Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO2fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO2concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.
Understanding the driving mechanisms behind existing patterns of vegetation hydraulic traits and community trait diversity is critical for advancing predictions of the terrestrial carbon cycle because hydraulic traits affect both ecosystem and Earth system responses to changing water availability. Here, we leverage an extensive trait database and a long-term continental forest plot network to map changes in community trait distributions and quantify “trait velocities” (the rate of change in community-weighted traits) for different regions and different forest types across the United States from 2000 to the present. We show that diversity in hydraulic traits and photosynthetic characteristics is more related to local water availability than overall species diversity. Finally, we find evidence for coordinated shifts toward communities with more drought-tolerant traits driven by tree mortality, but the magnitude of responses differs depending on forest type. The hydraulic trait distribution maps provide a publicly available platform to fundamentally advance understanding of community trait change in response to climate change and predictive abilities of mechanistic vegetation models.
more » « less- PAR ID:
- 10142247
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 117
- Issue:
- 15
- ISSN:
- 0027-8424
- Format(s):
- Medium: X Size: p. 8532-8538
- Size(s):
- p. 8532-8538
- Sponsoring Org:
- National Science Foundation
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Plant functional traits hold the potential to greatly improve the understanding and prediction of climate impacts on ecosystems and carbon cycle feedback to climate change. Traits are commonly used to place species along a global conservative-acquisitive trade-off, yet how and if functional traits and conservative-acquisitive trade-offs scale up to mediate community and ecosystem fluxes is largely unknown. Here, we combine functional trait datasets and multibiome datasets of forest water and carbon fluxes at the species, community, and ecosystem-levels to quantify the scaling of the tradeoff between maximum flux and sensitivity to vapor pressure deficit. We find a strong conservative-acquisitive trade-off at the species scale, which weakens modestly at the community scale and largely disappears at the ecosystem scale. Functional traits, particularly plant water transport (hydraulic) traits, are strongly associated with the key dimensions of the conservative-acquisitive trade-off at community and ecosystem scales, highlighting that trait composition appears to influence community and ecosystem flux dynamics. Our findings provide a foundation for improving carbon cycle models by revealing i) that plant hydraulic traits are most strongly associated with community- and ecosystem scale flux dynamics and ii) community assembly dynamics likely need to be considered explicitly, as they give rise to ecosystem-level flux dynamics that differ substantially from trade-offs identified at the species-level.
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Abstract The extent to which future climate change will increase forest stress and the amount to which species and forest ecosystems can acclimate or adapt to increased stress is a major unknown. We used high‐resolution maps of hydraulic traits representing the diversity in tree drought tolerance across the United States, a hydraulically enabled tree model, and forest inventory observations of demographic shifts to quantify the ability for within‐species acclimation and between‐species range shifts to mediate climate stress. We found that forests are likely to experience increases in both acute and chronic hydraulic stress with climate change. Based on current species distributions, regional hydraulic trait diversity was sufficient to buffer against increased stress in 88% of forested areas. However, observed trait velocities in 81% of forested areas are not keeping up with the rate required to ameliorate projected future stress without leaf area acclimation.
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Abstract Understanding the drivers of trait selection is critical for resolving community assembly processes. Here, we test the importance of environmental filtering and trait covariance for structuring the functional traits of understory herbaceous communities distributed along a natural environmental resource gradient that varied in soil moisture, temperature, and nitrogen availability, produced by different topographic positions in the southern Appalachian Mountains.
To uncover potential differences in community‐level trait responses to the resource gradient, we quantified the averages and variances of both abundance‐weighted and unweighted values for six functional traits (vegetative height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, and leaf δ13C) using 15 individuals of each of the 108 species of understory herbs found at two sites in the southern Appalachians of western North Carolina, USA.
Environmental variables were better predictors of weighted than unweighted community‐level average trait values for all but height and leaf N, indicating strong environmental filtering of plant abundance. Community‐level variance patterns also showed increased convergence of abundance‐weighted traits as resource limitation became more severe.
Functional trait covariance patterns based on weighted averages were uniform across the gradient, whereas coordination based on unweighted averages was inconsistent and varied with environmental context. In line with these results, structural equation modeling revealed that unweighted community‐average traits responded directly to local environmental variation, whereas weighted community‐average traits responded indirectly to local environmental variation through trait coordination.
Our finding that trait coordination is more important for explaining the distribution of weighted than unweighted average trait values along the gradient indicates that environmental filtering acts on multiple traits simultaneously, with abundant species possessing more favorable combinations of traits for maximizing fitness in a given environment.
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Abstract Plant functional traits provide a link in process‐based vegetation models between plant‐level physiology and ecosystem‐level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large‐scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re‐evaluation of trait‐based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type‐specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.
