Dynamic Energy Budget Research Articles

Linking individual experiments and multiscale models to simulate physiological perturbations on aquatic food webs

Numerous threats affect aquatic ecosystems at different biological organizational levels from individuals to ecosystems. Stresses occurring on the metabolism and physiological functions of individuals can have repercussions on the individual behavior, its ability to survive and reproduce, also known as the individual fitness, which may then influence the demography and spatial distribution of populations, and ultimately modify trophic flows and ecosystem functioning. In a context of a globally changing environment, predicting the life history traits and fitness of individuals can be relevantly performed with the association of laboratory experiments with Dynamic Energy Budget (DEB) theory, while modeling species interactions have proven to be an efficient tool to understand aquatic food webs using mass-balanced models such as linear inverse models (LIMs) or Chance and Necessity (CaN) models. However, while predictive results obtained on individuals can be provided with a thorough mechanistic interpretation, the propagation of the effects is most often limited to the closest biological hierarchical level, i.e., the population, and rarely to the food-web level. Furthermore, there is a need to understand how to avoid misleading approaches and interpretations due to the simplicity of experiments. For the moment, no clear methodology has stood out yet to do so. In this study, we provide a new methodology based on a combination of models (i.e., DEB, LIM, and CaN) aiming at upscaling information from laboratory experiments on individuals to ecosystems to address multiple ecological issues. This framework has a potential to enhance our understanding of higher-scale consequences of the effect of stressors measured at the sub-individual scale. This combination of models was chosen for the convergence of their framework but also their ability to consider a substantial portion of the projected uncertainty. The description of this methodology can help experimenters and modelers to jointly address a specific question involving upscaling from individual to ecosystem, proposes approaches, and gives tips on the pitfalls to avoid along the upscaling process.

Exploring aquaculture related traits of the grooved carpet shell (Ruditapes decussatus) in relation to other bivalve species using Dynamic Energy Budget theory

To assess the potential of the grooved carpet shell (Ruditapes decussatus) for aquaculture in Europe, we used Dynamic Energy Budget (DEB) theory to perform extensive parametrization on the species and compared its energy allocation strategy with those of commonly farmed bivalve species: mussels (Mytilus edulis and Mytilus galloprovincialis), oysters (Ostrea edulis and Magallana gigas), the common cockle (Cerastoderma edule), and great scallop (Pecten maximus). The comparison was based on DEB primary parameters relevant to aquaculture production, such as maximum assimilation rate and kappa, which represents the fraction of energy allocated to maintenance and growth, and compound parameters like the von Bertalanffy growth coefficient and maximum storage density. Furthermore, we evaluated the production efficiency at the population level, which represents the ratio of assimilated energy converted into biomass. Our results revealed notable differences in energy utilization strategies among species. However, uncertainties in parameter estimation and environmental factors challenge the direct translation of these parameters to real-world aquaculture, therefore our interpretation focuses on how these parameters might influence a species’ potential for aquaculture. The grooved carpet shell exhibits a balanced energy allocation strategy with a low growth coefficient and low maintenance costs, leading to high production efficiency. Similarly, the common mussel focuses on growth with significant biomass investment over reproduction, while the Pacific oyster and Mediterranean mussel prioritize reproductive development. The flat oyster and scallop demonstrate rapid growth at the cost of the low production efficiencies. The grooved carpet shell and mussels face constraints such as limited reserves, making them comparatively more susceptible to low food quality and quantity. In contrast, high storage densities in species like the common cockle, scallop, and Pacific oyster suggest resilience to fluctuating food conditions. These findings, along with both agreements and discrepancies with existing literature, highlight the need for further experimental research to refine DEB parameters and enhance their application in aquaculture. Overall, the DEB framework proves effective for exploring aquaculture traits across species and underscores the need for additional work on temperature-related processes, life-history events, and morphological variation.

Assessing between-individual variability in bioenergetics modelling: Opportunities, challenges, and potential applications

Population dynamics is influenced by between-individual variability. Dynamic Energy Budget (DEB) theory is an appealing framework for assessing such a variability, yet DEB parameters have rarely been estimated at the individual level. Bayesian hierarchical models show promise for inferring individual variability in DEB parameters, thought computational challenges have limited their use due to the need to solve differential equations. Timely, Stan has emerged as a general-purpose statistical tool for fitting dynamic models. This paper introduces an analytical strategy using Bayesian parametric inference and hierarchical modelling to estimate individual-specific DEB parameters. Two biologically relevant DEB parameters were successfully estimated for 69 Gilt-head breams (Sparus aurata) with up to 11 measures of length and wet weight each. The estimated between-individual variability in these two DEB parameters explained well the observed patterns in length and weight at between- and within-individual levels. Moreover, data-simulation experiments highlighted the potential and limitations of our approach, suggesting that improved data collection could enable to increase precision and the number of DEB parameters that can be estimated at the individual level. This strategy can better represent between-individual variability in DEB parameters, which ultimately may improve forecasting of population dynamics after integrating DEB into population models.

From formulae, via models to theories: Dynamic Energy Budget theory illustrates requirements

As sciences mature, they transition from observation and description to explanation and prediction. This transition is associated with qualitative changes in the way quantitative mathematical formulations are constructed and interpreted, resulting in a ‘theory’. Such transitions from phenomenology to theory are happening in biology but the heuristic framework involved is rarely articulated. We here describe how the use of models in research sets model requirements, using Dynamic Energy Budget (DEB) theory to illustrate the more elaborate ones. We first make the distinction between mathematical formulae and models based on their relation to the abstract and real worlds. We then explain how the transition from models to theory affects model construction and parameter estimation, and discuss the concept of parameter estimation-in-context using the database Add_my_Pet on animal energetics. The transition comes with the need to develop auxiliary and meta- theory and to work with multiple datasets, implying constraints for the loss function that is used for parameter estimation. Finally, we discuss the extra requirements for general explanatory models: they need to be explicit on relevant general principles and to be embedded in a wider scientific context. We also discuss how we see theory’s relationship to observation and prediction change in the future as we use it to deal with theoretical and applied problems in biology.

Environmental Risk Assessment of Time-Variable Toxicant Exposure with Toxicokinetic-Toxicodynamic Modeling of Sublethal Endpoints and Moving Time Windows: A Case Study with Ceriodaphnia dubia.

Toxicokinetic-toxicodynamic (TKTD) modeling has received increasing attention in terms of the regulatory environmental risk assessment of chemicals. This type of mechanistic model can integrate all available data from individual-level bioassays into a single framework and enable refined risk assessments by extrapolating from laboratory results to time-variable exposure scenarios, based, for instance, on surface water exposure modeling (e.g., FOCUS). Dynamic energy budget (DEB) models coupled with TKTD modules (DEB-TKTD) constitute the leading approach to assess and predict sublethal effects of chemicals on individual organisms. However, thorough case studies are rare. We provide a state-of-the-art example with the standard aquatic test species Ceriodaphnia dubia and the fungicide azoxystrobin, including all steps, from bespoke laboratory toxicity tests to model calibration and validation, through to environmental risk assessment. Following the framework proposed in the European Food Safety Authority Scientific Opinion from 2018, we designed bespoke good laboratory practice-compliant laboratory toxicity studies based on test guideline 211 of the Organisation for Economic Co-operation and Development and then identified robust parameter values from those data for all relevant model parameters through model calibration. The DEB-TKTD model, DEBtox2019, then informed the design of the validation experiment. Once validated, the model was used to perform predictions for a time-variable exposure scenario generated by FOCUS. A moving time-window approach was used to perform the environmental risk assessment. This assessment method reduces uncertainty in the risk assessment while maintaining consistency with the traditional measures of risk. Environ Toxicol Chem 2024;43:2409-2421. © 2024 Syngenta Crop Protection AG. ibacon GmbH and The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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.

Early-life dispersal traits of coastal fishes: an extensive database combining observations and growth models

Abstract. Early-life stages play a key role in the dynamics of bipartite life cycle marine fish populations. Difficult to monitor, observations of these stages are often scattered in space and time. While Mediterranean coastlines have often been surveyed, no effort has been made to assemble historical observations. Here we build an exhaustive compilation of dispersal traits for coastal fish species, considering in situ observations and growth models (Di Stefano et al., 2023; https://doi.org/10.17882/91148). Our database contains over 110 000 entries collected from 1993 to 2021 in various subregions. All observations are harmonized to provide information on dates and geolocations of both spawning and settlement, along with pelagic larval durations. When applicable, missing data and associated confidence intervals are reconstructed from dynamic energy budget theory. Statistical analyses allow traits’ variability to be revisited and sampling biases to be revealed across taxa, space and time, hence providing recommendations for future studies and sampling. Comparison of observed and modelled entries provides suggestions to improve the feed of observations into models. Overall, this extensive database is a crucial step to investigate how marine fish populations respond to global changes across environmental gradients.

Advancing Soil Risk Assessment: A Novel Earthworm Cocoon Test with a Complementary Toxicokinetic-Toxicodynamic Modeling Approach.

In the current European Union pesticide risk assessment for soil organisms, effect endpoints from laboratory studies (Tier 1) and field studies (higher-tier risk assessment) are compared with predicted environmental concentrations in soil, derived from the proposed use pattern. The simple but conservative initial Tier 1 risk assessment considers a range of worst-case assumptions. In contrast, the higher-tier assessment focuses on specific conditions tested in the corresponding field study. Effect modeling, such as toxicokinetic-toxicodynamic (TKTD) modeling, is considered a promising future tool to address uncertainties in soil risk assessment, such as extrapolation to different ecological, pedo-climatical, or agronomical situations, or to serve as an intermediate tier for potential refinement of the risk assessment. For the implementation of TKTD modeling in soil organism risk assessment, data on earthworm growth and reproduction over time are required, which are not provided by the standard Organisation for Economic Co-operation and Development (OECD) 222 laboratory test. The underlying study with carbendazim presents a new earthworm cocoon test design, based on the OECD 222 test, to provide the necessary data as input for TKTD modeling. This proposed test design involves destructive samplings at days 7, 14, 21, and 28, enabling the determination of growth, cocoon number, and the number of juveniles hatched per cocoon in 7-day intervals. The new cocoon test allowed the disentanglement of the toxic effect of carbendazim in earthworms: At the highest concentration prominent effects on growth and reproductive output were observed, and the number of cocoons was significantly reduced compared to control. The results highlighted different physiological modes of action: effect on growth via higher maintenance costs as a primary mode of action as well as a reduced number of cocoons (effect on reproduction) and a lower number of juveniles hatching from each cocoon (hazard during oogenesis) as a secondary mode of action. We provide an example of how this new test's data can be used to feed a dynamic energy budget theory-TKTD model of Eisenia fetida. We also validate it against the original OECD 222 test design, outlining its potential future use in soil risk assessment. Environ Toxicol Chem 2024;43:2377-2386. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Climatic temperature and precipitation jointly influence body size in species of western rattlesnakes.

Both the metabolic theory of ecology and dynamic energy budget theory predict that climate influences body size through its effects on first-order determinants of energetics: reactive temperatures, carbon resources and oxygen availability. Although oxygen is seldom limiting in terrestrial systems, temperature and resources vary spatially. We used redundancy analyses and variation partitioning to evaluate the influence of climatic temperature, precipitation and their seasonalities on multivariate body size across the distributions of four species of the western rattlesnake group in North America (Crotalus pyrrhus, C. scutulatus, C. oreganus and C. viridis). Most species showed a pattern of increased body size in cooler, mesic climates and decreased body size in warmer, xeric climates. Exceptions to the pattern provided additional context through climatic idiosyncrasies in the distributions of each species. For example, the general pattern of a negative influence of temperature on body size was not apparent for C. oreganus, which ranges across the mildest climates overall among the four species. In contrast to previous studies, we found that seasonality had negligible effects on body size. We suggest that precipitation gradients correlate positively with resource availability in driving intraspecific body size and that temperature compounds this gradient by increasing baseline metabolic demands and restricting activity in particularly warm or otherwise extreme climates.

Modelling and mapping carbon capture potential of farmed blue mussels in the Baltic Sea region

This study applies a regional Dynamic Energy Budget (DEB) model, enhanced to include biocalcification processes, to evaluate the carbon capture potential of farmed blue mussels (Mytilus edulis/trossulus) in the Baltic Sea. The research emphasises the long-term capture of carbon associated with shell formation, crucial for mitigating global warming effects. The model was built using a comprehensive pan-Baltic dataset that includes information on mussel growth, filtration and biodeposition rates, and nutrient content. The study also examined salinity, temperature, and chlorophyll a as key environmental factors influencing carbon capture in farmed mussels. Our findings revealed significant spatial and temporal variability in carbon dynamics under current and future environmental conditions. The tested future predictions are grounded in current scientific understanding and projections of climate change effects on the Baltic Sea. Notably, the outer Baltic Sea subbasins exhibited the highest carbon capture capacity with an average of 55 t (in the present scenario) and 65 t (under future environmental conditions) of carbon sequestrated per farm (0.25 ha) over a cultivation cycle – 17 months. Salinity was the main driver of predicted regional changes in carbon capture, while temperature and chlorophyll a had more pronounced local effects. This research advances our understanding of the role low trophic aquaculture plays in mitigating climate change. It highlights the importance of developing location-specific strategies for mussel farming that consider both local and regional environmental conditions. The results contribute to the wider discourse on sustainable aquaculture development and environmental conservation.

Dynamic Energy Budget model for E. coli growth in carbon and nitrogen limitation conditions

The simulations and predictions obtained from mathematical models of bioprocesses conducted by microorganisms are not overvalued. Mechanistic models are bringing a better process understanding and the possibility of simulating unmeasurable variables. The Dynamic Energy Budget (DEB) model is an energy balance that can be formulated for any living organism and can be classified as a structured model. In this study, the DEB model was used to describe E. coli growth in a batch reactor in carbon and nitrogen substrate limitation conditions. The DEB model provides a possibility to follow the changes in the microbes’ cells including their elemental composition and content of some important cell ingredients in different growth phases in substrate limitation conditions which makes it more informative compared to Monod’s model. The model can be used as an optimal choice between Monod-like models and flux-based approaches.Key points• The DEB model can be used to catch changes in elemental composition of E. coli• Bacteria batch culture growth phases can be explained by the DEB model• The DEB model is more informative compared to Monod’s based models

Comparing Energetics and Physiological Trait Patterns of North American Birds to Support Ecological Risk Assessment

The environmental risk assessment (ERA) of plant protection products (PPPs) is commonly conducted for a number of standard laboratory species, though its scope includes all species, especially those that are vulnerable or endangered. This begs the question of how the eco-physiological and life history traits of those data-rich species compare to those of less documented species. This paper investigates the utility of a database of such traits, the Add-my-Pet collection of Dynamic Energy Budget theory, for the ERA of North American birds. We identified 72 bird species in the collection that have a federal listing status or are otherwise of interest for the ERA of PPPs and compared their eco-physiological and life history traits in relation to body size, feeding guild, and taxonomic identity to those of 446 terrestrial Holarctic birds, as well as those of standard lab species, notably the northern bobwhite, mallard, and zebra finch. The properties of standard lab species generally align with those of a similar taxonomy and size, with the notable exception of the relatively high reproductive capacity of the northern bobwhite and mallard due to the unique properties of laboratory study data. In addition, taxonomy appears to be a better predictor of eco-physiological traits than feeding guild. We conclude that, to identify representative species for the ERA of PPPs, more traits need to be included, such as those directly linked to the likelihood of exposure and those related to reproductive behavior.

A multi-tier methodology for the estimation of individual-specific parameters of DEB models

Intraspecific variability plays a key role in modeling population dynamics and ecological interactions. It is also a fundamental issue for agriculture, livestock production, and aquaculture. Dynamic Energy Budget (DEB) theory is a metabolic theory that can provide insights for these applications, as it can accurately predict the response of an organism to changes in environmental conditions. However, DEB model parameters are typically estimated for the species using mean trait values, neglecting individual differences. With advancing data collection technologies, there is a growing need to leverage individual data to calibrate DEB models. In this paper, we propose a multi-tier methodology for estimating individual-specific DEB parameters based on techniques and principles of the standard DEB estimation procedure. Individual data is often not sufficiently complete, therefore we compliment it available data on organisms of the same species. To avoid estimation bias, we employ a hierarchical tier structure. Data is categorized into tiers, depending on how general it is. In each tier, only a subset of the parameters is estimated depending on available data. The estimation proceeds in a top-down approach, starting with the most general tier and culminating in the individual tier. Values obtained in previously estimated tiers are used as pseudo-data to anchor the parameter estimation. In this way, we obtain biologically sensible individual parameter estimates in an efficient manner. As a case study, we apply our methodology to a dataset that contains weight and feed intake measurements for 52 individuals of the Mertolenga cattle breed from two performance trials. We conclude that variability in the surface-specific maximum assimilation rate and the digestion efficiency is needed to accurately model the individual data. Furthermore, the analysis of tier parameters and individual parameter distributions uncovers differences in the diets fed to the animals.

A dynamic energy budget (DEB) model to assess the sublethal effects of imidacloprid toward Gammarus pulex at different temperatures

Environmental ambient temperature significantly impacts the metabolic activities of aquatic ectotherm organisms and influences the fate of various chemicals. Although numerous studies have shown that the acute lethal toxicity of most chemicals increases with increasing temperature, the impact of temperature on chronic effects — encompassing both lethal and sublethal endpoints — has received limited attention. Furthermore, the mechanisms linking temperature and toxicity, potentially unveiled by toxicokinetic-toxicodynamic models (TKTD), remains inadequately explored. This study investigated the effects of environmentally relevant concentrations of the insecticide imidacloprid (IMI) on the growth and survival of the freshwater amphipod Gammarus pulex at two different temperatures. Our experimental design was tailored to fit a TKTD model, specifically the Dynamic Energy Budget (DEB) model. We conducted experiments spanning three and six months, utilizing small G. pulex juveniles. We observed effects endpoints at least five times, employing both destructive and non-destructive methods, crucial for accurate model fittings. Our findings reveal that IMI at environmental concentrations (up to 0.3 μg/L) affects the growth and survival of G. pulex, albeit with limited effects, showing a 10% inhibition compared to the control group. These limited effects, observed in both lethal and sublethal aspects, suggest a different mode of action at low, environmentally-relevant concentrations in long-term exposure (3 months), in contrast to previous studies which applied higher concentrations and found that sublethal effects occurred at significantly lower levels than lethal effects in an acute test setting (4 days). Moreover, after parameterizing the DEB model for various temperatures, we identified a lower threshold for both lethal and sublethal effects at higher temperatures, indicating increased intrinsic sensitivity. Overall, this study contributes to future risk assessments considering temperature as a crucial factor and exemplifies the integration of the DEB model into experimental design for comprehensive toxicity evaluations.

Marine aquaculture spatial planning on market orientation for Pacific oyster in Shandong, China

Accessing the production value is essential to the selection of suitable sites for aquaculture farms. This study employed a Dynamic Energy Budget (DEB) model and used market-oriented indicators, including shell length, flesh weight, condition index and minimum farming duration, to analyze the suitability for Pacific oyster aquaculture in offshore Shandong, China. Chlorophyll a (Chl-a) concentration, Total Suspended Sediment (TSS) concentration, and Sea Surface Temperature (SST) were extracted by remote sensing and used as forcing variables in the bioenergetic model. Four market-oriented indicators and five zones in the study area were chosen to develop a Suitable Market-Aquaculture site-selection model (SMASM) and estimate the oyster farming suitability. The results demonstrated that Sanggou Bay exhibits high potential for Pacific oyster year-round aquaculture. Eastern Laizhou Bay is suitable for the autumn-spring fattening culture of adult oysters. Laoshan Bay and Changshan Islands are suitable for promoting rapid growth in juvenile oysters. The results of our model were consistent with the oyster production value in Shandong, showing an overall increasing trend except for the anomalous value observed in 2019. Sudden drops in water temperature, red tides, and significant increases in turbidity can exert detrimental effects on oyster production, which has been evidenced to be influenced by Super Typhoon Lekima in 2019. Although this study concentrated on a specific geographical region, the model could be applied to other regions to develop market-oriented suitability management for species and environments worldwide.

The temperature-size rule in the context of Dynamic Energy Budget theory

The temperature-size rule (TSR) refers to the observation that a wide variety of organisms reach smaller sizes under warmer temperatures. Although various hypotheses have been stated about the mechanisms underlying TSR, a general understanding is still lacking. In this context, it seems that Dynamic Energy Budget (DEB) theory could be useful, as it constitutes a mechanistic framework that predicts growth and development from individual energetics. However, a critical assumption of this framework is that temperature affects all physiological rates equally, which prevents it from capturing the TSR. It remains an open question if and how the DEB framework can be used to capture the TSR patterns.The model does, however, include a parameter, the food searching rate, that does not need to obey this constraint, as it is a physical rather than a physiological parameter. Here, we aimed to test whether introducing a differing temperature-dependence of food searching rate in DEB models makes it possible to capture the TSR. We parameterized the model using an extensive dataset of Daphnia life history response to temperature. The resulting model was able to capture the decrease of both size at maturity and asymptotic size observed in this dataset.Therefore, DEB models can capture the TSR without any major modification, but only requires to introduce a different function for the temperature dependence of the food searching rate. The mechanism underlying this effect essentially results from increased food limitation at high temperature, which, in combination with the particular allocation scheme of the DEB model, affects differentially growth and development.

Dynamic Energy Budget approach for modeling growth and reproduction of Neotropical stink bugs

Global warming and other climate change drivers have a significant impact on the life cycle of insects which in turn affect their population dynamics and geographic distribution. Among these insects are stink bugs (Hemiptera: Pentatomidae), which are hemimetabolous agricultural pests that cause major damage on crops in many countries. Their life cycle consists of three stages: egg, nymph, and adult. The nymph grows and molts through a small number of instars until reaching emergence, at which point growth ceases. The Dynamic Energy Budget (DEB) theory provides the framework for modeling the life cycle of stink bugs. Nevertheless, determining the most accurate model for nymphal growth and energy allocation during the adult stage remains a challenge, as the best model is not always evident. For two species of the Pentatomidae family, we parameterized and evaluated four DEB models that differ in nymphal growth and the energy allocation rules in adults: isomorphic or V1-morphic nymphal growth combined with the energy allocation scheme in adults that follows the κ-rule or the scheme that the κ-rule is not operational in adults. Overall, all models fit the data, but those with isomorphic nymphal growth reproduce the growth trajectories and instar duration better. However, with the available data we cannot conclude which rule is most likely the energy allocation in adults. Using these models, we further studied the effects of temperature and food availability on individual dynamics and its life cycle. Simulations show that temperature has a higher impact on the duration of life stages and survival, while food availability affects egg production. When simulating a variable environment in terms of temperature for both a summer and a fall generation, the results reveal that the summer generation has higher feeding and egg production rates in comparison to the fall generation. DEB models are valuable tools for simulating individual under various environmental conditions and when combined with appropriate modeling approaches, they can predict population traits and even the potential distribution of a species.

Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information

Practical, legal, and ethical reasons necessitate the development of methods to replace animal experiments. Computational techniques to acquire information that traditionally relied on animal testing are considered a crucial pillar among these so-called new approach methodologies. In this light, we recently introduced the Bio-QSAR concept for multispecies aquatic toxicity regression tasks. These machine learning models, trained on both chemical and biological information, are capable of both cross-chemical and cross-species predictions. Here, we significantly extend these models’ applicability. This was realized by increasing the quantity of training data by a factor of approximately 20, accomplished by considering both additional chemicals and aquatic organisms. Additionally, variable test durations and associated random effects were accommodated by employing a machine learning algorithm that combines tree-boosting with mixed-effects modeling (i.e., Gaussian Process Boosting). We also explored various biological descriptors including Dynamic Energy Budget model parameters, taxonomic distances, as well as genus-specific traits and investigated the inclusion of mode-of-action information. Through these efforts, we developed Bio-QSARs for fish and aquatic invertebrates with exceptional predictive power (R squared of up to 0.92 on independent test sets). Moreover, we made considerable strides to make models applicable for a range of use cases in environmental risk assessment as well as research and development of chemicals. Models were made fully explainable by implementing an algorithmic multicollinearity correction combined with SHapley Additive exPlanations. Furthermore, we devised novel approaches for applicability domain construction that take feature importance into account. We are hence confident these models, which are available via open access, will make a significant contribution towards the implementation of new approach methodologies and ultimately have the potential to support “Green Chemistry” and “Green Toxicology”.

Bioremediation potential of the hard clam Mercenaria mercenaria as an intensive shrimp aquaculture pond polyculture condidate

Polyculture practices are important for achieving sustainable aquaculture development. Recently, hard clams polyculture in intensive shrimp ponds has been encouraged because bivalves can consume excess nutrients in aquaculture systems and sequester carbon. To evaluate the bioremediation potential of hard clams polyculture in intensive shrimp ponds, this study built an assessment model based on individual growth models and estimated the potential for nitrogen and phosphorus removal as well as CO2 fixation by hard clams. Firstly, key parameters required for model construction were obtained through field surveys and physiological experiments. Subsequently, an individual growth model for the hard clam Mercenaria mercenaria was developed based on the Dynamic Energy Budget (DEB) theory. Fitting of the growth data indicated that the model accurately replicated the growth patterns of hard clams, with relative root mean square errors of 9.87 % for shell length and 5.02 % for dry tissue weight. Finally, the assessment model for the bioremediation potential of hard clams demonstrated that, over 110 days in the intensive shrimp mariculture pond, the net removal of nitrogen and phosphorus by hard clams were 3.68 kg ha−1 and 0.81 kg ha−1, respectively, and CO2 fixation was 507.00 kg ha−1. These findings suggested that the DEB model is an effective tool for evaluating bivalve ecological remediation potential and can aid in selecting species for sustainable polyculture.

DEBBIES Dataset to study Life Histories across Ectotherms

Demographic models are used to explore how life history traits structure life history strategies across species. This study presents the DEBBIES dataset that contains estimates of eight life history traits (length at birth, puberty and maximum length, maximum reproduction rate, fraction energy allocated to respiration versus reproduction, von Bertalanffy growth rate, mortality rates) for 185 ectotherm species. The dataset can be used to parameterise dynamic energy budget integral projection models (DEB-IPMs) to calculate key demographic quantities like population growth rate and demographic resilience, but also link to conservation status or biogeographical characteristics. Our technical validation shows a satisfactory agreement between observed and predicted longevity, generation time, age at maturity across all species. Compared to existing datasets, DEBBIES accommodates (i) easy cross-taxonomical comparisons, (ii) many data-deficient species, and (iii) population forecasts to novel conditions because DEB-IPMs include a mechanistic description of the trade-off between growth and reproduction. This dataset has the potential for biologists to unlock general predictions on ectotherm population responses from only a few key life history traits.