[Stand biomass model for Pinus koraiensis plantation based on different additive methods in Heilongjiang Province, China]. / åŸºäºŽä¸åŒå¯åŠ æ€§æ–¹æ³•çš„é»‘é¾™æ±Ÿçœçº¢æ¾äººå·¥æž—æž—åˆ†ç”Ÿç‰©é‡æ¨¡åž‹.

Large-scale estimation of forest biomass has received much attention. Constructing a stand-level biomass model is a method for estimating tree layer biomass. In this study, we constructed stand biomass models of Korean pine plantations based on aggregation method 1, aggregation method 2, adjustment method, and disaggregation method. The prediction precision of four additive methods was compared and analyzed to provide theoretical basis for biomass prediction of Korean pine plantations in Heilongjiang Province. Weighted functions were used to eliminate the heteroscedasticity of each model, with the leave-one-out cross validation (LOOCV) as the validation method. The results showed that the overall prediction ability of the adjustment method was slightly better than other methods. The specific prediction precision was ranked as adjustment method > aggregation method 1 > aggregation method 2 > disaggregation method. The prediction precision of four additive methods was not consistent when considering their prediction ability of different stand basal areas. When the stand basal area of Korean pine plantations was distributed in the interval of 0-10 or 50-60 m2·hm-2, the parameter estimation values of disaggregation method performed better. When the stand basal area was distributed in other intervals, the parameter estimation values of adjustment method was better.

Complete mitochondrial genome sequence of the blue sheep, Pseudois nayaur szechuanensis (Cetartiodactyla: Caprinae).

The blue sheep (Pseudois nayaur szechuanensis) belongs to the subfamily Caprinae, which distributes in Sichuan, Gansu, Qinghai, southeastern Xinjiang, northern Yunnan and Ningxia-Inner Mongolia border, China. In this study, the complete mitochondrial genome of P. n. szechuanensis was sequenced. The mitogenome was 16,738 bp in length, consisting of 13 protein-coding genes, 22 transfer RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes, and a non-coding control region. As in other mammals, most mitochondrial genes are encoded on the heavy strand, except for ND6 and eight tRNA genes which are encoded on the light strand. The overall base composition of the P. n. szechuanensis is 33.5% A, 26.4% T, 27.0% C, and 13.2% G. The alignment of the Pseudois species control regions exhibited high genetic variability and rich A + T content. The complete mitogenome of P. n. szechuanensis can provide an important data for the studies on phylogenetic relationship and population genetics to further explore the taxonomic status of this species.

Complete mitochondrial genome of a new subspecies of the blue sheep, Pseudois nayaur (Cetartiodactyla: Caprinae) from Helan Mountain in China.

The population of blue sheep, Pseudois nayaur, from Helan Mountain in China is considered as a new subspecies. We first determined and annotated its complete mitochondrial genome. The mitogenome is 16,795 bp in length, consisting of 13 protein-coding genes, 22 transfer RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes and a control region. As in other mammals, most mitochondrial genes are encoded on the heavy strand, except for ND6 and eight tRNA genes, which are encoded on the light strand. Its overall base composition is A: 33.2%, T: 26.6%, C: 26.8% and G: 13.3%. The complete mitogenome of the new subspecies of P. nayaur could provide an important data to further explore the taxonomic status of the subspecies.

The complete mitochondrial genome sequence of the blue sheep, Pseudois nayaur nayaur (Cetartiodactyla: Caprinae).

The blue sheep (Pseudois nayaur nayaur) belongs to the subfamily Caprinae, and is distributed in the Qinghai-Tibet Plateau and peripheral mountains of China. In this study, the complete mitochondrial genome of P. n. nayaur was sequenced. It was determined to be of 16,700 bases. The nucleotide sequence data of 12 heavy-strand protein-coding genes of P. n. nayaur and other 29 caprine species were used for phylogenetic analysis. Phylogenetic trees were reconstructed by Bayesian and maximum likelihood methods, and it suggested that P. n. nayaur was the sister group of P. schaeferi and P. nayaur, and also indicated a close relationship of genus Pseudois with genus Capra.

[Primary branch size of Pinus koraiensis plantation: a prediction based on linear mixed effect model].

By using the branch analysis data of 955 standard branches from 60 sampled trees in 12 sampling plots of Pinus koraiensis plantation in Mengjiagang Forest Farm in Heilongjiang Province of Northeast China, and based on the linear mixed-effect model theory and methods, the models for predicting branch variables, including primary branch diameter, length, and angle, were developed. Considering tree effect, the MIXED module of SAS software was used to fit the prediction models. The results indicated that the fitting precision of the models could be improved by choosing appropriate random-effect parameters and variance-covariance structure. Then, the correlation structures including complex symmetry structure (CS), first-order autoregressive structure [AR(1)], and first-order autoregressive and moving average structure [ARMA(1,1)] were added to the optimal branch size mixed-effect model. The AR(1) improved the fitting precision of branch diameter and length mixed-effect model significantly, but all the three structures didn't improve the precision of branch angle mixed-effect model. In order to describe the heteroscedasticity during building mixed-effect model, the CF1 and CF2 functions were added to the branch mixed-effect model. CF1 function improved the fitting effect of branch angle mixed model significantly, whereas CF2 function improved the fitting effect of branch diameter and length mixed model significantly. Model validation confirmed that the mixed-effect model could improve the precision of prediction, as compare to the traditional regression model for the branch size prediction of Pinus koraiensis plantation.

[Simulation of Larix gmelinii tree volume growth based on random effect].

Based on the stem analysis data of 80 sample trees in dahurian larch (Larix gmelinii) plantations of Daqingchuan Forest Farm, Dailing Forest Bureau in Heilongjiang Province and the Logistic growth model, the NLME procedure of S-PLUS software was adopted to fit the nonlinear tree volume growth models, with consideration of individual tree effect and plot effect, and the evaluation statistics such as AIC, BIC, Log Likelihood, and likelihood ratio test were used to compare the prediction precisions of the models. The results showed that the random effect models with parameters b1, b2, and b3 (representing the random parameters for progressive, scale, and shape in Logistic model, respectively) had the best performance when considering individual tree effect, while the models with parameter b1 had the best performance when considering plot effect. The models considering both individual tree effect and plot effect provided better model fitting than the basic model (Logistic growth model), and the models considering individual tree effect showed more precision, as compared with those considering plot effect. The model validation indicated that random effect models not only showed the mean variation trend of individual tree volume growth, but also showed the differences among the individuals. In addition, the prediction precision of the models could be further improved through the calibration of random parameters.