Find research datasets worth reusing

opencc-by-4.0Nov 2021View details →

Data & R-Code for "Weather and food availability additively affect reproductive output in an expanding raptor population"

Abstract The joint effects of interacting environmental factors on key demographic parameters can exacerbate or mitigate the separate factors’ effects on population dynamics. Given ongoing changes in climate and land use, assessing interactions between weather and food availability on reproductive performance is crucial to understand and forecast population dynamics. By conducting a feeding experiment in 4 years with different weather conditions, we were able to disentangle the effects of weather, food availability and their interactions on reproductive parameters in an expanding population of the red kite (Milvus milvus), a conservation-relevant raptor known to be supported by anthropogenic feeding. Brood loss occurred mainly during the incubation phase, and was associated with rainfall and low food availability. In contrast, brood loss during the nestling phase occurred mostly due to low temperatures. Survival of last-hatched nestlings and nestling development was enhanced by food supplementation and reduced by adverse weather conditions. However, we found no support for interactive effects of weather and food availability, suggesting that these factors affect reproduction of red kites additively. The results not only suggest that food-weather interactions are prevented by parental life-history trade-offs, but that food availability and weather conditions are crucial separate determinants of reproductive output, and thus population productivity. Overall, our results suggest that the observed increase in spring temperatures and enhanced anthropogenic food resources have contributed to the elevational expansion and the growth of the study population during the last decades.

opencc-by-4.0Jan 2022View details →

Data and code for 'Age structure of amphibian populations with endemic chytridiomycosis, across climatic regions with markedly different infection risk'

This repository provides all data and R code from the analysis presented in the following paper: Turner, A., Heard, G., Hall, A., Wassens, S. (in review). Age structure of amphibian populations with endemic chytridiomycosis, across climatic regions with markedly different infection risk. The data are provided as a series of .csv files, R script and two zip folders of R packages (Surv_mod and VB_mod) 1. Skeleto_dat_ready_Jan2021.csv Data from frog surveys conducted by Anna Turner 2. Geoffs_data.csv Data from frog surveys conducted by Geoff Heard 3. Environmental_variables_skeleto.csv Environmental data collected during surveys  4. sk.dat_July21.csv Collated data from Anna and Geoff - created by 'Data_collation_for_analysis_2.R' ready for analysis 5. Variables_that_are_highly_correlated_with_each_other_season_wide.csv Testing for correlation 6. Model_structure_skeleto_2.csv creates model structure for analysis 7. Model_selection_statistics_June_21.csv Output from model R code is provided seperately for each of the following components: 1. Data_collation_for_analysis_2.R Collating data from Anna and Geoffs datasets 2. Skeleto_analysis_5.R - First uses regression modelling to explore factors correlated with variation in age                                          - Following Scheele et al. (2016) regression models with a poisson distribution                                          - Use bayesian non-linear regression to fit the Von Bertalanffy growth model to size-at-age data                                          - Plots male and female growth curves                                          - Uses catch curve approach to estimate survival from best fitting regression model following Scroggie                                                   (2012) but with bayesian implementation

opencc-by-4.0Jun 2024View details →

Variant dataset and code for "Population-level whole genome sequencing of Ascochyta rabiei identifies genomic loci associated with isolate aggressiveness"

This dataset contains genetic variants (SNPs) of Ascochyta rabiei isolates and the R code used in their analysis to generate the results and figures described in the manuscript "Population-level whole genome sequencing of Ascochyta rabiei identifies genomic loci associated with isolate aggressiveness". <div> <div> </div> </div>

openapache2.0Jun 2019View details →

CellSIUS provides sensitive and specific detection of rare cell populations from complex single cell RNA-seq data: Codes and processed data

Codes and processed data to reproduce the analysis discussed in:  Wegmann et Al., CellSIUS provides sensitive and specific detection of rare cell populations from complex single cell RNA-seq data, Genome Biology 2019 (Accepted)

restrictedcc-by-4.0Jul 2024View details →

Data and code from: "Building multidimensional tolerance landscapes to predict the population dynamics of bacteria exposed to antibiotics in urban sewers"

City sewers harbor diverse bacterial communities exposed to various antibiotic residues resulting from human consumption and excretion. Although these residues typically occur at sub-inhibitory concentrations, they can still impact the growth rate and yield of susceptible wastewater bacteria. Many bacteria exhibit antibiotic tolerance through transient phenotypic changes. Antibiotic residues, combined with complex environmental factors like temperature and salinity, especially in coastal cities, contribute to non-additive interactions that modulate antibiotic tolerance and affect population dynamics. To better understand these interactions, we developed continuous multivariate tolerance landscapes for three bacterial species: Escherichia coli, the emerging pathogen Streptococcus suis, and the sewer-inhabiting Arcobacter cryaerophilus. We modeled their intrinsic growth rates and carrying capacities across complex environments, incorporating temperature, salinity, and concentrations of two antibiotics (ciprofloxacin and azithromycin). Using these multivariate tolerance curves, we predicted microbial population dynamics in two sewers of Barcelona, highlighting the importance of environmental complexity in shaping microbial responses to antibiotic stressors.   Usage Users can perform the analysis by running the R script (TC3D.R) after the installation of all package mentioned in the preamble,  This folder contains: - 3 datasets with OD measures for the 3 species:               * data_acrya.xlsx               * data_ecoli.xlsx               * data_ssuis.xlsx - 1 excel files with metadata (plate, well, species, environmental conditions)               * map_plate_all.xlsx - 4 datasets giving time series of the flow and several measures including  conductivity and   temperaturefor 2 sewers of Barcelona obtained from sample cabines  set during the implementation of SCOREWATER (ID:820751)               * carmel_flow.csv               * carmel_quality.csv               * poblenou_flow.csv               * poblenou_quality.csv - 1 C++ script compiled and run with the R TMB package:               * fit_growth_r_K_SS_treatment.cpp : computes the negative loglikelihood for r and K, and state DOs, given the observed DO, for the populations under one same environmental treatment (salinity * temperature * antibiotic), and computes the density-dependence parameter alpha from r and K using the Delta Method.

opencc-by-4.0May 2022View details →

Datasets, reproducible codes, and results for evaluating differential expression analysis methods on population-level RNA-seq data

This upload contains the necessary R codes and data to reproduce the FDR and Power results described in our correspondence "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives" to Li Y, Ge X, Peng F, Li W, Li JJ, Exaggerated false positives by popular differential expression methods when analyzing human population samples, Genome Biology 23, 79, 2022, DOI: 10.1186/s13059-022-02648-4.

opencc-by-4.0Jan 2023View details →

Open-population models for estimating roadkill rates - Data and R Code

Roadkill carcass capture-recapture data, capture histories for four and eight-occasion designs, and R code (with JAGS code) for roadkill rates estimation.

opencc-by-4.0Mar 2020View details →

R code and radiocarbon dates to reproduce figures and results of our paper "Population dynamics ..."

R Codes and dataset to reproduce figures and results of the paper Population dynamics during the Neolithic transition and the onset of megalithism in Portugal according to summed probability distribution of radiocarbon determinations.

opencc-by-4.0Oct 2024View details →

The chart of rapid population synthesis codes

A simplified chart of the current state-of-the-art population synthesis codes.  <h3>Chart Interpretation</h3> The river of the maps indicates detailed stellar evolution codes and stellar evolution tracks: <ul> <li>STARS (<a href="https://ui.adsabs.harvard.edu/abs/2011ascl.soft07008E/abstract">Eggleton et al., 2011, Astrophysics Source Code Library</a>)</li> <li>MESA (<a href="https://ui.adsabs.harvard.edu/abs/2011ApJS..192....3P/abstract">Paxton et al., 2011, ApJS, 192, 3</a>)</li> <li>PARSEC (<a href="https://ui.adsabs.harvard.edu/abs/2012MNRAS.427..127B/abstract">Bressan et al., 2012, MNRAS, 427, 127</a>)</li> <li>FRANEC (<a href="https://ui.adsabs.harvard.edu/abs/2008Ap%26SS.316...25D/abstract">Degl'Innocenti et al., 2008, Astrophys.Space Sci., 316, 25</a>)</li> <li>BASTI (<a href="https://ui.adsabs.harvard.edu/abs/2013A%26A...558A..46P/abstract">Pietrinferni et al., 2013, A&A, 558, 46</a>)</li> <li>GENEC (<a href="https://ui.adsabs.harvard.edu/abs/2008Ap%26SS.316...25D/abstracthttps://ui.adsabs.harvard.edu/abs/2008Ap%26SS.316...43E/abstract">Eggenberger et al., 2008, Astrophys.Space Sci., 316, 43</a>)</li> <li>BRUSSELS (<a href="https://ui.adsabs.harvard.edu/abs/2004NewAR..48..861D/abstract">De Donder & Vanbeveren, 2004,  New Astron.Rev. 48, 861</a>)</li> <li>BEC (<a href="https://iopscience.iop.org/article/10.1086/308158">Heger et al., 2000,  ApJ, 528, 368</a>)</li> </ul> The cities represent rapid population synthesis codes and their vicinity to a given (or multiple) rivers indicates that the stellar evolution recipes are taken from that stellar evolution code or track.   In particular, the codes in the BSE island follow stellar evolution by  fitting equations based on the <a href="https://ui.adsabs.harvard.edu/abs/1998MNRAS.298..525P/abstract">Pols+98 </a>stellar tracks made with the code STARS: <ul> <li>BSE (<a href="https://ui.adsabs.harvard.edu/abs/2002MNRAS.329..897H/abstract">Hurley et al., 2002, MNRAS, 329, 897</a>)</li> <li>MOBSE (<a href="http://dx.doi.org/10.1093/mnras/sty1999">Giacobbo N. & Mapelli M., 2018, MNRAS, 480, 2011</a>)</li> <li>BSEEMPH (<a href="https://arxiv.org/pdf/2110.10846">Tanikawa, A., 2022, AJ, 926, 83</a>)</li> <li>STAR TRACK (<a href="https://ui.adsabs.harvard.edu/abs/2008ApJS..174..223B/abstract">Belczynski K., et al., 2008, ApJS, 174, 223</a>)</li> <li>COSMIC (<a href="http://dx.doi.org/10.3847/1538-4357/ab9d85">Breivik K. et al., 2020, ApJ, 898, 71</a>)</li> <li>BINARY_C (<a href="http://dx.doi.org/10.1051/0004-6361:20066129">Izzard R. G., 2006, A&A, 460, 565</a>)</li> <li>COMPAS (<a href="http://dx.doi.org/10.3847/1538-4365/ac416c">Riley J. et al., 2022, ApJS, 258, 34</a>)</li> <li>SEBA (<a href="https://ui.adsabs.harvard.edu/abs/1996A%26A...309..179P/abstract">Portegies Zwart S. F. & Verbunt F., 1996, A&A, 309, 179</a>)</li> <li>BSELEVELC (<a href="https://academic.oup.com/mnras/article/511/3/4060/6484809">Kamlah A. W. H. et al., 2022, MNRAS, 511, 4060</a>)</li> </ul> Within the BSE island there are the Triple Peaks mountains referring to code implementing also formalisms for triple or multiple system evolutions. The one I am aware of all uses the BSE-like formalism for stellar and binary evolution and they are represtend by towers in the mountains: <ul> <li>TSE (<a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.1406S/abstract">Stegmann et al., 2022, MNRAS, 516, 1406</a>)</li> <li>TRES (<a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.516.1406S/abstract">Toonen et al., 2017, AAS, 229, 326</a>)</li> <li>MSE (<a href="https://ui.adsabs.harvard.edu/abs/2021MNRAS.502.4479H/abstract">Hamers et al., 2021, MNRAS, 502, 4479</a>)</li> <li>TRIPLE_C (<a href="https://ui.adsabs.harvard.edu/abs/2013MNRAS.430.2262H/abstract">Hamers et al., 2013, MNRAS, 430, 2262</a>)</li> </ul> The cities on the Interpolator lakes are codes that include stellar evolution by interpolating a set of stellar tracks, so in principle, they are not connected to any specific stellar evolution codes. The cities are anyway arranged to reflect stellar evolution models that have been mostly used in connection with the code (e.g. PARSEC and MESA for SEVN, MESA for MIST, BRUSSELS for COMBINE): <ul> <li>SEVN (<a href="https://ui.adsabs.harvard.edu/abs/2023MNRAS.524..426I/abstract">Iorio et al., 2023, MNRAS, 524, 426</a>)</li> <li>COMBINE  (<a href="http://dx.doi.org/10.1093/mnras/sty2190">Kruckow M. et al.,  2018, MNRAS, 481, 1908</a>)</li> <li>METISSE (<a href="http://dx.doi.org/10.1093/mnras/staa2264">Agrawal P. et al., 2020, MNRAS, 497, 4549</a>)</li> <li>MINT (<a href="https://doi.org/10.1093/mnras/stad2048">Mirouh et al., 2023, MNRAS, 524, 3978</a>)</li> <li>TRILEGAL (<a href="https://ui.adsabs.harvard.edu/abs/2005A%26A...436..895G/abstract">Girardi L., et al., 2005, 436, 895</a>)</li> </ul> The other cities present on the map indicate the codes: <ul> <li>STARBUST99 (<a href="https://ui.adsabs.harvard.edu/abs/1999ApJS..123....3L/abstract">Leitherer, C. et al., 1999, ApJS, 123, 3</a>)</li> <li>IBIS (<a href="http://dx.doi.org/10.1093/mnras/280.4.1035">Tutukov A. & Yungelson L., 1996, MNRAS, 280, 1035</a>)</li> <li>SCENARIO_MACHINE (<a href="https://ui.adsabs.harvard.edu/abs/1996A%26A...310..489L/abstract">Lipunov V. M. et al., 1996, A&A, 310, 489</a>)</li> </ul> The STARBUST99 code focuses mostly on modelling the spectroscopic properties of galaxies and uses the Geneva stellar evolution models. For the the last two codes, I was not able to find a direct connection to any of the known stellar evolution codes, therefore I put them somewhere close to a Glacier and I put a Dragon to refer to the famous sentence "hic sunt dracones" to indicate my ignorance about the details of the two codes. The three codes represented by ships are population synthesis codes that hybrid between detailed stellar and binary evolution models and population synthesis. They are located on the rivers related to the detailed codes they are based on: <ul> <li>BRUSSELS pop synth (<a href="https://ui.adsabs.harvard.edu/abs/2004NewAR..48..861D/abstract">Donder & Vanbeveren, 2004,  New Astron.Rev. 48, 861</a>)</li> <li>BPASS (<a href="http://dx.doi.org/10.1017/pasa.2017.51">Eldridge et al., 2017, PASA, 34, e058</a>)</li> <li>POSYDON (<a href="http://dx.doi.org/10.3847/1538-4365/ac90c1">Fragos T. et al., 2023, ApJS, 264, 45</a>)</li> </ul> <h3>Disclaimer</h3> The map represents an oversimplification for the sake of visualisation. The order of names, their fontsizes and relative locations, and possible Typos and errors do not have any specific meaning and do not "hide" any personal opinion of the authors.  If you want to suggest changes, additions or ask to remove a given code please send me an email at giuliano.iorio.astro@gmail.com

opencc-zeroFeb 2024View details →

Data and R code used in: Plant geographic distribution influences chemical defenses in native and introduced Plantago lanceolata populations

Plants growing outside their native range may be confronted by new regimes of herbivory, but how this affects plant chemical defense profiles has rarely been studied. Using Plantago lanceolata as a model species, we investigated whether introduced populations show significant differences from native populations in several growth and chemical defense traits. Plantago lanceolata (ribwort plantain) is an herbaceous plant species native to Europe and Western Asia that has been introduced to numerous countries worldwide. We sampled seeds from nine native and ten introduced populations that covered a broad geographic and environmental range and performed a common garden experiment in a greenhouse, in which we infested half of the plants in each population with caterpillars of the generalist herbivore Spodoptera littoralis. We then measured size-related and resource-allocation traits as well as the levels of constitutive and induced chemical defense compounds in roots and shoots of P. lanceolata. When we considered the environmental characteristics of the site of origin, our results revealed that populations from introduced ranges were characterized by an increase of chemical defense compounds without compromising plant biomass. The concentrations of iridoid glycosides and verbascoside, the major anti-herbivore defense compounds of P. lanceolata, were higher in introduced populations than in native populations. In addition, introduced populations exhibited greater rates of herbivore-induced volatile organic compound emission and diversity, and similar chemical diversity based on untargeted analyses of leaf methanol extracts. In general, the geographic origin of the populations had a significant influence on morphological and chemical plant traits, suggesting that P. lanceolata populations are not only adapted to different environments in their native range but also in their introduced range.

opencc-zeroMar 2024View details →

Data and code for: Nonlinear life table response analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. In this study, we compare the relative efficacy of linear and second-order LTRE analyses in capturing changes in population growth rate caused by environmental driver changes. To explore this question, we analyze demographic data collected for three long-lived plant species: Ardisia escallonioides (Pascarella & Horvitz, 1998), Silene acaulis, and Bistorta vivipara (Doak & Morris, 2010). This repository includes data files containing vital rate (survival, growth, reproduction) observations or models for our three case studies, as well as an R script in which we use these demographic data to calculate linear and second-order LTRE approximations of changes in population growth rate for each system and generate the figures we present in our paper.

opencc-by-4.0Oct 2024View details →

CEAD Population Survey Quito: Data and Variable Code Equivalencies

We conducted a cross-sectional study with 656 adults from health district 17D06, South Quito, Ecuador, using multi-stage cluster sampling. The study followed an adapted WHO STEPwise approach, considering Ecuador's 2018 STEPwise survey. For more information, contact Clara Blanes Mira: c.blanes@umh.es

opencc-zeroNov 2021View details →

Data and R code from: Relics of beavers past: time and population density drive scale-dependent patterns of ecosystem engineering

Like many ecological processes, natural disturbances exhibit scale-dependent dynamics that are largely a function of the magnitude, frequency, and scale at which they are assessed. Ecosystem engineers create patch-scale disturbances that affect ecological processes, yet we know little about how these effects scale across space or vary through time. Here, we investigate how patch disturbances by beavers (Castor canadensis), ecosystem engineers renowned for their pond-creation behavior, affect ecological processes across space and time. We evaluated how beaver population recovery influenced surface water dynamics in relation to population density over 70 years across multiple spatial scales (pond, watershed, and regional) in northern Minnesota. Surface water area was positively related to population density at the watershed scale; however, despite variation in beaver densities (and therefore surface water area) at the watershed scale, regional-scale surface water area was stable through time. This stability appears to have been driven by asynchronous beaver density fluctuations among watersheds, combined with the increasing importance of abandoned ponds. Beavers initially created and occupied larger ponds with greater surface water area, but through time shifted towards occupying smaller ponds. As ponds accumulated on the landscape proportionally more surface water was stored within abandoned ponds, which offset the smaller size of occupied ponds. Beaver engineering—driven by density-dependent mechanisms and the legacy effects from abandoned ponds—not only follows general patterns of patch disturbance dynamics by creating a spatial mosaic of patches, but the organism-created mosaic also appears to generate ecological stability at greater spatial scales. We suggest restoring beavers to landscapes is a viable method for increasing surface water storage and will ultimately help advance numerous conservation and rewilding objectives. Our study demonstrates that ecosystem engineering effects can be scale-dependent, indicating researchers should evaluate the ecological impact of engineers across diverse spatiotemporal scales to fully understand their functional roles in ecosystems.

opencc-zeroDec 2021View details →

Sequential and efficient neural-population coding of complex task information

Condensed neural and behavioral data, included secondary results from model fits and analyses. This dataset contains all information required to recreate figures from the paper.

opencc-by-4.0Feb 2022View details →

Data and code for "Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago"

This dataset contains the modeling results GIS data (maps) of the study “Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago” by Rodríguez et al. (2022). The NPP data (npp.zip) was computed using an empirical formula (the Miami model) from palaeo temperature and palaeo precipitation data aggregated for each timeslice from the Oscillayers dataset (Gamisch, 2019), as defined in Rodríguez et al. (2022, in review). The Population densities file (pop_densities.zip) contains the computed minimum and maximum population densities rasters for each of the defined MIS timeslices. With the population density value Dc in logarithmic form log(Dc). The Species Distribution Model (sdm.7z) includes input data (folder /data), intermediate results (folder /work) and results and figures (folder /results). All modelling steps are included as an R project in the folder /scripts. The R project is subdivided into individual scripts for data preparation (1.x), sampling procedure (2.x), and model computation (3.x). The habitat range estimation (habitat_ranges.zip) includes the potential spatial boundaries of the hominin habitat as binary raster files with 1=presence and 0=absence. The ranges rely on a dichotomic classification of the habitat suitability with a threshold value inferred from the 5% quantile of the presence data. The habitat suitability (habitat_suitability.zip) is the result of the Species Distribution Modelling and describes the environmental suitability for hominin presence based on the sites considered in this study. The values range between 0=low and 1=high suitability. The dataset includes the mean (pred_mean) and standard deviation (pred_std) of multiple model runs.

opencc-zeroJun 2022View details →

Code: A model of wild bee populations accounting for spatial heterogeneity and climate induced temporal variability of food resources at the landscape level

The viability of wild bee populations and the pollination services that they provide are driven by the availability of food resources during their activity period and within the surroundings of their nesting sites. Changes in climate and land use influence the availability of these resources and are major threats to declining bee populations. Because wild bees may be vulnerable to interactions between these threats, spatially explicit models of population dynamics that capture how bee populations jointly respond to land use at a landscape scale and weather are needed. Here, we developed a spatially and temporally explicit theoretical model of wild bee populations aiming for a middle ground between the existing mapping of visitation rates using foraging equations and more refined agent-based modelling. The model is developed for Bombus sp. and captures within-season colony dynamics. The model describes mechanistically foraging at the colony level and temporal population dynamics for an average colony at the landscape level. Stages in population dynamics are temperature-dependent triggered with a theoretical generalized seasonal progression, which can be informed by growing degree days (GDD). The purpose of the LandscapePhenoBee model is to evaluate the impact of systematic changes and within-season variability in resources on bee population sizes and crop visitation rates. In a simulation study, we used the model to evaluate the impact of the shortage of food resources in the landscape arising from extreme drought events in different types of landscapes (ranging from different proportions of semi-natural habitats and early and late flowering crops) on bumblebee populations.

opencc-by-4.0Jul 2022View details →

Code and Data associated with "Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations"

Code and data sufficient to reproduce analyses in "Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations".

opencc-zeroJul 2022View details →

Data and code from: Cooperation and coordination in heterogeneous populations

One landmark application of evolutionary game theory is the study of social dilemmas. This literature explores why people cooperate even when there are strong incentives to defect. Much of this literature, however, assumes that interactions are symmetric. Individuals are assumed to have the same strategic options and the same potential payoffs. Yet many interesting questions arise once individuals are allowed to differ. Here, we study asymmetry in simple coordination games. In our setup, human participants need to decide how much of their endowment to contribute to a public good. If a group's collective contributions reach a pre-defined threshold, all group members receive a reward. To account for possible asymmetries, individuals either differ in their endowments or their productivities. According to our theoretical equilibrium analysis, such games tend to have many possible solutions. In equilibrium, group members may contribute the same amount, different amounts, or nothing at all. According to the behavioral experiment, however, humans favor the equilibrium in which everyone contributes the same proportion of their endowment. We use these experimental results to highlight the nontrivial effects of inequality on cooperation, and we discuss to which extent models of evolutionary game theory can account for these effects.