Model predictions
Using our dynamical models (Box 1 and Box 2), we evaluated whether the
patterns of trait sensitivity to stressors we documented in the
meta-analysis reduce or increase infection prevalence across stress
gradients and how stressors ultimately impact host population densities.
The SI-Resource model predicts that a decrease in resource productivity
decreases infection prevalence (Fig. 5A), in part because host densities
also decrease with limited resources (Fig. 5C). Once a pathogen
establishes in a population, there is stabilizing feedback, where
pathogens suppress host density, increasing resources, and further
increasing transmission. Therefore, in all scenarios of sensitivity of
pathogen transmissibility to resources (smaller values of the
half-saturation transmission constant (ht) increase the
sensitivity of transmission rate (β) to resources), the model reaches
the same prevalence equilibrium. However, although population density
also stabilizes, the impacts on host density are different for each
scenario: populations that are more sensitive to resources available
will reach smaller population sizes compared to less sensitive
populations (Fig. 5C)
The SI-Environmental stress gradient models show that population density
decreases regardless of the effects of stress on hosts susceptibility
due to increased mortality. But it exponentially decreases host
populations when transmission rate is sensitive to the environmental
factor (Fig. 5B and D). Specifically, when stress increases host
susceptibility (i.e., greater values of βE), infection
prevalence will increase rapidly (Fig. 5B) but at the cost of increasing
host mortality (Fig. 5D). Therefore, infection prevalence will have a
maximum at intermediate stress level but will drop as population
densities are too low to sustain transmission. In contrast, as
transmission is more negatively affected by stressors (i.e., pathogens
are negatively affected by stressors), infection prevalence will quickly
reach zero with increasing environmental stress (Fig. 5B). But as the
stress increase and persist, populations will decline after the pathogen
is extirpated from the system (Fig. 5D).
Our models illustrate that the consequences of stress gradients on
disease can depend on the sensitivity that host traits, such as births
and deaths, and shared host-pathogen traits, such as transmission (i.e.,
β) have to stressors. Interestingly, and consistent with Lafferty &
Holt (2003) simulations, our models showed that increased environmental
stress generally decreased disease, mainly driven by host density
reductions. Although stress can make hosts more likely to become
infected at the individual level, at the population level, negative
impacts on host survival and reproduction may be driving pathogen and
host local extinctions (Lafferty & Holt 2003).