Data for variation of magnesium drives plant adaption to heterogeneous environments by regulating efficiency in photosynthesis on a large scale

Magnesium (Mg) is a vital nutrient for plants, and its role in
photosynthesis, enzyme regulation, and resistance to environmental stress
is becoming increasingly evident. However, there is a paucity of knowledge
regarding the characteristics of Mg (content, density, and stock) on a
large scale, particularly at the community level, which serves as a
fundamental unit for linking to ecosystem functions. A
leaf-branch-trunk-root-matched database of the Mg content (mg g–1) and
biomass (g m–2) of plant organs across 1972 sampling sites in China was
constructed based on field surveys and data compilation. Using machine
learning algorithms, we comprehensively explored the spatial patterns and
main influencing factors of plant Mg content and density (g m–2). Deserts
exhibited higher Mg content, with the primary influencing factors being
high temperature and soil Mg supply. High Mg density values occurred in
forests. The spatial patterns of Mg content and density underscore the
adaptation of plants to environmental changes and nutrient retention
capacity of forests, respectively. Our research not only provides valuable
information on the distribution of Mg across different communities.