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Replication data and analysis code for the article "Insect-habitat-plant interaction networks provide guidelines to mitigate the risk of transmission of Xylella fastidiosa to grapevine in Southern France"

This deposit contains the dataset used in the article "Insect-habitat-plant interaction networks provide guidelines to mitigate the risk of transmission of Xylella fastidiosa to grapevine in Southern France" in the form of a RData file, directly loadable in R, as well as the Rmd script used to analyse the data and produce the figures.

Fig. 1 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 1. Distribution map for Philaenus spumarius in Belgium. Data: RBINS; Observations.be (2010-2016); our own samplings (2016-2017).

Fig. 11 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 11. Distribution map for Aphrophora salicina in Belgium. Data: RBINS; Observations.be (2010-2016); our own samplings (2016-2017).

Fig. 8 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 8. Phenology of adult Cercopis vulnerata in Belgium. Data: RBINS; Observations.be (2005-2017); our own samplings (2016-2017).

Fig. 4 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 4. Distribution map for Cicadella viridis in Belgium. Data: RBINS; Observations.be (2010-2016); our own samplings (2016-2017).

Fig. 7 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 7. Distribution map for Cercopis vulnerata in Belgium: Data: RBINS; Observations.be (2010-2016); our own samplings (2016-2017).

Fig. 3 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 3. Immature development of Philaenus spumarius under outdoor conditions (Ixelles, Belgium, 2016).

Fig. 2 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 2. Phenology of adult Philaenus spumarius in Belgium: Data: RBINS; Observations.be (2005-2017); our own samplings (2016-2017).

Fig. 6A in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 6A. Immature development of Cicadella viridis under outdoor conditions (Ixelles, Belgium, 2016. Fig. 6B. Immature development of Cicadella viridis under controlled conditions (21.5°C; D:L= 9:15).

Fig. 9 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 9. Distribution map for Aphrophora alni in Belgium. Data: RBINS; Observations.be (2010-2016); our own samplings (2016-2017).

Fig. 12 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 12. Phenology of adult Aphrophora salicina in Belgium. Data: RBINS; Observations.be (2005-2017); our own samplings (2016-2017).

Fig. 10 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 10. Phenology of adult Aphrophora alni in Belgium. Data: RBINS; Observations.be (2005-2017); our own samplings (2016-2017).

Fig. 13 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 13. Immature development of Aphrophora salicina under outdoor conditions (Ixelles, Belgium, 2016.

Fig. 5 in Distribution, adult phenology and life history traits of potential insect vectors of Xylella fastidiosa in Belgium

Fig. 5. Phenology of adult Cicadella viridis in Belgium. Data: RBINS; Observations.be (2005-2017); our own samplings (2016-2017).

Fig. 2 A in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 2 A Manhattan plot of the V. arizonica genome showing markers associated with bacterial load. The plot denotes each of the 19 chromosomes for haplotype 1. Each circle represents a SNP with a corresponding p value, based on EMMAX genome-wide association analysis. The 25 SNPs that were detected in two separate GWA analyses are circled in red and define the 8 peaks of association, which are numbered as P1, P2, etc., and referred to in the text. In addition to SNPs, the locations of significantly associated kmers and CNVs are provided when they overlap with a SNP-defined peak. The colored horizontal lines represent the cut-off p-values (P <0.05, Bonferroni corrected) for the different marker types. Significant (P <0.05, Bonferroni corrected) kmers and CNVs are represented by red and blue triangles, respectively.

Fig. 1 Vitis arizonica sampling and phenotypes. A in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 1 Vitis arizonica sampling and phenotypes. A map of the Southwestern United States and Northern Mexico indicates sampling locations of the n = 167 V. arizonica accessions used in this study. The color of sample locations (circles) are colored according to their resistance phenotype, as measured by bacterial load (CFU/mL). The histogram of phenotypes (in CFU/mL) is to the right of the map. Map generation relied on information from GADM, a publicly available database (http:gadm.org).

Fig. 5 in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 5 Relationships among resistance, genetic markers and bioclimatic data. a The estimated relative importance, from GF modeling, of each of the bioclimatic variables tested. The y-axis is a measure of the importance of various variables to explain the model - i.e., the relative importance of each bioclimatic variable for predicting changes in allele frequency across the landscape. Each boxplot denotes the average inferred importance of the bioclimatic variable, with the whiskers plotting the standard deviation of 1000 separate analyses (gray dots). BIO8 was estimated to have the biggest impact on the model in all 1000 analyses. b The turnover function showing the temperature range of BIO8 on the x-axis and the change in the genetic composition on the y-axis. The circles represent individuals that are colored by resistance (gray) or susceptible (white). c Individual predictors in a linear model to predict resistance levels (CFU/ml). The label score_ref represents sets of 1000 randomly chosen sets of 25 SNPs; K1 and K2 are the proportion of the assignments to each admixture group for each individual. The other predictors include bioclimatic variables and genomic data, as listed in the text, each evaluated 1000 times with bootstrapped datasets. Each boxplot reports the second and third quartiles, with median values in the square and circles showing outliers. The barplot whiskers report standard deviation, and the dashed horizontal line reflects the median value of 1000 replicates of the Rpd score. d The density distribution of BIO8 for a global database of locations of Xylella fastidiosa detection.

Fig. 4 in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 4 The presence of resistance and susceptibility kmers in different data sets. a Analyses within the V. arizonica sample set. The top-left graph indicates the 99 different resistance (R-kmers) kmers across the x-axis, with their detection frequency across the resistant (CFU/mL <13) accessions. The top-right graph plots the average detection frequency of susceptibility kmers (S-kmers). The bottom-left and bottom-right graph are similar, they but show R-kmer and S-kmer detection frequencies among susceptible accessions. b The same graphs as in A, but the top graphs plot R-kmer and S-kmer detection frequencies for the five V. vinifera cultivars bred for PD resistance by backcrossing to V arizonica, while the bottom graphs represent susceptible V. vinifera cutlivars. c. Plots of kmer frequencies in six Vitis species. The species phylogeny is shown on the left, with the average detection frequency of R-kmers shown in red dot. The gray dots represent average detection frequencies of randomly chosen kmers that had similar population frequencies in V. arizonica as the set of R kmers. Whiskers denote 95% confidence intervals.