ABSTRACT
To reveal the community succession rule of natural secondary forest, we investigated basic characteristics and coordinates of each tree (DBH≥1 cm) within a plot (100 m×100 m) using the adjacent grid method and examined the distribution pattern and spatial associations of dead woods in a natural spruce-fir secondary forest in Jingouling Forest Farm, Wangqing Forestry Bureau, Jilin Province, China. The results showed that the diameter class distribution of dead woods showed the pattern of left single-peak curve, while the logs showed the pattern of multi-peak curve. The relationship between the abundance of dead woods and the standing individuals of a particular species was inconsistent. There was a significant negative exponential relationship between the number of dead woods and mixing degree of trees. The distribution of dead woods was concentrated at the 0-8 m scale. With the increases of scale, it gradually changed to random or uniform, with the random distribution being dominant. The aggregation distribution of dead woods with middle (10 cm≤DBHï¼20 cm) and small (1 cm≤DBHï¼10 cm) DBH was the main reason for the aggregation distribution of dead woods at small scale below 8 m. The spatial associations between dead woods and stan-ding trees at different diameter classes were significantly different. The relationship between dead woods and saplings (1 cm≤DBHï¼5 cm) was closely correlated. The dead woods with large DBH and saplings showed a significant positive association at 2-25 m scale. There was no spatial association between dead woods and small trees (5 cm≤DBHï¼15 cm). At the 0-3 m scale, there was a positive association between the middle trees (15 cm≤DBHï¼25 cm) and dead woods of small and middle DBH. At the 9, 11-14 and 15, 42-45 m scales, dead woods of small and middle DBH were significantly negatively associated with large trees (DBH≥25 cm). In conclusion, biological traits, diameter class distribution, and spatial distribution affected the abundance and diameter class distribution of dead woods. The species with low mixing degree tended to have more dead woods. The diameter and scale would affect the spatial distribution of dead woods. The spatial correlation between dead woods and standing trees varied across diameter classes and scales.
Subject(s)
Forests , Picea , China , Humans , Trees , WoodABSTRACT
To accurately assess carbon storage and its spatial distribution in natural secondary forest at the regional scale, we constructed seven expansion models by modifying the geographically weighted regression (GWR) in aspects of spatial dimension, parameter heterogeneity and residual spatial autocorrelation, based on data collected from 165 bureau level permanent plots in Langxi Forest Farm of Wangqing Forestry Bureau in Jilin Province. Stand factor, topography factor, and soil factor were selected as the influencing factors. The expansion models included geographically and altitudinal weighted regression (GAWR), semiparametric geographically weighted regression (SGWR), semiparametric geographically and altitudinal weighted regression (SGAWR), geographically weighted regression Kriging (GWRK), geographically and altitudinal weighted regression Kriging (GAWRK), semiparametric geographically weighted regression Kriging (SGWRK), and semiparametric geographically and altitudinal weighted regression Kriging (SGAWRK). Coefficient of determination (R2), mean square error (MSE) and Akaike's Information Criterion (AIC) were used to evaluate the fitness of these models. Finally, the spatial distribution diagram of forest carbon storage was drawn with the fitting results of the optimal regression model, and the distribution pattern of forest carbon storage in the research area was analyzed. The stand factor and topographic factor had strong influence on carbon storage of natural secondary forests, among which the average diameter at breast height (DBH) of stands was the dominant variable. There was positive correlation between stand factor and topographic factor. SGWR and SGAWR model could reduce the spatial autocorrelation of the GWR model residual. The geographically regression expansion model could improve the fitting effect of GWR model. Among them, the SGWRK model had the highest R2 and the lowest MSE and AIC. The method with altitude as the spatial weight did not effectively improve the fitting effect of the model. The total forest carbon storage of Langxi Forest Farm was 205×104 t, and the carbon density ranged from 8.56 to 145.74 t·hm-2, with a mean value of 57.98 t·hm-2. Overall, the distribution pattern of carbon storage was high in the northwest and low in the southeast, while high in the edge and low in the interior. By improving the parameter heterogeneity and residual spatial autocorrelation in the GWR model, we can accurately assess the spatial relationship between forest carbon storage and relevant variables in the study area, and improve the estimation accuracy of the forest carbon storage and its spatial distribution at the regional scale.
Subject(s)
Carbon , Spatial Regression , Carbon/analysis , China , Forestry , Forests , Soil , Spatial AnalysisABSTRACT
Establishing monoculture of native broadleaved tree species and mixed coniferous broadleaved plantations is the tendency for forest management in subtropical China. The variations of structure and function of soil bacterial community in monoculture and mixed tree plantations are still not clear. We examined soil bacterial community structure and function under different soil layers (0-20, 20-40 and 40-60 cm) in three planted forests, including broadleaved Castanopsis hystrix, coniferous Pinus massoniana and their mixed plantation, in south subtropical China, using 16S rRNA gene high-throughput sequencing and PICRUSt prediction. The results showed that soil bacterial community structure of mixed plantation and P. massoniana plantation were similar but being significant different from that in C. hystrix plantation. The diversity, biological pathways metabolic function, and nitrogen cycling function of soil bacterial community in C. hystrix plantation were lower than those in P. massoniana plantation and mixed plantation. Soil total nitrogen, nitrate nitrogen and C/N were the main factors driving the variations of soil bacterial community structure and function among different forest types. Our results suggested that the mixed plantation of C. hystrix and P. massoniana is better than C. hystrix plantation in this area in terms of soil bacterial community structure and function.
