Key Expoitable Results (KERs)

The Benguela Upwelling System is one of the most productive marine coastal ecosystems globally, driven by wind-induced upwelling of cold, nutrient-rich deep waters. However, the system’s complexity, combined with data scarcity, has left its dynamics and long-term response to a warming climate insufficiently understood. This study employs a high-resolution coupled physical-biogeochemical modeling system, using a two-way nesting strategy, to investigate the dynamics of the Benguela Upwelling System over a four-decade period (1980–2020). The physical model component, the Nucleus for European Modeling of the Ocean (NEMO), is coupled with the Biogeochemical Flux Model (BFM) to reproduce both physical and biogeochemical dynamics within a high-resolution Benguela domain. The physical component demonstrates good skill in replicating observational annual and seasonal climatologies of seawater temperature, salinity, and near-surface currents. The simulated biogeochemical fields satisfactorily compare with observational datasets available in the Benguela region for inorganic nutrients, dissolved oxygen, and upper ocean Chlorophyll-a (Chl-a) concentrations. Model outcomes were then used to investigate the long-term sea surface temperature and Chl-a trends by focusing on the upwelling zone, where a cooling trend was detected in both the northern and southern Benguela subregions, suggesting the occurrence of an upwelling intensification in recent decades. Although a positive Chl-a trend was observed in both subregions, the loose correspondence in either location or timing with the surface temperature signal indicates that algal growth is only partly influenced by the upwelling intensity. This coupled modeling framework provides valuable insights into the Benguela Upwelling System and could serve as a basis for improving our understanding of the variability in physical and ecological processes over recent decades.

Revealing the ongoing changes in ocean dynamics and their impact on marine ecosystems requires the joint analysis of multiple variables. However, global observational records only cover a few decades, posing a challenge in the separation of climatic trends from internal dynamical modes. Here, we apply an empirical stochastic model to identify the emergent patterns of trends in six fundamental components of upper ocean physics. We analyze a data-driven reconstruction of the ocean state covering the 1993–2018 period. We found that including temporal derivatives in the state vector enhances the description of the ocean’s dynamical system. Once Pacific oscillations are properly accounted for, averaged surface warming appears >60% faster, and a deep reshaping of the seascape is revealed. A clustering of the trend patterns identifies the main factors that drive observed trends in chlorophyll a concentration. This data-driven approach provides a wider framework for empirical climate modeling.

Microfluidic technology can expedite nucleic acid testing by converting the functions of bulky laboratory instruments and protracted bench methodologies into easy-to-use and inexpensive miniaturised systems without compromising speed and reliability. We developed a lab-on-a-chip (LOC) platform that integrates a dimethyl adipimidate (DMA)-based functionalised silica DNA isolation and pre-concentration method with a rapid and real-time loop-mediated isothermal amplification (LAMP) for detecting domoic acid-producing phytoplankton, Pseudo-nitzschia. An optimised design of a lab on a chip extraction module achieved a maximum DNA capture capacity of 61.73 ± 0.98 ng μL−1. The DMA-based method reduced reagent costs per sample by 97% compared to a commercial nucleic acid isolation kit. A subsequent on-chip LAMP process was capable of sensitively quantifying cytochrome P450 homologous to the dabD gene, coding for a component of the domoic acid toxin production pathway, with a limit-of-detection of 10 cells per mL. LAMP-based detection of the target gene was achieved using dry-preserved reagents with a shelf-life of five months without refrigeration. There was no significant difference in assay performance between the preserved LAMP and freshly prepared LAMP mixtures. The total analysis time at the LOD of 10 cells per mL, from sample to result, was achieved within one hour. Our results demonstrate the long-term stability of assay reagents, rapid turnaround, and cost-effectiveness, offering a simple and economical approach to environmental monitoring and environmental bio-hazard diagnostics.

The physical environment both above and below the ocean surface has changed dramatically during the last century. Changes in the marine environment induced by increased release of greenhouse gases and direct exploitation of resources include increased ocean temperature, decreased salinity and pH, and removal of apex predators. The risk of ecological regime shifts occurring has similarly increased. A variety of methodologies to identify regime shifts have already been used in the North Sea, which has become an important case study for the analysis of regime shifts in a semi-enclosed waterbody. The North Sea is regarded as a case study in part due to the operation of the continuous plankton recorder, which has provided detailed abundance records of phyto- and zooplankton for over 60 years. Here, we propose a new methodology to calculate regime shift likelihood for every month between 1958 and 2020. This unique model produces a single time series of regime shift likelihood, using sequential abundance data of more than 300 plankton species. We show the model's ability to identify when regime shifts occurred in the past by comparing it to previous less automated methodologies. We have validated the model for use in the North Sea by estimating how often false positives and false negatives are generated. Results from the model indicate evidence for three periods of high regime shift likelihood in various parts of the North Sea: between 1962 and 1972, between 1989 and 1999, and from 2002 until 2015. We show that these periods are consistent with previous estimates of North Sea regime shifts, and discuss possible applications of the model's output of a single time series.

Managing the risks associated with human activities and uses in marine and coastal regions is crucial in a time of maritime activity expansion promoted by Blue Growth, especially with the increasing effects of climate change. Effective management of the cumulative risks is essential to safeguard ecosystems from potential further degradation, maintaining their resistance and resilience and ability to provide ecosystem services (ES) and societal goods and benefits (SGB). Here, we adopt a cumulative risk-based approach to assess risk to habitats and ecosystems, considering human activities and two climate-derived pressures for three management narratives, across three IPCC Shared Socioeconomic Pathways in the northern marine and coastal region of Portugal. Our findings highlight high ecosystem risk in some marine areas and coastal segments, particularly affecting beaches, aphotic soft and rock bottoms, and estuarine areas. Across the management and climate scenarios, the most important contributors to risk included rising sea surface temperatures, increased coastal exposure to relative sea-level rise (SLR) and storminess, fishing, tourism, artificial areas, and maritime transport. Overall spatial risk patterns varied more with changes in management scenarios than between climate scenarios, with climate pressures having an additive effect on habitat and ecosystem risk. The inclusion of the climate-derived exogenous pressures (i.e. those whose causes emanate from outside the management system) altered the high-risk zone spatial patterns at the land-sea interface, while in marine areas, it increased the overall risk scores without changing the observed overall risk patterns. It is recommended that policymakers and managers should adopt a precautionary approach, using cumulative assessments integrated into decision-support systems and ecosystem-based management plans to anticipate and adapt to or mitigate future changes. Thereby, ensuring the maintenance of the ecosystem resilience to change, to avoid reaching tipping points that would disrupt the resource-provisioning capacity of these ecosystems and the provision of ES and SGB.

The present deliverable (D4.4) reports on AtlantECO’s Handbook of Standards and Best Practices. It was developed throughout the project, and its content is presented in three deliverables (D4.1, D4.2 & D4.4), which are all publicly accessible under a single DOI (https://doi.org/10.5281/zenodo.4897860) and also available via UNESCO’s Ocean Best Practices. AtlantECO generated new observations as part of the project’s sampling activities in synergy with other European and International projects (see deliverable D4.7). The Handbook provides a set of Standard Operating Procedures (SOPs) for methodologies used across these activities to study the Ocean microbiome. These SOPs also constitute a basis for comparing protocols and aggregating results from different observation programmes. The SOPs are generic and describe key methodological concepts, materials and procedural steps, which gives the different observation programmes enough flexibility to adopt the standards and best practices and adapt the SOPs to their specific context.