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Forests play a vital role in regulation of the global carbon cycle. Mechanistically understanding how their ecosystem functioning relates to biodiversity is necessary for predicting the consequences of biodiversity loss and for setting conservation priorities. Here, we test whether carbon stocks in a subtropical evergreen broad-leaved forest in China are more strongly influenced by plant functional diversity (FD), as would be predicted by the ‘niche complementarity hypothesis’, or by community-weighted mean (CWM) functional trait values, as would be predicted by the ‘mass ratio hypothesis’. Using data from a 24-ha plot subdivided into 400 m2 quadrats, we determined relationships of aboveground carbon (AGC) and topsoil (1–10 cm) organic carbon (SOC) to topographic variables, stem density, CWM and FD of six functional traits hypothesized to influence carbon stocks. After accounting for topographic variables and tree stem density, boosted regression tree models revealed that CWMs were the dominant driving factors for both AGC and SOC, whereas FD had negligible effects. AGC and SOC were influenced by different functional traits, with AGC responding most strongly to CWM values for wood density and maximum tree height, and SOC responding most strongly to elevation, indicating that these carbon stocks are shaped by different underlying mechanisms. Our results support the mass ratio hypothesis but not the niche complementarity hypothesis. Our study implies that, when it comes to maximizing forest carbon storage, conservation priorities should focus on protection of species with traits associated to high carbon stocks.

Gaining a better understanding of the legacy effects of logging and forest restoration on soil microbial communities could improve our ability to conserve biodiversity and promote ecosystem sustainability. Herein, we investigated how soil microbial community is linked to natural, restored, and planted forests and the legacies of historical forest. Soil microbial biomass and composition were measured in four forest types (i.e., primary forest, once-clearcut forest, twice-logged forest, and plantation forest) and related to physico-chemical soil properties and forest community structure data by using analysis of covariance. Fungal, bacterial, and total microbial biomass measured by phospholipid fatty acid profiles were significantly lower in the two secondary forests and the plantation than in the primary forest. The conversion of vegetation and soil regimes due to forest logging altered microbial communities. Our findings elucidate the correlation of plant communities and soil characteristics to soil microbial communities in the context of subtropical forest management. Naturally restored and planted forests may affect soil microorganisms largely by directly modifying the soil labile C and N fractions of organic matter.

Restoring the functions of disturbed forest to mitigation climate change is a main topic of policy makers. Better understanding of factors that directly influence post- disturbance forest biomass recovery is urgently needed to guide forest restoration and management. In this study, we examine changes in forest stand structure, wood density and biomass of forests recovering from different anthropogenic disturbances that represent forest land-use types in sub- tropical China: plantation, twice-logged and once-logged secondary forests, and compare them with undisturbed old- growth forest. Stand structure and wood density in all dis- turbed forests were evidently different from that of old- growth forest, even after 50-year regrowth. Forest biomass increased along plantation, twice-logged, once-logged and old-growth forests, with total living biomass (TLB) ranging from 150.8 ± 4.6 to 278.4 ± 1.5 Mg ha -1 , aboveground biomass from 111.8 ± 4.2 to 204.1 ± 1.5 Mg ha -1 and coarse-root biomass from 33.0 ± 0.9 to 71.0 ± 0.8 Mg ha -1 . However, fine-root biomass was highest in plan- tation (5.99 ± 0.52 Mg ha -1 ) and lowest in once-logged forest (3.35 ± 0.19 Mg ha -1 ). Both changes in stand structure and functional trait (wood density) directly deter- mine forest biomass recovery according to the result that 10.6,35.5and8.2 %ofvariationinTLBoverthedisturbance gradient were independently explained by basal area (\20 cmdiameter),basal area(C20 cmdiameter)andwood density,respectively.Ourresultssuggestthatrecoveryforest structure to the state associated with undisturbed forests will lead to large carbon sink in disturbed forests. In addition, trait-based managing approach should not be overlooked when maximizing carbon storage is a major management objective.

Deterministic and stochastic processes jointly determine the community dynamics of forest succession. However, it has been widely held in previous studies that deterministic processes dominate forest succession. Furthermore, inference of mechanisms for community assembly may be misleading if based on a single axis of diversity alone. In this study, we evaluated the relative roles of deterministic and stochastic processes along a disturbance gradient by integrating species, functional, and phylogenetic beta diversity in a subtropical forest chronosequence in Southeastern China. We found a general pattern of increasing species turnover, but little-to-no change in phylogenetic and functional turnover over succession at two spatial scales. Meanwhile, the phylogenetic and functional beta diversity were not significantly different from random expectation. This result suggested a dominance of stochastic assembly, contrary to the general expectation that deterministic processes dominate forest succession. On the other hand, we found significant interactions of environment and disturbance and limited evidence for significant deviations of phylogenetic or functional turnover from random expectations for different size classes. This result provided weak evidence of deterministic processes over succession. Stochastic assembly of forest succession suggests that post-disturbance restoration may be largely unpredictable and difficult to control in subtropical forests.

With the full survey data for a 24-ha subtropical evergreen broad-leaved forest dynamics plot, we evaluated spatial variation in forest structure characteristics (basal area and aboveground biomass), and calculated the minimal sample size and total sampling area necessary to estimate the forest structure characteristics within 20% (±10%) of the observed values with 95% probability for particular quadrat sizes by using a computer program that is designed to simulate the sampling process by allowing different sized quadrats to be randomly located within the sampling region. We found that (1) based on the 600 20 m×20 m subplots, basal area and aboveground biomass displayed a high degree of variation, with respective coefficients of variation of 27% and 31%; (2) based on the computer simulation analysis, the variability of basal area and aboveground biomass decreased with increasing quadrat size. The number of quadrats required to achieve the specified degree of precision dropped sharply with the increase of quadrat size. However, the total sampling area increased with increasing quadrat size, suggesting that using several small quadrats across the sampling area is more efficient than using fewer larger quadrats. Results of this study are valuable for evaluating the reliability of previous research and may assist researchers in designing effective sampling strategies for future field surveys, particularly in subtropical evergreen broad-leaved forests in China.

C � Springer-Verlag 2005 Abstract Tree-ring samples of Picea schrenkiana (Fisch. et Mey) were studied along an altitudinal gradient in the central Tianshan Mountains, and ring-width chronologies were developed for three sites at different altitudes: low- forest border (1600-1700 m a.s.l.), interior forest (2100- 2200 m a.s.l.), and upper treeline (2600-2700 m a.s.l.). Annual ring-width variations were similar among the three sites but variability was greatest at the low-forest border site. The statistical characters of the chronologies showed that mean sensitivity (MS) and standard deviation (SD) decreased with increasing elevation. In other words, the re- sponse of tree growth to environmental changes decreased with increasing altitude. To understand the differing re- sponse of trees at different elevations to the environmental changes, response function analysis was used to study the relationships between tree-ring widths and mean monthly temperature and total monthly precipitation from 1961 to 2000. The results showed that precipitation was the most important factor limiting tree radial growth in the arid cen- tral Tianshan Mountains, precipitation in August of the prior growth year played an important role on tree's ra- dial growth across the entire altitudinal gradient even at the cold, high-elevation treeline site. It is expected that with increasing altitude air temperature decreased and precip- itation increased, the importance of precipitation on tree growth decreased, and the response of tree growth to envi- ronmental changes decreased, too. This conclusion may be helpful to understand and research the relationship between climatic change and tree growth in arid and semiarid area.

In this paper, we compare the relationship between scale and period in ecological pattern analysis and wavelet analysis. We also adapt a commonly used wavelet, the Morlet, to ecological pattern analysis. Using Monte Carlo assessments, we apply methods of statistical significance test to wavelet analysis for pattern analysis. In order to understand the inherent strength and weakness of the Morlet and the Mexican Hat wavelets, we also investigate and compare the properties of two frequently used wavelets by testing with field data and four artificial transects of different typical patterns which is often encountered in ecological research. It is shown that the Mexican Hat provides better detection and localization of patch and gap events over the Morlet, whereas the Morlet offers improved detection and localization of scale over the Mexican Hat. There is always a trade-off between the detection and localization of scale versus patch and gap events. Therefore, the best composite analysis is the combination of their advantages. The properties of wavelet in dealing with ecological data may be affected by characteristics intrinsic to wavelet itself. The peaks of different scales in isograms of wavelet power spectrum from the Mexican Hat may overlap with each other. Alternatively, these peaks of different scales in isograms of wavelet power spectrum may combine with each other unless the size of the analyzed scales is significantly different. These overlapping or combining lead to combining of peaks for different scales, or the masking of trough between peaks of different scales in the scalogram. Ecologists should combine all the information in scalogram and isograms of wavelet coefficient and wavelet power spectrum from different wavelets, which can provide us a broader view and precise pattern information.