The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO₂, and few studies have considered how and to what extent climate change and CO₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP‐DGVM coupled with CLM3 and CLM4‐CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO₂ concentration. In the temperature sensitivity tests, warming reduced the global area‐averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP‐DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP‐DGVM and in semiarid and arid regions for CLM4‐CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO₂ concentration.

The tree height–diameter at breast height (H–DBH) and crown radius–DBH (CR–DBH) relationships are key for forest carbon/biomass estimation, parameterization in vegetation models and vegetation–atmosphere interactions. Although the H–DBH relationship has been widely investigated on site or regional scales, and a few of studies have involved CR–DBH relationships based on plot-level data, few studies have quantitatively verified the universality of these two relationships on a global scale. This study evaluated the ability of 29 functions to fit the H–DBH and CR–DBH relationships for six different plant functional types (PFTs) on a global scale, based on a global plant trait database. Results showed that most functions were able to capture the H–DBH relationship for tropical PFTs and boreal needleleaf trees relatively accurately, but slightly less for temperate PFTs and boreal broadleaf trees (BB). For boreal PFTs, the S-shaped Logistic function fitted the H–DBH relationship best, while for temperate PFTs the Chapman–Richards function performed well. For tropical needleleaf trees, the fractional function of DBH satisfactorily captured the H–DBH relationship, while for tropical broadleaf trees, the Weibull function and a composite function of fractions were the best choices. For CR–DBH, the fitting capabilities of all the functions were comparable for all PFTs except BB. The Logistic function performed best for two boreal PFTs and temperate broadleaf trees, but for temperate needleleaf trees and two tropical PFTs, some exponential functions demonstrated higher skill. This work provides valuable information for parameterization improvements in vegetation models and forest field investigations.

Carbon partition among plant parts has a vital influence not only on the growth of individual plants but also on decomposition, carbon and nitrogen sequestration, and plant–atmosphere water exchange. Although many studies have tried to reveal plant growth mechanisms using observational living biomass or the biomass ratio among different organs, knowledge and understanding about carbon partition is still scarce and exists much uncertainty. In this work, a dataset about 1,089 sample plots of natural forests downloaded from the Chinese Ecosystem Research Network (CERN) was used to explore the dependences of net primary production (NPP) partition among foliage, stem and branch, and root on forest age, and mean annual temperature (MAT). The results found that (a) for all forest types, NPP partition had a significant relationship with forest age (p < 0.0001), that is, younger plants usually allocated a higher proportion of the NPP to stems, branches, and roots. As plants aged, an increasing proportion of the NPP was allocated to foliage; (b) MAT was negatively correlated with the proportions of the NPP allocated to foliage (F_leaf; %) and roots (F_root; %), while proportions of the NPP allocated to stems and branches (F_stbr; %) were positively dependent on MAT; (c) independent effect analysis demonstrated that forest age had a larger direct influence on F_leaf and F_root, while MAT was relatively important for F_stbr; and (d) forest age and MAT had a stronger combined effect on NPP allocation for broad‐leaved forests, while for needled‐leaved forests, the influences of forest age and MAT existed large differences among different forest types. This work not only is important for understanding the contribution of climatic factor and forest age on forest NPP partition, but also provides valuable ideas for developing ecological models.