Environmental filtering and spatial processes equally contributed to macroinvertebrate metacommunity dynamics in the highly urbanized river networks in Shenzhen, South China

Background Disentangling the relative roles of environmental filtering and spatial processes in structuring ecological communities is a central topic in metacommunity ecology. Metacommunity ecology in the temperate river ecosystems has been well developed, while less attention has been paid to subtropical urban river networks. Here, we examined the ecological factors and seasonal difference in structuring macroinvertebrates metacommunity assembly in the subtropical urban river networks in Shenzhen, South China. Results Our results revealed that there was no significant distinction of macroinvertebrate community composition among seasons, with only the relative abundance of Mollusca and Odonata significantly differed in both wet and dry seasons. One possible explanation was that most macroinvertebrates are generally pollution-tolerant taxa characterized with nonseasonal life cycle. In addition, distance-based redundancy analysis and variation partitioning approach revealed that metacommunity was determined equally by the environmental and dispersal-related factors. Further, our results showed that, although a slight temporal variation of relative contribution, the identity and explanation power of ecological factors were different among seasons. Specifically, stronger environmental filtering structuring community dynamics was observed in the dry than wet seasons, which might be owing to higher environmental heterogeneity under a low water-flow condition. Moreover, we detected that the influence of spatial processes was stronger in the wet than dry seasons, indicating an obvious dispersal processes due to high connectivity among sites. Conclusion Overall, our results revealed that environmental and spatial factors equally explained variations of macroinvertebrate metacommunity, implying the necessity of considering dispersal-related processes structuring ecological communities in river bioassessment programs. Moreover, degraded habitat conditions and water quality were the predominant factors that affected macroinvertebrate communities, indicating the significance and feasibility of improving local abiotic conditions to sustain local biodiversity. Further, our findings revealed the importance of seasonal dynamics of these urban river networks in structuring macroinvertebrate metacommunity. Thereby, our study improves the understanding of ecological processes governing macroinvertebrate metacommunity and underlines the idea that community ecology studies should go beyond the single snapshot survey in river networks.

Freshwater nematodes in metacommunity studies.

This chapter discusses the application of the metacommunity concept to data on freshwater nematodes. First, the theoretical concepts, terminology, and methods used in metacommunity analyses are introduced. Second, metacommunity studies of freshwater nematodes are summarized and the results are compared with those obtained from studies of other organismal groups. Finally, research gaps in metacommunity ecology in general and freshwater nematodes in particular are highlighted.

Using metacommunity ecology to understand environmental metabolomes

Environmental metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, significant gaps exist in our understanding of their spatiotemporal organization, limiting our ability to uncover transferrable principles and predict ecosystem function. We propose that a theoretical paradigm, which integrates concepts from metacommunity ecology, is necessary to reveal underlying mechanisms governing metabolomes. We call this synthesis between ecology and metabolomics ‘meta-metabolome ecology’ and demonstrate its utility using a mass spectrometry dataset. We developed three relational metabolite dendrograms using molecular properties and putative biochemical transformations and performed ecological null modeling. Based upon null modeling results, we show that stochastic processes drove molecular properties while biochemical transformations were structured deterministically. We further suggest that potentially biochemically active metabolites were more deterministically assembled than less active metabolites. Understanding variation in the influences of stochasticity and determinism provides a way to focus attention on which meta-metabolomes and which parts of meta-metabolomes are most likely to be important to consider in mechanistic models. We propose that this paradigm will allow researchers to study the connections between ecological systems and their molecular processes in previously inaccessible detail.

A Metacommunity Approach to Improve Biological Assessments in Highly Dynamic Freshwater Ecosystems

Rapid shifts in biotic communities due to environmental variability challenge the detection of anthropogenic impacts by current biomonitoring programs. Metacommunity ecology has the potential to inform such programs, because it combines dispersal processes with niche-based approaches and recognizes variability in community composition. Using intermittent rivers—prevalent and highly dynamic ecosystems that sometimes dry—we develop a conceptual model to illustrate how dispersal limitation and flow intermittence influence the performance of biological indices. We produce a methodological framework integrating physical- and organismal-based dispersal measurements into predictive modeling, to inform development of dynamic ecological quality assessments. Such metacommunity-based approaches could be extended to other ecosystems and are required to underpin our capacity to monitor and protect ecosystems threatened under future environmental changes.

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed ‘meta-metabolome ecology.’ Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering. We refer to this phenomenon as ‘thermodynamic redundancy,’ which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable principles, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Unification of Environmental Metabolomics with Metacommunity Ecology

Environmental metabolomics, enabled by high-resolution mass spectrometric techniques, have demonstrated the biogeochemical importance of the metabolites which comprise natural organic matter (NOM). However, significant gaps exist in our understanding of the spatiotemporal organization of NOM composition. We suggest that the underlying mechanisms governing NOM can be revealed by applying tools and concepts from metacommunity ecology to environmental metabolomics. After illustrating the similarities between metabolomes and ecological communities, we call this conceptual synthesis ‘meta-metabolome ecology’ and demonstrate its potential utility using a freshwater mass spectrometry dataset. Specifically, we developed three relational metabolite dendrograms using combinations of molecular properties (i.e., aromaticity index, double-bond equivalents, etc.) and putative biochemical transformations. Using these dendrograms, which are similar to phylogenetic or functional trait trees in ecological communities, we illustrate potential analytical techniques by investigating relationally-informed α-diversity and β-diversity metrics (e.g., MPD, MNTD, UniFrac), and null model analyses (e.g., NRI, NTI, and βNTI). Furthermore, we demonstrate that this synthesis allows ecological communities (e.g., microbes) and the metabolites they produce and consume using the same framework. We propose that applying this framework to a broad range of ecosystems will reveal generalizable principles that can advance our predictive capabilities regarding NOM dynamics.