Matthew A. Etterson

Adverse outcome pathways and ecological risk assessment: Bridging to population‐level effects

Maintaining the viability of populations of plants and animals is a key focus for environmental regulation. Population-level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of population-level effects of contaminants can integrate information from lower levels of biological organization and feed that information into higher-level community and ecosystem models. As individual-level endpoints are used to predict population responses, this requires that biological responses at lower levels of organization be translated into a form that is usable by the population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on population-level risk assessments. First, we describe the regulatory context surrounding population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the level of the individual serve as the linkage, or bridge, between AOPs and predictions of population status, including consideration of community-level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into population modeling.

Mercury Exposure Affects the Reproductive Success of a Free-Living Terrestrial Songbird, the Carolina Wren (Thryothorus ludovicianus)

ABSTRACT. Despite mounting evidence of mercury accumulation in terrestrial ecosystems, few data exist on how environmental mercury exposure affects reproductive success in free-living songbirds. From 2007 through 2010, we monitored reproductive success of Carolina Wrens (Thryothorus ludovicianus) breeding along the forest floodplain of two mercury-contaminated rivers in Virginia. Using an information-theoretic approach, we found a 34% reduction in nesting success of Carolina Wrens on mercury-contaminated sites when compared with reference sites. Blood mercury concentration of the attending female was a strong predictor of nest success. Birds nesting on contaminated sites were 3× more likely to abandon their nests than birds on uncontaminated reference sites. We report a range of effects concentrations associated with various levels of reproductive impairment; for example, a 10% reduction in nest success corresponded with 0.7 µg g-1 mercury in the blood, 2.4 µg g-1 mercury in body feathers, 3.0 µg g-1 mercury in tail feathers, and 0.11 µg g-1 mercury in eggs. This is the first field study to document the effect of specific adult songbird blood mercury concentrations on breeding performance; our results show that free-living songbirds can suffer negative reproductive effects at relatively low mercury concentrations.

PARTITIONING RISK AMONG DIFFERENT CAUSES OF NEST FAILURE

Abstract Nest predation and nest parasitism receive the most attention as causes of nest failure for North American songbirds. Yet for many populations, interspecific competition, adverse weather, abandonment, nestling starvation, and egg failure may also be significant causes of nest failure. Despite the long interest in differential failure, serious challenges remain in the estimation of separate probabilities of nest failure from different causes. Apparent rates of failure suffer from at least two sources of bias: heterogeneous ages at discovery and classification error. We developed maximum-likelihood estimators for cause-specific daily probabilities of nest failure. We further show how the estimators can be extended to include classification error, if known. Finally, we demonstrate a simple application to Loggerhead Shrikes (Lanius ludovicianus), Tree Swallows (Tachycineta bicolor), Violet-green Swallows (T. thalassina), and Western Bluebirds (Sialia mexicana). Daily probabilities of survival were lower for the Loggherhead Shrike (0.978 ± 0.004) than for any of the three cavity-nesting species (range: 0.989 ± 0.002 − 0.993 ± 0.001). Weather was an important cause of nest failure for Loggerhead Shrikes (0.15 ± 0.05 overall). Conversely, competition among secondary cavity-nesters was not an important contributor to nest failure (range: 2–5% of nest failures) for bluebirds or swallows. Our estimator differs from others by allowing multiple fates to be modeled as separately estimated parameters rather than as covariates to a single estimated failure probability. Thus, our estimator should be viewed as an important complement to existing methods. División del Riesgo Entre Diferentes Causas de Fracaso Durante la Nidificación

Estimating the effects of detection heterogeneity and overdispersion on trends estimated from avian point counts

Point counts are a common method for sampling avian distribution and abundance. Although methods for estimating detection probabilities are available, many analyses use raw counts and do not correct for detectability. We use a removal model of detection within an N-mixture approach to estimate abundance trends corrected for imperfect detection. We compare the corrected trend estimates to those estimated from raw counts for 16 species using 15 years of monitoring data on three national forests in the western Great Lakes, USA. We also tested the effects of overdispersion by modeling both counts and removal mixtures under three statistical distributions: Poisson, zero-inflated Poisson, and negative binomial. For most species, the removal model produced estimates of detection probability that conformed to expectations. For many species, but not all, estimates of trends were similar regardless of statistical distribution or method of analysis. Within a given combination of likelihood (counts vs. mixtures) and statistical distribution, trends usually differed by both stand type and national forest, with species showing declines in some stand types and increases in others. For three species, Brown Creeper, Yellow-rumped Warbler, and Black-throated Green Warbler, temporal patterns in detectability resulted in substantial differences in estimated trends under the removal mixtures compared to the analysis of raw counts. Overall, we found that the zero-inflated Poisson was the best distribution for our data, although the Poisson or negative binomial performed better for a few species. The similarity in estimated trends that we observed among counts and removal mixtures was probably a result of both experimental design and sampling effort. First, the study was originally designed to avoid confounding observer effects with habitats or time. Second, our time series is relatively long and our sample sizes within years are large.

Seasonal dimorphism in the horny bills of sparrows

Bill size is often viewed as a species-specific adaptation for feeding, but it sometimes varies between sexes, suggesting that sexual selection or intersexual competition may also be important. Hypotheses to explain sexual dimorphism in avian bill size include divergence in feeding niche or thermoregulatory demands, intrasexual selection based on increased competition among males, or female preference. Birds also show seasonal changes in bill size due to shifts in the balance between growth rate and wear, which may be due to diet or endogenous rhythms in growth. Insight into the function of dimorphism can be gained using the novel approach of digital x-ray imaging of museum skins to examine the degree to which the skeletal core or the rhamphotheca contribute to overall dimorphism. The rhamphotheca is ever-growing and ever-wearing, varying in size throughout life; whereas the skeletal core shows determinant growth. Because tidal marsh sparrows are more dimorphic in bill size than related taxa, we selected two marsh taxa to investigate dimorphism and seasonality in the size of the overall bill, the skeletal core, and the rhamphotheca. Bill size varied by sex and season, with males having larger bills than females, and bill size increasing from nonbreeding to breeding season more in males. Skeletal bill size varied with season, but not sex. The rhamphotheca varied primarily with sex; males had a larger rhamphotheca (corrected for skeletal bill size), which showed a greater seasonal increase than females. The rhamphotheca, rather than the skeletal bill, was responsible for sexual dimorphism in overall bill size, which was particularly well developed in the breeding season. The size of the rhamphotheca may be a condition-based character that is shaped by sexual selection. These results are consistent with the evidence that bill size is influenced by sexual selection as well as trophic ecology.

Incorporating results of avian toxicity tests into a model of annual reproductive success

ABSTRACT Modeling the effects of pesticide exposure on avian populations requires knowledge of how the pesticide changes survival and fecundity rates for the population. Although avian reproduction tests are the primary source of information on reproductive effects in the pesticide risk assessment process, current tests cannot provide a direct estimate of the effects of a pesticide on fecundity rates. We present a mathematical model that integrates information on specific types of effects from reproduction tests with information on avian life history parameters, the timing of pesticide applications, and the temporal pattern of pesticide exposure levels to estimate pesticide effects on annual reproductive success. The model demonstration follows nesting success of females in no-pesticide or pesticide-exposed populations through a breeding season to estimate the mean number of successful broods per female. We demonstrate the model by simulating populations of a songbird exposed to 1 of 2 hypothetical pesticides during a breeding season. Finally, we discuss several issues for improving the quantitative estimation of annual reproductive success.

Landscape and regional context differentially affect nest parasitism and nest predation for Wood Thrush in central Virginia, USA

ABSTRACT Many empirical studies have shown that forest-breeding songbirds, and Neotropical migrants in particular, suffer greater rates of nest predation and nest parasitism in smaller forest patches and in fragmented landscapes. To compare the performance of different metrics of spatial habitat configuration resulting from deforestation, we studied nest predation and nest parasitism rates at 200 Wood Thrush (Hylocichla mustelina) nests in eight forest fragments ranging from 82 to 9,171 ha in central Virginia, USA. We analyzed nest parasitism rates using logistic regression and we analyzed daily nest predation rates under a multistate competing risks design. For both analyses we compared the performance of 16 covariates, 11 of which related to the spatial configuration of habitat (e.g., patch size, distance to edge, percent core forest in proximity to nest) and 5 of which were unrelated to habitat (e.g., year, serial date, nest height). Distance to agriculture gained the greatest support in analyses of nest predation and suggested that elevated predation rates are manifest primarily within 50 m of edges; at 5, 10, and 20 m, respectively, the estimated predation rates were 87%, 76%, and 68%. In contrast, biogeographic region received the greatest support in analyses of nest parasitism, which also showed increasing rates of Brown-headed Cowbird (Molothrus ater) parasitism with percent agricultural land and road density within 500 m of a nest. Among regions, the greatest difference seemed to be a virtual absence of nest parasitism along the Blue Ridge in the absence of disturbance (agriculture or road incursion) whereas the other two biogeographic regions showed 20–50% rates of nest parasitism as background rates. Interactive models between spatial configuration metrics and region gained little support from nest predation analyses, but considerable support from the nest parasitism analyses, suggesting regional context plays a more important role in nest parasitism than in nest predation at these central Virginia sites.

Estimating Pesticide Effects on Fecundity Rates of Wild Birds Using Current Laboratory Reproduction Tests

ABSTRACT Regulatory agencies have used laboratory toxicity tests for decades to assess potential risks of pesticide use to wildlife, but questions remain about the ecological significance of test results. Population models may provide a valuable tool for projecting the consequences of pesticide use if information exists on the relationship between exposure and effects on survival and fecundity rates. We review issues of using avian reproduction test results for estimating changes in fecundity rates of wild birds. The avian reproduction test originated from studies focused on eggshell quality and embryotoxic effects of bioaccumulating, organochlorine pesticides. Current pesticides exhibit other potential reproductive effects that are not measured or that are poorly characterized. Because several experimental design features of the laboratory test may lead to overestimation or underestimation of the magnitude of risk of a particular pesticide to wild birds, determination of the magnitude of effects on fecundity cannot be based solely on the results of standardized laboratory tests. Quantifying the overall impact of pesticides on avian fecundity rates for use in population modeling will require additional information from modified laboratory tests that address specific questions, field monitoring or experimental field studies, and simulation models of avian productivity.

Hidden Markov models for estimating animal mortality from anthropogenic hazards.

Carcass searches are a common method for studying the risk of anthropogenic hazards to wildlife, including nontarget poisoning and collisions with anthropogenic structures. Typically, numbers of carcasses found must be corrected for scavenging rates and imperfect detection. Parameters for these processes (scavenging and detection) are often estimated using carcass distribution trials in which researchers place carcasses in the field at known times and locations. In this manuscript I develop a variety of estimators based on multi-event or hidden Markov models for use under different experimental conditions. I apply the estimators to two case studies of avian mortality, one from pesticide exposure and another at wind turbines. The proposed framework for mortality estimation points to a unified framework for estimation of scavenging rates and searcher efficiency in a single trial and also allows estimation based only on accidental kills, obviating the need for carcass distribution trials. Results of the case studies show wide variation in the performance of different estimators, but even wider confidence intervals around estimates of the numbers of animals killed, which are the direct result of small sample size in the carcass distribution trials employed. These results also highlight the importance of a well-formed hypothesis about the temporal nature of mortality at the focal hazard under study.

Impact of natural organic matter on particle behavior and phototoxicity of titanium dioxide nanoparticles

Due to their inherent phototoxicity and inevitable environmental release, titanium dioxide nanoparticles (nano-TiO2) are increasingly studied in the field of aquatic toxicology. One of the particular interests is the interactions between nano-TiO2 and natural organic matter (NOM). In this study, a series of experiments was conducted to study the impacts of Suwannee River natural organic matter (SRNOM) on phototoxicity and particle behaviors of nano-TiO2. For Daphnia magna, after the addition of 5mg/L SRNOM, LC50 value decreased significantly from 1.03 (0.89-1.20) mg/L to 0.26 (0.22-0.31) mg/L. For zebrafish larvae, phototoxic LC50 values were 39.9 (95% CI, 25.9-61.2) mg/L and 26.3 (95% CI, 18.3-37.8) mg/L, with or without the presence of 5mg/L SRNOM, respectively. There was no statistically significant change of these LC50 values. The impact of SRNOM on phototoxicity of nano-TiO2 was highly dependent on test species, with D. magna being the more sensitive species. The impact on particle behavior was both qualitatively and quantitatively examined. A global predictive model for particle behavior was developed with a three-way interaction of SRNOM, TiO2 concentration, and time and an additive effect of ionic strength. Based on power analyses, 96-h exposure in bioassays was recommended for nanoparticle-NOM interaction studies. The importance of reactive oxygen species (ROS) quenching of SRNOM was also systematically studied using a novel exposure system that isolates the effects of environmental factors. These experiments were conducted with minimal impacts of other important interaction mechanisms (NOM particle stabilization, NOM UV attenuation, and NOM photosensitization). This study highlighted both the particle stabilization and ROS quenching effects of NOM on nano-TiO2 in an aquatic system. There is an urgent need for representative test materials, together with key environmental factors, for future risk assessment and regulations of nanomaterials.