Littoral macroinvertebrate communities: spatial scale and ecological relationships

SUMMARY 1. Spatial correlations between ecological patterns and processes are thought to be scale-dependent, yet surprisingly few studies have evaluated the correspondence between different levels of spatial scale and ecosystem structure and function.
2. We evaluated the strength of relationships between the benthic macroinvertebrate communities of stony littoral habitats and levels of ecological scale and geographical position, using partial constrained ordination. Our hypothesis was that correlation strength would be inversely related to ecological scale, i.e. habitat > ecosystem > riparian > catchment > ecoregion.
3. The effect of habitat was greater than that of other levels of spatial scale: 23% of the variance in taxonomic composition and 11% of that in functional composition was explained by habitat variables alone. However, greater spatial scales were also important. For example, the combined influence of riparian, catchment and ecoregion classification accounted for 24% (taxonomic) and 11% (functional) of the explained variance.
4. Relationships between organisms and scale variables were, however, non-linear and a substantial amount of the functional variance was hidden in joint effects. These findings were not unexpected, and presumably indicate a close interdependence between local and regional-scale variables.     

金沙江干旱河谷植物群落的数量分类及其结构分异的环境解释

植物群落的空间分异格局是异质生境条件下物种性状、种间相互作用等生态学过程共同作用的结果, 对其分析有助于深入理解群落构建进程。本文基于金沙江流域干旱河谷116个样点562个样方的植物群落调查数据, 采用自适应仿射传播聚类的方法进行群落数量分类, 运用莫兰特征向量地图, 和方差分解的方法对影响群落结构的空间和环境因子进行分析。结果表明: (1)自适应仿射传播聚类将金沙江干旱河谷的植物群落分为30组, 可归为7个植被型, 23个群系, 以稀树草原(30.0%)、暖性落叶阔叶灌丛(55.7%)为最主要的植被类型。(2)年均温和干燥指数是限制金沙江干旱河谷植物群落分布的主要环境因子。稀树草原、肉质灌丛、常绿阔叶灌丛是典型的干热河谷植被类型; 暖性落叶阔叶灌丛、常绿硬叶林是干暖河谷植被的优势类型; 暖性针叶林、落叶阔叶林则主要在干温河谷环境占优势。(3)纯环境因子可以解释群落物种组成变化的5.5%, 纯空间因子可以解释的物种组成变化为22.5%, 有空间结构的环境因子部分为6.6%, 未解释的部分为65.4%。在诸多环境因子中, 年均温及干燥指数的不同显示了不同群落生境的重要差异, 并显著影响到群落的分布格局。大尺度的空间因子则主要通过地理隔离对群落结构的差异产生影响。     

Influence of edaphic factors on the spatial structure of inland halophytic communities: a case study in China

Abstract. In order to understand the influence of edaphic factors on the spatial structure of inland halophytic plant communities, a 2.6 km² study site, located on the lower fringe of the alluvial fan of the Hutubi River, in an arid region of China, was sampled and mapped. 105 patches were found to be homogeneous in species composition. Plant species and their coverage were recorded in each patch. 45 patches were randomly selected for the measurement of edaphic variables. A map with quadrat locations and boundaries of patches was digitized into a GIS and related to the vegetation and edaphic data matrices. CCA was used to evaluate the relative importance of edaphic factors in explaining the variation of the species assemblages and to identify the ecological preferences of species. The spatial structure of the communities and the main edaphic factors were analyzed using correlograms, Mantel correlograms and clustering under constraint of spatial contiguity. Gradient analysis showed that there are two distinct vegetation gradients in the study area, one of which is determined mainly by soil moisture (determined by depth to the water table), and the other by soil salinity (determined by electrical conductivity and hydrolytic alkalinity of the first soil layer). However, spatial analyses showed that at the sampling scale the halophytic communities in the study area are structured along one main spatial gradient determined by the water table level. Similar spatial autocorrelation structures between the factors related to the first soil layer and the communities, given our sampling scale, could not be detected. Our results suggest that the relative importance of the effects of different edaphic factors on the spatial structure of halophytic communities is scale-dependent. The partitioning of species variation indicates that in addition to edaphic factors, other factors, such as biotic interactions, may play an important role in structuring these communities.     

长白山山杨种群的性比格局及其空间分布

以 5.2 hm²固定监测样地内山杨雌、雄植株的长期定位观测数据为基础,分析了长白山次生杨桦林内山杨(Populus davidiana)种群的性比格局、空间分布及其与环境因子间的关系。结果表明:山杨雌树和雄树的胸径大小差异不显著,始花大小相近,雄树的生长速率大于雌树,成熟个体的性比不显著偏离1 ∶ 1。山杨同性植株趋于相邻,雌雄植株的空间分离不显著;O-ring单变量点格局分析显示山杨在空间上呈异质性泊松分布。山杨同性别大树与小树在＜18m尺度上呈空间正相关;不同性别之间空间独立,说明性别之间的资源竞争不激烈。山杨雌树和雄树的空间分布与林分密度极显著正相关,林分密度对山杨雌雄植株空间分布变异的解释量较小,空间变量对雌树分布的解释量较大。     

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp ). Results Model selection based on cross‐validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross‐validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.     

Fine spatial grain,large spatial extent and biogeography of macrophyte‐associated cladoceran communities across Neotropical floodplains

相似文献   

Examining residual spatial correlation in variation partitioning of beta diversity in a subtropical forest

AimsThe relative roles of ecological processes in structuring beta diversity are usually quantified by variation partitioning of beta diversity with respect to environmental and spatial variables or gamma diversity. However, if important environmental or spatial factors are omitted, or a scale mismatch occurs in the analysis, unaccounted spatial correlation will appear in the residual errors and lead to residual spatial correlation and problematic inferences.     

Regeneration mode affects spatial genetic structure of Nothofagus dombeyi forests

Disturbance may generate population bottlenecks by reducing population size and the number of founders establishing a new colony. We tested the hypothesis that the scale of disturbance affects the levels of genetic diversity and the spatial distribution of genotypes in naturally regenerating stands of Nothofagus dombeyi, an evergreen angiosperm tree, in northwestern Patagonia. At similar spatial scales, we predicted that old-growth stands characterized by fine-scale gap phase dynamics would be genetically diverse due to restricted gene flow among temporal and spatially isolated gaps. In contrast, young massively regenerated postfire cohorts resulting from coarse-scale disturbances would be genetically more homogeneous. At each of three paired old-growth and postfire stands a minimum of 50 trees were mapped and sampled within 1 ha. Fresh tissue was collected for isozyme analysis from a total of 361 trees along with tree cores and diameters. Tree age distributions reflected the dominant modes of regeneration. Six out of nine analysed loci were polymorphic. Mean genetic diversity parameters were greater but not significant in mature stands. Fixation indices suggested significant heterozygous deficit at two-thirds of possible tests indicating a Wahlund effect due to local recruitment of related seeds. F(ST) indicated moderate between-stand divergence. Mature stands concentrated half of positively like joins and yielded significant (P < 0.05) autocorrelation coefficients at small distance classes (< 20 m). Fine-scale patch dynamics within mature stands favours the maintenance of fine-scale genetic structure as a result of shade intolerance and local seed dispersal. Conversely, postfire stands suffer the effects of genetic drift given that a few reproductive trees produce a somewhat impoverished and genetically uniform progeny. Bottleneck effects will depend upon the density of remnant trees which could also be a function of the severity of fire.     

基于ArcGIS的下辽河平原地下水脆弱性评价及空间结构分析

以下辽河平原为研究区,通过选取1991、2000和2010年3个代表年的相关参数,在DRASTIC模型基础上构建评价指标体系进行地下水脆弱性评价,并以地下水中氮元素浓度为响应指标通过显著性检验,在此基础上借助GS+、Arc GIS和Geoda095i等软件的制图功能和空间统计分析功能,对下辽河平原地下水脆弱性的空间分布特征、变异规律以及空间关联格局进行研究分析,结果表明:11991—2010年下辽河平原地下水脆弱性总体上呈先增后减趋势,空间分布上以沈阳市为中心的地下水高脆弱区向南部沿海方向扩散;21991—2010年研究区地下水脆弱性Moran's I表现为较强正相关现象,且关联程度呈略微下降趋势;31991—2010年研究区地下水脆弱性局部空间自相关和显著性水平均发生了明显的变化;4研究区内地下水脆弱性受结构性因素和随机性因素共同作用,且随机性因素在3个时期内有逐步上升趋势。研究成果反映了研究区地下水脆弱性空间结构的变异规律及驱动机制,为决策者在未来地下水污染防治方面提供相关参考依据。     

Environmental and spatial effects on coastal stream fishes in the Atlantic rain forest

Contemporary and historical factors influence assemblage structure. The environmental and spatial influences acting on fish organization of rain forest coastal streams in the Atlantic rain forest of Brazil were examined. Fish (and functional traits such as morphology, diet, velocity preference, body size), environmental variables (pH, water conductivity, dissolved oxygen, temperature, stream width, flow, depth, substrate), and altitude were measured from 59 stream reaches. Asymmetric eigenvector maps were used to model the spatial structure considering direction of fish movements. Elevation played an important role—fish abundance, biomass, and richness all decrease with increasing elevation. Fish communities are influenced by both environmental and spatial factors, but downstream movements were shown to be more important in explaining the observed spatial variation than were bidirectional and upstream movements. Spatial factors, as well as environmental variables influenced by the spatial structure, explained most of the variation in fish assemblages. The strong spatial structuring is probably attributable to asymmetric dispersal limitation along the altitudinal profile: Dispersal is likely to be more limiting moving upstream than downstream. These fish assemblages reflect scale-dependent processes: At the stream-reach scale, fish respond to local environmental filters (habitat structure, water chemistry, and food supply), which are in turn influenced by a larger scale, namely the altitudinal gradient expected in steep coastal mountains. Thus, environmental drivers are not independent of spatial factors, and the effects of local factors can be confounded across the altitudinal gradient. These results may have implications for conservation, because downstream reaches are often neglected in management and conservation plans.     

A comparison of simultaneous autoregressive and generalized least squares models for dealing with spatial autocorrelation

Aim  In their recent paper, Kissling & Carl (2008 ) recommended the spatial error simultaneous autoregressive model (SAR_err) over ordinary least squares (OLS) for modelling species distribution. We compared these models with the generalized least squares model (GLS) and a variant of SAR (SAR_vario). GLS and SAR_vario are superior to standard implementations of SAR because the spatial covariance structure is described by a semivariogram model.
Innovation  We used the complete datasets employed by Kissling & Carl (2008 ), with strong spatial autocorrelation, and two datasets in which the spatial structure was degraded by sample reduction and grid coarsening. GLS performed consistently better than OLS, SAR_err and SAR_vario in all datasets, especially in terms of goodness of fit. SAR_vario was marginally better than SAR_err in the degraded datasets.
Main conclusions  GLS was more reliable than SAR-based models, so its use is recommended when dealing with spatially autocorrelated data.     

Multiscale patterns of spatial variation in stream macroinvertebrate communities

Our ability to detect patterns of variation of communities depends on the spatial scale of observation. I examined the spatial variation of macroinvertebrate community structure: abundance, richness, evenness, percentage of Ephemeroptera, Plecoptera and Trichoptera (EPT), and taxonomic composition across a wide range of spatial scales in two mountain streams. In a nested design, three segments were selected within each basin, three riffles within each segment, three sections within each riffle, and three samples within each section. Significant variation of communities occurred mainly at sample and riffle scales, although different community characteristics may vary at different scales. Environmental factors were strongly related to communities, but these relationships depended on spatial scale in many cases, suggesting that the influence of the environment is ultimately regulated by the grain and extent of organisms. This study highlights the importance of multiscale studies to obtain a complete understanding of the spatial variation of macroinvertebrate communities and their relationship with the environment.     

三江平原湿地鸟类丰富度的空间格局及热点地区保护

全球气候变化和人类的开垦开发活动使湿地生物多样性遭到严重的干扰和破坏,导致生物多样性空间分布格局及热点地区的保护成为研究的热点。在对三江平原湿地鸟类预测的基础上,利用空间自相关方法分析三江平原湿地鸟类丰富度的空间分布格局,并找出湿地鸟类多样性的热点地区及优先保护顺序。研究结果表明,三江平原湿地鸟类丰富度高高集聚区主要分布在保护区及周边地区、河流和湖泊沿岸,是新建和扩建自然保护区的最佳区域。湿地鸟类丰富度高低集聚区主要分布在农田景观中,将它们设立成微型保护地块对于区域景观生态安全具有重要意义;利用湿地鸟类物种丰富度、国家级保护湿地鸟类、生境类型和结构、距最近保护区距离、破碎度、干扰度等指标,在研究区内共找到13个热点地区,总面积为1018.7km²,占研究区总面积的8%;利用系统聚类分析,将13个热点地区划分成3种优先保护顺序。构建的小区域范围内寻找生物多样性热点地区的方法,为相关政府部门更有效地进行湿地生物多样性的保护和管理提供科学依据。     

妫水河流域山水林田湖草空间格局与生态过程分析

妫水河流域是北京地区重要生态屏障,同时作为2019年世园会和2022年冬奥会的举办地,对其生态环境质量提出了更高的要求。基于妫水河流域2008、2013和2017年土地利用数据与数字高程影像,构建山水林田湖草空间信息图谱,采用空间自相关分析方法探究其时空演变特征,并结合植被覆盖度,揭示研究区不同山水林田湖草空间格局下的生态变化过程,实现对妫水河流域山水林田湖草空间格局的定量化分析。结果表明：1）低山丘陵和山前台地中山田面积持续减少,空间集聚程度也随之下降,但其植被覆盖度呈现稳步上升趋势;2）山区内山林、山草的空间复合结构较少,山林格局表现出较强的空间集聚性,但面积和空间集聚程度均不断下降,其植被覆盖度也呈现持续退化趋势;而山草的空间集聚度随面积增加总体呈增加趋势,整体波动幅度较小,其植被覆盖度总体是降低的,建议形成"山林-山草"复合格局;3）山水的面积在不同的地貌类型中基本呈现萎缩状态,且植被覆盖度均维持在相对较低的状态,河流生态退化较严重。研究结果将为改善妫水河流域的生态格局和生态环境质量提供重要的参考信息。