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.

Chronic Effects of an Insect Growth Regulator (teflubenzuron) on the Life Cycle and Population Growth Rate of Folsomia candida.

Current standard toxicity tests on nontarget soil invertebrates mainly focus on the endpoints survival and reproduction. Such results are likely insufficient to predict effects at higher organizational levels, for example, the population level. We assessed the effects of exposure to the pesticide teflubenzuron on the collembolan Folsomia candida, by performing a full life-cycle experiment exposing single individuals via contaminated food (uncontaminated control and 0.2, 0.32, 0.48, 0.72, 1.08, and 1.6 mg/kg dry yeast). Several life-history traits were considered by following the growth and development of newly hatched individuals over a period of 65 days. We assessed survival, body length, time to first oviposition, cumulative egg production, and hatchability of eggs. A two-stage model was applied to calculate the population growth rate (λ) combined with elasticity analysis to reveal the relative sensitivity of λ to the effects of teflubenzuron on each life-history parameter. Body length was the least sensitive life-history parameter (median effective concentration = 1.10 mg teflubenzuron/kg dry yeast) followed by time to first oviposition (0.96 mg/kg), survival (median lethal concentration = 0.87 mg/kg), cumulative egg production (0.32 mg/kg), and egg hatchability (0.27 mg/kg). Population growth decreased with increasing concentrations of teflubenzuron (λ = 1.162/day in control to 1.005/day in 0.72 mg/kg dry yeast, with populations going extinct at 1.08 and 1.6 mg/kg dry yeast). Elasticity analysis showed that changes in juvenile survival had a greater impact on the population growth rate compared with the other life-history traits. Our study provides a comprehensive overview of individual-level effects of long-term exposure to teflubenzuron and integrates these effects to assess the potential risk to collembolan populations. Environ Toxicol Chem 2024;43:1173-1183. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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.

Using life-history trait variation to inform ecological risk assessments for threatened and endangered plant species.

Developing population models for assessing risks to terrestrial plant species listed as threatened or endangered under the Endangered Species Act (ESA) is challenging given a paucity of data on their life histories. The purpose of this study was to develop a novel approach for identifying relatively data-rich nonlisted species that could serve as representatives for species listed under the ESA in the development of population models to inform risk assessments. We used the USDA PLANTS Database, which provides data on plants present in the US territories, to create a list of herbaceous plants. A total of 8742 species was obtained, of which 344 were listed under the ESA. Using the most up-to-date phylogeny for vascular plants in combination with a database of matrix population models for plants (COMPADRE) and cluster analyses, we investigated how listed species were distributed across the plant phylogeny, grouped listed and nonlisted species according to their life history, and identified the traits distinguishing the clusters. We performed elasticity analyses to determine the relative sensitivity of population growth rate to perturbations of species' survival, growth, and reproduction and compared these across clusters and between listed and nonlisted species. We found that listed species were distributed widely across the plant phylogeny as well as clusters, suggesting that listed species do not share a common evolution or life-history characteristics that would make them uniquely vulnerable. Lifespan and age at maturity were more important for distinguishing clusters than were reproductive traits. For clusters that were intermediate in their lifespan, listed and nonlisted species responded similarly to perturbations of their life histories. However, for clusters at either extreme of lifespan, the response to survival perturbations varied depending on conservation status. These results can be used to guide the choice of representative species for population model development in the context of ecological risk assessment. Integr Environ Assess Manag 2023;19:213-223. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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.

Pop-guide: Population modeling guidance, use, interpretation, and development for ecological risk assessment.

The assimilation of population models into ecological risk assessment (ERA) has been hindered by their range of complexity, uncertainty, resource investment, and data availability. Likewise, ensuring that the models address risk assessment objectives has been challenging. Recent research efforts have begun to tackle these challenges by creating an integrated modeling framework and decision guide to aid the development of population models with respect to ERA objectives and data availability. In the framework, the trade-offs associated with the generality, realism, and precision of an assessment are used to guide the development of a population model commensurate with the protection goal. The decision guide provides risk assessors with a stepwise process to assist them in developing a conceptual model that is appropriate for the assessment objective and available data. We have merged the decision guide and modeling framework into a comprehensive approach, Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE), for the development of population models for ERA that is applicable across regulatory statutes and assessment objectives. In Phase 1 of Pop-GUIDE, assessors are guided through the trade-offs of ERA generality, realism, and precision, which are translated into model objectives. In Phase 2, available data are assimilated and characterized as general, realistic, and/or precise. Phase 3 provides a series of dichotomous questions to guide development of a conceptual model that matches the complexity and uncertainty appropriate for the assessment that is in concordance with the available data. This phase guides model developers and users to ensure consistency and transparency of the modeling process. We introduce Pop-GUIDE as the most comprehensive guidance for population model development provided to date and demonstrate its use through case studies using fish as an example taxon and the US Federal Insecticide Fungicide and Rodenticide Act and Endangered Species Act as example regulatory statutes. Integr Environ Assess Manag 2021;17:767-784. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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.

Investigation of the fate and effects of acetyl cedrene on Capitella teleta and sediment bacterial community.

The fate of the fragrance material, acetyl cedrene (AC), in sediment was examined in a 16 day laboratory experiment using the sediment microbial community subjected to the following treatments: AC (nominal concentration; 0 and 50 microg g(-1) dw sediment) and macrofaunal worms (with/without Capitella teleta (formerly Capitella sp. I)). Furthermore effects of AC on microbial respiration in the system were determined by examining CO(2) flux. T-RFLP (terminal restriction fragment length polymorphism) was used to analyze PCR (polymerase chain reaction) amplified 16S DNA gene fragments from the sediments to detect changes in the structure and diversity of the bacterial community. In addition, survival of C. teleta in sediment was determined. Lastly, we examined how the interactions between microbes and C. teleta in the sediment affected the above-mentioned parameters. The results showed that there was an interaction between worm treatment and time of sampling on the loss of AC from the sediment. This was caused by AC loss initially being fastest in the sediment with C. teleta present, but at experimental termination there was no significant difference between the two treatments (i.e., with/without worms) in the amount of AC remaining in the sediment. Survival of C. teleta was significantly reduced by AC at experimental termination, but neither microbial respiration nor structure and diversity of the bacterial community were significantly affected.