Do fungi look like macroparasites? Quantifying the patterns and mechanisms of aggregation for host-fungal parasite relationships
Sarah A. R. SchrockiD, Jason M. WalsmaniD, Joseph A. DeMarchiiD, Emily H. Le SageiD, Michel E. B. OhmeriD, Louise A. Rollins‐SmithiD, Cheryl J. BriggsiD, Corinne L. Richards‐ZawackiiD, Douglas C. WoodhamsiD, Roland A. KnappiD, Thomas C. SmithiD, Célio F. B. HaddadiD, Carlos Guilherme BeckeriD, Pieter T. J. JohnsoniD, Mark Q. Wilber
Abstract
Most hosts contain few parasites, whereas few hosts contain many. This pattern, known as aggregation, is well-documented in macroparasites where parasite intensity distribution among hosts affects host-parasite dynamics. Infection intensity also drives fungal disease dynamics, but we lack a basic understanding of host-fungal aggregation patterns, how they compare to macroparasites, and if they reflect biological processes. To address these gaps, we characterized aggregation of the fungal pathogen Batrachochytrium dendrobatidis (Bd) in amphibian hosts. Utilizing the slope of Taylors Power Law, we found Bd intensity distributions were more aggregated than macroparasites, conforming closely to lognormal distributions. We observed that Bd aggregation patterns are strongly correlated with known biological processes operating in amphibian populations, such as epizoological phase--invasion, post-invasion, and enzootic--and intensity-dependent disease mortality. Using intensity-dependent mathematical models, we found evidence of evolution of host resistance based on aggregation shifts in systems persisting with Bd following disease-induced declines. Our results show that Bd aggregation is highly conserved across disparate systems and is distinct from aggregation patterns in macroparasites, and contains signatures of potential biological processes of amphibian-Bd systems. Our work lays a foundation to unite host-fungal dynamics under a common theoretical framework and inform future modeling approaches that may elucidate host-fungus interactions.
02 /Specification & Classification
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