Water transport through tall trees: A vertically explicit, analytical model of xylem hydraulic conductance in stems.

Trees grow by vertically extending their stems, so accurate stem hydraulic models are fundamental to understanding the hydraulic challenges faced by tall trees. Using a literature survey, we showed that many tree species exhibit continuous vertical variation in hydraulic traits. To examine the effects of this variation on hydraulic function, we developed a spatially explicit, analytical water transport model for stems. Our model allows Huber ratio, stem-saturated conductivity, pressure at 50% loss of conductivity, leaf area, and transpiration rate to vary continuously along the hydraulic path. Predictions from our model differ from a matric flux potential model parameterized with uniform traits. Analyses show that cavitation is a whole-stem emergent property resulting from non-linear pressure-conductivity feedbacks that, with gravity, cause impaired water transport to accumulate along the path. Because of the compounding effects of vertical trait variation on hydraulic function, growing proportionally more sapwood and building tapered xylem with height, as well as reducing xylem vulnerability only at branch tips while maintaining transport capacity at the stem base, can compensate for these effects. We therefore conclude that the adaptive significance of vertical variation in stem hydraulic traits is to allow trees to grow tall and tolerate operating near their hydraulic limits.

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.

Host-Symbiont Interaction Model Explains Non-monotonic Response of Soybean Growth and Seed Production to Nano-CeO2 Exposure.

Recent nanotoxicity studies have demonstrated non-monotonic dose-response mechanisms for planted soybean that have a symbiotic relationship with bacteroids in their root nodules: reduction of growth and seed production was greater for low, as compared to high, exposures. To investigate mechanistic underpinnings of the observed patterns, we formulated an energy budget model coupled to a toxicokinetic module describing bioaccumulation, and two toxicodynamic modules describing toxic effects on host plant and symbionts. By fitting data on plants exposed to engineered CeO2 nanoparticles to the newly formulated model, we show that the non-monotonic patterns can be explained as the interaction of two, individually monotonic, dose-response processes: one for the plant and the other for the symbiont. We further validate the newly formulated model by showing that, without the need for additional parameters, the model successfully predicts changes in dinitrogen fixation potential as a function of exposure (dinitrogen fixation potential data not used in model fitting). The symbiont buffers overall toxicity only when, in the absence of exposure to a toxicant, it has a parasitic interaction with the host plant. If the interaction is mutualistic or commensal, there is no buffering and only monotonic toxic responses are possible. Because the model is based on general biological principles, we expect it to be applicable to other similar symbiotic systems, especially other nodule-forming legumes.

The implications of reduced metabolic rate in resource-limited corals.

Many organisms exhibit depressed metabolism when resources are limited, a change that makes it possible to balance an energy budget. For symbiotic reef corals, daily cycles of light and periods of intense cloud cover can be chronic causes of food limitation through reduced photosynthesis. Furthermore, coral bleaching is common in present-day reefs, creating a context in which metabolic depression could have beneficial value to corals. In the present study, corals (massive Porites spp.) were exposed to an extreme case of resource limitation by starving them of food and light for 20 days. When resources were limited, the corals depressed area-normalized respiration to 37% of initial rates, and coral biomass declined to 64% of initial amounts, yet the corals continued to produce skeletal mass. However, the declines in biomass cannot account for the declines in area-normalized respiration, as mass-specific respiration declined to 30% of the first recorded time point. Thus, these corals appear to be capable of metabolic depression. It is possible that some coral species are better able to depress metabolic rates than others; such variation could explain differential survival during conditions that limit resources (e.g. shading). Furthermore, we found that maintenance of existing biomass, in part, supports the production of skeletal mass. This association could be explained if maintenance supplies needed energy (e.g. ATP) or inorganic carbon (i.e. CO2) that otherwise limits the production of skeletal mass. Finally, the observed metabolic depression can be explained as a change in pool sizes, and does not require a change in metabolic rules.

Feedbacks and tipping points in organismal response to oxidative stress.

Biological feedbacks play a crucial role in determining effects of toxicants, radiation, and other environmental stressors on organisms. Focusing on reactive oxygen species (ROS) that are increasingly recognized as a crucial mediator of many stressor effects, we investigate how feedback strength affects the ability of organisms to control negative effects of exposure. We do this by developing a general theoretical framework for describing effects of a wide range of stressors and species. The framework accounts for positive and negative feedbacks representing cellular processes: (i) production of ROS due to metabolism and the stressor, (ii) ROS reactions with cellular compounds that cause damage, and (iii) cellular control of both ROS and damage. We suggest functional forms that capture generic properties of cellular control mechanisms constituting the feedbacks, assess stability of equilibrium states in the resulting models, and investigate tipping points at which cellular control breaks down causing unregulated increase of ROS and damage. Depending on the chosen functional forms, the models can have zero, one, or two positive steady states; except in one singular case, the steady state with lowest values of ROS and damage is locally stable. We found two types of tipping points: those induced by changes in the parameters (including the stressor intensity), and those induced by the history of exposure, i.e. ROS and damage levels. The relatively simple models effectively describe several patterns of cellular responses to stress, such as the covariation of ROS and damage, the break-down of cellular control leading to explosion of ROS and/or damage, increase in damage even when ROS is (near)-constant, and the effects of exposure history on the ability of the cell to handle additional stress. The models quantify dynamics of cellular control, and could therefore be used to estimate the metabolic costs of stress and help integrate them into models that use energetic considerations to model organism's response to the environment. Although developed with unicellular organisms in mind, our models can be applied to all multicellular organisms that utilize similar feedbacks when dealing with stress.

Daphnia magna's sense of competition: intra-specific interactions (ISI) alter life history strategies and increase metals toxicity.

This work investigates whether the scale-up to multi-animal exposures that is commonly applied in genomics studies provides equivalent toxicity outcomes to single-animal experiments of standard Daphnia magna toxicity assays. Specifically, we tested the null hypothesis that intraspecific interactions (ISI) among D. magna have neither effect on the life history strategies of this species, nor impact toxicological outcomes in exposure experiments with Cu and Pb. The results show that ISI significantly increased mortality of D. magna in both Cu and Pb exposure experiments, decreasing 14 day LC50 s and 95 % confidence intervals from 14.5 (10.9-148.3) to 8.4 (8.2-8.7) µg Cu/L and from 232 (156-4810) to 68 (63-73) µg Pb/L. Additionally, ISI potentiated Pb impacts on reproduction eliciting a nearly 10-fold decrease in the no-observed effect concentration (from 236 to 25 µg/L). As an indication of environmental relevance, the effects of ISI on both mortality and reproduction in Pb exposures were sustained at both high and low food rations. Furthermore, even with a single pair of Daphnia, ISI significantly increased (p < 0.05) neonate production in control conditions, demonstrating that ISI can affect life history strategy. Given these results we reject the null hypothesis and conclude that results from scale-up assays cannot be directly applied to observations from single-animal assessments in D. magna. We postulate that D. magna senses chemical signatures of conspecifics which elicits changes in life history strategies that ultimately increase susceptibility to metal toxicity.

Relating suborganismal processes to ecotoxicological and population level endpoints using a bioenergetic model.

Ecological effects of environmental stressors are commonly evaluated using organismal or suborganismal data, such as standardized toxicity tests that characterize responses of individuals (e.g., mortality and reproduction) and a rapidly growing body of "omics" data. A key challenge for environmental risk assessment is relating such information to population dynamics. One approach uses dynamic energy budget (DEB) models that relate growth and reproduction of individuals to underlying flows of energy and elemental matter. We hypothesize that suborganismal information identifies DEB parameters that are most likely impacted by a particular stressor and that the DEB model can then project suborganismal effects on life history and population endpoints. We formulate and parameterize a model of growth and reproduction for the water flea Daphnia magna. Our model resembles previous generic bioenergetic models, but has explicit representation of discrete molts, an important feature of Daphnia life history. We test its ability to predict six endpoints commonly used in chronic toxicity studies in specified food environments. With just one adjustable parameter, the model successfully predicts growth and reproduction of individuals from a wide array of experiments performed in multiple laboratories using different clones of D. magna raised on different food sources. Fecundity is the most sensitive endpoint, and there is broad correlation between the sensitivities of fecundity and long-run growth rate, as is desirable for the default metric used in chronic toxicity tests. Under some assumptions, we can combine our DEB model with the Euler-Lotka equation to estimate longrun population growth rates at different food levels. A review of Daphnia gene-expression experiments on the effects of contaminant exposure reveals several connections to model parameters, in particular a general trend of increased transcript expression of genes involved in energy assimilation and utilization at concentrations affecting growth and reproduction. The sensitivity of fecundity to many model parameters was consistent with frequent generalized observations of decreased expression of genes involved in reproductive physiology, but interpretation of these observations requires further mechanistic modeling. We thus propose an approach based on generic DEB models incorporating few essential species-specific features for rapid extrapolation of ecotoxicogenomic assays for Daphnia-based population risk assessment.

Quantitative Adverse Outcome Pathway Analysis of Hatching in Zebrafish with CuO Nanoparticles.

This study develops and evaluates a mechanistic model of the hatching of zebrafish eggs that were exposed to CuO engineered nanoparticles (ENP) in a high-throughput screening system and places this model in an adverse outcome pathway (AOP) that also includes CuO ENP dissolution and Cu bioaccumulation. Cu(2+) inhibits the proteolytic activity of Zebrafish Hatching Enzyme 1 and thereby delay or impair hatching success. This study demonstrates that noncompetitive inhibition kinetics describe the impact of dissolved Cu on hatching; it is estimated that indefinitely long exposure to 1.88 µM dissolved Cu in the environment reduces hatching enzyme activity by 50%. The complexity arising from CuO ENP dissolution and CuO ENP assisted bioaccumulation of Cu has led to apparently contradictory findings about ion versus "nano" effects on hatching. Model-mediated data analyses indicate that, relative to copper salts, CuO ENPs increase the uptake rates of Cu into the perivitelline space up to 8 times. The toxicity assessment framework in this study can be adapted to accommodate other types of toxicant, environmental samples and other aquatic oviparous species.

Dynamic energy budget modeling reveals the potential of future growth and calcification for the coccolithophore Emiliania huxleyi in an acidified ocean.

Ocean acidification is likely to impact the calcification potential of marine organisms. In part due to the covarying nature of the ocean carbonate system components, including pH and CO2 and CO3(2-) levels, it remains largely unclear how each of these components may affect calcification rates quantitatively. We develop a process-based bioenergetic model that explains how several components of the ocean carbonate system collectively affect growth and calcification rates in Emiliania huxleyi, which plays a major role in marine primary production and biogeochemical carbon cycling. The model predicts that under the IPCC A2 emission scenario, its growth and calcification potential will have decreased by the end of the century, although those reductions are relatively modest. We anticipate that our model will be relevant for many other marine calcifying organisms, and that it can be used to improve our understanding of the impact of climate change on marine systems.

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.

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.

Benchmarks in organism performance and their use in comparative analyses.

Evaluating the response of organisms to stress assumes that functional benchmarks are available against which the response can be gauged, but this expectation remains unfulfilled for many taxa. As a result, attempts to describe the organismic effects of environmental degradation and physiological stress can prove misleading. Functional benchmarks and the effects of stress are particularly germane to coral reefs that globally are exposed to significant environmental challenges, and in this study, we compiled data on scleractinian corals to describe a reference against which stress responses can be gauged. Based on this construct, we tested the veracity of well-established contrasts--involving differences in physiological function among depths and families--to evaluate the capacity of available data to support synthetic analyses. Our analysis used 126 papers describing 37 genera, and at least 73 species, and described 13 traits, first independent of depth, and second, by depth. Data appropriate for these analyses were so sparse that depth- and family-level effects were inconspicuous, although the depth contrast revealed a decline in dark respiration and an increase in calcification (both normalized to area) in deeper water. Our analyses of scleractinian literature revealed limitations of the data available for synthetic analyses, as well for describing functional benchmarks within this taxon. We attribute some of these effects to differences in the physical environment under which measurements were made, and suspect that such problems are commonplace for other taxa. Dynamic Energy Budget (DEB) models provide one means to overcome some of these problems, and they can be used for any taxon to quantitatively summarize data for comparative analyses of stressor responses. The suitability of these models is illustrated for scleractinian corals by predicting from first principles the ratio of Symbiodinium to holobiont carbon and the respiration.

Impacts of metal oxide nanoparticles on marine phytoplankton.

Information on the toxicity of environmentally relevant concentrations of nanoparticles in marine ecosystems is needed for informed regulation of these emerging materials. We tested the effects of two types of metal oxide nanoparticles, TiO(2) and ZnO, on population growth rates of four species of marine phytoplankton representing three major coastal groups (diatoms, chlorophytes, and prymnesiophytes). These metal oxide nanoparticles (NPs) are becoming common components in many industrial, household, and cosmetic products that are released into coastal ecosystems. Titania NPs showed no measurable effect on growth rates of any species, while ZnO NPs significantly depressed growth rate of all four species. ZnO NPs aggregated rapidly in seawater, forming particles >400 nm hydrodynamic diameter within 30 min, and dissolved quickly, reaching equilibrium concentrations within 12 h. Toxicity of ZnO NPs to phytoplankton was likely due to dissolution, release, and uptake of free zinc ions, but specific nanoparticulate effects may be difficult to disentangle from effects due to free zinc ions. A modeling approach based on a Dynamic Energy Budget (DEB) framework was used to estimate sublethal effects of the two NPs on phytoplankton populations. Concentrations that were estimated to have no effect on population growth (NEC) were (one standard error in parentheses) 428 (58) µg L(-1) ZnO for the diatom Skeletonema marinoi and 223 (56) µg L(-1) for Thalassiosira pseudonana. NEC could not be estimated for the other taxa but were within the range of 500-1000 µg L(-1). Our results suggest that effects of metal oxide NPs on marine organisms is likely to vary with particle type and organism taxonomy.

Sublethal toxicant effects with dynamic energy budget theory: model formulation.

We develop and test a general modeling framework to describe the sublethal effects of pollutants by adding toxicity modules to an established dynamic energy budget (DEB) model. The DEB model describes the rates of energy acquisition and expenditure by individual organisms; the toxicity modules describe how toxicants affect these rates by changing the value of one or more DEB parameters, notably the parameters quantifying the rates of feeding and maintenance. We investigate four toxicity modules that assume: (1) effects on feeding only; (2) effects on maintenance only; (3) effects on feeding and maintenance with similar values for the toxicity parameters; and (4) effects on feeding and maintenance with different values for the toxicity parameters. We test the toxicity modules by fitting each to published data on feeding, respiration, growth and reproduction. Among the pollutants tested are metals (mercury and copper) and various organic compounds (chlorophenols, toluene, polycyclic aromatic hydrocarbons, tetradifon and pyridine); organisms include mussels, oysters, earthworms, water fleas and zebrafish. In most cases, the data sets could be adequately described with any of the toxicity modules, and no single module gave superior fits to all data sets. We therefore propose that for many applications, it is reasonable to use the most general and parameter sparse module, i.e. module 3 that assumes similar effects on feeding and maintenance, as a default. For one example (water fleas), we use parameter estimates to calculate the impact of food availability and toxicant levels on the long term population growth rate.

Sublethal toxicant effects with dynamic energy budget theory: application to mussel outplants.

We investigate the effectiveness of a sublethal toxic effect model embedded in Dynamic Energy Budget (DEB) theory for the analysis of field data. We analyze the performance of two species of mussels, Mytilus galloprovincialis and M. californianus, near a diffuser discharging produced water in the Southern California Bight, California. Produced water is a byproduct of oil production consisting of fossil water together with compounds added during the extraction process, and generally contains highly elevated levels of pollutants relative to sea water. Produced water negatively affects the production of somatic and reproductive biomass in both mussel species; we show that these negative effects can be quantified with our DEB-based modeling framework through the estimation of toxic effect scaling parameters. Our analyses reveal that the toxic impact of produced water on growth and reproduction of M. californianus is substantially higher than for M. galloprovincialis. Projections of the expected lifetime production of gonad biomass indicate that the environmental impact of produced water can be as large as 100%, whereas short-term assessment without the use of DEB theory projects a maximum effect of only 30%.

Conventional and nano-copper pesticides are equally toxic to the estuarine amphipod Leptocheirus plumulosus.

Modern nano-engineered pesticides have great promise for agriculture due to their extended, low dose release profiles that are intended to increase effectiveness but reduce environmental harm. Whether nanopesticides, including copper (Cu) formulations, cause reduced levels of toxicity to non-target aquatic organisms is unclear but important to assess. Predicting how aquatic species respond to incidental exposure to Cu-based nanopesticides is challenging because of the expected very low concentrations in the environment, and the two forms of exposure that may occur, namely to Cu ions and Cu nanoparticles. We conducted Cu speciation, tissue uptake, and 7-day toxicity laboratory experiments to test how a model estuarine organism, the amphipod Leptocheirus plumulosus, responded to two popular Cu-based nanopesticides, CuPRO and Kocide, and conventional CuCl2. Exposure concentrations ranged from 0 to 2.5 ppm, which were similar to those found in estuarine water located downstream of agricultural fields. Cu dissolution rates were much slower for the nanopesticides than the ionic formula, and Cu body burden in amphipods increased approximately linearly with the nominal exposure concentration. Amphipod survival declined in a normal dose-response manner with no difference among Cu formulations. Growth and movement rates after 7 days revealed no difference among exposure levels when analyzed with conventional statistical methods. By contrast, analysis of respiration rates, inferred from biomass measurements, with a bioenergetic toxicodynamic model indicated potential for population-level effects of exposure to very low-levels of the two nanopesticides, as well as the control contaminant CuCl2. Our results indicate that toxicity assessment of environmental trace pollutant concentrations may go undetected with traditional ecotoxicological tests. We present a process integrating toxicity test results and toxicodynamic modeling that can improve our capacity to detect and predict environmental impacts of very low levels of nanomaterials released into the environment.

Dynamic energy budgets in syntrophic symbiotic relationships between heterotrophic hosts and photoautotrophic symbionts.

In this paper we develop and investigate a dynamic energy budget (DEB) model describing the syntrophic symbiotic relationship between a heterotrophic host and an internal photoautotrophic symbiont. The model specifies the flows of matter and energy among host, symbiont and environment with minimal complexity and uses the concept of synthesizing units to describe smoothly the assimilation of multiple limiting factors, in particular inorganic carbon and nitrogen, and irradiance. The model has two passive regulation mechanisms: the symbiont shares only photosynthate that it cannot use itself, and the host delivers only excess nutrients to the symbiont. With parameter values plausible for scleractinian corals, we show that these two regulation mechanisms suffice to obtain a stable symbiotic relationship under constant ambient conditions, provided those conditions support sustenance of host and symbiont. Furthermore, the symbiont density in the host varies relatively little as a function of ambient food density, inorganic nitrogen and irradiance. This symbiont density tends to increase with light deprivation or nitrogen enrichment, either directly or via food. We also investigate the relative benefit each partner derives from the relationship and conclude that this relationship may shift from mutualism to parasitism as environmental conditions change.

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.

Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton.

High Throughput Screening (HTS) using in vitro assessments at the subcellular level has great promise for screening new chemicals and emerging contaminants to identify high-risk candidates, but their linkage to ecological impacts has seldom been evaluated. We tested whether a battery of subcellular HTS tests could be used to accurately predict population-level effects of engineered metal nanoparticles (ENPs) on marine phytoplankton, important primary producers that support oceanic food webs. To overcome well-known difficulties of estimating ecologically meaningful toxicity parameters, we used novel Dynamic Energy Budget and Toxicodynamic (DEBtox) modeling techniques to evaluate impacts of ENPs on population growth rates. Our results show that population growth was negatively impacted by all four ENPs tested, but the HTS tests assessing many cell/physiological functions lacked predictive power at the population level. However, declining photosynthetic efficiency, a traditional physiological endpoint for photoautotrophs, was a good predictor of population level effects in phytoplankton. DEBtox techniques provided robust estimates of EC10 for population growth rates in exponentially growing batch cultures of phytoplankton, and should be widely useful for ecotoxicological testing. Adoption of HTS approaches for ecotoxicological assessment should carefully evaluate the predictive power of specific assays to minimize the risk that effects at higher levels of biological organization may go undetected.