基于不同零模型的点格局分析

在种群空间格局研究中,定量分析格局及其形成过程已成为生态学家的主要目标。在量化分析的众多方法中,点格局分析是最常用的方法,而在选择零模型时,完全空间随机模型以外的复杂零模型很少使用,实际上,这些零模型可能有助于认识格局的内在特征。为此,我们在研究实例中,选择完全空间随机模型(complete spatial randomness)、泊松聚块模型(Poisson cluster process)和嵌套双聚块模型(nested double-cluster process)对典型草原处于不同恢复演替阶段的羊草(Leymus chinensis)种群空间格局进行了分析。结果发现:完全空间随机模型仅能检测种群在不同尺度下的格局类型;而通过泊松聚块模型和嵌套双聚块模型检验表明,在恢复演替的初期阶段,羊草种群在小尺度范围内偏离泊松聚块模型,而在整个取样范围内完全符合嵌套双聚块模型;随着恢复演替时间的推移,在恢复演替的后期,在整个取样尺度上,羊草种群与泊松聚块模型相吻合。这是很有意义的生态学现象。这一实例表明在应用点格局分析种群空间格局时,仅通过完全空间随机模型的检验来分析格局特征,或许很难论证复杂的生态过程,而选择一些完全空间随机模型以外的较复杂的零模型,可能发现一些有价值的生态学现象,对揭示格局掩盖下的内在机制有所裨益。     

不同恢复演替阶段糙隐子草种群的点格局分析

采用摄影定位法测定了羊草+大针茅草原不同恢复演替群落中糙隐子草种群的空间格局,并应用完全空间随机模型、泊松聚块模型和嵌套双聚块模型对其格局进行分析.结果表明:在严重退化的群落中,糙隐子草种群格局表现为嵌套双聚块结构,即在大聚块中分布着较高密度的小聚块;在恢复5年、8年和21年的群落中,则为以母体为中心的泊松聚块结构,即在糙隐子草种群空间格局的聚块中不存在较高密度的小聚块.这说明在严重退化的群落中正相互作用居主导,而在恢复演替群落中负相互作用居主导.糙隐子草种群在恢复演替过程中的格局变化主要是由于伴随放牧胁迫的消失,种群正相互作用(易化)向负相互作用(竞争)转化所致.     

基于不同零模型的三江平原沼泽湿地主要物种小尺度点格局分析

在三江平原沼泽湿地,基于不同零模型的点格局方法,研究了常年积水环境条件下沼泽湿地主要优势种毛苔草、漂筏苔草、狭叶甜茅以及小叶章种群的空间分布格局特征。结果表明:在0—200cm尺度范围内4种物种基本都偏离完全随机模型,表现为聚集分布,但偏离的程度不同;除了数量最少的小叶章种群外,其他3种物种都在一定尺度上偏离了泊松聚块模型;毛苔草和狭叶甜茅种群在极小尺度上偏离嵌套双聚块模型,但不显著,而漂筏苔草种群在所有尺度上符合嵌套双聚块模型。种群的实测值偏离完全随机模型的程度越大,越有可能符合符合泊松聚块模型,偏离泊松聚块模型的程度越大,越有可能符合嵌套双聚块模型。4种物种在0—200cm尺度范围内形成的聚块是由营养繁殖引起的,多个分株系统组成大聚块,而每个分株系统形成一个小聚块,聚块的形成加剧了种内竞争,使得种群的聚集强度降低。     

典型草原退化群落不同恢复演替阶段羊草种群空间格局的比较

羊草(Leymus chinensis)为典型草原群落的主要建群种之一, 在群落中扮演着重要角色。应用摄影定位法测定处于不同恢复演替阶段的羊草种群空间格局, 通过点格局、种群空斑、种群领地及种群领地密度等方法分析发现, 羊草种群在恢复演替过程中经历了种群增长和种群衰退的过程。在此过程中, 羊草种群数量出现最高点, 此点之前, 种群拓殖大于自疏, 种群整体增长; 此点之后, 种间竞争及种内竞争致使种群衰退, 而种间竞争占主导地位, 种内竞争相对较弱。羊草种群的增衰导致种群空斑发生变化, 从而引起种群格局类型发生相应的变化, 表现为在恢复21 a的群落中, 羊草种群在10 m×10 m的取样范围内表现出两种格局分布类型: 在0~4.85 m之间呈现聚集分布, 当尺度大于4.85 m时, 则表现为随机分布; 在恢复8 a的群落中, 羊草种群在10 m×10 m的取样范围内出现3种格局分布类型: 在0~3.01 m之间呈聚集分布, 在3.01~3.37 m之间为随机分布, 当尺度大于3.37 m时则表现为均匀分布; 在严重退化群落中, 羊草种群在整个10 m×10 m测定尺度上呈现聚集分布。由此可见, 羊草种群格局在恢复演替过程中是变化的, 这种变化主要由群落剩余资源驱动下的种群拓殖及种内种间竞争所致。     

基于零模型的宁夏荒漠草原优势种群点格局分析

植物种群空间分布格局是多种生态过程综合作用的结果。明确植物优势种群个体的空间分布格局与形成机制有助于认识种群生态适应对策与群落多样性维持机制。以宁夏荒漠草原优势种群蒙古冰草、短花针茅、牛枝子和牛心朴子为研究对象,采用完全空间随机零模型分析其种群空间分布格局特征,并通过异质泊松零模型与泊松聚块零模型探讨生境异质性、扩散限制等因子在其空间分布格局形成过程中的作用。结果显示:(1)完全空间随机零模型下,4个物种在<4 m尺度范围内表现为聚集分布,随尺度增大,逐渐过渡到随机分布和均匀分布。(2)在排除生境异质性的异质泊松零模型下,蒙古冰草种群在整个研究尺度上表现为随机分布;牛枝子、短花针茅和牛心朴子种群仅分别在0—0.2、0.1—0.4 m与0—0.2 m尺度范围内发生偏离,表现为均匀分布与聚集分布,其他尺度均为随机分布。(3)在排除扩散限制的泊松聚块零模型下,所研究种群均表现为随机分布。综上,荒漠草原优势种群在小尺度范围内主要表现为聚集分布;生境异质性与扩散限制均是驱动其空间分布格局形成的重要因子,相对而言,小尺度空间范围内扩散限制的作用更为显著。     

荒漠草原不同土壤条件下猪毛蒿幼苗种群的点格局分析

采用摄影定位法测定了宁夏荒漠草原3种不同土壤条件下猪毛蒿（Artemisia scoparia）幼苗种群的空间格局,并应用完全空间随机模型、泊松聚块模型和嵌套双聚块模型对其分布格局进行了分析。结果表明：（1）在灰钙土生境下,猪毛蒿幼苗种群在小尺度上（0-2.85m）表现为聚集分布,随着尺度的增大先呈现为随机分布（2.85-3.75 m）,然后又呈现为均匀分布（3.75-5m）;在风沙土生境下,猪毛蒿幼苗种群在0-1.85 m之间表现为聚集分布,在1.85-2.35 m之间表现为随机分布,当尺度大于2.35 m时表现为均匀分布;而基岩风化残积土上的猪毛蒿幼苗种群在整个尺度上均呈现随机分布。（2）猪毛蒿种群幼苗在基岩风化残积土上符合泊松聚块模型,即猪毛蒿种群空间格局的聚块中不存在较高密度的小聚块;而在风沙土和灰钙土上则符合嵌套双聚块模型,即在大聚块中分布较高密度的小聚块。猪毛蒿幼苗种群空间格局的形成与土壤异质性存在着密切的联系,种群在空间中分布格局的形成机制可以通过种群空间格局的分析加以解释。     

北京山区栓皮栎林优势种群点格局分析

采用点格局分析方法对北京山区栓皮栎林主要种群和不同发育阶段种群的空间分布格局及相互关系进行分析。结果表明:(1)群落物种组成简单,栓皮栎和油松是群落的优势种群,优势种群以中径木为主,缺乏可供更新的幼苗,种群呈现出衰退趋势;(2)在研究尺度内,栓皮栎、油松单种的空间分布格局以聚集型分布为主,随着尺度的增大呈现出随机分布和均匀分布的趋势;栓皮栎和油松呈现显著负相关;(3)优势种群不同发育阶段的空间分布格局与研究尺度紧密相关,栓皮栎小树和中树以聚集型分布为主、大树呈随机分布,而油松不同发育阶段均以随机分布为主;(4)栓皮栎、油松种群不同发育阶段之间的空间关联主要发生在小尺度范围内,小树和中树以正关联为主,而中树和大树、小树和大树以负关联为主;随着研究尺度的增大趋于无关联。     

蒙古栎次生林群落结构及优势种群点格局分析

为探求大小兴安岭过渡区物种共存、生物多样性保护与维持机制,以黑龙江中央站黑嘴松鸡国家级自然保护区蒙古栎天然次生林25 hm²固定样地调查数据为基础,从群落物种组成、结构特征、径级结构以及优势种群的空间点格局分析对该样地进行分析。结果表明：样地内共有胸径≥1 cm的维管植物10种,活立木共 34 778株,平均密度1 392株·hm^-2。其中,重要值大于10%的物种共计4种,依次为蒙古栎（Quercus mongolica Fisch.ex Ledeb.）、黑桦（Betula dahurica Pall.）、白桦（Betula platyphylla Suk.）、兴安落叶松（Larix gmelinii（Rupr.）Kuzen）,占全样地的89.65%。该样地的Shannon-Wiener多样性H′、Simpson多样性D、Pielou均匀度指数J分别为1.577、0.760、0.685。表明该群落稀有物种较少,常见种比例较大,群落结构较为简单。样地内所有树种平均胸径10.77 cm。群落内总径级分布呈“倒J型”,符合典型异龄林的分布特征。黑桦、白桦径级分布近似“倒J型”,属于增长种群,蒙古栎种群径级结构为双峰型。兴安落叶松种群径级近似正态分布,有随演替进行逐渐消失的趋势,属于该群落的衰退种。在CSR模型下,4种优势种群的空间格局主要表现为聚集分布,且聚集程度随尺度增加聚集程度减弱,最终呈现随机或均匀分布趋势。在NS模型下,除兴安落叶松外,其余3种植株在小尺度（0~5 m）表现聚集性,可能是受种子的扩散限制的影响。对比4种优势种群,聚集强度表现为黑桦＞白桦＞蒙古栎＞兴安落叶松,因此我们推断群落内不同种群的聚集强度不仅与研究尺度相关,与种群的多度也存在一定的相关关系。     

随机区块法在空间点格局分析中的应用

利用一种以随机模拟技术为基础的空间点格局分析方法--随机区块法对长白山阔叶红松林中5个主要树种的空间格局及空间关系进行了分析.随机区块法利用ICS(t)=s2(t)/x(t)-1来衡量不同尺度t上空间点的分布格局,并通过随机模拟技术构建零假设的95%或99%置信区间,以确定空间点格局偏离零假设的显著性程度.结果表明,除蒙古栎、山荆子、怀槐为随机分布外,其它树种均在局部空间尺度上呈聚集分布;并且绝大多数种对或种组在局部空间尺度上呈正相关关系.随机区块法克服了小样方统计法研究尺度单一的问题,也避免了以空间点距离为基础的点格局分析过程中边缘效应带来的影响和误差,尤其是在多变量点格局分析中具有明显的优势.     

内蒙古中东部草原大针茅的种群遗传分化

对内蒙古中东部草原区分布的 11个大针茅 (Stipa grandis P. Smirn)地理种群进行了 RAPD分析。从 10 0个随机引物中筛选出 18个有效引物 ,共扩增出 2 2 1条 DNA带 ,多态性 DNA带 12 1条 ,占 5 4 .75 % ,平均每个引物扩增的 DNA带数为 12 .2 8条 ;特异性 DNA带 2 5条 ,占 11.31%。基于 Jaccard遗传相似性系数对此 2 2 1条 DNA带进行 U PGMA聚类分析 ,将 11个种群分为 3类 ,白音锡勒牧场的 8个种群聚为一类 ,林西种群和克什克腾种群两个种群聚为一类 ,阿巴嘎种群单独成为第 3类。用Mantel检验作进一步分析表明 ,在相对较大的尺度上 ,大针茅的遗传分化与地理距离相关极显著 (g>g0 .0 0 5) ;而在相对较小的尺度上 (白音锡勒牧场 8个种群 ) ,相关不显著 (gg0 .0 5)。     

Caloric content of plant species and its role in a Leymus chinensis steppe community of Inner Mongolia, China

The caloric contents of 42 species and their composition in a Leymus chinensis steppe community of Inner Mongolia, China were determined and analyzed based on the field experiment for 11 years. The caloric content (x ± SD) of aboveground parts of plant species varied from (13156 ± 1141) J·g^?1 (ash contained) to (18141 ± 527) J·g^?1. The average caloric content of all species was (16899 ± 840) J·g^?1 and the inter-specific CV (coefficient of variation) was 4.9%. Of all the species, Caragana microphylla had the highest caloric content (18142 J·g^?1). Grasses had a higher average caloric content ((17425 ± 291) J·g^?1) than forbs ((16734 ± 844)J·g^?1). When the herbaceous species were classified into subgroups according to life-form and growth-form, the order of average caloric contents, from high to low, was: tall grasses ((17717 ± 92) J·g^?1) > legume ((17228 ± 433) J·g^?1) > short grasses ((17250 ± 218) J·g^?1) > remaining forbs ((16784 ± 529) J·g^?1) > subshrubs ((16719 ± 69) J·g^?1) > annuals and biennials ((15911 ± 1759) J·g^?1). There was a positive correlation (P < 0.05) between the caloric contents of 42 species and their relative biomass in the community. When all species were classified into 3 groups according to their composition in the community, the average caloric contents, weighed by the species relative biomass, followed the order: dominant (17740 J·g^?1) > companion (17244 J·g^?1) > incidental (16653 J·g^?1). The plants with high caloric contents were more competitive, which allowed them to gain a dominant status, whereas the competitive abilities of plants with low caloric contents were generally weak. The latter made up the companion or incidental species in a steppe community.     

Two-dimensional pattern analysis on dominant species and community in subalpine meadow of Luya Mountain,Shanxi Province,China

The spatial pattern analysis of population and community is important to understand community structure and has become one key topic in modern plant ecology.There are many techniques for analyzing one-dimensional pattern in ecological literature.Two-dimensional pattern analysis is better than one-dimensional analysis in the study on community spatial characteristics and structure.However,it is hard to analyze these two-dimensional patterns due to poor effective methodology.The two-dimensional sampling using two transects that meet at right angles was applied to get quadrat data in this work.And then the data from the two transects were analyzed separately by one-dimensional pattern analysis method,two-term local quadrat variance.The length,width,and area of patches at different scales of pattern for populations were obtained from the analysis.For community pattern,detrended correspondence analysis (DCA)was employed to summarize the species information firstly,and then the first DCA axis scores were analyzed to check its pattern.The application of this method to the pattern analysis on dominant populations and community for subalpine meadow (Comm.Polygonum viviparum+Carex rigescens+Kobresia bellardii)in the Luya mountains showed that it could release the characteristics of spatial pattern clearly and was a very effective technique.The method is easy to use and saves time with obvious advantages,compared with the twodimensional pattern analysis methods presented in the literatures.In the study meadow,the patterns of the main dominant species,Polygonum viviparum,Carex rigescens,and Kobresia bellardii,were apparent and comparatively regular in shape with large areas of patches at the same scale compared with other species such as Festuca sp.and Thalictrum petaloideum.There were two or three scales of patterns for each plant population studied.This was related to population features,the interaction with environmental factors,and their dominant position in the community.The two scales of patterns for the meadow community were clear.The pattern of community was closely correlated with that of the main dominant species.The patches of dominant species were inter-distributed and overlapped,and formed the community pattern together.This is beneficial for utilization of resources,and keeping the community stable.     

Two-dimensional pattern analysis on dominant species and community in subalpine meadow of Luya Mountain, Shanxi Province, China

The spatial pattern analysis of population and community is important to understand community structure and has become one key topic in modern plant ecology. There are many techniques for analyzing one-dimensional pattern in ecological literature. Two-dimensional pattern analysis is better than one-dimensional analysis in the study on community spatial characteristics and structure. However, it is hard to analyze these two-dimensional patterns due to poor effective methodology. The two-dimensional sampling using two transects that meet at right angles was applied to get quadrat data in this work. And then the data from the two transects were analyzed separately by one-dimensional pattern analysis method, two-term local quadrat variance. The length, width, and area of patches at different scales of pattern for populations were obtained from the analysis. For community pattern, detrended correspondence analysis (DCA) was employed to summarize the species information firstly, and then the first DCA axis scores were analyzed to check its pattern. The application of this method to the pattern analysis on dominant populations and community for subalpine meadow (Comm. Polygonum viviparum + Carex rigescens + Kobresia bellardii) in the Luya mountains showed that it could release the characteristics of spatial pattern clearly and was a very effective technique. The method is easy to use and saves time with obvious advantages, compared with the two-dimensional pattern analysis methods presented in the literatures. In the study meadow, the patterns of the main dominant species, Polygonum viviparum, Carex rigescens, and Kobresia bellardii, were apparent and comparatively regular in shape with large areas of patches at the same scale compared with other species such as Festuca sp. and Thalictrum petaloideum. There were two or three scales of patterns for each plant population studied. This was related to population features, the interaction with environmental factors, and their dominant position in the community. The two scales of patterns for the meadow community were clear. The pattern of community was closely correlated with that of the main dominant species. The patches of dominant species were inter-distributed and overlapped, and formed the community pattern together. This is beneficial for utilization of resources, and keeping the community stable. __________ Translated from Acta Ecologica Sinica, 2005, 25(6): 1264–1268 [译自: 生态学报]     

芦芽山亚高山草甸优势种群和群落的二维格局分析

种群和群落的二维空间格局研究能够更好地揭示群落的空间和结构特征,但在分析方法上有较大的困难。用垂直相交的两条样带在两个方向上同时取样的二维取样法,获得数据,用一维格局分析方法分别分析,可以得到各个种不同格局规模斑块的长、宽及面积,实现二维格局研究。用DCA排序和格局分析方法相结合,可以完成群落的二维格局分析。在山西芦芽山亚高山草甸应用的结果表明这样的垂直样带二维取样及分析方法较好地反映了种群和群落的空间特性,是非常有效的,并且该方法简单易做,具有较大的可操作性。所研究的草甸主要优势种格局斑块的形状比较规则,面积也较大。次要种斑块多为不规则形,面积也较小。群落格局与主要优势种的格局关系密切。