Energy Budget Model Research Articles

Evaluation of a Wisconsin-type bioenergetics model to estimate brook charr (Salvelinus fontinalis) growth and food consumption under two salinity conditions.

In Québec, Canada, brook charr (Salvelinus fontinalis) is the most sought-after species for recreational fisheries, which makes it economically important. To improve population monitoring and better anticipate climate change impacts on brook charr, bioenergetics models can be useful. The objective of this research was to evaluate the performance of a resident brook charr Wisconsin Energy Budget (WEB) model applied to an anadromous strain under two salinity treatments. Growth and food consumption were predicted by the model and compared to the observed values obtained after a 60-day experiment in the laboratory on fish reared in fresh or brackish water. Predictions for fish reared in fresh water better estimated growth rate and consumption than for fish reared in brackish water, for which growth was overestimated and consumption was underestimated. Overall, these results suggest that there is a difference for the WEB model’s predictions depending on the salinity and that observed food consumption is predicted more accurately than growth.

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.

From BIM to thermal comfort: Leveraging BIM for rapid outdoor comfort assessments

This study introduces a novel system within a Building Information Modeling (BIM) environment to rapidly evaluate Outdoor Thermal Comfort (OTC). Traditionally, direct microclimate analysis in the design phase is hindered by cumbersome and resource-intensive processes. By utilizing information from BIM and integrating the COMFA thermal energy budget model, this approach facilitates immediate OTC evaluation. The system automates the Sky View Factor simulation using 3D modeling techniques and utilizes BIM model data to assess the thermal environment. Tested on a university campus, it effectively processes geospatial BIM data to compute microclimate parameters and estimate OTC using COMFA. This research represents a significant advancement in BIM-integrated OTC analysis, streamlining the design feedback process and aiding practitioners in improving outdoor thermal environments amidst climate change challenges.

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

Evaluation of the energy budget of thermokarst lake in permafrost regions of the Qinghai–Tibet Plateau

Thermokarst lake formation accelerates permafrost degradation due to climate warming, thereby releasing significant amounts of carbon into the atmosphere, complicating hydrological cycles, and causing environmental damage. However, the energy transfer mechanism from the surface to the sediment of thermokarst lakes remains largely unexplored, thereby limiting our understanding of the magnitude and duration of biogeochemical processes and hydrological cycles. Therefore, herein, a typical thermokarst lake situated in the center of the Qinghai–Tibet Plateau (QTP) was selected for observation and energy budget modeling. Our results showed that the net radiation of the thermokarst lake surface was 95.1, 156.9, and 32.3 W m−2 for the annual, ice-free, and ice-covered periods, respectively, and was approximately 76% of the net radiation consumed by latent heat flux. Alternations in heat storage in the thermokarst lake initially increased from January to April, then decreased from April to December, with a maximum change of 48.1 W m−2 in April. The annual average heat fluxes from lake water to sediments were 1.4 W m−2; higher heat fluxes occurred during the ice-free season at a range of 4.9–12.0 W m−2. The imbalance between heat absorption and release in the millennium scale caused the underlying permafrost of the thermokarst lake to completely thaw. At present, the ground temperature beneath the lake bottom at a depth of 15 m has reached 2.0 °C. The temperatures and vapor-pressure conditions of air and lake surfaces control the energy budget of the thermokarst lake. Our findings indicate that changes in the hydrologic regime shifts and biogeochemical processes are more frequent under climate warming and permafrost degradation.

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.

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”.

Remote sensing and spectroscopy of lichens.

Lichens are combinations of two symbiotic organisms, a green alga or cyanobacterium and a fungus. They grow in nearly all terrestrial ecosystems and survive in habitats, which are very dry or cold, or too poor in nutrients to maintain vegetation growth. Because lichens grow on visible surfaces and exhibit spectral properties, which are clearly different from, for example, vegetation, it is possible to distinguish them in remote sensing data. In this first systematic review article on remote sensing of lichens, we analyze and summarize which lichen species or genera, and in which habitats and geographical regions, have been remotely sensed, and which remote sensing or spectroscopic technologies have been used. We found that laboratory or insitu measured spectra of over 70 lichen species have been reported to date. We show that studies on remote sensing of lichens fall under seven broad themes: (1) collection of lichen spectra for quantification of lichen species or characteristics, (2) pollution monitoring with lichens as ecological indicators, (3) geological and lithological mapping, (4) desert and dryland monitoring, (5) animal habitat monitoring, (6) land cover or vegetation mapping, and (7) surface energy budget modeling.

Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model

Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.

Assessing regional connectivity patterns of bivalvia in fragmented archipelagos: Insights from biophysical modeling in French Polynesia

Larval dispersal and connectivity are key processes that drive marine metapopulation dynamics, and therefore should be well characterized when designing effective management strategies. While temperature and food availability can structure marine species connectivity patterns, their contribution has not been thoroughly investigated in highly fragmented archipelagos. We used biophysical modeling of larval dispersal to explore the connectivity patterns of species with complex life-cycles across French Polynesia (FP), a territory formed by more than a hundred small, geographically isolated islands covering an area as large as Europe. We first simulated ten years of larval dispersal to investigate the spatial and temporal (seasonal and interannual) variability in larval dispersal pathways for different hypothetical species exhibiting a range of Larval Precompetency Period (LPP) values. Then, using the black-lip pearl oyster (Pinctada margaritifera) as a model species, we accounted for variability in the LPP induced by temperature and food availability, as derived from a Dynamic Energy Budget (DEB) model. The model showed that food availability and mesoscale turbulence (eddies) in the Marquesas jointly constrained larval dispersal, reducing its potential connectivity with other archipelagos in FP. The DEB simulations also revealed seasonal and interannual variability in connectivity driven by environmental conditions. However, accounting for food and temperature effects on larval development, barely changed the connectivity pattern at regional scale due to the remoteness of this archipelago. Our study thus provides appropriate management units definition at regional scale for the species across FP.

Environmental Risk Assessment with Energy Budget Models: A Comparison Between Two Models of Different Complexity.

The extrapolation of effects from controlled standard laboratory tests to real environmental conditions is a major challenge facing ecological risk assessment (ERA) of chemicals. Toxicokinetic-toxicodynamic (TKTD) models, such as those based on dynamic energy budget (DEB) theory, can play an important role in filling this gap. Through the years, different practical TKTD models have been derived from DEB theory, ranging from the full "standard" DEB animal model to simplified "DEBtox" models. It is currently unclear what impact a different level of model complexity can have on the regulatory risk assessment. In the present study, we compare the performance of two DEB-TKTD models with different levels of complexity, focusing on model calibration on standard test data and on forward predictions for untested time-variable exposure profiles. The first model is based on the standard DEB model with primary parameters, whereas the second is a reduced version with compound parameters, based on DEBkiss. After harmonization of the modeling choices, we demonstrate that these two models can achieve very similar performances both in the calibration step and in the forward prediction step. With the data presented in the present study, selection of the most suitable TKTD model for ERA therefore cannot be based alone on goodness-of-fit or on the precision of model predictions (within current ERA procedures for pesticides) but would likely be based on the trade-off between ease of use and model flexibility. We also stress the importance of modeling choices, such as how to fill gaps in the information content of experimental toxicity data and how to accommodate differences in growth and reproduction between different data sets for the same chemical-species combination. Environ Toxicol Chem 2024;43:440-449. © 2023 ibacon GmbH. Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A mechanistic model approach to characterize suitable regions for Salmo salar aquaculture in the Yellow Sea under global warming

Global warming has a profound effect on aquaculture. Salmon aquaculture, as an emerging industry in China, is particularly vulnerable to climate change. For this reason, spatial planning with mechanistic understanding is essential for mitigating and adapting to the impacts of climate change. Through the use of dynamic energy budget models for Atlantic salmon (Salmo salar) with fine-scale environmental data under 0 m, 20 m, 40 m, and 60 m depth, this study established a framework for identifying optimal regions for salmon aquaculture in the Yellow Sea under current and two Shared Socioeconomic Pathway scenarios (SSP1-2.6 and SSP5-8.5) in the 2050s. These results suggest that most regions in the Yellow Sea under 40 m and 60 m depth are suitable for salmon farming at both current and future scenarios, the central region of the Yellow Sea under 20 m (38°N, 123°E) is the optimal site for salmon aquaculture in China. Overall, these findings provide valuable support for aquaculture management and can help stakeholders create an effective blueprint for adaptation strategies.

Dynamic energy budget model for the complete life cycle of chub mackerel in the Northwest Pacific

Chub mackerel (Scomber japonicus) in the Northwest Pacific is an important pelagic fishery resource and a significant target species in purse seine fisheries. However, the catch of chub mackerel fluctuates greatly from year to year, and recent studies have shown that the Tsushima stock may be overfished. Therefore, research on the biology and population dynamics of this species is required to provide sufficient scientific support for the development of reasonable management and recovery plans and for the increased sustainable use of resource fisheries. In this study, a dynamic energy budget (DEB) model was constructed based on DEB theory for the complete life cycle of chub mackerel in the Northwest Pacific by using biological data to simulate processes, including growth, reproduction, and death. The key results were as follows. 1) The DEB model accurately simulated the complete life cycle of chub mackerel, with a good fit for the relationships between age and length as well as length and weight, while accurately estimating annual absolute fecundity, aging, and death and predicting the metamorphosis time of larval fish. 2) The DEB model can incorporate the effects of temperature and food to describe the effects of marine environmental conditions on chub mackerel growth. 3) The DEB model involved multiple interrelated parameters; however, owing to a lack of observational data, there was a certain degree of uncertainty in estimated parameter values. The DEB model provides a basis for establishing correlations and intrinsically unifying biological processes, including growth, sexual maturation, reproduction, aging, and death, thereby guiding studies of growth, reproduction, and population dynamics of chub mackerel in the Northwest Pacific.

Unravelling mechanisms behind population dynamics, biological traits and latitudinal distribution in two benthic ecosystem engineers: A modelling approach

The mechanistic approach consisting of coupling Dynamic Energy Budget (DEB) models to Individual-Based Models (IBMs) allows simulating individual and population biological traits and their dynamics. This approach was developed here to study population dynamics of two sympatric intertidal ecosystem engineers, Arenicola marina and Arenicola defodiens (Annelida Polychaeta) occurring in the North-East Atlantic from Portugal to Sweden. Latitudinal heterogeneity of the two species’ performances were investigated in terms of population dynamics and biological traits using latitudinal differences in environmental forcing variables. The impact of the forcing variables on population dynamics processes (shore colonisation and migration, spawning and recruitment, etc.) within a specific foreshore (mean values and seasonal patterns) was also assessed. Published DEB parameters were used for A. marina and a specific calibration was undertaken for A. defodiens, combining literature data and new laboratory experiments and field data. Our DEB-IBM simulated super-individuals’ growth and reproduction while lugworms were colonising, migrating and dying over a simulated foreshore. Density rules affected population dynamics. Environmental forcings consisted in monthly values of chlorophyll-a (chl-a) concentrations and daily values of SST. Scenarios focusing on the two most contrasted of these forcing variables time series were used to explore their relative effects over populations’ dynamics and on-shore processes were investigated at two sites displaying highly different simulated population abundances. Overall, northern sites with higher chl-a levels performed better displaying higher biomass, maximum length and reproductive outputs for both species. As expected, Sea Surface Temperature (SST) changes between sites did not impact greatly populations dynamics. Under favourable environmental conditions, intra- and inter-specific competitions emerged from the model. Under non-favourable environmental conditions, A. defodiens’ populations crashed and A. marina displayed atypical population processes, with rare spawning events barely allowing the population’s renewal, and lower size at maturity. Further use and development of this model will lead to better insights on the lugworm populations’ evolution over the next decades.

A dynamic energy budget model for black rockfish Sebastes schlegelii: Parameterization and application in marine ranching areas, Yellow Sea, China

Marine ranching has become a powerful tool for coastal habitat restoration, ecosystem conservation and stock enhancement. With increasing development of marine ranching in recent years, it has attracted wide attentions for fishery management and sustainability. The stock of black rockfish Sebastes schlegelii has undergone a serious decline due to overfishing in the past few decades, but has considerably recovered recently in marine ranching areas along the coasts of the Northwest Pacific. Appropriate management of the species is essential for marine ranching development. In this study, a dynamic energy budget (DEB) model of S. schlegelii was developed and applied in the Xixiakou, Changdao and Qiansandao marine ranching areas, Yellow Sea, China. The effects of food availability and water temperature on its growth and reproduction were quantified. The model was parameterised following the AmP procedure, which resulted in mean relative error of 0.123 and symmetric mean square errors of 0.134. The application of the model has showed that the model could reproduce the growth trajectories of both length and weight at each of the three marine ranching areas without site-specific calibration. The growth rates of S. schlegelii showed that Qiansandao > Changdao > Xixiakou in both length and weight. Temperature and food availability are the main contribution to the variations of growth amongst sites. In Qiansandao, the fast growth and maturation of the species correspond to relative high water temperature and sufficient food availability. Food availability limited growth and reproduction of S. schlegelii in Xixiakou, which indicated that the stock density in the areas might be close to the carrying capacity. The earlier maturation was a result of higher temperature and more food supply in Qiansandao than in Changdao and Xixiakou. Fishing and recapture in marine ranching areas should be adjusted to flexibly avoid spawning periods. The presented model is applicable to other marine ranching areas and coastal habitats. It provides an important component of ecosystem management approaches to estimate the ecological carrying capacities. This study provides information about the stock enhancement potential of coastal environments and a powerful tool for sustainable coastal fisheries management.

Assessment of some Bioclimatic Indices using RayMan Model for Baghdad-Iraq

Abstract The evaluation of bioclimatic conditions on a local scale is still an important topic. It might be a key component of the national plan for the sustainable development of various areas under changing climatic conditions. The present study aimed to examine the behaviour of four bioclimatic indices namely physiologically equivalent temperature (PET), Standard Effective Temperature (SET*), Universal thermal climate index(UTCI) and, Predictive mean vote(Pmv) derived from energy budget models for Baghdad city. The monthly means data of air temperature, relative humidity, wind speed, and solar radiation during the period (1981-2021) were used in this study. All calculations of this study were extracted using RayMan Model. The relationship between PET, Pmv, SET, and UTCI indices in addition to meteorological parameters was also conducted in this study. The results indicate that July and August had the highest values of Pmv (4), SET* (39.4), PET (43.9), and UTCI (39.4). For the majority of the studied indices, the comfortable thermal perception occurred only in March, April, and October. PET and UTCI revealed acceptable comparability in terms of temperature perception when compared to other indices for most months of the year. The maximum heat stress was reported for all indices between May and September, with the lowest stress occurring between January and December. April was the most comfortable month of the year, according to the data. Correlations between UTCI and meteorological parameters found a substantial association with air temperature (0.99) and relative humidity (0.98), respectively. The lowest correlation coefficient (R2=0.69) was found with wind speed. All other indicators indicate a substantial association with the UTCI.

Coupling dynamic energy budget and population dynamic models to inform stock enhancement in fisheries management

AbstractExtensive applications of fishery stock enhancement worldwide bring up broad concerns about its negative effects, creating a pivotal need for science‐based assessment and planning of enhancement strategies. However, the lack of mechanistic understanding of enhanced population dynamics, particularly the density‐dependent processes, leads to compromise in model development and limits the capacity in predicting enhancement effects. Here, we developed an individual‐based model based on dynamic energy budget theory and full life‐history processes, to understand the mechanism of density dependence in population dynamics that emerge from individual‐level processes. We demonstrated the utility of the model framework by applying it to an extensively enhanced species, Chinese prawn (Fenneropenaeus chinensis, Penaeidae). The model could yield projections reflecting the observed trajectory of population biomass and yields. The model also delineated the key effects of density dependence on the vital rates of growth, fecundity and starvation mortality. Regarding the manifold effects of stock enhancement, we demonstrated a dampened shape in population biomass and yields with increasing magnitude of enhancement, and trade‐offs between the ecological and economic objectives, that is, pursuing high benefit might compromise the wild population without proper management. Furthermore, we illustrated the possibility of combining stock enhancement and harvest regulation in promoting population recovery while maintaining fisheries yields. We highlight the potential of the proposed model for understanding density dependence in enhancement programme, and for designing integrated management strategies. The approach developed herein may serve as a general approach to assess the population dynamics in stock enhancement and inform enhancement management.