Towards (better) fluvial meta-ecosystem ecology: a research perspective

Rivers are an important component of the global carbon cycle and contribute to atmospheric carbon exchange disproportionately to their total surface area. Largely, this is because rivers efficiently mobilize, transport and metabolize terrigenous organic matter (OM). Notably, our knowledge about the magnitude of globally relevant carbon fluxes strongly contrasts with our lack of understanding of the underlying processes that transform OM. Ultimately, OM processing en route to the oceans results from a diverse assemblage of consumers interacting with an equally diverse pool of resources in a spatially complex network of heterogeneous riverine habitats. To understand this interaction between consumers and OM, we must therefore account for spatial configuration, connectivity, and landscape context at scales ranging from local ecosystems to entire networks. Building such a spatially explicit framework of fluvial OM processing across scales may also help us to better predict poorly understood anthropogenic impacts on fluvial carbon cycling, for instance human-induced fragmentation and changes to flow regimes, including intermittence. Moreover, this framework must also account for the current unprecedented human-driven loss of biodiversity. This loss is at least partly due to mechanisms operating across spatial scales, such as interference with migration and habitat homogenization, and comes with largely unknown functional consequences. We advocate here for a comprehensive framework for fluvial networks connecting two spatially aware but disparate lines of research on (i) riverine metacommunities and biodiversity, and (ii) the biogeochemistry of rivers and their contribution to the global carbon cycle. We argue for a research agenda focusing on the regional scale-that is, of the entire river network-to enable a deeper mechanistic understanding of naturally arising biodiversity-ecosystem functioning coupling as a major driver of biogeochemically relevant riverine carbon fluxes.

Dispersal behaviour and riverine network connectivity shape the genetic diversity of freshwater amphipod metapopulations

Theory predicts that the distribution of genetic diversity in a landscape is strongly dependent on the connectivity of the metapopulation and the dispersal of individuals between patches. However, the influence of explicit spatial configurations such as dendritic landscapes on the genetic diversity of metapopulations is still understudied, and theoretical corroborations of empirical patterns are largely lacking. Here, we used microsatellite data and stochastic simulations of two metapopulations of freshwater amphipods in a 28,000 km² riverine network to study the influence of spatial connectivity and dispersal strategies on the spatial distribution of their genetic diversity. We found a significant imprint of the effects of riverine network connectivity on the local and global genetic diversity of both amphipod species. Data from 95 sites showed that allelic richness significantly increased towards more central nodes of the network. This was also seen for observed heterozygosity, yet not for expected heterozygosity. Genetic differentiation increased with instream distance. In simulation models, depending on the mutational model assumed, upstream movement probability and dispersal rate, respectively, emerged as key factors explaining the empirically observed distribution of local genetic diversity and genetic differentiation. Surprisingly, the role of site‐specific carrying capacities, for example by assuming a direct dependency of population size on local river size, was less clear cut: while our best fitting model scenario included this feature, over all simulations, scaling of carrying capacities did not increase data‐model fit. This highlights the importance of dispersal behaviour along spatial networks in shaping population genetic diversity.

The role of habitat configuration in shaping animal population processes: a framework to generate quantitative predictions

By shaping where individuals move, habitat configuration can fundamentally structure animal populations. Yet, we currently lack a framework for generating quantitative predictions about the role of habitat configuration in modulating population outcomes. To address this gap, we propose a modelling framework inspired by studies using networks to characterize habitat connectivity. We first define animal habitat networks, explain how they can integrate information about the different configurational features of animal habitats, and highlight the need for a bottom–up generative model that can depict realistic variations in habitat potential connectivity. Second, we describe a model for simulating animal habitat networks (available in the R package AnimalHabitatNetwork), and demonstrate its ability to generate alternative habitat configurations based on empirical data, which forms the basis for exploring the consequences of alternative habitat structures. Finally, we lay out three key research questions and demonstrate how our framework can address them. By simulating the spread of a pathogen within a population, we show how transmission properties can be impacted by both local potential connectivity and landscape-level characteristics of habitats. Our study highlights the importance of considering the underlying habitat configuration in studies linking social structure with population-level outcomes.

Its all about connections: hubs and invasion in habitat networks

During the early stages of invasion, the interaction between the features of the invaded landscape, notably its spatial structure, and the internal dynamics of an introduced population has a crucial impact on establishment and spread. By approximating introduction areas as networks of patches linked by dispersal, we characterised their spatial structure with specific metrics and tested their impact on two essential steps of the invasion process: establishment and spread. By combining simulations with experimental introductions of Trichogramma chilonis (Hymenoptera: Trichogrammatidae) in artificial laboratory microcosms, we demonstrated that spread was hindered by clusters and accelerated by hubs but was also affected by small-population mechanisms prevalent for invasions, such as Allee effects. Establishment was also affected by demographic mechanisms, in interaction with network metrics. These results highlight the importance of considering the demography of invaders as well as the structure of the invaded area to predict the outcome of invasions.