Florian Hartig

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Bayesian inference of environmental and biotic factors determining the occurrence of the grapevine disease ‘bois noir’

Bernd Panassiti, Florian Hartig, Michael Breuer & Robert Biedermann

Ecosphere, 6(8), 143 (2015)
Cite this
@article{panassiti2015bayesian,
  author = {Bernd Panassiti and Florian Hartig and Michael Breuer and Robert Biedermann},
  title = {Bayesian inference of environmental and biotic factors determining the occurrence of the grapevine disease ‘bois noir’},
  journal = {Ecosphere},
  volume = {6},
  number = {8},
  pages = {143},
  year = {2015},
  doi = {10.1890/ES14-00439.1},
}

DOI: 10.1890/ES14-00439.1
Citation statistics: 20 (Google Scholar) · 19 (OpenAlex), as of 29 October 2026

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Funding

This study was supported through funding by Association of German Wine Scientists (FDW).

View article (DOI)

Abstract

Insect‐vectored plant diseases often create complex epidemiological systems that are challenging to understand, predict, and manage. An example is ‘bois noir' (BN), a phytoplasma‐associated grapevine disease commonly found in European vineyards. Although BN has the potential to cause substantial economic damage, the factors that contribute to BN prevalence in vineyards are still not well understood. We used Bayesian inference with generalized linear mixed‐effect models to test the hypotheses that (1) grapevine varieties exhibit different BN susceptibility; (2) environment drivers influence prevalence of the disease and occurrence of the vector; and (3) the presence of the main vector is a major determinant of BN occurrence. We found that the presence of the vector Hyalesthes obsoletus increased with increasing isothermality, minimum temperatures during the coldest period, soil erosion, and natural vegetation in close proximity to the vineyards. Presence of the BN disease increased with presence of the vector as well as increasing altitudes and mean annual temperatures. After accounting for those factors, Chardonnay and Riesling showed higher disease prevalence than Müller‐Thurgau, Silvaner, and Merlot. Although the vector had an overall positive effect on the disease prevalence, disease and vector occurrence show distinct spatial patterns. In conclusion, our analysis suggests that vector presence is not the only, and maybe not the most important factor for BN disease prevalence. Environment and grape cultivar also play important roles. Hence, area‐wide predictions of both environmental disease risk and vector presence, together with information about the susceptibility of grape cultivars, will enable a more targeted disease management. Our modelling framework could easily be applied to other diseases of concern, such as apple proliferation or flavescence dorée.

What the paper shows and why it matters

(AI-generated)

Insect-borne plant diseases are tangled systems of host plants, insect vectors and pathogens, and good data on them are often missing. For the grapevine disease bois noir, management focuses mainly on controlling its main vector, the planthopper Hyalesthes obsoletus, which is reasonable for the main carrier. An earlier habitat model (Panassiti et al. 2013) mapped where the insect is likely to live but did not test whether the disease occurs in the same places. The paper takes on the implicit assumption that knowing where the vector occurs is enough to explain where the disease occurs, although other vectors, other host plants or differences in cultivar susceptibility could break that link.

The paper argues that the presence of the main vector explains only part of where bois noir occurs, so the distribution of the insect alone does not seem sufficient to explain the distribution of the disease. It tests this with a survey of more than 100,000 grapevines in the Baden region of south-west Germany, analysed with a Bayesian mixed regression model (infected versus healthy plants, allowing for differences between regions and owners, with uncertainty carried through). Vector presence, taken from the earlier habitat model, had a positive effect that the paper describes as relatively weak and seemingly variable across the region. The disease increased with altitude and mean annual temperature, and disease and vector seemed to prefer different environments, spatially separated except in the north-east. With environment accounted for, Chardonnay and Riesling had the highest disease prevalence.

Figure 4. Posterior predictions of ‘bois noir’ (BN) disease and H. obsoletus in SW Germany: (a) BN average predictions; (b) standard deviations of BN predictions; (c) H. obsoletus average predictions; and (d) standard deviations of H. obsoletus average predictions. From Panassiti et al. (2015), Ecosphere, licensed under CC BY 3.0. Click the image to enlarge.

The paper reads these results as a reason to add to vector control less susceptible cultivars and area-wide maps of disease risk and vector presence to target measures. It treats the cultivar pattern as a correlation needing experimental verification, because growers choose cultivars to suit the site, and leaves open why vector and disease diverge, naming environmental effects, other host plants and unknown vectors as candidates. It proposes the framework for other diseases, such as apple proliferation, without testing it there. Murolo et al. (2020) discuss the paper’s findings on climate and altitude against their own result that climate did not correlate with the spatial pattern of the disease.

References

  • Panassiti et al. (2013). Influence of environment and climate on occurrence of the cixiid planthopper Hyalesthes obsoletus, the vector of the grapevine disease ‘bois noir’. Bulletin of Entomological Research 103, 621–633. doi:10.1017/s0007485313000163
  • Murolo et al. (2020). Spatial pattern of Bois noir: case study of a delicate balance between disease progression and recovery. Scientific Reports 10, 9801. doi:10.1038/s41598-020-66210-7