Disease ecologists now recognize the limitation behind examining host-parasite interactions in isolation: community members – especially predators – dramatically affect host-parasite dynamics. Although the initial paradigm was that predation should reduce disease in prey populations (“healthy herds hypothesis”), researchers have realized that predators sometimes increase disease in their prey. These “predator-spreaders” are now recognized as critical to disease dynamics, but empirical research on the topic remains fragmented. In a narrow sense, a “predator-spreader” would be defined as a predator that mechanically spreads parasites via feeding. However, predators affect their prey and, subsequently, disease transmission in many other ways such as altering prey population structure, behavior, and physiology. We review the existing evidence for these mechanisms and provide heuristics that incorporate features of the host, predator, parasite, and environment to understand whether or not a predator is likely to be a predator-spreader. We also provide guidance for targeted study of each mechanism and quantifying the effects of predators on parasitism in a way that yields more general insights into the factors that promote predator-spreading. We aim to offer a better understanding of this important and underappreciated interaction and a path towards being able to predict how changes in predation will influence parasite dynamics.

As an essential micronutrient for many organisms, sodium plays an important role in ecological and evolutionary dynamics. Although plants mediate trophic fluxes of sodium, from substrates to higher trophic levels, we know relatively little about plants’ comparative growth and sodium accumulation responses to variation in substrate sodium. We carried out a systematic review to examine how plants respond to variation in substrate sodium concentrations. We compared growth and tissue-sodium responses among 107 populations (67 species in 20 plant families), broadly expanding beyond the agricultural and model taxa for which several generalizations previously have been made. We hypothesized a priori response models for each population’s growth and sodium accumulation responses as a function of increasing substrate NaCl. We used BIC to choose the best model. Additionally, using a phylogenetic signal analysis, we tested for phylogenetic patterning of growth and sodium accumulation responses across plant taxa. The influence of substrate sodium on growth differed across taxa, with most populations experiencing detrimental effects at high concentrations. Irrespective of growth response, tissue concentrations of sodium for most taxa increased as sodium concentrations in the substrate increased. We found no strong associations between growth and types of sodium accumulation responses across taxa. Our phylogenetic signal analyses found that evolutionary history helps predict the distribution of total plant growth responses across the phylogeny, but not sodium accumulation responses. Our study suggests that saltier plants in saltier soils may prove to be a broadly general pattern for sodium across plant taxa. Regardless of growth responses, sodium accumulation mostly followed an increasing trend and did not have any evident association with growth responses as substrate sodium levels increased. Finally, plant adaptations to substrate sodium vary with a degree of phylogenetic conservatism.

Phenotypic plasticity can mask population genetic differentiation, reducing the predictability of trait-environment relationships. In short-lived plants, reproductive traits may be more genetically determined due to their direct impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with global field observations for the short-lived Plantago lanceolata, we 1) disentangled the genetic and plastic responses of functional traits to a set of environmental drivers and 2) assessed the utility of trait-environment relationshisps inferred from observational data for predicting genetic differentiation. Reproductive traits showed distinct genetic differentiation that was highly predictable from observational data, but only when correcting traits for differences in their (labile) biomass component. Vegetative traits showed higher plasticity and contrasting genetic and plastic responses, leading to unpredictable trait patterns. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related with fitness.