The role of Dynamic Energy Budgets in conservation physiology

Whole-Colony Dynamic Energy Budget Model for Bumble Bees: Assessing the Impact of Wildflower Patches on Crop Pollination

Bumble bees are important pollinators of many crops around the world. In recent decades, agricultural intensification has resulted in significant declines in bumble bee populations and the pollination services they provide. Empirical studies have shown that this trend can be reversed by enhancing the agricultural landscape, for example, by placing wildflower patches adjacent to crops. Despite the empirical evidence, the mechanisms behind these positive effects are not fully understood. Theoretical studies, in the form of mathematical or computational models, have proven useful in providing insights, but the complexity of the underlying system means that certain factors remain unexplored. In this work, we build a unique model coupling a whole-colony Dynamic Energy Budget (DEB) approach for population dynamics to a Maximum Entropy (MaxEnt) principle formulation for the spatial distribution of foraging bees. The use of a DEB to asses whole-colony energy budgets, and its coupling to a spacial model is novel. The use of MaxEnt to predict foraging spatial distributions is still in its early stages, and our work highlights its potential to advance and expand upon the traditional assumptions of the Ideal Free Distribution. We use the developed model to asses the possible benefits and drawbacks of planting wildflower nearby crops for crop pollination services. We answer questions of when should wildflowers bloom, how many should we plant, which type of wildflowers, and where should we place them.

Comparing freshwater mussel responses to stress using life-history and Dynamic Energy Budget theory

Freshwater mussels are experiencing severe population declines, affecting their critical role in freshwater ecosystems. A thorough assessment of threats posed by various stressors is needed; however, the large number of species to be considered and significant data gaps, especially for listed species, hinder the process. We combined a traits-based approach to represent multiple species grouped into three life-history categories - Equilibrium, Opportunistic, and Periodic - with the Dynamic Energy Budget modeling principles to capture the physiological mechanisms driving individual-level responses. We used the DEB model to simulate individual life cycles and explore relationships between underlying energetics and emerging individual traits of 47 freshwater mussel species and the common toxicity test surrogate, the Eastern oyster (Crassostrea virginica), under control and stressed conditions. Stress was introduced via physiological modes of action related to four key metabolic pathways: energy assimilation, maintenance, growth, and reproduction. We recorded maximum length, age at maturity, and fecundity and compared these endpoints and their stress-induced changes among life-history categories. The life-history differences among freshwater mussels directly emerged from underlying energetics, with high assimilation and maintenance supporting opportunistic traits. Stress imposed on energy assimilation had the strongest effect on all life-history traits, and a 25 % reduction in assimilation rate resulted in an average 25 % and 60 % decrease in maximum length and fecundity, respectively, and a 24 % increase in age at maturity. Equilibrium species suffered the greatest negative effects overall, indicating that this life-history strategy might be the most susceptible to stressors. The Eastern oyster displayed extreme opportunism in its life-history traits, but its responses to stress were generally within the range observed for freshwater mussels. The study provides a much-needed general understanding of stress responses across freshwater mussel life-history categories and contributes to the foundation for developing life-history-driven population models.

Could future ocean acidification be affecting the energy budgets of marine fish?

With the unprecedented environmental changes caused by climate change including ocean acidification, it has become crucial to understand the responses and adaptive capacity of fish to better predict directional changes in the ecological landscape of the future. We conducted a systematic literature review to examine if simulated ocean acidification (sOA) could influence growth and reproduction in fish within the dynamic energy budget theory framework. As such, we chose to examine metabolic rate, locomotion, food assimilation and growth in early life stages (i.e. larvae and juvenile) and adults. Our goal was to evaluate if acclimatization to sOA has any directional changes in these traits and to explore potential implications for energetic trade-offs in these for growth and reproduction. We found that sOA had negligible effects on energetic expenditure for maintenance and aerobic metabolism due to the robust physiological capacity regulating acid-base and ion perturbations but substantive effects on locomotion, food assimilation and growth. We demonstrated evidence that sOA significantly reduced growth performance of fish in early life stages, which may have resulted from reduced food intake and digestion efficiency. Also, our results showed that sOA may enhance reproduction with increased numbers of offspring although this may come at the cost of altered reproductive behaviours or offspring fitness. While these results indicate evidence for changes in energy budgets because of physiological acclimatization to sOA, the heterogeneity of results in the literature suggests that physiological and neural mechanisms need to be clearly elucidated in future studies. Lastly, most studies on sOA have been conducted on early life stages, which necessitates that more studies should be conducted on adults to understand reproductive success and thus better predict cohort and population dynamics under ongoing climate change.

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.

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.

Three perspectives on the prediction of chemical effects in ecosystems

The increasing production, use and emission of synthetic chemicals into the environment represents a major driver of global change. The large number of synthetic chemicals, limited knowledge on exposure patterns and effects in organisms and their interaction with other global change drivers hamper the prediction of effects in ecosystems. However, recent advances in biomolecular and computational methods are promising to improve our capacity for prediction. We delineate three idealised perspectives for the prediction of chemical effects: the suborganismal, organismal and ecological perspective, which are currently largely separated. Each of the outlined perspectives includes essential and complementary theories and tools for prediction but captures only part of the phenomenon of chemical effects. Links between the perspectives may foster predictive modelling of chemical effects in ecosystems and extrapolation between species. A major challenge for the linkage is the lack of data sets simultaneously covering different levels of biological organisation (here referred to as biological levels) as well as varying temporal and spatial scales. Synthesising the three perspectives, some central aspects and associated types of data seem particularly necessary to improve prediction. First, suborganism- and organism-level responses to chemicals need to be recorded and tested for relationships with chemical groups and organism traits. Second, metrics that are measurable at many biological levels, such as energy, need to be scrutinised for their potential to integrate across levels. Third, experimental data on the simultaneous response over multiple biological levels and spatiotemporal scales are required. These could be collected in nested and interconnected micro- and mesocosm experiments. Lastly, prioritisation of processes involved in the prediction framework needs to find a balance between simplification and capturing the essential complexity of a system. For example, in some cases, eco-evolutionary dynamics and interactions may need stronger consideration. Prediction needs to move from a static to a real-world eco-evolutionary view.

Dynamic Energy Budget models: fertile ground for understanding resource allocation in plants in a changing world

Climate change is having dramatic effects on the diversity and distribution of species. Many of these effects are mediated by how an organism's physiological patterns of resource allocation translate into fitness through effects on growth, survival and reproduction. Empirically, resource allocation is challenging to measure directly and so has often been approached using mathematical models, such as Dynamic Energy Budget (DEB) models. The fact that all plants require a very similar set of exogenous resources, namely light, water and nutrients, integrates well with the DEB framework in which a small number of variables and processes linked through pathways represent an organism's state as it changes through time. Most DEB theory has been developed in reference to animals and microorganisms. However, terrestrial vascular plants differ from these organisms in fundamental ways that make resource allocation, and the trade-offs and feedbacks arising from it, particularly fundamental to their life histories, but also challenging to represent using existing DEB theory. Here, we describe key features of the anatomy, morphology, physiology, biochemistry, and ecology of terrestrial vascular plants that should be considered in the development of a generic DEB model for plants. We then describe possible approaches to doing so using existing DEB theory and point out features that may require significant development for DEB theory to accommodate them. We end by presenting a generic DEB model for plants that accounts for many of these key features and describing gaps that would need to be addressed for DEB theory to predict the responses of plants to climate change. DEB models offer a powerful and generalizable framework for modelling resource allocation in terrestrial vascular plants, and our review contributes a framework for expansion and development of DEB theory to address how plants respond to anthropogenic change.

The comparative energetics of the turtles and crocodiles

The Add-my-Pet collection of data on energetics and Dynamic Energy Budget parameters currently contains 92 species of turtles and 23 species of crocodiles. We discuss patterns of eco-physiological traits of turtles and crocodiles, as functions of parameter values, and compare them with other taxa. Turtles and crocodiles accurately match the general rule that the life-time cumulated neonate mass production equals ultimate weight. The weight at birth for reptiles scales with ultimate weight to the power 0.6. The scaling exponent is between that of amphibians and birds, while that for mammals is close to 1. We explain why this points to limitations imposed by embryonic respiration, the role of water stress and the accumulation of nitrogen waste during the embryo stage. Weight at puberty is proportional to ultimate weight, and is the largest for crocodiles, followed by that of turtles. These facts explain why the precociality coefficient, s H bp -approximated by the ratio of weight at birth and weight at puberty at abundant food-decreases with ultimate weight. It is the smallest for crocodiles because of their large size and is smaller for turtles than for lizards and snakes. The sea turtles have a smaller s H bp than the rest of the turtles, linked to their large size and small offspring size. We link their small weight and age at birth to reducing risks on the beach. The maximum reserve capacity in both turtles and crocodiles clearly decreases with the precociality coefficient. This relationship has not been found that clearly in other taxa, not even in other reptiles, with the exception of the chondrichthyans. Among reptiles, crocodiles and sea turtles have a relatively large assimilation rate and a large reserve capacity.

Physiological performance of native and invasive crayfish species in a changing environment: insights from Dynamic Energy Budget models

Crayfish are keystone species important for maintaining healthy freshwater ecosystems. Crayfish species native to Europe, such as Astacus astacus and Austropotamobius torrentium, are facing decline and are increasingly endangered by changing climate and invasions of non-native crayfish, such as Pacifastacus leniusculus and Procambarus virginalis. The success of these invasions largely depends on differences in ontogeny between the native species and the invaders and how changes in the environment will affect the ontogeny. Dynamic Energy Budget (DEB) models can be used to investigate such differences because the models capture dependence of metabolism, and therefore ontogeny, on environmental conditions. We develop DEB models for all four species and investigate key elements of ontogeny and metabolism affecting interspecific competition. We then use the DEB models to predict individual growth and reproduction in current and new conditions that are expected to arise from climate change. Although observations suggest that P. leniusculus poses the major threat to native species, our analysis identifies P. virginalis, in spite of its smaller size, as the superior competitor by a large margin-at least when considering metabolism and ontogeny. Our simulations show that climate change is set to increase the competitive edge of P. virginalis even further. Given the prospects of P. virginalis dominance, especially when considering that it is able to withstand and spread at least some crayfish plague strains that severely affect native species, additional research into P. virginalis is necessary.

Timescale separation and models of symbiosis: state space reduction, multiple attractors and initialization

Dynamic Energy Budget models relate whole organism processes such as growth, reproduction and mortality to suborganismal metabolic processes. Much of their potential derives from extensions of the formalism to describe the exchange of metabolic products between organisms or organs within a single organism, for example the mutualism between corals and their symbionts. Without model simplification, such models are at risk of becoming parameter-rich and hence impractical. One natural simplification is to assume that some metabolic processes act on 'fast' timescales relative to others. A common strategy for formulating such models is to assume that 'fast' processes equilibrate immediately, while 'slow' processes are described by ordinary differential equations. This strategy can bring a subtlety with it. What if there are multiple, interdependent fast processes that have multiple equilibria, so that additional information is needed to unambiguously specify the model dynamics? This situation can easily arise in contexts where an organism or community can persist in a 'healthy' or an 'unhealthy' state with abrupt transitions between states possible. To approach this issue, we offer the following: (a) a method to unambiguously complete implicitly defined models by adding hypothetical 'fast' state variables; (b) an approach for minimizing the number of additional state variables in such models, which can simplify the numerical analysis and give insights into the model dynamics; and (c) some implications of the new approach that are of practical importance for model dynamics, e.g. on the bistability of flux dynamics and the effect of different initialization choices on model outcomes. To demonstrate those principles, we use a simplified model for root-shoot dynamics of plants and a related model for the interactions between corals and endosymbiotic algae that describes coral bleaching and recovery.