Modeling height-diameter relationship for artificial monoculture Metasequoia glyptostroboides in sub-tropic coastal megacity Shanghai,China

Tree height is a key variable in forest monitoring studies and for forest management. However, tree height measurement is time consuming, and the recommended procedure is to use estimates from tree height (H) - diameter at breast height (DBH) models. Increasingly, H-DBH models are being developed for urban forests, providing tools to forest management and ecosystem services estimation. Here, we compared model forms and approaches for predicting H as a function of DBH and additional stand level covariates variables. Four model forms were evaluated: (i) basic models (which only used DBH as predictor variable); (ii) generalized models (which used DBH and other predictor variables based on the best basic model); (iii) a mixed-effects model based on the best basic model; and (iv) a mixed-effects model based on the generalized model. Several sampling designs aimed at minimizing height measurement were tested in terms of accuracy and applicability. Taking predicted accuracy and investigation cost into account, we recommend generalized non-linear mixed-effects model (NLME) when there were two or less tree height measurements taken in a given stand. The basic NLME model could be calibrated when there were 3 or more tree height measurements, depending on the required level of accuracy and investigation cost. Additionally, we first reported that soil pH as a covariate variable in H-DBH model and our generalized NLME model implied that the difference in the H-DBH relationship caused by pH varies among different stands. This finding may be attributable to differing biological properties of the similar alkaline tolerance species.     

扬州市稻田高效种养模式应用现状及发展对策

近年来,扬州市根据国家农业供给侧结构性调整要求,充分利用自然资源禀赋,开展了多种形式稻田种养模式的示范与推广。本文阐述了扬州市稻鸭共作、稻虾共作以及稻田改作荷藕-虾共作等高效种养模式的应用现状,以单纯种稻为对照,比较了各种模式的生产效益;分析了稻田高效种养模式示范推广过程中存在的主要问题,并提出了促进稻田高效种养模式可持续发展的若干对策。     

Cohort‐specific variation in juvenile coho salmon habitat use

In this study, we examined summer and fall freshwater rearing habitat use by juvenile coho salmon (Oncorhynchus kisutch) in the quickly urbanising Big Lake drainage in south‐central Alaska. Habitat use was assessed by regressing fish count data against habitat survey information across thirty study sites using generalised linear mixed models. Habitat associations were examined by age‐0 and age‐1+ cohorts separately, providing an opportunity to compare habitat use across different juvenile coho salmon life stages during freshwater rearing. Regression results indicated that the age‐0 cohorts were strongly associated with shallow, wide stream reaches with in‐stream vegetation, whereas age‐1+ cohorts were associated with deeper stream reaches. Furthermore, associations between fork length and habitat characteristics suggest cohort‐specific habitat use patterns are distinct from those attributable to fish size. Habitat use information generated from this study is being used to guide optimal fish passage restoration planning in the Big Lake drainage. Evidence for habitat use partitioning by age cohort during freshwater juvenile rearing indicates that pooling age cohorts into a single “juvenile” stage for the purposes of watershed management may mask important habitat use dynamics.     

A stochastic surplus production model in continuous time

Surplus production modelling has a long history as a method for managing data‐limited fish stocks. Recent advancements have cast surplus production models as state‐space models that separate random variability of stock dynamics from error in observed indices of biomass. We present a stochastic surplus production model in continuous time (SPiCT), which in addition to stock dynamics also models the dynamics of the fisheries. This enables error in the catch process to be reflected in the uncertainty of estimated model parameters and management quantities. Benefits of the continuous‐time state‐space model formulation include the ability to provide estimates of exploitable biomass and fishing mortality at any point in time from data sampled at arbitrary and possibly irregular intervals. We show in a simulation that the ability to analyse subannual data can increase the effective sample size and improve estimation of reference points relative to discrete‐time analysis of aggregated annual data. Finally, subannual data from five North Sea stocks are analysed with particular focus on using residual analysis to diagnose model insufficiencies and identify necessary model extensions such as robust estimation and incorporation of seasonality. We argue that including all known sources of uncertainty, propagation of that uncertainty to reference points and checking of model assumptions using residuals are critical prerequisites to rigorous fish stock management based on surplus production models.     

Stability analysis of seven agronomic traits for soybean [(Glycine max (L.) Merr.] Tokachi nagaha and its derived cultivars using the AMMI model

The stabilities of seven agronomic traits were analyzed and the general stabilities of soybean [Glycine max (L.) Merr.] accessions were evaluated based on the additive main effects and multiplicative interactions (AMMI) model using the founder parent Tokachi nagaha and 137 of its derived cultivars as materials. The objective was to provide a theoretical basis for effectively using germplasm in soybean breeding and production. Analysis of variance (ANOVA) showed that genotype, environment, and genotype by environment interactions were significantly different for each trait. The first three interaction principal components axes (IPCA) were highly significant, accounting for 61.28–70.00% of the total variation. The stability differed for the different traits. 50 cultivars with high general stabilities were identified. The general stability of Tokachi nagaha was moderate, as the stability coefficients (D_i) of its seven traits were relatively high; this must be considered by breeders using this cultivar as a breeding parent. There were significant positive correlations between the phenotypic values and their own D_i values for number of branches per plant, number of pods per plant, number of seeds per plant, and seed weight per plant. This would lead to the expectation that the phenotypic stability would be lower when a cultivar had more branches, pods, seeds, and high per plant yields. Thus, it appears difficult to breed cultivars that simultaneously have high yields and high stability.     

基于ARIMA模型的我国大豆单产预测分析

在我国大豆单产光合潜力和"农业生态区划"(AEZ)潜力基础上,运用ARIMA(自回归单整移动平均)模型预测了2020年前我国大豆单产。结果表明:我国大豆单产最大潜力为3 400 kg·hm~(-2),而2017、2018、2019和2020年单产将分别为1 899,1 926,1 954和1 982 kg·hm~(-2),分别是最大潜力的55.85%、56.65%、57.47%和58.29%。这意味着:未来提高我国大豆单产尚有较大空间,应保持高产耕地生产力与改良中低产田土并重。研究结果旨在为我国大豆生产提供决策参考信息。     

斑节对虾Toll9受体基因免疫功能的研究与表达分析

Toll受体蛋白(Toll receptors)是一类重要的模式识别受体,在无脊椎动物先天性免疫系统中发挥重要作用。文章对斑节对虾(Penaeus monodon)新型Toll9受体基因(Pm Toll9)进行了研究:以人源胚胎肾细胞(HEK293T)成功构建体外细胞免疫模型,通过免疫印迹方法证实Pm Toll9重组真核蛋白可在HEK293T中成功表达。双荧光素酶报告系统检测发现在200 ng转染浓度处Pm Toll9对NF-κB报告基因的激活效果显著。q RT-PCR数据证明PmToll9成功激活HEK293T细胞Toll-like receptor(TLR)信号通路,促进通路下游髓样分化因子(My D88)、肿瘤坏死因子(TNF-α)和白介素(IL-10)的上调表达,同时酶联免疫吸附测定结果证明Pm Toll9可促进TNF-α蛋白表达水平显著上调。斑节对虾体内细菌刺激实验结果显示无乳链球菌(Streptococcus agalactiae)可激活Pm Toll9在肝胰腺、肠、淋巴和鳃中的表达,哈维氏弧菌(Vibrio harveyi)可显著抑制Pm Toll9在肝胰腺中的表达。提示无乳链球菌可通过Pm Toll9激活Toll信号通路,引起机体免疫防御反应,而哈维氏弧菌对此过程具有一定的抑制作用。     

基于YOLO v3与图结构模型的群养猪只头尾辨别方法

在利用视频监控技术对群养猪只进行自动行为监测时,对猪只准确定位并辨别其头尾位置对提高监测水平至关重要,基于此提出一种基于YOLO v3(You only look once v3)模型与图结构模型(Pictorial structure models)的猪只头尾辨别方法。首先,利用基于深度卷积神经网络的YOLO v3目标检测模型,训练猪只整体及其头部和尾部3类目标的检测器,从而在输入图像中获得猪只整体及头尾部所有的检测结果;然后,引入图结构模型,描述猪只的头尾结构特征,对每个猪只整体检测矩形框内的头尾部位组合计算匹配得分,选择最优的部位组合方式;对部分部位漏检的情况,采取阈值分割与前景椭圆拟合的方法,根据椭圆长轴推理出缺失部位。在实际猪场环境下,通过俯拍获得猪舍监控视频,建立了图像数据集,并进行了检测实验。实验结果表明,与直接利用YOLO v3模型相比,本文方法对头尾定位的精确率和召回率均有一定提高。本文方法对猪只头尾辨别精确率达到96.22%,与其他方法相比具有明显优势。