Variation partitioning of species data matrices: estimation and comparison of fractions

Establishing relationships between species distributions and environmental characteristics is a major goal in the search for forces driving species distributions. Canonical ordinations such as redundancy analysis and canonical correspondence analysis are invaluable tools for modeling communities through environmental predictors. They provide the means for conducting direct explanatory analysis in which the association among species can be studied according to their common and unique relationships with the environmental variables and other sets of predictors of interest, such as spatial variables. Variation partitioning can then be used to test and determine the likelihood of these sets of predictors in explaining patterns in community structure. Although variation partitioning in canonical analysis is routinely used in ecological analysis, no effort has been reported in the literature to consider appropriate estimators so that comparisons between fractions or, eventually, between different canonical models are meaningful. In this paper, we show that variation partitioning as currently applied in canonical analysis is biased. We present appropriate unbiased estimators. In addition, we outline a statistical test to compare fractions in canonical analysis. The question addressed by the test is whether two fractions of variation are significantly different from each other. Such assessment provides an important step toward attaining an understanding of the factors patterning community structure. The test is shown to have correct Type I. error rates and good power for both redundancy analysis and canonical correspondence analysis.     

西安夏季大气亚微米颗粒物化学组成与来源的在线观测研究

西安作为汾渭平原地区最大的城市,大气颗粒物污染形势严峻.2017年夏季期间,在西安市浐灞生态园区运用气溶胶化学组分监测仪,对大气亚微米颗粒物中的非难挥发性组分(NR-PM1)进行了在线监测.观测期间NR-PM1的平均质量浓度为(30.1?±?15.4)μg???m?3.其中有机物含量最高,占NR-PM1总质量浓度的63...     

Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses

Recently, analytical approaches based on the eigenfunctions of spatial configuration matrices have been proposed in order to consider explicitly spatial predictors. The present study demonstrates the usefulness of eigenfunctions in spatial modeling applied to ecological problems and shows equivalencies of and differences between the two current implementations of this methodology. The two approaches in this category are the distance-based (DB) eigenvector maps proposed by P. Legendre and his colleagues, and spatial filtering based upon geographic connectivity matrices (i.e., topology-based; CB) developed by D. A. Griffith and his colleagues. In both cases, the goal is to create spatial predictors that can be easily incorporated into conventional regression models. One important advantage of these two approaches over any other spatial approach is that they provide a flexible tool that allows the full range of general and generalized linear modeling theory to be applied to ecological and geographical problems in the presence of nonzero spatial autocorrelation.     

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.     

Trace metal dynamics in an industrialized Brazilian river: A combined application of Zn isotopes, geochemical partitioning, and multivariate statistics

The Paraiba do Sul (PSR) and Guandu Rivers (GR) water diversion system (120 km long) is located in the main industrial pole of Brazil and supplies drinking water for 9.4 million people in the metropolitan region of Rio de Janeiro. This study aims to discern the trace metals dynamics in this complex aquatic system. We used a combined approach of geochemical tools such as geochemical partitioning, Zn isotopes signatures, and multivariate statistics. Zinc and Pb concentrations in Suspended Particulate Matter (SPM) and sediments were considerably higher in some sites. The sediment partition of As, Cr, and Cu revealed the residual fraction (F4) as the main fraction for these elements, indicating low mobility. Zinc and Pb were mostly associated with the exchangeable/carbonate (F1) and the reducible (F2) fractions, respectively, implying a higher susceptibility of these elements to being released from sediments. Zinc isotopic compositions of sediments and SPM fell in a binary mixing source process between lithogenic (δ^66/64Zn_JMC ≈ + 0.30‰) and anthropogenic (δ^66/64Zn_JMC ≈ + 0.15‰) end members. The lighter δ^66/64Zn_JMC values accompanied by high Zn concentrations in exchangeable/carbonate fraction (ZnF1) enable the tracking of Zn anthropogenic sources in the studied rivers. Overall, the results indicated that Hg, Pb, and Zn had a dominant anthropogenic origin linked to the industrial activities, while As, Cr, and Cu were mainly associated with lithogenic sources. This work demonstrates how integrating geochemical tools is valuable for assessing geochemical processes and mixing source effects in anthropized river watersheds.