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1. Predicting global intraspecific trait variation of grasses

   https://doi.org/10.1002/ecog.07627  

   Griffin‐Nolan, Robert J; Vorontsova, Maria S; Sandel, Brody (April 2025, Ecography)

   Plant traits are important for understanding community assembly and ecosystem processes, yet our understanding of intraspecific trait variation (ITV) is limited. This gap in our knowledge is partially because collecting trait data across a species' entire range is impractical, let alone across the ranges of multiple species within a plant family. Using machine learning techniques to predict spatial ITV is an attractive and cost‐effective alternative to sampling across a species range, although this has not been applied beyond regional scales. We compiled a trait database of over 1000 grass species (family: Poaceae), encompassing six key functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height, leaf area, leaf nitrogen (Nmass) and leaf phosphorus content (Pmass). Using a random forest machine learning approach, we predicted local trait values within species' ranges considering climate, soil type, phylogeny, lifespan, and photosynthetic pathway as influential factors. An iterative random forest modeling technique incorporated correlations between traits, resulting in improved model performance (observed versus predicted R range of 0.72–0.91). Our models also highlight the importance of climate in predicting trait variation. For a subset of species (n = 860), we projected trait predictions across their known distribution, informed by expert maps from Royal Botanic Gardens, Kew, to create global maps of ITV for grasses. Such maps have the potential to inform conservation efforts and predictions of grazing and fire dynamics in grasslands worldwide. Overall, our research demonstrates the value and ecological applications of predicting plant traits. 

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2. The acquisitive–conservative axis of leaf trait variation emerges even in homogeneous environments

   https://doi.org/10.1093/aob/mcaa198  

   Gorné, Lucas D; Díaz, Sandra; Minden, Vanessa; Onoda, Yusuke; Kramer, Koen; Muir, Christopher; Michaletz, Sean T; Lavorel, Sandra; Sharpe, Joanne; Jansen, Steven; et al (November 2020, Annals of Botany)

   Abstract Background and Aims The acquisitive–conservative axis of plant ecological strategies results in a pattern of leaf trait covariation that captures the balance between leaf construction costs and plant growth potential. Studies evaluating trait covariation within species are scarcer, and have mostly dealt with variation in response to environmental gradients. Little work has been published on intraspecific patterns of leaf trait covariation in the absence of strong environmental variation. Methods We analysed covariation of four leaf functional traits [specific leaf area (SLA) leaf dry matter content (LDMC), force to tear (Ft) and leaf nitrogen content (Nm)] in six Poaceae and four Fabaceae species common in the dry Chaco forest of Central Argentina, growing in the field and in a common garden. We compared intraspecific covariation patterns (slopes, correlation and effect size) of leaf functional traits with global interspecific covariation patterns. Additionally, we checked for possible climatic and edaphic factors that could affect the intraspecific covariation pattern. Key Results We found negative correlations for the LDMC–SLA, Ft–SLA, LDMC–Nm and Ft–Nm trait pairs. This intraspecific covariation pattern found both in the field and in the common garden and not explained by climatic or edaphic variation in the field follows the expected acquisitive–conservative axis. At the same time, we found quantitative differences in slopes among different species, and between these intraspecific patterns and the interspecific ones. Many of these differences seem to be idiosyncratic, but some appear consistent among species (e.g. all the intraspecific LDMC–SLA and LDMC–Nm slopes tend to be shallower than the global pattern). Conclusions Our study indicates that the acquisitive–conservative leaf functional trait covariation pattern occurs at the intraspecific level even in the absence of relevant environmental variation in the field. This suggests a high degree of variation–covariation in leaf functional traits not driven by environmental variables. 

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3. Soil microenvironmental variation drives below‐ground trait variation and interacts with macroclimate to structure above‐ground trait variation of arctic shrubs

   https://doi.org/10.1111/1365-2745.14278  

   Fraterrigo, Jennifer M; Chen, Weile; Loyal, Joshua; Euskirchen, Eugénie S (April 2024, Journal of Ecology)

   Henn, J (Ed.)

   Abstract Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic.To fill this knowledge gap, we examined above‐ground and below‐ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root δ¹⁵N and leaf δ¹³C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots (N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine‐scale and broad‐scale factors on intraspecific trait variation.We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size‐structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate.Synthesis. Our results demonstrate that above‐ground and below‐ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above‐ground and below‐ground trait responses to climate change. 

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4. Trait coordination reveals the fast–slow plant economics spectrum along the vertical canopy profile in central Amazonian forests

   https://doi.org/10.1111/1365-2435.70213  

   Ziccardi, Leonardo G; Taylor, Tyeen C; Smith, Marielle N; Gonçalves, Nathan B; Kramer, David; Campos, Kleber Silva; Prohaska, Neill; Restrepo‐Coupe, Natalia; Saleska, Scott R; Siqueira‐Silva, Advanio Inácio; et al (December 2025, Functional Ecology)

   Abstract Understanding how environmental drivers affect tree functioning is essential to improve predictions of tropical forests' response to climate change. While functional traits directly influence tree performance, our understanding of how canopy environments shape their coordination and variation along the vertical forest profile remains limited.We quantified annual growth rates in terms of above‐ground biomass (AGB), the maximum efficiency of photosystem II (Fv/Fm) and six tree functional traits related to water transport (xylem density and Huber value), leaf morphology (leaf size, angle and stomatal density) and photosynthesis (specific leaf area) along the vertical forest profile in an old‐growth central Amazonian forest.To investigate the influence of canopy environments and ontogenetic stages on the variation of these traits, we divided the forest into three vertical strata defined by height from the ground (S1: 0–20 m; S2: 20–40 m; S3: >40 m). We sampled 162 branches and 486 leaves from 54 trees of 10 species, encompassing at least five of the most abundant species per stratum. Path analysis and correlation matrices were used to explore the links between canopy environments, traits and the ‘fast–slow’ plant economics spectrum.We found significant effects of height on relative tree growth, leaf size and specific leaf area. Trait correlations varied across strata suggesting an ecological stratification of canopy functional niches. Trait–growth correlations increased in number and strength with increasing height, suggesting greater trait‐mediated growth control in large trees.Our results reveal how traits and strategies on the ‘fast–slow’ plant economics spectrum are vertically distributed and coordinated along the forest profile. Our findings highlight important interactions between species and canopy environments in determining plant traits, with emergent species showing adaptive strategies at different stages of their development. Read the freePlain Language Summaryfor this article on the Journal blog. 

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5. The three major axes of terrestrial ecosystem function

   https://doi.org/10.1038/s41586-021-03939-9  

   Migliavacca, Mirco; Musavi, Talie; Mahecha, Miguel D.; Nelson, Jacob A.; Knauer, Jürgen; Baldocchi, Dennis D.; Perez-Priego, Oscar; Christiansen, Rune; Peters, Jonas; Anderson, Karen; et al (January 2021, Nature)

   null (Ed.)

   Abstract The leaf economics spectrum 1,2 and the global spectrum of plant forms and functions 3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species 2 . Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities 4 . However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability 4,5 . Here we derive a set of ecosystem functions 6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems 7,8 . 

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