当代森林动态的计算机模型述评

一、引言森林动态这一广义语,包括森林生态系统随时间的任何变化。要想经营好森林,使其为人类创造出最大的财富,必须深刻认识森林的动态规律。在过去的一个多世纪里,森林生态学家们对森林动态规律进行了广泛而深入的研究,现已形成各种动态学说。随着科学的发展以及森林经营水平的提高,人们逐渐用各种方     

广义森林生态效益货币量的空间模型分析

从广义森林生态效益计量概念出发,提出了广义森林生态效益货币量和森林生态环境空间的定义。根据广义森林生态环境的空间模型分析概念和实现空间模型分析的3个基本条件,采用Arcview和Autocad图形向GIS空间数据转换的方法对1986、1949和1896年黑龙江省森林资源空间图形资料和反推的小班资源数据库,通过环境图象叠置分析获得森林资源与环境的空间图象,建立广义森林生态效益经济计量模型,由此实现广义森林生态效益的GIS空间分析。结果表明：森林生态效益货币量的分布近似呈正态分布,各森林生态效益经济总量各占一定比重。利用GIS空间分析功能作出的黑龙江省森林生态效益主产区的空间分布图显示,黑龙江省森林生态效益的主产区主要分布在镜泊湖、兴凯湖、汤旺河、嫩江等江河的源头。通过分析黑龙江省森林生态效益货币总量的动态,得出1986年的黑龙江省森林生态效益比1949年下降38％,比原生状态的1896年下降59％。森林生态效益的下降与森林资源的数量和质量的下降呈正相关,森林生态效益的变化总是要滞后于森林资源的变化。     

Individual risk prediction: Comparing random forests with Cox proportional-hazards model by a simulation study

With big data becoming widely available in healthcare, machine learning algorithms such as random forest (RF) that ignores time-to-event information and random survival forest (RSF) that handles right-censored data are used for individual risk prediction alternatively to the Cox proportional hazards (Cox-PH) model. We aimed to systematically compare RF and RSF with Cox-PH. RSF with three split criteria [log-rank (RSF-LR), log-rank score (RSF-LRS), maximally selected rank statistics (RSF-MSR)]; RF, Cox-PH, and Cox-PH with splines (Cox-S) were evaluated through a simulation study based on real data. One hundred eighty scenarios were investigated assuming different associations between the predictors and the outcome (linear/linear and interactions/nonlinear/nonlinear and interactions), training sample sizes (500/1000/5000), censoring rates (50%/75%/93%), hazard functions (increasing/decreasing/constant), and number of predictors (seven, 15 including noise variables). Methods' performance was evaluated with time-dependent area under curve and integrated Brier score. In all scenarios, RF had the worst performance. In scenarios with a low number of events (⩽70), Cox-PH was at least noninferior to RSF, whereas under linearity assumption it outperformed RSF. Under the presence of interactions, RSF performed better than Cox-PH as the number of events increased whereas Cox-S reached at least similar performance with RSF under nonlinear effects. RSF-LRS performed slightly worse than RSF-LR and RSF-MSR when including noise variables and interaction effects. When applied to real data, models incorporating survival time performed better. Although RSF algorithms are a promising alternative to conventional Cox-PH as data complexity increases, they require a higher number of events for training. In time-to-event analysis, algorithms that consider survival time should be used.     

PROSPECT5耦合4SAIL模型的亚热带典型森林冠层反射率时间序列模拟

冠层反射率在森林植被类型精确解译、森林碳同化关键参数如叶面积指数(LAI)、叶绿素等遥感反演等方面具有重要意义.本研究以亚热带毛竹林、雷竹林和常绿落叶阔叶混交林3种典型森林类型为研究对象,通过耦合PROSPECT5和4SAIL模型模拟其冠层反射率时间序列.首先,对PROSPECT5和4SAIL模型参数进行敏感性分析,探讨模型参数对冠层反射率的影响;其次,利用实测反射率对不敏感参数进行优化,并确定其参数值;最后,耦合PROSPECT5和4SAIL模型模拟3种亚热带森林冠层反射率,并与MODIS反射率进行对比.结果表明:LAI对第1、2、3、5、7波段最敏感,各波段的总敏感指数分别为0.80、0.83、0.94、0.66、0.47;叶绿素含量对第4波段最敏感,总敏感指数为0.59;叶片含水量对第6波段的敏感性最大,总敏感性指数为0.54;叶子结构参数、类胡萝卜素、热点参数、干物质含量和土壤干湿比等参数对各个波段都不敏感或敏感性较小.优化后的PROSPECT5和4SAIL模型模拟得到的冠层反射率能够真实反映3种典型森林的季节性变化规律,通过与MODIS反射率对比分析发现,模拟冠层反射率和MODIS反射率之间具有较高的决定系数,分别为0.86、0.90、0.93,均方根误差(RMSE)也较小,分别为0.09、0.07、0.05,且模拟反射率能在一定程度上解决MODIS反射率数据冬季易受雨雪、混合像元影响等问题.     

省域森林生态安全评价——基于5省的经验数据

生态安全是国家安全体系的重要组成部分。面对严峻的生态环境形势,以及大气污染、水污染、土壤污染等严重的生态环境问题,改善生态环境的需求和呼声越来越迫切。作为陆地生态系统的主体和重要资源,森林是人类生存发展的重要生态保障,森林关系国家生态安全。基于森林生态系统与自然、人类社会系统的交互关系,从森林资源状况、地理气候条件、地区社会经济压力、人类管护响应状况四个方面构建省域森林生态安全评价指标体系,并建立森林生态安全指数模型。选取我国五个具有代表性的省份:贵州、湖北、浙江、吉林、青海作为试点省份,对其2004—2014年的森林生态安全状况进行评价和对比。结果表明:影响森林生态安全状况的最主要因素是森林资源类因子,在研究期内,5省森林生态安全状况大体上处于改善状态,但省与省之间森林生态安全状况差异显著,吉林省在研究期内森林生态安全整体状况最好,青海省森林生态安全状况较脆弱。在发展经济的同时,应该加强造林,重视对森林资源的管护,尤其要注意对天然林的保护,维护森林生态安全。     

基于森林调查数据的长白山天然林森林生物量相容性模型

森林生物量估算是进行陆地生态系统碳循环和碳动态分析的基础,但现有估测模型存在着总量与分量不相容的问题.本文以吉林省汪清天然林区为例,提出了基于森林调查的相容性森林生物量模型设计思想,并采用联立方程组为不同森林群落构造了一系列引入林分蓄积因子的相容性生物量模型,得到的预估精度较高.其中,针叶林、阔叶林和针阔混交林群落的森林生物量模型预估精度均在95%以上,基本上解决了森林生物量模型的相容性问题.     

基于个体的集水区森林动态模型

研制了基于个体的在景观尺度上运行的森林动态模型CFDM(individual-based catchmentscale forest dynamic model),介绍了CFDM模型的研制和检验过程,以及GIS技术的应用、气候和生理因子的参数化.对卧龙保护区一个139hm2小集水区进行了400年的模拟(包括地形数据的预处理、改进的山地小气候模型的运算和森林动态模拟).结果表明:CFDM模型能够描述林木个体的生理过程与空间分布,进而实现对整个集水区范围内森林的空间格局及其动态的模拟.     

长白山温带森林生态系统关键要素耦合及演替过程动态模拟

认识生态系统内和生态系统间耦合机制,揭示复合生态系统功能规律,对促进我国山水林田湖草沙项目一体化修复和保护实践具有重要的意义。针对目前修复和保护工程中出现的缺乏系统性、连续性等问题,以拥有丰富生态资源的长白山温带森林生态系统为研究区域,对其关键要素"水土气生"进行耦合建模。通过分析模型的运行机理,探究重要子模块之间的相互作用以及子模块内部生态关键要素的耦合机制,并以长白山温带落叶阔叶林的组成树种和环境因素为对象构建模型参数,通过运行林窗模型1000次,得出长白山温带森林的动态演替过程。结果表明:在森林生态系统的演替过程中,"水土气生"体现为模型中有效积温、干旱天数(低于土壤凋萎点的天数)、土壤可利用氮以及可利用光,这些关键要素之间相互影响,综合决定着每棵树木的更新、生长、死亡过程。模拟结果显示在长白山温带针阔混交林的动态演替过程中0-70 a,70-170 a,170-280 a,280-400 a四个阶段分别有不同的树种组成特征,与真实演替过程比较发现模拟林具有明显的阶段性。白桦、山杨为演替先锋树种,0-70 a期间生物量共占比为55%,70 a后生物量减少最后消失;紫椴、蒙古栎、水曲柳等为过渡树种,这些树种进一步改变了生长环境。红松在170 a前生物量占比仅为3%左右,随演替的发展生物量持续增加,170-280 a期间生物量占比15%,280 a之后红松生物量占总林分的50%。该结果模拟森林动态过程符合演替规律,充分说明多关键要素"水土气生"耦合机制的合理性,对于促进生态系统尺度上多生态要素耦合的相关研究提供了科学理论基础以及方法技术。     

Using null model analysis of species co-occurrences to deconstruct biodiversity patterns and select indicator species

Aim Using total species richness to characterize biodiversity may mask multiple response patterns of species. We propose a null model analysis of species co‐occurrence‐based classification to identify sets of species that may have similar (within‐groups) and distinct (between groups) response patterns to their environment. The classification should also provide an explicit framework for selecting indicator species with characteristic co‐occurrence patterns to predict overall species richness. Location Côte‐Nord, Québec, Canada. Methods We combined null‐model of species co‐occurrence and cluster analysis to identify species groups within diverse assemblages of ground‐dwelling and flying beetles of stands in a boreal forest mosaic; we then examined their co‐occurrence and response patterns to habitat characteristics. Best subset regressions were used to select indicator species of richness within each group, from which indicators of total species richness were selected. Results The identified species groups appeared to display contrasting co‐occurrence and response patterns to at least one of the stand‐level habitat characteristics. Among flying beetles, for example, richness increased with stand‐level heterogeneity for two groups and decreased for two other groups, but the relationship was non‐significant for the total richness. We identified 28 indicator species that explained > 80% (validated by bootstrap analysis) of the variation in total species richness. Predictive performance of indicators was higher than when their co‐occurrence were reshuffled, even under a highly constrained null model, indicating that co‐occurrence patterns contributed to their predictive performance. Main conclusions Co‐occurrence‐based classification appears as a promising and effective tool for deconstructing biodiversity into species groups which reflect their ecological commonalities and differences, thus reducing the risk of making faulty inferences about the causes underlying overall diversity patterns. The method provides an explicit framework for selecting indicator species representing different species groups that may reflect the multiple responses of species co‐occurring with them. Indicator species can be effective for predicting overall species richness.     

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。     

中国成熟天然林土壤有机碳垂直分异特征

以分布在中国不同气候区的131个成熟天然林土壤为研究对象,测定不同土层(0～10、10～20、20～30、30～50和50～100 cm)土壤有机碳(SOC)密度,分析其与气象因子、土壤性质的关系,研究天然林SOC垂直分布特征及其影响机理。结果表明: 温带针叶林、温带落叶阔叶林、亚热带落叶阔叶林和亚热带常绿阔叶林0～30 cm土层SOC密度均随土壤深度增加而降低。在0～100 cm土层,SOC密度地带性分异明显,温带针叶林SOC密度显著高于温带落叶阔叶林,亚热带常绿阔叶林SOC密度显著高于亚热带落叶阔叶林。SOC密度与土壤黏粒、年降水量以及地上净初级生产力呈显著正相关,与土壤pH和年均温呈显著负相关。年降水量与年均温调节天然林SOC输入与输出,土壤pH与黏粒影响天然林SOC积累,对成熟的天然针叶林与常绿阔叶林进行有效保护,有利于增加我国森林土壤碳库。     

Effects of adjacent stand characteristics and boundary distance on density and volume of mapped land units in the boreal forest

The possibility that forest characteristics on one side of a stand boundary will be related to the characteristics of the forest type on the other side of the boundary was examined in this study for the boreal forest in Quebec, Canada. It was found that alone, due to uncertainty in the photo-interpretation process, forest density and height – as identified by photo-interpreters – explained only about 10% of the variability inherent in total forest volume, balsam fir volume, or percentage balsam fir volume. The addition of boundary-related variables improved this to about 15% of variability explained. This led to the conclusion that the volume at any given location in the forest is related to the distance of the location from its stand boundary, as well as the characteristics of the forest type on the other side of the boundary. However, it was concluded that the relatively small improvement in R² does not justify using boundary-related information for additional forest stratification in the planning of (for example) forest inventories. Nonetheless, this work has implications for all ecosystem sampling that is based on maps derived from manual interpretation of natural phenomena.     

Density-dependent demography in a Japanese temperate broad-leaved forest

A method of detecting the density-dependent dynamics of a size-structured population is developed. The method is applied to a Japanese broad-leaved forest and the density-dependent and-independent projection matrix models are constructed based on the data of the forest. Then, the difference between the density-independent and density-dependent dynamics is compared in terms of several statistical quantities obtained from the matrices. Three kinds of sensitivity matrices are proposed for the density-dependent matrix model. At earlier stages, the sensitivity when the population density is low are higher than at the equilibrium. On the other hand, the inverse result is obtained at later stages. Moreover, the responses of the forest is analyzed to a decrease in survival rate and to an increase in the probability of gap formation. The decrease in survival rate leads to an extreme decrease in the density of the forest. However, the decrease in recruitment rate gives little effect on it because the effect of density-dependence in recruitment of new individuals is strong. The forest has the optimal rate of gap formation such that leads to the maximum population density.     

A simple multivariate analysis to assess diversity in a complex long-term managed forest area in central Italy

Today wood and nonwood forest resources management meets and often clashes with environment and biological diversity protection. A main problem is to understand relationships between the different roles of forest biodiversity, site, and management parameters. A multivariate statistical analysis has been carried out in order to interpret relationships between some forest biodiversity components and forest inventory data. Several indices of floristic diversity, species abundance, and structural heterogeneity at stand level have been calculated. The different components of forest biodiversity were separated by principal components analysis. Relations between forest biodiversity indices and site and management attributes have been investigated by two multivariate statistical techniques: bivariate correlation analysis and multiple linear regression. Results showed a high correlation between all the investigated components of forest biodiversity and some topographic and/or forest management attributes. Results also gave ancillary information to define sustainable forest management criteria.     

贡嘎山亚高山森林自然演替特征与模拟

通过对贡嘎山典型天然林样地动态的调查和群落结构的研究,基本掌握了青藏高原东部亚高山森林植被的演替特征和过程,在自然生态竞争条件下,树木的种源通过扩散,就地下种和萌发新技产生的幼苗只有极少数能够生长成大树,在树木繁育过程中,光照,水分,温度和养分竞争是决定性条件,山地灾变干扰对森林的更新也具有重要作用,提出的贡嗄山森林演替模型（GFSM）在树木个体生命史模型的基础上重现了群落的演替动态,特别是将土壤形成与树木演变结合起来,采用随机过程模拟气候波动及单木生长死亡的不确定性,揭示了亚高山天然条件下的森林个体与群落的行动态,对于解决天然林更新与保护提供了系统的分析预测技术与理论。     

Regional analysis of drought and heat impacts on forests: current and future science directions

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species‐level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait‐based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio‐temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change.     

Individual-scale inference to anticipate climate-change vulnerability of biodiversity

Anticipating how biodiversity will respond to climate change is challenged by the fact that climate variables affect individuals in competition with others, but interest lies at the scale of species and landscapes. By omitting the individual scale, models cannot accommodate the processes that determine future biodiversity. We demonstrate how individual-scale inference can be applied to the problem of anticipating vulnerability of species to climate. The approach places climate vulnerability in the context of competition for light and soil moisture. Sensitivities to climate and competition interactions aggregated from the individual tree scale provide estimates of which species are vulnerable to which variables in different habitats. Vulnerability is explored in terms of specific demographic responses (growth, fecundity and survival) and in terms of the synthetic response (the combination of demographic rates), termed climate tracking. These indices quantify risks for individuals in the context of their competitive environments. However, by aggregating in specific ways (over individuals, years, and other input variables), we provide ways to summarize and rank species in terms of their risks from climate change.     

A global model of the response of tropical and sub-tropical forest biodiversity to anthropogenic pressures

Habitat loss and degradation, driven largely by agricultural expansion and intensification, present the greatest immediate threat to biodiversity. Tropical forests harbour among the highest levels of terrestrial species diversity and are likely to experience rapid land-use change in the coming decades. Synthetic analyses of observed responses of species are useful for quantifying how land use affects biodiversity and for predicting outcomes under land-use scenarios. Previous applications of this approach have typically focused on individual taxonomic groups, analysing the average response of the whole community to changes in land use. Here, we incorporate quantitative remotely sensed data about habitats in, to our knowledge, the first worldwide synthetic analysis of how individual species in four major taxonomic groups—invertebrates, ‘herptiles’ (reptiles and amphibians), mammals and birds—respond to multiple human pressures in tropical and sub-tropical forests. We show significant independent impacts of land use, human vegetation offtake, forest cover and human population density on both occurrence and abundance of species, highlighting the value of analysing multiple explanatory variables simultaneously. Responses differ among the four groups considered, and—within birds and mammals—between habitat specialists and habitat generalists and between narrow-ranged and wide-ranged species.