Chemical activity and biological effect of sludge-borne heavy metals and inorganic metal salts added to soils

Summary A greenhouse experiment was conducted in order to evaluate the chemical activity and the uptake by Italian ryegrass (Lolium perenne cv. S24) of Zn, Cu, Cd and Ni added to a sandy and a heavy clay soil in two different forms: as inorganic salts and sludge-borne.The chemical activity of heavy metals as evaluated with different extractants was higher for the inorganic salt treatment and for the sandy soil, indicating that the chemical form of the metal and soil characteristics largely affect their extractability.The different chemical activity was also reflected in plant uptake. For all metals the degree of plant accumulation decreased in the following order: sandy soil-salt sandy soil-sludge> clay soil-salt>clay soil-sludge.These findings indicate that caution must be used when using results of inorganic salt treatments and different soil types to evaluate plant uptake of heavy metals from sludge amended soils.     

Common and rare species respond to similar niche processes in macroinvertebrate metacommunities

Ecologists have long investigated why communities are composed of a few common species and many rare species. Most studies relate rarity to either niche differentiation among species or spatial processes. There is a parallel between these processes and the processes proposed to explain the structure of metacommunities. Based on a metacommunity perspective and on data on stream macroinvertebrates from different regions of Brazil, we answer two questions. 1) Are sets of common and rare species affected by similar niche and spatial processes? 2) How does the community composition of common and of rare species differ? The main hypothesis we test is that common species are mainly affected by environmental factors, whereas rare species are mostly influenced by dispersal limitation. We used variation partitioning to determine the proportion of variation explained by the environment and space in common and rare species matrices. Contrary to our expectations, evidence supported the idea that both common and rare species are affected mainly by environmental factors, even after controlling for the differing information content between common and rare species matrices. Moreover, the abundance of some common species is also a good predictor of variation in rare species matrices. Niche differences are unlikely to be the sole cause of patterns of rarity in these metacommunities. We suggest that sets of common and rare species react to similar major environmental gradients and that rare species also respond to processes that operate at a more fine‐grained spatial scale, particularly biotic interactions. We extend the view that species sorting is the dominant process structuring metacommunities and argue that future studies focusing on rarity would benefit from a metacommunity perspective.     

Distinguishing ecological from evolutionary approaches to transposable elements

Considerable variation exists not only in the kinds of transposable elements (TEs) occurring within the genomes of different species, but also in their abundance and distribution. Noting a similarity to the assortment of organisms among ecosystems, some researchers have called for an ecological approach to the study of transposon dynamics. However, there are several ways to adopt such an approach, and it is sometimes unclear what an ecological perspective will add to the existing co‐evolutionary framework for explaining transposon‐host interactions. This review aims to clarify the conceptual foundations of transposon ecology in order to evaluate its explanatory prospects. We begin by identifying three unanswered questions regarding the abundance and distribution of TEs that potentially call for an ecological explanation. We then offer an operational distinction between evolutionary and ecological approaches to these questions. By determining the amount of variance in transposon abundance and distribution that is explained by ecological and evolutionary factors, respectively, it is possible empirically to assess the prospects for each of these explanatory frameworks. To illustrate how this methodology applies to a concrete example, we analyzed whole‐genome data for one set of distantly related mammals and another more closely related group of arthropods. Our expectation was that ecological factors are most informative for explaining differences among individual TE lineages, rather than TE families, and for explaining their distribution among closely related as opposed to distantly related host genomes. We found that, in these data sets, ecological factors do in fact explain most of the variation in TE abundance and distribution among TE lineages across less distantly related host organisms. Evolutionary factors were not significant at these levels. However, the explanatory roles of evolution and ecology become inverted at the level of TE families or among more distantly related genomes. Not only does this example demonstrate the utility of our distinction between ecological and evolutionary perspectives, it further suggests an appropriate explanatory domain for the burgeoning discipline of transposon ecology. The fact that ecological processes appear to be impacting TE lineages over relatively short time scales further raises the possibility that transposons might serve as useful model systems for testing more general hypotheses in ecology.     

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels

The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity‐based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within‐basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low.     

Dispersal abilities of riverine freshwater mussels influence metacommunity structure

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Zooplankton on the move: first results on the quantification of dispersal of zooplankton in a set of interconnected ponds

In systems of interconnected ponds or lakes, the dispersal of zooplankton may be mediated by the active population component, with rivulets and overflows functioning as dispersal pathways and the dispersal being unidirectional. Such systems offer the possibility to study the impact of dispersal rates on local population dynamics and community structure, and provide opportunities to quantify dispersal in the field in a straightforward manner. In this study, dispersal of active zooplankton populations among interconnected ponds was quantified directly in the field by sampling the small waterways connecting the ponds. The number of dispersing zooplankton sampled in connecting elements was on average high (almost 7000 ind h^–1). However, the contribution of dispersing individuals to total population size in the target ponds was very limited (< 1% 24 h^–1.). Only a weak diel pattern in dispersal rates was observed.     

Spatial autocorrelation and dispersal limitation in freshwater organisms

Dispersal can limit the ranges of species and the diversity of communities. Despite its importance, little is known about its role in freshwater habitats and its relation to habitat type (lentic vs. lotic), especially for organisms with cryptic dispersal methods such as plankton. Poor dispersers are expected to show more clumped distributions or greater spatial autocorrelation (SA) in community composition than good dispersers. We examined patterns of SA across freshwater taxa with different dispersal modes (active vs. passive) and their association with habitat type (lake vs. stream) using 18 spatially explicit community composition data sets. We found significant relationships between SA and body size among taxa in lake habitats, but not in streams. However, the increase in SA with body size in lakes was driven entirely by fishes—organisms ranging in size from diatoms to macro-invertebrates showed equivalent levels of SA. These results support the idea that large organisms are less effective dispersers in aquatic environments, resulting in greater SA in community structure over broad scales. Streams may be effectively more connected than lakes as patterns of SA and body size were weaker in lotic habitats. Our data suggest that the critical threshold where greater body size increases dispersal limitation seems to come at the juncture between invertebrates and vertebrates rather than that between unicellular and multicellular organisms as has been previously suggested. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)

Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographical or environmental resolution of population genetic studies. Here, we investigated the population structure of turbot (Scophthalmus maximus) by screening 17 random and gene‐linked markers in 999 individuals at 290 geographical locations throughout the northeast Atlantic Ocean. A seascape genetics approach with the inclusion of high‐resolution oceanographical data was used to quantify the association of genetic variation with spatial, temporal and environmental parameters. Neutral loci identified three subgroups: an Atlantic group, a Baltic Sea group and one on the Irish Shelf. The inclusion of loci putatively under selection suggested an additional break in the North Sea, subdividing southern from northern Atlantic individuals. Environmental and spatial seascape variables correlated marginally with neutral genetic variation, but explained significant proportions (respectively, 8.7% and 10.3%) of adaptive genetic variation. Environmental variables associated with outlier allele frequencies included salinity, temperature, bottom shear stress, dissolved oxygen concentration and depth of the pycnocline. Furthermore, levels of explained adaptive genetic variation differed markedly between basins (3% vs. 12% in the North and Baltic Sea, respectively). We suggest that stable environmental selection pressure contributes to relatively strong local adaptation in the Baltic Sea. Our seascape genetic approach using a large number of sampling locations and associated oceanographical data proved useful for the identification of population units as the basis of management decisions.