Interactive effects of climate change and pathogens on plant performance: a global meta-analysis

Plant health is increasingly threatened by abiotic and biotic stressors
linked to anthropogenic global change. These stressors are frequently
studied in isolation. However, they might have non-additive (antagonistic
or synergistic) interactive effects that affect plant communities in
unexpected ways. We conducted a global meta-analysis to summarize existing
evidence on the joint effects of climate change (drought, warming) and
biotic attack (pathogens) on plant performance. We also investigated the
effect of drought and warming on pathogen performance, as this information
is crucial for a mechanistic interpretation of potential indirect effects
of climate change on plant performance mediated by pathogens. The final
databases included 1230 pairwise cases extracted from 117 recently
published scientific articles (dating from 2006) on a global scale. We
found that the combined negative effects of drought and pathogens were
lower than expected based on their main effects, supporting the existence
of antagonistic interactions. Thus, the larger the magnitude of the
drought, the lower was the pathogen capacity to limit plant growth. On the
other hand, the combination of warming and pathogens caused larger plant
damage than expected, supporting the existence of synergistic
interactions. Our results on the effects of drought and warming on
pathogens revealed a limitation of their growth rates and abundance in
vitro but improved under natural conditions, where multiple factors
operate across the microbiome. Further research on the impact of climate
change on traits explicitly defining the infective ability of pathogens
would enhance the assessment of its indirect effects on plants. The
evaluated plant and pathogen responses were conditioned by the intensity
of drought or warming and by moderator categorical variables defining the
pathosystems. Overall, our results clearly support the need to incorporate
both abiotic and biotic components of global change into predictive models
of plant performance due to the prevalence of non-additive interactions.