The role of environmental and spatial factors for the composition of aquatic bacterial communities

This study investigates the importance of local vs. spatial factors on bacterial community composition of 35 rock pools at the Baltic Sea coast. The pools were located in five distinct spatial clusters over a total scale of <500 m and differed widely in terms of water chemistry. To determine the fractions of the variance in bacterial community composition (BCC) between rock pools that are explained by local environmental vs. spatial factors, a variance partitioning procedure using partial canonical correspondence analysis was performed. Three environmental variables (salinity, chlorophyll a concentration, and water color) had a significant effect on BCC, irrespective of the spatial location of the pools. Vice versa, there was a significant effect of spatial factors on BCC irrespective of any of the environmental factors included in this study. Hence, the patchy spatial distribution of the pools was partly reflected in the composition of the bacterial communities in the pools, which might be caused by congruent colonization events of adjacent pools, such as simultaneous seaspray inputs or direct exchange of bacteria via connecting rivulets. This study shows that the composition of planktonic bacteria can show provincialism at small spatial scales, which is likely to be caused by environmental conditions as well as historical events.     

Estimating landscape-scale species richness: reconciling frequency- and turnover-based approaches

One hypothesis for why estimators of species richness tend to underestimate total richness is that they do not explicitly account for increases in species richness due to spatial or environmental turnover in species composition (beta diversity). I analyze the similarity of a data set of native trees in Great Smoky Mountains National Park, USA, and assess the robustness of these estimators against recently developed ones that incorporate turnover explicitly: the total species accumulation method (T-S) and a method based on the distance decay of similarity. I show that the T-S estimator can give reliable estimates of species richness, given an appropriate grouping of sites. The estimator based on distance decay of similarity performed poorly. There are two main reasons for this: sample size effects and the assumption that distance decay of similarity exhibits a power law relationship. I show that estimators based on distance-decay relationships exhibit systematically lower rates of distance decay for samples with few individuals per site independent of environmental variation. Second, the data presented here and many other survey data sets exhibit exponential rather than power law distance-decay relationships. Richness estimators that explicitly incorporate beta diversity can be improved by beginning from an exponential distance-decay relationship and adjusting for the systematic errors introduced by small sample sizes.     

Responses of phytoplankton and periphytic diatoms to environmental factors in a tropical riverine reservoir北大核心CSCD

Riverine reservoirs have a short water retention time, which is ecologically more similar to that of rivers. Generally, phytoplankton-based approaches are used for lakes and periphytic diatom-based approach for rivers. To understand the differences in the responses of phytoplankton and periphytic diatoms to environmental variables for riverine reservoirs, we collected periphytic diatom samples on artificial substrata as well as phytoplankton samples from a tropical reservoir with a resident time less than 10 days. Our results showed that 131 phytoplankton species and 138 periphytic diatoms were detected; the variation of phytoplankton community was mainly reflected by the dominant species with a strong response to the environmental variables at a time scale, whereas the variation of periphytic diatom community was noted in both the species composition and the dominant species, with a strong response at spatial-temporal scales. The multivariate regression analysis and redundancy analysis showed that environmental factors have higher explanations for the variance of the periphytic diatom community (R2 = 0.27). Temperature was the key explanatory variable for phytoplankton, planktonic diatoms and periphytic diatoms (P < 0.01). However, dissolved oxygen and nitrate were also detected as significant explanatory factors associated with periphytic diatom community (P < 0.01). Thus, the periphytic diatoms were concluded to be more sensitive to environmental change and were associated with more environmental variables than phytoplankton. Periphytic diatoms appear to provide more ecological information than phytoplankton for riverine reservoirs. © 2018 Science Press. All rights reserved.     

若尔盖高寒沼泽植物群落与环境因子的关系

了解高寒沼泽植物群落与环境因子之间的关系,对揭示物种对生态环境的需求以及高寒沼泽的保护管理有重要意义,然而目前尚不清楚影响若尔盖高寒沼泽植物分布的主要环境因素。作者于2011—2012年间在若尔盖高寒沼泽随机调查32个样地,收集了植被样方数据、土壤理化性质数据、地表水位等实测数据,借助方差分析、CCA分析和相关分析等经典的统计方法,研究高寒沼泽植物群落物种组成和不同地表积水状况下多样性的差异,以及高寒沼泽植物群落与环境因子的关系。结果显示：若尔盖高寒沼泽植物共有151个种,隶属于39科98属;多样性指数随地表积水的减少呈现出增加的趋势。典范对应分析（CCA）结果表明,第一轴与水位、土壤水分含量、土壤有机碳、土壤总氮显著负相关,与土壤容重显著正相关,第二轴与裸斑率和鼠洞数显著相关。前2个轴一共解释了79．8％的物种与环境因子的关系,与环境因子的相关系数均在0．87以上;其中,水分和土壤养分条件是影响物种分布的主导因子,其次是裸斑面及啮齿动物活动。植物多样性指数与土壤水分负相关,与土壤有机碳和土壤全氮显著负相关,与土壤容重显著正相关。若尔盖沼泽植物群落物种多样性除了受土壤水分和养分条件的影响以外,啮齿动物的活动可能是影响若尔盖沼泽物种分布以及促进群落进一步演替的主要因素之一。     

宝天曼木本植物群落数量排序与环境解释

研究选取14个分别代表植被群落、地形因子、土壤因子的指标,利用宝天曼自然保护区32块样地资料,研究了物种分布与环境之间关系。采用DCCA法可将该地区木本植物群落划分为3个类型;物种与9个环境因子之间存在显著的相关关系,前4轴可解释物种总变异的94.1%;海拔、坡度、土壤含水量、坡向是影响该地区物种分布的主要因子,其中海拔是指示物种分布变化的最敏感因子。不同指标集团的典型相关分析结果表明：地形与植被因子之间、土壤因子与植被因子之间第1对典范相关系数分别为0.712和0.783,存在着显著的相关关系,影响植被特征的最重要地形因子是海拔和坡度,土壤因子为土壤厚度和土壤含水量,而对地形和土壤反应最敏感的植被指标分别为林分密度和平均树高,群落分布状态是由地形和土壤因子共同作用所控制的。     

The role of environmental and spatial processes in structuring lake communities from bacteria to fish

We assessed the relative roles of local environmental conditions and dispersal on community structure in a landscape of lakes for the major trophic groups. We use taxonomic presence-absence and abundance data for bacteria, phytoplankton, zooplankton, and fish from 18 lakes in southern Quebec, Canada. The question of interest was whether communities composed of organisms with more limited dispersal abilities, because of size and life history (zooplankton and fish) would show a different effect of lake distribution than communities composed of good dispersers (bacteria and phytoplankton). We examine the variation in structure attributable to local environmental (i.e., lake chemical and physical variables) vs. dispersal predictors (i.e., overland and watercourse distances between lakes) using variation partitioning techniques. Overall, we show that less motile species (crustacean zooplankton and fish) are better predicted by spatial factors than by local environmental ones. Furthermore, we show that for zooplankton abundances, both overland and watercourse dispersal pathways are equally strong, though they may select for different components of the community, while for fish, only watercourses are relevant dispersal pathways. These results suggest that crustacean zooplankton and fish are more constrained by dispersal and therefore more likely to operate as a metacommunity than are bacteria and phytoplankton within this studied landscape.     

Constrained additive ordination

For several decades now, ecologists have sought to determine the shape of species' response curves and how they are distributed along unknown underlying gradients, environmental latent variables, or ordination axes. Its determination has important implications for both continuum theory and community analysis because many theories and models in community ecology assume that responses are symmetric and unimodal. This article proposes a major new technique called constrained additive ordination (CAO) that solves this problem by computing the optimal gradients and flexible response curves. It allows ecologists to see the response curves as they really are, against the dominant gradients. With one gradient, CAO is a generalization of constrained quadratic ordination (CQO; formerly called canonical Gaussian ordination or CGO). It supplants symmetric bell-shaped response curves in CQO with completely flexible smooth curves. The curves are estimated using smoothers such as the smoothing spline. Loosely speaking, CAO models are generalized additive models (GAMs) fitted to a very small number of latent variables. Being data driven rather than model driven, CAO allows the data to "speak for itself" and does not make any of the assumptions made by canonical correspondence analysis. The new methodology is illustrated with a hunting spider data set and a New Zealand tree species data set.     

A strong test of a maximum entropy model of trait-based community assembly

We evaluate the predictive power and generality of Shipley's maximum entropy (maxent) model of community assembly in the context of 96 quadrats over a 120-km2 area having a large (79) species pool and strong gradients. Quadrats were sampled in the herbaceous understory of ponderosa pine forests in the Coconino National Forest, Arizona, U.S.A. The maxent model accurately predicted species relative abundances when observed community-weighted mean trait values were used as model constraints. Although only 53% of the variation in observed relative abundances was associated with a combination of 12 environmental variables, the maxent model based only on the environmental variables provided highly significant predictive ability, accounting for 72% of the variation that was possible given these environmental variables. This predictive ability largely surpassed that of nonmetric multidimensional scaling (NMDS) or detrended correspondence analysis (DCA) ordinations. Using cross-validation with 1000 independent runs, the median correlation between observed and predicted relative abundances was 0.560 (the 2.5% and 97.5% quantiles were 0.045 and 0.825). The qualitative predictions of the model were also noteworthy: dominant species were correctly identified in 53% of the quadrats, 83% of rare species were correctly predicted to have a relative abundance of < 0.05, and the median predicted relative abundance of species actually absent from a quadrat was 5 x 10(-5).     

Distribution and ecology of deep-water mollusks from the continental slope,southeastern Gulf of California,Mexico

Specimens of deep-water mollusks were collected with a bottom dredge in the SE Gulf of California during four cruises (TALUD project) in 2000–2001. A total of 24 species (16 Pelecypoda, 5 Gastropoda, and 3 Scaphopoda) were collected. Analyses of environmental data (depth, epibenthic temperature and oxygen content, sediment texture and organic matter content) associated with each record indicated that the community diversity of these deep-water mollusks was related to oxygen concentration and density was correlated with depth. A canonical correspondence analysis (CCA) indicated that the five environmental variables explained 53.8% of observed variance in the model. In a multiple regression analysis, density (ind l⁻¹) was best correlated with dissolved oxygen concentration (R = −0.25), followed by temperature (R = −0.20), organic matter content (R = −0.15), and depth (R = −0.12). As oxygen best explained variance in the CCA it was selected to perform a single correspondence analysis (CA) using the most abundant and frequent species (two Pelecypoda and three Scapophoda). The analysis shows that pelecypods occur in near anoxic values while scaphopods occur in intermediate oxygen concentrations.     

A Procedure for Making Optimal Selection of Input Variables for Multivariate Environmental Classifications

Abstract:  Multivariate classifications of environmental factors are used as frameworks for conservation management. Although classification performance is likely to be sensitive to choice of input variables, these choices have been subjective in most previous studies. We used the Mantel test on a limited set of sites for which biological data were available to iteratively seek a definition of environmental space (i.e., intersite distances calculated with a set of appropriately transformed and weighted environmental variables) that had maximal correlation with the same sites described in a biological space. The procedure was used to select input variables for a classification of New Zealand's rivers that discriminates variation in fish communities for biodiversity management. The classification performed (i.e., discriminated biological variation) better than classifications with subjectively chosen variables. The inherently linear measures of environmental distance that underlie multivariate environmental classifications mean that they will perform best if they are defined based on variables for which there is a linear variation in the biological community throughout the entire range of the variable. Classification performance will therefore be improved when variables that have nonlinear relationships with biological variation are transformed to make their relationship with biological turnover more linear and when the contributions of environmental factors that have particularly strong relationships with biological variation are increased by weighting. Our results indicate that attention to the manner in which environmental space is defined improves the efficacy of multivariate classification and other techniques in which the environment is used as a surrogate for biological variation.     

乳山湾外海夏季大型底栖动物分布与环境因子的典范对应分析

应用典范对应分析(Canonical correspondence analysis,CCA)研究了乳山湾外海21个样点中的32种大型底栖动物与包括化学耗氧量、溶解氧等在内的11个沉积物和底层水体环境因子间的相关关系.作出种类分布与环境因子关系的二维排序图,排序图直观地反映了主要大型底栖动物种类分布与环境因子间的关系.排序图中环境因子与前两个排序轴的相关系数大小表明,总氮、溶解氧、盐度、pH、水深和总磷是影响乳山湾外海大型底栖动物群落分布的主导因素.排序图还揭示了大型底栖动物物种对生态环境的需求以及它们在不同资源维上的生态分化现象,不同生境中大型底栖动物分布的种类不同.根据对环境因子的生态需求不同,32种大型底栖动物可分为6组:组Ⅰ,8种,分布在高总氮生境;组Ⅱ,4种,分布在高溶解氧、高盐度、低总氮生境;组Ⅲ,10种,分布在水浅、高pH生境;组Ⅳ,4种,分布在水深、低pH生境;组Ⅴ,仅1种,分布在高总磷生境;组Ⅵ,5种,分布在水深、低总磷生境.图2表5参29     

GIS-based niche modeling for mapping species' habitat

Ecological "niche modeling" using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.     

冀北山区森林群落草本多样性及其与地形关系研究

通过野外调查取样,应用Menhinick丰富度指数、Simpson指数、Shannon-Wiener指数和Pielou均匀度指数研究了冀北山区12种典型森林群落内的草本植物多样性规律,并采用典范对应分析（CCA）方法研究其分布与地形的关系。结果表明：不同的群落类型草本植物的组成和多样性指数不同,山杨（Populus davidiana）纯林的种数最多为34种,黑桦（Betula dahurica Pall）纯林的种数最少为19种,其Simpson指数、Shannon-Wiener指数最高,分别为0.927 3和2.879 6;在1 200～1 700 m之间,随海拔升高物种多样性指数、均匀度指数和丰富度指数呈正相关性,但没有线性上升的趋势关系;选取的地形因子对样点草本的影响程度大小为：坡向〉海拔〉坡度〉坡位〉坡形,坡向是样点草本植物空间差异的最主要地形制约因子,环境解释率为98.7%,证明排序可信。     

Variation partitioning involving orthogonal spatial eigenfunction submodels

When partitioning the variation of univariate or multivariate ecological data with respect to several submodels of spatial eigenfunctions (e.g., Moran's eigenvector maps, MEM) acting as explanatory data, a problem occurs: although the submodels are constructed to be orthogonal to one another, the partitioning based on adjusted R2 statistics produces nonzero values in the intersections between spatial submodels. This phenomenon is described and two solutions are proposed. The first solution is to apportion the intersection fractions proportionally to the variation explained by each submodel. The second solution consists in creating a hierarchy among the spatial submodels, in accordance with hierarchy theory. These solutions lead to new partitioning equations that are described in the Appendix. R functions are provided to carry out partitioning with respect to environmental variables and spatial eigenfunction submodels. This development is important for the correct interpretation of spatial modeling results implying explanatory environmental data as well as submodels of spatial eigenfunctions involving two or more spatial scales.     

Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions

Two statistical modelling techniques, generalized additive models (GAM) and multivariate adaptive regression splines (MARS), were used to analyse relationships between the distributions of 15 freshwater fish species and their environment. GAM and MARS models were fitted individually for each species, and a MARS multiresponse model was fitted in which the distributions of all species were analysed simultaneously. Model performance was evaluated using changes in deviance in the fitted models and the area under the receiver operating characteristic curve (ROC), calculated using a bootstrap assessment procedure that simulates predictive performance for independent data. Results indicate little difference between the performance of GAM and MARS models, even when MARS models included interaction terms between predictor variables. Results from MARS models are much more easily incorporated into other analyses than those from GAM models. The strong performance of a MARS multiresponse model, particularly for species of low prevalence, suggests that it may have distinct advantages for the analysis of large datasets. Its identification of a parsimonious set of environmental correlates of community composition, coupled with its ability to robustly model species distributions in relation to those variables, can be seen as converging strongly with the purposes of traditional ordination techniques.     

Species richness patterns along environmental gradients in island land molluscan fauna

The relationship between species richness and environmental variables may change depending on habitat structure, dispersal ability, species mixing, and community adaptation to the environment. It is crucial to know how these factors regulate the environment-diversity relationship. The land molluscan fauna of the Ogasawara Islands in the West Pacific is an excellent model system to address this question because of the high species endemicity (> 90%), small area, and simple habitat structure of the islands. I examined relationships among indigenous species composition, richness, and habitat condition, and especially productivity and forest moisture on the island of Anijima. Two major communities of snails could be distinguished by detrended correspondence analysis (DCA): one group dominated in a moist habitat with high productivity, and the other group dominated in a dry habitat with low productivity. However, species richness became highest at the intermediate condition between the habitats in which the two snail communities were dominant, so that species richness showed a hump-shaped relationship with moisture and productivity. In contrast, the species richness of the snail community in the moist habitat showed a monotonically positive correlation, and that in the dry habitat showed a monotonically negative correlation with moisture and productivity. Thus, the greater species richness in intermediate moisture and productivity resulted from the ecotone effect or community overlap at the transitional areas, where faunas with different ecologies can meet in a single site. These findings suggest that hump-shaped productivity-diversity relationships in land Mollusca would reflect the ecotone effect as a result of the mixing of species adapted to either fertile habitats or sterile habitats.     

Structure of and relationships within and between the littoral,rock-substrate fish communities off four islands in the Canarian Archipelago

A total of 577 visual surveys (each of 5 min in duration and 100 m² in area) were conducted throughout 1990 and 1991 at 32 locations off four Canary islands (i.e., Alegranza, Fuerteventura, Gran Canaria and Tenerife) with the objects of describing the coastal fish community, comparing the differences in the fish fauna within and between these islands, and determining the biotic and abiotic factors related to the structure of the fish communities. A total of 76 species were recorded; the most common were Abudefduf luridus, Canthigaster rostrata, Chromis limbatus, Sparisoma cretense and Thalassoma pavo (94.28, 86.48, 52.34, 73.31, and 94.10% frequency of occurrence, respectively). The abundance and average size of the commercially important species was greater in those locations where there was less fishing pressure. The stepwise linear regression models were capable of explaining only a low amount of variation in the dependent variables (i.e., number of species, number of individuals, average size and species diversity) of the fish community. The independent variables recorded were date, time of day, depth, slope of the substrate, substrate type, percentage of sand, percentage of algae, algal height, number of sea urchins (Diadema antillarum) and the individual islands. An ANOVA, using the islands only as independent variables, indicated that each island contributed significantly to the variation in the four dependent variables and there were significant differences among the islands. Detrended correspondence analysis (DCA) and a two-way indicator species analysis (TWINSPAN) determined associations between species and environmental attributes of the survey locations. The patterns in the TWINSPAN analysis indicated that localities had faunal resemblances based on the island off which where they were located.     

Multiple functions increase the importance of biodiversity for overall ecosystem functioning

Biodiversity is proposed to be important for the rate of ecosystem functions. Most biodiversity-ecosystem function studies, however, consider only one response variable at a time, and even when multiple variables are examined they are analyzed separately. This means that a very important aspect of biodiversity is overlooked: the possibility for different species to carry out different functions at any one time. We propose a conceptual model to explore the effects of species loss on overall ecosystem functioning, where overall functioning is defined as the joint effect of many ecosystem functions. We show that, due to multifunctional complementarity among species, overall functioning is more susceptible to species loss than are single functions. Modeled relationships between species richness and overall ecosystem functioning using five empirical data sets on monocultures reflected the range of effects of species loss on multiple functions predicted by the model. Furthermore, an exploration of the correlations across functions and the degree of redundancy within functions revealed that multifunctional redundancy was generally lower than single-function redundancy in these empirical data sets. We suggest that by shifting the focus to the variety of functions maintained by a diversity of species, the full importance of biodiversity for the functioning of ecosystems can be uncovered. Our results are thus important for conservation and management of biota and ecosystem services.     

武汉月湖水体主要元素与浮游植物的PCA与CCA分析

通过2007年1—12月对武汉月湖不同的取样点进行监测,并选择汉江琴台段水域作为研究对照,调查了月湖水体硅藻、蓝藻与水体主要元素的种类,采用PCA、CCA分析法探讨了月湖水体硅藻、蓝藻与水体元素种类的关系。结果表明：月湖水体中所含元素全年监测出28种;汉江琴台段水域中所含元素全年监测出27种。经PCA分析表明,月湖水体中累计贡献率较大为磷（P）、砷（As）、铁（Fe）、铜（Cu）、锰（Mn）;汉江琴台段水域累计贡献率较大为硅（Si）、锑（Sb）、镉（cd）、钒（V）、钡（Ba）、Ag（银）、钼（Mo）。月湖水体中蓝藻密度大于硅藻,汉江琴台段水域硅藻密度大于蓝藻。经CCA分析表明,月湖硅藻密度与硒（Se）、锶（sr）、银（Ag）、Ba、铝（A1）呈正相关关系;月湖蓝藻密度与P、Cu、铬（Cr）呈正相关关系,月湖蓝藻密度与镁（Mg）、镍（Ni）、钙（ca）、锌（zn）、硫（S）呈负相关关系。CCA分析中,汉江琴台段硅藻密度与铅（Pb）、硼（B）、As、Cr、Zn、A1、Cu、Mn、Fe、P呈负相关关系,汉江琴台段硅藻密度与Mo、ca、钴（Co）、V、Sr、Ag呈正相关关系;汉江琴台段蓝藻密度与钠（Na）、S、Mg、Ni、钾（K）呈负相关关系。月湖水体缺乏可溶硅（dissolvedsilicon,DSi）,硅藻会提升对其他元素（Se、Sr、Ag、Ba、A1）的吸收能力,这些元素会起到缺乏元素（si）近似的作用,替代性可能出现。水中各种元素的组态是导致月湖浮游植物群落发生演变的重要原因之一。