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There is a lack in representation of biosphere–atmosphere interactions in current climate models. To fill this gap, one may introduce vegetation dynamics in surface transfer schemes or couple global climate models (GCMs) with vegetation dynamics models. As these vegetation dynamics models were not designed to be included in GCMs, how are the latest generation dynamic global vegetation models (DGVMs) suitable for use in global climate studies? This paper reviews the latest developments in DGVM modelling as well as the development of DGVM–GCM coupling in the framework of global climate studies. Limitations of DGVM and coupling are shown and the challenges of these methods are highlighted. During the last decade, DGVMs underwent major changes in the representation of physical and biogeochemical mechanisms such as photosynthesis and respiration processes as well as in the representation of regional properties of vegetation. However, several limitations such as carbon and nitrogen cycles, competition, land-use and land-use changes, and disturbances have been identified. In addition, recent advances in model coupling techniques allow the simulation of the vegetation–atmosphere interactions in GCMs with the help of DGVMs. Though DGVMs represent a good alternative to investigate vegetation–atmosphere interactions at a large scale, some weaknesses in evaluation methodology and model design need to be further investigated to improve the results.

Relationships between stand growth and structural diversity were examined in spruce-dominated forests in New Brunswick, Canada. Net growth, survivor growth, mortality, and recruitment represented stand growth, and tree species, size, and height diversity indices were used to describe structural diversity. Mixed-effects second-order polynomial regressions were employed for statistical analysis. Results showed stand structural diversity had a significant positive effect on net growth and survivor growth by volume but not on mortality and recruitment. Among the tested diversity indices, the integrated diversity of tree species and height contributed most to stand net growth and survivor growth. Structural diversity showed increasing trends throughout the developmental stages from young, immature, mature, and overmature forest stands. This relationship between stand growth and structural diversity may be due to stands featuring high structural diversity that enhances niche complementarities of resource use because trees exist within different horizontal and vertical layers, and strong competition resulted from size differences among trees. It is recommended to include effects of species and structural diversity in forest growth modeling initiatives. Moreover, uneven-aged stand management in conjunction with selective or partial cutting to maintain high structural diversity is also recommended to maintain biodiversity and rapid growth in spruce-dominated forests.

Abstract Global rivers and streams are important carbon transport pathways from land to the ocean. However, few studies have quantified terrigenous carbon dynamics in river ecosystems and its variations due to climate change and anthropogenic perturbations. Therefore, our study analysed fluvial particulate organic carbon (POC) and developed a processed‐based model (TRIPLEX‐HYDRA) to simulate the production, transport and removal (i.e., deposition, degradation and dam retention) processes of fluvial POC along the land–ocean aquatic continuum (LOAC). Based on our results, approximately 0.29 Pg of POC is exported from land to the ocean through rivers each year. More specifically, we found that rivers at low latitudes (30°S–30°N, 0.18 Pg yr −1 ) and high northern latitudes (60°N–90°N, 0.05 Pg yr −1 ) had higher POC fluxes compared to rivers in other regions. This high POC flux is related to strong erosion rates and high soil organic carbon storage. Additionally, our model simulation revealed that total POC flux from global river has not significantly changed from 1983 to 2015 but displays markedly decreased or increased trend at regional scale. These regional variations in POC export are affected by climate warming and dam construction. Moreover, approximately 0.46 Pg of POC is deposited or trapped by dams along the LOAC system, which plays a vital role in the global river carbon budget. Although some limitations and uncertainties remain, this study establishes a theoretical and methodological basis for quantifying riverine POC dynamics in the LOAC system.

Abstract Elevated nitrogen (N) deposition alters the terrestrial carbon (C) cycle, which is likely to feed back to further climate change. However, how the overall terrestrial ecosystem C pools and fluxes respond to N addition remains unclear. By synthesizing data from multiple terrestrial ecosystems, we quantified the response of C pools and fluxes to experimental N addition using a comprehensive meta-analysis method. Our results showed that N addition significantly stimulated soil total C storage by 5.82% ([2.47%, 9.27%], 95% CI, the same below) and increased the C contents of the above- and below-ground parts of plants by 25.65% [11.07%, 42.12%] and 15.93% [6.80%, 25.85%], respectively. Furthermore, N addition significantly increased aboveground net primary production by 52.38% [40.58%, 65.19%] and litterfall by 14.67% [9.24%, 20.38%] at a global scale. However, the C influx from the plant litter to the soil through litter decomposition and the efflux from the soil due to microbial respiration and soil respiration showed insignificant responses to N addition. Overall, our meta-analysis suggested that N addition will increase soil C storage and plant C in both above- and below-ground parts, indicating that terrestrial ecosystems might act to strengthen as a C sink under increasing N deposition.

Numerous empirical studies have demonstrated that street trees not only reduce dust pollution and absorb particulate matter (PM) but also improve microclimates, providing both ecological functions and aesthetic value. However, recent research has revealed that street tree canopy cover can impede the dispersion of atmospheric PM within street canyons, leading to the accumulation of street pollutants. Although many studies have investigated the impact of street trees on air pollutant dispersion within street canyons, the extent of their influence remains unclear and uncertain. Pollutant accumulation corresponds to the specific characteristics of individual street canyons, coupled with meteorological factors and pollution source strength. Notably, the characteristics of street tree canopy cover also exert a significant influence. There is still a quantitative research gap on street tree cover impacts with respect to pollution and dust reduction control measures within street spaces. To improve urban traffic environments, policymakers have mainly focused on scientifically based street vegetation deployment initiatives in building ecological garden cities and improving the living environment. To address uncertainties regarding the influence of street trees on the dispersion of atmospheric PM in urban streets, this study reviews dispersion mechanisms and key atmospheric PM factors in urban streets, summarizes the research approaches used to conceptualize atmospheric PM dispersion in urban street canyons, and examines urban plant efficiency in reducing atmospheric PM. Furthermore, we also address current challenges and future directions in this field to provide a more comprehensive understanding of atmospheric PM dispersion in urban streets and the role that street trees play in mitigating air pollution.

Historically, height–diameter models have mainly been developed for mature trees; consequently, few height–diameter models have been calibrated for young forest stands. In order to develop equations predicting the height of trees with small diameters, 46 individual height–diameter models were fitted and tested in young black spruce (Picea mariana) and jack pine (Pinus banksiana) plantations between the ages of 4 to 8 years, measured from 182 plots in New Brunswick, Canada. The models were divided into 2 groups: a diameter group and a second group applying both diameter and additional stand- or tree-level variables (composite models). There was little difference in predicting tree height among the former models (Group I) while the latter models (Group II) generally provided better prediction. Based on goodness of fit (R 2 and MSE), prediction ability (the bias and its associated prediction and tolerance intervals in absolute and relative terms), and ease of application, 2 Group II models were recommended for predicting individual tree heights within young black spruce and jack pine forest stands. Mean stand height was required for application of these models. The resultant tolerance intervals indicated that most errors (95%) associated with height predictions would be within the following limits (a 95% confidence level): [-0.54 m, 0.54 m] or [-14.7%, 15.9%] for black spruce and [-0.77 m, 0.77 m] or [-17.1%, 18.6%] for jack pine. The recommended models are statistically reliable for growth and yield applications, regeneration assessment and management planning. Key words: composite model, linear model, model calibration, model validation, prediction interval, tolerance interval

Abstract The knowledge of potential impacts of climate change on terrestrial vegetation is crucial to understand long‐term global carbon cycle development. Discrepancy in data has long existed between past carbon storage reconstructions since the Last Glacial Maximum by way of pollen, carbon isotopes, and general circulation model (GCM) analysis. This may be due to the fact that these methods do not synthetically take into account significant differences in climate distribution between modern and past conditions, as well as the effects of atmospheric CO 2 concentrations on vegetation. In this study, a new method to estimate past biospheric carbon stocks is reported, utilizing a new integrated ecosystem model (PCM) built on a physiological process vegetation model (BIOME4) coupled with a process‐based biospheric carbon model (DEMETER). The PCM was constrained to fit pollen data to obtain realistic estimates. It was estimated that the probability distribution of climatic parameters, as simulated by BIOME4 in an inverse process, was compatible with pollen data while DEMETER successfully simulated carbon storage values with corresponding outputs of BIOME4. The carbon model was validated with present‐day observations of vegetation biomes and soil carbon, and the inversion scheme was tested against 1491 surface pollen spectra sample sites procured in Africa and Eurasia. Results show that this method can successfully simulate biomes and related climates at most selected pollen sites, providing a coefficient of determination ( R ) of 0.83–0.97 between the observed and reconstructed climates, while also showing a consensus with an R ‐value of 0.90–0.96 between the simulated biome average terrestrial carbon variables and the available observations. The results demonstrate the reliability and feasibility of the climate reconstruction method and its potential efficiency in reconstructing past terrestrial carbon storage.

ABSTRACT The relationship between plant diversity and animal diversity on a broadscale and its mechanisms are uncertain. In this study, we explored this relationship and its possible mechanisms using data from 186 nature reserves across China on species richness of vascular plants and terrestrial vertebrates, and climatic and topographical variables. We found significant positive correlations between species richness in almost all taxa of vascular plants and terrestrial vertebrates. Multiple regression analyses indicated that plant richness was a significant predictor of richness patterns for terrestrial vertebrates (except birds), suggesting that a causal association may exist between plant diversity and vertebrate diversity in China. The mechanisms for the relationships between species richness of plants and animals are probably dependent on vertebrate groups. For mammals (endothermic vertebrates), this relationship probably represents the integrated effects of plants on animals through trophic links (i.e. providing foods) and non‐trophic interactions (i.e. supplying habitats), whereas for amphibians and reptiles (ectothermic vertebrates), this may be a result of the non‐trophic links, such as the effects of plants on the resources that amphibians and reptiles require.

Explaining species richness patterns over broad geographic scales is a central issue of biogeography and macroecology. In this study, we took spatial autocorrelation into account and used terrestrial vertebrate species richness data from 211 nature reserves, together with climatic and topographical variables and reserve area, to explain terrestrial vertebrate species richness patterns in China and to test two climatically based hypotheses for animals. Our results demonstrated that species richness patterns of different terrestrial vertebrate taxa were predicted by the environmental variables used, in a decreasing order, as reptiles (56.5%), followed by amphibians (51.8%), mammals (42%), and birds (19%). The endothermic vertebrates (mammals and birds) were closely correlated with net primary productivity (NPP), which supports the productivity hypothesis, whereas the ectothermic vertebrates (amphibians and reptiles) were strongly associated with both water and energy variables but weakly with NPP, which supports the physiologically based ambient climate hypothesis. The differences in the dependence of endothermic and ectothermic vertebrates on productivity or ambient climate may be due in part to their different thermoregulatory mechanisms. Consistent with earlier studies, mammals were strongly and positively related to geomorphologic heterogeneity, measured by elevation range, implying that the protection of mountains may be especially important in conserving mammalian diversity.

Many hypotheses have been proposed to explain elevational species richness patterns; however, evaluating their importance remains a challenge, as mountains that are nested within different biogeographic regions have different environmental attributes. Here, we conducted a comparative study for trees, shrubs, herbs, and ferns along the same elevational gradient for 22 mountains worldwide, examining the performance of hypotheses of energy, tolerance, climatic variability, and spatial area to explain the elevational species richness patterns for each plant group. Results show that for trees and shrubs, energy-related factors exhibit greater explanatory power than other factors, whereas the factors that are associated with climatic variability performed better in explaining the elevational species richness patterns of herbs and ferns. For colder mountains, energy-related factors emerged as the main drivers of woody species diversity, whereas in hotter and wetter ecosystems, temperature and precipitation were the most important predictors of species richness along elevational gradients. For herbs and ferns, the variation in species richness was less than that of woody species. These findings provide important evidence concerning the generality of the energy theory for explaining the elevational species richness pattern of plants, highlighting that the underlying mechanisms may change among different growth form groups and regions within which mountains are nested.