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Measuring the shape of the biodiversity-disease relationship across systems reveals new findings and key gaps

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  • Fletcher W. Halliday

    (University of Zurich, Winterthurerstrasse 190)

  • Jason R. Rohr

    (University of Notre Dame)

Abstract

Diverse host communities commonly inhibit the spread of parasites at small scales. However, the generality of this effect remains controversial. Here, we present the analysis of 205 biodiversity–disease relationships on 67 parasite species to test whether biodiversity–disease relationships are generally nonlinear, moderated by spatial scale, and sensitive to underrepresentation in the literature. Our analysis of the published literature reveals that biodiversity–disease relationships are generally hump-shaped (i.e., nonlinear) and biodiversity generally inhibits disease at local scales, but this effect weakens as spatial scale increases. Spatial scale is, however, related to study design and parasite type, highlighting the need for additional multiscale research. Few studies are unrepresentative of communities at low diversity, but missing data at low diversity from field studies could result in underreporting of amplification effects. Experiments appear to underrepresent high-diversity communities, which could result in underreporting of dilution effects. Despite context dependence, biodiversity loss at local scales appears to increase disease, suggesting that at local scales, biodiversity loss could negatively impact human and wildlife populations.

Suggested Citation

  • Fletcher W. Halliday & Jason R. Rohr, 2019. "Measuring the shape of the biodiversity-disease relationship across systems reveals new findings and key gaps," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13049-w
    DOI: 10.1038/s41467-019-13049-w
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    Cited by:

    1. Chen, Shiliang & Liu, Xiang & He, Qiang & Zhou, Shurong, 2022. "Higher-order interactions on disease transmission can reverse the dilution effect or weaken the amplification effect to unimodal pattern," Ecological Modelling, Elsevier, vol. 474(C).
    2. Lin Zhang & Jason Rohr & Ruina Cui & Yusi Xin & Lixia Han & Xiaona Yang & Shimin Gu & Yuanbao Du & Jing Liang & Xuyu Wang & Zhengjun Wu & Qin Hao & Xuan Liu, 2022. "Biological invasions facilitate zoonotic disease emergences," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Magdalena Meyer & Dominik W. Melville & Heather J. Baldwin & Kerstin Wilhelm & Evans Ewald Nkrumah & Ebenezer K. Badu & Samuel Kingsley Oppong & Nina Schwensow & Adam Stow & Peter Vallo & Victor M. Co, 2024. "Bat species assemblage predicts coronavirus prevalence," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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