First-passage-time statistics of growing microbial populations carry an imprint of initial conditions.

In exponential population growth, variability in the timing of individual division events and environmental factors (including stochastic inoculation) compound to produce variable growth trajectories. In several stochastic models of exponential growth we show power-law relationships that relate variability in the time required to reach a threshold population size to growth rate and inoculum size. Population-growth experiments in E. coli and S. aureus with inoculum sizes ranging between 1 and 100 are consistent with these relationships. We quantify how noise accumulates over time, finding that it encodes-and can be used to deduce-information about the early growth rate of a population.

Connecting Suborganismal Data to Bioenergetic Processes: Killifish Embryos Exposed to a Dioxin-Like Compound.

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population-level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal responses that influence population dynamics. We describe a novel application of dynamic energy budget (DEB) theory in the context of a toxicity framework (adverse outcome pathways [AOPs]) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early-life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP key events to DEB processes through "damage" that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and DEB models to predict sublethal and lethal effects on young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters point to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern. Environ Toxicol Chem 2023;42:2040-2053. © 2023 Oak Ridge National Laboratory and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Analysis of a mechanistic model of corals in association with multiple symbionts: within-host competition and recovery from bleaching.

Coral reefs are increasingly experiencing stressful conditions, such as high temperatures, that cause corals to undergo bleaching, a process where they lose their photosynthetic algal symbionts. Bleaching threatens both corals' survival and the health of the reef ecosystems they create. One possible mechanism for corals to resist bleaching is through association with stress-tolerant symbionts, which are resistant to bleaching but may be worse partners in mild conditions. Some corals have been found to associate with multiple symbiont species simultaneously, which potentially gives them access to the benefits of both stress-sensitive and -tolerant symbionts. However, within-host competition between symbionts may lead to competitive exclusion of one partner, and the consequences of associating with multiple partners simultaneously are not well understood. We modify a mechanistic model of coral-algal symbiosis to investigate the effect of environmental conditions on within-host competitive dynamics between stress-sensitive and -tolerant symbionts and the effect of access to a tolerant symbiont on the dynamics of recovery from bleaching. We found that the addition of a tolerant symbiont can increase host survival and recovery from bleaching in high-light conditions. Competitive exclusion of the tolerant symbiont occurred slowly at intermediate light levels. Interestingly, there were some cases of post-bleaching competitive exclusion after the tolerant symbiont had helped the host recover.

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.

Extrapolating Contaminant Effects from Individuals to Populations: A Case Study on Nanoparticle Toxicity to Daphnia Fed Environmentally Relevant Food Levels.

Ecological risk assessment (ERA) is charged with assessing the likelihood a chemical will have adverse environmental or ecological effects. When assessing the risk of a potential contaminant to biological organisms, ecologists are most concerned with the sustainability of populations of organisms, rather than protecting every individual. However, ERA most commonly relies on data on the effect of a potential contaminant on individuals because these experiments are more feasible than costly population-level exposures. In this work, we address the challenge of extrapolating these individual-level results to predict population-level effects. Previous per-capita population growth rate estimates calculated from individual-level exposures of Daphnia pulicaria to silver nanoparticles (AgNPs) at different food rations predict a critical daily food requirement for daphnid populations exposed to 200 µg/L AgNPs to avoid extinction. To test this, we exposed daphnid populations to the same AgNP concentration at three different food inputs, with the lowest ration close to the extinction threshold predicted from data on individuals. The two populations with the higher food inputs persisted, and the population with the lowest food input went extinct after 50 days but did persist through two generations. We demonstrate that we can extrapolate between these levels of biological organization by parameterizing an individual-level biomass model with data on individuals' response to AgNPs and using these parameters to predict the outcome for control and AgNP-exposed populations. Key to successful extrapolation is careful modeling of temporal changes in resource density, driven by both the experimental protocols and feedback from the consumer. The implication for ecotoxicology is that estimates of extinction thresholds based on studies of individuals may be reliable predictors of population outcomes, but only with careful treatment of resource dynamics.

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.

Fertilization by coral-dwelling fish promotes coral growth but can exacerbate bleaching response.

Many corals form close associations with a diverse assortment of coral-dwelling fishes and other fauna. As coral reefs around the world are increasingly threatened by mass bleaching events, it is important to understand how these biotic interactions influence corals' susceptibility to bleaching. We used dynamic energy budget modeling to explore how nitrogen excreted by coral-dwelling fish affects the physiological performance of host corals. In our model, fish presence influenced the functioning of the coral-Symbiodiniaceae symbiosis by altering nitrogen availability, and the magnitude and sign of these effects depended on environmental conditions. Although our model predicted that fish-derived nitrogen can promote coral growth, the relationship between fish presence and coral tolerance of photo-oxidative stress was non-linear. Fish excretions supported denser symbiont populations that provided protection from incident light through self-shading. However, these symbionts also used more of their photosynthetic products for their own growth, rather than sharing with the coral host, putting the coral holobiont at a higher risk of becoming carbon-limited and bleaching. The balance between the benefits of increased symbiont shading and costs of reduced carbon sharing depended on environmental conditions. Thus, while there were some scenarios under which fish presence increased corals' tolerance of light stress, fish could also exacerbate bleaching and slow or prevent subsequent recovery. We discuss how the contrast between the potentially harmful effects of fish predicted by our model and results of empirical studies may relate to key model assumptions that warrant further investigation. Overall, this study provides a foundation for future work on how coral-associated fauna influence the bioenergetics of their host corals, which in turn has implications for how these corals respond to bleaching-inducing stressors.

Transmission potential of human schistosomes can be driven by resource competition among snail intermediate hosts.

Predicting and disrupting transmission of human parasites from wildlife hosts or vectors remains challenging because ecological interactions can influence their epidemiological traits. Human schistosomes, parasitic flatworms that cycle between freshwater snails and humans, typify this challenge. Human exposure risk, given water contact, is driven by the production of free-living cercariae by snail populations. Conventional epidemiological models and management focus on the density of infected snails under the assumption that all snails are equally infectious. However, individual-level experiments contradict this assumption, showing increased production of schistosome cercariae with greater access to food resources. We built bioenergetics theory to predict how resource competition among snails drives the temporal dynamics of transmission potential to humans and tested these predictions with experimental epidemics and demonstrated consistency with field observations. This resource-explicit approach predicted an intense pulse of transmission potential when snail populations grow from low densities, i.e., when per capita access to resources is greatest, due to the resource-dependence of cercarial production. The experiment confirmed this prediction, identifying a strong effect of infected host size and the biomass of competitors on per capita cercarial production. A field survey of 109 waterbodies also found that per capita cercarial production decreased as competitor biomass increased. Further quantification of snail densities, sizes, cercarial production, and resources in diverse transmission sites is needed to assess the epidemiological importance of resource competition and support snail-based disruption of schistosome transmission. More broadly, this work illustrates how resource competition can sever the correspondence between infectious host density and transmission potential.

A time-since-infection model for populations with two pathogens.

The pioneering work of Kermack and McKendrick (1927, 1932, 1933) is now most known for introducing the SIR model, which divides a population into discrete compartments for susceptible, infected and removed individuals. The SIR model is the archetype of widely used compartmental models for epidemics. It is sometimes forgotten, that Kermack and McKendrick introduced the SIR model as a special case of a more general framework. This general framework distinguishes individuals not only by whether they are susceptible, infected or removed, but additionally tracks the time passed since they got infected. Such time-since-infection models can mechanistically link within-host dynamics to the population level. This allows the models to account for more details of the disease dynamics, such as delays of infectiousness and symptoms during the onset of an infection. Details like this can be vital for interpreting epidemiological data. The time-since-infection framework was originally formulated for a host population with a single pathogen. However, the interactions of multiple pathogens within hosts and within a population can be crucial for understanding the severity and spread of diseases. Current models for multiple pathogens mostly rely on compartmental models. While such models are relatively easy to set up, they do not have the same mechanistic underpinning as time-since-infection models. To approach this gap of connecting within-host dynamics of multiple pathogens to the population level, we here extend the time-since-infection framework of Kermack and McKendrick for two pathogens. We derive formulas for the basic reproduction numbers in the system. Those numbers determine whether a pathogen can invade a population, potentially depending on whether the other pathogen is present or not. We then demonstrate use of the framework by setting up a simple within-host model that we connect to the population model. The example illustrates the context-specific information required for this type of model, and shows how the system can be simulated numerically. We verify that the formulas for the basic reproduction numbers correctly specify the invasibility conditions.

The Effect of Dietary Exposure to Coal Ash Contaminants within Food Ration on Growth and Reproduction in Daphnia magna.

Coal ash contains numerous contaminants and is the focus of regulatory actions and risk assessments due to environmental spills. We exposed Daphnia magna to a gradient of coal ash contamination under high and low food rations to assess the sublethal effects of dietary exposures. Whereas exposure to contaminants resulted in significant reductions in growth and reproduction in daphnids, low, environmentally relevant food rations had a much greater effect on these endpoints. Environ Toxicol Chem 2020;39:1998-2007. © 2020 SETAC.

Soybeans Grown with Carbonaceous Nanomaterials Maintain Nitrogen Stoichiometry by Assimilating Soil Nitrogen to Offset Impaired Dinitrogen Fixation.

Engineered nanomaterials (ENMs) can enter agroecosystems because of their widespread use and disposal. Within soil, ENMs may affect legumes and their dinitrogen (N2) fixation, which are critical for food supply and N-cycling. Prior research focusing on end point treatment effects has reported that N2-fixing symbioses in an important food legume, soybean, can be impaired by ENMs. Yet, it remains unknown how ENMs can influence the actual amounts of N2 fixed and what plant total N contents are since plants can also acquire N from the soil. We determined the effects of one already widespread and two rapidly expanding carbonaceous nanomaterials (CNMs: carbon black, multiwalled carbon nanotubes, and graphene; each at three concentrations) on the N economy of soil-grown soybeans. Unlike previous studies, this research focused on processes and interactions within a plant-soil-microbial system. We found that total plant N accumulation was unaffected by CNMs. However, as shown by 15N isotope analyses, CNMs significantly diminished soybean N2 fixation (by 31-78%). Plants maintained N stoichiometry by assimilating compensatory N from the soil, accompanied by increased net soil N mineralization. Our findings suggest that CNMs could undermine the role of legume N2 fixation in supplying N to agroecosystems. Maintaining productivity in leguminous agriculture experiencing such effects would require more fossil-fuel-intensive N fertilizer and increase associated economic and environmental costs. This work highlights the value of a process-based analysis of a plant-soil-microbial system for assessing how ENMs in soil can affect legume N2 fixation and N-cycling.

REGULATION OF REPRODUCTIVE PROCESSES WITH DYNAMIC ENERGY BUDGETS.

1. The simple bioenergetic models in the family of Dynamic Energy Budget (DEB) consist of a small number of state equations quantifying universal processes, such as feeding, maintenance, development, reproduction and growth. Linking these organismal level processes to underlying suborganismal mechanisms at the molecular, cellular and organ level constitutes a major challenge for predictive ecological risk assessments. 2. Motivated by the need for process-based models to evaluate the impact of endocrine disruptors on ecologically relevant endpoints, this paper develops and evaluates two general modeling modules describing demand-driven feedback mechanisms exerted by gonads on the allocation of resources to production of reproductive matter within the DEB modeling framework. 3. These modules describe iteroparous, semelparous and batch-mode reproductive strategies. The modules have a generic form with both positive and negative feedback components; species and sex specific attributes of endocrine regulation can be added without changing the core of the modules. 4. We demonstrate that these modules successfully describe time-resolved measurements of wet weight of body, ovaries and liver, egg diameter and plasma content of vitellogenin and estradiol in rainbow trout (Oncorynchus mykiss) by fitting these models to published and new data, which require the estimation of less than two parameters per data type. 5. We illustrate the general applicability of the concept of demand-driven allocation of resources to reproduction as worked out in this paper by evaluating one of the modules with data on growth and seed production of an annual plant, the common bean (Phaseolis vulgaris).

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment.

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

Bioenergetic theory predicts infection dynamics of human schistosomes in intermediate host snails across ecological gradients.

Epidemiological dynamics depend on the traits of hosts and parasites, but hosts and parasites are heterogeneous entities that exist in dynamic environments. Resource availability is a particularly dynamic and potent environmental driver of within-host infection dynamics (temporal patterns of growth, reproduction, parasite production and survival). We developed, parameterised and validated a model for resource-explicit infection dynamics by incorporating a parasitism module into dynamic energy budget theory. The model mechanistically explained the dynamic multivariate responses of the human parasite Schistosoma mansoni and its intermediate host snail to variation in resources and host density. At the population level, feedbacks mediated by resource competition could create a unimodal relationship between snail density and human risk of exposure to schistosomes. Consequently, weak snail control could backfire if reductions in snail density release remaining hosts from resource competition. If resource competition is strong and relevant to schistosome production in nature, it could inform control strategies.

Remediation of Cadmium Toxicity by Sulfidized Nano-Iron: The Importance of Organic Material.

Nanozerovalent iron (nZVI) is widely used for its ability to remove or degrade environmental contaminants. However, the effect of nZVI-pollutant complexes on organisms has not been tested. We demonstrate the ability of a sulfidized derivative of nZVI (FeSSi) to sorb cadmium (Cd) from aqueous media and alleviate Cd toxicity to a freshwater alga for 32 days. FeSSi particles removed over 80% of the aqueous Cd in the first hour and nearly the same concentration of free Cd remained unbound at the end of the experiment. We found that FeSSi particles with Cd sorbed onto them are an order of magnitude more toxic than FeSSi alone. Further, algal-produced organic material facilitates safer remediation of Cd by FeSSi by decreasing the toxicity of FeSSi itself. We developed a dynamic model to predict the maximum Cd concentration FeSSi can remediate without replacing Cd toxicity with its own. FeSSi can remediate four times as much Cd to phytoplankton populations when organic material is present compared to the absence of organic material. We demonstrate the effectiveness of FeSSi as an environmental remediator and the strength of our quantitative model of the mitigation of nanoparticle toxicity by algal-produced organic material.

A dynamic bioenergetic model for coral-Symbiodinium symbioses and coral bleaching as an alternate stable state.

Coral reef ecosystems owe their ecological success - and vulnerability to climate change - to the symbiotic metabolism of corals and Symbiodinium spp. The urgency to understand and predict the stability and breakdown of these symbioses (i.e., coral 'bleaching') demands the development and application of theoretical tools. Here, we develop a dynamic bioenergetic model of coral-Symbiodinium symbioses that demonstrates realistic steady-state patterns in coral growth and symbiont abundance across gradients of light, nutrients, and feeding. Furthermore, by including a mechanistic treatment of photo-oxidative stress, the model displays dynamics of bleaching and recovery that can be explained as transitions between alternate stable states. These dynamics reveal that "healthy" and "bleached" states correspond broadly to nitrogen- and carbon-limitation in the system, with transitions between them occurring as integrated responses to multiple environmental factors. Indeed, a suite of complex emergent behaviors reproduced by the model (e.g., bleaching is exacerbated by nutrients and attenuated by feeding) suggests it captures many important attributes of the system; meanwhile, its modular framework and open source R code are designed to facilitate further problem-specific development. We see significant potential for this modeling framework to generate testable hypotheses and predict integrated, mechanistic responses of corals to environmental change, with important implications for understanding the performance and maintenance of symbiotic systems.

Standardized toxicity testing may underestimate ecotoxicity: Environmentally relevant food rations increase the toxicity of silver nanoparticles to Daphnia.

Daphnia in the natural environment experience fluctuations in algal food supply, with periods when algal populations bloom and seasons when Daphnia have very little algal food. Standardized chronic toxicity tests, used for ecological risk assessment, dictate that Daphnia must be fed up to 400 times more food than they would experience in the natural environment (outside of algal blooms) for a toxicity test to be valid. This disconnect can lead to underestimating the toxicity of a contaminant. We followed the growth, reproduction, and survival of Daphnia exposed to 75 and 200 µg/L silver nanoparticles (AgNPs) at 4 food rations for up to 99 d and found that AgNP exposure at low, environmentally relevant food rations increased the toxicity of AgNPs. Exposure to AgNP at low food rations decreased the survival and/or reproduction of individuals, with potential consequences for Daphnia populations (based on calculated specific population growth rates). We also found tentative evidence that a sublethal concentration of AgNPs (75 µg/L) caused Daphnia to alter energy allocation away from reproduction and toward survival and growth. The present findings emphasize the need to consider resource availability, and not just exposure, in the environment when estimating the effect of a toxicant. Environ Toxicol Chem 2017;36:3008-3018. © 2017 SETAC.

Agglomeration Determines Effects of Carbonaceous Nanomaterials on Soybean Nodulation, Dinitrogen Fixation Potential, and Growth in Soil.

The potential effects of carbonaceous nanomaterials (CNMs) on agricultural plants are of concern. However, little research has been performed using plants cultivated to maturity in soils contaminated with various CNMs at different concentrations. Here, we grew soybean for 39 days to seed production in soil amended with 0.1, 100, or 1000 mg kg-1 of either multiwalled carbon nanotubes (MWCNTs), graphene nanoplatelets (GNPs), or carbon black (CB) and studied plant growth, nodulation, and dinitrogen (N2) fixation potential. Plants in all CNM treatments flowered earlier (producing 60% to 372% more flowers when reproduction started) than the unamended controls. The low MWCNT-treated plants were shorter (by 15%) with slower leaf cover expansion (by 26%) and less final leaf area (by 24%) than the controls. Nodulation and N2 fixation potential appeared negatively impacted by CNMs, with stronger effects at lower CNM concentrations. All CNM treatments reduced the whole-plant N2 fixation potential, with the highest reductions (by over 91%) in the low and medium CB and the low MWCNT treatments. CB and GNPs appeared to accumulate inside nodules as observed by transmission electron microscopy. CNM dispersal in aqueous soil extracts was studied to explain the inverse dose-response relationships, showing that CNMs at higher concentrations were more agglomerated (over 90% CNMs settled as agglomerates >3 µm after 12 h) and therefore proportionally less bioavailable. Overall, our findings suggest that lower concentrations of CNMs in soils could be more impactful to leguminous N2 fixation, owing to greater CNM dispersal and therefore increased bioavailability at lower concentrations.

Integrating lipid storage into general representations of fish energetics.

Fish, even of the same species, can exhibit substantial variation in energy density (energy per unit wet weight). Most of this variation is due to differences in the amount of storage lipids. In addition to their importance as energy reserves for reproduction and for survival during unfavourable conditions, the accumulation of lipids represents a large energetic flux for many species, so figuring out how this energy flux is integrated with other major energy fluxes (growth, reproduction) is critical for any general theory of organismal energetics. Here, we synthesize data from a wide range of fish species and identify patterns of intraspecific variation in energy storage, and use these patterns to formulate a general model of energy allocation between growth, lipid storage and reproduction in fishes. From the compiled data we identified two patterns: (1) energy density increases with body size during the juvenile period, but is invariant with body size within the adult size range for most species, and (2) energy density changes across seasons, with depletion over winter, but increases fastest in periods of transition between favourable and unfavourable conditions for growth (i.e. fall). Based on these patterns we propose DEBlipid, a simple, general model of energy allocation that is closely related to a simplified version of Dynamic Energy Budget theory, DEBkiss. The crux of the model is that assimilated energy is partitioned, with κ fraction of energy allocated to pay maintenance costs first, and the surplus allocated to growth, and 1 - κ fraction of assimilated energy is allocated to accumulating storage lipids during the juvenile phase, and later to reproduction as adults. This mechanism, in addition to capturing the two patterns that motivated the model, was able to predict lipid dynamics in a novel context, the migration of anadromous fish from low-food freshwater to high-food marine environments. Furthermore, the model was used to explain intra and interspecific variation in reproductive output based on patterns of lipid accumulation as juveniles. Our results suggest that many seemingly complex, adaptive energy allocation strategies in response to ontogeny, seasonality and habitat quality can emerge from a simple physiological heuristic.