Stoichiometry versus ecology: the relationships between genome size and guanine-cytosine content, and tissue nitrogen and phosphorus in grassland herbs

. 2022 Sep 06 ; 130 (2) : 189-197.

Jazyk angličtina Země Velká Británie, Anglie Médium print

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid35700050

BACKGROUND AND AIMS: Plant tissue nitrogen (N) and phosphorus (P) and genome traits, such as genome size and guanine-cytosine (GC) content, scale with growth or metabolic rates and are linked to plant ecological strategy spectra. Tissue NP stoichiometry and genome traits are reported to affect plant growth, metabolic rates or ecological strategies in contrasting ways, although the elemental costs for building and maintaining DNA are typically overlooked. METHODS: We formulated stoichiometry- and ecology-based predictions on the relationship between genome size and GC content to tissue N, P and N : P and tested them on a set of 130 herbaceous species from a temperate grassland using ordinary, phylogenetic and quantile regression. KEY RESULTS: Genome size was only negatively linked to plant N and N : P in species with very small genomes. We found no link between genome size and plant P. GC content was negatively linked to plant N and P but we found these significant links consistently in both GC-rich and GC-poor species. Finally, GC content correlated positively with plant N : P but only in species with GC-rich genomes. CONCLUSIONS: Our results provide stronger support for the ecology-based predictions than the stoichiometry-based predictions, and for the links between GC content and plant N and P stoichiometry than for genome size. We argue that the theories of plant metabolic rates and ecological strategies (resource-acquisitive vs. conservative or ruderal vs. stress-tolerator spectra) better explain interspecific genome-NP stoichiometry relationships at the tissue level (although relatively weakly) than the stoichiometric theory based on the elemental costs for building and maintaining DNA.

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