Forest disturbance and recovery are critical ecosystem processes,but the temporal patterns of disturbance have not been studied in subtropical China.Using a tree-ring analysis approach,we studied post-logging above-ground(ABG)biomass recovery dynamics over a 26-year period in four plots with different degrees of logging disturbance.Before logging,the ABG biomass ranged from 291 to 309 t ha-1.Soon after logging,the plots in primary forest,secondary forest,mixed forest and singlespecies forest had lost 33,91,90 and 100%of their initial ABG biomass,respectively.Twenty-six years after logging,the plots had regained 147,62,80 and 92%of their original ABG biomass,respectively.Over the 26 years following logging,the mean CAI(Current annual increment)were 10.1,5.5,6.4 and 10.8 t ha^-1 a^-1 and the average MAI(Mean annual increment)8.7,2.5,5.6 and 7.8 t ha^-1 a^-1 for the four forest types,respectively.The results indicate that subtropical forests subjected to moderate logging or disturbances do not require intensive management and single-species plantings can rapidly restore the above-ground biomass to levels prior to heavy logging. 相似文献
The leaf area index (LAI) of 16 sample plots was estimated based on terrestrial three-dimensional laser scanning. The point-cloud data of stand canopy were first scaled and projected onto a hemisphere according to Lambert azimuthal equal-area projection or stereographic projection, and the resulting hemispherical point-cloud images were used to extract the canopy porosity coefficients. Then, single-angle inversion and Miller formula inversion methods were used, respectively, to calculate the effective leaf area indices with canopy porosity coefficients. Results showed that the effective LAIs estimated by single-angle inversion method with Lambert projection and stereographic projection were within the range of 2.14~5.36 and 1.83~4.67, respectively. The effective LAIs obtained by Miller formula inversion method with Lambert projection and stereographic projection were within the range of 1.84~4.67 and 1.68~4.34, respectively. As a comparison, the LAI measured with a fish-eye camera ranged from 1.55 to 3.87. The LAI values estimated with four different calculation methods were linearly correlated with those measured by a fish-eye camera. The highest coefficient of determination (R2) 90.28% was obtained by the Miller formula inversion method combined with stereographic projection, and Duncan’s new multiple range test also further showed that this method had a relatively higher precision compared to other three methods. 相似文献
Soil organic carbon (SOC) in mountainous regions is characterized by strong topography-induced heterogeneity, which may contribute to large uncertainties in regional SOC stock estimation. However, the quantitative effects of topography on SOC stocks in semiarid alpine grasslands are currently not well understood. Therefore, the purpose of this research study is to determine the role of topography in shaping the spatial patterns of SOC stocks.
Materials and methods
Soils from the summit, shoulder, backslope, footslope, and toeslope positions along nine toposequences within three elevation-dependent grassland types (i.e., montane desert steppe at ~?2450 m, montane steppe at ~?2900 m, and subalpine meadow at ~?3350 m) are sampled at four depths (0–10, 10–20, 20–40, and 40–60 cm). SOC content, bulk density, soil texture, soil water content, and grassland biomass are determined. The general linear model (GLM) is employed to quantify the effects of topography on the SOC stocks. Ordinary least squares regressions are performed to explore the underlying relationships between SOC stocks and the other edaphic factors.
Results and discussion
In accordance with the present results, the SOC stocks at 0–60 cm show an increasing trend in respect to the elevation zone, with the highest stock being approximately 37.70 g m?2 in the subalpine meadow, about 2.07 and 3.41 times larger than that in the montane steppe and montane desert steppe, respectively. Along the toposequences, it is revealed the SOC stocks are maximal at toeslope, reaching to 14.98, 31.76, and 49.52 kg m?2, which are also significantly larger than those at the shoulder by a factor of 1.38, 2.31, and 1.44, in montane desert steppe, montane steppe, and subalpine meadow, respectively. Topography totally is seen to explain about 84% of the overall variation in SOC stocks, of which 70.61 and 9.74% are attributed to elevation zone and slope position, while the slope aspect and slope gradient are seen to plausibly explain only about 1.84 and 0.01%, respectively.
Conclusions
The elevation zone and the slope position are seen to markedly shape the spatial patterns of the SOC stocks, and thus, they may be considered as key indicating factors in constructing the optimal SOC estimation model in such semiarid alpine grasslands.
