Plant disease risk is modified by multiple global change drivers

Diversity inhibits foliar fungal diseases in grasslands: Potential mechanisms and temperature dependence

A long-standing debate exists among ecologists as to how diversity regulates infectious diseases (i.e., the nature of diversity-disease relationships); a dilution effect refers to when increasing host diversity inhibits infectious diseases (i.e., negative diversity-disease relationships). However, the generality, strength, and potential mechanisms underlying negative diversity-disease relationships in natural ecosystems remain unclear. To this end, we conducted a large-scale survey of 63 grassland sites across China to explore diversity-disease relationships. We found widespread negative diversity-disease relationships that were temperature-dependent; non-random diversity loss played a fundamental role in driving these patterns. Our study provides field evidence for the generality and temperature dependence of negative diversity-disease relationships in grasslands, becoming stronger in colder regions, while also highlighting the role of non-random diversity loss as a mechanism. These findings have important implications for community ecology, disease ecology, and epidemic control.

Phenological evolution in annual plants under light competition, changes in the growth season and mass loss

Flowering time is an important phenological trait in plants and a critical determinant of the success of pollination and fruit or seed development, with immense significance for agriculture as it directly affects crop yield and overall food production. Shifts in the growth season, changes in the growth season duration and changes in the production rate are environmental processes (potentially linked to climate change) that can lead to changes in flowering time in the long-term due to selection. In contrast, biomass loss (due to, for example, herbivory or diseases) can have profound consequences for plant mass production and food security. We model the effects of these environmental processes on the flowering time evolutionarily stable strategy (ESS) of annual plants and the potential consequences for reproductive output. Our model recapitulates previous theoretical results linked to climate change and light competition and makes novel predictions about the effects of biomass loss on the evolution of flowering time. Our analysis elucidates how both the magnitude and direction of the evolutionary response can depend on whether biomass loss occurs during the earlier vegetative phase or during the later reproductive phase and on whether or not plants are adapted to grow in dense, competitive environments. Specifically, light competition generates an asymetric effect of mass loss on flowering time even when loss is indiscriminate (equal rates), with vegetative mass loss having a stronger effect on flowering time (resulting in greater ESS change) and final reproductive output.

Label-Free Surface-Enhanced Raman Scattering Detection of Fire Blight Pathogen Using a Pathogen-Specific Bacteriophage

Fire blight is one of the most devastating plant diseases, causing severe social and economic problems. Herein, we report a novel method based on label-free surface-enhanced Raman scattering (SERS) combined with an Erwinia amylovora-specific bacteriophage that allows detecting efficiently fire blight bacteria E. amylovora for the first time. To achieve the highest SERS signals for E. amylovora, we synthesized and compared plasmonic nanoparticles (PNPs) with different sizes, i.e., bimetallic gold core-silver shell nanoparticles (Au@AgNPs) and monometallic gold nanoparticles (AuNPs) and utilized the coffee-ring effect for the self-assembly of PNPs and enrichment of fire blight bacteria. Furthermore, we investigated the changes in the SERS spectra of E. amylovora after incubation with an E. amylovora-specific bacteriophage, and we found considerable differences in the SERS signals as a function of the bacteriophage incubation time. The results indicate that our bacteriophage-based label-free SERS analysis can specifically detect E. amylovora without the need for peak assignment on the SERS spectra but simply by monitoring the changes in the SERS signals over time. Therefore, our facile method holds great potential for the label-free detection of pathogenic bacteria and the investigation of viral-bacterial interactions.

No plant is an island

Most of the world's ecosystems are dominated by plants, and preserving the natural and agricultural landscapes that we depend on therefore requires understanding plants and their interactions at local and global scales. This is challenging because plants' ways of perceiving each other and communicating with each other and with animals are so fundamentally different from the ways we animals communicate with, and manipulate, each other. The collection of articles in the present issue of Current Biology illustrates the progress being made in deciphering some of the processes and mechanisms involved in plant interactions at different scales. While the topic of interactions with plants is very broad, any overview will require covering chemical signals and their reception; mutualisms and symbioses; interactions with pathogens; and interactions in communities. Approaches taken in these fields range from molecular biology and physiology to ecology.