Assessing glyphosate in water, marine particulate matter, and sediments in the Lagoon of Venice

Lagoon water, suspended particulate matter, and sediment samples from seven sites at Lagoon of Venice were collected from 2019 to 2021 in order to study the presence of the herbicide glyphosate (N-(phosphonomethyl)glycine), among the most widely used agricultural chemicals worldwide, but its occurrence in lagoon water environment has not been deeply investigated. The sites were selected considering a supposed diversity of inputs and of pollution levels. An analytical method based on ion chromatography coupled with tandem mass spectrometry was optimized and validated for lagoon water, marine particulate matter, and sediment samples. Maximum concentrations of glyphosate were 260 and 7 ng L-1 for lagoon water and suspended particulate matter, respectively, and 15 ng g-1 for sediment, with some spatial and temporal fluctuations. Our results demonstrate that glyphosate content in the Venice Lagoon mainly depends on external forcing from river inlets and agricultural lagoon activities.

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Implicit estimation of ecological model parameters

We introduce an implicit method for state and parameter estimation and apply it to a stochastic ecological model. The method uses an ensemble of particles to approximate the distribution of model solutions and parameters conditioned on noisy observations of the state. For each particle, it first determines likely values based on the observations, then samples around those values. This approach has a strong theoretical foundation, applies to nonlinear models and non-Gaussian distributions, and can estimate any number of model parameters, initial conditions, and model error covariances. The method is called implicit because it updates the particles without forming a predictive distribution of forward model integrations. As a point of comparison for different assimilation techniques, we consider examples in which one or more bifurcations separate the true parameter from its initial approximation. The implicit estimator is asymptotically unbiased, has a root-mean-squared error comparable to or less than the other methods, and is accurate even with small ensemble sizes.

Fuzziness and heterogeneity of benthic metacommunities in a complex transitional system

We propose an extension to the metacommunity (MC) concept and a novel operational methodology that has the potential to refine the analysis of MC structure at different hierarchical levels. We show that assemblages of species can also be seen as assemblages of abstract subregional habitat-related metacommunities (habMCs). This intrinsically fuzzy concept recognizes the existence of habMCs that are typically associated with given habitats, while allowing for the mixing and superposition of different habMCs in all sites and for boundaries among subregions that are neither spatially sharp nor temporally constant. The combination of fuzzy clustering and direct gradient analysis permits us to 1) objectively identify the number of habMCs that are present in a region as well as their spatial distributions and relative weights at different sites; 2) associate different subregions with different biological communities; and 3) quantitatively assess the affinities between habMCs and physical, morphological, biogeochemical, and environmental properties, thereby enabling an analysis of the roles and relative importance of various environmental parameters in shaping the spatial structure of a metacommunity. This concept and methodology offer the possibility of integrating the continuum and community unit concepts and of developing the concept of a habMC ecological niche. This approach also facilitates the practical application of the MC concept, which are not currently in common use. Applying these methods to macrophytobenthic and macrozoobenthic hard-substrate assemblages in the Venetian Lagoon, we identified a hierarchical organization of macrobenthic communities that associated different habMCs with different habitats. Our results demonstrate that different reference terms should be applied to different subregions to assess the ecological status of a waterbody and show that a combination of several environmental parameters describes the spatial heterogeneity of benthic communities much better than any single property can. Our results also emphasize the importance of considering heterogeneity and fuzziness when working in natural systems.