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Lianas, climbing woody plants, influence the structure and function of tropical forests. Climbing traits have evolved multiple times, including ancestral groups such as gymnosperms and pteridophytes, but the genetic basis of the liana strategy is largely unknown. Here, we use a comparative transcriptomic approach for 47 tropical plant species, including ten lianas of diverse taxonomic origins, to identify genes that are consistently expressed or downregulated only in lianas. Our comparative analysis of full-length transcripts enabled the identification of a core interactomic network common to lianas. Sets of transcripts identified from our analysis reveal features related to functional traits pertinent to leaf economics spectrum in lianas, include upregulation of genes controlling epidermal cuticular properties, cell wall remodeling, carbon concentrating mechanism, cell cycle progression, DNA repair and a large suit of downregulated transcription factors and enzymes involved in ABA-mediated stress response as well as lignin and suberin synthesis. All together, these genes are known to be significant in shaping plant morphologies through responses such as gravitropism, phyllotaxy and shade avoidance.

 

Maples (the genusAcer) represent important and beloved forest, urban, and ornamental trees distributed throughout the Northern hemisphere. They exist in a diverse array of native ranges and distributions, across spectrums of tolerance or decline, and have varying levels of susceptibility to biotic and abiotic stress. AmongAcerspecies, several stand out in their importance to economic interest. Here we report the first two chromosome‐scale genomes for North American species,Acer negundoandAcer saccharum. Both assembled genomes contain scaffolds corresponding to 13 chromosomes, withA. negundoat a length of 442 Mb, an N50 of 32 Mb, and 30 491 genes, andA. saccharumat a length of 626 Mb, an N50 of 46 Mb, and 40 074 genes. No recent whole genome duplications were detected, thoughA. saccharumhas local gene duplication and more recent bursts of transposable elements, as well as a large‐scale translocation between two chromosomes. Genomic comparison revealed thatA. negundohas a smaller genome with recent gene family evolution that is predominantly contracted and expansions that are potentially related to invasive tendencies and tolerance to abiotic stress. Examination of RNA sequencing data obtained fromA. saccharumgiven long‐term aluminum and calcium soil treatments at the Hubbard Brook Experimental Forest provided insights into genes involved in the aluminum stress response at the systemic level, as well as signs of compromised processes upon calcium deficiency, a condition contributing to maple decline.

 

Abstract Background and Aims The composition and dynamics of plant communities arise from individual-level demographic outcomes, which are driven by interactions between phenotypes and the environment. Functional traits that can be measured across plants are frequently used to model plant growth and survival. Perhaps surprisingly, species average trait values are often used in these studies and, in some cases, these trait values come from other regions or averages calculated from global databases. This data aggregation potentially results in a large loss of valuable information that probably results in models of plant performance that are weak or even misleading. Methods We present individual-level trait and fine-scale growth data from >500 co-occurring individual trees from 20 species in a Chinese tropical rain forest. We construct Bayesian models of growth informed by theory and construct hierarchical Bayesian models that utilize both individual- and species-level trait data, and compare these models with models only using individual-level data. Key Results We show that trait–growth relationships measured at the individual level vary across species, are often weak using commonly measured traits and do not align with the results of analyses conducted at the species level. However, when we construct individual-level models of growth using leaf area ratio approximations and integrated phenotypes, we generated strong predictive models of tree growth. Conclusions Here, we have shown that individual-level models of tree growth that are built using integrative traits always outperform individual-level models of tree growth that use commonly measured traits. Furthermore, individual-level models, generally, do not support the findings of trait–growth relationships quantified at the species level. This indicates that aggregating trait and growth data to the species level results in poorer and probably misleading models of how traits are related to tree performance.