High‐dimensional elementomes outperform CNP models in explaining photosynthetic traits

Links between plant elementomes (i.e. the concentration of chemical elements in plant tissue) and functional traits have the potential to improve predictions of plant physiological performance and ecosystem processes, and their response to environmental change. High‐dimensional plant elementomes, which encompass not only macronutrients but also micronutrients and trace elements, have been associated with various morphological and physiological plant traits, but not with photosynthetic traits.

We determined elementomes, comprising 21 elements and isotopic ratios of C and N, of 26 hygrophytic bryophyte species (16 mosses and 10 liverworts) in Mediterranean springs, and examined their relationship with four photosynthetic light response traits: maximum photosynthetic rates, apparent quantum yield, light compensation point and dark respiration rates.

Results from linear mixed effects models showed that high‐dimensional elementomes are strongly associated with photosynthetic traits, explaining substantially more variance ( R ²  = 38%–61%; 72%–85% when also including taxonomic information) than models based solely on C, N and P ( R ²  = 6%–45% and 35%–72%, respectively). Model selection and averaging revealed that each photosynthetic light response trait was optimally modelled by a set of 8–13 elemental variables, including various macronutrients (e.g. N, S, K), micronutrients (e.g. Zn, Cu), trace elements (e.g. Ni, Co) and isotopic ratios (δ ¹³ C and δ ¹⁵ N).

We demonstrate that plant elementomes capture key drivers of photosynthetic variation, which adds to growing evidence of strong links between elementomes and various functional traits that underpin organismal and ecosystem functioning. Our results suggest that characterising plant elementomes could contribute to improved predictions of ecosystem‐scale processes such as CO ₂ uptake.