When things don't add up: quantifying impacts of multiple stressors from individual metabolism to ecosystem processing.

Ecosystems are exposed to multiple stressors which can compromise functioning and service delivery. These stressors often co-occur and interact in different ways which are not yet fully understood. Here, we applied a population model representing a freshwater amphipod feeding on leaf litter in forested streams. We simulated impacts of hypothetical stressors, individually and in pairwise combinations that target the individuals' feeding, maintenance, growth and reproduction. Impacts were quantified by examining responses at three levels of biological organisation: individual-level body sizes and cumulative reproduction, population-level abundance and biomass and ecosystem-level leaf litter decomposition. Interactive effects of multiple stressors at the individual level were mostly antagonistic, that is, less negative than expected. Most population- and ecosystem-level responses to multiple stressors were stronger than expected from an additive model, that is, synergistic. Our results suggest that across levels of biological organisation responses to multiple stressors are rarely only additive. We suggest methods for efficiently quantifying impacts of multiple stressors at different levels of biological organisation.

Impaired ecosystem process despite little effects on populations: modeling combined effects of warming and toxicants.

Freshwater ecosystems are exposed to many stressors, including toxic chemicals and global warming, which can impair, separately or in combination, important processes in organisms and hence higher levels of organization. Investigating combined effects of warming and toxicants has been a topic of little research, but neglecting their combined effects may seriously misguide management efforts. To explore how toxic chemicals and warming, alone and in combination, propagate across levels of biological organization, including a key ecosystem process, we developed an individual-based model (IBM) of a freshwater amphipod detritivore, Gammarus pseudolimnaeus, feeding on leaf litter. In this IBM, life history emerges from the individuals' energy budgets. We quantified, in different warming scenarios (+1-+4 °C), the effects of hypothetical toxicants on suborganismal processes, including feeding, somatic and maturity maintenance, growth, and reproduction. Warming reduced mean adult body sizes and population abundance and biomass, but only in the warmest scenarios. Leaf litter processing, a key contributor to ecosystem functioning and service delivery in streams, was consistently enhanced by warming, through strengthened interaction between the detritivorous consumer and its resource. Toxicant effects on feeding and maintenance resulted in initially small adverse effects on consumers, but ultimately led to population extinction and loss of ecosystem process. Warming in combination with toxicants had little effect at the individual and population levels, but ecosystem process was impaired in the warmer scenarios. Our results suggest that exposure to the same amount of toxicants can disproportionately compromise ecosystem processing depending on global warming scenarios; for example, reducing organismal feeding rates by 50% will reduce resource processing by 50% in current temperature conditions, but by up to 200% with warming of 4 °C. Our study has implications for assessing and monitoring impacts of chemicals on ecosystems facing global warming. We advise complementing existing monitoring approaches with directly quantifying ecosystem processes and services.

Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

Stakeholders' perspective on ecological modeling in environmental risk assessment of pesticides: challenges and opportunities.

The article closely examines the role of mechanistic effect models (e.g., population models) in the European environmental risk assessment (ERA) of pesticides. We studied perspectives of three stakeholder groups on population modeling in ERA of pesticides. Forty-three in-depth, semi-structured interviews were conducted with stakeholders from regulatory authorities, industry, and academia all over Europe. The key informant approach was employed in recruiting our participants. They were first identified as key stakeholders in the field and then sampled by means of a purposive sampling, where each stakeholder identified as important by others was interviewed and asked to suggest another potential participant for our study. Our results show that participants, although having different institutional backgrounds often presented similar perspectives and concerns about modeling. Analysis of repeating ideas and keywords revealed that all stakeholders had very high and often contradicting expectations from models. Still, all three groups expected effect models to become integrated in future ERA of pesticides. Main hopes associated with effect models were to reduce the amount of expensive and complex testing and field monitoring, both at the product development stage, and as an aid to develop mitigation measures. Our analysis suggests that, although the needs of stakeholders often overlapped, subtle differences and lack of trust hinder the process of introducing mechanistic effect models into ERA.

Mechanistic population models for ecological risk assessment and decision support: The importance of good conceptual model diagrams.

The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;00:1-9. © 2023 SETAC.

Moving beyond Risk Quotients: Advancing Ecological Risk Assessment to Reflect Better, More Robust and Relevant Methods.

Under standard guidance for conducting Ecological Risk Assessments (ERAs), the risks of chemical exposure to diverse organisms are most often based on deterministic point estimates evaluated against safety-factor-based levels of concern (LOCs). While the science and guidance for mechanistic effect models (e.g., demographic, population, and agent-based) have long been demonstrated to provide more ecologically relevant effect endpoints upon which risk can be evaluated, their application in ERAs has been limited, particularly in the US. This special issue highlights the state of the science in effect modeling for ERAs through demonstrated application of the recently published Population modeling Guidance, Use, Interpretation, and Development for ERA (Pop-GUIDE). We introduce this issue with a perspective on why it is critical to move past the current application of deterministic endpoints and LOCs. We demonstrate how the current, widely used approaches contain extensive uncertainty that could be reduced considerably by applying models that account for species life histories and other important endogenous and exogenous factors critical to species sustainability. We emphasize that it is long past time to incorporate better, more robust, and ecologically relevant effect models into ERAs, particularly for chronic risk determination. The papers in this special issue demonstrate how mechanistic models that follow Pop-GUIDE better inform ERAs compared to the current standard practice.

Probable role of Cutibacterium acnes in the gut of the polychaete Capitella teleta.

Capitella teleta, a marine polychaete that feeds on a refractory diet consisting of sediment, was shown to contain unique gut microbiota comprised of microbial functional groups involved in fermentation. Results of our previous studies showed that C. teleta's core gut microbiota were dominated by propionibacteria, and that these bacteria were more abundant in worms than in sediment and feces. In order to test the hypothesis that the worm nutritionally benefits from its gut microbiota, we identified, and genetically and biochemically characterized Cutibacterium acnes strains (formerly Propionibacterium acnes) that were isolated from the gut of C. teleta. Here we show that 13 worm-isolated Cutibacterium acnes strains primarily belonged to phylotype group IB, likely as a clonal population. We also provide evidence that all tested strains produced propionate and vitamin B12, which are essential host-requiring microbial metabolites. The presence of C. acnes in C. teleta was not unique to our worm culture and was also found in those obtained from geographically distant laboratories located in the U.S. and Europe. Moreover, populations of worm gut-associated C. acnes increased following antibiotic treatment. Collectively, results of this study demonstrated that C. acnes is a member of the worm's core functional microbiota and is likely selectively favored by the physiology and chemistry of the host gut environment. To our knowledge, this is the first report of the presence of C. acnes in the C. teleta gut. Our data strongly suggest that C. acnes, a bacterium previously studied as an opportunistic pathogen, can likely act as a symbiont in C. teleta providing the host essential nutrients for survival, growth, and reproduction.

Population modeling to inform management and recovery efforts for lake sturgeon, Acipenser fulvescens.

Lake sturgeon (Acipenser fulvescens) populations have significantly declined across their historic range, in large part due to anthropogenic impacts that have likely been exacerbated by the life-history traits of this slow-growing and long-lived species. We developed a population model to explore how Contaminants of Emerging Concern (CECs) impact lake sturgeon populations. We explored how different physiological modes of action (pMoAs) of CECs impacted population abundance and recovery and how different simulated management actions could enable recovery. We first estimated the impacts on population abundance and recovery by comparing the trajectory of an unexposed population to a population that had been exposed to a CEC with a specific pMoA after the end of the exposure. We then predicted how different management actions would impact population recovery by comparing the trajectories of an unexposed population to an exposed population for which a management action started at a fixed time without discontinuation of the exposure. Our results predicted that the individual-level pMoA of CECs has an important impact on population-level effects because different stressor's pMoA impacts the life-history traits of sturgeon differently. For example, the feeding and reproduction pMoAs caused the strongest and weakest population declines, respectively. For the same reason, pMoA also impacted recovery. For example, recovery was delayed when the pMoA was growth, maintenance, or feeding, but it was immediate when the pMoA was reproduction. We found that management actions that increased the egg survival rate or the stocking of fingerlings resulted in faster and stronger recovery than management actions that increased the juvenile or adult survival rate. This result occurred because the first two management actions immediately impacted recruitment, whereas the impact was delayed for the last two. Finally, there was greater potential for recovery when management action targeted eggs and fingerlings because these life stages have lower natural survival rates. Integr Environ Assess Manag 2022;18:1597-1608. © 2022 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Long-term effects of sediment-associated silver nanoparticles and silver nitrate on the deposit-feeding polychaete Capitella teleta.

Aquatic sediments are predicted to be an important sink for released silver nanoparticles (AgNPs). Knowing the long-term effects of AgNPs on benthic deposit-feeders is therefore an important step towards assessing their potential environmental risks. The aim of this study was to examine the effects on survival, growth and reproduction of the deposit-feeding polychaete Capitella teleta exposed for ten weeks to sediment-associated un-coated AgNPs or silver nitrate (AgNO3). C. teleta exhibited tolerance towards exposure to both AgNPs and AgNO3. Significant effects were observed for percentage of pairs that reproduced as well as worm growth after eight weeks, but the effects did not show a clear concentration- or Ag type-dependent pattern. Further investigations of long-term effects of un-coated AgNPs in additional sediment-dwelling organisms are needed and should involve comparisons to coated AgNPs.

Temperature dependence of population responses to competition and metabolic stress: An agent-based model to inform ecological risk assessment in a changing climate.

Understanding the interactions among multiple stressors is a crucial issue for ecological risk assessment and ecosystem management. However, it is often impractical, or impossible, to collect empirical data concerning all the interactions at any scale because the type of interaction differs across species and levels of biological organization. We applied an agent-based model to simulate the effects of a hypothetical chemical stressor and inter-specific competition (both alone and together) on greenback cutthroat trout (GCT), a listed species under the US Endangered Species Act, in two temperature scenarios. The trout life cycle is modeled using the Dynamic Energy Budget theory. The chemical stressor is represented by a reduction in ingestion efficiency, and competition is implemented by introducing a population of brown trout. Results show that chemical exposure is the major stressor in the colder temperature scenario, whereas competition mostly affected the GCT population in the warmer environment. Moreover, the effects of the stressors at the individual level were not predictive of the type of interactions between stressors (additive, antagonistic, synergistic) at the population level, which differed between the two-temperature scenarios. We conclude that mechanistic models can help to identify generalities about interactions among environmental and stressor properties, create in-silico experiments to provide different scenarios for conservation purposes, and explore multiple-exposure consequences at higher levels of biological organization. In this way they can provide useful tools for improving ecological risk assessment and informing management decisions.

A simulation-based evaluation of management actions to reduce the risk of contaminants of emerging concern (CECs) to walleye in the Great Lakes Basin.

Contaminants of emerging concern (CECs) are ubiquitous, present in complex chemical mixtures, and represent a threat to the Great Lake ecosystem. Mitigation strategies are needed to protect populations of key species, but knowledge about ecological and biological effects of CECs at the population level are limited. In this study, we combined laboratory data on CEC effects at the individual-level with in-situ CEC concentration data in a walleye (Sander vitreus) population model to simulate the effectiveness of different CEC mitigation strategies in the Maumee River and Lake Erie. We compared the effectiveness of moderate mitigation (50% reduction in exposure level) of an entire watershed versus intensive mitigation (reduction of exposure to a level that does not affect walleye) of single river sites for three CEC mixture scenarios (agricultural, urban, and combined). We also explored the impact of hypothetical chemical toxicokinetics (the time course of chemicals in walleye) on the relative effectiveness of the mitigation strategies. Our results suggest that when CECs impact fecundity, single-site mitigation is more effective when it focuses on spawning sites and nearby downstream sites that are substantially impaired. Our simulations also suggest that chemical toxicokinetics are important when evaluating single-site mitigation strategies, but that population characteristics, such as stage-specific mortality rate, are more important when evaluating watershed mitigation strategies. Results can be used to guide fisheries management, such as choosing habitat restoration sites, and identify key knowledge gaps that direct future research and monitoring.

Bioturbation by the marine polychaete Capitella teleta alters the sediment microbial community by ingestion and defecation of sediment particles.

Deposit-feeding benthic invertebrates are known to modify sediment structure and impact microbial processes associated with biogeochemical cycles in marine sedimentary environments. Despite this, however, there is limited information on how sediment ingestion and defecation by marine benthos alters microbial community structure and function in sediments. In the current study, we used high-throughput sequencing data of 16S rRNA genes obtained from a previous microcosm study to examine how sediment processing by the marine polychaete Capitella teleta specifically affects sediment microbiota. Here we show that both sediment ingestion and defecation by C. teleta significantly alters overall microbial community structure and function. Sediment processing by C. teleta resulted in significant enrichment of sediment microbial communities involved in sulfur and carbon cycling in worm fecal pellets. Moreover, C. teleta's microbiota was predominantly comprised of bacterial functional groups involved in fermentation, relative to microbiota found outside of the host. Collectively, results of this study indicate that C. teleta has the ability to alter microbial biogeochemical cycles in the benthic sedimentary environment by altering microbial assemblages in the worm gut, and in the sediment ingested and defecated by worms as they feed on sediment particles. In this sense, C. teleta plays an important role as an ecosystem engineer and in shaping nutrient cycling in the benthic environment.

A Review of Key Features and Their Implementation in Unstructured, Structured, and Agent-Based Population Models for Ecological Risk Assessment.

Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life-history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent-based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent-based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521-540. © 2020 SETAC.

Mechanistic Effect Modeling of Earthworms in the Context of Pesticide Risk Assessment: Synthesis of the FORESEE Workshop.

Earthworms are important ecosystem engineers, and assessment of the risk of plant protection products toward them is part of the European environmental risk assessment (ERA). In the current ERA scheme, exposure and effects are represented simplistically and are not well integrated, resulting in uncertainty when the results are applied to ecosystems. Modeling offers a powerful tool to integrate the effects observed in lower tier laboratory studies with the environmental conditions under which exposure is expected in the field. This paper provides a summary of the (In)Field Organism Risk modEling by coupling Soil Exposure and Effect (FORESEE) Workshop held 28-30 January 2020 in Düsseldorf, Germany. This workshop focused on toxicokinetic-toxicodynamic (TKTD) and population modeling of earthworms in the context of ERA. The goal was to bring together scientists from different stakeholder groups to discuss the current state of soil invertebrate modeling and to explore how earthworm modeling could be applied to risk assessments, in particular how the different model outputs can be used in the tiered ERA approach. In support of these goals, the workshop aimed at addressing the requirements and concerns of the different stakeholder groups to support further model development. The modeling approach included 4 submodules to cover the most relevant processes for earthworm risk assessment: environment, behavior (feeding, vertical movement), TKTD, and population. Four workgroups examined different aspects of the model with relevance for risk assessment, earthworm ecology, uptake routes, and cross-species extrapolation and model testing. Here, we present the perspectives of each workgroup and highlight how the collaborative effort of participants from multidisciplinary backgrounds helped to establish common ground. In addition, we provide a list of recommendations for how earthworm TKTD modeling could address some of the uncertainties in current risk assessments for plant protection products. Integr Environ Assess Manag 2021;17:352-363. © 2020 SETAC.

Environmentally sensitive life-cycle traits have low elasticity: implications for theory and practice.

The relationships between population growth rate and the life-cycle traits contributing to it are nonlinear and variable. This has made it difficult for ecologists to consistently predict changes in population dynamics from observations on changes in life-cycle traits. We show that traits having a high sensitivity to chemical toxicants tend to have a low elasticity, meaning that changes in them have a relatively low impact on population growth rate, compared to other life-cycle traits. This makes evolutionary sense in that there should be selection against variability in population growth rate. In particular, we found that fecundity was generally more sensitive to chemical stress than was juvenile or adult survival or time to first reproduction, whereas fecundity typically had a lower elasticity than the other life-cycle traits. Similar relationships have been recorded in field populations for a wide range of taxa, but the conclusions were necessarily more tentative because stochastic effects and confounding variables could not be excluded. Better knowledge of these relationships can be used to optimize population management and protection strategies and to increase understanding of the drivers of population dynamics.

Lack of evidence for the role of gut microbiota in PAH biodegradation by the polychaete Capitella teleta.

Capitella teleta is a marine sediment-feeding polychaete known to degrade various polycyclic aromatic hydrocarbons (PAHs) and reported to possess genes involved in PAH transformation, such as those in the P450 cytochrome superfamily. Previous research focusing on biodegradation of PAHs by C. teleta demonstrated that these worms are effective biodegraders, but overlooked the possible role of its gut microbiota in facilitating PAH metabolism. Recently, C. teleta's microbiome was characterized and found to contain several bacterial genera known to contain PAH-degrading members, including Acinetobacter, Thalassotalea, and Achromobacter. Despite this, however, no data have thus far been presented demonstrating the role of C. teleta's gut microbiota in PAH degradation. The present study was designed to more conclusively determine the presence of PAH-degrading bacteria in worm digestive tracts and to more clearly distinguish the relative roles of worm versus gut-microbial metabolism in the removal of PAH from sediment. To do this, we manipulated marine sediment microorganisms and worm gut microbiota by autoclaving and antibiotic treatment, respectively. Our results showed that no fluoranthene degradation occurred in microcosms in the absence of worms. More importantly, there was no significant difference in fluoranthene degradation between antibiotic-treated and non-treated worms. We also found no evidence of fluoranthene degradation using resting cells of gut microbes of C. teleta, and we were unable to isolate fluoranthene-degrading bacterial strains from enrichments of polychaete gut contents, despite multiple attempts. Gut microbiota in worms treated with antibiotics recovered, through bidirectional transfer, between worms and sediment after 2 weeks of microcosm incubation, and gut microbes appear to be required for the survival and growth of C. teleta. Our results build on previous studies suggesting that C. teleta itself is primarily responsible for the metabolism of fluoranthene in ingested sediment. We hypothesize that C. teleta's core microbiota, which includes members of Propionibacterium as the most abundant genus, likely aid worms in obtaining key nutrients (e.g., vitamins) from its sediment diet.

Divergent density feedback control of migratory predator recovery following sex-biased perturbations.

Uncertainty in risks posed by emerging stressors such as synthetic hormones impedes conservation efforts for threatened vertebrate populations. Synthetic hormones often induce sex-biased perturbations in exposed animals by disrupting gonad development and early life-history stage transitions, potentially diminishing per capita reproductive output of depleted populations and, in turn, being manifest as Allee effects. We use a spatially explicit biophysical model to evaluate how sex-biased perturbation in life-history traits of individuals (maternal investment in egg production and male-skewed sex allocation in offspring) modulates density feedback control of year-class strength and recovery trajectories of a long-lived, migratory fish-shovelnose sturgeon (Scaphirhynchus platorynchus)-under spatially and temporally dynamic synthetic androgen exposure and habitat conditions. Simulations show that reduced efficiency of maternal investment in gonad development prolonged maturation time, increased the probability of skipped spawning, and, in turn, shrunk spawner abundance, weakening year-class strength. However, positive density feedback disappeared (no Allee effect) once the exposure ceased. By contrast, responses to the demographic perturbation manifested as strong positive density feedback; an abrupt shift in year-class strength and spawner abundance followed after more than two decades owing to persistent negative population growth (a strong Allee effect), reaching an alternative state without any sign of recovery. When combined with the energetic perturbation, positive density feedback of the demographic perturbation was dampened as extended maturation time reduced the frequency of producing male-biased offspring, allowing the population to maintain positive growth rate (a weak Allee effect) and gradually recover. The emergent patterns in long-term population projections illustrate that sex-biased perturbation in life-history traits can interactively regulate the strength of density feedback in depleted populations such as Scaphirhynchus sturgeon to further diminish reproductive capacity and abundance, posing increasingly greater conservation challenges in chemically altered riverscapes.

The effects of spatial and temporal heterogeneity on the population dynamics of four animal species in a Danish landscape.

BACKGROUND: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. RESULTS: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23-30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3-13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. CONCLUSION: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.

Individual- and population-level effects of the synthetic musk, HHCB, on the deposit-feeding polychaete, Capitella sp. I.

A life table response experiment lasting 120 d was used to investigate the effects of the synthetic polycyclic musk HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8-hexamethylcyclopenta-gamma-2-benzopyrane; 0, 1.5, 26, 123, and 168 mg/kg dry wt sediment) on the life history of the infaunal polychaete Capitella species I. The HHCB exposure showed no detectable effects on adult survival, age at first reproduction, length of the reproductive period, number of broods, individual worm body volumes, or body size-specific egestion rates. In contrast, HHCB significantly affected juvenile survival (>or=123 mg/kg), maturation time (168 mg/kg), total number of eggs produced (>or=26 mg/kg), and brood size (>or=123 mg/kg) and marginally increased time between breeding attempts (>or=26 mg/kg). A declining trend was observed for population growth rate with increasing HHCB concentrations, but differences between the control and exposed groups were not significant. Thus, despite detectable effects of HHCB on individual life-history traits, the results suggest that environmentally realistic concentrations of HHCB are not likely to reduce the growth rate of Capitella sp. I populations.