Mercury exposure of tidal marsh songbirds in the northeastern United States and its association with nest survival

The biogeochemistry of tidal marsh sediments facilitates the transformation of mercury (Hg) into the biologically available form methylmercury (MeHg), resulting in elevated Hg exposures to tidal marsh wildlife. Saltmarsh and Acadian Nelson's sparrows (Ammospiza caudacutua and A. nelsoni subvirgatus, respectively) exclusively inhabit tidal marshes, potentially experiencing elevated risk to Hg exposure, and have experienced range-wide population declines. To characterize spatial and temporal variation of Hg exposure in these species, we sampled total mercury (THg) in blood collected from 9 populations spanning 560 km of coastline, including individuals resampled within and among years. Using concurrent nesting studies, we tested whether THg was correlated with nest survival probabilities, an index of fecundity. Blood THg ranged from 0.074-3.373 µg/g ww across 170 samples from 127 individuals. We detected high spatial variability in Hg exposure, observing differences of more than 45-fold across all individuals and 8-fold in mean blood THg among all study plots, including 4-fold between study plots within 4 km. Intraindividual changes in blood Hg exposure did not vary systematically in time but were considerable, varying by up to 2-fold within and among years. Controlling for both species differences and maximum water level, the dominant driver of fecundity in this system, nest survival probability decreased by 10% across the full range of female blood THg concentrations observed. We conclude that Hg has the potential to impair songbird reproduction, potentially exacerbating known climate-change driven population declines from sea-level rise in saltmarsh and Acadian Nelson's sparrows.

DEVELOPING INTEGRAL PROJECTION MODELS FOR ECOTOXICOLOGY

In many ecosystems, especially aquatic ecosystems, size plays a critical role in the factors that determine an individual's ability to survive and reproduce. In aquatic ecotoxicology, size informs both realized and potential acute and chronic effects of chemical exposure. This paper demonstrates how chemical and nonchemical effects on growth, survival, and reproduction can be linked to population-level dynamics using size-structured integral projection models (IPM). The modeling approach was developed with the goals and constraints of ecological risk assessors in mind, who are tasked with estimating the effects of chemical exposures to wildlife populations in a data-limited environment. The included case study is a collection of daily time-step IPMs parameterized for the life history and annual cycle of fathead minnows (Pimephales promelas), which motivated the development of modeling techniques for seasonal, iteroparous reproduction, density dependent growth effects, and size-dependent over-winter survival. The effects of a time-variable annual chemical exposure were interpreted using a toxicokinetic-toxicodynamic model for acute survival and sub-lethal growth effects model for chronic effects and incorporated into the IPMs. This paper presents a first application of integral projection models to ecotoxicology. Our research demonstrates that size-structured IPMs provide a promising, flexible, framework for synthesizing ecotoxicologically relevant data and theory to explore the effects of chemical and nonchemical stressors and the resulting impacts on exposed populations.

Endogenous Lifecycle Models for Chemical Risk Assessment

Despite over 50 years of research on the use of population models in chemical risk assessment, their practical utility has remained elusive. A novel application and interpretation of ecotoxicological models, Endogenous Lifecycle Models (ELM), is proposed that offers some of the benefits sought from population models, at much lower cost of design, parametrization, and verification. ELMs capture the endogenous lifecycle processes of growth, development, survival, and reproduction and integrate these to estimate and predict expected fitness. Two measures of fitness are proposed as natural model predictions in the context of chemical risk assessment, lifetime reproductive success, and the expected annual propagation of genetic descendants, including self (intrinsic fitness). Six characteristics of the ELM approach are reviewed and illustrated with two ELM examples, the first for a general passerine lifecycle and the second for bald eagle (Haliaeetus leucocephalus). Throughout, the focus is on development of robust qualitative model predictions that depend as little as possible on specific parameter values. Thus, ELMs sacrifice precision to optimize generality in understanding the effects of chemicals across the diversity of avian lifecycles. Notably, the ELM approach integrates naturally with the adverse outcome pathway framework; this integration can be employed as a midtier risk assessment tool when lower tier analyses suggest potential risk.

Foraging Ecology Differentiates Life Stages and Mercury Exposure in Common Terns (Sterna hirundo)

Some populations of common terns (Sterna hirundo) breeding at inland lakes in North America are declining, including the Laurentian Great Lakes. Terns nesting at inland colonies forage in freshwater during the breeding season and primarily in coastal marine environments during the nonbreeding season. As piscivores, they are susceptible to dietary Hg exposure. To characterize patterns of Hg exposure in this population, we 1) quantified within and among season differences in total mercury (THg) concentrations (μg/g) in blood and feathers at 2 Lake Superior breeding colonies, and 2) documented spatial and temporal variation in exposure by studying adult foraging ecology using geospatial tracking devices and stable isotopes. We used general linear models to assess the relationship between isotopic composition and THg concentrations in bird tissues relative to sex, age, colony location, and season. The THg concentrations were lowest in winter-grown feathers (geometric mean [95% confidence limits]): 1.32 (1.09-1.59) μg/g dw (n = 60), higher at the more industrially influenced colony (chick feathers: 4.95 [4.62-5.37] μg/g dw [n = 20]), and increased with a riverine-based diet. During the breeding season, Hg exposure varied along a gradient from lake to river, with adult females having lower blood THg concentrations than males (females: 0.83 [0.67-1.03]) μg/g ww (n = 7); males: 1.15 (0.92-1.45) μg/g ww (n = 5). Stable isotope values suggested adults obtained 42 ± 12% (n = 12) of their diet from the river during incubation, which was validated with tracking data. During chick-rearing, chicks obtained 68 ± 19% (n = 44) of their diet from the river. Our results indicate colony location, foraging behavior, and season influenced Hg exposure for these Lake Superior colonies and underscores the importance of local contamination with respect to exposure. Integr Environ Assess Manag 2021;17:398-410. © 2020 SETAC.

Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes' Areas of Concern

During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.

Demographic analysis demonstrates systematic but independent spatial variation in abiotic and biotic stressors across 59 percent of a global species range

The balance of abiotic and biotic stressors experienced by a species likely varies across its range, resulting in spatially heterogeneous limitations on the species' demographic rates. Support for spatial variation in stressors (often latitudinal gradients) has been found in many species, usually with physiological or correlative occupancy data, but it has rarely been estimated directly with demographic data. We collected demographic data from 23 sites spanning the majority of the Saltmarsh Sparrow (Ammodramus caudacutus) breeding range. Using data from 837 nests, we quantified the abiotic and biotic variables most important to nest survival, which is the dominant driver of both fecundity and population growth rate in this species. We separately estimated daily nest failure probability due to nest depredation (biotic stressor) and nest flooding (abiotic stressor), which collectively account for almost all nest failure in the species. Nest depredation decreased with latitude, whereas nest flooding was not related to latitude. Instead, nest flooding was best predicted by a combination of maximum high tide, extremity of rare flooding events, and date. For a single vital rate, we observed predictable variation in competing biotic and abiotic stressors across this species range. We observed that biotic and abiotic stressors were geographically independent, both on a large spatial scale and locally. Our results suggest that stressors on the fecundity of Saltmarsh Sparrow vary systematically across its range, but independently. The observed patterns of biotic and abiotic stress provide information for efforts to conserve the Saltmarsh Sparrow, which is considered threatened. Further, understanding the effects that different stressors, and their interactions, have on demographic rates is necessary to unravel the processes that govern species distributions and to effectively conserve biodiversity in the face of global change.

Factors that influence vital rates of Seaside and Saltmarsh sparrows in coastal New Jersey, USA

As saltmarsh habitat continues to disappear, understanding the factors that influence saltmarsh breeding bird population dynamics is an important step for the conservation of these declining species. Using five years (2011 - 2015) of demographic data, we evaluated and compared Seaside (Ammodramus maritimus) and Saltmarsh (A. caudacutus) sparrow apparent adult survival and nest survival at the Edwin B. Forsythe National Wildlife Refuge, New Jersey, USA. We determined the effect of site management history (unditched vs. ditched marsh) on adult and nest survival to aid in prioritizing future management or restoration actions. Seaside Sparrow apparent adult survival (61.6%, 95% CI: 52.5 - 70.0%) averaged >1.5 times greater than Saltmarsh Sparrow apparent adult survival (39.9%, 95% CI: 34.0 - 46.2%). Nest survival and predation and flooding rates did not differ between species, and predation was the primary cause of failure for both species. Apparent adult survival and nest survival did not differ between unditched and ditched marshes for either species, indicating that marsh ditching history may not affect breeding habitat quality for these species. With predation as the primary cause of nest failure for both species in New Jersey, we suggest that future research should focus on identification of predator communities in salt marshes and the potential for implementing predator-control programs to limit population declines.

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.

Exposure and effects of perfluoroalkyl substances in tree swallows nesting in Minnesota and Wisconsin, USA

The exposure and effects of perfluoroalkyl substances (PFASs) were studied at eight locations in Minnesota and Wisconsin between 2007 and 2011 using tree swallows (Tachycineta bicolor). Concentrations of PFASs were quantified as were reproductive success end points. The sample egg method was used wherein an egg sample is collected, and the hatching success of the remaining eggs in the nest is assessed. The association between PFAS exposure and reproductive success was assessed by site comparisons, logistic regression analysis, and multistate modeling, a technique not previously used in this context. There was a negative association between concentrations of perfluorooctane sulfonate (PFOS) in eggs and hatching success. The concentration at which effects became evident (150-200 ng/g wet weight) was far lower than effect levels found in laboratory feeding trials or egg-injection studies of other avian species. This discrepancy was likely because behavioral effects and other extrinsic factors are not accounted for in these laboratory studies and the possibility that tree swallows are unusually sensitive to PFASs. The results from multistate modeling and simple logistic regression analyses were nearly identical. Multistate modeling provides a better method to examine possible effects of additional covariates and assessment of models using Akaike information criteria analyses. There was a credible association between PFOS concentrations in plasma and eggs, so extrapolation between these two commonly sampled tissues can be performed.

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.

Quantifying the effects of pesticide exposure on annual reproductive success of birds

The Markov chain nest productivity model (MCnest) was developed for quantifying the effects of specific pesticide-use scenarios on the annual reproductive success of simulated populations of birds. Each nesting attempt is divided into a series of discrete phases (e.g., egg laying, incubation, nestling rearing), and results from avian toxicity tests are used to represent the types of effects possible in the field during each breeding phase. The expected exposure dose each day throughout the breeding season can be compared to the toxicity thresholds assigned to each breeding phase to determine whether the nest attempt is at risk. The primary output of the model is an estimate of the number of successful nest attempts per female per year, which is multiplied by the number of fledglings per successful nest to estimate the number of fledglings per female per breeding season (i.e., annual reproductive success). In this article, we present a series of MCnest simulations to demonstrate the extent to which the magnitude of change in annual reproductive success can be affected by considering life history attributes and the timing of pesticide applications relative to a species' typical breeding phenology. For a given pesticide-use scenario, MCnest can identify which species are at greatest risk. By allowing multiple species to be run under a single scenario, it can also help to identify the life-history traits that contribute to a species' vulnerability to a given pesticide-use scenario. It also can determine which application dates have the greatest impact and demonstrate the extent to which pesticide characteristics (e.g., residue half-life, mode of action) affect productivity. MCnest goes beyond the current qualitative screening-level assessments of risks to avian reproduction to provide an approach for quantifying the reduction in annual reproductive success by integrating species life history and timing of pesticide exposures, despite limitations in existing information on species life history and toxicity responses from existing laboratory tests.

Selecting surrogate endpoints for estimating pesticide effects on avian reproductive success

A Markov chain nest productivity model (MCnest) has been developed for projecting the effects of a specific pesticide-use scenario on the annual reproductive success of avian species of concern. A critical element in MCnest is the use of surrogate endpoints, defined as measured endpoints from avian toxicity tests that represent specific types of effects possible in field populations at specific phases of a nesting attempt. In this article, we discuss the attributes of surrogate endpoints and provide guidance for selecting surrogates from existing avian laboratory tests as well as other possible sources. We also discuss some of the assumptions and uncertainties related to using surrogate endpoints to represent field effects. The process of explicitly considering how toxicity test results can be used to assess effects in the field helps identify uncertainties and data gaps that could be targeted in higher-tier risk assessments.

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.

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.

Markov chain estimation of avian seasonal fecundity

Avian seasonal fecundity is of interest from evolutionary, ecological, and conservation perspectives. However, direct estimation of seasonal fecundity is difficult, especially with multi-brooded birds, and models representing the renesting and quitting processes are usually required. To explore the consequences of modeling decisions on inference about avian seasonal fecundity, we generalize previous Markov chain (MC) models of avian nest success to formulate two different MC models of avian seasonal fecundity that represent two different ways to model renesting decisions and breeding cessation. We parameterize both Markov chains (regular and absorbing) for two species (Eastern Meadowlark, Sturnella magna, and Dickcissel, Spiza americana) and compare the results using mean-square error of the estimated number of successful broods per breeding female. We also provide formulae for estimating the expected variation in female breeding success. The absorbing MC performed better for both species, although the regular MC performed almost as well when the duration of the breeding season was estimated by taking the 95th percentile of a negative binomial distribution fit to the observed durations among all females. In their simplest form the models contain very few parameters (four or five) and should also prove useful as a foundation for more complex models of avian seasonal fecundity and demography.

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

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.