Cross-shore parallel tidal channel systems formed by alongshore currents.

Parallel tidal channel systems, characterized by commonly cross-shore orientation and regular spacing, represent a distinct class of tidal channel networks in coastal environments worldwide. Intriguingly, these cross-shore oriented channel systems can develop in environments dominated by alongshore tidal currents, for which the mechanisms remain elusive. Here, we combine remote sensing imagery analysis and morphodynamic simulations to demonstrate that the deflection of alongshore tidal currents at transitions in bed elevation determines the characteristic orientation of the parallel tidal channels. Numerical results reveal that sharp changes in bed elevation lead to nearly 90-degree intersection angles, while smoother transitions in bed profiles result in less perpendicular channel alignments. These findings shed light on the potential manipulation of tidal channel patterns in coastal wetlands, thus equipping coastal managers with a broader range of strategies for the sustainable management of these vital ecosystems in the face of climate change and sea level rise.

Transport and retention of sinking microplastics in a well-mixed estuary.

Estuaries have been shown to be potential hotspots of microplastic accumulation, but the hydrodynamic conditions and particle properties that control this process need further investigation. We have designed a series of numerical particle-tracking experiments to examine the sensitivity of retention in estuaries to particle size, particle density and varying tides and freshwater flow. At the end of the simulation, over 90 % of sinking particles are retained in the estuary, and the retention rate is further increased by high river runoff. In contrast, increased river discharge increases the number of marginally-buoyant (i.e. density close to estuarine water) particles that escape the estuary. Larger particle size tends to limit the downstream transport of sinking particles but can facilitate the transport of marginally-buoyant particles. Tidal asymmetry, vertical turbulent mixing and the vertical structure of the subtidal circulation are proposed as the underlying mechanisms controlling the fate of particles.

Polyester microfiber impacts on coastal sediment organic matter consumption.

As plastic pollution continues to accumulate at the seafloor, concerns around benthic ecosystem functionality heightens. This research demonstrates the systematic effects of polyester microfibers on seafloor organic matter consumption rates, an important benthic ecosystem function connected to multiple reactions and processes. We used a field-based assay to measure the loss of organic matter, both with and without polyester microfiber contamination. We identified sediment organic matter content, mud content, and mean grain size as the main drivers of organic matter consumption, however, polyester microfiber contamination decoupled ecosystem relationships and altered observed organic matter cycling dynamics. Organic matter consumption rates varied across horizontal and vertical spaces, highlighting that consumption and associated plastic effects are dependent on environmental heterogeneity at both small (within sites) and larger (between sites) scales. Our results emphasize the important role habitat heterogeneity plays in seafloor organic matter consumption and the associated effects of plastic pollution on ecosystem function.

Mangrove removal exacerbates estuarine infilling through landscape-scale bio-morphodynamic feedbacks.

Changes in upstream land-use have significantly transformed downstream coastal ecosystems around the globe. Restoration of coastal ecosystems often focuses on local-scale processes, thereby overlooking landscape-scale interactions that can ultimately determine restoration outcomes. Here we use an idealized bio-morphodynamic model, based on estuaries in New Zealand, to investigate the effects of both increased sediment inputs caused by upstream deforestation following European settlement and mangrove removal on estuarine morphology. Our results show that coastal mangrove removal initiatives, guided by knowledge on local-scale bio-morphodynamic feedbacks, cannot mitigate estuarine mud-infilling and restore antecedent sandy ecosystems. Unexpectedly, removal of mangroves enhances estuary-scale sediment trapping due to altered sedimentation patterns. Only reductions in upstream sediment supply can limit estuarine muddification. Our study demonstrates that bio-morphodynamic feedbacks can have contrasting effects at local and estuary scales. Consequently, human interventions like vegetation removal can lead to counterintuitive responses in estuarine landscape behavior that impede restoration efforts, highlighting that more holistic management approaches are needed.

Retention of buoyant plastic in a well-mixed estuary due to tides, river discharge and winds.

Estuaries can act as plastic retention hotspots, but the hydrodynamic controls on retention are not well understood. This study investigates the retention of river-sourced buoyant plastics in a well-mixed estuary, the Waitemata Estuary, using validated numerical simulations of floats with different tides, winds, and freshwater discharge. The proportion of floats grounded on the shore in all seven simulations is higher than 60 % and over 90 % in five simulations after ten days. <20 % of the floats leave the estuarine mouth in any of the simulations. An increase of two orders of magnitude in freshwater discharge doubles the likelihood for floats to reach the lower estuary. However, we find increased freshwater discharge doubles the lateral circulation towards the shore and results in similar proportions of grounding (90 %) as the low discharge cases. These findings challenge the conventional view that plastics preferentially enter the open ocean after high river discharge.

Real-world impacts of microplastic pollution on seafloor ecosystem function.

Emerging research shows that microplastic pollution could be impacting seafloor ecosystem function, but this has been primarily demonstrated without environmental and ecological context. This causes uncertainty in the real-world effects of microplastic pollution and leaves out essential information guiding policy and mitigation. In this study, we take a well-supported sampling design and statistical approach commonly employed in benthic ecology to evaluate real-world effects of microplastic pollution on coastal, benthic ecosystem function. We utilised environmental gradients in the Waitemata Harbour of Auckland, New Zealand to evaluate the importance of commonly assessed biological, chemical, and geological sediment variables and the characteristics of microplastic contaminants in driving essential ecosystem functions. Our results showed that models including microplastic terms were more accurate and explained more variability than those without microplastic terms, highlighting that microplastics impact real-world seafloor ecosystem function. Specifically, microplastic fibers significantly influenced oxygen flux (p < 0.03) and the diverse forms of microplastics (i.e., richness) significantly influenced ammonium flux (p < 0.02). Additionally, interactions between microplastic fiber concentrations and mollusc abundances significantly contributed to oxygen flux (p < 0.02). These results provide the first evaluation of in situ relationships between microplastics and ecosystem function. Even more importantly, this study suggests the value of environmental and ecological context for addressing microplastic impacts on benthic ecosystems and argues for further field examination.

Retention and dispersion of buoyant plastic debris in a well-mixed estuary from drifter observations.

Buoyant plastics enter estuaries largely from urban streams and an unknown fraction is retained before further transport to the open ocean. Plastic drifters were launched in a well-mixed estuary to simulate the movement of surface buoyant plastics. Two experiments were conducted, one during spring tides and one during neap tides, both with similar river flows and winds. Stronger tidal currents during spring tides resulted in larger dispersion and further downstream transport of the drifters. Half of the drifters were grounded within two tidal cycles. During the neap experiment, even more of the drifters (87%) were retained in the estuary. The grounding of such a high proportion of drifters suggests that much of the plastic pollution in estuaries of this type remains close to the riverine source. These findings imply that local clean-up programs removing grounded litter can reduce over half of the plastic pollution input to these estuaries.

Creating communities and communicating science during COVID-19: From Coast2Coast to Coast2Cast.

The global COVID-19 pandemic has seen extended lockdowns, isolation periods and travel restrictions across many countries around the world since early 2020. Some countries, such as Australia and New Zealand, closed their international borders in early 2020 preventing researchers travelling to other parts of the world. To facilitate the exposure of our students' work, and for them to meet international researchers, as well as foster a sense of coastal community, we started a zoominar series (seminars via Zoom) in April 2020. The Coast2Coast zoominar series had therefore humble origins but we soon discovered that there was an appetite for more widely sharing science across the coastal research disciplines. The Coast2Coast zoominar grew rapidly, attracting researchers from many countries around the world who presented and attended fortnightly online seminars. In just one year and a half we had 38 presentations with roughly 1900 attendees, creating a sense of community and belonging for the researchers involved. In early 2021, two of the co-authors, Giovanni (GC) and Ana (AVC) decided to expand and take this sense of community further creating the Coast2Cast podcast series, where researchers are asked research and non-research questions. In only 7 months, the podcasts have attracted more than 3700 listeners. Importantly, while the main prerequisite was high-quality and impactful research, diversity and inclusion were also a priority in selecting and inviting speakers for the zoominars and guests for the podcast. Importantly, our survey results suggest that there is a place for online events similar to Coast2Coast and Coast2Cast in a pandemic-free future, and that the coastal community involved has greatly benefited from such initiatives.

The distribution and ecological effects of microplastics in an estuarine ecosystem.

Coastal sediments, where microplastics (MPs) accumulate, support benthic microalgae (BMA) that contribute to ecosystem functions such as primary production, nutrient recycling and sediment biostabilization. The potential interactions between MPs, BMA and associated properties and functions remain poorly understood. To examine these interactions, a survey of 22 intertidal sites was conducted. MP abundance, size and a suite of MP diversity indices (based on color and shape) were determined from surface sediments alongside biochemical and physical properties. MPs were detected at all sites and dominated by polypropylene (34%), polyester (18%) and polyethylene (11%). Fragment and fiber dominance (16-92% and 6-81% respectively) and color-shape category diversity varied significantly by site. Distance-based linear models demonstrated that estuary-wide, mean grain size and mud were the best predictors of MP abundance-diversity matrices, but variance explained was low (9%). Relationships were improved when the data was split into sandy and muddy habitats. In sandy habitats (<8% mud), physical properties of the bed (mean grain size, mud content and distance from the estuary mouth) were still selected as predictors of MP abundance-diversity (14% variance explained); but a number of bivariate relationships were detected with biochemical properties such as BMA associated pigments and organic matter. In muddy habitats (>8% mud), porewater ammonium was lower when fiber abundance and overall MP diversity were higher. The inclusion of porewater ammonium, organic matter content and pheophytins alongside physical properties explained a greater percentage of the variance in MP abundance-diversity for muddy habitats (21%). The results highlight the importance of examining plastic shapes and MP categories in addition to abundance and emphasize that functionally different habitats should be examined separately to increase our understanding of MP-biota-function relationships.

Benthic species as mud patrol - modelled effects of bioturbators and biofilms on large-scale estuarine mud and morphology.

Sediment-stabilizing and -destabilizing organisms, i.e. microphytobenthos (biofilms) and macrozoobenthos (bioturbators), affect the erodibility of muddy sediments, potentially altering large-scale estuarine morphology. Using a novel eco-morphodynamic model of an idealized estuary, we investigate eco-engineering effects of microphytobenthos and two macrozoobenthic bioturbators. Local mud erodibility is based on species pattern predicted through hydrodynamics, soil mud content, competition and grazing. Mud resuspension and export is enhanced under bioturbation and prevented under biostabilization through respective exposure and protection of the supra- and intertidal. Bioturbation decreases mud thickness and bed elevations, which increases net mud fluxes. Microphytobenthos reduces erosion, leading to a local mud increase of intertidal sediments. In multi-species scenarios, an effective mud-prone bioturbator strongly alters morphology, exceeding that of a more abundant sand-prone moderate species, showing that morphological change depends on species traits as opposed to abundance. Altering their habitat, the effective mud-prone bioturbator facilitates expansion of the sand-prone moderate bioturbator. Grazing and species competition favor species distributions of dominant bioturbators. Consequently, eco-engineering affects habitat conditions while species interactions determine species dominance. Our results show that eco-engineering species determine the mud content of the estuary, which suggests large effects on the morphology of estuaries with aggravating habitat degradation.

A call to evaluate Plastic's impacts on marine benthic ecosystem interaction networks.

Plastic pollution continues to seep into natural and pristine habitats. Emerging laboratory-based research has evoked concern regarding plastic's impact on ecosystem structure and function, the essence of the ecosystem services that supports our life, wellbeing, and economy. These impacts have yet to be observed in nature where complex ecosystem interaction networks are enveloped in environmental physical and chemical dynamics. Specifically, there is concern that environmental impacts of plastics reach beyond toxicity and into ecosystem processes such as primary production, respiration, carbon and nutrient cycling, filtration, bioturbation, and bioirrigation. Plastics are popularly regarded as recalcitrant carbon molecules, although they have not been fully assessed as such. We hypothesize that plastics can take on similar roles as natural recalcitrant carbon (i.e., lignin and humic substances) in carbon cycling and associated biogeochemistry. In this paper, we review the current knowledge of the impacts of plastic pollution on marine, benthic ecosystem function. We argue for research advancement through (1) employing field experiments, (2) evaluating ecological network disturbances by plastic, and (3) assessing the role of plastics (i.e., a carbon-based molecule) in carbon cycling at local and global scales.

Effects of Polyester Microfibers on Microphytobenthos and Sediment-Dwelling Infauna.

Microfibers often dominate sediment microplastic samples, but little is known about their ecological effects on benthic organisms and functions. Polyethylene terephthalate) (PET) microfibers were added to 36 sediment chambers at six concentrations (0-0.5 g kg-1 sediment) to assess the effects on microphytobenthos (MPB), a key deposit-feeding bivalve, Macomona liliana, and sediment nutrient pools. MPB photosynthesis was promoted in 18 chambers through a 12 h light/dark cycle. Another 18 chambers were maintained under dark conditions to inhibit photosynthesis. After 35 days of MPB growth and stabilization, four M. liliana were added to each chamber for a further 40 days. MPB biomass and composition were examined alongside M. liliana biochemical and behavioral properties and porewater dissolved inorganic nutrient concentrations. Increasing microfibers resulted in lower MPB biomass, fewer diatom-associated fatty acids (FAs), and an increase in cyanobacteria. The changes in MPB coincided with up to 75% lower energy reserves and reduced burrowing activity in M. liliana. In the light, nitrate + nitrate (NOx) was significantly elevated and related to M. liliana and MPB biochemical properties. Ammoniu (NH4+) concentrations increased but were variable in both the light and the dark. Our results suggest that increasing microfiber concentrations influence the interactions between M. liliana and MPB and affect biogeochemical processing in coastal marine sediments.

A predictive model of recreational water quality based on adaptive synthetic sampling algorithms and machine learning.

Predicting recreational water quality is one of the most difficult tasks in water management with major implications for humans and society. Many data-driven models have been used to predict water quality indicators to allow a real time assessment of public health risk. This assessment is most commonly based on Faecal Indicator Bacteria (FIB), with the value of FIB compared with thresholds published in guidelines. However, FIB values usually tend to be unbalanced within water quality datasets, with small proportions of data exceeding guideline thresholds and far larger numbers that do not. This can be a limiting factor in the uptake of model predictions since, even if the overall accuracy is high, the sensitivity of the predictions can be low. To address this issue, this paper proposes an adaptive synthetic sampling algorithm (ADASYN) to generate synthetic above-threshold FIB instances and test the validity of the approach for the prediction of recreational water quality. The models in this paper are based on four machine learning techniques: k-mean nearest neighbour, boosting decision tree, support vector machine, and multi-layer perceptron artificial neural network and are applied to five different locations in Auckland, New Zealand. Aside from support vector machine, all models provide favourable predictions with relatively high sensitivity (around 75%) and overall accuracy (over 90%), indicating that both the compliant and exceedance conditions can be effectively predicted through the use of more sophisticated model training which involves artificial data. Considering the model accuracy and stability, boosting decision trees (BDT) and multi-layer perceptron artificial neural (MLP-ANN) network are the best two models and the multi-layer perceptron is the most efficient with the shortest computation time.

Blind testing of shoreline evolution models.

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

Forecasting the limits of resilience: integrating empirical research with theory.

Despite the increasing evidence of drastic and profound changes in many ecosystems, often referred to as regime shifts, we have little ability to understand the processes that provide insurance against such change (resilience). Modelling studies have suggested that increased variance may foreshadow a regime shift, but this requires long-term data and knowledge of the functional links between key processes. Field-based research and ground-truthing is an essential part of the heuristic that marries theoretical and empirical research, but experimental studies of resilience are lagging behind theory, management and policy requirements. Empirically, ecological resilience must be understood in terms of community dynamics and the potential for small shifts in environmental forcing to break the feedbacks that support resilience. Here, we integrate recent theory and empirical data to identify ways we might define and understand potential thresholds in the resilience of nature, and thus the potential for regime shifts, by focusing on the roles of strong and weak interactions, linkages in meta-communities, and positive feedbacks between these and environmental drivers. The challenge to theoretical and field ecologists is to make the shift from hindsight to a more predictive science that is able to assist in the implementation of ecosystem-based management.

Complex positive connections between functional groups are revealed by neural network analysis of ecological time series.

The relationships between functional linkages within communities and community dynamics are fundamental to biodiversity-stability relationships. By teasing apart the hidden layers within artificial neural networks (ANNs), we developed webs defining how functional groups influence each other's temporal dynamics. ANNs were based on 15 years of bimonthly monitoring of macrobenthic communities on three intertidal sandflats in Manukau Harbor (New Zealand). Sites differed in web topology and diversity, with the site dominated by one functional group exhibiting only a few strong links, the lowest alpha-, beta-, and gamma-diversity, and the highest temporal stability in alpha-diversity. However, positive interactions between functional groups, nonconcordant with harborwide or site-specific environmental variables, always dominated the interaction webs. The increased number of links we observed with increased temporal variation of species richness within functional groups and overall diversity supports the insurance hypothesis. While our findings suggest that there may be no consistent model characterizing the topology of temporal interactions between functional groups, decreasing diversity is likely to decouple interactions between functional groups and decrease ecosystem functionality.

Feedbacks between bivalve density, flow, and suspended sediment concentration on patch stable states.

We explore the role of biophysical feedbacks occurring at the patch scale (spatial scale of tens of meters) that influence bivalve physiological condition and affect patch stability by developing a numerical model for the pinnid bivalve, Atrina zelandica, in cohesive sediments. Simulated feedbacks involve bivalve density, flow conditions (assumed to be primarily influenced by local water depth and peak current speed), suspended sediment concentration (evaluated through a balance between background concentration, deposition, and erosion), and changes in the physiology of Atrina derived from empirical study. The model demonstrates that high bivalve density can lead to skimming flow and to a concomitant decrease in resuspension that will affect suspended sediment concentration over the patch directly feeding back on bivalve physiology. Consequently, for a given flow and background suspended sediment load, the stability of a patch directly depends on the size and density of bivalves in the patch. Although under a range of conditions patch stability is ensured independently of bivalve density, simulations clearly indicate that sudden changes in bivalve density or suspended sediment concentration can substantially affect patch structure and lead to different stable states. The model highlights the role of interactions between organisms, flow, and broader scale environmental conditions in providing a mechanistic explanation for the patchy occurrence of benthic suspension feeders.