Multiple niche components predict the strength of priority effects

Background/Question/Methods

Predicting the strength of priority effects among species remains difficult, presenting a major challenge in explaining variation in the structure and function of ecological communities. Here we argue that mechanistic predictions of the strength of priority effects within and among environments are possible by considering three related but distinct components of the species’ niche, namely, impact niche, requirement niche, and niche overlap. Specifically, we develop four general hypotheses: 1) Species that impact the environment to a larger extent will exert stronger priority effects, 2) species whose growth rate is more sensitive to changes in the environment will experience stronger priority effects, 3) priority effects are stronger among species with higher niche overlap, and 4) environments that support more rapid growth will be characterized by stronger priority effects. We test these predictions using nectar yeast communities grown in four synthetic nectar environments that included a factorial design manipulating initial resource availability and environmental harshness.  Pairwise priority effects were observed after five days of growth and changes to environmental conditions imposed by yeast species were quantified. We calculated multiple metrics to represent niche components and used model selection to determine which components predict the strength of priority effects.

Results/Conclusions

The strength of priority effects varied among nectar environments, and was stronger in benign than in harsh conditions. All niche components significantly affected the strength of priority effects. Species with high overlap in resource use exert strong priority effects (PE), and niche overlap explained 23% of total variation in PE. A species’ impact on the environment (% amino acids remaining) was positively correlated with PE, and explained 11% of variation in the response variable. Priority effects were stronger in benign than harsh environments (5.8% variance explained), and the response of species to changes in environmental resource level was positively correlated with PE (6.7% variance explained). We conclude that separating multiple niche components improves our understanding of the mechanisms that underlie priority effects and increases our ability to predict when such effects will be important in natural systems.