AI Article Synopsis

  • Leaf venation networks evolved to optimize resource transport, damage resistance, mechanical strength, and construction cost through varying architectural traits across different scales.
  • A framework was developed to analyze network architecture using statistics like elongation ratios and vein density, based on samples from 260 Southeast Asian tree species.
  • The study found that functional linkages between vein characteristics and mechanical traits are scale-dependent, revealing a complex relationship between leaf structure and function that could inform future research on venation networks.

Article Abstract

Leaf venation networks evolved along several functional axes, including resource transport, damage resistance, mechanical strength, and construction cost. Because functions may depend on architectural features at different scales, network architecture may vary across spatial scales to satisfy functional tradeoffs. We develop a framework for quantifying network architecture with multiscale statistics describing elongation ratios, circularity ratios, vein density, and minimum spanning tree ratios. We quantify vein networks for leaves of 260 southeast Asian tree species in samples of up to 2 cm , pairing multiscale statistics with traits representing axes of resource transport, damage resistance, mechanical strength, and cost. We show that these multiscale statistics clearly differentiate species' architecture and delineate a phenotype space that shifts at larger scales; functional linkages vary with scale and are weak, with vein density, minimum spanning tree ratio, and circularity ratio linked to mechanical strength (measured by force to punch) and elongation ratio and circularity ratio linked to damage resistance (measured by tannins); and phylogenetic conservatism of network architecture is low but scale-dependent. This work provides tools to quantify the function and evolution of venation networks. Future studies including primary and secondary veins may uncover additional insights.

Download full-text PDF

Source
http://dx.doi.org/10.1111/nph.16830DOI Listing

Publication Analysis

Top Keywords

multiscale statistics
16
venation networks
12
damage resistance
12
mechanical strength
12
network architecture
12
leaf venation
8
resource transport
8
transport damage
8
resistance mechanical
8
vein density
8

Similar Publications

Basalt, which is a geological medium used for engineering construction in Southwest China, contains defect structures at various scales. In particular, the widespread presence of mesoscale hidden joints significantly affects the mechanical properties of basalt and the stability of engineering structures. However, research in this specific subject has been limited.

View Article and Find Full Text PDF

The epidemiological behavior of Plasmodium vivax malaria occurs across spatial scales including within-host, population, and metapopulation levels. On the within-host scale, P. vivax sporozoites inoculated in a host may form latent hypnozoites, the activation of which drives secondary infections and accounts for a large proportion of P.

View Article and Find Full Text PDF

Assessment of ComBat Harmonization Performance on Structural Magnetic Resonance Imaging Measurements.

Hum Brain Mapp

December 2024

Department of Neurosciences and Mental Health, Fondazione IRCS Cà Granda Ospedale Policlinico, Milano, Italy.

Data aggregation across multiple research centers is gaining importance in the context of MRI research, driving diverse high-dimensional datasets to form large-scale heterogeneous sample, increasing statistical power and relevance of machine learning and deep learning algorithm. Site-related effects have been demonstrated to introduce bias in MRI features and confound subsequent analyses. Although Combating Batch (ComBat) technique has been recently reported to successfully harmonize multi-scale neuroimaging features, its performance assessments are still limited and largely based on qualitative visualizations and statistical analyses.

View Article and Find Full Text PDF

This study aims to develop a stable and efficient magnetic nanocomposite hydrogel (MNCH) for selective removal of methylene blue (MB) and crystal violet (CV). MNCHs with different FeO contents (0-9 wt%) were synthesized following graft co-polymerization method using sodium alginate, acrylamide, itaconic acid, ammonium persulfate and N,N-methylene bisacrylamide. Among them, MNCH, with 5 wt% FeO, showed highest removal efficiency (>95 %).

View Article and Find Full Text PDF

Interferometric Synthetic Aperture Radar (InSAR) is a widely used remote sensing technology for Earth observation, enabling the detection and measurement of ground deformation through the generation of interferograms. However, phase noise remains a critical factor that degrades interferogram quality. To address this issue, this study proposes MOMFNet, a deep learning approach for InSAR phase filtering based on multi-objective multi-kernel feature extraction that leverages multi-objective multi-kernel feature extraction.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!