Science and Engineering Papers

Permanent URI for this collectionhttps://researchcommons.waikato.ac.nz/handle/10289/38

This collection houses research from the School of Science and from the School of Engineering at the University of Waikato.

Browse

Now showing 1 - 20 of 3435

An Interoperable User-Centred Digital Twin Framework for sustainable energy system management
(MDPI, 2026-01-09) Adeel, Aleeza; Apperley, Mark; Walmsley, Tim G
This paper presents an Interoperable User-Centred Digital Twin (I-UCDT) framework for sustainable energy system management, addressing the growing complexity of energy generation, storage, demand, and grid interaction across industrial and community-scale systems. The proposed framework provides a unified environment for the visual representation and management of interconnected energy components, supporting informed decision-making among diverse stakeholder groups. The I-UCDT framework adopts a modular plug-and-play architecture based on the Functional Mock-up Interface (FMI) standard, enabling scalable and interoperable integration of heterogeneous energy models from platforms such as Modelica, MATLAB/Simulink, and EnergyPlus. A standardised data layer processes and structures raw model inputs, while an interactive visualisation layer translates complex energy flows into intuitive, user-accessible insights. By applying human–computer interaction principles, the framework reduces cognitive load and enables users with varying technical backgrounds to explore supply–demand balancing, decarbonisation pathways, and optimisation strategies. It supports the full lifecycle of energy system design, planning, and operation, offering flexibility for both industrial and community-scale applications. A case study demonstrates the framework’s potential to enhance transparency, usability, and energy efficiency. Overall, this work advances digital twin research for energy systems by combining technical interoperability with explicitly formalised user-centred design characteristics (C1–C10) to promote flexible and sustainable energy system management.
Rethinking the concept of pixel intensity contrast from a machine learning perspective
(IEEE, 2025) Abeysekera, Sanush K.; Ooi, Melanie Po-Leen; Kuang, Ye Chow; Faisal, Shah; Thawdar, Yaminn; Holmes, Geoffrey; Fletcher, Dale; Reutemann, Peter
Image contrast is a critical factor for machine vision tasks. A promising approach for enhancing contrast involves the use of algorithmically optimized, spectrally tunable illumination. However, the very definition of 'contrast' is often rooted in principles of human perception, which may not be optimal for a machine observer. For an algorithm, contrast is an objective, task-driven metric that can be mathematically defined. To investigate the impact of this definition, we first use eigenvalue-based optimization algorithms to compute optimal illumination spectra. We then systematically evaluate these spectra using four distinct, physically realizable contrast formulations. Our analysis reveals that the performance of a given optimization algorithm is entirely dependent on the subsequent choice of evaluation metric. An illumination spectrum considered optimal under one metric can be significantly suboptimal when measured by another. This demonstrates that the choice of contrast metric is not a passive measurement, but an active design parameter with tangible physical consequences. From a machine learning perspective, the choice of this 'loss function' should be codesigned with the physical hardware and the ultimate downstream task to achieve true system-level optimization.
An overview of integrating deep learning methods with close-range hyperspectral imaging for agriculture
(IEEE, 2025-07-10) Faisal, Shah; Po-Leen Ooi, Melanie; Chow Kuang, Ye; Abeysekera, Sanush K.; Fletcher, Dale
Hyperspectral imaging combines spectroscopy with imaging, thus capturing both spectral and spatial features. This makes it a useful technology in several application areas such as remote sensing and smart agriculture. Extracting spatial-spectral information of objects-of-interest from hyperspectral images requires sophisticated computational methods. The last decade saw the rapid advancement of deep learning methods due to their superior automatic feature extraction capability from images, and hence it is no surprise that these methods have been adapted and used for hyperspectral image analysis. Yet, while deep learning methods have achieved some success for hyperspectral remote sensing, it has been less explored in close range (or proximal) hyperspectral imaging, which is likely because at this range, it is more akin to spectroscopy with spatial information, rather than the case of remote sensing, which is more akin to imaging with higher spectral resolution. Close-range HSI allows for fine-scale analysis of plant health, nutrient levels, disease detection, and crop quality, which is very important in precision agriculture. In light of the new computational methods in deep learning, this review article provides an in-depth analysis and comparisons of such methods when applied to proximal hyperspectral imagery, with a particular emphasis on unsolved challenges (e.g., limited availability of annotated datasets, the need for robust models under real-world conditions, and the integration of spatial and spectral information) and potential future research directions for agricultural applications. The review emphasizes the importance of further explorations and has provided recommended directions for future research that could elevate close-range hyperspectral imaging technology from research to industry use for smart agriculture applications.
Pest fish removal by boat electrofishing Western Springs Lake - Te Wai Orea February 2026
(Environmental Research Institute, University of Waikato, 2026) Ling, Nicholas; Rowe, Kat; Roche, Ben
Invasive exotic fish species were removed from Western Springs Lake Te Wai Orea by boat electrofishing in February 2026. Over five days, a total of 372 fish (252 goldfish, 43 koi carp, 77 brown bullhead catfish) totalling 509.6 kg were removed from the lake. These were the only exotic species captured or observed. Eels were abundant in the lake, and three smaller native fish were also captured (īnanga, common smelt, common bully). Due to targeted fishing effort in areas frequented by fish rather than employing a randomised sampling method, and varying electrofishing pulsator settings to target particular species, a reduction in catch per unit effort (CPUE) was not observed for the two less common species (carp and catfish). However, a reduction in CPUE was observed for goldfish, and analysis of goldfish catch data by the Leslie plot method estimated 78% removal of this species from the lake. Goldfish catch rate declined from a peak of 18.7 fish per hour on day one to three fish per hour by day five. Most goldfish and catfish were captured in weedy habitat in Pumphouse Bay at the south-eastern end of the lake. Goldfish and koi carp were also associated with marginal beds of papyrus sedge (Cyperus papyrus) and also occurred in shallow bays on the western side of the lake. Few fish were captured or observed in devegetated central areas of the lake.
Sediment aluminium content of Lakes Rotorua and Rotoehu: 2024 monitoring survey
(Environmental Research Institute, University of Waikato, 2026) Tempero, Grant Wayne
Continuous alum (aluminium sulphate) dosing of the Utuhina Stream was initiated in 2006, with the objective of reducing dissolved reactive phosphate (DRP) loading of Lake Rotorua, thereby reducing lake primary productivity. A second continuous alum dosing station began operation on the Puarenga Stream in 2010. The water quality of Lake Rotorua has improved, with the Trophic Lake Index (TLI) declining from 5.0 in 2004 to 4.3 in 2024. Similarly, continuous alum dosing of the Waitangi Stream which flows into Lake Rotoehu began in 2011. However, alum dosing at this site was not as effective as anticipated, as invasive aquatic weed inhibited alum from reaching the main basin. As of 31 December 2023, a total of 993 tonnes of aluminium had been dosed to Lake Rotorua and 128 tonnes to Lake Rotoehu.
The crack location index for crack detection of a beam
(The Japan Society of Mechanical Engineers (JSME), 2024) Mochida, Yusuke; Sun, Tao
This study introduces a new index to be used for crack detection on a beam like structure. Our recent numerical modelling found sudden shifts in structural natural frequencies as a body with rotary inertia roving on a structure’s surface passes a crack. Theoretically, this phenomenon made it possible to locate the crack by observing the abrupt frequency change from the curve of natural frequency versus mass location. In practice, the mass is located at discrete positions thus the curve of natural frequency is not continuous. This led to the consideration of Δ𝑓 and Δ(Δ𝑓), where Δ𝑓 is the natural frequency change when the mass is located in two adjacent positions and Δ(Δ𝑓) is the change of Δ𝑓. The plots of Δ𝑓 or Δ(Δ𝑓) against mass location show peaks at the crack location and they could be highlighted. However, further study shows that the plots of Δ𝑓 or Δ(Δ𝑓) sometimes give false peaks, which makes it challenging to pinpoint the crack location This study aims to introduce a more robust index than Δ(Δ𝑓) that can suppress some of the false peaks, and hence the resulting curve can be more suitable for crack detection. We name it the crack location index. The crack location index was devised based on the participation of modal data in the expressions of natural frequency of a beam carrying a roving mass with rotary inertia and its derivative. They were demonstrated to be good candidates for locating the crack. The crack location index was applied to a numerical example of beam with a crack, and the crack location was pinpointed. It was shown that there were fewer false peaks in the curve of the crack location index than that of Δ(Δ𝑓).
Relationship between microstructure, mechanical, and biological response in biomedical Ti–Nb–Cu alloys
(Elsevier, 2026) Peters, Linda M.; Manogar, Balakrishnan; Yang, Fei; Bolzoni, Leandro
Titanium alloys are highly used in biomedical applications, especially structural ones, due to their mechanical properties and biocompatibility. However, they are susceptible to pathogenic bacterial infections, a long-lasting challenge of biomaterials exacerbated by the rise of antibiotic resistant bacteria. To address this, novel Ti–Nb–Cu alloys with intrinsic antibacterial capability were developed and characterised in this study. It is found that changing the amount of Nb and Cu brings about manufacturability and microstructural modifications. Specifically, the amount of porosity increases, the microstructure changes from lamellar to β type, and precipitation of the eutectoid Ti₂Cu intermetallic phase occurs as the contents of Nb and Cu increase. Accordingly, the Ti–Nb–Cu alloys become stronger and less ductile, though they do not fail catastrophically. They always form a protective passivation layer against corrosion, though the corrosion rate is composition dependent. They are characterised by a very strong antibacterial efficacy against both gram negative and gram positive bacteria, and they are not cytotoxic. This combination makes the developed Ti–Nb–Cu alloys promising candidates for structural biomedical applications.
Early Cretaceous continental-scale sediment dispersal: Towards resolving the McMurray conundrum - Discussion
(Society for Sedimentary Geology (SEPM), 2026) Dashtgard, Shahin E.; Gingras, Murray K.; Ranger, Mike; La Croix, Andrew D.; MacEachern, James A.
Wahbi et al. (2025) addresses aspects of the oilsands-hosting McMurray Formation (Fm) in northeast Alberta, Canada. As one of the largest petroleum reservoirs on Earth, resolving the geology of the McMurray Fm has potentially wide-ranging economic implications, and so the interval has received significant research attention. As noted by Wahbi et al. (2025), differing interpretations of the McMurray Fm stem largely from varying assessments of the degree of marine influence, and this is commonly referred to as the “McMurray conundrum” (Gingras and Leckie 2017; Gingras et al. 2019). At its core, the McMurray conundrum describes the seemingly irreconcilable juxtaposition of: 1) fluvial architectures (point bars and channel belts) that are associated mainly with the C2 through A2 parasequences and some evidence that the regional parasequences were deposited in freshwater (terrestrial) environments; versus 2) the preservation of bioturbation in both sand beds and the mudstone layers that drape point bar surfaces (i.e., inclined heterolithic stratification) coupled with the minimal preservation of terrestrial strata (e.g., floodplain deposits, coal beds, and paleosols).
Seismic porosity estimation using geologically-informed seismic attributes and a kriging-enhanced random forest: Application to a shallow-marine carbonate reservoir
(Springer, 2026-05-08) Rezaei, Mohammadali; La Croix, Andrew D.; Emami Niri, Mohammad; Asghari, Omid
Reliable property modeling is vital for Earth resource development, and seismic data can provide secondary variables to improve accuracy. However, seismic-integrated models remain uncertain due to inherent limitations in seismic data such as the cumulative effects of signal processing and attribute computation. In this study, we aimed to estimate a high-accuracy 3D secondary variable for porosity modeling from seismic attributes using a kriging-enhanced random forest (RF). This approach leverages the ensemble learning capabilities of RF to effectively handle limited training data, while incorporating the ability of kriging to account for spatial correlation. Prior to implementing this model, we developed an innovative workflow to correct seismic attributes based on geological trends. This workflow generated geologically informed seismic attributes by vertically correcting seismic attributes in areas of lower quality, while preserving their original lateral trends. We applied our methodology to a late Albian–early Turonian shallow-marine carbonate reservoir with a complex diagenetic history. After creating geologically informed seismic attributes, we used them, along with porosity well logs, as inputs for the kriging-enhanced RF model. This model calculated the mean of decision trees through kriging estimation rather than the usual averaging method. To evaluate effectiveness, we compared it with a deep neural network, a kriging-enhanced deep neural network, and a standard RF. The kriging-enhanced RF produced porosity closer to blind-well values than other methods and captured complex heterogeneities, such as channels and differing reservoir qualities across sequences, making the porosity cube a reliable 3D trend for further geostatistical simulations.
Tensile and flexural performance of FDM 3D printed Harakeke (NZ Flax) fiber -PLA composites for lightweight structural applications
(Elsevier, 2026) Selvamani, S K.; Clint, K S.; Samykano, M.; Kadirgama, K.; Beg, Mohammad Dalour Hossen; Pickering, Kim L.; Megalingam, A.
Current research on the shift toward sustainable materials has intensified interest in biodegradable alternatives polymers, with poly-lactic acid (PLA) emerging as a leading candidate. With various advantages, including biodegradability and processability, PLA's tensile and flexural strength can be further enhanced to increase its use in lightweight structural applications. This study introduces a novel integration of harakeke (New Zealand flax) fibers into PLA, a material pairing that has not been comprehensively investigated for additive manufacturing-based components. The research uniquely employs a Response Surface Methodology (RSM)-based optimization framework to systematically analyze and model the combined effects of fiber content (0-20 wt.%), raster angle (45-90°), and raster width (0.5-1.0 mm) on the composite’s tensile and flexural performance. The findings reveal that a raster width of 0.5 mm, raster angle of 45°, and a flax infill of 10% by weight provide the best synergy of stiffness and strength. The maximum values of Young's modulus are 4453.85 MPa, and the flexural stress is 73.395 MPa. Increased fiber loadings above 20 wt.% reduce performance due to fiber agglomeration. Among orientations, the 45° raster is preferable to 90° due to increased load transfer and stress distribution, and narrower raster widths facilitate greater interlayer bonding and deposition density.
Low-cost Ti alloys: Assessment of their microstructure, mechanical properties, corrosion behaviour, and biological response
(Elsevier, 2026) Bolzoni, Leandro; Nishio, W; Appadan, AM; Manogar, Balakrishnan
Orthopaedic and dental implants, the majority of which are made from titanium alloys, face the crucial challenge of both inducing osteogenesis whilst inhibiting bacterial biofilm formation in an economical manner over the life of the implant. This study introduces an innovative strategy combining cost-effective alloying elements, selected due to their reported biological benefits, for developing new titanium alloys that achieve a tailorable mechanical, corrosion, and biological response. The combination of alloying and manufacturing results in homogeneous materials characterised by a lamellar microstructure. The developed low-cost Ti alloys have a maximum ultimate compression strength of 659 MPa, maximum tensile yield stress of 606 MPa, and maximum elongation of 8.3% without failing catastrophically. The alloys do not degrade as abiotic corrosion is significantly hampered by their intrinsic passivation behaviour (maximum corrosion rate of 8.9 μm/year), and have adjustable surface wettability with contact angles in the 60-81° range. Consequently, stomal cell attachment, cytotoxicity and cytokine production (IL-6 and TGF-β1), and antibacterial rate on S. aureus are consistent and comparable to those of current implnat materials. Based on these characteristics, the low-cost Ti alloys are promising materials for load-bearing biomedical devices.
On a Neural Phonon Model of EEG Brain Dynamics
(Springer, 2026-03-16) Head, Mitchell; Batterton, Christopher; Owen, Mahonri; König, Jemma Lynette ; Ensing, Simeon; Shepherd, Craig
Neuronal oscillations are a ubiquitous feature of brain activity, indexing functions from sensory selection to memory formation. Yet a unified framework that (i) accommodates the nonlinear, noise-driven nature of cortical dynamics and (ii) explains standard empirical measures—power, spectral entropy, coherence, Phase-Locking Value (PLV), Phase-Amplitude Coupling (PAC), and envelope correlations—remains elusive. A natural candidate is the noisy Stuart–Landau (SL) oscillator, whose deterministic form models cortical rhythms as limit cycles, while additive noise induces stochastic phase and amplitude fluctuations. Prior work has shown that networks of SL oscillators can replicate burst statistics, multistability, and cross-frequency modulation in electroencephalography/magnetoencephalography (EEG/MEG). However, an analytical framework linking these models directly to observed connectivity metrics has been lacking. Here we derive such a framework by mapping the Fokker–Planck equation (FPE) of each SL oscillator to an imaginary-time Schrödinger operator via a classical similarity transform. A second-order expansion around the limit-cycle amplitude yields a quadratic Hamiltonian whose ladder operators describe quantised fluctuations—neural phonons—in oscillatory power. Bilinear coupling terms inherited from diffusion give rise to analytically diagonalisable bosonic interactions. This construction yields closed-form expressions for spectral observables and their dynamics, including Green-function-derived coherence and PLV, perturbative PAC, and a five-parameter “personality map” linking microscopic physics to macroscopic brain states. By unifying noisy limit-cycle theory with operator methods from statistical physics, we introduce a tractable, interpretable formalism for understanding neural coherence as the dynamics of quantised phonons.
Effects of PZT Reinforcement on the Properties of Fe-Based Composites Fabricated by Powder Metallurgy
(MDPI, 2026-02-05) Alshammari, Yousef; Parol, Jafarali; Yang, Fei; Bolzoni, Leandro
Fe composites are highly valued for their unique mechanical and magnetic properties, making them essential in various industrial applications. This study represents the first reported attempt to combine PZT into an Fe matrix, aiming to develop novel Fe-PZT composites. The primary objective was to assess how the concentration of PZT influences the properties of these composites. The results show that increasing the PZT content in Fe-xPZT composites (where x = 1, 5, and 10 wt.%) reduces the relative sintered density. Microstructural analysis reveals that the composites with higher PZT levels contained numerous large, irregularly shaped pores due to a pronounced Kirkendall effect and limited densification. Furthermore, the evaporation of the volatile PbO compound was observed to affect the thermal stability of the PZT system, leading to reduced composite homogeneity. SEM analysis showed the formation of intermetallic compounds corresponding to Fe2Ti, FeTi, and FeZr2. Finally, an increase in PZT content tends to degrade the tensile and mechanical properties of the Fe-xPZT composites, though they still do not fail catastrophically. These preliminary findings prove the concept of the feasibility of producing Fe-PZT composites and set the basis for the optimization of their manufacturing process. This should eventually unlock the possibility of producing multifunctional materials.
Machine learning-based prediction of young’s modulus in Ti-Alloys
(MDPI, 2026-02-19) Dinibutun, Seza; Alshammari, Yousef; Bolzoni, Leandro
This study explores the use of machine learning to predict the experimental Young’s modulus of titanium alloys based on their mechanical and microstructural properties. Several regression models were developed and compared, including Random Forest, XGBoost, CatBoost, Multi-Layer Perceptron, and a Stacking Regressor. Among these, Random Forest, XGBoost and CatBoost achieved the most accurate results with R² values above 0.85. To improve interpretability, SHapley Additive exPlanations were applied to examine which input features most strongly influenced the predictions. The results showed that yield strength, hardness, and the molybdenum equivalent parameter (moe) were among the most influential descriptors. While yield strength and hardness were positively associated with the predicted values, higher moe values corresponded to lower predicted Young’s modulus. This study focuses on the prediction of Young’s modulus, a comparatively less explored elastic property in Ti-alloy machine learning studies and combines systematic model comparison with SHAP-based interpretability to provide physically consistent insights into feature–property relationships.
On the precipitability of binary Ti alloys bearing 4-period d-metal eutectoid stabilisers
(Elsevier, 2026-06) Bolzoni, Leandro; Yang, Fei
There is no specific, simple approach for predicting whether the addition of an eutectoid beta stabiliser to Ti leads to an ‘active’ eutectoid transformation upon primary processing (e.g., sintering). Here, we demonstrate that, among theoretical/empirical models, phase diagram features, and electronic structure parameters, the hypoeutectoid area is the best predictor, followed by the molybdenum equivalent parameter (MoE), of the precipitability for 4-period d-metals. As the area increases, which corresponds to the addition of progressively stronger β-eutectoid stabilisers, the less active the eutectoid phase transformation, changing from pearlitic to bainitic (i.e., need for an ageing heat treatment). This occurs if the MoE weighted coefficient is, respectively, lower than or higher than 1. This is because molybdenum is taken as reference, and the higher the coefficient, the larger the drop of the β transus temperature (i.e., higher stabilisation). Valid for 4-period d-metals, it remains to be proven for 5-period and 6-period d-metals.
Tephra seismites - Understanding seismic hazard of hidden faults by analyzing liquefied tephra layers in lakes
(American Association for the Advancement of Science, 2026-02) Kluger, Max O.; Melchert, Richard A.; Moratalla, José M.; Ilanko, Tehnuka; Lowe, David J.; Moon, Vicki G.; Villamor, Pilar; Chaneva, Jordanka; Ross, Nic; Orense, Rolando P.
Assessing seismic hazards in regions with hidden or poorly expressed faults is one of the major challenges in paleoseismology today. Here, we used computed tomography imaging to quantify the dimensions and distribution of liquefaction structures in ≤17.5-thousand-year-old tephra layers in 18 lakes scattered across the poorly expressed Hamilton Basin fault system in northern New Zealand. These "tephra seismites," embedded in unconsolidated, organic-bearing lake sediment, increase in occurrence and dimensions toward known faults and indicate the occurrence of a local hidden fault segment. Through incorporating peak ground acceleration modeling, we found that the spatial distribution of tephra seismites directly relates to the ground shaking induced by near-field fault ruptures. We used the variability in tephra seismites within the stratigraphic record and tephrochronology to better constrain the recurrence intervals and magnitudes of paleoearthquakes from both the Hamilton Basin and adjacent Hauraki Basin fault systems. Our methodology is globally applicable in volcanic and tectonic regions where liquefaction structures are preserved among (hidden) faults.
Student perceptions of paid and unpaid work placements: A comparative analysis
(WACE (Advancing Cooperative & Work-Integrated Education), 2024) Zegwaard, Karsten E.; Adams-Hutcheson, Gail; Zegwaard, Karsten E.; Fleming, Jenny
Work-integrated learning (WIL) is an educational approach that is highly authentic and meaningful, therefore, some of the challenges within can be complex. Student wellbeing has been a focal point within higher education for some years (Konstantinou et al., 2023), albeit the debate around unpaid work placements has only recently been given some scholarly attention (see, e.g., Hoskyn et al., 2023).
Work-integrated learning in higher education
(2024) Zegwaard, Karsten E.
Seminar presented at University College Cork, Ireland, on the definition of WIL, design of quality WIL frameworks and the different models of WIL such as curricular, co-curricular and extra-curricular activities. Also international perspectives - developments from various countries including New Zealand, Australia, Canada, and Germany. Discussions included the critical role of WIL in enhancing employability outcomes for students and detailing the University of Waikato’s approach to integrating WIL into their curriculum, which includes compulsory WIL components across all disciplines.
Time's scales: Working with time at Roonka
(2023) Littleton, Judith; Allen, Harry; Emmitt, Joshua; Karstens, Sarah; Petchey, Fiona; Walshe, Keryn
The site of Roonka, subject of long-term excavation by Graeme Pretty and volunteers under the aegis of the South Australian Museum, is still the most extensive excavation of a Holocene burial ground in Australia. The Roonka project between the University of Auckland and the River Murray and Mallee Aboriginal Corporation began in 2014 with the aim of re-analysing the mortuary customs and human remains through the lens of time prior to repatriation. Rather than assuming a single site function e.g. a cemetery or a history which can be divided into two phases (e.g. pre- and post-ENSO), we aim to trace changes in human health and behaviour over the Holocene as people adapted or accommodated changing conditions – the cycle of change and resilience. This means thinking through the nature of the record and the periods of time within it – the event of death, precise memories of other events, the life history of an individual, discontinuous records of site formation, long term continuities of cultural change and differential preservation. In this paper we go back to that original set of ideas and consider how the work and conversations we have had with each other have added more elements of time and different conceptions of what matters. We now have a much clearer model of site formation, taphonomic processes, long term cultural practices and short term catastrophes of individual lives. But what has been added to our sense of time? Ideas of time here in Australia versus time elsewhere, legacy archaeology, the rapidity of time’s change post 1830, COVID time, lived time, research project time… In this paper, we analyse how these different aspects of time interact or remain separate, are useful in different circumstances and provide new interpretations of Roonka and its people.
Advice on the use of models to support estuarine outcomes
(Environmental Research Institute, The University of Waikato, 2025) Ellis, Joanne I.; Flowers, Georgina; Gladstone-Gallagher, Rebecca; Pilditch, Conrad A.; Hewitt, Judi ; Maradasz-Smith, Anna; Thrush, Simon; Thomas, Sam
As the interface between the land and sea, estuaries are uniquely distinctive and dynamic environments. They are highly productive and provide numerous ecosystem services (e.g., improving water quality, supporting fisheries, protecting our coastline). The diversity of habitats contained within estuaries (e.g., crab burrows, seagrass meadows, worm mats, shellfish beds) support a wide array of species that are critical for ecosystem functioning and integrity. Unfortunately, the Our Marine Environment 2019 report clearly identified continued national degradation of the marine environment, particularly for estuaries. Subsequent reports in 2022 and 2025 have not indicated any reversal of these trends.

Browse

Recent Submissions