Plant Competition Varies with Community Composition in an Edaphically Complex Landscape

• Published in: Ecology (Durham) 2007-10, Vol.88 (10), p.2640-2650
• Main Authors: Elmendorf, Sarah C., Moore, Kara A.
• Format: Article
• Language: English
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Biological and medical sciences; Biomass; California; Communities; community composition; competition; Ecological competition; Ecology; Ecosystem; Environment; Environmental impact; Fundamental and applied biological sciences. Psychology; General aspects; Grasses; Grasslands; Heavy metals; McLaughlin Natural Reserve; NMDS; Nutrient availability; Nutrients; Plants; Poaceae - growth & development; Population Dynamics; Productivity; relative interaction intensity; reproductive fitness; Restoration ecology; RII; serpentine; Soil; Species; Species Specificity; stress gradients; Synecology; USA
• ISSN: 0012-9658; 1939-9170
• DOI: 10.1890/06-1155.1

There is currently no consensus on how physical and biological factors affect competitive intensity. Tests of whether competitive intensity varies along axes of environmental change have commonly been conducted in systems with a single strong environmental gradient, such as productivity, a soil resource, or an environmental stress. Frequently, these same axes are associated with changes in species composition, yet few studies have asked whether shifts in the identity of competitors affect competitive intensity. We ask whether resources (nutrients, water), stressors (heavy metals, Ca:Mg ratio), productivity (aboveground biomass), or species identity (an ordination axis of plant community composition) were the best predictors of the intensity of competition in a heterogeneous grassland landscape that included multiple independent environmental gradients. The reproductive fitness of six annual plant species was measured in the presence and absence of competitors and used to calculate relative interaction intensity (RII). We found that RII was best predicted by community composition. Nutrient availability was also important, and a post hoc test showed that competitive intensity was best explained by the combined effects of community composition and nutrient availability. We argue that community composition may be the most effective metric for predicting competitive intensity in many ecosystems because it includes both the competitive effects of the local community and information about covarying environmental characteristics.