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172 results for “R script”
Applicability of the inverse dispersion method to measure emissions from animal housings - data set & R scripts
<h2>Data availability</h2> <p>Provided are:<br>- raw data of the instruments<br>- R Scripts to reproduce the findings in the publication<br>- R outputs</p> <h2>Scripts</h2> <p>In total, there are 10 scripts provided, of which most of them are needed to reproduce the data in the publication.</p> <p>Below, a brief explanation of the content of the different scripts.</p> <ul> <li>01_Datatreatment_01_Weatherstation.r ## This script reads in the weather station data and makes it ready for further use.</li> <li>01_Datatreatment_02_Sonics.r ## This script reads in the 3D ultrasonic data and makes it ready for further use.</li> <li>01_Datatreatment_03_GasFinder.r ## This script reads in the GasFinder data and makes it ready for further use.</li> <li>01_Datatreatment_04_MFC_Pressuresensor.r ## This script reads in the mass flow controller (MFC) and pressure sensor data and makes it ready for further use.</li> <li>02_Calculation_01_bLS.r ## This script is made to run the bLSmodelR and tailored to the number cruncher of the University of Applied Sciences BFH. The code should also work on your computer but you have to adopt the number of cores.</li> <li>02_Calculation_02_Concentration.r ## This script treats the unprocessed concentration data. It removes false concentrations, applies an intercalibration, and makes the data ready for further use.</li> <li>02_Calculation_03_Emissions.r ## This script calculates emissions and makes it ready for further use.</li> <li>02_Calculation_04_contourXYZ_Plume.r ## This script calculates the plume contours in the XY and XZ plane. This script is not necessary to reproduce the findings of the publication.</li> <li>03_Apply_filter.r ## This script applies the quality filtering and makes the data ready for further use.</li> <li>04_Plots_Tables.r ## With this script one can recreate all the plots and values in the tables of the publication, the supplement, and the initial submission.</li> </ul> <p>Note, for the geometry, there is no script provided. The coordinates of the different sensors and the source are solely provided as R output.</p> <h3>Naming of instruments</h3> <p>The instruments in the publication have different names than in the scripts. In some scripts the final names are also provided but throughout the evaluation the original device names are used. Only in the script 04_Plots_Tables.r are the final names introduced. Below is an overview of what original name corresponds to the final name of the devices:</p> <h4><strong>GasFinder instruments called 'OP' in the publication</strong></h4> <ul> <li>OP-UW = GF26</li> <li>OP-2.0h = GF17</li> <li>OP-5.3h = GF18</li> <li>OP-6.8h = GF16</li> <li>OP-12h = GF25</li> </ul> <p><strong>3D ultrasonic anemometer instruments called 'UA' in the publication</strong></p> <ul> <li>UA-UW = SonicC</li> <li>UA-2.0h = SonicA</li> <li>UA-5.3h = Sonic2</li> <li>UA-6.8h = SonicB</li> </ul> <p><strong>Source</strong><br>In some of the scripts, the source might be called 'Schopf' which is a local term for 'shed'.</p> <h2>Note</h2> <p>This code was written by Marcel Bühler (minor code chunks were originally written by Christoph Häni) and is intended to reproduce the findings of the linked publication. Please feel free to use and modify it (e.g., use it to run different dispersion models), but attribution is appreciated.</p> <h2>Disclaimer</h2> <p>I do not guarantee that everything works. It might be that not all variables were changed to English for better understanding correctly. Unfortunately, it is not possible to provide all the catalogs of the bLS run, as the total size is several 100s of GB. In case you run the bLS model on your own, the result will have a minimal difference, as no bLS run produces the same result twice. This should, however, not alter the findings.</p> <h2>Contact</h2> <p>In case you have questions, please contact Marcel Bühler (mb@bce.au.dk). In case this does not work, Christoph Häni might also be able to help (christoph.haeni@bfh.ch).</p>
Dataset and R script - Non-linear transcriptomic responses to compounded environmental changes across temperature and resources in a pest beetle, Callosobruchus maculatus
<p>This dataset contains data and R script for analysis on life history and transcriptomic responses to single dimensional changes in resource (chickpea-27<span>°</span>C) and temperature (cowpea-35<span>°</span>C) and multi-dimensional environmental changes in resource and temperature (chickpea-35<span>°</span>C) in a pest beetle, <em>Callosobruchus maculatus</em> (control treatment = cowpea-27<span>°</span>C). Dataset contains life history data collected in laboratory conditions<em> </em>(tab 1), logFC data (RNA-sequencing; Novogene Co. Ltd.) for Spearman rank correlation tests between treatments (tabs 2-4), read count data (RNA-sequencing; Novogene Co. Ltd.) for differential expression analysis using edgeR (R1-5 = Four samples at cowpea-27<span>°</span>C; R7-12 = Four samples at cowpea-35<span>°</span>C; R13-17 = Four samples at chickpea-27<span>°</span>C; R25-28 = Four samples at chickpea-35<span>°</span>C; tab 5) and edgeR output data for plotting in R (tab 6). </p>
R scripts for the practical exercises with QGIS in the book "Land Use Cover Datasets and Validation Tools"
<p>This dataset includes a series of R scripts required to carry out some of the practical exercises in the book “Land Use Cover Datasets and Validation Tools”, available in open access.</p> <p>The scripts have been designed within the context of the R Processing Provider, a plugin that integrates the R processing environment into QGIS. For all the information about how to use these scripts in QGIS, please refer to Chapter 1 of the book referred to above.</p> <p>The dataset includes 15 different scripts, which can implement the calculation of different metrics in QGIS:</p> <ul> <li>Change statistics such as absolute change, relative change and annual rate of change (Change_Statistics.rsx)</li> <li>Areal and spatial agreement metrics, either overall (Overall Areal Inconsistency.rsx, Overall Spatial Agreement.rsx, Overall Spatial Inconsistency.rsx) or per category (Individual Areal Inconsistency.rsx, Individual Spatial Agreement.rsx)</li> <li>The four components of change (gross gains, gross losses, net change and swap) proposed by Pontius Jr. (2004) (LUCCBudget.rsx)</li> <li>The intensity analysis proposed by Aldwaik and Pontius (2012) (Intensity_analysis.rsx)</li> <li>The Flow matrix proposed by Runfola and Pontius (2013) (Stable_change_flow_matrix.rsx, Flow_matrix_graf.rsx)</li> <li>Pearson and Spearman correlations (Correlation.rsx)</li> <li>The Receiver Operating Characteristic (ROC) (ROCAnalysis.rsx)</li> <li>The Goodness of Fit (GOF) calculated using the MapCurves method proposed by Hargrove et al. (2006) (MapCurves_raster.rsx, MapCurves_vector.rsx)</li> <li>The spatial distribution of overall, user and producer’s accuracies, obtained through Geographical Weighted Regression methods (Local accuracy assessment statistics.rsx).</li> </ul> <p>Descriptions of all these methods can be found in different chapters of the aforementioned book.</p> <p>The dataset also includes a readme file listing all the scripts provided, detailing their authors and the references on which their methods are based.</p>
Data and R scripts from: Assemblage reorganisation of South African dragonflies due to climate change
<p><b>Aim:</b> Climate change is expected to cause large shifts in species assemblages such as dragonflies and damselflies (Insecta: Odonata). Here we assess the influence of environmental drivers of turnover on Odonata assemblages. Secondly, we map the predicted spatial variation in species composition, first as a gradient of assemblage similarity, and then as discrete bioregions delineating major areas of odonate endemism. Finally, we map the magnitude of expected change in species turnover in response to climate change under two emission scenarios.</p> <p><b>Location:</b> South Africa</p> <p><b>Methods:</b> We used a spatial database comprising of 164 species of odonates and 20 covariates, to explore changes in compositional turnover using generalised dissimilarity models. Bioregions were compiled through various clustering techniques.</p> <p><b>Results: </b>Present-day odonate bioregions correspond to climatic zones and are clearly separated by transitional zones with rapid spatial turnover. Present odonate bioregions are projected to undergo extensive reorganisation by 2050 and 2070. Temporal turnover in species composition is expected to reach up to 80% in the large arid interior and 64% along the coast. Half of all South Africa's protected areas are likely to experience climate-induced changes to dragonfly bioregions in the near future.</p> <p><b>Main conclusions:</b> Species assemblages are rapidly changing. This work highlights future shifts in climate will result in complex and non-linear responses in Odonata communities. With ongoing climate change, current odonate bioregions are predicted to expand while others will contract considerably in size within the next thirty years. The current demarcated protected areas may be inadequate to protect dragonflies as climates change. Odonata can be used to track forefronts of climate change, which will likely affect a larger array of taxa as well.</p>
Data and R-Scripts: Predicting hotspots for invasive species introduction in Europe
<p>The .rar file comprises all data and R-scripts needed to replicate our study entitled "<em>Predicting Hotspots for Invasive Species Introduction in Europe</em>" published in <em>Environmental Research Letters</em>. The folder <em>data </em>holds all input data as well as the final datasets used for training the algorithms, in the subfolder <em>A_ML_ready_datasets</em>. The folder <em>descriptives </em>provides tables with descriptive statistics<em>. </em>The folder<em> figures </em>provides files for all figures displayed in the manuscript and the supplementary material as well as visualizations of descriptive statistics for all background approaches in the corresponding subfolders. The folder <em>results </em>holds all generated results. The folder <em>scripts</em> provides all R-scripts used for intermediate computations. The <em>master </em>and <em>master_results</em> scripts coordinate all computations and the generation of results, respectively.</p> <p>Notably, various spatial layers were used to extract point-values of features which subsequently were used to estimate the models and generate the predictions. Here, we only upload the extracted point-values in the <em>data </em>folder. If you are interested in using any of the raw spatial layers, please refer to section 2.1.3. of our publication to find the corresponding references. Alternatively, feel free to reach out to me and I will direct you to the original databases and/or send you the raw spatial layers.</p>
Host phylogeny and elevation predict infection by avian haemosporidians in a diverse New Guinean bird community (R script for analyses, figures, and supplemental figures )
<p>This script performs the glmm analysis of the elevation and infection prevalence data as well as the script required to generate the figures in the article.</p>
Data and R scripts for: Effects of hunting on genetic diversity, inbreeding and dispersal in Finnish black grouse (Lyrurus tetrix)
<p>While intensive hunting activities, such as commercial fishing and trophy hunting, can have profound influences on natural populations, less intensive recreational hunting can also have more subtle effects on animal behaviour, habitat use and movement, with implications for population persistence. Lekking species such as the black grouse (<em>Lyrurus</em> <em>tetrix</em>) may be especially prone to hunting as leks are temporally and spatially predictable, making them easy targets. Furthermore, inbreeding in black grouse is mainly avoided through female-biased dispersal, so any disruptions to dispersal caused by hunting could lead to changes in gene flow, leading to an increasing risk of inbreeding. We therefore investigated the impact of hunting on genetic diversity, inbreeding and dispersal on a metapopulation of black grouse in Central Finland. We genotyped 1,065 adult males and 813 adult females from twelve lekking sites (six hunted, six unhunted) and 200 unrelated chicks from seven sites (two hunted, five unhunted) at up to thirteen microsatellite loci. Our initial confirmatory analysis of sex-specific fine-scale population structure revealed little genetic structure in the metapopulation. Levels of inbreeding did not differ significantly between hunted and unhunted sites in both adults and chicks. However, immigration rates into hunted sites were significantly higher among adults compared to immigration into unhunted sites. We conclude that the influx of migrants into hunted sites may compensate for the loss of harvested individuals, thereby increasing gene flow and mitigating inbreeding. Given the absence of any obvious potential barriers to gene flow in Central Finland, a spatially heterogeneous matrix of hunted and unhunted regions may be crucial to ensure sustainable harvests into the future.</p>
Data and R scripts for: Ant invasions is associated with lower root density and different root distribution of a foundational savanna tree species
<p>Some invasive ants have worldwide distributions and impose substantial impacts on human society and native biodiversity. Yet we know little about how ants impact soil ecosystems in general, much less how soil ecosystems shift when invasive ants move in. We excavated the coarse roots of a monodominant savanna tree in invaded and uninvaded areas to test the hypothesis that the presence of invasive ants would be associated with changes in root distribution and biomass across the landscape. We found that in the presence of invasive ants, trees had a shifted distribution of lateral coarse roots, with proportionally less root biomass near the surface and far from tree stems. In addition, the density of lateral coarse-root biomass was ~20% lower for trees within invaded landscapes. Our results suggest that soil-nesting invasive ants can drive important changes in rooting strategy for a tree species that serves a foundational role in the biogeochemical cycles of vertisol savannas.</p>
Datasets and R script to replicate the theoretical modeling from the article entitled Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission
<p>Datasets and R script to replicate the theoretical modeling from the article entitled "<strong> </strong>Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission" by Vantaux A., Moiroux N., Dabire K. R., Cohuet A., Lefevre T. 2023</p>
Insect visits to cherry blossoms and wildflowers in sweet cherry orchards: datasets and R scripts
<p>This repository contains a number of datasets, all collected in commercial sweet cherry orchards in the West Midlands, UK between 2017-2019. Alleyways in these orchards were sown with native perennial plant species. Datasets include:</p> <p>- cherry blossom and wildflower visitors recorded on pollinator transect surveys.<br> - fruit set and quality (in 2019) from cherry blossoms which were either exposed to insects, insect-excluded, or hand-pollinated.</p> <p>Additionally, all the scripts to analyse these datasets using the software R are also included.</p>
Data and R scripts from: Using conservation genetics to prioritise management options for an endangered songbird
<p>Genetic data can be highly informative for answering questions relevant to practical conservation efforts but remain one of the most neglected aspects of species recovery plans. Framing genetic questions with reference to practical and tractable conservation objectives can help bypass this limitation of the application of genetics in conservation. Using a single-nucleotide polymorphism dataset from reduced-representation sequencing (DArTSeq), we conducted a genetic assessment of remnant populations of the endangered forty-spotted pardalote (<em>Pardalotus</em> <em>quadragintus</em>), a songbird endemic to Tasmania, Australia. Our objectives were to inform strategies for conservation of genetic diversity in the species and estimate effective population sizes and patterns of inter-population movement to identify management units relevant to population conservation and habitat restoration. We show population genetic structure and identify two small populations on mainland Tasmania as 'satellites' of larger Bruny Island populations connected by migration. Our data identify management units for conservation objectives relating to genetic diversity and habitat restoration. Although our results do not indicate the immediate need to genetically manage populations, the small effective population sizes we estimated for some populations indicate that they are vulnerable to genetic drift, highlighting the urgent need to implement habitat restoration to increase population size and to conduct genetic monitoring. We discuss how our genetic assessment can be used to inform management interventions for the forty-spotted pardalote, and show that by assessing contemporary genetic aspects, valuable information for conservation planning and decision-making can be produced to guide actions that account for genetic diversity and increase chances of recovery in species of conservation concern.</p>
R scripts for manuscript "The circulating phageome reflects bacterial infections"
<p>These are documents and an R script associated with the manuscript "The circulating phageome reflects bacterial infections".</p> <p>These include:</p> <p>1. allphagedf_seqids.csv which is a table including number of BLAST hits to unique phage Genbank IDs by sample. The samples used in this table are the 71 (61 septic, 10 asymptomatic controls) sequenced in this study. The rows of this table correspond to samples (rownames are library IDs) and columns correspond to all identified phage Genbank IDs from the blast output.</p> <p>2. Phageome Summaries.RMD which is an R markdown document which demonstrates i) processing of blast output into a new allphagedf_seqids document, ii) use of the phage dictionary to summarize representation of phage taxonomic families as well as host genuses, and iii) use of the coliphage dictionary to assess how E. coli phages represent known host bacterial characteristics across samples.</p> <p>3. Readme.txt which summarizes the above as well as provides links to other relevant data.</p>
R-script: Deterioration of respiratory health following changes to land cover and climate in Indonesia
<p>This file contains the R-script presented in "Santika, T., Muhidin, S., Haryanto, B. et al. (2023) Deterioration of respiratory health following changes to land cover and climate in Indonesia".</p> <p>** R-script.txt</p> <p>This is the main script used to produce the results of the paper, which contains three parts:</p> <ol> <li>Analysis of the change in rainfall patterns across regencies in Sumatra, Indonesia</li> <li>Analysis of the change in fire patterns across Sumatra by soil type and land cover/degradation</li> <li>Analysis of the link between respiratory illness prevalence and environmental and socio-economic variables</li> </ol>
Datasets and R script to replicate the statistical analyses from the article entitled Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission
<p>Datasets and R script to replicate the statistical analyses from the article entitled " Multiple hosts, multiple impacts: the role of vertebrate host diversity in shaping mosquito life history and pathogen transmission " by Vantaux A., Moiroux N., Dabire K. R., Cohuet A., Lefevre T. 2023</p>
Physiological constraints and cognitive chunking in Zebra Finch songs: Data and R script
<p>Learned bird songs often have a hierarchical organization. In the case of zebra finches, each bird's song is made up of a string of notes delivered in a stereotyped sequence to form a "motif", and motifs are repeated to form a song bout. During song learning, young males copy "chunks" of two or more consecutive notes from their tutors' songs. These chunks are represented as distinct units within memory (during learning) and within motor systems (during song production). During song performance, motifs may deviate from the learned sequence by stopping short, starting late, or by skipping, inserting or repeating notes. We measured acoustic and temporal variables related to the respiratory and vocal physiology of song production and asked how they related to deviations from each bird's "canonical" sequence. The best predictor of deviations from that sequence was the duration of the silent interval between notes, when inspiration normally occurs. Deviations from the canonical motif occurred less often after higher-pitched notes, perhaps because a high-low sequence forms a prosodic unit. Premature stops often followed louder and longer notes, suggesting that respiratory and muscular physiology influence the location of such stops. Boundaries between the learned chunks of a male's motif predicted where and how often non-canonical starts occurred. Physiological and cognitive elements also interacted to define the segmentation of zebra finch song sequences. Long silent intervals between notes were associated both with physiology (inspirations) and with the cognitive boundaries of learned chunks – and hence with deviations from the canonical motif.</p>
Experimental data and R scripts for simulations and analysis
<p>Zip file including the experimental data and R scripts for simulations and analysis used in the following article: "Colonisation debt: when invasion history impacts current range expansion by Morel-Journel, T., Haond M., Dunan L., Mailleret L. and Vercken E.</p>
Recolonizing native wildlife facilitates exotic plant invasion into Singapore's rain forests: Data and R script
<p>Halting biological invasions and rewilding extirpated fauna are conservation interventions to bolster biodiversity, species interactions, and ecosystems. These actions are often considered separately and the potential for reintroduced wildlife to facilitate invasive plants has been largely overlooked. Here, we investigate the role of Singapore's recolonizing native wild pigs (<em>Sus scrofa</em>) in facilitating an invasive weed <em>Miconia crenata </em>into tropical rain forests, which are normally highly resistant to invasion. We conducted line-transect surveys in 11 Singaporean rain forests and used generalized linear mixed models to consider the contribution of pigs' soil disturbances, human forest paths, and other environmental covariates, on the density of <em>M. crenata</em>. We found that <em>M. crenata</em> was more abundant at forest edges and invasion into forest interior was facilitated by pigs, paths, and canopy gaps, but that these effects were all additive, not synergistic (i.e. not multiplicative). These<span> results highlight how modern invasions are driven by multiple disturbances as well as propagule pressure (e.g. urban birds dispersing seeds at forest edges where they establish in pig soil disturbances). </span>Singapore's extensive native forest restoration efforts may have provided plentiful edge and secondary forests that are well suited to pigs and <em>M. crenata</em>, which in turn undermine the aims of fostering later-successional native plant communities. To prevent negative externalities, we suggest that plant restoration and rewilding projects consider the potential role of wildlife in facilitating non-native plants, and couple these actions with preliminary screening of unintended consequences and continued monitoring, as well as limiting human-mediated weed invasion to minimize propagule sources.</p>
Dataset and R-script for Article: Increased heat tolerance of geothermal plants comes at the cost of reduced performance under cooler conditions
<p>Dataset and R-script for Article</p> <p>"Increased heat tolerance of geothermal plants comes at the cost of reduced performance under cooler conditions"</p> <p>to be published in the Journal "Ecology and Evolution"</p>
Raw data and R Script: Bleaching coral event due to cold waters in the Gulf of California: effect on Pocillopora cryptofauna
<p>R script code and raw data to reproduce the analyses made in the study "Bleaching coral event due to cold waters in the Gulf of California: effect on Pocillopora cryptofauna" published in Coral Reefs (10.1007/s00338-023-02422-3).</p>
Learning can be detrimental for a parasitic wasp: R scripts and Telenomus podisi data
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OpenNeuro
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