我国林火发生预测模型研究进展

通过文献回顾,总结了国内林火发生预测模型的研究现状,并从林火发生驱动因子、林火发生概率预测模型、林火发生频次预测模型和模型检验方法等方面进行归纳分析。得出以下结论: 1)气象、地形、植被、可燃物、人类活动等因素是影响林火发生及模型预测精度的主要驱动因子;2)林火发生概率模型中,地理加权逻辑斯蒂回归模型考虑了变量之间的空间相关性,Gompit回归模型适宜非对称结构的林火数据,随机森林模型不需要多重共线性检验,在避免过度拟合的同时提高了预测精度,是林火发生概率预测模型的优选方法之一;3)林火发生频次模型中,负二项回归模型更适合对过度离散数据进行模拟,零膨胀模型和栅栏模型可以处理林火数据中包含大量零值的问题;4)ROC检验、AIC检验、似然比检验和Wald检验方法是林火概率和频次模型的常用检验方法。林火发生预测模型研究仍是我国当前林火管理工作的重点,预测模型的选择需要依据不同地区林火数据特点。此外,构建林火预测模型时需要考虑更多的影响因素,以提高模型预测精度;未来,需要进一步探索其他数学模型在林火发生预测中的应用,不断提高林火发生预测模型的准确度。     

基于多元回归树的公益林群落结构解析

为揭示不同生境类型下公益林群落物种多样性及优势种种间关系特征, 以临安市公益林125个固定监测样地为研究对象, 利用多元回归树(MRT)进行群落分类, 以物种多样性指数和种间联结系数为指标, 对不同群落类型的结构特征进行探索。结果表明: 临安市公益林125个典型样地可划分为5个类型; 类型I、II、III与类型V的多样性指数之间均无显著差异, 但类型III的多样性指数均最高, 类型IV的物种多样性指数均显著低于其它类型, 海拔是影响群落多样性水平的主要因子。种间联结初步分析显示, 研究区群落中稳定性最高的层片是乔木层, 且毛竹入侵极可能是影响5个类型植物群落稳定性的关键因素。研究结果可为临安市公益林分类经营管理提供理论依据, 同时为区域公益林群落数量结构研究奠定基础。     

Application of frequency ratio and logistic regression models for assessing physical wetland vulnerability in Punarbhaba river basin of Indo-Bangladesh

Growingly scarce ecologically viable flood plain wetland of the Punarbhaba river basin is further endangered due to flow modification through Komardanga dam. This work intends to discover physical vulnerability of the wetlands in Punarbhaba river basin of Indo-Bangladesh considering seven conditioning parameters, e.g., water presence frequency (WPF) map, flood inundation map, frequency of pixel being non-permanent, agriculture presence frequency (APF) map, fragmentation of wetland, normalized differentiation built up index (NDBI), and wetland changes (WC). Frequency Ratio and Logistic Regression models have been used for deriving the vulnerability of wetland for both pre (1988–1992) and post dam (1993–2016) periods. From computed FR models it is exhibited that out of the total wetland area (194.81 km²), 5.88% and 2.92% area are high and very highly vulnerable in pre-dam period but such vulnerable area is increased to 33.45% and 23.10% in post-dam state (total wetland: 126.11 km²). LR models also state that in pre-dam period, high and very high vulnerable wetland area were 5.02% and 3.82% (total wetland: 194.79 km²) and it is enhanced to 28.94% and 24.49% in post-dam state (total wetland: 126.11 km²). Extensions of agricultural land, squeezing of active flood plain, lowering flood frequency are dominant determinants for growing wetland vulnerability.     

A two-stage model for multiple time series data of counts

We propose a two-stage model for time series data of counts from multiple locations. This method fits first-stage model(s) using the technique of iteratively weighted filtered least squares (IWFLS) to obtain location-specific intercepts and slopes, with possible lagged effects via polynomial distributed lag modeling. These slopes and/or intercepts are then taken to a second-stage mixed-effects meta-regression model in order to stabilize results from various locations. The representation of the models from the stages into a combined mixed-effects model, issues of inference and choices of the parameters in modeling the lag structure are discussed. We illustrate this proposed model via detailed analysis on the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.     

A quantitative structure-activity relationship study for structurally diverse HIV-1 protease inhibitors: contribution of conformational flexibility to inhibitory activity

In this study, we investigated by linear regression model the SAR data of the 15 HIV-1 protease inhibitors possessing structurally diverse scaffolds. First, a regression model was developed only using the enzyme-inhibitor interaction energy as a term of the model, but did not provide a good correlation with the inhibitory activity (R² = 0.580 and Q² = 0.500). Then, we focused on the conformational flexibility of the inhibitors which may represent the diversity of the inhibitors, and added two conformational parameters into the model, respectively: the number of rotatable bonds of ligands (ΔSrot) and the distortion energy of ligands (ΔElig). The regression model by adding ΔElig successfully improved the quality of the model (R² = 0.771 and Q² = 0.713) while the model with ΔSrot was unsuccessful. The prediction for a training inhibitor by the ΔElig model also showed good agreement with experimental activity. These results suggest that the conformational flexibility of HIV-1 protease inhibitors directly contributes to the enzyme inhibition.     

Testing for size and allometric differences in fossil hominin body mass estimation

Body size reconstructions of fossil hominins allow us to infer many things about their evolution and lifestyle, including diet, metabolic requirements, locomotion, and brain/body size relationships. The importance of these implications compels anthropologists to attempt body mass estimation from fragmentary fossil hominin specimens. Most calculations require a known “calibration” sample usually composed of modern humans or other extant apes. Caution must be taken in these analyses, as estimates are sensitive to overall size and allometric differences between the fossil hominin and the reference sample. Am J Phys Anthropol 151:215–229, 2013. © 2013 Wiley Periodicals, Inc.     

人参药材中人参皂苷与生态因子的相关性及人参生态区划

为了扩大人参(Panax ginseng)栽培面积, 解决人参资源日益短缺的问题, 研究了人参皂苷与生态因子之间的相关性。利用超高效液相(UPLC)色谱法, 测定了辽宁、吉林和黑龙江三省不同产区人参样品中3种人参皂苷(Rg1、Re和Rb1)的含量, 并基于“中药材产地适宜性分析地理信息系统”(TCMGIS)平台, 获得采样区域10个生态因子(包括活动积温、年平均气温、海拔、相对湿度、年日照时数、年降水量、7月最高气温、7月平均气温、1月最低气温和1月平均气温等)数据; 利用因子分析法对16个人参基地进行因子得分评价, 得分最高的是吉林和辽宁的人参基地, 故将吉林和辽宁的人参基地作为人参生态适宜性分析的最佳区域; 通过偏最小二乘回归法建立3种人参皂苷成分与上述10个生态因子间的回归方程并获取其相应的权重, 结果发现多个温度因子与人参皂苷含量呈强负相关关系, 说明热量因子对人参皂苷活性成分的累积起主要作用, 而水分因子、地理因子和光照因子与人参皂苷含量呈弱相关关系; 以因子得分最高的吉林和辽宁人参基地为基点区域, 分别对3种人参皂苷进行单成分生态适宜性区划以及综合区划, 得知3种人参皂苷成分积累的最佳区域主要集中在长白山脉, 而燕山山脉和太行山脉只有少量分布区域。     

A quantile‐slicing approach for sufficient dimension reduction with censored responses

Sufficient dimension reduction (SDR) that effectively reduces the predictor dimension in regression has been popular in high‐dimensional data analysis. Under the presence of censoring, however, most existing SDR methods suffer. In this article, we propose a new algorithm to perform SDR with censored responses based on the quantile‐slicing scheme recently proposed by Kim et al. First, we estimate the conditional quantile function of the true survival time via the censored kernel quantile regression (Shin et al.) and then slice the data based on the estimated censored regression quantiles instead of the responses. Both simulated and real data analysis demonstrate promising performance of the proposed method.     

基于GWR模型的伊河流域土壤有机碳空间分布特征及影响因素分析

土壤有机碳作为陆地碳库主体,其分布特征及与驱动因素的空间关系对土壤碳周转过程有重大影响。通过野外调查、采样和室内分析,基于地理加权回归（GWR）模型结合9个环境和土壤变量,建模分析伊河流域土壤有机碳空间分布状况,以及影响其分布的主要因素。研究发现,流域表层土壤有机碳在3.37-38.34 g/kg之间,上、中、下游有机碳分布存在空间差异,其中上游差异最大,下游差异最小。相关分析表明,有机碳与土壤理化性质相关性显著,与年平均气温以外的环境因子相关性不显著。GWR模型较好地预测了伊河流域土壤有机碳空间分布,局部决定系数在0.49-0.64之间,自下游到上游,决定系数逐步升高,对上游的预测精度最高。分析发现,在海拔较高的中上游区域,土壤有机碳含量主要受立地环境、成土母质和地表覆盖的影响;在中上游低山丘陵区,人类活动和环境因素共同影响了土壤有机碳含量;在中下游平原区农业活动和化肥投入是造成土壤有机碳含量较高的主要因素。研究揭示了各因素对有机碳影响的空间分异特征,可为伊河流域土壤生态系统的合理发展和管理提供依据。