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Abstract 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.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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On the modelling of tropical tree growth: the importance of intra-specific trait variation, non-linear functions and phenotypic integration
Abstract Background and Aims The composition and dynamics of plant communities arise from individual-level demographic outcomes, which are driven by interactions between phenotypes and the environment. Functional traits that can be measured across plants are frequently used to model plant growth and survival. Perhaps surprisingly, species average trait values are often used in these studies and, in some cases, these trait values come from other regions or averages calculated from global databases. This data aggregation potentially results in a large loss of valuable information that probably results in models of plant performance that are weak or even misleading. Methods We present individual-level trait and fine-scale growth data from >500 co-occurring individual trees from 20 species in a Chinese tropical rain forest. We construct Bayesian models of growth informed by theory and construct hierarchical Bayesian models that utilize both individual- and species-level trait data, and compare these models with models only using individual-level data. Key Results We show that trait–growth relationships measured at the individual level vary across species, are often weak using commonly measured traits and do not align with the results of analyses conducted at the species level. However, when we construct individual-level models of growth using leaf area ratio approximations and integrated phenotypes, we generated strong predictive models of tree growth. Conclusions Here, we have shown that individual-level models of tree growth that are built using integrative traits always outperform individual-level models of tree growth that use commonly measured traits. Furthermore, individual-level models, generally, do not support the findings of trait–growth relationships quantified at the species level. This indicates that aggregating trait and growth data to the species level results in poorer and probably misleading models of how traits are related to tree performance.
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- PAR ID:
- 10207865
- Date Published:
- Journal Name:
- Annals of Botany
- ISSN:
- 0305-7364
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/aob/mcaa085
