Strain and vegetation effects on local limiting resources explain the outcomes of biotic interactions

Positive interactions are hypothesized to increase with stress (stress-gradient hypothesis, “SGH”), which is defined in terms of standing biomass at the community level. However, recent evidence suggests that facilitation may decrease or remain constant as stress increases. Several reasons for this discrepancy are possible: (i) the outcomes of biotic interactions depend on the component of the fitness considered; (ii) they are influenced by how vegetation affects local limiting resources; (iii) within a particular community, only species that are deviated from their physiological optima are likely to be facilitated. In a removal experiment, we quantified the deviations of species in subalpine grassland from their physiological optima, defined here as species-level “strain”, and examined whether strain and vegetation effects on local resources can explain the outcome of biotic interactions. The experiment was performed along a gradient of standing biomass driven by contrasting land use and resource availability, and used five grass species with contrasting traits and ecological optima. Strain for each species was estimated by comparing growth without vegetation (target species only submitted to local abiotic factors) to growth in optimal conditions (under controlled conditions in an experimental garden). The outcomes of biotic interactions, recorded in terms of survival and growth, could be predicted from the data about strain and vegetation effects on local limiting resources (light and water). Only highly strained species were affected by facilitation, which occurred when the surrounding vegetation alleviated the constraining factors. On the other hand, standing biomass was poorly related with the outcomes of biotic interactions. The “SGH” was only partially validated with growth data when strain and vegetation effects co-varied with standing biomass. As a consequence, strain (at species level) represents a mechanistic basis which could improve the prediction of the outcomes of biotic interactions along ecological gradients.