Assessing reproductive effects on fish populations: an evaluation of methods to predict the reproductive strategy of fishes.

Many environmental monitoring programs include an assessment of the health of fish populations using a sentinel species and include an indicator of reproductive potential. Knowledge of the reproductive strategy of the fish species is critical for data interpretation but is not always known. The reproductive strategy of a species can be determined from detailed histological analyses of ovaries throughout the reproductive cycle; however, these studies can be costly and can delay the implementation of a monitoring program. Three quick and cost-effective methods of predicting the reproductive strategy (annual single spawning or annual multiple spawning) are evaluated in this study using predicted probabilities from binary logistic regression models as a means of classifying the reproductive strategies of 18 different fish species in Atlantic Canada. The first method was based on the hypothesis that the variability in the ovary weight-body weight relationship in prespawning females is higher in multiple spawners. This method did not have a good classification rate due to some multiple spawners having low variability. The other two methods involved predictor variables representing the proportion of oocytes in different stages of development and predictor variables representing the distribution of oocyte sizes during the prespawning season for 111 fish (25 different samples for species). Predicted probabilities from these regression models could be used to correctly classify the reproductive strategies of all 25 samples (development stage model) and all but one sample (oocyte size distribution model). These models can be used to estimate the reproductive strategy of a species from a single sample of fish collected during the prespawning period to support species selection and data interpretation in environmental monitoring programs.

Non-indigenous predators threaten ecosystem engineers: Interactive effects of green crab and oyster size on American oyster mortality.

Non-indigenous green crabs (Carcinus maenas) are emerging as important predators of autogenic engineers like American oysters (Crassostrea virginica) throughout the eastern seaboard of Canada and the United States. To document the spreading distribution of green crabs, we carried out surveys in seven sites of Prince Edward Island during three fall seasons. To assess the potential impact of green crabs on oyster mortality in relation to predator and prey size, we conducted multiple predator-prey manipulations in the field and laboratory. The surveys confirmed an ongoing green crab spread into new productive oyster habitats while rapidly increasing in numbers in areas where crabs had established already. The experiments measured mortality rates on four sizes of oysters exposed to three sizes of crab, and lasted 3-5 days. The outcomes of experiments conducted in Vexar® bags, laboratory tanks and field cages were consistent and were heavily dependent on both crab size and oyster size: while little predation occurred on large oysters, large and medium green crabs preyed heavily on small sizes. Oysters reached a refuge within the 35-55 mm shell length range; below that range, oysters suffered high mortality due to green crab predation and thus require management measures to enhance their survival. These results are most directly applicable to aquaculture operations and restoration initiatives but have implications for oyster sustainability.

Testing against "normal" with environmental data.

Normal ranges are some fraction of a reference distribution deemed to represent an expected condition, typically 95%. They are frequently used as the basis for generic criteria for monitoring programs designed to test whether a sample is outside of "normal," as in reference-condition approach studies. Normal ranges are also the basis for criteria for more classic environmental effects monitoring programs designed to detect differences in mean responses between reference and exposure areas. Limits on normal ranges are estimated with error that varies depending largely on sample size. Direct comparison of a sample or a mean to estimated limits of a normal range will, with some frequency, lead to incorrect conclusions about whether a sample or a mean is inside or outside the normal range when the sample or the mean is near the limit. Those errors can have significant costs and risk implications. This article describes tests based on noncentral distributions that are appropriate for quantifying the likelihood that samples or means are outside a normal range. These noncentral tests reverse the burden of evidence (assuming that the sample or mean is at or outside normal), and thereby encourage proponents to collect more robust sample sizes that will demonstrate that the sample or mean is not at the limits or beyond the normal range. These noncentral equivalence and interval tests can be applied to uni- and multivariate responses, and to simple (e.g., upstream vs downstream) or more complex (e.g., before vs after, or upstream vs downstream) study designs. Statistical procedures for the various tests are illustrated with benthic invertebrate community data collected as part of the Regional Aquatics Monitoring Program (RAMP) in the vicinity of oil sands operations in northern Alberta, Canada. An Excel workbook with functions and calculations to carry out the various tests is provided in the online Supplemental Data. Integr Environ Assess Manag 2017;13:188-197. © 2016 SETAC.

Reproductive strategies and seasonal changes in the somatic indices of seven small-bodied fishes in Atlantic Canada in relation to study design for environmental effects monitoring.

Small-bodied fishes are more commonly being used in environmental effects monitoring (EEM) studies. There is a lack of understanding of the biological characteristics of many small-bodied species, which hinders study designs for monitoring studies. For example, 72% of fish population surveys in Canada's EEM program for pulp and paper mills that used small-bodied fishes were conducted outside of the reproductive period of the species. This resulted in an inadequate assessment of the EEM program's primary effect endpoint (reproduction) for these studies. The present study examined seasonal changes in liver size, gonad size, and condition in seven freshwater and estuarine small-bodied fishes in Atlantic Canada. These data were used to examine differences in reproductive strategies and patterns of energy storage among species. Female gonadal recrudescence in all seven species began primarily in the 2-month period in the spring before spawning. Male gonadal development was concurrent with females in five species; however, gonadal recrudescence began in the fall in male three-spined stickleback (Gasterosteus aculeatus) and slimy sculpin (Cottus cognatus). The spawning period for each species was estimated from the decline in relative ovary size after its seasonal maximum value in spring. The duration of the spawning period reflected the reproductive strategy (single vs multiple spawning) of the species. Optimal sampling periods to assess reproductive impacts in each species were determined based on seasonal changes in ovary size and were identified to be during the prespawning period when gonads are developing and variability in relative gonad size is at a minimum.

Quantifying natural variability as a method to detect environmental change: Definitions of the normal range for a single observation and the mean of m observations.

The normal range has been defined as the range that encloses 95% of reference values; in practice this range has been defined as the reference mean ± 2 standard deviations (SD). When sample sizes are small and reference data are not normally distributed, the mean ± 2 SDs do not enclose 95% of data values. Prediction intervals (PI) calculated using sample statistics are used in the present study to define the normal range for a single observation and the mean of m observations. The PIs provide confidence limits for the next randomly selected observation (or mean of m observations) from a population. The PIs are defined using normally distributed reference data; normality can typically be achieved with transformations of the data. Covariates can be used to explain some of the variability in the reference distribution, increasing the ability to detect change. When assumptions of normality are not met, alternative methods of defining the normal range are provided. The normal range can be used to quantify natural variability and assess change from the reference distribution. It can be used as an early warning indicator of change in environmental monitoring to identify the need for further investigation.

Negative consequences of using α = 0.05 for environmental monitoring decisions: a case study from a decade of Canada's Environmental Effects Monitoring Program.

Using the traditional α = 0.05 significance level for null hypothesis significance tests makes assumptions about relative costs of Type I vs relevant Type II errors and inflates their combined probabilities. We have examined the results of 1254 monitoring tests conducted under the Canadian Environmental Effects Monitoring (EEM) program from 1992 to 2003, focusing on how the choice of α affected the relative probabilities and implied costs of Type I and Type II errors. Using α = 0.05 resulted in implied relative costs of Type I vs Type II errors that were both inconsistent among monitoring end points and also inconsistent with the philosophy of the monitoring program. Using α = 0.05 also resulted in combinations of Type I and II error that were 15-17% larger than those for "optimal" α levels set to minimize Type I and II errors for each study, and 12% of all monitoring tests would have reached opposite conclusions had they used these optimal α levels for decision-making. Thus, if the Canadian EEM program used study-specific optimal α levels, they would reduce the incidence of relevant errors and eliminate inconsistent implied relative costs of these errors. Environmental research and monitoring programs using α = 0.05 as a decision-making threshold should re-evaluate the usefulness of this "one-size-fits-all" approach.

Effects of pulp and paper mill effluent on fish: a temporal assessment of fish health across sampling cycles.

The Canadian environmental effects monitoring (EEM) program is a regulated, cyclical, industry-funded program designed to determine whether receiving water impacts exist when a mill is in compliance with its discharge limits. The results from three cycles of the fish monitoring program (1992 to 2004) are available from over 200 surveys of fish compared between sites located upstream and downstream of pulp and paper mill effluent outfalls. Previous meta-analyses have shown a national average response pattern across cycles characterized by an increase in endpoints measuring energy storage and growth and a decrease in a reproductive endpoint, consistent with a response of nutrient enrichment in combination with some form of metabolic disruption. Although the national average pattern of effects was temporally consistent, there was some variability in the magnitude of effects among cycles. Questions were raised as to whether the intercycle variability was due to changes in effluent quality or due, at least in part, to other factors. The present study compares responses over the first three cycles, and shows that the choice of sentinel species is likely to be a major contributing factor to the variability in observed effects. Subset analyses using studies from mills that used the same sentinel species across cycles reveal fairly uniform responses and little evidence of significant improvements in overall fish health from cycles one to three. However, a meta-analysis using 1991 data collected from 10 mills before the implementation of the EEM program and data from the same mills collected during cycles one to three of the program reveal significantly reduced effects on relative liver weight and potential improvements in other endpoints.

Evaluation of antimicrobial resistance phenotypes for predicting multidrug-resistant Salmonella recovered from retail meats and humans in the United States.

Although multidrug-resistant (MDR) non-Typhi Salmonella (NTS) strains are a concern in food production, determining resistance to multiple antimicrobial agents at slaughter or processing may be impractical. Single antimicrobial resistance results for predicting multidrug resistance are desirable. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were used to determine each antimicrobial agent's ability to predict MDR phenotypes of human health significance: ACSSuT (resistance to at least ampicillin, chloramphenicol, streptomycin, sulfamethoxazole, tetracycline) in NTS isolates, and MDR-AmpC-SN (resistance to ACSSuT, additional resistance to amoxicillin-clavulanate and to ceftiofur, and decreased susceptibility [MIC >= 2 microg/ml] to ceftriaxone) in NTS serotype Newport. The U.S. National Antimicrobial Resistance Monitoring System determined MICs to 15 or more antimicrobial agents for 9,955 NTS isolates from humans from 1999 to 2004 and 689 NTS isolates from retail meat from 2002 to 2004. A total of 847 (8.5%) human and 26 (3.8%) retail NTS isolates were ACSSuT; 995 (10.0%) human and 16 (2.3%) retail isolates were serotype Newport. Among Salmonella Newport, 204 (20.5%) human and 9 (56.3%) retail isolates were MDR-AmpC-SN. Chloramphenicol resistance provided the highest PPVs for ACSSuT among human (90.5%; 95% confidence interval, 88.4 to 92.3) and retail NTS isolates (96.3%; 95% confidence interval, 81.0 to 99.9). Resistance to ceftiofur and to amoxicillin-clavulanate and decreased susceptibility to ceftriaxone provided the highest PPVs (97.1, 98.1, and 98.6%, respectively) for MDR-AmpC-SN from humans. High PPVs for these agents applied to retail meat MDR-AmpC-SN, but isolate numbers were lower. Variations in MIC results may complicate ceftriaxone's predictive utility. Selecting specific antimicrobial resistance offers practical alternatives for predicting MDR phenotypes. Chloramphenicol resistance works best for ACSSuT-NTS, and resistance to ceftiofur, amoxicillin-clavulanate, or chloramphenicol works best for MDR-AmpC-SN.

Dealing with heterogeneous regression slopes in analysis of covariance: new methodology applied to environmental effects monitoring fish survey data.

Analysis of covariance (ANCOVA) is a powerful statistical method which incorporates one or more covariates into the analysis to reduce error associated with measurement. ANCOVA (modeling response as a function of fish size) is frequently used to analyze environmental effects monitoring (EEM) fish survey data. In approximately 12% of fish survey data sets taken from cycles 1 to 3 of Environment Canada's EEM database for pulp and paper mills, the standard assumption of parallel regression slopes is not met. For the first three cycles of the EEM program, these data sets were classified as indicating a mill effect, but for the most part were excluded from subsequent analyses aimed at quantifying the effect. We present two different methods for initially dealing with data sets that exhibit heterogeneous slopes so that they can be analyzed using the parallel slope model. The first method identifies data sets where heterogeneous slopes are forced by a few high-influence observations. The second approach identifies data sets where a model with heterogeneous slopes is statistically, but not practically, significant: with a high coefficient of determination for the parallel slope model. These new methodologies are applied to EEM pulp and paper data sets and about 55% of cases with heterogeneous slopes can be described by a parallel slope model. We also discuss a third method that can be used to describe mill effects when regression slopes remain heterogeneous even after applying the above two methods, enabling comparison with a critical effect size. These new methodologies could benefit the EEM program by enabling more data sets to be incorporated into meta-analyses and be used to make more equitable mill monitoring decisions in the future.

Increase in nalidixic acid resistance among non-Typhi Salmonella enterica isolates in the United States from 1996 to 2003.

Fluoroquinolones commonly are used to treat adult Salmonella infections. Fluoroquinolone treatment has failed for persons infected with nalidixic acid-resistant Salmonella. From 1996 to 2003, state public health laboratories forwarded 12,252 non-Typhi Salmonella enterica isolates to the Centers for Disease Control and Prevention for antimicrobial susceptibility testing; 203 (1.6%) of the isolates were nalidixic acid resistant, and 14 (7%) of those were ciprofloxacin resistant. Resistance to nalidixic acid significantly increased from 0.4% in 1996 to 2.3% in 2003. All ciprofloxacin-resistant isolates had at least one point mutation in the quinolone resistance determining region (QRDR) of gyrA and did not harbor qnr or have point mutations in the QRDR of gyrB, parC, or parE. Continued surveillance of antimicrobial resistance among non-Typhi S. enterica isolates is needed to mitigate the increasing prevalence of nalidixic acid resistance.

Human Salmonella and concurrent decreased susceptibility to quinolones and extended-spectrum cephalosporins.

The National Antimicrobial Resistance Monitoring System monitors susceptibility among Enterobacteriaceae in humans in the United States. We studied isolates exhibiting decreased susceptibility to quinolones (nalidixic acid MIC >32 microg/mL or ciprofloxacin MIC > or =0.12 microg/mL) and extended-spectrum cephalosporins (ceftiofur or ceftriaxone MIC > or =2 microg/mL) during 1996-2004. Of non-Typhi Salmonella, 0.19% (27/14,043) met these criteria: 11 Senftenberg; 6 Typhimurium; 3 Newport; 2 Enteridis; and 1 each Agona, Haifa, Mbandaka, Saintpaul, and Uganda. Twenty-six isolates had gyrA mutations (11 at codon 83 only, 3 at codon 87 only, 12 at both). All Senftenberg isolates had parC mutations (S801 and T57S); 6 others had the T57S mutation. The Mbandaka isolate contained qnrB2. Eight isolates contained bla(CMY-2); 1 Senftenberg contained bla(CMY-23). One Senftenberg and 1 Typhimurium isolate contained bla(SHV-12); the Mbandaka isolate contained bla(SHV-30). Nine Senftenberg isolates contained bla(OXA-1) contained bla(OXA-9). Further studies should address patient outcomes, risk factors, and resistance dissemination prevention strategies.

Enterococcus caccae sp. nov., isolated from human stools.

The National Antimicrobial Resistance Monitoring System Laboratory at the Centers for Disease Control and Prevention (CDC) isolated two enterococcus-like strains that were referred to the CDC Streptococcus Laboratory for further identification. The isolates were recovered from human stool samples collected on different occasions from the same individual in Portland (OR, USA) in July 2000. Conventional physiological tests distinguished these strains from all known species of enterococci. Analyses of whole-cell-protein electrophoretic profiles showed the same unique profile for the two isolates, being most similar those of Enterococcus moraviensis and Enterococcus haemoperoxidus albeit not close enough to allow conclusive inclusion in any enterococcal species. Both isolates gave positive results in tests using the AccuProbe Enterococcus genetic probe, and Lancefield extracts reacted with CDC group D antiserum. Comparative 16S rRNA gene sequencing studies also revealed that these strains were closely related to the species E. moraviensis (99.6 % identity). The results of DNA-DNA relatedness experiments confirmed that these strains represented a single novel taxon. The highest level of DNA-DNA relatedness found between the novel taxon and any of the currently recognized species of Enterococcus was 32 %, for both E. moraviensis and E. haemoperoxidus. On the basis of this evidence, it is proposed that these stool isolates constitute a novel species, for which the name Enterococcus caccae sp. nov. is proposed. The type strain is 2215-02(T) (=SS-1777(T)=ATCC BAA-1240(T)=CCUG 51564(T)).

Plasmid-mediated quinolone resistance in non-Typhi serotypes of Salmonella enterica.

BACKGROUND: Serious infections with Salmonella species are often treated with fluoroquinolones or extended-spectrum beta-lactams. Increasingly recognized in Enterobacteriaceae, plasmid-mediated quinolone resistance is encoded by qnr genes. Here, we report the presence of qnr variants in human isolates of non-Typhi serotypes of Salmonella enterica (hereafter referred to as non-Typhi Salmonella) from the United States National Antimicrobial Resistance Monitoring System for Enteric Bacteria. METHODS: All non-Typhi Salmonella specimens from the United States National Antimicrobial Resistance Monitoring System for Enteric Bacteria collected from 1996 to 2003 with ciprofloxacin minimum inhibitory concentrations > or = 0.06 microg/mL (233 specimens) and a subset with minimum inhibitory concentrations < or = 0.03 microg/mL (102 specimens) were screened for all known qnr genes (A, B, and S) by polymerase chain reaction. For isolates with positive results, qnr and quinolone resistance-determining region sequences were determined. Plasmids containing qnr genes were characterized by conjugation or transformation. RESULTS: Conjugative plasmids harboring qnrB variants were detected in 7 Salmonella enterica serotype Berta isolates and 1 Salmonella enterica serotype Mbandaka isolate. The S. Mbandaka plasmid also had an extended-spectrum beta -lactamase. Variants of qnrS on nonconjugative plasmids were detected in isolates of Salmonella enterica serotype Anatum and Salmonella enterica serotype Bovismorbificans. CONCLUSIONS: Plasmid-mediated quinolone resistance appears to be widely distributed, though it is still uncommon in non-Typhi Salmonella isolates from the United States, including strains that are quinolone susceptible by the criteria of the Clinical and Laboratory Standards Institute (formerly the National Committee for Clinical Laboratory Standards). The presence of this gene in non-Typhi Salmonella that causes infection in humans suggests potential for spread through the food supply, which is a public health concern.

The clonal spread of multidrug-resistant non-typhi Salmonella serotypes.

Non-typhoid Salmonella are one of the most important organisms causing food-borne diseases worldwide. There have been significant increases in developed countries in recent years in the occurrence of resistance, in particular multidrug resistance phenotypes, in non-typhoid Salmonella spp. Such increases have been observed in many countries, not only within the European community but also the Americas and Southeast Asia. Of particular concern is the increasing detection of Salmonella isolates displaying resistance to key antimicrobials, notably fluoroquinolones and third-generation cephalosporins. An important factor associated with this increase in multidrug resistance among particular Salmonella spp. is the national and international spread of certain clonal genotypes, the most recent being the global epidemic spread of multidrug-resistant S. Typhimurium DT104, since the early 1990s. In this review, we describe examples where particular antimicrobial-resistant Salmonella serotypes emerged, persisted for periods of time, and then quickly decreased in prevalence.

Salmonella resistant to extended-spectrum cephalosporins: prevalence and epidemiology.

Salmonella resistant to extended-spectrum cephalosporins (ESCs) have emerged worldwide since 1988. By 2004, 43 countries had reported this public health problem. Resistance was mediated by classical extended-spectrum beta-lactamases, plasmid-mediated cephalosporinases, and recently a class A carbapenemase. Of these, CMY-2 is the most widely disseminated enzyme. Salmonella enterica serotype Typhimurium and S. enterica serotype Enteritidis are the most common serovars associated with ESC resistance in human infections. Many outbreaks in humans have been reported, most often among children and neonates. ESC-resistant Salmonella is frequently recovered from animals and food, with poultry as primary food source, suggesting that humans are often infected by these routes.

Interpretation of pulsed-field gel electrophoresis patterns in foodborne disease investigations and surveillance.

Since the establishment of the well-known Tenover criteria in 1995 (Tenover et al., 1995), relatively few papers have been published about the interpretation of subtyping data generated by pulsed-field gel electrophoresis (PFGE). This paper describes the approach that has been used in the PulseNet network during the past 10 years. PFGE data must always be interpreted in the proper epidemiological context and PFGE data can not alone prove an epidemiological connection. The Tenover criteria are not generally applicable to the interpretation of PFGE subtyping data of foodborne pathogens. The reproducibility of the method with a particular organism, the quality of the PFGE gel, the variability of the organism being subtyped, and the prevalence of the pattern in question must always be considered. Only isolates displaying indistinguishable patterns should be included in the detection of clusters of infections or the initial case definition in a point-source outbreak. More variability (patterns differing from each other in two to three band positions) may be accepted if the outbreak has been going on for some time or if person-person spread is a prominent feature. If epidemiological information is sufficiently strong, isolates with markedly different PFGE patterns may be included in an outbreak.

Standardization of pulsed-field gel electrophoresis protocols for the subtyping of Escherichia coli O157:H7, Salmonella, and Shigella for PulseNet.

Standardized rapid pulsed-field gel electrophoresis (PFGE) protocols for the subtyping of Escherichia coli O157:H7, Salmonella serotypes, and Shigella species are described. These protocols are used by laboratories in PulseNet, a network of state and local health departments, and other public health laboratories that perform real-time PFGE subtyping of these bacterial foodborne pathogens for surveillance and outbreak investigations. Development and standardization of these protocols consisted of a thorough optimization of reagents and reaction conditions to ensure that the protocols yielded consistent results and high-quality PFGE pattern data in all the PulseNet participating laboratories. These rapid PFGE protocols are based on the original 3-4-day standardized procedure developed at Centers for Disease Control and Prevention that was validated in 1996 and 1997 by eight independent laboratories. By using these rapid standardized PFGE protocols, PulseNet laboratories are able to subtype foodborne pathogens in approximately 24 h, allowing for the early detection of foodborne disease case clusters and often aiding in the identification of the source responsible for the infections.