Functional traits affect the demographic performance of individuals in their environment, leading to fitness differences that scale up to drive population dynamics and community assembly. Understanding the links between traits and fitness is, therefore, critical for predicting how populations and communities respond to environmental change. However, the net effects of traits on species fitness are largely unknown because we have lacked a framework for estimating fitness across multiple species and environments. We present a modelling framework that integrates trait effects on demographic performance over the life cycles of individuals to estimate the net effect of traits on species fitness. This approach involves (1) modelling trait effects on individual demographic rates (growth, survival and recruitment) as multidimensional performance surfaces that vary with individual size and environment and (2) integrating these effects into a population model to project population growth rates (i.e., fitness) as a function of traits and environment. We illustrate our approach by estimating performance surfaces and fitness landscapes for trees across a temperature gradient in the eastern United States. Functional traits (wood density, specific leaf area and maximum height) interacted with individual size and temperature to influence tree growth, survival and recruitment rates, generating demographic trade‐offs and shaping the contours of fitness landscapes. Tall tree species had high survival, growth and fitness across the temperature gradient. Wood density and specific leaf area had interactive effects on demographic performance, resulting in fitness landscapes with multiple peaks. With this approach it is now possible to empirically estimate the net effect of traits on fitness, leading to an improved understanding of the selective forces that drive community assembly and permitting generalizable predictions of population and community dynamics in changing environments.
- Award ID(s):
- 1638488
- NSF-PAR ID:
- 10207862
- Editor(s):
- D'Amato, A.W.
- Date Published:
- Journal Name:
- Ecology
- Volume:
- 101
- Issue:
- 6
- ISSN:
- 0094-6621
- Page Range / eLocation ID:
- e03007
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract -
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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. -
A fundamental assumption of functional ecology is that functional traits are related to interspecific variation in performance. However, the relationship between functional traits and performance is often weak or uncertain, especially for plants. A potential explanation for this inconsistency is that the relationship between functional traits and vital rates (e.g., growth and mortality) is dependent on local environmental conditions, which would lead to variation in trait-rate relationships across environmental gradients. In this study, we examined trait-rate relationships for six functional traits (seed mass, wood density, maximum height, leaf mass per area, leaf area, and leaf dry matter content) using long-term data on seedling growth and survival of woody plant species from eight forest sites spanning a pronounced precipitation and soil phosphorus gradient in central Panama. For all traits considered except for leaf mass per area-mortality, leaf mass per area-growth, and leaf area-mortality relationships, we found widespread variation in the strength of trait-rate relationships across sites. For some traits, trait-rate relationships showed no overall trend but displayed wide site-to-site variation. In a small subset of cases, variation in trait-rate relationships was explained by soil phosphorus availability. Our results demonstrate that environmental gradients have the potential to influence how functional traits are related to growth and mortality rates, though much variation remains to be explained. Accounting for site-to-site variation may help resolve a fundamental issue in trait-based ecology – that traits are often weakly related to performance – and improve the utility of functional traits for explaining key ecological and evolutionary processes.more » « less
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Abstract Individual‐level demographic outcomes should be predictable upon the basis of traits. However, linking traits to tree performance has proven challenging likely due to a failure to consider physiological traits (i.e. hard‐traits) and the failure to integrate organ‐level and whole plant‐level trait information.
Here, we modelled the survival rate and relative growth rate of trees while considering crown allocation, hard‐traits and local‐scale biotic interactions, and compared these models to more traditional trait‐based models of tree performance.
We found that an integrative trait, total tree‐level photosynthetic mass (estimated by multiplying specific leaf area and crown area) results in superior models of tree survival and growth. These models had a lower AIC than those including the effect of initial tree size or any other combination of the traits considered. Survival rates were positively related to higher values of crown area and photosynthetic mass, while relative growth rates were negatively related to the photosynthetic mass. Relative growth rates were negatively related to a neighbourhood crowding index. Furthermore, none of the hard‐traits used in this study provided an improvement in tree performance models.
Synthesis . Overall, our results highlight that models of tree performance can be greatly improved by including crown area information to generate a better understanding of plant responses to their environment. Additionally, the role of the hard‐traits in improving models of tree performance is likely dependent upon the level of stress (e.g. drought stress), micro‐environmental conditions or short‐term climatic variations that a particular forest experiences. -
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Abstract Traits differentially adapt plant species to particular conditions generating compositional shifts along environmental gradients. As a result, community‐scale trait values show concomitant shifts, termed trait‒environment relationships. Trait‒environment relationships are often assessed by evaluating community‐weighted mean (CWM) traits observed along environmental gradients. Regression‐based approaches (CWMr) assume that local communities exhibit traits centred at a single optimum value and that traits do not covary meaningfully. Evidence suggests that the shape of trait‒abundance relationships can vary widely along environmental gradients—reflecting complex interactions—and traits are usually interrelated. We used a model that accounts for these factors to explore trait‒environment relationships in herbaceous forest plant communities in Wisconsin (USA).
We built a generalized linear mixed model (GLMM) to analyse how abundances of 185 species distributed among 189 forested sites vary in response to four functional traits (vegetative height—VH, leaf size—LS, leaf mass per area—LMA and leaf carbon content), six environmental variables describing overstorey, soil and climate conditions, and their interactions. The GLMM allowed us to assess the nature and relative strength of the resulting 24 trait‒environment relationships. We also compared results between GLMM and CWMr to explore how conclusions differ between approaches.
The GLMM identified five significant trait‒environment relationships that together explain ~40% of variation in species abundances across sites. Temperature appeared as a key environmental driver, with warmer and more seasonal sites favouring taller plants. Soil texture and temperature seasonality affected LS and LMA; seasonality effects on LS and LMA were nonlinear, declining at more seasonal sites. Although often assumed for CWMr, only some traits under certain conditions had centred optimum trait‒abundance relationships. CWMr more liberally identified (13) trait‒environment relationships as significant but failed to detect the temperature seasonality‒LMA relationship identified by the GLMM.
Synthesis . Although GLMM represents a more methodologically complex approach than CWMr, it identified a reduced set of trait‒environment relationships still capable of accounting for the responses of forest understorey herbs to environmental gradients. It also identified separate effects of mean and seasonal temperature on LMA that appear important in these forests, generating useful insights and supporting broader application of GLMM approach to understand trait‒environment relationships.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/ecy.3007
