two primer pairs retained for each taxon within each sample. Relative read abundances were converted to presence-absence data of each detected prey taxon in each individual spider, but relative read abundance data were also retained for separate analyses to compare experimental outcomes between treatments. Invertebrate surveys To estimate prey availability using sticky traps, we placed one white dry 100 mm x 125 mm trap (Oecos) in the 4 m2 quadrat centred at the position where the spider was captured. The trap was suspended with wire approximately 25 mm above the ground to catch falling, crawling and flying invertebrates, and left in place for 72 hours. Invertebrates were identified on the traps under a stereomicroscope. To estimate prey availability using suction sampling, ground and crop stems were sampled using a ‘G-vac’ for approximately 30 seconds at each location. The collected material was emptied into a bag, any organisms immediately killed with ethyl-acetate and material frozen for storage before sorting into 70 % ethanol in the lab. All invertebrates were identified to family level to match the resolution of the least resolved of the metabarcoding-derived trophic interaction data, and due to difficulties associated with identification to finer taxonomic resolution for many taxa. Exceptions included springtails of the superfamily Sminthuroidea (Sminthuridae and Bourletiellidae were often indistinguishable following suction sampling and preservation due to the fine features necessary to distinguish them) which were left at super-family, mites (many of which were immature or in poor condition) which were identified to order level, and wasps of the superfamily Ichneumonoidea which were identified no further due to obscurity of wing venation due to damage following suction sampling. Statistical Analysis All analyses were conducted in R v4.0.3 (R Core Team, 2021) and carried out on invertebrate data at the family or superfamily level. Alongside the dietary data derived from metabarcoding, and prey availability as determined directly by suction sampling (abundance) and sticky trapping (activity density), three additional datasets were generated where two were designed to combine data from the two trapping methods. The first approach simply set all invertebrate taxa detected in the field to have equal abundance, to provide a baseline against which to assess the effects of different prey abundance estimates. When generating the two combined data sets, it was apparent that simply adding them together would underrepresent one of the datasets as abundance and activity density are measured in different units. Therefore, a ‘proportional combined’ dataset was generated by converting counts to relative proportions of each sample (to equally weight the two methods), which were then combined by summing proportions between the two methods for each sample, multiplied by the total count of individuals across both methods for each sample (to create realistic abundance values), and then rounded to the nearest integer (to return count data). In addition, a ‘frequency of occurrence (FOO) combined’ dataset was generated by converting counts to binary presence-absence values of each sample, which were then summed between the two methods for each sample. To assess the diversity represented by the two sampling methods and their combinations, and the completeness of those datasets, coverage-based rarefaction and extrapolation were carried out, and Hill diversity calculated (Chao et al., 2014; Roswell et al., 2021) using the ‘iNEXT’ package with families represented by frequency-of-occurrence across samples (Chao et al., 2014; Hsieh et al., 2016). The remaining analyses were performed using both presence-absence and relative read abundance dietary data separately to show how differences in the treatment of the observed data are reflected in the outcomes of the analyses. Figures and outputs given in the main text relate to the presence-absence data, while relative read abundance figures and outputs are presented in the Supplementary Information. Prey preferences of spiders were analysed using network-based null models in the ‘econullnetr’ package (Vaughan et al., 2018) with the ‘generate_null_net’ function. Econullnetr generates null models based on prey availability to predict how consumers would forage if based on the availability of resources alone. These null models are then compared against the observed interactions of consumers (e.g., interactions of spiders with their prey based on dietary metabarcoding) to ascertain the extent to which resource consumption deviated from random. In five separate null models, prey availability was represented separately by the datasets described above: abundance (suction sampling), activity density (sticky trapping), proportional combined, FOO combined and equal prey abundance. To compare effect sizes between null models for each resource taxon, mean prey preference standardised effect size (SES) values were calculated from the individual spiders per model. The SES values were plotted and joined between taxa to visualise paired differences using ‘ggplot’ (Wickham, 2016). Null model-predicted trophic interactions were generated via an econullnetr null model with 999 simulations with outputs extended to allow the comparison of the null interactions for individual consumers (generate_null_net_indiv; Cuff, Kitson, et al., 2023). A visualisation of the per-individual differences in null model and observed data was generated via non-metric multi-dimensional scaling (NMDS) using the ‘metaMDS’ function in the ‘vegan’ package (Oksanen et al., 2016) in two dimensions and 9999 simulations, with Euclidean distance. Centroid coordinates for each null model and the observed data were extracted and pairwise distances calculated between model centroids: The ‘observed’ network (i.e., the network determined solely by dietary data, not necessarily the objectively ‘true’ network) and each null network were visualised with the associated prey choice effect sizes as a bipartite network using ‘ggnetwork’ (Briatte, 2021; Wickham, 2016) via an ‘igraph’ object (Csardi & Nepusz, 2006). The degree of each prey node, weighted nestedness and linkage density were generated using the ‘bipartite’ package (Dormann et al., 2008) for each network and compared visually via ggplot2.

opencc-by-4.0May 2023View details →

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Dataset: Preliminary analysis of open data pertaining to the services available through the Health Insurance Institute of Slovenia and provided by family medicine

BACKGROUND: The Health Insurance Institute of Slovenia (ZZZS) began publishing service-related data in May 2023, following a directive from the Ministry of Health (MoH). The ZZZS website provides easily accessible information about the services provided by individual doctors, including their names. The user is provided relevant information about the doctor's employer, including whether it is a public or private institution. The data provided is useful for studying the public system's operations and identifying any errors or anomalies.  METHODS: The data for services provided in May 2023 was downloaded and analysed. The published data were cross-referenced using the provider's RIZDDZ number with the daily updated data on ambulatory workload from June 9, 2023, published by ZZZS. The data mentioned earlier were found to be inaccurate and were improved using alerts from the zdravniki.sledilnik.org portal. Therefore, they currently provide an accurate representation of the current situation. The total number of services provided by each provider in a given month was determined by adding up the individual services and then assigning them to the corresponding provider.  RESULTS: A pivot table was created to identify 307 unique operators, with 15 operators not appearing in both lists. There are 66 public providers, which make up about 72% of the contractual programme in the public system. There are 241 private providers, accounting for about 28% of the contractual programme. In May 2023, public providers accounted for 69% (n=646,236) of services in the family medicine system, while private providers contributed 31% (n=291,660). The total number of services provided by public and private providers was 937,896. Three linear correlations were analysed. The initial analysis of the entire sample yielded a high R-squared value of .998 (adjusted R-squared value of .996) and a significant level below 0.001. The second analysis of the data from private providers showed a high R Squared value of .904 (Adjusted R Squared = .886), indicating a strong correlation between the variables. Furthermore, the significance level was < 0.001, providing additional support for the statistical significance of the results. The third analysis used data from public providers and showed a strong level of explanatory power, with a R Squared value of 1.000 (Adjusted R Squared = 1.000). Furthermore, the statistical significance of the findings was established with a p-value < 0.001.  CONCLUSION: Our analysis shows a strong linear correlation between contract size of the program signed and number services rendered by family medicine providers. A stronger linear correlation is observed among providers in the public system compared to those in the private system. Our study found that private providers generally offer more services than public providers. However, it is important to acknowledge that the evaluation framework for assessing services may have inherent flaws when examining the data. Prescribing a prescription and resuscitating a patient are both assigned a rating of one service. It is crucial to closely monitor trends and identify comparable databases for pairing at the secondary and tertiary levels.

opencc-by-4.0Dec 2022View details →

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Data from: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People

These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4">https://doi.org/10.5061/dryad.bnzs7h4h4</a>. The files consist of the code of an agent-based model (ABM) in a NetLogo, detailed documentation of the ABM in a standard format, and a table of data exported from the simulation experiment reported on in the paper. By downloading the Netlogo file, one could not only rerun the experiment we report on and recreate the data table but toggle parameters or edit the model to explore other dynamics.

opencc-zeroSep 2023View details →

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Vaccination of poultry against highly pathogenic avian influenza – part 1. Available vaccines and vaccination strategies. Annex A–Supplementary information on ToR 1 data

Table A.1 - Available vaccines for HPAI in poultry. The table includes information on vaccine characteristics such as HA seed strain, vaccine dosage and administration route, target species, authorisation status, challenge strain, duration of immunity and source of information. Table A.2 - Challenge experiments. The table includes data extracted from 28 selected studies from literature on challenge experiments. The data was used to quantify VES, VEm, VEsh and VEs,sh for each vaccine assessed within each study. For each value of VEs,sh the probability Rvac < 1 was estimated to infer the probability of the vaccine to potentially stop transmission in vaccinated birds (VET). Table A.3 - Transmission experiments. The table includes data extracted from 12 studies from the literature, data was used from the unvaccinated and vaccinated groups to quantify VES, VEm, VEsh and VEs,sh for each vaccine assessed within each study; the estimated R values for the unvaccinated (Runv) and vaccinated (Rvac) groups were also extracted. The Rvac values were used to create a binomial variable classifying whether the vaccine could stop transmission (R < 1) or not.

opencc-by-4.0Oct 2023View details →

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