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Figure 4 in Identification key for chewing lice (Phthiraptera: Amblycera, Ischnocera) infesting the Indian Peafowl (Pavo cristatus) with one new country record and new host record for Saudi Arabia
Figure 4. Male Goniodes dissimilis. Normal image on the left and modified image on the right.
Figure 6 in Colotis lais (Butler, 1876) and Colotis euippe omphale (Godart, [1819]) use Cadaba aphylla (Thunb.) Wild LC as a host-plant at Tswalu Kalahari, Northern Cape Province, South Africa)
Figure 6 – Location of Tswalu Kalahari in southern Africa.
Impact of host climate model on contrail cirrus effective radiative forcing estimates
<p>Data to reproduce the figures in the article 'Impact of host climate model on contrail cirrus effective radiative forcing estimates'.</p>
Evolution of sympatric host-specialized lineages of the fungal plant pathogen Zymoseptoria passerinii in natural ecosystems
<p>This repository contains the data sets from the research paper "Evolution of sympatric host-specialized lineages of the fungal plant pathogen <em>Zymoseptoria passerinii</em> in natural ecosystems"</p>
Data and code for: Host-use Drives Convergent Evolution in Clownfish
<p>This folder contains the following files:</p> <p>data/Alignments_WithOutgroups.tar.gz:<br> Contains the alignments of 10,720 genes with the sequences of the outgroup Pomacentrus moluccensis. The gene IDs correspond to the ID of the Amphiprion frenatus reference genome (Marcionetti et al., 2018; https://datadryad.org/stash/dataset/doi:10.5061/dryad.nv1sv). The position of the gene on the Amphiprion percula chromosomes is also reported. For information on the methods and sample names, please refer to the publication. These alignments were used to infer the species tree with ASTRAL-III. Alignments for the genes selected with SortaDate and used for dating with BEAST are also available and are: chr04_g2455.t1.WithOutgroup.phy, chr05_g51486.t1.WithOutgroup.phychr05_g56452.t1.WithOutgroup.phy, chr08_g50086.t1.WithOutgroup.phy, chr09_g35092.t1.WithOutgroup.phy, chr09_g49030.t1.WithOutgroup.phy, chr10_g47484.t1.WithOutgroup.phy, chr11_g5494.t1.WithOutgroup.phy, chr11_g32313.t1.WithOutgroup.phy, chr12_g7961.t1.WithOutgroup.phy, chr12_g27572.t1.WithOutgroup.phy, chr12_g32580.t1.WithOutgroup.phy, chr13_g33152.t1.WithOutgroup.phy, chr15_g60485.t1.WithOutgroup.phy, chr16_g18013.t1.WithOutgroup.phy, chr17_g60288.t1.WithOutgroup.phy, chr22_g6154.t1.WithOutgroup.phy, chr22_g22141.t1.WithOutgroup.phy, chr22_g29206.t1.WithOutgroup.phy, chr23_g36756.t1.WithOutgroup.phy. </p> <p>data/DatedTree.WithOutgroup.tree:<br> BEAST2 output. The clownfish dated phylogenetic tree with the outgroup Pomacentrus moluccensis used for rooting. The tree was obtained with BEAST2, using 20 most informative genes. For each partition, we applied a GTR+ G site model and an uncorrelated relaxed clock with a lognormal distribution. A secondary calibration points was used, setting uniform prior from 10 to 18 MYA for the crown age of clownfishes. For more information on the methods, please refer to the publication. </p> <p><br>data/Example.DatFile.evolver.tar.gz: <br> Templates of the .dat files (MCcodonNSbranchsites.Shifts_to_Entacmaea.dat, MCcodonNSbranchsites.Shifts_to_Radianthus.dat) containing information to simulate sequences with evolver. The two .dat files were used to simulate sequences under different selection scenarios (no positive selection, convergent positive selection, positive selection on "long" or "clade" branches only) during the shifts to Entacmaeae or Radianthus hosts. The files were used with the scripts Create_DATFile_Evolved.Shift_to_Entacmaea.py and Create_DATFile_Evolved.Shift_to_Radianthus.py to generate .dat files for all the conditions, used then in evolver. For more information on the methods, please refer to the publication. </p> <p>data/DatFiles.Evolver.tar.gz<br> The .dat files that were obtained for the different omega and evolutionary scenarios, for shifts to Entacmaea and Radianthus hosts. The files are obtained with the template files (Example.DatFile.evolver.tar.gz) and the scripts Create_DATFile_Evolved.Shift_to_Entacmaea.py and Create_DATFile_Evolved.Shift_to_Radianthus.py. The resulting .dat files are run in evolver:</p> <p> evolverNSbranchsites 6 DAT_FILES.dat </p> <p> to obtain the codon alignment files to perform power and false positive rate analyses. For more information, please refer to the publication. </p> <p>data/Alignments_ProteinCodingGenes.tar.gz: <br> Contains the alignments of the 18,390 protein-coding genes analysed in the study. The gene IDs correspond to the ID of the Amphiprion frenatus reference genome (Marcionetti et al., 2018; https://datadryad.org/stash/dataset/doi:10.5061/dryad.nv1sv). The position of the gene on the Amphiprion percula chromosomes is also reported. For information on the methods and sample names, please refer to the publication. These alignments were used to test for convergent positive selection occurring during host shifts. </p> <p>data/Example.ControlFiles.CodeML.tar.gz<br> It contains examples of the control files for the null model (no positive selection, H0), alternative model (positive selection, H1), and the site model M1a (used to verify the correct optimization of the null model). The final control files for each gene and condition (shift to Entacmaea or Readianthus host) were generated with the script Create_CTLFile_CodeML.py. </p> <p>data/LabelledTree.CodeML.tar.gz<br> Tree files used in codeml analyses, with shifts to Entacmaea labelled as foreground branches (ClownTree.Rooted.Label_Entacmaea.nwk, ClownTree.Rooted.Label_Entacmaea.NoLongBranches.nwk) and shifts to Radianthus labelled as foreground branches (ClownTree.Rooted.Label_Radianthus.nwk, ClownTree.Rooted.Label_Radianthus.NoLongBranches.nwk). The trees do or do not have the 3 "long branches" species (A. ocellaris, A. percula, P. biaculeatus). For more information, refer to the publication. An additional folder (Additional_labelled_trees_for_test_on_simulated_data.tar.gz) containg the trees with only specific species kept and labelled. These trees were used for codeml analyses on simulated alignments, to investigate false positives and power of the analyses. For more information, refer to the publication. </p> <p>data/SimulatedData_BranchSite_Results.tar.gz<br> It contains the results for the branch site model on the simulated data. Each file name reports the simulated scenario (Simulated without positive selection: Simulated_NO_PS_Entacmaea / Simulated_NO_PS_Radianthus; simulated convergent positive selection: Simulated_PS_Entacmaea / Simulated_PS_Radianthus; Simulated positive selection on long branches : Simulated_PS_LongBranches / Simulated_PS_Premnas; Simulated positive selection on "clade" branches: Simulated_PS_AKA / Simulated_PS_Ephi), as well as the tested scenario (Tested for positive selection: Tested_PS_Entacmaea / Tested_PS_Radianthus; or tested for positive selection on specific branches). Each file contains the information on the name of the original file, the simulated scenario, the tested scenario, the simulated omega, the replicate number, the log-likelihood of the tested model (site model: M1a, null model without positive selection: H0, alternative model with positive selection: H1), and the p-values associated to the likelihood-ratio test (LRT_pvalue). For more information, refer to the publication. </p> <p>data/EmpiricalData_BranchSite_Results.tar.gz<br> It contains the results for the branch site model for the 18,390 protein-coding genes tested in the study, for shifts to Entacmaea (Results.BranchSiteModel.Shifts_To_Entacmaea.txt, Results.BranchSiteModel.Shifts_To_Entacmaea.NoLongBranches.txt) and shifts to Radianthus hosts (Results.BranchSiteModel.Shifts_To_Radianthus.txt, Results.BranchSiteModel.Shifts_To_Radianthus.NoLongBranches.txt). Each file contains information on the chromosome information of the analyzed gene, the name of the gene, the log-likelihood of the M1a model (site model, used to verify the correct optimization of the null model), the log-likelihood of the null model (H0) and the alternative model (H1), and the p-values associated to the likelihood-ratio test (LRT_pvalue). These p-values were subsequentially corrected for multiple testing. For more information, refer to the publication. </p> <p>data/ASR_adult_host_4st.rds<br> It contains the results of reproductive host associations ancestral states reconstruction to the form of a list() R object. In the list $joint returns a tree with joint ancestral states (returns the most likely ancestral reproductive host association at nodes), $marginal returns a tree with the likelihood of each state at nodes, $simmap returns 100 stochastic maps of ancestral states along branches of the tree calculated over the marginal reconstruction, $map returns a map of ancestral states along branches estimated from the joint reconstruction.</p> <p>data/Absolute_host_assoc.tar.gz<br> It contains description of the sources used for characterizing host associations for each species of clownfish. For each species, we provide a list of pictures used from public citizen science databases with associated urls and additional published references if used. reprod_host.csv contains our final classification of reproductive host associations.</p> <p>data/DEC.tar.gz<br> It contains files used for the biogeographic reconstruction (areas_adjacency_clowns.txt, areas_clowns.txt, calibrated_tree.tre, distances.txt, geo_col.txt) and results of the biogeographic reconstruction. geo_obj.rds is a R object containing the joint reconstruction of ancestral biogeographic states formatted for being used in phylogenetic comparative methods analyses. list_geo_obj.rds is a list of a 100 similar objects generated from stochastic maps of ancestral biogeographic states.</p> <p>data/phenotype.tar.gz<br> It contains results of clownfish individuals phenotyping. Within each file, the first column is the name of the species identified from the picture. morph_pca.csv contains results of the pca analysis performed on the procrustes of clownfish individuals. morph_traits.csv contains traits values calculated from the prcrustes of clownfish individuals. colorRGB.csv contains results of the pca analysis performed on the concatenated red green and blue channels of each clownfish image. colorWOB.csv contains results of the pca analyses performed independantly on white, orange and black channels. columns with names ending with W represent pca axis generated from white channel (O: orange channel, B: black channel)</p> <p>scripts/Create_CTLFile_CodeML.py: <br> Script used to generate the codeml control files for codeml analyses (simulated data or empirical data). The scripts needs the path to the folder were the codon alignments (see Alignments_ProteinCodingGenes.tar.gz or Alignments created for simulations) are found, the path were the output file are gonna be written; the path to the alignment, tree file and output as they will be written in the control file; the output suffix. </p> <p> python Create_CTLFile_CodeML.py PATH/to/Alignments/ PATH/to/out/CTL_files/ alignment_in_ctlFile tree_in_ctlFile path_to_output_in_ctlFile Output_Suffix</p> <p> This produces the control files of the null model (H0, no positive selection) and alternative model (H1, positive selection), that can be run with codeml</p> <p> codeml CONTROL_FILE.ctl </p> <p> to obtain the results. This was done using the tree with shifts to Ratianthus or Entacmaea as foreground branches (see LabelledTree.CodeML.tar.gz). This was also performed on real data or simulated data. For more information, refer to the publication. </p> <p><br>scripts/Create_DATFile_Evolved.Shift_to_Entacmaea.py<br>scripts/Create_DATFile_Evolved.Shift_to_Radianthus.py<br> Scripts used to generate the .dat files for evolver simulations. The scripts need the template .dat files (provided in Example.DatFile.evolver.tar.gz) and the information of the path where to save the resulting .dat files:</p> <p> python Create_DATFile_Evolved.Shift_to_Entacmaea.py MCcodonNSbranchsites.Shifts_to_Entacmaea.dat Out_dat_files_Entacmaeae/</p> <p> python Create_DATFile_Evolved.Shift_to_Radianthus.py MCcodonNSbranchsites.Shifts_to_Radianthus.dat Out_dat_files_Radianthus/</p> <p> The .dat files obtained are then run in evolver to generate the simulated alignments:</p> <p> evolverNSbranchsites 6 DAT_FILES.dat </p> <p> The simulated alignments and tree were then used in codeml to evaluate power and false positive rate of positive selection analyes. The file Create_CTLFile_CodeML.py was used to create control files and control files were run with codeml. For more information, refer to the publication. </p> <p>scripts/ASR_adult_host.R<br> Script used to perform the ancestral state reconstruction of reproductive host assocication. It uses data/Absolute_host_assoc/reprod_host.csv and data/BEAST2.DatedTree.WithOutgroup.tree and outputs the data/ASR_adult_host_4st.rds file. It requires the instalation of a few R packages ("ape", "igraph", "mvMORPH", "scales", "sda", "TeachingDemos","png", "corHMM","phytools") that can be installed with the function (install.packages("package-name"))</p> <p> Rscript scripts/ASR_adult_host.R</p> <p>scipts/BGB_fit.R<br> Script used to perform the ancestral state reconstruction of biogeographic region. It uses data embeded into data/DEC.tar.gz and outputs data/geo_obj.rds and data/list_geo_obs.rds. It requires the instalation of a few R packages ("ape","BioGeoBEARS", "GenSA", "FD", "snow", "parallel","cladoRcpp","rexpokit") that can be installed with the function (install.packages("package-name")).</p> <p> Rscript scripts/BGB_fit.R</p> <p>scripts/PCM_fit.R<br> Script used to perform the phylogenetic comparative analyses. It uses data embeded into the data folder. First part performs multivariate phylogenetic anova. Second part performs model testing and parameter estimations using multivariate and univariate datasets and ancestral state reconstruction joint maps. Third part performs model testing and parameter estimations using multivariate and univariate datasets and 100 stochastic maps from marginal ancestral state reconstructions. Results are saved into .rds files. It requires the instalation of a few R packages ("ape", "phytools", "mvMORPH", "RPANDA", "geiger","OUwie") that can be installed with the function (install.packages("package-name")).</p> <p> Rscript scripts/PCM_fit.R</p> <p>scripts/manova_var.R<br> Script used to estimate uncertainties on the mANOVA that are due to intraspecific variation. It uses data embeded into the data folder. Results are saved into .rds files. It requires the instalation of a few R packages ("ape", "phytools", "mvMORPH", "RPANDA", "geiger","OUwie") that can be installed with the function (install.packages("package-name")).</p> <p> Rscript scripts/manova_var.R</p> <p> </p> <p> </p> <p> </p>
A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment
<p>All processed data used in the manuscript 'A Spatial Multi-Modal Dissection of Host-Microbiome Interactions within the Colitis Tissue Microenvironment'. For more detail please refer to the manuscript. If there is any question please contact Bokai Zhu via email: BZHU0@MGH.HARVARD.EDU.</p> <p>Data folder structure:</p> <p>Main data (eg. presented in main figures etc): Please see .zip file 'data_submission.zip'.</p> <p>Additional data (eg. during revision, or other misc files): Please see .zip file 'data_submission_part2.zip'.</p>
Data: Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD
<p>This archive contains all scripts, resource data and results, including intermediate results to reproduce the results for "Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD". </p>
Preferential allocation of benefits and resource competition among recipients allows coexistence of symbionts within hosts
<p>Functionally variable symbionts commonly co-occur including within the roots of individual plants, in spite of arguments from simple models of the stability of mutualism that predict competitive exclusion among symbionts. We explore this paradox by evaluating the dynamics generated by symbiont competition for plant resources, and the plant's preferential allocation to the most beneficial symbiont, using a system of differential equations representing the densities of mutualistic and non-mutualistic symbionts and the level of preferentially allocated and non-preferentially allocated resources for which the symbionts compete. We find that host preferential allocation and costs of mutualism generate resource specialization that makes the coexistence of beneficial and non-beneficial symbionts possible. Furthermore, coexistence becomes likely due to negative physiological feedbacks in host preferential allocation. We find that biologically realistic models of plant physiology and symbiont competition predict that the coexistence of beneficial and non-beneficial symbionts should be common in root symbioses, and that the density and relative abundance of mutualists should increase in proportion to the needs of the host.</p>
Data from: Host-parasite dynamics shaped by temperature and genotype: quantifying the role of underlying vital rates
<p>1. Global warming challenges the persistence of local populations, not only through heat-induced stress, but also through indirect biotic changes. We study the interactive effects of temperature, competition and parasitism in the water flea <i>Daphnia magna</i>.</p> <p>2. We carried out a common garden experiment monitoring the dynamics of <i>Daphnia</i> populations along a temperature gradient. Halfway through the experiment, all populations became infected with the ectoparasite <i>Amoebidium parasiticum</i>, enabling us to study interactive effects of temperature and parasite dynamics. We combined Integral Projection Models with epidemiological models, parameterized using the experimental data on the performance of individuals within dynamic populations. This enabled us to quantify the contribution of different vital rates and epidemiological parameters to population fitness across temperatures and <i>Daphnia</i> clones originating from two latitudes.</p> <p>3. Interactions between temperature and parasitism shaped competition, where Belgian clones performed better under infection than Norwegian clones, mainly due to higher survival. Infected <i>Daphnia</i> populations performed better at higher than at lower temperatures, mainly due to an increased host capability of reducing parasite loads. Temperature strongly affected individual vital rates, but effects largely cancelled out on a population-level. In contrast, parasitism strongly reduced fitness through consistent negative effects on all vital rates. As a result, temperature-mediated parasitism was more important than the direct effects of temperature in shaping population dynamics. Both the outcome of the competition treatments and the observed extinction patterns support our modeling results.</p> <p>4. Our study highlights that shifts in biotic interactions can be equally or more important for responses to warming than direct physiological effects of warming, emphasizing that we need to include such interactions in our studies to predict the competitive ability of natural populations experiencing global warming.</p>
Host diversity outperforms climate as a global driver of symbiont diversity in the bird-feather mite system
<p><b>Aim: </b>The simultaneous influence of abiotic and biotic factors as main drivers of global species distributions remains poorly understood, especially in host-dependent groups. In this study, we diverge from traditional macroecological approaches by considering both biotic (avian species diversity) and abiotic (climatic) factors in determining the global distribution pattern of feather mite species richness, one of the most abundant and diverse bird ectosymbionts.</p> <p><b>Location: </b>Global.</p> <p><b>Methods: </b>We used a global dataset of feather mite-bird interactions published in 2016, complemented with an up-to-date literature survey. We created statistical models designed to explain the effect of abiotic (i.e., temperature, precipitation, and energy-related variables) and biotic factors (bird species richness) on the species richness of feather mites. We used these models to predict global distribution patterns of mites and estimate each explanatory variable's relative importance in temperate and tropical regions.</p> <p><b>Results: </b>According to our models, bird species richness accounts for ~63% of the global distribution pattern of mites, which is ten times more relevant than climatic variables. Among abiotic drivers, precipitation intensity and seasonality were the most important variables, accounting for 10% of mite species richness. This figure is lower in tropical regions, where biotic factors are seven times more important than in temperate regions.</p> <p><b>Main Conclusions: </b>We demonstrate that global mite diversity was primarily determined by biotic and, to a lesser extent, abiotic factors. The relative importance of the predictive variables, however, varied between tropical and temperate regions. The strong association between bird species richness and feather mite species diversity at a global scale raises concerns about the potential for future co-extinctions.</p>
Context dependent host-symbiont interactions: shifts along the parasitism-mutualism continuum
<p>Symbiotic interactions can shift along a mutualism to parasitism continuum. While there are many studies examining dynamics typically considered to be mutualistic that sometimes shift towards parasitism, little is known about conditions underlying shifts from parasitism towards mutualism. In lake populations, we observed that infection by a microsporidian gut symbiont sometimes conferred a reproductive advantage and other times a disadvantage to its <i>Daphnia </i>host. We hypothesized that the microsporidian might benefit its host by reducing infection by more virulent parasites, which attack via the gut. In a lab study using field-collected animals, we found that spores of a virulent fungal parasite were much less capable of penetrating the guts of <i>Daphnia </i>harboring the microsporidian gut symbiont. We predicted that this altered gut penetrability could cause differential impacts on host fitness depending on ecological context. Using data from field surveys, we found that microsporidian-infected <i>Daphnia </i>hosts experienced a reproductive advantage when virulent parasites were common and a reproductive disadvantage when resources were scarce and virulent parasites were rare. Our findings highlight the importance of considering multiparasite community context and resource availability in host-parasite studies and open the door for future research into conditions driving shifts along parasitism to mutualism gradients.</p>
Raw data to: "Vectored antibody gene delivery restores host B and T cell control of persistent viral infection"
<p>Raw data underlying the publication by Ertuna et al. entitled "Vectored antibody gene delivery restores host B and T cell control of persistent viral infection"</p>
Host cell maturation modulates parasite invasion and sexual differentiation in Plasmodium.
<p>Raw expression counts data is provided along with code needed to analyse the scRNA-seq data presented in the publication "Host cell maturation modulates parasite invasion and sexual differentiation in Plasmodium."</p>
Host traits and environment interact to drive persistence of bat populations impacted by white-nose syndrome
<p>Emerging infectious diseases have resulted in severe population declines across diverse taxa. In some instances, despite attributes associated with high extinction risk, disease emergence and host declines are followed by host stabilization for unknown reasons. While host, pathogen, and the environment are recognized as important factors that interact to determine host-pathogen coexistence, they are often considered independently. Here, we use a translocation experiment to disentangle the role of host traits and environmental conditions in driving the persistence of remnant bat populations a decade after they declined 70-99% due to white-nose syndrome and subsequently stabilized. While survival was significantly higher than during the initial epidemic within all sites, protection from severe disease only existed within a narrow environmental space, suggesting host traits conducive to surviving disease are highly environmentally dependent. Ultimately, population persistence following pathogen invasion is the product of host-pathogen interactions that vary across a patchwork of environments.</p>
Temperature perturbation of cellular host-microbe interactions explains continent-wide endosymbiont prevalence
<p>Endosymbioses influence host physiology, reproduction, and fitness, but these relationships require efficient microbe transmission between host generations to persist. Maternally transmitted <i>Wolbachia</i> are the most common known endosymbionts, but their frequencies vary widely within and among host populations for unknown reasons. Here we integrate genomic, cellular, and phenotypic analyses with mathematical models to provide an unexpectedly simple explanation for global <i>w</i>Mel <i>Wolbachia</i> prevalence in <i>Drosophila melanogaster</i>. Cooling temperatures decrease <i>w</i>Mel cellular abundance at a key stage of host oogenesis, producing temperature-dependent variation in maternal transmission that plausibly explains latitudinal clines of <i>w</i>Mel frequencies on multiple continents. <i>w</i>Mel sampled from a temperate climate targets the germline more efficiently in the cold than a recently differentiated tropical variant (~2,200 years ago), indicative of rapid <i>w</i>Mel adaptation to climate. Genomic analyses identify a very narrow list of <i>w</i>Mel alleles—most notably, a derived stop codon in the major <i>Wolbachia</i> surface protein WspB—that underlie thermal sensitivity of cellular<i>Wolbachia</i> abundance and covary with temperature globally. Decoupling temperate <i>w</i>Mel and host genomes further reduces transmission in the cold, a pattern that is characteristic of host-microbe co-adaptation to a temperate climate. Complex interactions among <i>Wolbachia</i>, hosts, and the environment (GxGxE) mediate <i>w</i>Mel cellular abundance and maternal transmission, implicating temperature as a key determinant of <i>Wolbachia</i> spread and equilibrium frequencies, in conjunction with <i>Wolbachia</i> effects on host fitness and reproduction. Our results motivate strategic use of locally selected <i>w</i>Mel variants for <i>Wolbachia</i>-based biocontrol efforts, which currently protect millions of individuals from arboviruses that cause human disease.</p>
Bottom-up effect of host protective symbionts on parasitoid diversity: Limited evidence from two field experiments
<p>1. Protective symbionts can provide effective and specific protection to their hosts. This protection can differ between different symbiont strains with each strain providing protection against certain components of the parasite and pathogen community their host faces. Protective symbionts are especially well known from aphids where, among other functions, they provide protection against different parasitoid wasps. However, most of the evidence for this protection comes from laboratory experiments.</p> <p>2. Our aim was to understand how consistent protection is across different symbiont strains under natural field conditions and whether symbiont diversity enhanced the species diversity of colonizing parasitoids, as could be expected from the specificity of their protection.</p> <p>3. We used experimental colonies of the black bean aphid, Aphis fabae, to investigate symbiont conferred protection under natural field conditions over two seasons. Colonies differed only in their symbiont composition, carrying either no symbionts, a single strain of the protective symbiont Hamiltonella defensa, or a mixture of three H. defensa strains. These aphid colonies were exposed to natural parasitoid communities in the field. Subsequently, we determined the parasitoids hatched from each aphid colony.</p> <p>4. The evidence for a protective effect of H. defensa was limited and inconsistent between years, and aphid colonies harboring multiple symbiont strains did not support a more diverse parasitoid community. Instead, parasitoid diversity tended to be highest in the absence of H. defensa.</p> <p>5. Symbiont conferred protection, although a strong and repeatable effect under laboratory conditions, may not always cause the predicted bottom-up effects under natural conditions in the field.</p>
Warming decreases host survival with multiple parasitoids, but parasitoid performance also decreases
<p>README</p> <p>##############<br> ## DATASETS ##<br> ##############</p> <p>### data_FR.csv ### <br> Daily recording of emerges from Experiment 1</p> <p>- Vial.ID: unique name for each experimental vial <br> - Heggs: aimed initial host density per vial (5, 10,15, 25, 50 or 100)<br> - Block: from 1 to 8 (same as replicate)<br> - T: temperature treatment (23°C or 27°C)<br> - Hsp: host species (BIR = D. birchii, PAL = D. pallidifrons, SIM = D. simulans)<br> - Psp: parasitoid species (C = controls, A = Asobara sp., L = Leptopilina sp., G = Ganaspis sp.) <br> - Rep: replicate (from 1 to 8)<br> - H_P: H = host and P = parasitoid<br> - sp: species name (abbreviations: Asb = Asobara sp., Lept = Leptopilina sp., Gana = Ganaspis sp., BIR = D. birchii, PAL = D. pallidifrons, SIM = D. simulans) <br> - sex: M = male and F = female (for parasitoids only, NA for hosts)<br> - column 6 to 46: number of emerges from day 6 to day 46 from the start of the experiment (when eggs were placed in vials) -> emerges where checked daily</p> <p>### data_C.BM.csv ### <br> Measurements of host body mass in controls from Experiment 1</p> <p>- Vial.ID: unique name for each experimental vial <br> - Heggs: initial host density (here 50 only)<br> - Block: from 1 to 8 (same as replicate)<br> - T: temperature treatment (23°C or 27°C)<br> - Hsp: host species (BIR = D. birchii, PAL = D. pallidifrons, SIM = D. simulans)<br> - Psp: parasitoid species (C = controls: no parasitoids)<br> - Rep: replicate (from 1 to 8)<br> - H_P: H = host<br> - column 1 to 10: individual host body mass (in µg): 10 host were weighted per vial when possible<br> - BM: mean host body mass from this vial (in µg)<br> - BM_N: number of hosts weighted from this vial</p> <p>### data_FR.P.BM.csv ### <br> Measurements of parasitoid body mass from Experiment 1</p> <p>- Vial.ID: unique name for each experimental vial <br> - Heggs: initial host density (here 50 only)<br> - Block: from 1 to 8 (same as replicate)<br> - T: temperature treatment (23°C or 27°C)<br> - Hsp: host species (BIR = D. birchii, PAL = D. pallidifrons, SIM = D. simulans)<br> - Psp: parasitoid species (Asb = Asobara sp., Lept = Leptopilina sp., Gana = Ganaspis sp.)<br> - Rep: replicate (from 1 to 8)<br> - H_P: P = parasitoid<br> - column 1 to 10: individual parasitoid body mass (in µg): 10 parasitoids were weighted per vial when possible<br> - BM: mean parasitoid body mass from this vial (in µg)<br> - BM_N: number of parasitoids weighted from this vial</p> <p>### data_MPEexp2.csv ### <br> Daily recording of emerges from Experiment 2</p> <p>- Vial.ID: unique name for each experimental vial <br> - Heggs: initial host density (here 50 only)<br> - Block: from 1 to 2<br> - T: temperature treatment (23°C or 27°C)<br> - Hsp: host species (here only D. simulans)<br> - Treat: H1P1 = one host and one parasitoid species, H1P2 = one host and 2 parasitoid species (always two parasitoid individuals)<br> - Pcomb: parasitoid assemblage (abbreviations: A = Asobara sp., L = Leptopilina sp., G = Ganaspis sp.) <br> - Rep: replicate (from 1 to 8)<br> - H_P: H = host and P = parasitoid<br> - sp: species name (abbreviations: Asb = Asobara sp., Lept = Leptopilina sp., Gana = Ganaspis sp., SIM = D. simulans) <br> - sex: M = male and F = female<br> - column 7 to 40: number of emerges from day 7 to day 40 from the start of the experiment (when eggs were placed in vials) -> emerges where checked daily</p> <p>### data_MPEexp3.csv ### <br> Data from dissections from Experiment 3</p> <p>- T: temperature treatment (23°C or 27°C)<br> - Pcomb: parasitoid assemblage (abbreviations: A: Asobara sp., and G: Ganaspis sp.) <br> - Block: from 1 to 2 (different than Experiment 1 and 2)<br> - Rep: replicate (from 1 to 12)<br> - Observer: name of the observer<br> - Dissection: time of dissection (early or late)<br> - Day_infection: number of days between initialization of the vial and the dissection<br> - H_number: larvae ID from the vial (from 1 to 10 for each vial)<br> - Larvae_pupae: if the host dissected was at the larval or pupal stage (we aimed to dissected larvae but it was not always possible)<br> - ASB_egg: number of Asobara sp. eggs<br> - ASB_larvae: number of Asobara sp. larvae<br> - ASB_melanized: number of Asobara sp. melanized eggs<br> - GANA_egg: number of Ganaspis sp. eggs<br> - GANA_larvae: number of Ganaspis sp. larvae<br> - GANA_melanized: number of Ganaspis sp. melanized eggs<br> - NA_melanized: number of melanized eggs not identified to species level<br> - Melanization_trace: if presence (y) or not (na) of other trace of melanization<br> - Melanization_eggs: presence (y) or not (n) of melanized eggs<br> - P_larvae: total number of parasitoid larvae<br> - P_eggs: total number of parasitoid eggs<br> - TOT_ASB: total number of Asobara sp.<br> - TOT_GANA: total number of Ganaspis sp.<br> - TOT_P: total number of parasitoids<br> - TOT_Melanized: total number of melanized eggs <br> - Melanization: presence (y) or not (n) of melanization (either melanized eggs or trace of melanization)<br> - Super_ASB: presence (y) or not (n) of multiple Asobara sp.<br> - Super_GANA: presence (y) or not (n) of multiple Ganaspis sp.<br> - Superparasitism: presence (y) or not (n) of superparasitism<br> - Multiparasitism: presence (y) or not (n) of multiparasitism<br> - Sup_Mult: presence (y) or not (n) of either super- or multiparasitism<br> - ASB: presence (y) or not (n) of Asobara sp.<br> - GANA: presence (y) or not (n) of Ganaspis sp.<br> - Parasitized: presence (y) or not (n) of parasitism</p> <p><br> ###############<br> ## R scripts ##<br> ###############</p> <p>### MPE0_data-cleaning.R ### <br> R script to import, clean and modify the datasets<br> --> save the data needed for analyses in "MPE_data.RData"</p> <p>### MPE1_FRfit.R ###<br> R script to fit parasitoid functional responses<br> --> save the results in "data.FRfitSIM.csv"<br> --> save the data needed for analyses in "MPE_data_FR.RData"</p> <p>### MPE2_analyses1.R ### <br> R script to analyze data from Experiment 2 <br> using the method proposed in McCoy et al. (2012). Emergent effects of multiple predators on prey survival: the importance of depletion and the functional response. Ecology letters, 15(12), 1449-1456.</p> <p>### MPE3_analyses2_exp2.R ### <br> R script to analyze data from Experiment 2</p> <p>### MPE4_analyses3_exp3.R ### <br> R script to analyze data from Experiment 3</p>
Figures 8–9. Stenelytrana splendens. 8 in New larval host plants and ecological observations on North American Cerambycidae (Coleoptera)
Figures 8–9. Stenelytrana splendens. 8) Female. 9) Male.
Post-association barrier to host switching maintained despite strong selection in a novel mutualism
<p class="MsoNormal"><span>Following a host shift, repeated co-passaging of a mutualistic pair is expected to increase fitness over time in one or both species.<span> </span>Without adaptation, a novel association may be evolutionarily short-lived as it is likely to be outcompeted by native pairings.<span> </span>Here we test whether experimental evolution can rescue a low-fitness novel pairing between two sympatric species of <em>Steinernema</em> nematodes and their symbiotic <em>Xenorhabdus</em> bacteria.<span> </span>Despite low mean fitness in the novel association, considerable variation in nematode reproduction was observed across replicate populations.<span> </span>We selected the most productive infections, co-passaging this novel mutualism nine times to determine whether selection could improve fitness of either or both partners.<span> </span>We found that neither partner showed increased fitness over time.<span> </span>Our results suggest that the variation in association success was not heritable and that mutational input was insufficient to allow evolution to facilitate this host shift.<span> </span>Thus, post-association costs of host switching may represent a formidable barrier to novel partnerships among sympatric mutualists. </span></p>
Parasitic trophic mode of plant host affects the extent of colonization, but does not induce systematic shifts in the composition of foliar endophytic assemblages in temperate meadow ecosystems
<p>1. Foliar endophytic bacteria and fungi are increasingly being recognized as important drivers of plant host phenotype – affecting a wide range of eco-physiological processes. However, we are still lacking fundamental ecosystem-level knowledge about the structure, function, and inter-species interactions in endophytic assemblages associated with plant hosts sharing a common life strategy or ecological specialization.</p> <p>2. In this study, we chose two groups of plants with contrasting physiology as model systems: parasites and their hosts. We assessed whether plant life history strategy, namely differences in nutrient acquisition and accumulation, plays a role in structuring above-ground microbiomes under field conditions.</p> <p>3. We focused on the structure, colonization extent, and potential function of foliar endophytic bacteria and fungi in three root hemiparasitic species (Orobanchaceae), one stem holoparasite (Convolvulaceae), and their potential host plants co-occurring in species-rich temperate grassland ecosystems. For this purpose, we combined next generation amplicon sequencing with quantitative real-time PCR, chemical analyses of leaf tissue, and, in the case of bacteria, functional predictions using information deposited in available databases.</p> <p>4. We found the foliar endophytic assemblages to be diverse, dominated by generalist taxa, but highly similar across all studied species. Despite of the highly contrasting leaf tissue chemistry in the parasitic and non-parasitic plant species, the parasitic trophic mode did not induce systematic shifts in the diversity, composition, or predicted biogeochemical function of the endophytic microbiomes under field conditions. However, compared to their potential hosts, leaves of both hemiparasitic and holoparasitic species harbored significantly lower fungal counts, estimated as <em>ß-actin</em> gene copies ng DNA<sup>-1</sup>, which suggests that parasitic plants may possess mechanisms to regulate the extent of colonization by endophytic fungi.</p>
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Annotated Behaviour and Observability Dataset (ABODe)
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