Turnover in species composition and the dominant functional strategies in plant communities across environmental gradients is a common pattern across biomes, and is often assumed to reflect shifts in trait optima. However, the extent to which community‐wide trait turnover patterns reflect changes in how plant traits affect the vital rates that ultimately determine fitness remain unclear. We tested whether shifts in the community‐weighted means of four key functional traits across an environmental gradient in a southern California grassland reflect variation in how these traits affect species' germination and fecundity across the landscape. We asked whether models that included trait–environment interactions help explain variation in two key vital rates (germination rates and fecundity), as well as an integrative measure of fitness incorporating both vital rates (the product of germination rate and fecundity). To do so, we planted seeds of 17 annual plant species at 16 sites in cleared patches with no competitors, and quantified the lifetime seed production of 1360 individuals. We also measured community composition and a variety of abiotic variables across the same sites. This allowed us to evaluate whether observed shifts in community‐weighted mean traits matched the direction of any trait–environment interactions detected in the plant performance experiment. We found that commonly measured plant functional traits do help explain variation in species responses to the environment—for example, high‐SLA species had a demographic advantage (higher germination rates and fecundity) in sites with high soil Ca:Mg levels, while low‐SLA species had an advantage in low Ca:Mg soils. We also found that shifts in community‐weighted mean traits often reflect the direction of these trait–environment interactions, though not all trait–environment relationships at the community level reflect changes in optimal trait values across these gradients.
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Abstract Synthesis . Our results show how shifts in trait–fitness relationships can give rise to turnover in plant phenotypes across environmental gradients, a fundamental pattern in ecology. We highlight the value of plant functional traits in predicting species responses to environmental variation, and emphasise the need for more widespread study of trait–performance relationships to improve predictions of community responses to global change. -
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Abstract When species simultaneously compete with two or more species of competitor, higher‐order interactions (HOIs) can lead to emergent properties not present when species interact in isolated pairs. To extend ecological theory to multi‐competitor communities, ecologists must confront the challenges of measuring and interpreting HOIs in models of competition fit to data from nature. Such efforts are hindered by the fact that different studies use different definitions, and these definitions have unclear relationships to one another. Here, we propose a distinction between ‘soft’ HOIs, which identify possible interaction modification by competitors, and ‘hard’ HOIs, which identify interactions uniquely emerging in systems with three or more competitors. We show how these two classes of HOI differ in their motivation and interpretation, as well as the tests one uses to identify them in models fit to data. We then show how to operationalise this structure of definitions by analysing the results of a simulated competition experiment underlain by a consumer resource model. In the course of doing so, we clarify the challenges of interpreting HOIs in nature, and suggest a more precise framing of this research endeavour to catalyse further investigations.
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Abstract Understanding the role of native biodiversity in controlling exotic species invasion is a critical goal in ecology. In terrestrial plant communities, most research has focused on the effects of native vascular plants on invasion by exotic vascular plants. However, in many ecosystems, native bryophytes and other non‐vascular plants are common and can affect the establishment, survival, and growth of vascular plants. A more complete picture of how native biodiversity affects exotic plant invasion demands that more studies measure the effects of native bryophytes on exotic vascular plants. Moreover, there is growing realization that the effects of native species on invaders can range from negative to positive and that a complete picture of interactions between native and exotic plants requires measuring interactions in multiple environments. We used both observational and experimental studies to quantify the effects of native bryophytes on vascular plants along a 200‐m environmental gradient in a coastal dune in northern California. We found a positive association between vascular plants and bryophytes across the environmental gradient. Our experiments with two exotic annual grass species showed the effects of bryophytes to be species‐specific and to vary with environmental context. Bryophytes facilitated the survival of one exotic grass species,
Vulpia bromoides , at both ends of the environmental gradient. Bryophytes reduced the survival and inflorescence production of the other exotic grass,Bromus diandrus , at one end of the environmental gradient and had no effect at the other end. Our findings provide a test of the effects of native bryophytes on exotic vascular plant invasion and show that these effects can vary dramatically even across local environmental gradients. -
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Abstract Plant species can show considerable morphological and functional variation along environmental gradients. This intraspecific trait variation (ITV) can have important consequences for community assembly, biotic interactions, ecosystem functions and responses to global change. However, directly measuring ITV across many species and wide geographic areas is often infeasible. Thus, a method to predict spatial variation in a species’ functional traits could be valuable.
We measured specific leaf area (SLA), height and leaf area (LA) of grasses across California, covering 59 species at 230 sampling locations. We asked how these traits change along climate gradients within each species and used machine learning to predict local trait values for any species at any location based on phylogenetic position, local climate and that species’ mean traits. We then examined how much these local predictions alter patterns of assemblage‐level trait variation across the state.
Most species exhibited higher SLA and grew taller at higher temperatures and produced larger leaves in drier conditions. The random forests predicted spatial variation in functional traits very accurately, with correlations up to 0.97. Because trait records were spatially biased towards warmer areas, and these areas tend to have higher SLA individuals within each species, species means of SLA were upwardly biased. As a result, using species means over‐estimates SLA in the cooler regions of the state. Our results also suggest that height may be substantially under‐predicted in the warmest areas.
Synthesis . Using only species mean traits to characterize the functional composition of communities risks introducing substantial error into trait‐based estimates of ecosystem properties including decomposition rates or NPP. The high performance of random forests in predicting local trait values provides a way forward for estimating high‐resolution patterns of ITV without a massive data collection effort.
