露水河林业局森林多目标经营规划设计

改变单一经营目标的传统森林经营方式,进行森林多目标经营,综合发挥森林的生态、社会与经济功能是我国林业发展的一个新阶段。如何从一个生产单位的角度出发,统筹森林利用和保护相关的社会、经济及环境等各方面,进行多目标规划和决策,是林业研究和实践中的重要命题。以长白山区露水河林业局为例,探讨了森林多目标经营的必要性,设计了森林多目标经营的规划设计体系,从群落生境分析、发展类型设计、林分作业设计以及生命周期经营计划设计等方面对露水河林业局森林多目标经营进行了规划设计,以期为我国开展森林多目标经营提供借鉴和手段支撑。     

动物生境选择研究中的时空尺度

尺度研究已成为生态学上的一个重要概念和研究热点,但是在动物生境选择的研究中尚未引起足够的重视。动物的生境选择包括多层次的判别和一系列等级序位,在各个尺度和水平上具有不同的特征和机制,受到时空尺度的严格限定。繁殖期的时间限制、社群压力、环境变化、动物生理需求的变化决定了动物生境选择的时间制约性;而生境资源的斑块化分布、功能生境之间的相互作用决定了动物生境选择的空间制约性。研究者对时间和空间尺度的选取与应用会直接影响到生境选择研究结果的科学性和实效性。本文从动物生境选择的时空制约性出发,分析了生境选择研究中时间尺度的重要性,叙述了国内外生境选择研究中常见的研究尺度,强调了多尺度研究和长期生态研究的必要性,尺度的选择应该成为生境选择研究的起点和基础。     

森林生物量遥感降尺度研究

森林生物量是评价全球碳氧平衡、气候变化的重要指标。目前已有基于星载激光雷达数据的全球森林生物量产品,但空间分辨率较低,不能很好地满足小区域森林调查和动态监测的需要。针对这一现状,以美国马里兰州两个森林分布状况不同的区域为研究区,基于CMS(Carbon Monitoring System)30 m分辨率和GEOCARBON 1 km分辨率森林地上生物量产品以及TM等数据源,通过升尺度模拟低分辨率生物量数据和直接使用低分辨率产品两种方式,分别尝试建立了多光谱地表参数和低分辨率森林地上生物量之间的统计关系,以此作为降尺度模型实现了森林地上生物量空间分辨率从1 km到30 m的转换,并对降尺度结果进行精度评价和误差分析。结果表明:模拟数据降尺度后的30 m分辨率森林地上生物量空间分布和CMS森林地上生物量分布状况大致相同,RMSE=59.2—65.5 Mg/hm~2,相关系数约为0.7;其降尺度结果优于GEOCARBON产品直接降尺度结果RMSE=75.3—79.9 Mg/hm~2;相较于线性模型,非线性模型能更好地呈现森林地上生物量和地表参数间的关系;总体上,降尺度生物量呈现高值区低估,低值区高估的现象。     

青藏高原城市扩展过程的区位因素——基于随机森林的多尺度分析

过去几十年,青藏高原快速的城市扩展过程给生态环境带来了严重威胁。区位因素会影响城市扩展的空间格局,进而改变其对区域生态环境的影响。因此,认识青藏高原城市扩展过程的区位因素特征对于保护区域生态环境具有重要意义。在全区、生物群区和生态区3个尺度上分析了区位因素对青藏高原城市扩展过程的影响。基于长时间序列城市土地数据分析青藏高原城市扩展过程。利用随机森林模型分析青藏高原城市扩展区位因素特征。研究表明,青藏高原在1990-2020年期间经历了快速的城市扩展过程。全区城市土地面积从277.4 km²增加到974.9 km²,增长了2.5倍。对青藏高原城市扩展影响最大的区位因素高程对城市扩展的重要性不断下降。与之相对,铁路因素的重要性迅速上升,其重要性从2.15%增长到10.56%,增加了3.9倍。然而,铁路建设在促进青藏高原城市发展的同时,也会对区域内近三成的濒危物种产生影响。因此,在青藏高原未来城市发展过程中,既要重视铁路对城市扩展带动作用,也要注意减少铁路对区域生物多样性的影响,进而促进高原的可持续发展。     

山地森林样带植被-环境关系的多尺度研究

为了评价和比较地形和其它“直接”环境因子对植被变化影响的大小 ,通过调查一条亚热带山地森林样带及其生境因子 ,分析不同层次植被的水平格局 ;并利用多元回归和 DCCA方法比较了诸生境因子对植被格局变化的影响及其与分析尺度相关的变化。结果表明 :( 1 )影响乔木、灌木和草本层植被格局变化的首要因子都是地形特征 ;最重要的土壤因子是土壤发生层厚度。在对林下物种构成的影响方面 ,坡向和坡度的作用大于林冠空隙度。 ( 2 )除坡向外 ,其它地形因子之间存在不同程度的相关性 ;林冠孔隙度和土壤理化属性分别与不同的地形特征显著相关 ,显示了地形对林隙干扰和土壤侵蚀过程的控制。乔、灌、草的覆盖度是生境条件的综合反映 ;它们与非生物因子的相关性显示了成熟林下灌木和草本层物种生态习性的整体差异。 ( 3)各分析尺度上诸生境因子间的相关关系基本稳定。但随尺度增大 ,生境的小尺度异质性被平滑掉。诸因子之间的相关显著性程度逐渐降低。 ( 4 )从 5× 5 m2到 5× 4 0 m2 ,立地因子对乔、灌、草 3层植被变化的解释量随尺度的倍增而接近成倍增长 ;但其主要原因是样方数量增加 ;分析尺度变化的影响小得多。 ( 5 )地形与土壤、光照等直接生境因子对植被格局解释量之和相当。但在不同尺度上 ,地形特征都是     

热带森林树种多度和丰富度空间分布特征研究

用巴拿马50 hm2森林动态监测样地内直径≥1 cm的树种资料,分析了该样地树种多度(个体数)和丰富度(物种数)及其方差和变异系数在6个取样尺度(5 m×5 m,10 m×10 m,20 m×20 m,25 m×25 m,50 m×50 m,100 m×100 m)的变化规律.结果显示:(1)由于多度的可加性,不同取样尺度在样地内树种多度的变化表现出一致性;随取样尺度的增加,多度方差呈线性增加,而变异系数呈线性减小.(2)丰富度随取样尺度的变化较为复杂,随取样尺度的增加,丰富度方差呈非线性变化,在取样尺度为25 m×25 m时方差最大;变异系数随取样尺度的增加而呈线性减小.研究表明,大尺度的多度值可以由小尺度的多度值通过外推法估计,而丰富度却不能,在生物多样性的保护和管理中不能简单地从一个取样尺度的生物丰富度推测另一个取样尺度丰富度.     

种群分布格局的多尺度分析

种群分布格局的分析对于了解种群空间分布规律以及种内与种间关系具有重要的意义。最近邻体分析方法 (Nearestneighboranalysis, NNA) 作为种群空间分布格局的重要分析方法, 仅局限于种群格局的单尺度分析。改进NNA方法以应用于种群格局的多尺度分析, 将有助于解决种群格局的尺度依赖性。该文在前人研究的基础上提出扩展最近邻体分析方法 (Extendednearestneighboranalysis, ENNA), 也即在传统Clark_Evans指数公式的基础上增加一个距离尺度参数d (m), 并定义其所对应的Clark_Evans 指数CE (d) 的计算公式及其相应的显著性检验计算公式 (u (d) ) 分别为 :CE (d) =rdA/rdE= (1Nd∑Ndi=1 rdi) / (0.5Ad/Nd+0.0 5 14Pd/Nd+0.0 4 1Pd/Nd3 /2 ) 和u (d) = (rdA-rdE) /σd, 在距离尺度d (m) 范围内, 参数rdA指样地内各个体与其最近邻体间距离的平均值 (m) 、rdE指相同环境中个体呈随机状态时最近邻体距离的平均值 (m) 、Nd 为样地内个体总数、rdi为第i个个体与其最近邻体间的距离 (m) 、Ad 为样地面积 (m2 ) 、Pd 为样地周长 (m) 和σd 代表标准差。ENNA尺度变换采用与分形理论中计算沙盒维数相类似的过程, 而格局类型判断的标准与传统最近邻体分析方法相同。传统最近邻体分析结果是EN NA中距离尺度d取最大值dmax时的一个特例。以广东省黑石顶自然保护区针阔叶混交林中的马尾松 (Pinusmas soniana) 、黄牛奶树 (Symplocoslaurina) 、水栗 (Castanopsisnigrescens) 、鼠刺 (Iteachinensis) 和桃金娘 (Rhodomyrtustomentosa) 等 5个代表性种群为例, 在地理信息系统软件ArcViewGIS技术平台上进行的实例研究显示, 5个种群均表现出不同程度的尺度相关性。由此表明, 该文提出的新方法ENNA能够检测出种群空间分布格局的尺度依赖性, 获得关于种群空间分布格局的多尺度信息, 是进行种群空间格局多尺度分析的有效方法。     

庐山森林景观空间分布格局及多尺度特征

森林景观是区域整体景观的重要组成部分,研究其空间分布格局对于优化区域景观整体结构和发挥生态经济效益具有重要意义。基于庐山2010年植被斑块数据,将森林景观划分为常绿阔叶林、落叶阔叶林、松类、杉类和竹类等5类景观,从森林景观的不同发育阶段和林分类型角度出发,运用点格局分析法分析5类森林景观空间分布格局特征。最邻近距离分析表明:5类森林景观空间分布类型均服从集聚分布但聚集强弱有变化;不同发育阶段的森林景观空间分布类型以集聚分布为主,随机分布为辅,尤其幼龄林比较显著,中龄林和老龄林次之;5类森林景观的天然林均服从集聚分布,人工林大多趋于随机分布,只有松类和杉类呈显著集聚分布。Ripley's K函数揭示了不同发育阶段和林分类型的森林景观的多尺度集聚特征,即在小尺度范围内服从随机分布,随着空间距离的增大,以空间特征尺度为分界线,空间聚集强度先逐渐增强,随后不断减弱。总体来看,庐山森林景观的发育阶段主要处于幼年时期,原始植被遭到人类大肆破坏,幼龄林大片分布,属于典型的恢复性植被,未来要重点保护好天然林,减少人为干扰,实现森林景观适度集聚。研究庐山森林景观的空间分布和多尺度特征可以为生态环境保护和实现森林可持续经营提供理论指导。     

基于多尺度快速样本熵与随机森林的心电图分析

目的:探讨基于多尺度快速样本熵与随机森林的心电图分析方法对常见心律失常(房性早搏、室性早搏)的自动诊断的可行性和有效性。方法:利用不同心律失常疾病的心电信号存在复杂性差异的特点,通过多尺度熵计算心电信号在不同尺度下的样本熵值以组成特征向量;利用kd树提高多尺度熵的计算效率,增强算法的实时性。利用训练样本的特征向量构建随机森林分类器,再根据众多决策树的分类结果结合投票原则确定测试样本心律失常疾病的类型。结果:本文提出的心电图分析方法能够有效地识别正常心律、房性早搏(APB)及室性早搏(VPB),平均识别准确率达到91.60%。结论:本文提出的心电图分析方法对常见心律失常(APB,VPB)具有较高的识别准确率及临床实用价值。     

地形因子对森林景观格局多尺度效应分析

以TM影像和野外调查为数据源,3S技术为研究手段,分析了泰山的森林景观结构动态变化以及景观格局沿高程的分异。选择相对高差较大的区域设计了8个地形方位,采用3种由连续样方组成的辐射状样带,在遥感影像上进行信息采集,研究地形对森林景观格局的多尺度效应,分析了不同地形因子对森林景观分异的影响。结果表明,在景观尺度上,地形方位、海拔、山地类型是影响森林景观镶嵌格局的控制因素,坡向、坡度是重要因素,坡形、坡位是不明显因素。以TM影像为信息源,从森林景观分异和梯度分析上,首先要考虑海拔坡向指数、坡形坡位指数和海拔,并立足于地形方位。地形主要因子间存在着稳定的显著正相关,为森林分异多尺度格局提供了较强的综合解释能力。     

不同尺度上环境因子对常绿阔叶林群落的谱系结构的影响

群落的谱系结构是反映作用于群落组成的各种生态过程的综合指标。通过研究群落的谱系结构, 能够有效地推断形成群落谱系结构的生态过程。该文从环境因子(海拔、地形、pH、土壤湿度和土壤元素等)对群落谱系结构的影响这一视角出发, 采用圆形随机取样, 在半径为5、25、50、75和100 m 5个尺度上, 深入研究了古田山24 hm²永久样地群落的谱系结构。研究发现: 古田山样地在所有研究尺度上(半径 > 5 m)都表现为谱系聚集, 随着尺度的增加, 群落的聚集程度呈现出先增加后下降的格局。采用多元线性回归模型分析环境因子对群落谱系结构的影响时发现: 随着尺度的增加, 环境因子对群落谱系结构的影响逐渐增强; 在小尺度上, 环境因子对谱系结构没有显著影响, 这可能是由于小尺度上近缘种之间较强的竞争排斥作用所致。当尺度达到100 m半径时, 高海拔区域表现出谱系发散格局, 而低海拔区域保持谱系聚集, 这可能是由于古田山样地海拔较高的地带生境异质性较强和较大的干扰所致。该研究在所有的尺度上都表现出显著的谱系聚集, 与中性理论所预测的群落是物种的随机组合、无谱系结构相反, 因而为生态位理论提供了证据。     

Drivers of temporal changes in temperate forest plant diversity vary across spatial scales

Global biodiversity is affected by numerous environmental drivers. Yet, the extent to which global environmental changes contribute to changes in local diversity is poorly understood. We investigated biodiversity changes in a meta‐analysis of 39 resurvey studies in European temperate forests (3988 vegetation records in total, 17–75 years between the two surveys) by assessing the importance of (i) coarse‐resolution (i.e., among sites) vs. fine‐resolution (i.e., within sites) environmental differences and (ii) changing environmental conditions between surveys. Our results clarify the mechanisms underlying the direction and magnitude of local‐scale biodiversity changes. While not detecting any net local diversity loss, we observed considerable among‐site variation, partly explained by temporal changes in light availability (a local driver) and density of large herbivores (a regional driver). Furthermore, strong evidence was found that presurvey levels of nitrogen deposition determined subsequent diversity changes. We conclude that models forecasting future biodiversity changes should consider coarse‐resolution environmental changes, account for differences in baseline environmental conditions and for local changes in fine‐resolution environmental conditions.     

洞庭湖森林生态系统空间结构均质性评价

以东、南、西洞庭湖区域君山岛、龙山、赤山岛龙虎山林场、明朗山、常德林场、和洑林场和桃源县天然次生林为对象,借鉴生态学有关生态系统内部均衡和均质原理,在森林生态系统(斑块)尺度,从空间结构的混交、竞争、空间分布格局3个方面分析提出空间优化的均质性目标、均质性指数及均质性评价方法和评价标准.结果表明:15个洞庭湖湿地调查林分平均均质性评价指数为0.2517.均质性评价的5个等级中处于l级和2级的林分为12个,占80％,处于3级的林分只有3个,仅占20％.说明洞庭湖各林分整体上在空间结构、生长环境和树种优势度等方面不具有明显优势,离理想空间结构差距太大;按照高程不同,洞庭湖湿地从湖沼到丘陵岗地,林分空间结构均质性特征逐渐增强.森林生态系统空间优化均质性目标及均质性指数的提出是森林可持续经营空间途径的拓展,为森林经营的理想空间结构及其表达探索一条新途径.     

Species richness change across spatial scales

Humans have elevated global extinction rates and thus lowered global scale species richness. However, there is no a priori reason to expect that losses of global species richness should always, or even often, trickle down to losses of species richness at regional and local scales, even though this relationship is often assumed. Here, we show that scale can modulate our estimates of species richness change through time in the face of anthropogenic pressures, but not in a unidirectional way. Instead, the magnitude of species richness change through time can increase, decrease, reverse, or be unimodal across spatial scales. Using several case studies, we show different forms of scale‐dependent richness change through time in the face of anthropogenic pressures. For example, Central American corals show a homogenization pattern, where small scale richness is largely unchanged through time, while larger scale richness change is highly negative. Alternatively, birds in North America showed a differentiation effect, where species richness was again largely unchanged through time at small scales, but was more positive at larger scales. Finally, we collated data from a heterogeneous set of studies of different taxa measured through time from sites ranging from small plots to entire continents, and found highly variable patterns that nevertheless imply complex scale‐dependence in several taxa. In summary, understanding how biodiversity is changing in the Anthropocene requires an explicit recognition of the influence of spatial scale, and we conclude with some recommendations for how to better incorporate scale into our estimates of change.     

Choosing appropriate temporal and spatial scales for ecological restoration

Classic ecological restoration seems tacitly to have taken the Clementsian “balance of nature” paradigm for granted: plant succession terminates in a climax community which remains at equilibrium until exogenously disturbed after which the process of succession is restarted until the climax is reached. Human disturbance is regarded as unnatural and to have commenced in the Western Hemisphere at the time of European incursion. Classic ecological restoration thus has a clear and unambiguous target and may be conceived as aiming to foreshorten the natural processes that would eventually lead to the climax of a given site, which may be determined by its state at “settlement”. According to the new “flux of nature” paradigm in ecology a given site has notelos and is constantly changing. Human disturbance is ubiquitous and long-standing, and at certain spatial and temporal scales is “incorporated”. Any moment in the past 10,000 years that may be selected as a benchmark for restoration efforts thus appears to be arbitrary. Two prominent conservationists have therefore suggested that the ecological conditions in North America at the Pleistocene—Holocene boundary, prior to the anthropogenic extinction of the Pleistocene megafauna, be the target for ecological restoration. That suggestion explicitly assumes evolutionary temporal scales and continental spatial scales as the appropriate frame of reference for ecological restoration. However, ecological restoration should be framed in ecological spatio-temporal scales, which may be defined temporally in reference to ecological processes such as disturbance regimes and spatially in reference to ecological units such as landscapes, ecosystems, and biological provinces. Ecological spatio-temporal scales are also useful in achieving a scientifically defensible distinction between native and exotic species, which plays so central a role in the practice of ecological restoration and the conservation of biodiversity. Because post-settlement human disturbances have exceeded the limits of such scales, settlement conditions can be justified scientifically as appropriate targets of restoration efforts without recourse to obsolete teleological concepts of equilibria and without ignoring the presence and ecological influence of indigenous peoples.     

Determining spatial and temporal scales for management: lessons from whaling

Selection of the appropriate management unit is critical to the conservation of animal populations. Defining such units depends upon knowledge of population structure and upon the timescale being considered. Here, we examine the trajectory of eleven subpopulations of five species of baleen whales to investigate temporal and spatial scales in management. These subpopulations were all extirpated by commercial whaling, and no recovery or repopulation has occurred since. In these cases, time elapsed since commercial extinction ranges from four decades to almost four centuries. We propose that these subpopulations did not recover either because cultural memory of the habitat has been lost, because widespread whaling among adjacent stocks eliminated these as sources for repopulation, and/or because segregation following exploitation produced the abandonment of certain areas. Spatial scales associated with the extirpated subpopulations are frcequently smaller than those typically employed in management. Overall, the evidence indicates that: (1) the time frame for management should be at most decadal in scope (i.e., <100 yr) and based on both genetic and nongenetic evidence of population substructure, and (2) at least some stocks should be defined on a smaller spatial scale than they currently are.     

Reconciling the influence of global climate phenomena on macrofaunal temporal dynamics at a variety of spatial scales

Determining the relative importance of environmental forces on population dynamics is a fundamental question for ecologists. Growing concern over the ecological effects of climate change emphasizes the importance of defining whether broad-scale environmental forces uniformly act upon local populations (hierarchy theory) or cross-scale interactions influence local responses (multiscale theory). This study analyses 13 years of data on species abundances at six sites within a large harbour to determine the effect of the El Niño Southern Oscillation (ENSO). Environmental variables both directly and indirectly related to ENSO were observed to be important predictors of the temporal dynamics of abundance in many species, but the observed effects were not consistent across sites or species. While nearly all species were affected by large temporal and spatial scale variability, smaller temporal scale, location-specific environmental variables (such as wind-generated wave exposure and turbidity) were also generally important, increasing the variability explained by our models by up to 25%. As with many other broad-scale variables, generality of response to ENSO is affected by interactions across time and space with smaller scale heterogeneity. This study therefore suggests that the degree of interaction between broad-scale climatic factors, such as ENSO, with smaller scale variability, will determine the consistency of responses over large spatial scales, and control our ability to predict effects of climate change on coastal and estuarine communities.     

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。     

Latitudinal patterns of forest ecosystem stability across spatial scales as affected by biodiversity and environmental heterogeneity

Our planet is facing a variety of serious threats from climate change that are unfolding unevenly across the globe. Uncovering the spatial patterns of ecosystem stability is important for predicting the responses of ecological processes and biodiversity patterns to climate change. However, the understanding of the latitudinal pattern of ecosystem stability across scales and of the underlying ecological drivers is still very limited. Accordingly, this study examines the latitudinal patterns of ecosystem stability at the local and regional spatial scale using a natural assembly of forest metacommunities that are distributed over a large temperate forest region, considering a range of potential environmental drivers. We found that the stability of regional communities (regional stability) and asynchronous dynamics among local communities (spatial asynchrony) both decreased with increasing latitude, whereas the stability of local communities (local stability) did not. We tested a series of hypotheses that potentially drive the spatial patterns of ecosystem stability, and found that although the ecological drivers of biodiversity, climatic history, resource conditions, climatic stability, and environmental heterogeneity varied with latitude, latitudinal patterns of ecosystem stability at multiple scales were affected by biodiversity and environmental heterogeneity. In particular, α diversity is positively associated with local stability, while β diversity is positively associated with spatial asynchrony, although both relationships are weak. Our study provides the first evidence that latitudinal patterns of the temporal stability of naturally assembled forest metacommunities across scales are driven by biodiversity and environmental heterogeneity. Our findings suggest that the preservation of plant biodiversity within and between forest communities and the maintenance of heterogeneous landscapes can be crucial to buffer forest ecosystems at higher latitudes from the faster and more intense negative impacts of climate change in the future.     

Variance and spatial scales in a tropical rain forest: changing the size of sampling units

The size of a sampling unit has a critical effect on our perception of ecological phenomena; it influences the variance and correlation structure estimates of the data. Classical statistical theory works well to predict the changes in variance when there is no autocorrelation structure, but it is not applicable when the data are spatially autocorrelated. Geostatistical theory, on the other hand, uses analytical relationships to predict the variance and autocorrelation structure that would be observed if a survey was conducted using sampling units of a different size. To test the geostatistical predictions, we used information about individual tree locations in the tropical rain forest of the Pasoh Reserve, Malaysia. This allowed us to simulate and compare various sampling designs. The original data were reorganised into three artificial data sets, computing tree densities (number of trees per square meter in each quadrat) corresponding to three quadrat sizes (5×5, 10×10 and 20×20 m⁽²⁾). Based upon the 5×5 m⁽²⁾ data set, the spatial structure was modelled using a random component (nugget effect) plus an exponential model for the spatially structured component. Using the within-quadrat variances inferred from the variogram model, the change of support relationships predicted the spatial autocorrelation structure and new variances corresponding to 10×10 m⁽²⁾ and 20×20 m⁽²⁾ quadrats. The theoretical and empirical results agreed closely, while the classical approach would have largely underestimated the variance. As quadrat size increases, the range of the autocorrelation model increases, while the variance and proportion of noise in the data decrease. Large quadrats filter out the spatial variation occurring at scales smaller than the size of their sampling units, thus increasing the proportion of spatially structured component with range larger than the size of the sampling units.