漓江河岸带木本植物功能性状跨尺度变异研究

研究植物功能性状变异,有助于揭示植物对环境的适应策略以及群落构建机制。以漓江河岸带木本植物为研究对象,利用广义线性模型和"varcomp"函数对漓江河岸带主要木本植物的3个叶功能性状（比叶面积SLA;叶面积LA;叶厚度LTH）跨不同尺度（样方、物种、个体、叶）变异进行方差分解,分析各尺度的相对贡献及变异的主要来源。结果表明：（1）植物功能性状在4个巢式尺度的解释方差规律较一致,均表现为物种（0.51-0.70） > 个体（0.21-0.22） > 叶和残差（0.09-0.20） > 样方（0-0.07）;（2）4个功能性状种间尺度的解释方差均最大（SLA、LA和LTH分别为64%、70%和51%）;其次种内尺度的解释方差（SLA、LA和LTH分别为34%、30%和42%）仅次于种间。（3）样方尺度的解释方差很小甚至为零。发现：（1）植物功能性状变异主要由种间变异驱动;（2）种内性状变异是功能性状变异的重要且不容忽视的来源;（3）生境过滤并非直接作用于群落间物种组成,而可能是通过直接作用于植物功能性状的总体分布来影响植物群落构建过程,基于功能性状的生境过滤可能在漓江河岸带植物群落构建中起重要作用。     

不同生境下福寿螺的可量性状特征、种群结构和密度效应

对广东省11个地区中4种不同生境下福寿螺(Pomacea canaliculata)种群的可量性状特征、年龄结构、性比和密度效应进行了对比研究。结果表明:福寿螺的可量性状特征在不同生境之间存在显著差异(P0.05),体重与壳高之间关系符合异速生长方程,且不同生境下有不同的异速指数;福寿螺种群在不同生境条件下有不同的年龄结构,稻田、沟渠中种群表现为增长型,废田、池塘中种群表现为稳定型;生境因素对福寿螺的性比没有显著影响(P0.05),但对性比与体重的关系影响显著(P0.05);福寿螺种群增长受密度制约,不同生境下的密度制约效应存在差异,沟渠中最小,池塘中最大,稻田和废田居中。本研究表明,生境条件对福寿螺的可量性状特征、种群结构均有显著的影响,不同生境下福寿螺种群的增长潜力也不同,需要制定有针对性的防控措施。     

表型可塑性与外来植物的入侵能力

外来植物的入侵能力与其性状之间的关系是入侵生态学中的基本问题之一。成功的入侵种常常能占据多样化的生境,并以广幅的环境耐受性为特征。遗传分化(包括生态型分化)和表型可塑性是广布性物种适应变化、异质性生境的两种不同但并不矛盾和排斥的策略。越来越多的实验证据表明,表型可塑性具有确定的遗传基础,本身是一种可以独立进化的性状。许多入侵种遗传多样性比较低,但同时又占据了广阔的地理分布区和多样化的生境,表型可塑性可能在这些物种的入侵成功和随后的扩散中起到了关键作用。本文首先介绍表型可塑性的含义,简述表型可塑性和生物适应的关系,然后从理论分析和实验证据两个方面论述了表型可塑性与外来植物入侵能力的相关性,最后针对进一步的研究工作进行了讨论。当然,并非所有入侵种的成功都能归因于表型可塑性,作者认为对于那些遗传多样性比较低同时又占据多样化生境的入侵种,表型可塑性和入侵能力的正相关可能是一条普遍法则,而非特例。     

生境破碎化对动物种群存活的影响

生境破碎是生物多样性下降的主要原因之一。通常以岛屿生物地理学、异质种群生物学和景观生态学的理论来解释不同空间尺度中生境破碎化的生态学效应。生境破碎化引起面积效应、隔离效应和边缘效应。这些效应通过影响动物种群的绝灭阈值、分布和多度、种间关系以及生态系统过程,最终影响动物种群的存活。野外研究表明,破碎化对动物的影响,因物种、生境类型和地理区域不同而有所变化,因此,预测物种在破碎生境中的存活比较困难。研究热点集中于：确定生境面积损失和生境斑块的空间格局对破碎景观中物种绝灭的相对影响,破碎景观中物种的适宜生境比例和绝灭阈值,异质种群动态以及生态系统的生态过程。随着3S技术的发展,生境破碎化模型趋于复杂,而发展有效的模型和验证模型将成为一项富有挑战性的任务。     

外来植物成功入侵的生物学特征

外来植物的入侵能力与其性状之间的关系是入侵生态学中的基本问题之一.成功的入侵种常常能占据多样化的生境,具有较强的适应性、繁殖力和散布力.表型可塑性和遗传分化是外来入侵植物对生境异质性的两种适应策略;散布体多态型和散布途径多种化,使外来入侵植物迅速占领入侵生境,并进行远距离扩散;无性生殖和有性生殖并存,并根据生境和入侵阶段权衡的繁育对策不仅使入侵种群大面积暴发成为可能,而且直接影响散布机制并对种群遗传结构具有调节作用.高效的资源利用性竞争,加之以化感作用为基础的干扰性竞争使植物更具入侵性.     

福寿螺入侵机制的研究进展

福寿螺(Pomacea canaliculata)是被世界自然保护联盟列入全球100种恶性外来入侵物种中唯一的一种淡水螺,已在世界范围内造成了严重的农业与生态危害。福寿螺适应性广、抗逆性强、繁殖率高、遗传多样性丰富等特点使其在新栖息地(尤其是脆弱生境)能够获得对土著种的竞争优势,并迅速建立扩大种群;福寿螺对天敌、寄生虫和病菌的防御为其生存和繁衍提供了保障;福寿螺的入侵降低了入侵地的生物多样性,并且形成恶性循环。本文从福寿螺的生态耐受性、种群遗传变异与繁殖增长、对入侵地其他生物的防御与竞争以及入侵地的生态脆弱性等4个方面对福寿螺的入侵机制进行了归纳和总结,并指出了未来在福寿螺入侵机制方面应着重研究的方向,旨在为福寿螺的预防控制提供基础资料及参考依据。     

北京暖温带次生林种群分布格局与种间空间关联性

种群分布格局和种间空间关联性研究有助于深入理解物种共存机制.本研究在北京地区5个1 ha典型暖温带森林样地,在0-50 m尺度范围内综合分析了常见种的种群分布格局及成年树种问的空间关联性.研究发现:(1)所有检验的物种都表现了聚集格局,主要发生在较小(0-15 m)的尺度范围内,并且同种聚集强度峰值普遍出现在目标个体周围1 m的距离内;在>15 m的较大尺度上,随着尺度增加,随机和规则格局成为物种分布的主要形式;(2)种间不相关联的比例高(～50%),即使种间存在显著的关联性,也是以隔离和部分重叠为主要的关联形式;很少的物种对(～4%)呈混合分布.种子扩散限制和牛境异质性在某种程度上解释了种群普遍聚集的格局,种群聚集分布又促使种间分布不相关联,或者种间呈现隔离和部分重叠格局,反映了物种分布与生境存在紧密的关联性.另外,种间隔离的格局会阻止种间个体相互竞争.然而,由于同种个体聚集分布,密度制约成为调节种群分布的主要形式.本结果将有助于揭示森林群落物种共存的潜在维持机制.     

广东省福寿螺形态性状变异及其与体质量的关系

【背景】福寿螺是危害极其严重的入侵我国的水生生物,目前利用相关分析、通径分析对福寿螺形态性状变异的研究较少。【方法】随机采集7个地区的福寿螺(雌雄比例差别很大),测量其壳高、壳宽、口宽、层高4个形态性状和体质量,采用相关分析、通径分析方法计算福寿螺的各形态指标变异系数、相关系数和通径系数,剔除对体质量影响不显著的指标,确定每个地区与体质量最相关的指标。【结果】除惠州之外,其余地区福寿螺的壳高和壳宽与体质量的相关性较高,且口宽与壳高共同作用对体质量的直接影响很大。【结论与意义】此结果为研究不同生境、不同温度下福寿螺的形态性状变异程度奠定了基础,同时为福寿螺形态鉴定、分类及其灾害预测预报提供了基础数据。     

玫瑰种群生物学研究进展

玫瑰(Rosa rugosa Thunb.)原产于我国东部沿海、日本、朝鲜半岛和俄罗斯远东地区,18世纪作为园艺种引入欧洲后逃逸并入侵至北海和波罗的海周边多个国家以及北美沙质海岸,而中国野生种群却在过去30年间持续萎缩,成为珍稀濒危物种。从玫瑰种群生物学角度,通过文献比较和综合,在阐明玫瑰生态学特性和野生分布变化的基础上,全面论述了玫瑰种群在我国的生境退化、种群动态、种子繁殖、遗传多样性、濒危机理、保育方面的成果和悬疑问题;并结合欧洲入侵种群分布范围和敏感生境、对本地群落和物种的影响、种子繁殖、遗传变异、种群扩张和模拟预测、管理和控制方面的研究进展,分析了濒危种群和入侵种群数量动态、群落组成、幼苗更新、遗传变异、管理策略方面的差异及其影响因素;进而提出未来的玫瑰研究可从濒危种群和入侵种群的比较研究、种群和灌丛的动态监测、适合度相关性状的变异及其遗传基础、基于种群生物学的保育或控制4个方面为切入点,集中探索玫瑰种群濒危和入侵动态的规律、遗传基础和主要驱动力,为玫瑰保育和管理提供理论依据,为相似物种的适应和进化机制研究提供例证。     

外来入侵生物福寿螺与本地生物的互作影响研究进展

福寿螺作为一种恶性的水生入侵动物, 通常进入新生境后, 种群迅速增长, 大量取食本地植物, 与本地物种形成竞争,进而对当地的生物多样性造成全方位影响。在查阅国内外研究成果基础上, 综述了福寿螺在入侵地与所处生境中本地生物(植物、动物和微生物)之间的相互影响与相关效应, 旨在为福寿螺的生态风险评估和防控提供参考。     

Environmental and Ontogenetic Effects on Intraspecific Trait Variation of a Macrophyte Species across Five Ecological Scales

Although functional trait variability is increasingly used in community ecology, the scale- and size-dependent aspects of trait variation are usually disregarded. Here we quantified the spatial structure of shoot height, branch length, root/shoot ratio and leaf number in a macrophyte species Potamogeton maackianus, and then disentangled the environmental and ontogenetic effects on these traits. Using a hierarchical nested design, we measured the four traits from 681 individuals across five ecological scales: lake, transect, depth stratus, quadrat and individual. A notable high trait variation (coefficient variation: 48–112%) was observed within species. These traits differed in the spatial structure, depending on environmental factors of different scales. Shoot height and branch length were most responsive to lake, transect and depth stratus scales, while root/shoot ratio and leaf number to quadrat and individual scales. The trait variations caused by environment are nearly three times higher than that caused by ontogeny, with ontogenetic variance ranging from 21% (leaf number) to 33% (branch length) of total variance. Remarkably, these traits showed non-negligible ontogenetic variation (0–60%) in each ecological scale, and significant shifts in allometric trajectories at lake and depth stratus scales. Our results highlight that environmental filtering processes can sort individuals within species with traits values adaptive to environmental changes and ontogenetic variation of functional traits was non-negligible across the five ecological scales.     

Spatial variation in adult sex ratio across multiple scales in the invasive golden apple snail,Pomacea canaliculata

Adult sex ratio (ASR) has critical effects on behavior and life history and has implications for population demography, including the invasiveness of introduced species. ASR exhibits immense variation in nature, yet the scale dependence of this variation is rarely analyzed. In this study, using the generalized multilevel models, we investigated the variation in ASR across multiple nested spatial scales and analyzed the underlying causes for an invasive species, the golden apple snail Pomacea canaliculata. We partitioned the variance in ASR to describe the variations at different scales and then included the explanatory variables at the individual and group levels to analyze the potential causes driving the variation in ASR. We firstly determined there is a significant female‐biased ASR for this species when accounting for the spatial and temporal autocorrelations of sampling. We found that, counter to nearly equal distributed variation at plot, habitat and region levels, ASR showed little variation at the town level. Temperature and precipitation at the region level were significantly positively associated with ASR, whereas the individual weight, the density characteristic, and sampling time were not significant factors influencing ASR. Our study suggests that offspring sex ratio of this species may shape the general pattern of ASR in the population level while the environmental variables at the region level translate the unbiased offspring sex ratio to the female‐biased ASR. Future research should consider the implications of climate warming on the female‐biased ASR of this invasive species and thus on invasion pattern.     

Trait variation and functional diversity maintenance of understory herbaceous species coexisting along an elevational gradient in Yulong Mountain,Southwest China

Characterizing trait variation across different ecological scales in plant communities has been viewed as a way to gain insights into the mechanisms driving species coexistence. However, little is known about how changes in intraspecific and interspecific traits across sites influence species richness and community assembly, especially in understory herbaceous communities. Here we partitioned the variance of four functional traits (maximum height, leaf thickness, leaf area and specific leaf area) across four nested biological scales: individual, species, plot, and elevation to quantify the scale-dependent distributions of understory herbaceous trait variance. We also integrated the comparison of the trait variance ratios to null models to investigate the effects of different ecological processes on community assembly and functional diversity along a 1200-m elevational gradient in Yulong Mountain. We found interspecific trait variation was the main trait variation component for leaf traits, although intraspecific trait variation ranged from 10% to 28% of total variation. In particular, maximum height exhibited high plasticity, and intraspecific variation accounted for 44% of the total variation. Despite the fact that species composition varied across elevation and species richness decreased dramatically along the elevational gradient, there was little variance at our largest (elevation) scale in leaf traits and functional diversity remained constant along the elevational gradient, indicating that traits responded to smaller scale influences. External filtering was only observed at high elevations. However, strong internal filtering was detected along the entire elevational gradient in understory herbaceous communities, possibly due to competition. Our results provide evidence that species coexistence in understory herbaceous communities might be structured by differential niche-assembled processes. This approach--integrating different biological scales of trait variation--may provide a better understanding of the mechanisms involved in the structure of communities.     

Trait variation and integration across scales: is the leaf economic spectrum present at local scales?

Trait‐based approaches have taken an increasingly dominant role in community ecology. Although trait‐based strategy dimensions such as the leaf economic spectrum (LES) have been identified primarily at global‐scales, trait variation at the community scale is often interpreted in this context. Here we argue from several lines of evidence that a research priority should be to determine whether global‐scale trait relationships hold at more local scales. We review recent literature assessing trait variation at smaller scales, and then present a case study exploring the relationship between the correlation strength of leaf traits and their similarity in variation structure across ecological scales. We find that the correlation strength between pairs of leaf traits does not predict whether the traits respond similarly to different drivers of variation. Instead, correlation strength only sets an upper bound to the dissimilarity in trait variation structure. With moderate correlation strengths, LES traits largely retain the ability to respond independently to different drivers of phenotypic variation at different scales. Recent literature and our results suggest that LES relationships may not hold at local scales. Clarifying under what conditions and at which scales the LES is consistently expressed is necessary for us to make the most of the emerging trait toolbox.     

Individual‐level leaf trait variation and correlation across biological and spatial scales

Even with increasing interest in the ecological importance of intraspecific trait variation (ITV) for better understanding ecological processes, few studies have quantified ITV in seedlings and assessed constraints imposed by trade‐offs and correlations among individual‐level leaf traits. Estimating the amount and role of ITV in seedlings is important to understand tree recruitment and long‐term forest dynamics. We measured ten different size, economics, and whole leaf traits (lamina and petiole) for more than 2,800 seedlings (height ≥ 10 cm and diameter at breast height < 1 cm) in 283 seedling plots and then quantified the amount of ITV and trait correlations across two biological (intraspecific and interspecific) and spatial (within and among plots) scales. Finally, we explored the effects of trait variance and sample size on the strength of trait correlations. We found about 40% (6%–63%) variation in leaf‐level traits was explained by ITV across all traits. Lamina and petiole traits were correlated across biological and spatial scales, whereas leaf size traits (e.g., lamina area) were weakly correlated with economics traits (e.g., specific lamina area); lamina mass ratio was strongly related to the petiole length. Trait correlations varied among species, plots, and different scales but there was no evidence that the strength of trait relationships was stronger at broader than finer biological and spatial scales. While larger trait variance increased the strength of correlations, the sample size was the most important factor that was negatively related to the strength of trait correlations. Our results showed that a large amount of trait variation was explained by ITV, which highlighted the importance of considering ITV when using trait‐based approaches in seedling ecology. In addition, sample size was an important factor that influenced the strength of trait correlations, which suggests that comparing trait correlations across studies should consider the differences in sample size.     

Within‐species patterns challenge our understanding of the leaf economics spectrum

The utility of plant functional traits for predictive ecology relies on our ability to interpret trait variation across multiple taxonomic and ecological scales. Using extensive data sets of trait variation within species, across species and across communities, we analysed whether and at what scales leaf economics spectrum (LES) traits show predicted trait–trait covariation. We found that most variation in LES traits is often, but not universally, at high taxonomic levels (between families or genera in a family). However, we found that trait covariation shows distinct taxonomic scale dependence, with some trait correlations showing opposite signs within vs. across species. LES traits responded independently to environmental gradients within species, with few shared environmental responses across traits or across scales. We conclude that, at small taxonomic scales, plasticity may obscure or reverse the broad evolutionary linkages between leaf traits, meaning that variation in LES traits cannot always be interpreted as differences in resource use strategy.     

桂林岩溶石山青冈群落植物功能性状的尺度变化与关联

研究植物功能性状在不同尺度的变异和关联,对于揭示植物对环境的适应策略和群落构建规律具有重要意义。以岩溶石山青冈群落为研究对象,测量了研究区内20个样方74种木本植物的叶面积、比叶面积和木材密度3个功能性状值,利用性状梯度分析法分析了3个性状在群落内部(α组分)及群落间(β组分)的变异格局及相关性。结果表明:(1)群落内3个植物功能性状的α值范围均大于β值范围,即物种相对于共生物种性状值的变化大于沿着群落平均性状梯度的变化。(2)植物功能性状比叶面积的种内差异引起的变化小于群落水平。(3)叶面积与比叶面积、比叶面积与木材密度、叶面积与木材密度的β组分相关性均最强,而α组分间无相关性或相关性较弱,即叶面积与比叶面积、比叶面积与木材密度、叶面积与木材密度两两性状间的相关性在群落间的依赖程度比群落内共生物种的依赖性要强,暗示物种在群落内和群落间采取不同的生态策略来适应环境。     

The importance of spatial scale for trait–abundance relations

The concept of community assembly through trait‐based environmental filtering has played a key role in our understanding of how communities change over space and time, however, the importance of spatial scale in the filtering process remains unclear. We propose that different environmental filters may operate at different spatial scales, and that filters at finer scales would be nested within those acting at coarser scales. We tested for the existence of spatially nested sets of trait‐based filters in a temperate native grassland by applying the recently proposed maximum entropy (MaxEnt) approach to trait‐based community assembly, which we extend through a trait selection procedure. We found that different traits were important in influencing the abundances of species at the three different spatial scales examined (micro‐habitat, habitat, landscape), supporting the idea that trait based filtering processes operating at coarse spatial scales can be quite distinct from those operating at fine scales. Despite this result, we identified several traits which were frequently related to abundance at all spatial scales. Taken together, our results support the proposition that trait‐based environmental filters at finer spatial scales are nested within those operating at coarser scales. We compared our results to those obtained using a simpler trait‐by‐trait analytical approach (correlation analysis and MaxEnt on individual traits). The capacity for MaxEnt to incorporate multiple traits simultaneously provided unique insights into the important traits at each spatial scale and presents significant advantages over existing univariate and multivariate approaches.     

cati: an R package using functional traits to detect and quantify multi‐level community assembly processes

Community ecologists are active in describing species by their functional traits, quantifying the functional structure of plant and animal assemblages and inferring community assembly processes with null‐model analyses of trait distribution and functional diversity indices. Intraspecific variation in traits and effects of spatial scale are potentially important in these analyses. Here, we introduce the R package cati (Community Assembly by Traits: Individuals and beyond) available on CRAN, for the analysis of community assembly with functional traits. cati builds on a recent approach to community assembly that explicitly incorporates individual differences in community assembly analyses and decomposes phenotypic variations across scales and organizational levels, based on three phenotypic variance ratios, termed the T‐statistics. More generally, the cati package 1) calculates a variety of single‐trait and multi‐trait indices from interspecific and intraspecific trait measures; 2) it partitions functional trait variation among spatial and taxonomic levels; 3) it implements a palette of flexible null models for detecting non‐random patterns of functional traits. These patterns can be used to draw inferences about hypotheses of community assembly such as environmental filtering and species interactions. The basic input for cati is a data frame in which columns are traits, rows are species or individuals, and entries are the measured trait values. The cati package can also incorporate a square distance matrix into analyses, which could include phylogenetic or genetic distances among individuals or species. Users select from a variety of functional trait metrics and analyze these relative to a null model that specifies trait distributions in a regional source pool.     

Integrating trait and phylogenetic distances to assess scale‐dependent community assembly processes

Biodiversity is structured by multiple mechanisms that are dependent, at least in part, on ecological similarities and differences among species. Integrating traits and phylogenies in diversity metrics may provide deeper insight into community assembly processes across spatial scales. However, different traits are influenced by processes at different spatial scales, and it is not clear how trait‐spatial scale mismatches skew our ability to detect assembly patterns. An additional complexity is how phylogenetic distances, which might capture unmeasured traits, reflect spatially dependent processes. Here we analyze a freshwater zooplankton dataset from 91 ponds and show that different traits are associated with processes at different spatial scales. We first assessed the response of individual traits to processes at both α‐ and β‐scales, and then quantified the power of different combinations of traits and phylogenetic distances to reveal environmental and spatial drivers of α‐ and β‐diversity. We found that explanatory power was maximised when we accounted for environmental and spatial drivers with single, but different traits for α‐ and β‐diversity. Using the most appropriate trait for each spatial scale outperformed phylogenetic information, but phylogenetic information outperformed the same traits when these were used at the wrong spatial scale, and all outperformed taxonomic analyses that ignore trait and phylogenetic information. We demonstrate that accounting for species’ similarities and differences provides important information about dominant assembly mechanisms at different spatial scales, and that phylogeny is especially useful when measured traits are uninformative at a given spatial scale or when there is lack of trait data. Our study also indicates, however, that trait‐scale mismatches among phylogenetically conserved traits may affect the performance of phylogenetic indices compared to indices that account only for the best single trait at each spatial scale.