混交林测树因子概率分布模型的构建及应用

基于最大熵原理,针对目前对混交林测树因子概率分布模型研究的不足,提出了联合最大熵概率密度函数,该函数具有如下特点：1）函数的每一组成部分都是相互联系的最大熵函数,故可以综合混交林各主要组成树种测树因子的概率分布信息;2）函数是具有双权重的概率表达式,能体现混交林结构复杂的特点,在最大限度地利用混交林每一主要树种测树因子概率分布信息的同时,还能精确地全面反映混交林测树因子概率分布规律;3）函数的结构简洁、性能优良.用天目山自然保护区的混交林样地对混交林测树因子概率分布模型进行了应用与检验,结果表明：模型的拟合精度(R²=0.9655)与检验精度(R²=
0.9772)都较高.说明联合最大熵概率密度函数可以作为混交林测树因子概率分布模型,为全面了解混交林林分结构提供了一种可行的方法.     

最大熵原理及其在生态学研究中的应用

最大熵原理(the principle of maximum entropy)起源于信息论和统计力学,是基于有限的已知信息对未知分布进行无偏推断的一种数学方法.这一方法在很多领域都有成功应用,但只是近几年才被应用到生态学研究中,并且还存在很多争论.我们从基本概念和方法出发,用掷骰子的例子阐明了最大熵原理的概念,并提出运用最大熵原理解决问题需要遵从的步骤.最大熵原理在生态学中的应用主要包括以下方面:(1)用群落水平功能性状的平均值作为约束条件来预测群落物种相对多度的模型;(2)基于气候、海拔、植被等环境因子构建物种地理分布的生态位模型;(3)对物种多度分布、种一面积关系等宏生态学格局的推断;(4)对物种相互作用的推断;(5)对食物网度分布的研究等等.最后我们综合分析了最大熵原理在生态学应用中所存在的争议,包括相应模型的有效性、可靠性等方面,介绍了一些对最大熵原理预测能力及其局限性的检验结果,强调了生态学家应用最大熵原理需要注意的问题,比如先验分布的选择、约束条件的设置等等.在物种相互作用、宏生态学格局等方面对最大熵原理更广泛的讨论与应用可能会给生态学带来新的发展机会.     

一个基于熵的对疾病基因精细定位的指数

针对人类疾病基因的精细定位,本文利用稠密的标记位点,通过比较标记的熵和条件熵,给出了一个基于熵的指数。该指数可以度量标记基因和性状位点间连锁不平衡(LD)程度。该指数的特性是它不依赖于标记基因的频率。同时它对应疾病易感位点(DSL)精细定位的哈迪-温伯格不平衡(HWD)指数。通过计算机模拟,文章调查了不同遗传参数下该指数的性质。模拟结果表明该指数用作疾病易感位点精细定位是有效的。     

基于广义线性模型和最大熵模型的黑龙江省林火空间分布模拟

林火分布模型是在较大区域上描述林火空间分布的强有力工具,并可以确定影响林火分布的控制因子.本研究基于黑龙江省1996-2006年的历史火烧记录数据,分别采用广义线性模型和最大熵模型分析了地形、人类活动和土地覆被类型等环境控制因子对黑龙江省林火空间分布的影响,并比较了模型预测精度、评价环境变量重要性及预测火点概率分布图等.结果表明:两个模型的预测精度达中等水平,而最大熵模型的预测精度要略高于广义线性模型.总体而言,与人类活动相关的变量是林火分布模型最佳的环境变量,地形变量次之.尽管两个模型在预测精度和环境变量重要性方面都有很大的相似性,但最大熵模型产生的火点概率图空间格局与广义线性模型产生的明显不同.本研究说明,为了更加精确地确定森林火灾发生的热点地区,应该采用不同模型进行比较,或者有选择性地进行组合以产生综合的预测结果,从而为森林防火工作提供更加合理高效的建议.     

通过熵理论使用核心家系进行精细定位(英文)

针对精细定位人类复杂性状基因位点,我们拓展了基于熵的连锁不平衡指数到使用病例-父母和无关的对照-父母设计的家系研究.这个指数比较杂合子父母传递给受累子代和非受累子代基因的熵和条件熵.在单一群体和混合群体两种情形下,我们通过模拟调查了该指数的性质.结果表明在不同遗传模型下利用该指数定位的概率随着样本容量的增大而增大.当样本容量超过200,显性模型和加性模型的概率在90%以上.当样本容量超过300,隐性模型和乘积模型的概率在80%以上.当存在群体混杂时,该指数仍然适用于精细定位.     

应用GIS和最大熵模型分析秦岭冷杉潜在地理分布

秦岭冷杉(Abies chensiensis)为松科常绿针叶乔木,属国家濒危野生物种。本文利用获取的秦岭冷杉地理分布记录和14个气候指标、3个土壤指标和3个地形指标,通过最大熵模型(Max Ent)和Arc GIS空间分析构建秦岭冷杉潜在分布区。结果表明,影响秦岭冷杉潜在生境适宜性的主要环境指标为6个气候指标(年平均气温、年极端最高气温、1月平均气温、≥0℃积温、年干燥度指数和年日照时数)、1个土壤指标(p H)和1个地形指标(海拔)。研究区秦岭冷杉生长的最适宜区面积为19498.87 km2,适宜区面积为32219.61 km2,边缘适宜区面积为51874.76 km2,不适宜区面积为106307.97 km2,秦岭冷杉适宜生长区域狭窄,其中最适宜区和适宜区主要集中在甘肃东南部、陕西中南部、四川东北部,湖北西北部和河南西北部,适宜区内次生植被丰富、地形复杂。研究表明,基于最大熵模型与GIS空间分析构建的秦岭冷杉潜在地理分布,可以对我国秦岭冷杉适宜生长区做出科学的区划,为秦岭冷杉资源的保护和管理提供科学依据。     

煤炭资源型城市生态安全评价——以锡林浩特市为例

煤炭资源型城市生态安全评价能够协调人口、资源和环境之间的矛盾,保障城市可持续发展。基于PSR模型,以煤炭资源型城市锡林浩特市为研究区域,从生态环境和社会经济方面共选取了33个指标因子,构建了煤炭资源型城市的生态安全评价指标体系,运用熵权TOPSIS法进行了城市生态安全综合评价,并通过障碍度模型对城市生态安全的主要障碍因子进行了研究。研究结果表明:(1)2008—2017年锡林浩特市生态安全水平总体呈缓慢上升趋势。生态安全综合评价指数从0.464上升到0.553,安全等级由较不安全转为临界安全状态;(2)10年间PSR三大指数表现出不同变化特征。压力指数呈下降后上升再小幅下降的变化趋势,状态指数呈波动上升趋势,响应指数呈快速上升趋势;(3)子系统的障碍度分析表明压力系统的障碍度最大,是影响煤炭资源型城市生态安全的首要因素。子系统的障碍度变化趋势表现为:压力系统和状态系统的障碍度均不同程度增大,响应系统的障碍度越来越小;(4)单项指标的障碍度分析表明影响该资源型城市生态安全的主要障碍因子集中在压力系统和状态系统,10年间最大障碍因子经历了从城镇化率到矿区面积的演变。     

基于最大熵原理的浙江毛竹胸径分布及测量不确定度评定

应用最大熵原理构造了测树因子概率分布的统一模型,这样构造的模型具有明确的解析表达式,并能克服常用方法无法解释测树因子服从某种概率分布的真正原因,从而为测树因子统计分布建模提供了一种有效方法.使用1-3阶样本矩、1-4阶样本矩与1-5阶样本矩,用所构建的概率分布统一模型分别对浙江省域毛竹胸径分布分别作了仿真试验,结果表明当采用1-4阶样本矩时,仿真效果最好,而且比通过假设检验的Weibull分布仿真结果理想:(1)图形非常相似,对实测数据都能很好的模拟;(2)最大熵法的离差平方和为0.00018,Weibull分布的为0.00045[1].由于各种系统与非系统的原因,都会影响测量结果的准确性,对所构建的模型作了不确定度评定,表明结果具有很大的可靠性,测量结果的估计:7.85100,测量结果的标准不确定度:1.82710,置信概率:0.96020.     

基于最大熵原理的多尺度毛竹胸径分布统一模型构建及应用

在生态学中,尺度问题一直是重点也是难点,多尺度胸径分布问题经常遇到且至今没有很好的解决方法,建立多尺度胸径分布统一模型是解决问题的关键;多尺度胸径分布统一模型的建立包括2方面的内容:第一,选择合适的概率分布函数,应用最大熵原理推出胸径分布统一模型,它具有明确的解析表达式,既能克服常用方法无法解释测树因子服从某种概率分布的真正原因,也能克服常用方法无法区分测树因子服从多种概率分布的不足,从而可以作为林分尺度测树因子概率分布的统一模型.第二,尺度与尺度转换,常用研究尺度问题的方法具有2个不足:(1)研究大尺度时损失了样地(林分尺度)资料的宝贵信息;(2)研究林分尺度时无法进行尺度转换.提出的联合最大熵概率密度函数可以克服常用研究尺度方法的以上2个不足,该函数的每一个组成部分都是最大熵函数;联合最大熵概率密度函数可以作为多尺度胸径分布统一模型,既可以最大限度的利用每个样地的信息,又可以进行多尺度的自由转换,从而为测树因子统计分布建模提供了一种有效方法;用森林资源连续清查样地中属于安吉的22个毛竹样地对文中提出的方法进行了验证,结果表明方法可行且对每个样地的拟合精度都很高.     

一个基于熵的精细定位数量性状位点的指数

针对数量性状位点的精细定位,本文采用群体的极端样本,利用稠密的标记位点,通过比较标记的熵和条件熵,给出了一个基于熵的指数。该指数是标记基因和性状位点间连锁不平衡系数的函数,它不依赖于标记基因的频率。该指数对应我们之前提出的数量性状位点精细定位的哈迪-温伯格不平衡(HWD)指数,但在精细定位数量性状位点时,本文提出的指数的效能要高于哈迪-温伯格不平衡(HWD)指数。通过计算机模拟,文章调查了不同遗传参数下该指数的性质。模拟结果表明该指数用作精细定位是有效的。     

Metabolic networks evolve towards states of maximum entropy production

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles.     

The strategy of ecosystem development: specific dissipation as an indicator of ecosystem maturity

The ratio of entropy generation rate to entropy embodied in structures relatively to the surroundings can be considered as an indicator of the ability of a self-organizing dissipative system to maintain itself far from equilibrium by pumping out entropy. The higher the ratio (which may be called the specific entropy production or the specific dissipation of a system), the lower the capacity of a system to convert the incoming low-entropy energy into internal organization. It appears that the ratio attains special significance for interpreting the evolution of biological systems, as the maximum expression of self-organizing systems, from the sub-cellular to the ecosystem scale. This paper proposes specific dissipation, written as the ratio of biological entropy production to exergy stored in the living biomass, as a thermodynamic orientor as well as an indicator of the development state of ecological systems. After having presented a method for estimating the specific dissipation in lakes, the adequacy of the proposed indicator is discussed and also tested by comparing its response to those of some classical ecological attributes (successional sequences of species, biodiversity, individual body size, structural organization and generation time of organisms) throughout the seasonal progression of the plankton community in Lake Trasimeno (Umbria, Italy). The results support the hypothesis that the minimization of specific dissipation is a primary criterion of evolution of ecological systems and also sustain the use of specific dissipation as an indicator of ecological maturity.     

最大信息熵原理与群体遗传平衡

建立了用最大信息熵原理推导群体遗传平衡定律的统一数学模型,并给出了模型的统一解,此解正是Hardy-Weinberg定律所给出的平衡群体的基因型频率,说明当群体信息熵达到最大时,群体基因型频率不再变化,即达到“平衡”。这证明了最大熵分布就是Hardy-Weinberg平衡分布。Hardy-Weinberg平衡定律与最大信息熵原理的内在一致性说明,杂交和随机交配是一个不可逆过程,使群体基因型信息熵增大,无序性增,是选择和近亲交配使群体的信息熵降低,有序性增加,育种过程实际就是调节群体信息熵的过程。过程信息熵的含义是表示一个概率分布的不确定性,最大熵原理意味着在一定的约束条件,选择具有最大不确定性的分布,从而其分布是最为随机的。最大熵原理在信息,工程,天文,地理,图像处理,模式识别等自然科学和社会科学领域都有广泛的成功应用,本文从群体遗传学角度证明了这一原理具有普遍适用性。熵是描述系统状态的函数,而最大熵原理则表明了系统发展变化的趋势,系统的最终状态必然是熵增加至最大值的状态,对于任何系统都是如此。因此,群体遗传系统的平衡定律可以统一用最大熵原理进行判定和描述;任意群体的基因型信息熵在随机交配世代传递时有不断增加的趋势;在一定约束条件下基因型信息熵达到最大值时,就称之为达到遗传平衡。本文将信息论原理应用于群体遗传学研究,揭示了基因信息熵的生物学意义,并表明可以用信息学和控制论的原理和方法来研究群体遗传学问题。     

A River Runs through Us

The Anacostia River severs Washington, D.C. Military waste, urban runoff, and former farmland dirty the water, but people who live along its shores cherish the river and fight to make it clean. Political ecology, stressing the power relations, inequalities, connections, and contradictions that join natural and social processes over time, enlarges historical and anthropological theory in Washington. In this article I explore the experiences and perspectives of people who have lived along the Anacostia River over the last 10,000 years. Linked transformations in environmental and social processes repeatedly created unsettled, contradictory, and unjust relations between people and the natural and built environment. The pollution of the Anacostia River reflects colonialism and conquest: nationalism, militarism, empire; racism, inequality, and urban renewal. I begin with the British conquest, then turn to four successive moments in state formation: the founding of the capital, the invention of a strong central government, urban renewal in the capital core, and the contemporary development of the waterfront. The use values of people who live along the river conflict with the exchange values that have dominated the city's history. The city's environmental justice movement has emerged from these use values and today confronts a massive redevelopment plan that exploits and undermines the movement, [political ecology, environmental justice, urban history, race, and poverty]     

Modeling the Origin and Possible Control of the Wealth Inequality Surge

The rapid increase of wealth inequality in the past few decades is a most disturbing social and economic issue of our time. In order to control, and even reverse that surge, its origin and underlying mechanisms should be revealed. One of the challenges in studying these mechanisms is to incorporate realistic individual dynamics in the population level in a self-consistent manner. Our theoretical approach meets the challenge by using interacting multi-agent master-equations to model the dynamics of wealth inequality. The model is solved using stochastic multi-agent iterated maps. Taking into account growth rate, return on capital, private savings and economic mobility, we were able to capture the historical dynamics of wealth inequality in the United States during the course of the 20th century. We show that the fraction of capital income in the national income and the fraction of private savings are the critical factors that govern the wealth inequality dynamics. In addition, we found that economic mobility plays a crucial role in wealth accumulation. Notably, we found that the major decrease in private savings since the 1980s could be associated primarily with the recent surge in wealth inequality and if nothing changes in this respect we predict further increase in wealth inequality in the future. However, the 2007–08 financial crisis brought an opportunity to restrain the wealth inequality surge by increasing private savings. If this trend continues, it may lead to prevention, and even reversing, of the ongoing inequality surge.     

Maximization principles and daisyworld

We investigate whether the equilibrium time-averaged state of a self-organizing system with many internal degrees of freedom, 2D-daisyworld, can be described by optimizing a single quantity. Unlike physical systems where a principle of maximum energy production has been observed, daisyworld follows evolutionary dynamics rather than Hamiltonian dynamics. We find that this is sufficient to invalidate the maximum entropy production principle, finding instead a different principle, that the system self-organizes to a state which maximizes the amount of life.     

Gaia again

The ideas of the Gaia hypothesis from the 1960s are today largely included in global ecology and Earth system sciences. The interdependence between biosphere, oceans, atmosphere and geosphere is well-established by data from global monitoring. Nevertheless the theory underlying the holistic view of the homeostatic Earth has remained obscure. Here the foundations of Gaia theory are examined from the recent formulation of the 2nd law of thermodynamics as an equation of motion. According to the principle of increasing entropy, all natural processes, inanimate just as animate, consume free energy, the thermodynamic driving force. All species, abiotic just as biotic are viewed as mechanisms of energy transduction for the global system to evolve toward a stationary state in its surroundings. The maximum entropy state displays homeostasis by being stable against internal fluctuations. When surrounding conditions change or when new mechanisms emerge, the global system readjusts its flows of energy to level newly appeared gradients. Thus, the propositions of Gaia theory and holistic understanding of the global system are recognized as consequences of thermodynamic imperatives.     

The Changing Moral Economy of Ancestor Worship in a Chinese Emigrant District

This paper describes the reciprocal influences between Anxi County Fujianese, whose families and clans have migrated to Singapore, and their ancestral villages in Fujian, China. The Singaporeans bring wealth and cultural capital to their poor relations in rural China. Their participation is crucial for local socioeconomic development. Besides bringing material support and globalizing values and lifestyles, they also reinvigorate and transform the local religious tradition. They, in turn, reaffirm and even remake their own ethnic and regional identity. The complex outcome illustrates the fact that China's social change under economic reforms and global influence is, in its huge rural core, not merely a matter of infrastructural, market, and social welfare improvements, but involves exchange and transformation in meanings of rituals and experiences. We can see that kinship and religion are not unchanging aspects of the cultural tradition that are separate from programs of modernity. Indeed, modernity and tradition appear to be inseparable, and they may reveal that the recipe for effective community projects requires a vital tie between cultural, social, and interpersonal processes.     

Increases in environmental entropy demand evolution

An application of the entropic theory of perception to evolutionary systems indicates that environmental entropy increases will exert pressures on an organism to adapt. We speculate that the instability caused by such environmental changes will also cause an increase in the mutation rate of organisms leading to an eventual increase in their complexity. Such complexity generation allows organisms to adapt to the more entropic environment. Although we conclude that increases in environmental entropy cause an organism to evolve into a more complex organism, increases in entropy may not be necessary for complexity generationper se.     

The Role of Community and Individuals in the Formation of Social Capital

Because social capital shapes many desirable socioeconomic outcomes, we ask what incentives drive private investments in social capital. We estimate the association between private investments in social capital (outcome variable) and the following explanatory variables: (a) individual-level variables from an optimal investment model, (b) spillovers from group social capital, (c) village income inequality, and (d) market openness. We draw on information from Tsimane’, a native Amazonian society of foragers and farmers in Bolivia, and equate social capital with gifts, help given, and communal labor offered by the household. Age bore an inverted U-shaped and income bore a positive association with social capital, but geographic mobility, wealth, and schooling bore no significant association with social capital. We found strong group-level associations even after instrumenting social capital; the association probably stems from strong kinship ties which tend to blur the line between the group and the individual. Village measures of social capital were positively and significantly associated with private investments in social capital. We found some evidence that village income inequality and market openness were negatively associated with private investments in social capital.