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Vegetation index is a key indicator for qualitative and quantitative assessment of green vegetation, which has been widely used in vegetation monitoring. Forests are often distributed in mountainous areas with complex topography, which is one of the main factors of accurate retrieval of forest vegetation information. Here, we analyzed the topographic effects on canopy reflectance using a geometric optical model. The responses of complete ratio vegetation indices [simple ratio index (SR), normalized difference vegetation index (NDVI) and moisture adjusted vegetation index (MAVI)], incomplete ratio vegetation indices [enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI)], non-ratio vegetation indices [reduced simple ratio (RSR), modified normalized difference vegetation index (MNDVI), greenness vegetation index (GVI)] and, topography adjusted vegetation index [topography adjusted vegetation index (TAVI)] to topography were discussed in detail, with the aim to provide reference for selecting vegetation index in complex terrain mountainous area. The shortcomings of current literatures about the topographic effects on vegetation indices were analyzed and the future research directions were prospected. [ABSTRACT FROM AUTHOR]

This study focused on retrieval of net photosynthetic rate (Pn) of moso bamboo forest based on analysis of wavelet transform on hyperspectral reflectance data of moso bamboo forest leaf. The result showed that the accuracy of Pn retrieved by the ideal high frequency wavelet vegetation index (VI) was higher than that retrieved by low frequency wavelet VI and spectral VI. Normalized difference vegetation index of wavelet (NDVIw), simple ratio vegetation index of wavelet (SRw) and difference vegetation index of wavelet (Dw) constructed by the first layer of high frequency coefficient through wavelet decomposition had the highest relationship with Pn, with the R2 of 0.7 and RMSE of 0.33; low frequency wavelet VI had no advantage compared with spectral VI. Significant correlation existed between Pn estimated by multivariate linear model constructed by the ideal wavelet VI and the measured Pn, with the R2 of 0.77 and RMSE of 0.29, and the accuracy was significantly higher than that of using the spectral VI. Compared with the fact that sensitive spectral bands of the retrieval through spectral VI were limited in the range of visible light, the wavelength of sensitive bands of wavelet VI ranged more widely from visible to infrared bands. The results illustrated that spectrum of wavelet transform could reflect the Pn of moso bamboo more in detail, and the overall accuracy was significantly improved than that using the original spectral data, which provided a new alternative method for retrieval of Pn of moso bamboo forest using hyper spectral remotely sensed data. [ABSTRACT FROM AUTHOR]

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle ( UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis ( SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R ) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error ( RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest. [ABSTRACT FROM AUTHOR]

CO2, N2OH4 and CH4 are important greenhouse gases, and soils in forest ecosystems are their important sources. Carya cathayensis is a unique tree species with seeds used for high-grade dry fruit and oil production. Understory vegetation management plays an important role in soil greenhouse gases emission of Carya cathayensis stands. A one-year in situ experiment was conducted to study the effects of understory removal on soil CO2, N2O and CH4 emissions in C. cathayensis plantation by closed static chamber technique and gas chromatography method. Soil CO2 flux had a similar seasonal trend in the understory removal and preservation treatments, which was high in summer and autumn, and low in winter and spring. N2O emission occurred mainly in summer, while CH4 emission showed no seasonal trend. Understory removal significantly decreased soil CO2 emission, increased N2O emission and CH4 uptake, but had no significant effect on soil water soluble organic carbon and microbial biomass carbon. The global warming potential of soil greenhouse gases emitted in the understory removal treatment was 15.12 t CO2-e • hm-2 • a-1, which was significantly lower than that in understory preservation treatment ( 17.04 t CO2-e • hm-2 • a-1). [ABSTRACT FROM AUTHOR]

Effect of biochar addition on soil CO2 efflux in a typical Chinese chestnut (Castanea mollissima) plantation in Lin'an, Zhejiang Province, China was investigated from July 2012 to July 2013 by the static closed chamber-GC technique. Soil temperature, soil moisture, WSOC and MBC concentrations were determined as well. Results showed that soil CO2 efflux exhibited a strong seasonal pattern. Compared with the control (without biochar application), the biochar treatment increased the soil CO2 efflux only in the first month since application, and then the effect diminished thereafter. There were no significant differences in the annual cumulative value of soil CO2 efflux between the biochar and control treatments. The annual mean value in soil MBC concentration (362 mg.kg-1) in the biochar treatment was higher than that (322 mg.kg-1) in the control. However, no significant difference in the soil WSOC concentration was found between the biochar and control treatments. Strong exponential relationships between soil temperature and soil CO2 efflux were observed regardless of the treatment and soil layer. The apparent temperature sensitivity (Q10) of soil CO2 efflux in the biochar treatment was higher than that in the control. Soil CO2 efflux was related to soil WSOC concentration but not with soil MBC or moisture content. To conclude, the application of bamboo leaf biochar did not affect the annual cumulative CO2 emission in the Chinese chestnut plantation but increased the Q10, and the CO2 efflux was predominantly controlled by the soil temperature and soil WSOC level. [ABSTRACT FROM AUTHOR]

By using eddy covariance technique, this paper studied the CO2 flux in a Phyllostachys edulis forest ecosystem with high-efficiency management in Zhejiang Province of China from December, 2010 to November, 2011, and analyzed the variations of net ecosystem exchange (NEE), ecosystem respiration (RE), and gross ecosystem exchange (GEE). During the study period, the monthly NEE was always negative, with the maximum (-99. 33 g C•m-2 ) in July and the minimum (-23. 49 g C•m-2 ) in November, and the seasonal change showed a bimodal shape. The average diurnal change of the monthly CO2 flux varied greatly from -0. 30 g CO2•m-2•s-1 (January) to -0. 60 g CO2•m-2•s-1 (September). The NEE at the time point of positive and negative conversion had obvious seasonal characteristics. The yearly RE changed in unimodal shape, with the maximum in summer and the minimum in winter. The RE at nighttime had significant negative correlation with soil temperature. The yearly NEE, RE, and GEE were -668.40, 932. 55, and -1600. 95 g C•m-2•a-1, respectively, among which, the NEE occupied 41. 8% of the GEE. As compared with other ecosystems, P. edulis forest ecosystem had a strong capability in carbon sequestration. [ABSTRACT FROM AUTHOR]

In June 2011-June 2012, a fertilization experiment was conducted in a typical Castanea mollissima stand in Lin'an of Zhejiang Province, East China to study the effects of inorganic and organic fertilization on the soil CO2 flux and the relationships between the soil CO2 flux and environmental factors. Four treatments were installed, i. e. , no fertilization (CK), inorganic fertilization (IF), organic fertilization (OF), half organic plus half inorganic fertilization (OIF). The soil CO2 emission rate was determined by the method of static closed chamber/ GC technique, and the soil temperature, soil moisture content, and soil water-soluble organic carbon (WSOC) concentration were determined by routine methods. The soil CO2 emission exhibited a strong seasonal pattern, with the highest rate in July or August and the lowest rate in February. The annual accumulative soil CO2 emission in CK was 27. 7 t CO2 ·hm-2 ·a-1, and that in treatments IF, OF, and OIF was 29. 5%, 47. 0%, and 50. 7% higher than the CK, respectively. The soil WSOC concentration in treatment IF (105. 1 mg kg-1) was significantly higher than that in CK (76. 6 mg·kg-1), but was obviously lower than that in treatments OF (133. 0 mg·kg-1 ) and OIF (121. 2 mg·kg-1 ). The temperature sensitivity of respiration (Q10) in treatments CK, IF, OF, and OIF was 1. 47, 1. 75, 1. 49, and 1. 57, respectively. The soil CO2 emission rate had significant positive correlations with the soil temperature at the depth of 5 cm and the soil WSOC concentration, but no significant correlation with soil moisture content. The increase of the soil WSOC concentration caused by fertilization was probably one of the reasons for the increase of soil CO2 emission from the C. mollissima stand. [ABSTRACT FROM AUTHOR]

The PROSAIL canopy radiative transfer model was used to establish leaf area index (LAI) and canopy reflectance lookup-table for Moso bamboo forest. The combination of Landsat Thematic Mapper (TM) image and this model was then used to retrieve LAI. The results demonstrated that the sensitivity of the input parameters in the PROSAIL model decreased in order of LAI >chlorophyll content (Cab) > leaf structure parameters (N) > mean leaf angle (ALA) > equivalent water thickness (Cw) > dry matter content (Cm). The most sensitive factors LAI and Cab were then used to construct the LAI-canopy reflectance lookup-table. The LAI estimates from the PROSAIL model had good agreement with the reference data, with the coefficient of determination (R2 ) reached 0. 90. The root mean square error (RMSE) and relative RMSE were 0. 58 and 13-0%, respectively. However, the mean LAI estimate was higher than the observed value. [ABSTRACT FROM AUTHOR]

By using open-path eddy covariance system and meteorological instruments, an observation was conducted on the sensitive heat flux, latent heat flux, net radiation, soil heat flux, air temperature, ground temperature, and precipitation in a intensively managed Lei bamboo forest ecosystem in 2011, with the diurnal and monthly variations of energy flux as well as the distribution pattern of each energy component analyzed, and the Bowen ratio and energy balance closure calculated. The yearly net radiation of the forest ecosystem was 2928. 92 MJ.m-2, and the latent heat flux, sensitive heat flux, and soil heat flux were 1384. 90, 927. 54, and -28. 27 MJ.m-2, respectively. Both the daily and the monthly variations of the energy components showed a single peak curve. The sensible and latent heat fluxes were 31. 7% and 47. 3% of the net radiation, respectively, indicating that latent heat flux was the main form of energy loss. The Bowen ratio followed the "U"-shaped pattern, and fluctuated from 0. 285 to 2. 062, suggesting that soil was a heat source. The yearly energy balance closure of the forest ecosystem was 0. 782, and the monthly average was 0. 808. [ABSTRACT FROM AUTHOR]

Taking the moso bamboo production areas Lin'an, Anji, and Longquan in Zhejiang Province of East China as study areas, and based on the integration of field survey data and Landsat 5 Thematic Mappr images, five models for estimating the moso bamboo (Phyllostachys heterocycla var. pubescens) forest biomass were constructed by using linear, nonlinear, stepwise regression, multiple regression, and Erf-BP neural network, and the models were evaluated. The models with higher precision were then transferred to the study areas for examining the model's transferability. The results indicated that for the three moso bamboo production areas, Erf-BP neural network model presented the highest precision, followed by stepwise regression and nonlinear models. The Erf-BP neural network model had the best transferability. Model type and independent variables had relatively high effects on the transferability of statistical-based models. [ABSTRACT FROM AUTHOR]

To investigate the effects of the conversion from native shrub forest (NF) to Chinese chestnut plantation (CP) on the soil carbon (C) and nitrogen (N) pools, soil samples were collected from the adjacent NF and CP in Anji County of Zhejiang Province, with their water-soluble organic C (WSOC), microbial biomass C (MBC), readily oxidizable C (ROC), water-soluble organic N (WSON), and microbial biomass N (MBN) determined. The spectral characteristics of soil organic C were also determined by using nuclear magnetic resonance (NMR) technique. After the conversion from NF to CP, the soil alkalyzable N, available phosphorus, and available potassium contents increased significantly, while the soil WSOC, MBC, ROC, WSON, and MBN were in adverse. The soil organic C in both NF and CP was dominated by alkyl C and O-alkyl C, but the proportions of O-alkyl C and carbonyl C in soil organic C decreased while the proportions of alkyl C and aromatic C as well as the alkyl C / O-alkyl C ratio and the aromaticity of soil organic C all increased significantly after the conversion from NF to CP, indicating that this conversion increased the stability of soil organic C pool significantly. In conclusion, the conversion from NF to CP and the intensive management of CP decreased the contents of soil labile C and soil N but increased the stability of soil C pool significantly. [ABSTRACT FROM AUTHOR]

Landsat Thematic Mapper (TM) image was used to estimate Moso bamboo forest biomass, and six atmospheric calibration methods (FLAASH model, 6S model, and DOS1-4 models) were adopted to analysis the effects of atmospheric calibration on the remote sensing estimation of Moso bamboo forest biomass. All the six calibration methods could effectively reduce the atmospheric impacts on TM spectral responses. The relationships between NDVI and Moso bamboo forest biomass under the calibration by the six calibration methods were improved. Great differences were observed in the relationships of Moso bamboo forest biomass with NDVI, II , and MI when using the same calibration methods, suggesting that atmospheric calibration should be made for studying the biophysical significance of vegetation indices. The Landsat TM data corrected with DOS3 model had the highest correlation coefficient with Moso bamboo forest biomass, but there were no significant differences in the correlation coefficients after corrected with the six calibration methods, which indicated that atmospheric calibration might be not required if a single TM image was used for biomass estimation with multiple linear regression model. [ABSTRACT FROM AUTHOR]

Forest fire is an important disturbance factor of natural ecosystem, which can release great amount of greenhouse gases. With the persistent global warming, forest fire tends to happen more frequently. Based on the statistical data of forest fires and the biomass data of dominant forest types in Zhejiang Province in 1991-2006, the annual greenhouse gases emission from forest fires in the Province was estimated by using emission factors and emission ratio. The results showed that the annual emissions of CO2, CO, CH4, and non-methane hydrocarbon (NMHC) from forest fires were 127930, 7672.8, 3098.7, and 1475.5 t, and the amounts of annually consumed biomass and carbon were 86148.1 and 38776.7 t, respectively, suggesting that forest fire had definite effects on the regional carbon budget. [ABSTRACT FROM AUTHOR]

The litters of seven tree species representing the dominant plant species in three main successional stages in subtropical China, i.e., Pinus massoniana in early successional forests, Schima superba and Cinnamanun camphora in transitional forests, and Castanopsis eyeri, Cyclobalanopsis gracilis, Cyclobalanopsis glauca, and Michelia chapensis in late successional forests, were collected, and their decomposition rates were measured with litterbags. The results showed that M. chapensls and C. gracilis had the highest litter decomposition rate (k=1.12 and 0.89, respectively), followed by C. camphora and S. superba (k=0.61 and 0.55, respectively), and P. massoniana (k=0.51), indicating that there was a trend of litter decomposition rate being increased with succession stage. Litter decomposition rate had significant correlations with the litter's initial P, N, and lignin contents, lignin/N ratio (P<0.01), and C/N ratio (P<0.05), suggesting that the initial P, N, and lignin contents and lignin/N ratio of leaf litter could be the good indictors of litter decomposition rate. [ABSTRACT FROM AUTHOR]

Elevated atmospheric CO 2 concentration, altered precipitation regime, increased nitrogen deposition, and land cover change have not only changed the physical and chemical properties of forest soils, but also affected plant growth and microbial activity, with concequences on soil carbon and nitrogen cycles, including soil CH 4 uptake. In this study, we summarized the important role of soil CH 4 uptake in forests under global change scenarios. The differences of responses as well as the underlying mechanisms of soil CH 4 uptake in forests to global change were reviewed. Elevated atmospheric CO 2 concentration inhibits soil CH 4 uptake. Reduced precipitation tends to promote soil CH 4 uptake. Increased nitrogen input inhibits soil CH 4 uptake in nitrogen-rich forests, but promotes or has no effects on soil CH 4 uptake in nitrogen-poor forests. Conversion of forests to grassland, farmland, or plantations would reduce soil CH 4 uptake, while afforestation increases soil CH 4 uptake. The future research should explore the long-term and multiple effects of global changes on forest soil CH 4 uptake. In addition, molecular biology methods should be developed to explore the microbial mechanism of soil CH 4 uptake.

Based on the MODIS surface reflectance data, five vegetation indices, including norma-lized difference vegetation index (NDVI), simple ratio index (SR), Gitelson green index (GI), enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI) were constructed as remote sensing variables, coupled with the seven original spectral reflectance bands of MODIS. Stepwise regression and correlation analysis were used to select the variables, and the stepwise regression and Back Propagation (BP) neural network models were constructed based on the measured LAI to retrieve the LAI time series data of Phyllostachys praecox (Lei bamboo) forest during the period from January 2014 to March 2017. The retrieval results were compared with MOD15A2 LAI products during the same period. The results showed that SR was the single variable selected for the stepwise regression model. The correlations of LAI with bands b 1 , b 2 , b 3 , b 7 and five vegetation indices were significant, which could be used as input variables of BP neural network model. There was a significant correlation between the LAI estimated from BP neural network and measured LAI, with the R 2 of 0.71, RMSE of 0.34, and RMSE r of 13.6%. R 2 was increased by 10.9%, RMSE decreased by 5.6%, and RMSE r decreased by 12.3% compared with LAI estimated from stepwise regression method. R 2 was increased by 54.5%, RMSE decreased by 79.3%, and RMSE r decreased by 79.1% compared with MODIS LAI. The LAI of Lei bamboo forest could be accurately retrieved using BP neural network method based on MODIS reflectance time series data, which would be a feasible method for rapid monitoring of LAI in Lei bamboo forest.

Vegetation index is a key indicator for qualitative and quantitative assessment of green vegetation, which has been widely used in vegetation monitoring. Forests are often distributed in mountainous areas with complex topography, which is one of the main factors of accurate retrieval of forest vegetation information. Here, we analyzed the topographic effects on canopy reflectance using a geometric optical model. The responses of complete ratio vegetation indices [simple ratio index (SR), normalized difference vegetation index (NDVI) and moisture adjusted vegetation index (MAVI)], incomplete ratio vegetation indices [enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI)], non-ratio vegetation indices [reduced simple ratio (RSR), modified normalized difference vegetation index (MNDVI), greenness vegetation index (GVI)] and, topography adjusted vegetation index [topography adjusted vegetation index (TAVI)] to topography were discussed in detail, with the aim to provide reference for selecting vegetation index in complex terrain mountainous area. The shortcomings of current literatures about the topographic effects on vegetation indices were analyzed and the future research directions were prospected.

The typical natural secondary shrub community was chosen in Lin'an of Zhejiang Pro-vince to discover its possibility of restoration to arbor forest with three kinds of forest management models being taken, i.e., no care as control, closed forest management and target tree tending. Over four years growth, compared with control, closed forest management significantly increased average DBH and height by 130% and 50%, respectively, while 260% and 110% for target tree tending. In target tree tending plots, larger trees had been emerging with 4.5-8.5 cm diameter class and 4.5-8.5 m height class and formed a new storey of 4 m compared with control. The species biodiversity indexes at shrub layer were significantly increased in closed management plots, and did not decrease in target tree tending plots. Closed forest management did not change the tree species composition, following its previous succession direction. However, target tree tending increased the importance value of target species with the high potential succession direction of mixed coniferous-broadleaved forest. The results revealed that the secondary shrub community with target tree tending achieved more desired goals on DBH and height growth of dominant trees and species composition improvement compared with closed management. If the secondary shrub community could be managed when the operational conditions existed, target tree tending model should be selected to accelerate the restoration of shrub toward arbor forest.

LAI is one of the most important observation data in the research of carbon cycle of forest ecosystem, and it is also an important parameter to drive process-based ecosystem model. The Moso bamboo forest (MBF) and Lei bamboo forest (LBF) were selected as the study targets. Firstly, the MODIS LAI time series data during 2014-2015 was assimilated with Dual Ensemble Kalman Filter method. Secondly, the high quality assimilated MBF LAI and LBF LAI were used as input dataset to drive BEPS model for simulating the gross primary productivity (GPP), net ecosystem exchange (NEE) and total ecosystem respiration (TER) of the two types of bamboo forest ecosystem, respectively. The modeled carbon fluxes were evaluated by the observed carbon fluxes data, and the effects of different quality LAI inputs on carbon cycle simulation were also studied. The LAI assimilated using Dual Ensemble Kalman Filter of MBF and LBF were significantly correlated with the observed LAI, with high R 2 of 0.81 and 0.91 respectively, and lower RMSE and absolute bias, which represented the great improvement of the accuracy of MODIS LAI products. With the driving of assimilated LAI, the modeled GPP, NEE, and TER were also highly correlated with the flux observation data, with the R 2 of 0.66, 0.47, and 0.64 for MBF, respectively, and 0.66, 0.45, and 0.73 for LBF, respectively. The accuracy of carbon fluxes modeled with assimilated LAI was higher than that acquired by the locally adjusted cubic-spline capping method, in which, the accuracy of mo-deled NEE for MBF and LBF increased by 11.2% and 11.8% at the most degrees, respectively.

In order to elucidate the effects of intensive management on soil carbon pool, nitrogen pool, enzyme activities in Moso bamboo (Phyllostachys pubescens) plantations, we collected soil samples from the soil surface (0-20 cm) and subsurface (20-40 cm) layers in the adjacent Moso bamboo plantations with extensive and intensive managements in Sankou Township, Lin'an City, Zhejiang Province. We determined different forms of C, N and soil invertase, urease, catalase and acid phosphatase activities. The results showed that long-term intensive management of Moso bamboo plantations significantly decreased the content and storage of soil organic carbon (SOC), with the SOC storage in the soil surface and subsurface layers decreased by 13.2% and 18.0%, respectively. After 15 years' intensive management of Masoo bamboo plantations, the contents of soil water soluble carbon (WSOC), hot water soluble carbon (HWSOC), microbial carbon (MBC) and readily oxidizable carbon (ROC) were significantly decreased in the soil surface and subsurface layers. The soil N storage in the soil surface and subsurface layers in intensively managed Moso bamboo plantations increased by 50.8% and 36.6%, respectively. Intensive management significantly increased the contents of nitrate-N (NO 3 - -N) and ammonium-N (NH 4 + -N), but decreased the contents of water-soluble nitrogen (WSON) and microbial biomass nitrogen (MBN). After 15 years' intensive management of Masoo bamboo plantations, the soil invertase, urease, catalase and acid phosphatase activities in the soil surface layer were significantly decreased, the soil acid phosphatase activity in the soil subsurface layer were significantly decreased, and other enzyme activities in the soil subsurface layer did not change. In conclusion, long-term intensive management led to a significant decline of soil organic carbon storage, soil labile carbon and microbial activity in Moso bamboo plantations. Therefore, we should consider the use of organic fertilizer in the intensive mana-gement process for the sustainable management of Moso bamboo plantations in the future.

Converting natural forests to plantations significantly affects the characteristics of soil organic carbon (C) pools, due to the changes of vegetation cover and management practices. In this paper, to investigate the effects of conversion from evergreen broad-leaved forest (EBF) to Chinese chestnut plantation (CP) on soil organic C pool, the soils from surface (0-20 cm) and subsurface (20-40 cm) layers were sampled from the above two forests (the CP was converted from the EBF and had been intensively managed for 10 years) in Lin'an City, Zhejiang Province. The soil orga-nic C storage, labile organic C pools, and other basic soil properties were determined. The chemical composition of soil organic C was determined by nuclear magnetic resonance (NMR) technique. Results showed that the soil organic C storage, water soluble organic C (WSOC), hot water soluble organic C (HWSOC), microbial biomass C (MBC) and readily oxidizable C (ROC) concentrations in the surface layer decreased by 19.7%, 34.4%, 25.8%, 30.4% and 25.2%, respectively, after the conversion from EBF to CP. Such values for the subsurface layers decreased by 13.5%, 38.4%, 19.8%, 34.1% and 22.2%, respectively. The O-alkyl C content, aromatic C content and aromaticity of soil organic C in the surface layer decreased signi-ficantly by the land-use conversion, while alkyl C content, carbonyl C content and alkyl C to O-alkyl C (A/O-A) ratio increased signi-ficantly. The O-alkyl C content of soil organic C in the subsurface layer decreased significantly by the land-use conversion, alkyl C content and A/O-A ratio increased significantly, and aromatic C content, carbonyl C content and aromaticity of soil organic C were not changed. In conclusion, conve-rting EBF to CP and subsequent intensive management significantly decreased the soil organic C sto-rage and labile C pool contents and altered the chemical composition of soil organic C.

This study focused on retrieval of net photosynthetic rate (Pn) of moso bamboo forest based on analysis of wavelet transform on hyperspectral reflectance data of moso bamboo forest leaf. The result showed that the accuracy of Pn retrieved by the ideal high frequency wavelet vegetation index ( VI) was higher than that retrieved by low frequency wavelet VI and spectral VI. Normalized difference vegetation index of wavelet (NDVIw), simple ratio vegetation index of wavelet (SRw) and difference vegetation index of wavelet (Dw) constructed by the first layer of high frequency coefficient through wavelet decomposition had the highest relationship with Pn, with the R² of 0.7 and RMSE of 0.33; low frequency wavelet VI had no advantage compared with spectral VI. Significant correlation existed between Pn estimated by multivariate linear model constructed by the ideal wavelet VI and the measured Pn, with the R² of 0.77 and RMSE of 0.29, and the accuracy was significantly higher than that of using the spectral VI. Compared with the fact that sensitive spectral bands of the retrieval through spectral VI were limited in the range of visible light, the wavelength of sensitive bands of wavelet VI ranged more widely from visible to infrared bands. The results illustrated that spectrum of wavelet transform could reflect the Pn of moso bamboo more in detail, and the overall accuracy was significantly improved than that using the original spectral data, which provided a new alternative method for retrieval of Pn of moso bamboo forest using hyper spectral remotely sensed data.

Soil CO2 effluxes in natural broad-leaved forest and the conversed Chinese fir plantation in Linglong Mountains Scenic of Zhejiang Province were evaluated by using static closed chamber and gas chromatography method. The results showed that soil CO2 efflux showed consistent seasonal dynamics in natural broad-leaved forest and Chinese fir plantation, with the maximums observed in summer and autumn, the minimums in winter and spring. Soil CO2 effluxes were 20.0-111.3 and 4.1-118.6 mg C . m-2 . h-1 in natural broad-leaved forest and Chinese fir plantation, respectively. The cumulative soil CO2 emission of natural broad-leaved forest (16.46 t CO2 . hm-2 . a-1) was significantly higher than that of Chinese fir plantation (11.99 t CO2 . hm-2 . a-1). Soil moisture did not affect soil CO2 efflux. There was a significant relationship between soil CO2 efflux and soil temperature at 5 cm depth. There was no significant relationship between soil CO2 efflux of natural broad-leaved forest and water soluble organic carbon content, while water soluble organic carbon content affected significantly soil CO2 efflux in Chinese fir plantation. Converting the natural broad-leaved forest to Chinese fir plantation reduced soil CO2 efflux significantly but improved the sensitivity of soil respiration to environmental factors.

Dynamic changes (from April 2013 to March 2014) in soil respiration components were investigated by Li-8100 in the Moso bamboo plantation in Lin' an City, Zhejiang Province. Results showed that the average annual values for the soil total respiration rate, heterotrophic respiration rate, and autotrophic respiration rate in the Moso bamboo plantation were 2.93, 1.92 and 1.01 imol CO2 . m-2 . s-1, respectively. The soil respiration rate and its components exhibited strongly a seasonal dynamic pattern. The maximum appeared in July 2013, and the minimum appeared in January 2014. The annual cumulative CO2 emissions through soil respiration, heterotrophic respiration, and autotrophic respiration were 37.25, 24.61 and 12.64 t CO2 . hm-2 . a-1, respectively. The soil respiration and its components showed a close relation with soil temperature of 5 cm depth, and the corresponding Q10, values at 5 cm depth were 2.05, 1.95 and 2.34, respectively. Both the soil respiration and heterotrophic respiration were correlated to soil water soluble organic C (WSOC) content, but no significant relationship between autotrophic respiration and WSOC was observed. There were no significant relationships between soil respiration components and soil moisture content or microbial biomass C. The seasonal changes in soil respiration components in the Moso bamboo plantation were predominantly controlled by the soil temperature, and the soil WSOC content was an important environmental factor controlling total soil respiration and soil heterotrophic respiration.

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

CO2, N2O and CH4 are important greenhouse gases, and soils in forest ecosystems are their important sources. Carya cathayensis is a unique tree species with seeds used for high-grade dry fruit and oil production. Understory vegetation management plays an important role in soil greenhouse gases emission of Carya cathayensis stands. A one-year in situ experiment was conducted to study the effects of understory removal on soil CO2, N2O and CH4 emissions in C. cathayensis plantation by closed static chamber technique and gas chromatography method. Soil CO2 flux had a similar seasonal trend in the understory removal and preservation treatments, which was high in summer and autumn, and low in winter and spring. N2O emission occurred mainly in summer, while CH4 emission showed no seasonal trend. Understory removal significantly decreased soil CO, emission, increased N2O emission and CH4 uptake, but had no significant effect on soil water soluble organic carbon and microbial biomass carbon. The global warming potential of soil greenhouse gases emitted in the understory removal. treatment was 15.12 t CO2-e . hm-2 a-1, which was significantly lower than that in understory preservation treatment (17.04 t CO2-e . hm-2 . a-1).

Effect of biochar addition on soil CO2 efflux in a typical Chinese chestnut (Castanea mollissima) plantation in Lin'an, Zhejiang Province, China was investigated from July 2012 to July 2013 by the static closed chamber-GC technique. Soil temperature, soil moisture, WSOC and MBC concentrations were determined as well. Results showed that soil CO2 efflux exhibited a strong sea- sonal pattern. Compared with the control (without biochar application), the biochar treatment increased the soil CO2 efflux only in the first month since application, and then the effect diminished thereafter. There were no significant differences in the annual cumulative value of soil CO2 efflux between the biochar and control treatments. The annual mean value in soil MBC concentration (362 mg · kg(-1)) in the biochar treatment was higher than that (322 mg · kg(-1)) in the control. However, no significant difference in the soil WSOC concentration was found between the biochar and control treatments. Strong exponential relationships between soil temperature and soil CO2 efflux were observed regardless of the treatment and soil layer. The apparent temperature sensitivity (Q10) of soil CO2 efflux in the biochar treatment was higher than that in the control. Soil CO2 efflux was related to soil WSOC concentration but not with soil MBC or moisture content. To conclude, the application of bamboo leaf biochar did not affect the annual cumulative CO2 emission in the Chinese chestnut plantation but increased the Q10, and the CO2 efflux was predominantly controlled by the soil temperature and soil WSOC level.

By using eddy covariance technique, this paper studied the CO2 flux in a Phyllostachys edulis forest ecosystem with high-efficiency management in Zhejiang Province of China from December, 2010 to November, 2011, and analyzed the variations of net ecosystem exchange (NEE), ecosystem respiration (RE), and gross ecosystem exchange (GEE). During the study period, the monthly NEE was always negative, with the maximum (-99.33 g C x m(-2)) in July and the minimum (-23.49 g C x m(-2)) in November, and the seasonal change showed a bimodal shape. The average diurnal change of the monthly CO2 flux varied greatly from -0.30 g CO2 x m(-2) x s(-1) (January) to -0.60 g CO2 x m(-2) x s(-1) (September). The NEE at the time point of positive and negative conversion had obvious seasonal characteristics. The yearly RE changed in unimodal shape, with the maximum in summer and the minimum in winter. The RE at nighttime had significant negative correlation with soil temperature. The yearly NEE, RE, and GEE were -668.40, 932.55, and -1600.95 g C x m(-2) x a(-1), respectively, among which, the NEE occupied 41.8% of the GEE. As compared with other ecosystems, P. edulis forest ecosystem had a strong capability in carbon sequestration.

In order to explore the influence of Phyllostachys edulis invasion on the surrounding forest environment,the effects of aqueous extracts from P. edulis on two dominant species (Castanopsis sclerophylla and Cyclobalanopsis glaunca)in southern China were assessed by germination bioassays. The results showed that seed germination effects depended on the concentration of aqueous extracts and the extract sources. The highest extract concentration showed significant inhibitory effects on seed germination percentage, which was 82. 3% -102. 2% of control for C. sclerophylla and 80% -90. 9% of control for C. glauca, while in the treatment with lowest extract concentration the values were 101.7% - 107.6% of control for C. sclerophylla and 94.9% - 109. 1% of control for C. glauca, respectively. The extracts had inhibitory effects on the germination speed of both species (P < 0.05) , except that no effects on C. sclerophylla were observed in the low concentration treatment. Extracts at the highest concentration reduced the root activity of C. sclerophylla by 41. 1% -62. 4% (P <0.05). There were obvious different effects among the treatments with different extract sources. Seed germination percentage was the lowest in root extract treatments. There was no obvious difference for shoot height of C. sclerophylla in different treatments(P >0.05) , while there was significant difference for C. glauca, its shoot height was higher in the leaf, root, and litter extracts treatments than in the soil extracts treatments. P. edulis possesses allelopathic potential that could possibly facilitate its invasion and monoculture formation, and does harm to the surrounding forest environment.

In June 2011-June 2012, a fertilization experiment was conducted in a typical Castanea mollissima stand in Lin' an of Zhejiang Province, East China to study the effects of inorganic and organic fertilization on the soil CO2 flux and the relationships between the soil CO2 flux and environmental factors. Four treatments were installed, i. e., no fertilization (CK), inorganic fertilization (IF), organic fertilization (OF), half organic plus half inorganic fertilization (OIF). The soil CO2 emission rate was determined by the method of static closed chamber/GC technique, and the soil temperature, soil moisture content, and soil water-soluble organic carbon (WSOC) concentration were determined by routine methods. The soil CO2 emission exhibited a strong seasonal pattern, with the highest rate in July or August and the lowest rate in February. The annual accumulative soil CO2 emission in CK was 27.7 t CO2 x hm(-2) x a(-1), and that in treatments IF, OF, and OIF was 29.5%, 47.0%, and 50.7% higher than the CK, respectively. The soil WSOC concentration in treatment IF (105.1 mg kg(-1)) was significantly higher than that in CK (76.6 mg x kg(-1)), but was obviously lower than that in treatments OF (133.0 mg x kg(-1)) and OIF (121.2 mg x kg(-1)). The temperature sensitivity of respiration (Q10) in treatments CK, IF, OF, and OIF was 1.47, 1.75, 1.49, and 1.57, respectively. The soil CO2 emission rate had significant positive correlations with the soil temperature at the depth of 5 cm and the soil WSOC concentration, but no significant correlation with soil moisture content. The increase of the soil WSOC concentration caused by fertilization was probably one of the reasons for the increase of soil CO2 emission from the C. mollissima stand.

The PROSAIL canopy radiative transfer model was used to establish leaf area index (LAI) and canopy reflectance lookup-table for Moso bamboo forest. The combination of Landsat Thematic Mapper (TM) image and this model was then used to retrieve LAI. The results demonstrated that the sensitivity of the input parameters in the PROSAIL model decreased in order of LAI >chlorophyll content (C(ab)) > leaf structure parameters (N) > mean leaf angle (ALA) > equivalent water thickness (C(w)) > dry matter content (C(m)). The most sensitive factors LAI and C(ab) were then used to construct the LAI-canopy reflectance lookup-table. The LAI estimates from the PROSAIL model had good agreement with the reference data, with the coefficient of determination (R2) reached 0.90. The root mean square error (RMSE) and relative RMSE were 0.58 and 13.0%, respectively. However, the mean LAI estimate was higher than the observed value.

By using open-path eddy covariance system and meteorological instruments, an observation was conducted on the sensitive heat flux, latent heat flux, net radiation, soil heat flux, air temperature, ground temperature, and precipitation in a intensively managed Lei bamboo forest ecosystem in 2011, with the diurnal and monthly variations of energy flux as well as the distribution pattern of each energy component analyzed, and the Bowen ratio and energy balance closure calculated. The yearly net radiation of the forest ecosystem was 2928. 92 MJ m-2, and the latent heat flux, sensitive heat flux, and soil heat flux were 1384.90, 927.54, and -28.27 MJ m-2, respectively. Both the daily and the monthly variations of the energy components showed a single peak curve. The sensible and latent heat fluxes were 31.7% and 47.3% of the net radiation, respectively, indicating that latent heat flux was the main form of energy loss. The Bowen ratio followed the "U"-shaped pattern, and fluctuated from 0. 285 to 2. 062, suggesting that soil was a heat source. The yearly energy balance closure of the forest ecosystem was 0. 782, and the monthly average was 0.808.

Taking the moso bamboo production areas Lin'an, Anji, and Longquan in Zhejiang Province of East China as study areas, and based on the integration of field survey data and Landsat 5 Thematic Mappr images, five models for estimating the moso bamboo (Phyllostachys heterocycla var. pubescens) forest biomass were constructed by using linear, nonlinear, stepwise regression, multiple regression, and Erf-BP neural network, and the models were evaluated. The models with higher precision were then transferred to the study areas for examining the model's transferability. The results indicated that for the three moso bamboo production areas, Erf-BP neural network model presented the highest precision, followed by stepwise regression and nonlinear models. The Erf-BP neural network model had the best transferability. Model type and independent variables had relatively high effects on the transferability of statistical-based models.

To investigate the effects of the conversion from native shrub forest (NF) to Chinese chestnut plantation (CP) on the soil carbon (C) and nitrogen (N) pools, soil samples were collected from the adjacent NF and CP in Anji County of Zhejiang Province, with their water-soluble organic C (WSOC), microbial biomass C (MBC), readily oxidizable C (ROC), water-soluble organic N (WSON), and microbial biomass N (MBN) determined. The spectral characteristics of soil organic C were also determined by using nuclear magnetic resonance (NMR) technique. After the conversion from NF to CP, the soil alkalyzable N, available phosphorus, and available potassium contents increased significantly, while the soil WSOC, MBC, ROC, WSON, and MBN were in adverse. The soil organic C in both NF and CP was dominated by alkyl C and O-alkyl C, but the proportions of O-alkyl C and carbonyl C in soil organic C decreased while the proportions of alkyl C and aromatic C as well as the alkyl C/O-alkyl C ratio and the aromaticity of soil organic C all increased significantly after the conversion from NF to CP, indicating that this conversion increased the stability of soil organic C pool significantly. In conclusion, the conversion from NF to CP and the intensive management of CP decreased the contents of soil labile C and soil N but increased the stability of soil C pool significantly.

In the present study, we evaluate the relative content of chlorophyll and spectral reflectance variations in the visible light under different intensity of UVB (L-UVB, CK and UVB) of three typical evergreen broadleaf plants in China subtropical area. In different simulated UVB condition, the experiment shows that different tree species have different UVB sensitivity, and chlorophyll content varies greatly with species, and the chlorophyll relative content with the filter UVB w as significantly higher than with enhanced UVB. In the spectral reflectance of the visible part, it is generally higher with enhanced UVB's treatment than with L-UVB treatment; and any treatments present adaptation, species under different stress. After roles of the different UVB intensity, for each tree species the visible part of the spectral reflectance shows difference between green and red mainly. The study results show that the subtropical evergreen broad-leaved species has a strong sensitivity to the UVB, and UVB response of different tree species varies greatly.

Landsat Thematic Mapper (TM) image was used to estimate Moso bamboo forest biomass, and six atmospheric calibration methods (FLAASH model, 6S model, and DOS1-4 models) were adopted to analysis the effects of atmospheric calibration on the remote sensing estimation of Moso bamboo forest biomass. All the six calibration methods could effectively reduce the atmospheric impacts on TM spectral responses. The relationships between NDVI and Moso bamboo forest biomass under the calibration by the six calibration methods were improved. Great differences were observed in the relationships of Moso bamboo forest biomass with NDVI, II, and MI when using the same calibration methods, suggesting that atmospheric calibration should be made for studying the biophysical significance of vegetation indices. The Landsat TM data corrected with DOS3 model had the highest correlation coefficient with Moso bamboo forest biomass, but there were no significant differences in the correlation coefficients after corrected with the six calibration methods, which indicated that atmospheric calibration might be not required if a single TM image was used for biomass estimation with multiple linear regression model.

Acid rain is a worldwide environmental problem. Serious acid rain pollution in subtropical China has constituted a potential threat to the health of the local forest. In the present paper, the changing properties of the chlorophyll concentration and spectral reflectance at the visible wavelengths for the six subtropical broad-leaved tree species leaves under simulated acid rain (SAR) treatment with different pH levels were studied. With the increasing strength of the SAR, the chlorophyll concentrations of the experimental species under pH 2.5 and pH 4.0 treatment were higher than that under pH 5.6; the spectral reflectance at the visible wavelengths for pH 2.5 and pH 4.0 were lower than that for pH 5.6 in general; while there weren't significant differences between pH 2.5 and pH 4.0. After the treatment with different levels of SAR, the differences in spectral reflectance at the visible wavelengths mainly focused around the green peak and red edge on the reflectance curve. The subtropical broad-leaved tree species studied were relatively not sensitive to acid rain stresses; some stronger acid rain may accelerate the growth of the tree species used here to some extent.

Aiming at the deficiencies in the researches about the probability distribution model for mixed forests tree measurement factors, a joint maximum entropy probability density function was put forward, based on the maximum entropy principle. This function had the characteristics of 1) each element of the function was linked to the maximum entropy function, and hence, could integrate the information about the probability distribution of measurement factors of main tree species in mixed forests, 2) the function had a probability expression of double-weight, being possible to reflect the characteristics of the complex structure of mixed forests, and accurately and completely reflect the probability distribution of tree measurement factors of mixed forests based on the fully use of the information about the probability distribution of measurement factors of main tree species in mixed forests, and 3) the joint maximum entropy probability density function was succinct in structure and excellent in performance. The model was applied and tested in two sampling plots in Tianmu Mountain Nature Reserve. The fitting precision (R2 = 0.9655) and testing accuracy (R2 = 0.9772) were both high, suggesting that this model could be used as a probability distribution model for mixed forests tree measurement factors, and provided a feasible method to fully understand the comprehensive structure of mixed forests.

Forest fire is an important disturbance factor of natural ecosystem, which can release great amount of greenhouse gases. With the persistent global warming, forest fire tends to happen more frequently. Based on the statistical data of forest fires and the biomass data of dominant forest types in Zhejiang Province in 1991-2006, the annual greenhouse gases emission from forest fires in the Province was estimated by using emission factors and emission ratio. The results showed that the annual emissions of CO2, CO, CH4, and non-methane hydrocarbon (NMHC) from forest fires were 127930, 7672.8, 3098.7, and 1475.5 t, and the amounts of annually consumed biomass and carbon were 86148.1 and 38776.7 t, respectively, suggesting that forest fire had definite effects on the regional carbon budget.

The litters of seven tree species representing the dominant plant species in three main successional stages in subtropical China, i.e., Pinus massoniana in early successional forests, Schima superba and Cinnamanun camphora in transitional forests, and Castanopsis eyeri, Cyclobalanopsis gracilis, Cyclobalanopsis glauca, and Michelia chapensis in late successional forests, were collected, and their decomposition rates were measured with litterbags. The results showed that M. chapensls and C. gracilis had the highest litter decomposition rate (k = 1.12 and 0.89, respectively), followed by C. camphora and S. superba (k = 0.61 and 0.55, respectively), and P. massoniana (k = 0.51), indicating that there was a trend of litter decomposition rate being increased with succession stage. Litter decomposition rate had significant correlations with the litter' s initial P, N, and lignin contents, lignin/N ratio (P < 0.01), and C/N ratio (P < 0.05), suggesting that the initial P, N, and lignin contents and lignin/N ratio of leaf litter could be the good indictors of litter decomposition rate.