Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V_cmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co‐optimization of carboxylation and water costs for photosynthesis, suggests that optimal V_cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field‐measured V_cmax dataset for C₃ plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first‐order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Bacteria are the highest abundant microorganisms in the soil. To investigate bacteria community structures, diversity, and functions, contrasting them in four different seasons all the year round with/within two different forest type soils of China. We analyzed soil bacterial community based on 16S rRNA gene sequencing via Illumina HiSeq platform at a temperate deciduous broad-leaved forest (Baotianman, BTM) and a tropical rainforest (Jianfengling, JFL). We obtained 51,137 operational taxonomic units (OTUs) and classified them into 44 phyla and 556 known genera, 18.2% of which had a relative abundance >1%. The composition in each phylum was similar between the two forest sites. Proteobacteria and Acidobacteria were the most abundant phyla in the soil samples between the two forest sites. The Shannon index did not significantly differ among the four seasons at BTM or JFL and was higher at BTM than JFL in each season. The bacteria community at both BTM and JFL showed two significant (P < 0.05) predicted functions related to carbon cycle (anoxygenic photoautotrophy sulfur oxidizing and anoxygenic photoautotrophy) and three significant (P < 0.05) predicted functions related to nitrogen cycle (nitrous denitrificaton, nitrite denitrification, and nitrous oxide denitrification). We provide the basis on how changes in bacterial community composition and diversity leading to differences in carbon and nitrogen cycles at the two forests.

Northern peatlands have stored large amounts (~500 Pg) of carbon (C) since the last glaciation. Combined with peat C are nutrients such as nitrogen (N), phosphorus (P), calcium (Ca), magnesium (Mg), and potassium (K), each of which plays an important role in plant production, litter decomposition, and the biogeochemical functioning of peatlands. Yet little attention has been given to the amounts of these nutrients stored in northern peatlands and their stoichiometry with C. Here we use data on nutrient concentrations in over 400 peat profiles in Ontario, Canada, representing bogs, fens, and swamps and their vegetation. We show that the C:N ratio is high (>40:1) in vegetation and litter but declines through the peat profiles to reach ratios between 22:1 and 29:1 in peat below 50 cm. In contrast, the C:P ratio rises from vegetation and litter (500:1 to 1300:1) to 1500:1 to 2000:1 in the lower part of the peat profile. Ratios of C to Ca, Mg, and K vary with peatland type. Most of these stoichiometric changes occur in the early stages of organic matter decomposition, where the litter structure remains intact. We estimate that ~18 Pg of N has been stored in northern peatlands since deglaciation, reflecting high N accumulation rates (~0.8 g m⁻² yr⁻¹), whereas P accumulation is small (~0.3 Pg, ~0.016 g m⁻² yr⁻¹), indicating that P is quickly recycled in the surface layers.