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Long-Distance Dispersal of Fungi

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  • Authors: Jacob J. Golan1, Anne Pringle2
  • Editors: Joseph Heitman3, Pedro W. Crous4
    Affiliations: 1: Department of Botany, Department of Bacteriology, University of Wisconsin–Madison, Madison, WI 35706; 2: Department of Botany, Department of Bacteriology, University of Wisconsin–Madison, Madison, WI 35706; 3: Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC 27710; 4: CBS-KNAW Fungal Diversity Centre, Royal Dutch Academy of Arts and Sciences, Utrecht, The Netherlands
  • Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
  • Received 05 February 2017 Accepted 01 May 2017 Published 14 July 2017
  • Jacob J. Golan, jacobjgolan@gmail.com
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  • Abstract:

    Dispersal is a fundamental biological process, operating at multiple temporal and spatial scales. Despite an increasing understanding of fungal biodiversity, most research on fungal dispersal focuses on only a small fraction of species. Thus, any discussion of the dispersal dynamics of fungi as a whole is problematic. While abundant morphological and biogeographic data are available for hundreds of species, researchers have yet to integrate this information into a unifying paradigm of fungal dispersal, especially in the context of long-distance dispersal (LDD). Fungal LDD is mediated by multiple vectors, including meteorological phenomena (e.g., wind and precipitation), plants (e.g., seeds and senesced leaves), animals (e.g., fur, feathers, and gut microbiomes), and in many cases humans. In addition, fungal LDD is shaped by both physical constraints on travel and the ability of spores to survive harsh environments. Finally, fungal LDD is commonly measured in different ways, including by direct capture of spores, genetic comparisons of disconnected populations, and statistical modeling and simulations of dispersal data. To unify perspectives on fungal LDD, we propose a synthetic three-part definition that includes (i) an identification of the source population and a measure of the concentration of source inoculum and (ii) a measured and/or modeled dispersal kernel. With this information, LDD is defined as (iii) the distance found within the dispersal kernel beyond which only 1% of spores travel.

  • Citation: Golan J, Pringle A. 2017. Long-Distance Dispersal of Fungi. Microbiol Spectrum 5(4):FUNK-0047-2016. doi:10.1128/microbiolspec.FUNK-0047-2016.

Key Concept Ranking

Fungal Proteins
Asexual Spores
Sexual Spores
Fusarium graminearum


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Dispersal is a fundamental biological process, operating at multiple temporal and spatial scales. Despite an increasing understanding of fungal biodiversity, most research on fungal dispersal focuses on only a small fraction of species. Thus, any discussion of the dispersal dynamics of fungi as a whole is problematic. While abundant morphological and biogeographic data are available for hundreds of species, researchers have yet to integrate this information into a unifying paradigm of fungal dispersal, especially in the context of long-distance dispersal (LDD). Fungal LDD is mediated by multiple vectors, including meteorological phenomena (e.g., wind and precipitation), plants (e.g., seeds and senesced leaves), animals (e.g., fur, feathers, and gut microbiomes), and in many cases humans. In addition, fungal LDD is shaped by both physical constraints on travel and the ability of spores to survive harsh environments. Finally, fungal LDD is commonly measured in different ways, including by direct capture of spores, genetic comparisons of disconnected populations, and statistical modeling and simulations of dispersal data. To unify perspectives on fungal LDD, we propose a synthetic three-part definition that includes (i) an identification of the source population and a measure of the concentration of source inoculum and (ii) a measured and/or modeled dispersal kernel. With this information, LDD is defined as (iii) the distance found within the dispersal kernel beyond which only 1% of spores travel.

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Image of FIGURE 1

A framework for understanding fungal LDD.

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Image of FIGURE 2

Sizes of fungal spores and other airborne particles. Some species are wind dispersed (e.g., ), while others have other means of dispersal (e.g., ). The smallest plant seed, , the pollen grains of and , and a glomerospore of the arbuscular mycorrhizal are provided for comparison. Species labeled with an asterisk are not fungi.

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Image of FIGURE 3

To integrate the disparate approaches used to describe and measure fungal LDD, we propose a synthetic three-part definition building on the general framework presented by Nathan ( 1 , 28 ). A description of fungal LDD should include (i) identification of a source population and measure of source inoculum concentration (e.g., the number of spores in a single rust pustule), (ii) a measured and/or modeled dispersal kernel, and (iii) a measure of the distance, based on the dispersal kernel, past which only 1% of spores travel. Adopting a standard approach would mitigate the confusion caused by differing definitions and measurements of LDD and facilitate comparisons among the dispersal kernels of different species. In the illustration, the blue and red dispersal kernels demonstrate idealized kernels for two hypothetical species. LDD is defined per species at distances A and B, respectively—the distance beyond which only 1% of spores travel. We next used our approach with real dispersal data of (measured as the number of resistant lesions per square meter of banana leaf measured from a source to 1,000 m) ( 52 ), (measured as the recovery rate of ascospores of a unique clone released from a source to 1,000 m) ( 58 ), and (measured as the proportion of DNA from snow samples identical to an isolated source of soredia up to a distance of 40 m [ 193 ]) to estimate dispersal kernels and identify LDD for each species. We smoothed the published data to estimate an approximate dispersal kernel, and the distance beyond which 1% of spores traveled was found by integrating the area under each kernel from 0 m to the distance at which 99% of spores had been captured. Although both and are capable of dispersing to approximately 1,000 m, the proportion of spores that fit our definition of LDD varies considerably, because LDD is defined past 714 m for and past 250 m for . A holistic comparison of the two dispersal kernels suggests that different dynamics will shape the effective reach of each species. The dispersal kernel of illustrates how truncated experimental setups can impact measures of LDD. At the furthest collection point (40 m), a large proportion of samples tested positive, and the best dispersal kernel that can be modeled from the data ( 193 ) provides what is likely an underestimate of LDD, at approximately 39 m (15% of the positive samples collected at 0 m were detected). Ideally, the tail end of a modeled dispersal kernel should very closely approach a horizontal line at = 0.

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Image of FIGURE 4

A phylogram of genetic distances among 15 geographic populations of . The fact that geographically distant populations of are grouped together, e.g., Uruguayan populations are grouped with Algerian and Syrian populations, likely suggests movement mediated by humans. infects one of the most traded agricultural products (wheat), and its ascospores cannot survive prolonged exposure to, e.g., dry air ( 183 ). Data adapted from Zhan et al. ( 64 ); similar clustering of geographically distant populations is found from data on ( 129 ), ( 131 ), and ( 60 ).

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Image of FIGURE 5

Images of various fungal spores. Basidiospores of (brown powder) next to seeds of (semicircles) and sugar crystals (white cubes). Urediniospores of (Fig. 1 of reference 194 ). Conidia of and . is a putative long-distance disperser, while (10× in size) is not (courtesy of Steve Jordan). Glomerospore of (Fig. 5i of reference 195 ). Conidium of (Fig. 5c of reference 196 ). Teliospore of (Fig. 9 of reference 197 ). Urediniospore of (Fig. 1e of reference 198 ). Urediniospore size, shape, and ornamentation of (Fig. 1d of reference 199 ). Zoospores of chytrid ( 200 ). Ascospores of ( 200 ). Sporangiospores of var. ( 200 ). Basidiospores of still on soredia ( 200 ). Conidia of the aquatic ascomycete (Fig. 66 of reference 92 ).

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Image of FIGURE 6

Comparing spore sizes to reported maximum dispersal distances. Spore volume in square micrometers is measured on the left-hand vertical axis, and spore Q-ratio (the ratio of spore length to width) is measured on the right. Data points were calculated from the parameters listed in Table 1 . There is a poor correlation between approximate maximum dispersal distance and both average spore volumes (R = 0.0167, = 0.5568) and Q-ratios (R = 0.1113, = 0.1198). The lack of any correlation likely reflects inconsistent definitions and measurements of LDD, rather than any biological reality.

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Image of FIGURE 7

Images of spore dispersal structures among fungi. Basidiospores of carried vertically by evaporative airflows from mushroom cap (Fig. 1e of reference 174 ). Hypogeous spore body of (Wikimedia Commons Creative Commons Attribution-Share Alike 3.0 Unported [WC]). Sporangium of releasing sporangiospores (courtesy of Andrii Gryganskyi). mushroom (Doug Collins, WC). Synchronous spore release from apothecia (Fig. 1b of reference 135 ). Asci of ( 200 ). Apothecia of ( 200 ). Typical gilled agaric mushroom with gills to increase surface area of spore-producing tissue (WC).

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016
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Spore parameters for putative long-distance dispersers

Source: microbiolspec July 2017 vol. 5 no. 4 doi:10.1128/microbiolspec.FUNK-0047-2016

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