Parasite and pathogen effects on ecosystem processes: A quantitative review

Pathogens and parasites (henceforth “pathogens”) can make up a large percentage of the biomass found in ecosystems, and therefore, their impacts on ecosystem processes should be prominent. Pathogens influence ecosystem processes by affecting the abundance or phenotype of hosts and through direct contributions to ecosystem production. However, there has been little quantitative synthesis of the relative effect sizes of these impacts on ecosystem processes. This study presents a systematic review and meta-analysis of pathogen effects on primary production, secondary production, and biogeochemical cycles. We find that the effects of pathogens on ecosystem processes were greater where pathogens influenced host or community abundance or biomass than when they influenced phenotypes. Pathogen impacts on primary production were larger than on secondary production or biogeochemical cycles. By contrast, we detected no general differences in effect sizes across host or pathogen taxon or ecosystem type (terrestrial vs. aquatic). While we have found potential evidence of publication bias against negative results, a well-known issue in meta-analyses, our work nonetheless shows that the available literature under-represents some taxa and geographic regions. To better understand the extent and magnitude of pathogen impacts on ecosystem processes, future research is needed in four areas. First, research is needed on the most understudied systems, including bacteria and viruses, as well as tropical ecosystems. A second priority is research seeking to understand how key components of ecosystem variation, including age (time of ecological continuity), productivity, and species diversity and composition, may interact to mediate pathogen impacts. Third, we suggest expanding on work examining how pathogen effects are influenced by climate change, species introductions, deforestation, and other human impacts. Fourth, we expect that host coinfection influences ecosystem processes in ways that cannot always be predicted based on studies of single infections. To enable others to build on this work, we make available the data we extracted from the literature, with the code for computing effect sizes.