Find research datasets worth reusing

opencc-by-4.0Oct 2022View details →

Dataset for: Owner-ascribed personality profiles distinguish domestic cats that capture and bring home wild animal prey

Dataset allowing repetition of the analyses in the above paper, comprising personality scores and predation data, with details of cat characteristics. See readme.txt file.

opencc-zeroNov 2022View details →

Data for Few studies of wild animal performance account for parasite infections: a systematic review

Data from a systematic review across eight scientific journals publishing primarily studies in animal behaviour and physiology over a 5-year period to assess the proportion of studies which acknowledge, treat or control for parasite infection in their study design and/or analyses. Wild animals have parasites. This inconvenient truth has far-reaching implications for biologists measuring animal performance traits: infection with parasites can alter host behaviour and physiology in profound and sometimes counterintuitive ways. Yet, to what extent do studies on wild animals take individual infection status into account? We explored whether parasite inclusion differed between studies that are experimental versus observational, conducted in the field vs the laboratory and measure behavioural vs physiological traits. We also investigated the importance of other factors such as the journal, the year of publication, the trait category (e.g. locomotion, reproduction) measured, the vertebrate taxonomic group investigated, and the host climatic zone of origin. Our results show that parasite inclusion was generally lacking across recent studies on wild vertebrates. In over 680 filtered papers, we found that only 21.9% acknowledged the potential effects of infections on animal performance in the text, and only 5.1% of studies treated animals for infection (i.e. parasite control) or considered infection status in the statistical analyses (i.e. parasite analysis). Parasite inclusion, control and analysis were higher in laboratory compared to field studies and higher for physiological studies compared to behavioural studies but did not differ among journals, performance trait categories and taxonomic groups. Overall, our literature review suggests that parasites are sorely under-acknowledged by researchers in recent years despite growing evidence that infections can modify animal performance. Given the ubiquity of parasites in the environment, we encourage scientists to consider individual infection status when assessing performance of wild animals. We also suggest ways for researchers to implement such practices in both experimental and observational studies.

opencc-by-4.0Feb 2023View details →

Experimental 3D convex hull tiling of a wild moss specimen ( Rhytidiadelphus or Eurhynchium ?) embedded in 1% agarose

Experimental 3D convex hull tiling of a wild moss specimen ( Rhytidiadelphus or Eurhynchium ?) embedded in 1% agarose Raw data consists of 18 tiles of varying number of Z stacks, depending on where the 3D convex hull points were determined. Images acquired on a Zeiss Lightsheet Z1 using a W Plan-Apochromat 20x/1.0 UV-VIS objective simultaneous dual camera acquisition of autofluorescence under 488nm and 561nm excitation. Original voxel sizes are (x,y,z) = (0.326, 0.326, 2.0) microns Data provided here are tiles fused using BigStitcher, downsampled to the following voxel sizes - Moss_Fused_Downsampled.tif: (4, 4, 24) microns - Moss_Fused_Downsampled_Anisotropy_2.tif: (12, 12, 24) microns Sample acquisition, sample preparation, imaging and stitching performed by Olivier Burri, at the Ecole Polytechnique Fédérale de Lausanne BioImaging and Optics Platform (EPFL - SV - PTECH - PTBIOP)

opencc-by-4.0Mar 2023View details →

Centripetal migration in Drosophila ovary I: wild type timelapse & milestones pt1

Timelapse imaging data tracking inward migration of follicle cells during centripetal migration in Drosophila ovary.  Part of data supporting Figs 2, S1 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration” DOI: 10.1242/dev.200492      •Timelapse imaging data of wild type samples      •Quantitative analysis of specific milestone morphologies      •Analysis of distances between leader FC tips from opposite sides of egg chamber prior to Milestone VII in relevant samples

opencc-by-4.0Sep 2022View details →

Data from: Pathogen community composition and co-infection patterns in a wild community of rodents

ABSTRACT Rodents are major reservoirs of pathogens that can cause disease in humans and livestock. It is therefore important to know what pathogens naturally circulate in rodent populations, and to understand the factors that may influence their distribution in the wild. Here, we describe the incidence and distribution patterns of a range of endemic and zoonotic pathogens circulating among rodent communities in northern France. The community sample consisted of 713 rodents, including 11  host species  from diverse habitats. Rodents were screened for virus exposure (hantaviruses, cowpox virus, Lymphocytic choriomeningitis virus, Tick-borne encephalitis virus) using antibody assays. Bacterial communities were characterized using 16S rRNA amplicon sequencing of splenic samples. Multiple correspondence (MCA), regression and association screening (SCN) analyses were used to determine the degree to which extrinsic factors contributed to pathogen community structure, and to identify patterns of associations between pathogens within hosts. We found a rich diversity of bacterial genera, with 36 known or suspected to be pathogenic. We revealed that host species is the most important determinant of pathogen community composition, and that hosts that share habitats can have very different pathogen communities. Pathogen diversity and co-infection rates also vary among host species. Aggregation of pathogens responsible for zoonotic diseases suggests that some rodent species may be more important for transmission risk than others. Moreover we detected positive associations between several pathogens, including Bartonella, Mycoplasma species, Cowpox virus (CPXV) and hantaviruses, and these patterns were generally specific to particular host species. Altogether, our results suggest that host and pathogen specificity is the most important driver of pathogen community structure, and that interspecific pathogen-pathogen associations also depend on host species. FILE DESCRIPTION: MiSeq raw sequences of the 16Sv4 rRNA gene from spleen rodent samples This ZIP file contains the FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each spleen rodent sample using the MiSeq platform. The 749 multiplexed PCR products were indexed using both forward and reverse indices. Information of the multiplexed samples (n=363 in replicate) and positive (n= 6) & negative controls (n= 17) is provided in the following XLSX file titled: 16S_raw_abundance_data.xlsx File name: MiSeq raw sequences of the V4 region 16S rRNA gene.zip Raw input and output files generated by the mothur program This ZIP file contains all the input and output files generated during the MiSeq sequence analysis with the mothur program. File name: Raw input and output files generated by the mothur program.zip Log file generated by the mothur program This TXT file contains is the history of all the command lines and parameters used during the MiSeq sequence analysis with the mothur program. File name: mothur.1428506786.logfile Raw abundance table of the 16v4 rRNA gene from spleen rodent samples before data filtering This XLSX file contains the number of reads for each distinct Operational Taxonomic Unit (OTU) and each of the PCR products, including the 332 spleen rodent samples analyzed in the study and the negative & positive controls, sequenced in the MiSeq run before the data filtering. This file contains also the following information: Study_site, Study_year, Sample_habitat, Host_species, Host_age, Host_sex, PCR_ID and the taxonomic classification (Kingdom to Genus) of each OTU. File name: 16S_raw_abundance_data.xlsx Occurrence table of the 16v4 rRNA gene from spleen rodent samples after data filtering This XLSX file contains the occurrences (presence: 1 ; absence: 0) after data filtering of each putative pathogenic Operational Taxonomic Unit (OTU) for each of the 332 spleen rodent samples analyzed in the study. File name: 16S_presence_absence_data.xlsx Statistical Analysis Scripts and Data File This ZIP file contains the R scripts for performing statistical analyses reported in the main text and supplemental materials. There is one main file (Analyses.R), as well as two source scripts required for association screening analyses (SCN.txt and FctTestScreenENV.txt). It also includes an R-legible data file containing occurrences (presence: 1 ; absence: 0) for all pathogen exposure variables on which statistical analyses were conducted (PA_DATA.csv) for each of the 332 spleen rodent samples analyzed in the study. The column names for bacterial exposures correspond to the “Pathogen Code” given in the 16S_presence_absence_data.xlsx file. File name: Statistical Analysis Scripts and Data File.zip

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Nitrogen cycling and metabolic rates of aquacultured and wild Acropora coral from Guam in response to ammonium loading rates during 2020-2022

Rates from aquacultured corals and coral fragments collected in Guam in response to ammonium loading. These data are from two separate experiments, one using aquacultured corals and artificial seawater and light. The second was done with wild collected Acropora pistillata from two reef sites in Guam. The first site was West Hagåtña Bay (N13.479650, E144.741750; N13.479833, E144.741733) which had more nearby urban influences and was near the sewage outfall for the city (Redding et al. 2013). The second site was Luminao Reef (N13.4652417, E144.6477483; N13.465467, E144.648050) which was a more isolated reef on the seaward side of the breakwater for Guam’s major port. We measured respiration, gross primary production, 15N ammonium uptake to corals, related nitrogen cycling fluxes in the tanks (reminerization, net uptake, nitrification).

openCC (other)May 2024View details →

opencc-by-4.0Feb 2020View details →

MRI and unbiased averages of wild muskrats (Ondatra zibethicus) and red squirrels (Tamiasciurus hudsonicus)

Preprocessed data from: Amuno, S., Rudko, D.A., Gallino, D., Tuznik, M., Shekh, K., Kodzhahinchev, V., Niyogi, S., Chakravarty, M.M., Devenyi, G.A., 2020. Altered neurotransmission and neuroimaging biomarkers of chronic arsenic poisoning in wild muskrats (Ondatra zibethicus) and red squirrels (Tamiasciurus hudsonicus) breeding near the City of Yellowknife, Northwest Territories (Canada). Sci. Total Environ. 707, 135556. https://doi.org/10.1016/j.scitotenv.2019.135556   As well as averages and brain masks generated during DBM processing. Files in both MINC2 and NIFTI format.

opencc-by-4.0Mar 2020View details →

Model outputs for validation and inference of high‐resolution information (downscaling) of ENETwild abundance model for wild boar, January 2020 update

These maps are models obtained in intermediate phases of the ENETWILD project based on available information. There are frequent updates in order to improve the results. Objectives: - Validation of previously produced hunting yield maps and new ones - Downscaling to 10x10 km grid >>> file  "January_2020_HY_nut01_10x10.tif" - Downscaling to 2x2 km grid   >>> file "January_2020_HY_nut00_2x2.tif" Model settings and predictors:     - Assuming cells as municipality in 10x10 km grid downscaling - Assuming cells as hunting grounds in 2x2 km grid downscaling     Conclusions guiding future methodological steps: - To update wild boar hunting yield data for some specific regions - To increase hunting yield data resolution - To explore model independent parametrization for each bioregion For further details and methodological approach see the paper: ENETWILD-consortium, P. Acevedo, S .Croft, G C Smith, J. A. Blanco-Aguiar, J. Fernandez-Lopez, M. Scandura, M. Apollonio, E.Ferroglio, Oliver Keuling, M. Sange, S. Zanet, F. Brivio, T. Podgórski, K.Petrović, G. Body, A.  Cohen, R. Soriguer, J. Vicente (2020) Validation and inference of high-resolution information (downscaling) of ENETwild abundance model for wild boar. EFSA supporting publication 2020:EN-1787. 23pp. doi:10.2903/sp.efsa.2020.EN-1787. Permission for reuse hunting yield outputs is granted under the terms indicated  by EFSA.

opencc-by-4.0Mar 2020View details →

Model outputs for occurrence and hunting data‐based models of wild boar distribution and abundance, July 2019 update

These maps  are wild boar habitat suitability outputs based on newly available data of wild boar, and models for predicting wild boar relative abundance using hunting yields. Objectives: - Validation of previously produced hunting yield maps and new ones - Downscaling to 10x10 km grid - Downscaling to 2x2 km grid Model settings and predictors:     - Model from ENETWILD report August 2019 - Assuming cells as municipality in 10x10 km grid downscaling - Assuming cells as hunting grounds in 2x2 km grid downscaling     Conclusions guiding future methodological steps - To update wild boar hunting yield data for some specific regions; - To increase hunting yield data resolution; - To explore model independent parametrization for each bioregion. Files: August_2019_HY_nut00_10x10        >> Model outputs based on hunting yield GLM analyses August_2019_occurrences_bioclim   >> Model outputs based on Bioclim analyses August_2019_occurrences_glm         >> Model outputs based on Generalised linear model August_2019_occurrences_ksvm      >> Model outputs based on Support vector Machine analyses August_2019_occurrences_maxent   >> Model outputs based on Maxent analyses August_2019_occurrences_randomForest>> Model outputs based on Random Forest analyses --------------------------------------------------------------------------------------------------------------------------------------------------------- These maps are models obtained in intermediate phases of the ENETWILD project based on available information.  There are frequent updates in order to improve the results. For methodological approach and details check the paper:  ENETWILD‐consortium, P. Acevedo, S .Croft, G C Smith, J. A. Blanco-Aguiar, J. Fernandez-Lopez, M. Scandura, M. Apollonio, E.Ferroglio, Oliver Keuling, M. Sange, S. Zanet, F. Brivio, T. Podgórski, K.Petrović, G. Body, A.  Cohen, R. Soriguer, J. Vicente (2019). ENETwild modelling of wild boar distribution and abundance: update of occurrence and hunting data‐based models. EFSA Supporting Publications, 16(8), 1674E. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fefsa.onlinelibrary.wiley.com%2Fdoi%2Fabs%2F10.2903%2Fsp.efsa.2019.EN-1674&data=02%7C01%7C%7Ca8ad922eefde42f5cb5208d7c5054851%7C406a174be31548bdaa0acdaddc44250b%7C1%7C0%7C637194498792136402&sdata=fqdiYEOqYIlHaDbp5a7kVdGQ6FWuFEydJNhSWOghH%2FQ%3D&reserved=0">https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/sp.efsa.2019.EN-1674</a> . Permission for reuse occurrence  outputs records is granted under the terms of a CC-BY-NC license. Permission for reuse hunting yield outputs is granted under the terms indicated by EFSA.

opencc-by-4.0May 2020View details →

Model outputs for update of occurrence and hunting yield-based data models for wild boar at European scale: new approach to handle the bioregion effect, May 2020 update

These maps are models obtained in intermediate phases of the ENETWILD project based on available information. There are frequent updates in order to improve the results. Objectives: - Incorporate additional data to provide new maps of wild boar suitability with a resolution of 2x2 km >>> file 3_June_2020_suitability_2x2.tif - New model based on hunting yield with different approaches to handle the biorregion effect >>> files 1_June_2020_HY_nut01_10x10_twostep.tif  &  2_June_2020_HY_nut01_10x10_pca.tif Model settings and predictors:     - Hunting yield modeling including biorregion effect as bioclimatic PCA scores - Hunting yield addressing biorregion effect in a two-step procedure with independent parametrization for each bioregion Conclusions guiding future methodological steps: - For wild boar suitability maps at 2x2 km, additional data on survey effort is critical in the southern bioregion - Hunting yield model predictions at 10x10 km grids overestimated the hunting bag numbers obtained from the external datasets - HY model with independent parametrization for each bioregion performed better that previous and new strategies For further details and methodological approach see the paper: ENETWILD-consortium, P. Acevedo, S .Croft, G C Smith, J. A. Blanco-Aguiar, J. Fernandez-Lopez, M. Scandura, M. Apollonio, E.Ferroglio, Oliver Keuling, M. Sange, S. Zanet, F. Brivio, T. Podgórski, K.Petrović, Soriguer, J. Vicente (2020) update of occurrence and hunting yield-based data models for wild boar at European scale: new approach to handle the bioregion effect. EFSA supporting publication 2020 TO BE COMPLETED Permission for reuse hunting yield outputs is granted under the terms indicated  by EFSA.

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Chromosomal-level genome assembly of the scimitar‐horned oryx: insights into diversity and demography of a species extinct in the wild

Captive populations provide a valuable insurance against extinctions in the wild. However, they are also vulnerable to the negative impacts of inbreeding, selection and drift. Genetic information is therefore considered a critical aspect of conservation management. Recent developments in sequencing technologies have the potential to improve the outcomes of management programmes; however, the transfer of these approaches to applied conservation has been slow. The scimitar‐horned oryx (Oryx dammah) is a North African antelope that has been extinct in the wild since the early 1980s and is the focus of a large‐scale and long‐term reintroduction project. To enable the selection of suitable founder individuals, facilitate post‐release monitoring and improve captive breeding management, comprehensive genomic resources are required. Here, we used 10X Chromium sequencing together with Hi‐C contact mapping to develop a chromosomal‐level genome assembly for the species. The resulting assembly contained 29 chromosomes with a scaffold N50 of 100.4 Mb, and displayed strong chromosomal synteny with the cattle genome. Using resequencing data from six additional individuals, we demonstrated relatively high genetic diversity in the scimitar‐horned oryx compared to other mammals, despite it having experienced a strong founding event in captivity. Additionally, the level of diversity across populations varied according to management strategy. Finally, we uncovered a dynamic demographic history that coincided with periods of climate variation during the Pleistocene. Overall, our study provides a clear example of how genomic data can uncover valuable insights into captive populations and contributes important resources to guide future management decisions of an endangered species.

opencc-zeroJun 2020View details →

opencc-by-4.0Mar 2020View details →

Structural Profiling of Web Sites in the Wild

The dataset contains and processes results of a large-scale survey of 708 websites, made in December 2019, in order to measure various features related to their size and structure: DOM tree size, maximum degree, depth, diversity of element types and CSS classes, among others. The goal of this research is to serve as a reference point for studies that include an empirical evaluation on samples of web pages. See the Readme.md file inside the archive for more details about its contents.

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Adaptive changes in the genomes of wild rabbits after 16 years of viral epidemics

Since its introduction to control overabundant alien rabbits (Oryctolagus cuniculus), the highly virulent Rabbit Haemorrhagic Disease Virus (RHDV) has caused regular annual disease outbreaks in Australian rabbit populations. Although initially reducing rabbit abundance by 60%, continent-wide, experimental evidence has since indicated increased genetic resistance in wild rabbits that have experienced RHDV-driven selection. To identify genetic adaptations, which explain the increased resistance to this biocontrol virus, we investigated genome-wide SNP (single nucleotide polymorphism) allele frequency changes in a South Australian rabbit population that was sampled in 1996 (pre-RHD genomes) and after 16 years of RHDV outbreaks. We identified several SNPs with changed allele frequencies within or in proximity of genes that have roles potentially important for increased RHD resistance. Many of the identified genes are known to be involved in virus infections or immunity, or had previously been identified as being differentially expressed in healthy vs. acutely RHDV-infected rabbits. Furthermore, we show in a simulation study that the allele/genotype frequency changes cannot be explained by drift alone, and that several candidate genes had also been identified as being associated with surviving RHD in a different Australian rabbit population. Our unique dataset allowed us to identify candidate genes for RHDV resistance that have evolved under natural conditions, and over a time span that would not have been feasible to study in an experimental setting. Moreover, it provides a rare example of host genetic adaptations to virus-driven selection in response to a suddenly emerging infectious disease.

opencc-zeroJun 2020View details →

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Paternal effects in a wild-type zebrafish implicate a role of sperm-derived small RNAs

While the importance of maternal effects has long been appreciated, a growing body of evidence now points to the paternal environment having an important influence on offspring phenotype. Indeed, research on rodent models suggests that paternal stress leaves an imprint on the behaviour and physiology of offspring via non-genetic information carried in the spermatozoa, however fish have been understudied with regard to these sperm-mediated effects. Here we investigated whether the zebrafish was subject to heritable influences of paternal stress by exposing males to stressors (conspecific-derived alarm cue, chasing, and bright light) before mating and assessing the behavioural and endocrine responses of their offspring, including their behavioural response to conspecific-derived alarm cue. We found that after males are exposed to stress, their larval offspring show weakened responses to stressors. Small RNA sequencing subsequently revealed that the levels of several small noncoding RNAs, including microRNAs, PIWI-interacting RNAs, and tRNA-derived small RNAs, were altered in the spermatozoa of stressed fathers, suggesting that stress-induced alterations to the spermatozoal RNA landscape may contribute to shaping offspring phenotype. The work demonstrates that paternal stress should not be overlooked as a source of phenotypic variation and that spermatozoal small RNAs may be important intergenerational messengers in fish.

opencc-zeroJul 2020View details →

opencc-by-4.0Sep 2015View details →

Figure 7 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina

Figure 7. Mean number of (a) above-ground nesting bee individuals, (b) floral specialist bee individuals, (c) oligolectic bee individuals and (d) oil-collecting bee individuals in cropped area (n = 28 points) and semi-natural area (n = 11 points). ns indicates a non-significant result. Asterisks indicate that means are significantly different (Wilcoxon rank sum test, ** = P <0.01). Bars show SEs.

opencc-by-4.0Sep 2015View details →

Figure 2 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina

Figure 2. Semi-natural area of the study site: (a) semi-natural grassland; (b) the stream 'Arroyo Dulce' and its banks (Photos: Violette Le Féon).

Figure 11 in Environmental influences on movements and distribution of a wild horse (Equus caballus) population in western Nevada, USA: a 25-year study

Figure 11. Relationships of human presence, horse key summer range (KSR) use, and lion numbers in the Montgomery Pass Wild Horse Territory (MPWHT). Human presence (May– September) is presented as per cent of its highest year. Horse KSR use is presented as per cent of the total population using the KSR. Adult lion numbers are presented as the percentage of the maximum single-year lion number.

Figure 6 in Environmental influences on movements and distribution of a wild horse (Equus caballus) population in western Nevada, USA: a 25-year study

Figure 6. Montgomery Pass Wild Horse Territory (MPWHT) horse use of non-key summer range (KSR) areas. Use outside the MPWHT primarily includes areas east of Basalt and west of Adobe Valley.

Figure 5. Changes from 1987 in Environmental influences on movements and distribution of a wild horse (Equus caballus) population in western Nevada, USA: a 25-year study

Figure 5. Changes from 1987 to 2007 in patterns of the geographic distribution of wild horses in the Montgomery Pass Wild Horse Territory (MPWHT). The central, lightly shaded area is the key summer range (KSR). The black mark within it is the highest elevation in the Territory (elevation decreases 360 degrees around it throughout). Dark shaded areas indicate regular horse use and represent> 90% of the population. Many wild horse populations in the intermountain west accommodate to seasonal conditions, spending winter at lower elevations and summer at higher elevations. The pattern across years in the MPWHT changed from summer horse concentration in the KSR to decreasing return to KSR from winter range. In addition to establishment of decreased KSR use and increased year-round use of historical winter-range areas, expansion of the geographic use areas occurred in the latter, including seasonal use beyond MPWHT map boundaries.

Figure 8 in Environmental influences on movements and distribution of a wild horse (Equus caballus) population in western Nevada, USA: a 25-year study

Figure 8. The relationship of key summer range (KSR) horse use and carrying capacity in the context of the Montgomery Pass Wild Horse Territory (MPWHT) horse population. As KSR horse numbers decreased, use outside the KSR increased. Total population range use is presented as a percentage of KSR carrying capacity. As total population increased across years, it remained <80% of carrying capacity for KSR alone, suggesting that considerable population growth can continue without reaching carrying capacity.