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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.

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.

The Chapman-Richards growth function is used to model jack pine (Pinus banksiana Lamb.) tree height-diameter relationships at provincial, regional, and ecoregional levels. The results suggest that the tree height-diameter relationships of jack pine are significantly different among the geographic regions of Ontario, depending on local climatic, soil, and ecological conditions. In light of this study, the provincial and regional height-diameter models are not appropriate for predicting tree heights at the ecoregional level. Further, applying a specific ecoregional model to other ecoregions will also result in significant biases for predicting local tree heights. The ecoregion-based height-diameter models developed in this study may provide more accurate information on tree growth and development to forest resource managers and planners. Key words: Chapman-Richards growth function, permanent sample plot, non-linear extra sum of square method, forest management

Abstract Natural vegetation restoration can enhance soil organic carbon (SOC) sequestration, but the mechanisms and control factors underlying SOC sequestration are still unknown. The objectives of the study are to quantify the temporal variation of soil and aggregate‐associated organic carbon (OC) and identify factors controlling the variation following natural vegetation restoration after farmland abandonment. We collected soils from sites having 5, 30, 60, 100, and 160 years of a natural vegetation restoration chronosequence after farmland abandonment in the Loess Plateau, China. The results showed that natural vegetation restoration increased macroaggregates (0.25–2 mm; 46.6% to 73.9%), SOC (2.27 to 9.81 g kg −1 ), and aggregate OC (7.33 to 36.98 g kg −1 ) in the top 20‐cm soil compared with abandoned farmland, and the increases mainly occurred in the early stage (<60 years). The increase of SOC was contributed by OC accumulated in macroaggregates (0.25–2 mm) rather than microaggregates (≤0.25 mm). Moreover, SOC sequestration in the topsoil (0–10 cm) was mainly determined by fine root biomass (FR), labile organic carbon (LOC), and microbial biomass carbon (MBC). And in the subsoil (10–20 cm), SOC sequestration was mainly determined by the proportion of macroaggregates. The results suggest that natural vegetation restoration increased SOC and aggregate OC, and FR, MBC, LOC, and the physical protection of aggregates played important roles in regulating SOC and aggregate OC.