哀牢山亚热带中山湿性常绿阔叶林树种beta多样性格局形成的驱动力

Beta多样性通常指群落在时间和空间上物种组成的差异, 包括物种周转组分和物种丰富度差异组分。驱动beta多样性格局形成的生态过程决定了群落的时空动态, 然而关于beta多样性及其两个组分格局形成的驱动力还存在较多争议。以往研究表明, beta多样性的格局存在取样尺度的依赖性, 驱动其形成的生态过程在不同取样尺度下的相对重要性也随之改变。本研究以哀牢山亚热带中山湿性常绿阔叶林20 ha动态监测样地为研究对象, 在不同取样尺度上, 将样方间的Bray-Curtis指数分解为物种周转组分和物种丰富度差异组分, 通过典范冗余分析和方差分解的方法揭示环境过滤和扩散限制对于beta多样性及其两个组分格局形成的相对重要性及其尺度依赖性。结果表明: (1) beta多样性、物种周转组分和物种丰富度差异组分均随取样尺度的增大而减小。在不同取样尺度下, 物种周转组分对于beta多样性的贡献始终占主导地位。(2)随着取样尺度的增大, 环境过滤驱动beta多样性格局形成的相对重要性逐渐增加, 而扩散限制的相对重要性逐渐降低。本研究进一步证实了取样尺度在beta多样性格局形成及其驱动力定量评价中的重要性, 今后的研究需要进一步解析上述尺度效应的形成机制。     

百山祖自然保护区植物群落beta多样性

本文采用植物群落学的典型样方法,研究了百山祖自然保护区森林植物群落beta多样性格局及其维持机制。通过对45个20m?20m标准样地的调查数据进行分析,运用Chao’s群落距离指数衡量该植物群落beta多样性格局,并通过Mantel检验、基于距离矩阵的偏RDA分析和方差分解等方法初步检验和衡量了各环境因子差异（包括群落郁闭度、海拔、坡度、坡向和坡位）和群落空间距离对该区域beta多样性格局的影响。结果显示,该区域内植物群落beta多样性随着群落间综合环境差异或群落空间距离的增加而增大, 但环境差异和群落空间距离只能解释36%左右的beta多样性格局。检验的5个环境因子中,只有群落郁闭度和海拔对百山祖自然保护区植物群落beta多样性有显著影响,并且群落郁闭度对beta多样性的解释度（20.0%）略高于海拔对beta多样性的解释度（18.0%）。群落空间距离对百山祖自然保护区beta多样性的解释度最小（9.0%）。本文展现了百山祖自然保护区内植物群落beta多样性格局及其与群落环境和空间距离的关系,所获得的结果支持生境异质性和扩散限制联合对植物群落beta多样性起作用的假说。     

南亚热带森林不同林型功能性状分布格局及其驱动机制

植物功能性状能反映植物对环境变化的响应,研究植物功能性状的分布格局有助于揭示群落的构建过程及其内在作用机制。该研究以鼎湖山南亚热带山地常绿阔叶林和沟谷雨林为研究对象,采集并测量了样地中木本植物的12种不同的功能性状,分别以5 m×5 m、10 m×10 m、20 m×20 m的样方为尺度单元,通过计算平均成对性状距离指数来探讨群落中功能性状的分布格局及其驱动机制。结果表明,两个林型的群落中12个功能性状均存在不同程度变异,但功能性状在群落间的差异不显著(P>0.05)。两个林型的群落中功能性状空间分布格局均具有尺度依赖性,但不同尺度的驱动机制有差异,随着空间尺度的增大,山地常绿阔叶林的功能性状空间分布格局主要驱动机制由环境过滤转为扩散限制;沟谷雨林的由环境过滤和相似性限制转为扩散限制,两个林型在20m×20m空间尺度上都是扩散限制。生态位分化和扩散限制综合作用于鼎湖山南亚热带山地常绿阔叶林和沟谷雨林的群落功能性状分布格局的产生及其群落构建过程,二者的贡献作用会随空间尺度发生变化。坡度是影响山地常绿阔叶林功能性状分布格局的最关键地形因子,海拔是影响沟谷雨林的最关键地形因子。     

辽东山区次生林木本植物空间分布

森林木本植物的空间格局有助于揭示群落结构的形成机制与潜在的生态学过程,且对林分经营具有一定指导意义。在0—50 m尺度范围内综合分析了辽东山区4 hm2温带次生林样地多度10的树种空间格局。研究发现:(1)在完全随机零模型下,大部分树种呈现聚集格局,聚集格局树种的比例随尺度增加而降低;在32 m的较大尺度下,随尺度增加,随机和规则格局成为树种分布的主要形式;(2)在异质性泊松过程零模型下,55.9%的树种呈现随机格局,其余大部分树种在10 m的尺度下呈现聚集格局,且随尺度增加,规则格局成为主要形式;(3)在完全随机零模型下,树种属性(林层、径级和多度)显著地影响种群聚集度,而在异质性泊松过程零模型下,树种属性对种群聚集度不存在显著影响。综上,生境异质性、扩散限制和树种属性部分解释了辽东山区次生林木本植物空间分布格局,相对而言,生境异质性的效应更为突出。研究结果有助于揭示次生林群落生物多样性的维持机制。     

美洲森林群落beta多样性的纬度梯度性

Beta多样性度量不同时空尺度物种组成的变化,是生物多样性的重要组成部分;理解其地理格局和形成机制已成为当前生物多样性研究的热点问题。基于Alwyn H. Gentry在美洲收集的131个森林样方数据,采用倍性和加性分配方法度量群落beta多样性,检验beta多样性随纬度的变化趋势,并分析其形成机制。研究表明:(1) 美洲森林群落beta多样性随纬度增加显著下降,热带和亚热带地区beta多样性高于温带地区;此格局可由物种分布范围的纬度梯度性和不同粒度(grain)下物种丰富度与纬度回归斜率的差异推论得出;(2) 加性分配方法表明beta多样性对各个温度带森林群落gamma多样性的相对贡献率平均为78.2%,并且随纬度升高而降低;(3) 美洲南半球森林群落beta多样性高于其北半球,这可能反映了区域间物种进化和环境变迁历史的差异。此外,还探讨了不同beta多样性计算方法的适用情景,首次证实了森林生态系统群落水平beta多样性的纬度梯度性,这对研究生物多样性的形成机制和生物多样性保护都具有重要的意义。     

中国东部海岛维管植物的beta多样性及其驱动因素

beta多样性描述群落物种组成如何随环境梯度而变化。海岛具有边界清晰、面积和离岸距离不同以及环境变化剧烈等自然禀赋。目前, 我们对离岸距离、岛间距离和气候因素在海岛植物beta多样性变化格局中的相对贡献仍认识不足。本研究基于中国东部36个海岛的维管植物物种名录, 以Jaccard相异性指数度量beta多样性, 利用Mantel偏相关分析和beta多样性的变异分解, 探究了海岛不同生活型维管植物的beta多样性格局及其非生物影响因素。结果显示: 36个海岛共记录维管植物1,404种, 其中木本植物481种, 草本植物859种, 藤本植物64种。植物beta多样性随岛间距离和离岸距离差的增大而显著增加(P < 0.001); 海岛面积和气候要素对植物beta多样性无显著影响(P > 0.05)。岛间距离单独对beta多样性总变异的解释度为29.3%, 离岸距离独立解释了2.8%, 面积和气候共同解释了0.5%。木本植物与草本植物的beta多样性格局与总体一致, 距离因子对木本植物beta多样性的解释度高于草本植物(37.5% > 25.3%)。综上, 海岛植物beta多样性主要受岛间距离和离岸距离的影响, 反映了扩散限制是塑造中国东部海岛植物beta多样性格局的主要生态过程。     

海南尖峰岭热带山地雨林林冠层树种功能多样性特征

以海南尖峰岭热带山地雨林3块1 hm²样地为研究对象,利用11个林冠功能性状结合样地地形及林冠乔木树种样地清查数据,分别基于单维性状和多维性状比较物种多度加权对群落功能离散度指数——平均成对距离(MPD)和平均最近类群距离(MNTD)的影响;同时分析林冠层功能丰富度(FRic)与物种丰富度之间的关系,最后利用零模型探讨不同生境类型下标准化效应MPD和MNTD(经过物种多度加权且剔除群落物种丰富度差异影响)的变化,进而评价林冠层群落水平功能多样性格局及其对局域生境异质性的响应.结果表明: 功能性状维度和物种多度对MPD的影响强烈,不同维度功能性状多度加权前后MPD相关性较弱(R=0.359～0.628);但对MNTD的影响相对较弱,不同维度功能性状多度加权前后MNTD相关性较强(R=0.746～0.820);未经物种多度加权的MPD和MNTD均普遍高估了林冠层的功能离散度.林冠层功能丰富度与物种丰富度基本呈指数相关关系(F=128.20;R²=0.632;AIC=97.72;P＜0.001),且功能丰富度很有可能存在一定的物种丰富度阈值.基于不同维度功能性状的林冠层功能多样性格局及其生境响应存在一定的差异性.在生物竞争激烈的低沟生境中,林冠层功能多样性倾向于比预期零模型随机产生的功能多样性高,林冠树种功能性状表现出离散分布;而在其他生境类型中,林冠层功能多样性倾向于接近或低于随机产生的功能多样性,林冠树种功能性状随机或聚集分布.     

基于PGGB途径优化桫椤组织培养繁殖体系研究

该研究以龙溪-虹口国家级自然保护区内11个典型地震滑坡体为研究对象,采用非度量多维尺度分析(NMDS)和相似性分析(ANOSIM)初步探讨了β多样性海拔格局,并运用Mantel检验和基于距离矩阵的多元回归方法(MRM)进一步分析不同生态因子对群落β多样性变异的贡献,以揭示地震干扰后滑坡体植物群落β多样性的响应机制及生物多样性形成和维持机制。结果表明：(1)随着海拔的升高,木本植物β多样性表现出单调递减格局,而草本植物β多样性则表现出“U”形变化格局,滑坡体植物群落组成和结构在海拔梯度上存在显著的差异(P< 0.001)。(2)草本植物和木本植物β多样性与地理距离、海拔距离、局地生境差异均呈显著递增趋势(P< 0.001),地理距离和海拔距离是引起群落物种组成变化的关键因子,且海拔距离的重要性均大于地理距离。(3)地理距离和生境差异作为主导因子,分别共同解释了木本和草本β多样性变异的61.52%和40.91%,且环境差异单独解释率均大于地理距离单独解释率。(4)环境差异和地理距离对木本植物β多样性的作用均强于草本植物。研究认为,生境过滤和扩散限制共同影响着地震滑坡体植物群落的β多样性格局,且生境过滤所起作用更为显著。     

桂西北喀斯特常绿落叶阔叶混交林物种多样性分布格局的尺度效应

物种多样性的空间分布格局及其与尺度的关系研究对于了解群落物种多样性形成机制具有重要意义。为了探讨喀斯特地区物种多样性空间分布格局的尺度效应,以喀斯特常绿落叶阔叶混交林25 hm~2样地的(胸径DBH≥1)木本植物为研究对象,分析了6个空间尺度(5 m×5 m,10 m×10 m,20 m×20 m,50 m×50 m,100 m×100 m,250 m×250 m)上的多度、物种丰富度、Shannon-Wiener指数、Simpson指数以及Pielou均匀度指数的变化规律。结果表明:物种多样性指数的空间分布均表现出较高的空间异质性;物种多样性指数的方差随取样尺度增加呈现单峰分布特征,并且在100 m×100 m尺度上达到最大值;物种多样性指数的变异系数随尺度的增加呈线性下降趋势,其中,Shannon-Wiener指数、Simpson指数以及Pielou均匀度指数均在5 m×5 m至20 m×20 m尺度上明显减小;在大于50 m×50 m的尺度上,物种丰富度与多度的正相关性不显著(P0.05)。喀斯特常绿落叶阔叶混交林物种多样性的空间分布格局与不同空间尺度密切相关,深入解析物种多样性随空间尺度的变化模式,需要在类似的森林生态系统做更多的研究。     

芦芽山寒温性针叶林冠层下植被beta多样性格局及其成因

群落构建机制是生态学的中心议题之一。对山地植被beta多样性格局及其成因的探究有助于加深对此问题的认识。以芦芽山寒温性针叶林群落冠层下植被为研究对象,结合野外调查与室内实验获取的详细数据,运用Mantel检验、普通最小二乘回归和典范对应分析(CCA)等统计方法,探讨了林下植被的beta多样性格局及其成因,结果显示:(1)沿海拔梯度相邻群落间草本层物种周转率呈现递减格局,而灌木层变化规律不明显;(2)灌、草层beta多样性与海拔差异、地理距离呈显著正相关关系,而与局地环境异质性关系不显著。控制海拔作用后发现,灌、草层beta多样性与地理距离关系依然显著,而当消除地理距离的线性影响后,beta多样性与海拔关系也变得不显著(3)CCA模型中,环境因子共解释了物种组成变异的74.4%,其中,海拔、坡度、凋落物厚度、乔木密度与总干面积对林下灌、草植被物种组成具有显著影响,但土壤因子的作用未见显著。综上,生境筛滤与扩散限制共同主导了芦芽山寒温性针叶林冠层下群落构建过程,但扩散限制的影响强于生境筛滤作用。     

Local and Regional Effects on Community Structure of Dung Beetles in a Mainland-Island Scenario

Understanding the ecological mechanisms driving beta diversity is a major goal of community ecology. Metacommunity theory brings new ways of thinking about the structure of local communities, including processes occurring at different spatial scales. In addition to new theories, new methods have been developed which allow the partitioning of individual and shared contributions of environmental and spatial effects, as well as identification of species and sites that have importance in the generation of beta diversity along ecological gradients. We analyzed the spatial distribution of dung beetle communities in areas of Atlantic Forest in a mainland-island scenario in southern Brazil, with the objective of identifying the mechanisms driving composition, abundance and biomass at three spatial scales (mainland-island, areas and sites). We sampled 20 sites across four large areas, two on the mainland and two on the island. The distribution of our sampling sites was hierarchical and areas are isolated. We used standardized protocols to assess environmental heterogeneity and sample dung beetles. We used spatial eigenfunctions analysis to generate the spatial patterns of sampling points. Environmental heterogeneity showed strong variation among sites and a mild increase with increasing spatial scale. The analysis of diversity partitioning showed an increase in beta diversity with increasing spatial scale. Variation partitioning based on environmental and spatial variables suggests that environmental heterogeneity is the most important driver of beta diversity at the local scale. The spatial effects were significant only at larger spatial scales. Our study presents a case where environmental heterogeneity seems to be the main factor structuring communities at smaller scales, while spatial effects are more important at larger scales. The increase in beta diversity that occurs at larger scales seems to be the result of limitation in species dispersal ability due to habitat fragmentation and the presence of geographical barriers.     

Beta diversity of stream diatoms at two hierarchical spatial scales: implications for biomonitoring

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Biome transitions as centres of diversity: habitat heterogeneity and diversity patterns of West African bat assemblages across spatial scales

It is widely accepted that species diversity is contingent upon the spatial scale used to analyze patterns and processes. Recent studies using coarse sampling grains over large extents have contributed much to our understanding of factors driving global diversity patterns. This advance is largely unmatched on the level of local to landscape scales despite being critical for our understanding of functional relationships across spatial scales. In our study on West African bat assemblages we employed a spatially explicit and nested design covering local to regional scales. Specifically, we analyzed diversity patterns in two contrasting, largely undisturbed landscapes, comprising a rainforest area and a forest‐savanna mosaic in Ivory Coast, West Africa. We employed additive partitioning, rarefaction, and species richness estimation to show that bat diversity increased significantly with habitat heterogeneity on the landscape scale through the effects of beta diversity. Within the extent of our study areas, habitat type rather than geographic distance explained assemblage composition across spatial scales. Null models showed structure of functional groups to be partly filtered on local scales through the effects of vegetation density while on the landscape scale both assemblages represented random draws from regional species pools. We present a mixture model that combines the effects of habitat heterogeneity and complexity on species richness along a biome transect, predicting a unimodal rather than a monotonic relationship with environmental variables related to water. The bat assemblages of our study by far exceed previous figures of species richness in Africa, and refute the notion of low species richness of Afrotropical bat assemblages, which appears to be based largely on sampling biases. Biome transitions should receive increased attention in conservation strategies aiming at the maintenance of ecological and evolutionary processes.     

Determinants of beta diversity of spiders in coastal dunes along a gradient of mediterraneity

Aim The Mediterranean Basin is recognized for its high levels of species richness, rarity and endemicity. Our main aim was to evaluate the relative effects of environmental and spatial variables and their scale‐specific importance on beta diversity patterns along a gradient of mediterraneity, using spiders as a model group. Location This study was carried out in 18 coastal dune sites along the Portuguese Atlantic coast. This area encompasses 445 km and comprises two distinct biogeographic regions, Eurosiberian (northern coast) and Mediterranean (centre and south). Methods A forward selection procedure was carried out to select environmental and spatial variables responsible for determining beta diversity patterns. Variation partitioning and principal coordinates of neighbour matrices (PCNM) were used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta diversity patterns and to estimate the relative importance of environmental structured variation and pure spatial variation at multiple spatial scales. Results Climate, ground vegetation dune cover and area were selected by a forward selection procedure. The same procedure identified three PCNM variables, all corresponding to large and medium spatial scales. Variation partitioning revealed that 46.1% of the variation of beta diversity patterns was explained by a combination of environmental and PCNM variables. Most of this variation (42.5%) corresponded to spatial variation (environmental spatially structured and pure spatial). Climate and vegetation structure influences were predominant at the PCNM1 and PCNM3 scales, while area was more important at the intermediate PCNM2 scale. Main conclusions Our study revealed that beta diversity of spiders was primarily controlled by a broad‐scale gradient of mediterraneity. The relative importance of environmental variables on the spider assemblage composition varied with spatial scale. This study highlights the need of considering the scale‐specific influence of niche and neutral processes on beta diversity patterns.     

Woody plant composition of forest layers: the importance of environmental conditions and spatial configuration

The species–environment relationships for woody species may vary according to the forest layers considered. In fragmented forest, spatial configuration may also influence forest layer composition. We investigated the relationships between four forest layer compositions and environmental conditions, and spatial variables accounting for forest fragmentation, in 59 forest stands. Field and shrub layer compositions were mainly linked to environmental conditions, particularly to soil pH and slope aspect, while the upper layer compositions were principally correlated to the spatial configuration. The distance from the forest edge was correlated with all the forest layer compositions. Our results suggest that woody species respond to factors acting at different spatial and temporal scales, depending on the forest layer they belong to. The species–environment relationship seems to weaken from the lower to upper layer, the upper layer being more closely linked to the spatial configuration and probably to the past management. This study underlines the importance of taking spatial configuration in addition to environmental conditions into account when studying woody plant diversity for different forest layers in stands located in deciduous fragmented forests. Moreover, stand history seems to have a lasting effect on woody plant composition, particularly for the tree layer.     

Does environmental heterogeneity drive functional trait variation? A test in montane and alpine meadows

While community‐weighted means of plant traits have been linked to mean environmental conditions at large scales, the drivers of trait variation within communities are not well understood. Local environmental heterogeneity (such as microclimate variability), in addition to mean environmental conditions, may decrease the strength of environmental filtering and explain why communities support different amounts of trait variation. Here, we assess two hypotheses: first, that more heterogeneous local environments and second, that less extreme environments, should support a broader range of plant strategies and thus higher trait variation. We quantified drivers of trait variation across a range of environmental conditions and spatial scales ranging from sub‐meter to tens of kilometers in montane and alpine plant communities. We found that, within communities, both environmental heterogeneity and environmental means are drivers of trait variation. However, the importance of each environmental factor varied depending on the trait. Our results indicate that larger‐scale trait–climate linkages that hold across communities also apply at small spatial scales, suggesting that microclimate variation within communities is a key driver of community functional diversity. Microclimatic variation provides a potential mechanism for helping to maintain diversity in local communities and also suggests that small‐scale environmental heterogeneity should be measured as a better predictor of functional diversity.     

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem‐mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best‐explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad‐leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.     

Environmental and spatial drivers of spider diversity at contrasting microhabitats

The relative importance of environmental and spatial drivers of animal diversity varies across scales, but identifying these scales can be difficult if a sampling design does not match the scale of the target organisms' interaction with their habitat. In this study, we quantify and compare the effects of environmental variation and spatial proximity on ground‐dwelling spider assemblages sampled from three distinct microhabitat types (open grassland, logs, trees) that recur across structurally heterogeneous grassy woodlands. We used model selection and multivariate procedures to compare the effects of different environmental attributes and spatial proximity on spider assemblages at each microhabitat type. We found that species richness and assemblage composition differed among microhabitat types. Bare ground cover had a negative effect on spider richness under trees, but a positive effect on spider richness in open grassland. Turnover in spider assemblages from open grassland was correlated with environmental distance, but not geographic distance. By contrast, turnover in spiders at logs and trees was correlated with geographic distance, but not environmental distance. Our study suggests that spider assemblages from widespread and connected open grassland habitat were more affected by environmental than spatial gradients, whereas spiders at log and tree habitats were more affected by spatial distance among these discrete but recurring microhabitats. Deliberate selection and sampling of small‐scale habitat features can provide robust information about the drivers of arthropod diversity and turnover in landscapes.