Consumers (predators or pathogens) can respond to increasing resource (prey or host) density in multiple ways. When consumer success increases consumer abundance (the numerical response), per capita predation or infection risk increases with resource density. However, consumers can become saturated at high resource density (the functional response), resulting in the opposite pattern – decreasing risk with increasing resource density (safety in numbers). Finally, consumers can be attracted to dense resource populations (the aggregative response), thereby increasing per capita risk. The numerical, functional and aggregative responses combine to allow consumers to stabilize or destabilize resource population dynamics. However, because these responses operate over different spatial and temporal scales, the results of a study can depend on the scale at which it is conducted. Often theoretical predictions are made at large scales, whereas empirical tests are conducted at small scales.
Results/Conclusions
To resolve mismatches between theoretical and empirical studies that occur at different spatial and temporal scales, we modify the General Consumer-Resource Model to include scale. Specifically, our model includes the numerical, functional, and aggregative responses, and tracks how per capita predation or infection risk changes with resource density across scales from local to global. We use scale transition theory to account for patchy resources. We find that safety in numbers reverses with scale; the functional response dominates in small-scale studies, whereas the numerical response dominates in large-scale studies. Furthermore, resource patchiness decreases risk, but consumer aggregation can overcome this effect. Additionally, we find that safety in numbers is stronger for predators than for pathogens, suggesting that pathogens should be more likely than predators to stabilize resource populations. Hence, density-dependent regulation of resource populations by consumers changes with scale.