Global relationships in tree functional traits

Maynard, Daniel S.; Bialic‐Murphy, Lalasia; Zohner, Constantin M.; Averill, Colin; Hoogen, Johan van den; Ma, Haozhi; Mo, Lidong; Smith, Gabriel Reuben; Acosta, Alicia Teresa Rosario; Aubin, Isabelle; Berenguer, Erika; Boonman, Coline C. F.; Catford, Jane A.; Cerabolini, Bruno E. L.; Dias, Arildo S.; González‐Melo, Andrés; Hietz, Peter; Lusk, Christopher H.; Mori, Akira; Niinemets, Ülo; Pillar, Valério D.; Pinho, Bruno X.; Rosell, Julieta A.; Schurr, Frank M.; Sheremetiev, Serge; Silva, Ana Carolina da; Sosinski, E. E.; Bodegom, Peter M. van; Weiher, Evan; Bönisch, Gerhard; Kattge, Jens; Crowther, Thomas W.

doi:10.1038/s41467-022-30888-2

Cited by 38 publications

(23 citation statements)

References 95 publications

(187 reference statements)

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“…LA, representing leaf size, is closely related to plant energy balance (including energy uptake and conversion) and is a reliable indicator of GPP on a large scale 20 . A recent global-scale study revealed a strong relationship between LA and canopy size (including canopy height, diameter, and tree height), which reflects the total photosynthetic capacity of the whole tree 40 . While this explains why LA can predict large-scale variation in GPP, this coupling does not necessarily reflect causality.…”

Section: Discussionmentioning

confidence: 99%

“…The measured individual-level functional traits for woody and herbaceous plants included leaf area (LA, cm 2 ), leaf dry mass (LM, g), specific leaf area (SLA, cm 2 /g), leaf nitrogen concentration (LNC, mg/g), and leaf phosphorus concentration (LPC, mg/g), closely related to plant photosynthesis and growth 29 , 49 (Text S 4 ). Functional traits were divided into size traits, reflecting plant size and light competitiveness, and economic traits, reflecting leaf photosynthetic capacity and nutrient economic 40 , 50 . All of these traits selected in this study are closely related to the plant light competitiveness and ecosystem photosynthetic capacity.…”

Section: Methodsmentioning

confidence: 99%

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Integrating multiple plant functional traits to predict ecosystem productivity

Yan

et al. 2023

Commun Biol

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Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R2 values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Integrating multiple plant functional traits to predict ecosystem productivity

Yan

et al. 2023

Commun Biol

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“…On the one hand, species occurrence data from large databases such as GBIF or iNaturalist have been combined with machine learning techniques (Wolf et al, 2022) (Moreno-Martínez et al, in prep. ) in an effort to make use of the strong predictive power of species and phylogeny (Kattge et al, 2011;Vallicrosa et al, 2021;Maynard et al, 2022). On the other hand, hyperspectral reflectance of plant canopies in the visible and near-infrared range has already been successfully used to map foliar traits at regional scales based on airborne remote sensing Wang et al, 2020).…”

Section: Future Opportunitiesmentioning

confidence: 99%

Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches

Dechant¹,

Kattge²,

Pavlick³

et al. 2023

Preprint

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Foliar traits such as specific leaf area (SLA), leaf nitrogen (N) and phosphorus (P) concentrations play an important role in plant economic strategies and ecosystem functioning. Various global maps of these foliar traits have been generated using statistical upscaling approaches based on in-situ trait observations.Here, we intercompare such global upscaled foliar trait maps at 0.5° spatial resolution (six maps for SLA, five for N, three for P), categorize the upscaling approaches used to generate them, and evaluate the maps with trait estimates from a global database of vegetation plots (sPlotOpen). We disentangled the contributions from different plant functional types (PFTs) to the upscaled maps and calculated a top-of-canopy-weighted mean (TWM) and the community-weighted mean (CWM) of sPlotOpen trait estimates.We found that the global foliar trait maps of SLA and N differ drastically and fall into two groups that are almost uncorrelated (for P only maps from one group were available). The primary factor explaining the differences between these groups is the use of PFT information combined with land cover products in one group while the other group relied only on environmental predictors. The impact of using TWM or CWM on spatial patterns is considerably smaller than that of including PFT and land cover information. The maps that used PFT and land cover information exhibit considerable similarities in spatial patterns that are strongly driven by land cover. The maps not using PFTs show a lower level of similarity and tend to be strongly driven by individual environmental variables.Overall, the maps using PFT and land cover information better reproduce the between-PFT trait differences and trait distributions of the plot-level sPlotOpen data, while the two groups performed similarly in capturing within-PFT trait variation. Upscaled maps of both groups were moderately correlated to grid-cell-level sPlotOpen data (R = 0.2-0.6), but only when accounting for the differences in processing in the upscaling approaches by applying similar scaling to the sPlotOpen data.Our findings indicate the importance of accounting for within-grid-cell trait variation, which has important implications for applications using existing maps and future upscaling efforts.

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“…We have a broad understanding of how trade-offs between traits along the fast-slow spectrum relate to plant ecological strategies, yet the timing of the trade-offs between the traits and how this intraspecific variation impacts plant function is poorly understood. Furthermore, key evolutionary synapomorphies that separate seed-free lineages and seed-bearing lineages may have strong impacts on allocation and life-history variation including secondary growth (woodiness) (Pittermann et al, 2006(Pittermann et al, , 2011Chave et al, 2009;Maynard et al, 2022) and reproductive structures borne on sporophytic vegetative structures (seeds, cones, flowers, etc.) (Obeso, 2002;Queenborough et al, 2007;Wiley et al, 2017;Krieg et al, 2023).…”

mentioning

confidence: 99%

Functional traits and trait coordination change over the life of a leaf in a tropical fern species

Krieg

Seeger

Campany

et al. 2023

American J of Botany

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Premise Plant ecological strategies are often defined by the integration of underlying traits related to resource acquisition, allocation, and growth. Correlations between key traits across diverse plants suggest that variation in plant ecological strategies is largely driven by a fast–slow continuum of plant economics. However, trait correlations may not be constant through the life of a leaf, and it is still poorly understood how trait function varies over time in long‐lived leaves. Methods Here, we compared trait correlations related to resource acquisition and allocation across three different mature frond age cohorts in a tropical fern species, Saccoloma inaequale. Results Fronds exhibited high initial investments of nitrogen and carbon, but with declining return in photosynthetic capacity after the first year. In the youngest fronds, we found water‐use efficiency to be significantly lower than in the oldest mature fronds due to increased transpiration rates. Our data suggest that middle‐aged fronds are more efficient relative to younger, less water‐use efficient fronds and that older fronds exhibit greater nitrogen investments without higher photosynthetic return. In addition, several trait correlations expected under the leaf economics spectrum (LES) do not hold within this species, and some trait correlations only appear in fronds of a specific developmental age. Conclusions These findings contextualize the relationship between traits and leaf developmental age with those predicted to underlie plant ecological strategy and the LES and are among the first pieces of evidence for when relative physiological trait efficiency is maximized in a tropical fern species.

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Global relationships in tree functional traits

Cited by 38 publications

References 95 publications

Integrating multiple plant functional traits to predict ecosystem productivity

Integrating multiple plant functional traits to predict ecosystem productivity

Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches

Functional traits and trait coordination change over the life of a leaf in a tropical fern species

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