Food Web Model Research Articles

The Soil Food Web Model as a Diagnostic Tool for Making Sense out of Messy Data: A Case of the Effects of Tillage, Cover Crop and Nitrogen Amendments on Nematodes and Soil Health

Tillage, cover crops (CC) and nutrient amendments are regenerative agricultural practices (RAPs) which enhance desirable ecosystem services (DESs), including the beneficial nematode community structure (BNCS), soil organic matter (SOM), pH, and available nitrogen, and the Ferris et al. soil food web (SFW) model relates changes in the BNCS to biophysicochemical conditions generating DESs. However, the SFW model’s power to identify soil health conditions influencing DESs’ outcomes has been limited. We tested how tillage, winter rye CC, and 0, 112, or 224 kg N/ha from inorganic and compost sources affected the DESs after four years of corn production. The SOM and NO3 was much greater in the no-till than the tilled soil, and the SOM in the 224 kg organic source, compared with the rest of the N rates, was significantly increased. The N recovery was not proportional to what was applied. The variable effects of the RAPs on the DESs suggest either changing or continuing treatments until suitable outcomes are achieved, all without knowing the source(s) of variability. The SFW model revealed primarily resource-limited and structured (Quadrant C) conditions, suggesting that (1) nutrient cycling needs biological activities and (2) the presence of a process-limiting factor may have contributed to the variable results. The impacts of the SFW model as a diagnostic tool are outlined.

A systematic review on the use of food web models for addressing the social and economic consequences of fisheries policies and environmental change

A systematic review on the use of food web models for addressing the social and economic consequences of fisheries policies and environmental change

Matrix Differential Equation Modeling Of Sex Ratio Change And Multivariable Effect Analysis Of Ecosystem

Adequacy of food supply has a significant effect on the sex ratio of juvenile sea lampreys, which also adjusts to changes in the external environment, influenced by resource availability, position in the food web, and ecological niche. Therefore, it is necessary to pay attention to the effects of changes in sea lampreys' sex ratio on ecosystem interactions. In this paper, we constructed an ecosystem model. We comprehensively analysed the impacts of sea lamprey's sex ratio changes on the ecosystem from the four dimensions of the logistic equation of the population dynamics model, the sex ratio model, the food web model, and the spatio-temporal model1,2,3. The study showed that the sea lampreys population showed adaptability to changes in the environment4 , and its population was affected by ecological niche and resource utilisation; incubation temperature had a significant effect on the sex ratio; the sea lampreys played an important role in the balance between predators and prey; and showed adaptability to the gradient of the environment, suggesting that spatial heterogeneity exists in the ecosystem. The comprehensive assessment showed that the multilevel impacts of the sea lampreys on ecosystems included the regulation of population dynamics, the maintenance of food web balance and adaptation to changes in the environment, thus playing an important role in the stability and functioning of ecosystems.

Food web analysis shows an exacerbated dependence of zooplankton on detritus in oligotrophic systems due to ocean warming

Ocean warming can affect plankton both directly, through altered metabolic activities, and indirectly, modifying the physical–chemical properties of the water column, with possible effects on ecosystem functioning. To evaluate the combined action of warming-related physiological responses and environmental changes on plankton assemblage functioning, we carried out a long-term analysis (from 1994 to 2019) of the Bermuda Atlantic Time-series Study (BATS) dataset where ocean warming and stratification have driven a decrease in net primary production over the last decade. Using the time series of plankton observations, we assembled 1000 replicates of a food web model for each year. We observed that the total flow of matter through the model remained constant over time, despite the increased oligotrophication, due to global warming, after 2014. In fact, the plankton food web remained robust through re-modulated trophic interactions with an increased detritivory to herbivory ratio of the food web over time. Moreover, there was difficulty to re-establish broken trophic connections of the food web (increased relative internal ascendency) due to global warming. Thanks to trophic plasticity, the reduced zooplankton dependence on herbivory was compensated by significant increase in the dependence on carnivory and detritivory, highlighting the crucial role of trophic interactions in buffering significant environmental short-term changes.

The value of information in predicting harmful algal blooms

Environmental decision-making is inherently subject to uncertainty. However, decisions are often urgent, and whether to take direct action or invest in collecting additional data beforehand is pervasive. To make this trade-off explicit, the value of information (VoI) theory offers a powerful decision analytic tool to quantify the expected benefit of resolving uncertainty in a decision context. Although it is mainly used in economic contexts, it can be applied to biodiversity conservation and management.In our approach, we evaluate the expected surplus in resolving uncertainty about the occurrence of harmful algal blooms (HABs) in the German North Sea coastal waters and the effect on decision-making. We use an established dynamic foodweb model (NPPZ) with two competing phytoplankton consortia (harmful, non-harmful) and regional monitoring data to analyse the prediction accuracy of different indicators. Our analysis revealed a prediction accuracy of a HAB occurrence of 0.65 % if additional information on zooplankton is included. We then evaluate the effect of reducing uncertainty about these indicators (e.g., through extended monitoring) on management decisions employing a VoI analysis. We find that additional information may lead to an expected welfare gain of up to 2.67 million Euro in our decision context. Our results highlight the significant potential for VoI analysis to enhance decision-making in fishery and ecosystem management and provide insights for future monitoring strategies to mitigate the adverse effects of HABs. This approach contributes valuable methodological insights for optimising management strategies and further emphasises the importance of considering uncertainty in decision-making processes.

A role of fear on diseased food web model with multiple functional response.

In this paper, we analyze the role of fear in a three-species non-delayed ecological model that examines the interactions among susceptible prey, infectious (diseased) prey, and predators within a food web. The prey population grows in a logistic manner until it achieves a carrying capacity, reflecting common population dynamics in the absence of predators. Diseased prey is assumed to transmit infection to healthful prey by the use of a Holling type II reaction. Predators, alternatively, are modeled to consume their prey using Beddington--DeAngelis and Crowley--Martin response features. This evaluation specializes in ensuring the non-negativity of solutions, practical constraints on population dynamics, and long-term stability of the system. Each biologically possible equilibrium point is tested to understand the environmental stable states. Local stability is assessed through eigenvalue analysis, while global stability of positive equilibria is evaluated by the use of Lyapunov features to determine the overall stability of the model. Furthermore, Hopf bifurcation is explored primarily based on infection rate $\varepsilon$. Numerical simulations are carried out to validate the theoretical effects and offer practical insights into the model behaviour under specific conditions.

Food web bioaccumulation model for ecological risk assessment of emerging organic pollutants in marine ecosystems: Principles, advances and challenges

The bioaccumulation and trophic transfer of pollutants in marine ecosystem members determine their ultimate ecological risks. Food web bioaccumulation models are widely used in scientific and regulatory programs to assess the bioaccumulation and ecological risks of pollutants at the ecosystem scale. The food web models are mainly established through concentration- and fugacity-based modeling approaches and include some chemical, food web-related, physiological and environmental factors. The models applied in the “forward approach” predict bioaccumulation and conduct internal exposure level-based ecological risk assessment (IEL-ERA), whereas those in the “reverse approach” are used to back-calculate the IEL-based predicted no-effect concentrations (PNECs) or environmental criteria. However, some challenges still exist in the application of food web model integrated risk assessment, including the lack of standardized/generalized frameworks, the lack of chemical- and species-specific toxicokinetic data and internal exposure (or tissue residue)-based toxicity data, and the lack of uncertainty-control methods in model estimation and parameterization. There are urgent requirements to improve models, integrate methods and update study designs in the assessment and prediction of “system-scale risks” of marine emerging organic pollutants.

Spatial multi-criteria analysis based on food web model results: application to a marine conservation area

Effective marine management requires balancing conservation and sustainable use of resources. Food web models are useful for simulating direct and indirect effects of management scenarios on ecosystem functioning by using multiple indicators. However, a key challenge is consolidating these indicators into a single, comprehensive, measure, which is often required to guide management decisions, such as in Strategic Environmental Assessment. This study applies spatial multi-criteria analysis to food web model outputs to develop a single index for different marine management applications. We applied this framework to the case of the “Tegnùe di Chioggia”, a Special Area of Conservation (SAC; IT3250047) under the Natura 2000 European network, located in the northern Adriatic Sea (Italy). This area, characterised by the presence of biogenic rocky outcrops, currently lacks a formal management plan. Using the Ecospace module of the Ecopath with Ecosim software, we simulated three management scenarios: 1) SAC expansion; 2) winter artisanal fishing in the SAC; 3) a combination of both. In line with ecosystem-based management, we focused on economically important trophic groups in the region, such as the Mediterranean mussel, Mytilus galloprovincialis, and striped venus clam, Chamelea gallina, which are present near the SAC. We also considered the efforts of the local fishing fleets. Ecosystem structure and functioning indicators, generated by the spatial food-web model, were linked to three criteria aligned with the management priorities of the area: nature conservation, aquaculture productivity, and fishing productivity. These criteria were aggregated into a final score to compare the management scenarios. The results showed that none of the scenarios would significantly alter community composition or ecosystem functioning compared to the current situation. However, they did show contrasting responses in the food web model. The SAC expansion scenario notably increased total biomass and commercial fish biomass, especially pectinids and cephalopods. The fishing scenario had a minimal impact on trophic groups. Ecosystem resilience and structure indicators were less sensitive to management scenarios than biomass indicators. However, the multi-criteria analysis revealed that the fishing scenario limited the benefits of expanding the SAC, due to reduced catches. The final score effectively ranked proposed scenarios, highlighting key indicators that influenced these variations. The proposed approach shows potential for supporting participatory modelling and engaging stakeholders in developing management scenarios.

Evaluating microplastic particles as vectors of exposure for plastic additive chemicals using a food web model

Microplastic particles (MPs) represent potential hazards for humans and wildlife, including as vectors for chemical exposure (e.g. plastic additives and pollutants sorbed from the surrounding environment). The leaching of chemicals from MPs has been identified as a potential exposure pathway but the relative magnitude of this pathway under environmentally relevant conditions remains unclear. Here, we describe a modification of the ACC-HUMANSTEADY bioaccumulation model to include dietary exposure to MPs containing either accumulated chemicals from the surrounding environment or embedded plastic additive chemicals (PACs). Chemical transfer to humans and wildlife is described using two-film resistance concepts assuming spheroidal particles of different sizes. The relative contribution of MPs and environmental media to the estimated daily chemical intake in humans was assessed in various exposure scenarios, for a range of hypothetical chemicals with varying octanol-water and air-water partition coefficients (KOW and KAW, respectively; i.e. 0 < log KOW <8 and − 5 < log KAW < 3). Results imply that MPs could act as sources of exposure to chemical additives when the ingestion rate of 1 μm MPs is ≥ 10 mg d− 1, and the concentration of hydrophobic plastic additive is ≥ 5% wt wt− 1. The contribution made by MPs as vectors of exposure decreased with increasing particle size and decreasing ingestion rates of MPs. Human health risks were evaluated for four specific PACs to illustrate the application of the model for risk assessment. Risks were negligible when the ingestion rate of MPs was < 100 μg d− 1. Uncertainties are high regarding the characterization and quantification of ingestion of MPs by humans and wildlife, including particle sizes and polymer composition, as well as on the presence of PACs in MPs. These data gaps need to be addressed if the issue of MPs as vectors of chemical exposure is to be fully understood. The work illustrates that mechanistic models, which account for all major exposure pathways, can be used to identify the importance of different exposure pathways, help prioritize research needs and support decision making.

Future impacts of reduced freshwater inflow and sea level rise on forage fish and their predators in Apalachicola Bay, Florida

Estuarine ecosystems often support large populations of forage fish, but these small-medium sized fish and the predators they feed may be affected by multiple climate change and human-induced stressors. In the Apalachicola Bay estuary, Florida, USA, reduced freshwater inflow and sea level rise are two prevalent stressors, and little is known about how these environmental changes might impact the forage fish species who inhabit the estuary. This study uses a food web model for Apalachicola Bay to simulate the impacts of future changes in water temperature and salinity on forage fish and predator species who inhabit the estuary. Water temperature and salinity conditions were based on previously developed simulations of reduced freshwater inflow and sea level rise in Apalachicola Bay from 2020 to 2049. These simulated environmental changes were applied as forcing functions in the food web model to drive shifts in species biomasses over time. This study centered on changes in biomass for two highly abundant forage fish species, juvenile silver perch (Bairdiella chrysoura) and juvenile pinfish (Lagodon rhomboides), as well as their major predators, spotted seatrout (Cynoscion nebulosus) and inshore lizardfish (Synodus foetens). These changes were assessed at both 10- and 30-year time intervals relative to 2019, along with an examination of forage fish consumption by their predators. Juvenile silver perch biomass increased across all scenarios and time scales, while juvenile pinfish biomass decreased. Consumption of juvenile silver perch by spotted seatrout increased across all scenarios and time scales, and consumption of juvenile pinfish by inshore lizardfish decreased, in concordance with the trends in prey biomass. Both spotted seatrout and inshore lizardfish biomasses decreased across future scenarios, though the high biomass of juvenile silver perch may have played a role in stabilizing the decline of spotted seatrout. Changes in forage fish biomasses and their impacts on predator species as a result of reduced freshwater inflow and sea level rise have implications for ecosystem productivity and the fisheries of the region.

Lake Restoration Improved Ecosystem Maturity Through Regime Shifts—A Case Study of Lake Baiyangdian, China

Lake ecosystems are impacted by anthropogenic disturbances and have become vulnerable worldwide. Highly disturbed lake ecosystems are not well understood due to the lack of data on changes in the structures and functions of ecosystems. In this paper, we focus on Lake Baiyangdian (BYDL), the largest shallow lake in North China. Following the establishment of the Xiong’an New Area (XNA) in 2017, concerted efforts to restore BYDL’s aquatic environment have been undertaken, which has led to significant changes in the structures and functions of the ecosystems. We evaluated the biomass dynamics of main biological communities and detected the regime shifts of environmental factors in BYDL from 2016 to 2023. Further, we constructed a food web model for the BYDL ecosystem in 2023 by using Ecopath with Ecosim (EwE) and made a comparison with the reported results in 2018. The results showed significant changes in the ecosystem structure of BYDL over the last 6 years. In 2023, the submerged macrophytes biomass in the system increased by 4.2 times compared to 2018, leading to an increase in total system throughput. We found that BYDL changed from an algal-type lake to a macrophyte-dominated lake. In addition, we found TN, NH4+-N, and CODMn were significantly decreased in BYDL during the restoration. TN and NH4+-N had a change point in approximately 2021, indicating that a regime shift had occurred during restoration. Overall, the BYDL ecosystem was in an immature but developing state, as indicated by ecological network analysis indicators. Nutrient-loading reduction, hydrological regulation, and rational biomanipulation may be the potential driving factors of change in the BYDL ecosystem. We strongly recommend the timely harvesting of submerged macrophytes, the proliferation and release of herbivorous fishes, and the assessment of the ecological capacity of carnivorous fishes in the future ecological restoration of BYDL.

Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation

Capturing ecological data variability in food web models is an important step for improving model representation of empirical systems. One approach is to use linear inverse modelling and Markov Chain Monte Carlo (LIM-MCMC) techniques to set up an inverse LIM problem using empirical data constraints, and then sample multiple plausible food webs from the inverse problem using an MCMC algorithm. We describe the set of plausible food webs as an ‘ensemble’ of solutions to the inverse problem sampled with the LIM-MCMC algorithm. The extent of data variability eventually integrated into an ensemble depends on how well the LIM-MCMC algorithm samples the solution space. Algorithm quality can be adjusted via user-defined parameters describing starting points, jump sizes, and number of iterations or food webs produced. However, little information exists on how each LIM-MCMC algorithm parameter affects the degree of empirical data variability introduced into the ensemble. Further, post hoc algorithm quality diagnostics with commonly used trace plots and the coefficient of variation (CoV) rarely address critical aspects of algorithm quality, such as (1) if the returned ensemble successfully targeted the solution space distribution (stationarity), (2) correlation between ensemble solutions (mixing), and (3) if the ensemble contains enough solutions to adequately capture input data variability (sampling efficiency). Therefore, we used several established MCMC convergence diagnostics to (1) quantify how algorithm parameters affect ensemble flow values and if these differences propagate to ecological indicators and (2) evaluate algorithm quality and compare to current evaluation and ecosystem modelling methods. We applied 30 LIM-MCMC algorithm combinations of varying starting points, jump sizes, and number of iterations to solve food web ensembles from a single food web model. We analysed ensembles with Ecological Network Analysis (ENA) to calculate indicators describing system function. Results show that LIM-MCMC algorithm parameters, in particular the jump size, affect ensemble flow values, which propagate to ecological indicators describing different ecosystem function of the same model. Thereafter, comparisons of post hoc diagnostics show that MCMC convergence diagnostics provided more robust estimates of algorithm quality than trace plots and CoV. Together, these findings underpin several novel recommendations to enhance LIM-MCMC algorithm parameter selection and quality assessments applicable to any ecological ensemble network study.

A temperature tipping point in hypoxic zone size

AbstractTemperature increases will have ubiquitous effects on aquatic food webs, from microbes to consumers, and affect the quality and quantity of carbon flows within and between water layers. A decline in the biological pump moving carbon from surface to lower layers is anticipated. We reviewed 37 years of data on hypoxic zone size and water quality in the northern Gulf of Mexico to determine if air and bottom water temperature increases (0.5°C decade−1) are significantly related to variations in its areal size. There was no significant decline in important river water quality in the 24 years since the national Hypoxia Action Plan was developed to reduce its size. Changes in the ratio of km2 hypoxia per 1000 mt nitrate loading from the Mississippi River from 2000 to 2023 reveals a tipping point in the hypoxic zone size that is driven by ocean warming. Biological factors varying with temperature such as ectotherm growth rates, zooplankton grazing, cell sinking rates, and diatom sequestration of Si or N are apparently more important influences on recent hypoxic zone size than variations in physical factors. This tipping point may be common to similarly warmed and eutrophic coastal waters where warming will likely result in diminished oxygen deficiency (&lt; 2 mgO2 L−1). Hypoxia and food web models assuming a stationary equipoise of nutrient loadings, ratios and food webs will be deficient as coastal waters warm further, coastal storm and hurricane frequency increase and land uses in the watershed are altered with climate change.

A food-web assessment model for marine mammals, fish, and fisheries in the Norwegian and Barents Seas

The Norwegian and Barents Seas host large commercial fish populations that interact with each other, as well as marine mammal populations that feed on plankton and fish. Quantifying the past dynamics of these interacting species, and of the associated fisheries in the Norwegian and Barents Sea is of high relevance to support ecosystem-based management. The purpose of this work is to develop a food-web model of intermediate complexity and perform a quantitative assessment of the Norwegian and Barents Sea ecosystems in the period 1988–2021 in a manner that is consistent with existing data and expert knowledge, and that is internally coherent. For this purpose, we use the modelling framework of chance and necessity (CaN). The model construction follows an iterative process that allows to confront, discuss, and resolve multiple issues as well as to recognise uncertainties in expert knowledge, data, and input parameters. We show that it is possible to reconstruct the past dynamics of the food-web only if recognising that some data and assumptions are more uncertain than originally thought. According to this assessment, consumption by commercial fish and catch by fisheries jointly increased until the early 2010s, after which consumption by fish declined and catches by fisheries stabilised. On an annual basis, fish have consumed an average of 135.5 million tonnes of resources (including 9.5 million tonnes of fish), marine mammals have consumed an average of 22 million tonnes of which 50 % (11 million tonnes) were fish. Fisheries and hunting have captured an average of 4.4 million tonnes of fish and 7 thousand tonnes of marine mammals.

Ecological networks reveal important taxa for ecosystem function in two subtropical South African estuaries

Biodiversity is essential for estuarine ecosystems' functioning, resilience, and persistence. While biodiversity assessments provide some insight into the ecosystem state, they cannot quantify every aspect of ecosystem-level function. We assessed aspects of estuarine ecosystem function and pinpointed taxa of interest that fulfil specific roles in estuarine ecosystems, using a series of novel food web model ensembles and Ecological Network Analysis. We investigated emergent network properties of two subtropical South African estuaries, the anthropogenically impacted large temporarily closed uMdloti Estuary and the ‘near natural’ predominantly open uMlalazi Estuary, during a drought period induced by the El Niño Southern Oscillation. In addition, important network components were identified to elucidate the importance of estuarine/marine taxa in maintaining ecosystem function. The key findings included (1) estuaries exhibit system-specific functional responses under drought conditions, and (2) estuarine/marine taxa are critical for overall ecosystem function. Both estuaries showed seasonal differences in ecosystem activity and reliance on trophic level I (microalgae and detritus) to fuel the food web, and persistently low cycling (<9.3 %). However, compared to uMdloti Estuary, uMlalazi Estuary showed less variation in mean seasonal activity (1597–2095 mgC m−2 d−1), and higher reliance on detritus to fuel the food web (D:H > 2.02), indicating greater ecosystem functional resilience to external perturbations. uMlalazi Estuary ecosystem function could be attributed to predominantly open mouth conditions maintaining a salinity gradient, and subsequent large contributions to overall ecosystem function from typically estuarine/marine invertebrate taxa. In contrast, the uMdloti Estuary, dominated by freshwater/brackish taxa under prolonged closed mouth conditions, showed greater seasonal variations in mean system activity (1084–2289 mgC m−2 d−1) and generally high reliance on microalgae (D:H < 1.26), indicative of decreased resilience to external perturbations. During this study, a single mouth breach acted as a ’biological reset’ of uMdloti Estuary, enabling recruitment of estuarine/marine taxa, and a temporary recovery in ecosystem function reflected in increased system cycling (FCI >14.05 %) and decreased reliance on microalgae (D:H > 1. 41). These findings suggest that future predicted drought impacts on estuarine ecosystem function may be partially system-specific due to differing estuarine types, anthropogenic impact, and invertebrate community composition. This study provides a scientific link between ecosystem-level indicators and the role of individual taxa within the system, which is a valuable complement to biodiversity assessments and ecosystem state evaluation.

Drivers of trophodynamics of the open-ocean and deep-sea environments of the Azores, NE Atlantic

Marine ecosystems associated with mid-oceanic elevations harbour unique pelagic and benthic biodiversity and sustain food webs critical for Nature’s contributions to people (NCP). The United Nations Sustainable Development Goals and the Convention on the Law of the Sea recognize the need to implement ecosystem-based management approaches to conserve the structure and functioning of oceanic and deep-sea ecosystems within sustainable reference points. However, uncertainties regarding the interactions between multiple drivers of change, and their impacts on the state of these ecosystems and the NCP, present significant challenges to effective management. Trophic models offer a holistic approach to identify the main drivers affecting the dynamics of marine ecosystems. Here, we used a food web model of the open-ocean and deep-sea environments of the Azores for identifying the drivers that best explain historical biomass trends of demersal fish of high commercial value. Our hindcast simulations suggested that historical trends can be explained by the combined effects of deep-sea fisheries exploitation and variability in environmental conditions, likely dominated by primary productivity anomalies. In particular, deficits in primary production and high levels of fishing exploitation might have contributed to the pronounced decline in biomass observed between 2008 and 2012. These findings reinforce that failure to consider environmental factors in ecosystem-based management may result in shortfalls at achieving biodiversity conservation and sustainability objectives, particularly in the context of climate change.

Numerical modelling of radionuclide uptake by bluefin tuna along its migration routes in the Mediterranean Sea after a nuclear accident

A numerical model which simulates the adsorption of radionuclides by migrating bluefin tuna in the Mediterranean Sea is described, in order to determine the level of contamination of these fish after a hypothetical nuclear accident and thus be able to assess the possible impact on human consumption. A 4–species foodweb model is incorporated into a Lagrangian model describing physical transport (advection, mixing, radioactive decay and interactions of radionuclides with sediments). Tuna is the last trophic level in the foodweb model and the equation providing the temporal evolution of radionuclide concentration in its flesh is solved along the fish trajectories, which were obtained through electronic tagging of fishes. The model was applied to the western Mediterranean, where several worst–case hypothetical accidents were simulated, both from a coastal nuclear power plant and from a vessel. Resulting 137Cs concentrations in migrating tuna were similar, or slightly higher, than reported background concentrations in these fishes and well below established safety levels. Maximum calculated concentrations in tuna flesh is in the order of 1 Bq/kg (wet weight). This is due to the rapid movement of the fishes, which spend only limited time over the most contaminated spots.

Developing a dynamic energy budget model to project potential effects of deep-sea mining plumes on the Atlantic deep-sea mussel, Bathymodiolus azoricus

Due to the consistent lack of Environmental Risk Assessment (ERA) for deep-sea mining scenarios, the potential impacts of this industry on marine ecosystems remain largely unknown. In order to fill this gap, a Dynamic Energy Budget (DEB) model was developed to study the consequences of toxic sediment plumes derived from deep-sea mining on the energy budget of the Atlantic deep-sea mussel, Bathymodiolus azoricus. Model calibration was based on environmental conditions observed at the Menez Gwen (MG) vent field (Mid-Atlantic Ridge- MAR), assuming a B. azoricus lifespan of 10 years and a maximum shell length of 119 mm. Scenario simulations were conducted to mimic the effects of increased concentrations of toxic sediment plumes on mussel filtration rates, the absorption of reduced substrates by their endosymbionts, and the energetic costs associated with metal toxicity. Data were sourced from B. azoricus and, when necessary, from proxy species. One disturbance scenario (EF1) incorporated measured rates and realistic parameters, while the other (EF2) was intentionally designed to encompass cumulative effects and uncertainties, representing a potential worst-case scenario. Both disturbance scenarios were initiated at three different timings (0, 1200 and 2400 days) to accommodate the mining effects at different stages of the mussels' life cycle. Results indicate that B. azoricus is significantly impacted by toxic sediment plumes, particularly during earlier life stages, potentially leading to severe growth impairment and mortality. These results were integrated into a food web model of the MG vent field, revealing that disruptions to the energetic balance of the vent mussel have widespread consequences for the entire ecosystem. Overall, we argue that this numerical framework offers a valuable tool for conducting ERA and Environmental Impact Assessments (EIA) in the context of industrial deep-sea mining.

The dynamic of two prey–One predator food web model with fear and harvesting

This study presents a predator-prey model within a food web, incorporating the impact of fear responses in prey and the effects of harvesting. The analysis begins by exploring equilibrium points and assessing the boundedness and uniqueness of the model's solutions. The local stability of each of the seven possible equilibrium points is then evaluated. To determine global stability, a suitable Lyapunov function is utilized. Finally, numerical simulations are carried out across different parameter values, with graphical representations provided to support the analytical findings.

Ecosystem engineering and food web stability

Ecosystem engineering, which involves organism-triggered physical modification of the environment, is a widespread phenomenon. Despite this, the role of engineering in ecological communities remains poorly understood. This study employs a food web model to uncover the key roles of ecosystem engineering in maintaining food webs. While engineers facilitating population growth and suppressing consumers’ foraging activity can help maintain complex communities with diverse species, engineering effects that suppress population growth and facilitate consumers’ foraging activity can largely destabilize community dynamics. Furthermore, in the middle levels of engineering-related species within a community, an increase in species richness can increase community stability, contrary to classical ecological prediction. The study findings suggest that ecosystem engineering can explain biodiversity persistence in nature, but it depends on the proportion of engineering-related species and how engineering affects organisms.