cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7906997.v1
title: Table S1 from The history, genome and biology of NCTC 30: a non-pandemic <i>Vibrio cholerae</i> isolate from World War One

description: Additional genomes used in this study (attached .xls spreadsheet).
DOI: 10.6084/m9.figshare.7907000.v2
title: Table S2 from The history, genome and biology of NCTC 30: a non-pandemic <i>Vibrio cholerae</i> isolate from World War One.

description: Accession numbers for NCTC 30 genome sequencing (attached .xls spreadsheet).
DOI: 10.6084/m9.figshare.7907000.v1
title: Table S2 from The history, genome and biology of NCTC 30: a non-pandemic <i>Vibrio cholerae</i> isolate from World War One

description: Accession numbers for NCTC 30 genome sequencing (attached .xls spreadsheet).
DOI: 10.6084/m9.figshare.7928327
title: Supplementary Data 4 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Transcriptomic analysis regarding genes involved in metabolism
DOI: 10.6084/m9.figshare.7928339
title: Supplementary Data 3 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Transcriptomic analysis related to fig. 2
DOI: 10.6084/m9.figshare.7928327.v2
title: Supplementary Data 4 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Transcriptomic analysis regarding genes involved in metabolism
DOI: 10.6084/m9.figshare.7928339.v2
title: Supplementary Data 3 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Transcriptomic analysis related to fig. 2
DOI: 10.6084/m9.figshare.7928330
title: Supplementary Data 2 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Transcriptomic analysis related to fig. 1
DOI: 10.6084/m9.figshare.7928327.v1
title: Supplementary Data 4 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model

description: Transcriptomic analysis regarding genes involved in metabolism
DOI: 10.6084/m9.figshare.7928339.v1
title: Supplementary Data 3 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model

description: Transcriptomic analysis related to fig. 2
DOI: 10.6084/m9.figshare.7928330.v2
title: Supplementary Data 2 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Transcriptomic analysis related to fig. 1
DOI: 10.6084/m9.figshare.7928333
title: Supplementary Data 1 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Supplementary data (viral sequence data)
DOI: 10.6084/m9.figshare.7928330.v1
title: Supplementary Data 2 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model

description: Transcriptomic analysis related to fig. 1
DOI: 10.6084/m9.figshare.7928333.v2
title: Supplementary Data 1 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

description: Supplementary data (viral sequence data)
DOI: 10.6084/m9.figshare.7928333.v1
title: Supplementary Data 1 from Haemolymph removal by <i>Varroa</i> mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model

description: Supplementary data (viral sequence data)
DOI: 10.6084/m9.figshare.7932395
title: Dataset from The Third Plague Pandemic in Europe.

description: Collected data for plague cases in Europe from the Public Health Reports (formerly Bulletins of the Public Health and Weekly Abstract of Sanitary Reports) between 1879-1950.
DOI: 10.6084/m9.figshare.7932395.v2
title: Dataset from The Third Plague Pandemic in Europe.

description: Collected data for plague cases in Europe from the Public Health Reports (formerly Bulletins of the Public Health and Weekly Abstract of Sanitary Reports) between 1879-1950.
DOI: 10.6084/m9.figshare.7932395.v1
title: Dataset from The third plague pandemic in Europe

description: Collected data for plague cases in Europe from the Public Health Reports (formerly Bulletins of the Public Health and Weekly Abstract of Sanitary Reports) between 1879-1950.
DOI: 10.6084/m9.figshare.7937483
title: Table 1-9 from Fluctuating selection strength and intense male competition underlie variation and exaggeration of a water strider's male weapon.

description: Sexually selected traits can reach high degrees of phenotypic expression and variation under directional selection. A growing number of studies suggest that such selection can vary in space, time and form within and between populations. However, the impact of these fluctuations on sexual trait evolution is poorly understood. In the water strider <i>Microvelia longipes</i>, males display striking trait exaggeration and phenotypic variation manifested as extreme differences in the rear leg length. To study the origin and maintenance of this exaggerated trait, we conducted comparative behavioural, morphometric and reaction norm experiments in a selection of <i>Microvelia</i> species. We uncovered differences both in the mating behaviour and the degree of sexual dimorphism across these species. Interestingly, <i>M. longipes</i> evolved a specific mating behaviour where males compete for egg-laying sites, consisting of small floating objects, to intercept and copulate with gravid females. Through male–male competition assays, we demonstrated that male rear legs are used as weapons to dominate egg-laying sites and that intense competition is associated with the evolution of rear leg length exaggeration. Field observations revealed rapid fluctuation in <i>M. longipes</i> habitat stability and the abundance of egg-laying sites. Paternity tests using genetic markers demonstrated that small males could only fertilize about 5% of the eggs when egg-laying sites are limiting, whereas this proportion increased to about 20% when egg-laying sites become abundant. Furthermore, diet manipulation and artificial selection experiments also showed that the exaggerated leg length in <i>M. longipes</i> males is influenced by both genetic and nutritional factors. Collectively, our results highlight how fluctuation in the strength of directional sexual selection, through changes in the intensity of male competition, can drive the exaggeration and phenotypic variation in this weapon trait.
DOI: 10.6084/m9.figshare.7937483.v2
title: Table 1-9 from Fluctuating selection strength and intense male competition underlie variation and exaggeration of a water strider's male weapon.

description: Sexually selected traits can reach high degrees of phenotypic expression and variation under directional selection. A growing number of studies suggest that such selection can vary in space, time and form within and between populations. However, the impact of these fluctuations on sexual trait evolution is poorly understood. In the water strider <i>Microvelia longipes</i>, males display striking trait exaggeration and phenotypic variation manifested as extreme differences in the rear leg length. To study the origin and maintenance of this exaggerated trait, we conducted comparative behavioural, morphometric and reaction norm experiments in a selection of <i>Microvelia</i> species. We uncovered differences both in the mating behaviour and the degree of sexual dimorphism across these species. Interestingly, <i>M. longipes</i> evolved a specific mating behaviour where males compete for egg-laying sites, consisting of small floating objects, to intercept and copulate with gravid females. Through male–male competition assays, we demonstrated that male rear legs are used as weapons to dominate egg-laying sites and that intense competition is associated with the evolution of rear leg length exaggeration. Field observations revealed rapid fluctuation in <i>M. longipes</i> habitat stability and the abundance of egg-laying sites. Paternity tests using genetic markers demonstrated that small males could only fertilize about 5% of the eggs when egg-laying sites are limiting, whereas this proportion increased to about 20% when egg-laying sites become abundant. Furthermore, diet manipulation and artificial selection experiments also showed that the exaggerated leg length in <i>M. longipes</i> males is influenced by both genetic and nutritional factors. Collectively, our results highlight how fluctuation in the strength of directional sexual selection, through changes in the intensity of male competition, can drive the exaggeration and phenotypic variation in this weapon trait.
DOI: 10.6084/m9.figshare.7937483.v1
title: Table 1-9 from Fluctuating selection strength and intense male competition underlie variation and exaggeration of a water strider's male weapon

description: Sexually selected traits can reach high degrees of phenotypic expression and variation under directional selection. A growing number of studies suggest that such selection can vary in space, time and form within and between populations. However, the impact of these fluctuations on sexual trait evolution is poorly understood. In the water strider <i>Microvelia longipes</i>, males display striking trait exaggeration and phenotypic variation manifested as extreme differences in the rear leg length. To study the origin and maintenance of this exaggerated trait, we conducted comparative behavioural, morphometric and reaction norm experiments in a selection of <i>Microvelia</i> species. We uncovered differences both in the mating behaviour and the degree of sexual dimorphism across these species. Interestingly, <i>M. longipes</i> evolved a specific mating behaviour where males compete for egg-laying sites, consisting of small floating objects, to intercept and copulate with gravid females. Through male–male competition assays, we demonstrated that male rear legs are used as weapons to dominate egg-laying sites and that intense competition is associated with the evolution of rear leg length exaggeration. Field observations revealed rapid fluctuation in <i>M. longipes</i> habitat stability and the abundance of egg-laying sites. Paternity tests using genetic markers demonstrated that small males could only fertilize about 5% of the eggs when egg-laying sites are limiting, whereas this proportion increased to about 20% when egg-laying sites become abundant. Furthermore, diet manipulation and artificial selection experiments also showed that the exaggerated leg length in <i>M. longipes</i> males is influenced by both genetic and nutritional factors. Collectively, our results highlight how fluctuation in the strength of directional sexual selection, through changes in the intensity of male competition, can drive the exaggeration and phenotypic variation in this weapon trait.
DOI: 10.6084/m9.figshare.7937516
title: Data from A new mechanistic model of weather-dependent <i>Septoria tritici</i> blotch disease risk.

description: We present a new mechanistic model for predicting <i>Septoria tritici</i> blotch (STB) disease, parameterized with experimentally derived data for temperature- and wetness-dependent germination, growth and death of the causal agent, <i>Zymoseptoria tritici</i>. The output of this model (A) was compared with observed disease data for UK wheat over the period 2002–2016. In addition, we compared the output of a second model (B), in which experimentally derived parameters were replaced by a modified version of a published <i>Z. tritici</i> thermal performance equation, with the same observed disease data. Neither model predicted observed annual disease, but model A was able to differentiate UK regions with differing average disease risks over the entire period. The greatest limitations of both models are: broad spatial resolution of the climate data, and lack of host parameters. Model B is further limited by its lack of explicitly defined pathogen death, leading to a cumulative overestimation of disease over the course of the growing season. Comparison of models A and B demonstrates the importance of accounting for the temperature-dependency of pathogen processes important in the initiation and progression of disease. However, effective modelling of STB will probably require similar experimentally derived parameters for host and environmental factors, completing the disease triangle.This article is part of the theme issue ‘Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants Part 1’.
DOI: 10.6084/m9.figshare.7937516.v1
title: Data from A new mechanistic model of weather-dependent Septoria tritici blotch disease risk

description: We present a new mechanistic model for predicting Septoria tritici blotch (STB) disease, parametrized with experimentally derived data for temperature- and wetness-dependent germination, growth and death of the causal agent, <i>Zymoseptoria tritici</i>. The output of this model (A) was compared to observed disease data for UK wheat over the period 2002–2016. In addition, we compared the output of a second model (B), in which experimentally derived parameters were replaced by a modified version of a published <i>Z. tritici</i> thermal performance equation, to the same observed disease data. Neither model predicted observed annual disease, but model A was able to differentiate UK regions with differing average disease risks over the entire period. The greatest limitations of both models are: broad spatial resolution of the climate data, and lack of host parameters. Model B is further limited by its lack of explicitly defined pathogen death, leading to a cumulative overestimation of disease over the course of the growing season. Comparison of models A and B demonstrates the importance of accounting for the temperature-dependency of pathogen processes important in the initiation and progression of disease. However, effective modelling of STB will probably require similar experimentally derived parameters for host and environmental factors, completing the disease triangle.This article is part of the theme issue ‘Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants Part 1’.
DOI: 10.6084/m9.figshare.7944242
title: Data from Chimpanzees (<i>Pan troglodytes</i>) coordinate by communicating in a collaborative problem-solving task.

description: Data
DOI: 10.6084/m9.figshare.7944242.v2
title: Data from Chimpanzees (<i>Pan troglodytes</i>) coordinate by communicating in a collaborative problem-solving task.

description: Data
DOI: 10.6084/m9.figshare.7944242.v1
title: Data from Chimpanzees (<i>Pan troglodytes</i>) coordinate by communicating in a collaborative problem-solving task

description: Data
DOI: 10.6084/m9.figshare.7957469
title: Simulation code for Fig S1 from The distribution of epistasis on simple fitness landscapes.

description: Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.
DOI: 10.6084/m9.figshare.7957469.v2
title: Simulation code for Fig S1 from The distribution of epistasis on simple fitness landscapes.

description: Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.
DOI: 10.6084/m9.figshare.7957472
title: Simulation code for Fig S2 from The distribution of epistasis on simple fitness landscapes.

description: Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.
DOI: 10.6084/m9.figshare.7957469.v1
title: Simulation code for Fig S1 from The distribution of epistasis on simple fitness landscapes

description: Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.
DOI: 10.6084/m9.figshare.7957472.v2
title: Simulation code for Fig S2 from The distribution of epistasis on simple fitness landscapes.

description: Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.
DOI: 10.6084/m9.figshare.7957472.v1
title: Simulation code for Fig S2 from The distribution of epistasis on simple fitness landscapes

description: Fitness interactions between mutations can influence a population’s evolution in many different ways. While epistatic effects are difficult to measure precisely, important information is captured by the mean and variance of log fitnesses for individuals carrying different numbers of mutations. We derive predictions for these quantities from a class of simple fitness landscapes, based on models of optimizing selection on quantitative traits. We also explore extensions to the models, including modular pleiotropy, variable effect sizes, mutational bias and maladaptation of the wild type. We illustrate our approach by reanalysing a large dataset of mutant effects in a yeast snoRNA. Though characterized by some large epistatic effects, these data give a good overall fit to the non-epistatic null model, suggesting that epistasis might have limited influence on the evolutionary dynamics in this system. We also show how the amount of epistasis depends on both the underlying fitness landscape and the distribution of mutations, and so is expected to vary in consistent ways between new mutations, standing variation and fixed mutations.
DOI: 10.6084/m9.figshare.7964243
title: Supplementary Dataset from Pterin-pigmented nanospheres create the colours of the polymorphic damselfly <i>Ischnura elegans</i>.

description: Spectral reflectance data of the thorax and the compound eye of Ischnura elegans.
DOI: 10.6084/m9.figshare.7964243.v2
title: Supplementary Dataset from Pterin-pigmented nanospheres create the colours of the polymorphic damselfly <i>Ischnura elegans</i>.

description: Spectral reflectance data of the thorax and the compound eye of Ischnura elegans.
DOI: 10.6084/m9.figshare.7964243.v1
title: Supplementary Dataset from Pterin-pigmented nanospheres create the colours of the polymorphic damselfly <i>Ischnura elegans</i>

description: Spectral reflectance data of the thorax and the compound eye of Ischnura elegans.
DOI: 10.6084/m9.figshare.7964456
title: Table S7 from A phylogenomic framework, evolutionary timeline and genomic resources for comparative studies of decapod crustaceans.

description: Formatted list of node calibration priors.