Mutualism describes the biological phenomenon where two or more species are reciprocally beneficial, regardless of their ecological intimacy or evolutionary history. Classic theory shows that mutualistic benefit must be relatively weak, or else it overpowers the stabilizing influence of intraspecific competition and leads to unrealistic, unbounded population growth. Interestingly, the conclusion that strong positive interactions lead to runaway population growth is strongly grounded in the behavior of a single model. This model-the Lotka-Volterra competition model with a sign change to generate mutualism rather than competition between species-assumes logistic growth of each species plus a linear interaction term to represent the mutualism. While it is commonly held that the linear interaction term is to blame for the model's unrealistic behavior, we show here that a linear mutualism added to a θ-logistic model of population growth can prevent unbounded growth. We find that when density dependence is decelerating, the benefit of mutualism at equilibrium is greater than when density dependence is accelerating. Although there is a greater benefit, however, decelerating density dependence tends to destabilize populations whereas accelerating density dependence is always stable. We interpret these findings tentatively, but with promise for the understanding of the population ecology of mutualism by generating several predictions relating growth rates of mutualist populations and the strength of mutualistic interaction.

While plant community theory tends to emphasize the importance of abiotic heterogeneity along niche axes, much empirical work seeks to characterize the influence of the absolute magnitude of key abiotic variables on diversity. Both magnitude (as reflected, e.g., by a mean) and heterogeneity (variance) in abiotic conditions likely contribute to biodiversity patterns in plant communities, but given the large number of putative abiotic drivers and the fact that each may vary at different spatiotemporal scales, the challenge of linking observed biotic patterns with the underlying environment remains acute. Using monitoring data from a natural resource agency, we compared how well statistical models of the mean, heterogeneity, and both the mean and heterogeneity combined of 17 abiotic factor variables explained patterns of forb species richness in Northeast Ohio, USA. We performed our analyses at two spatial scales, repeated in spring and summer across four forest types. Although all models explained a great deal of the variance in species richness, models including both the mean and heterogeneity of different abiotic factors together outperformed models including either the mean or the heterogeneity of abiotic factors alone. Variability in forb species richness was mostly due to changes in mean calcium levels regardless of forest type. After accounting for forest type, we were able to attribute variation in forb species richness to changes in the heterogeneity of different abiotic factors as well. Our results suggest that multiple mechanisms act simultaneously according to different aspects of the abiotic environment to structure forb communities, and this underscores the importance of considering both the magnitude of and heterogeneity in multiple abiotic factors when looking for links between the abiotic environment and plant community patterns. Finally, we identify novel patterns across spatial scales, forest types, and seasons that can guide future research in this vein.OPEN RESEARCH BADGES This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at https://doi.org/10.5061/dryad.kp3cb17.

During community assembly, abiotic factors can influence species at multiple stages during their life history, for example by affecting early settlement or establishment probabilities and thus initial densities (route 1: abiotic effects on density), or later by affecting the strength of biotic interactions during subsequent life stages (route 2: abiotic effects on interaction strengths). Since real abiotic landscapes are multivariate and complex, how these two distinct routes of abiotic influence affect community patterns has not been quantified. Using an individual-based spatially explicit simulation model, we compared scenarios where abiotic conditions shaped initial densities, interaction strengths, or both, of plant species with unique abiotic niches. We then partitioned the effect of the abiotic landscape on community patterns into components arising from variable density, variable interaction strengths, and their interaction. Even when plants responded to identical landscapes, variable density and variable interaction strengths led to different community patterns, and their combined effects were non-additive. Variable density promoted more spatial structure, while variable interaction strengths promoted higher local species richness. We highlight important implications these findings have in applied plant community ecology.

Summary Difficulties quantifying pathogen load and mutualist abundance limit our ability to connect disease dynamics to host community ecology. For example, specific predictions about how differential pathogen load is hypothesised to drive host competitive outcomes are rarely tested. Additionally, although infection is known to affect mutualists, we rarely measure the magnitude of pathogen effects on mutualist abundance across host competitive contexts. We tested for both mechanisms in a plant–rhizobia–nematode system. We paired the legume Medicago lupulina with intraspecific and interspecific plant competitors, with and without a generalist nematode parasite Meloidogyne sp. Relative change in plant biomass was used to determine how nematode inoculation affected plant competitive outcomes. We counted nematode galls to test for direct effects of parasitism on plant competition and rhizobia nodules to test for indirect effects of nematode presence on rhizobium abundance. Parasites were destabilising despite similar nematode load across competition treatments. During interspecific compared with intraspecific competition, nematode inoculation decreased nodulation on M. lupulina, increased nodulation on Trifolium repens and had no effect on nodulation on Chamaecrista fasciculata. We found no support for hypothesised direct effects of nematode load on competitive outcomes and strong but idiosyncratic indirect effects of nematode inoculation on rhizobium abundance.