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    The present study was carried out in six fjords within New Zealand’s Fiordland system, specifically Breaksea Sound, Chalky Inlet, Doubtful Sound, Dusky Sound, Long Sound, and Wet Jacket Arm, as described in Tobias-Hünefeldt et al.15. Analyses were divided into three categories: (1) a multi-fjord analysis comprising five of the tested fjords (excluding Long Sound), (2) a high-resolution study along Long Sound’s horizontal axis, and (3) a depth profile of Long Sound’s deepest location (at 421 m). These categories were established to identify trends across multiple fjords, and then test the trends using a fjord analysed at a higher resolution. Total community composition (via 16S and 18S rRNA gene sequencing) and metabolic potential did not significantly covary across the five studied fjords (Mantel, r  More

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    The effect of estuarine system on the meiofauna and nematodes in the East Siberian Sea

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    Impact of feed glyphosate residues on broiler breeder egg production and egg hatchability

    This is an observational study with no intervention on flock and hatchery practices. None of the birds or eggs were exposed to experimental procedures. The study was based mainly on existing data provided by the hatchery company (DanHatch Denmark A/S) from five broiler breeder flocks in Denmark during the period from November 2018 to January 2019 when the breeders were 46 to 62 weeks of age, see details in Table 1. In addition, feed samples from the flock locations and eggs from grocery stores were acquired.Table 1 Flocks and production periods.Full size tableThe average age of breeders was 48–59 weeks (SD from 0.5 to 2.2) ranging from 46–50 weeks to 57–62 weeks (Table 1; Supplementary Fig. S1 online) with observation period ranging from 1.6 to 7.6 weeks in the five flocks. Average laying percent over observation days was 65% (SD = 5.4%) and average hatchability over deliveries was 79% (SD = 5.8%).Feed samplesTwenty-six feed samples were collected for analysis of glyphosate content, 3 to 10 feed samples per flock. The glyphosate concentration related to a given sampling date was assumed representative for the flock from this day and until next sampling. Average duration of the preceding samples were used as duration for the last sampling date within each flock. Glyphosate (N‐(phosphonomethyl) glycine) and the glyphosate degradation product, aminomethylphosphonic acid (AMPA) in feed samples were analysed by the method described by Nørskov et al.4.Production dataData on egg production and hatchability from periods following each feed sampling was obtained from the hatchery company. Daily information was available on laying percent (100% * number of eggs/number of breeders), breeder age (days) and egg weight. For the hatchability, this was calculated as the proportion of eggs placed in incubators from which a viable chicken hatched (but presented as a percentage, i.e. multiplied by 100%). Daily egg weight had been calculated as the average from approx. 30 randomly sampled eggs.Glyphosate concentration of the feed consumed by the breeders during the 10 days prior to laying was the explanatory variable of main interest. The weighted average of glyphosate concentrations across the 10 days of development from follicle to ovulation of egg was used with number of days each glyphosate sample is representative during these 10 days as weights. For hatchability, glyphosate concentrations were aggregated at the level of delivery by weighted averaging using number of hatch eggs as weights.Eggs from grocery storesNo eggs were obtained from the five flocks, however we acquired eight cartons of conventional as well as eight cartons of organic eggs from eight different grocery stores. Three eggs from each carton were selected and egg yolk were analysed for glyphosate by the microLC-MS/MS method as described by Nørskov et al.4 adjusted to the egg yolk matrix.Statistical analysisLaying percent and hatchability were analysed by linear mixed effects models, including a random effect of flock and a first order autoregressive correlation structure to account for the repeated measurements from each flock. Following two covariates were considered for both outcomes: average egg weight (g) and breeder age (decimal weeks). However, since egg weight and breeder age are highly correlated (Pearson’s correlation coefficient ranging from 0.73 to 0.95 in the five flocks; Supplementary Fig. S1 online), only breeder age was included in the models. An important reason for this choice being that average egg weight was missing for 24% and 43% of the days from flock 4 and 5, respectively. In the age range used for this study, laying percent decrease with breeder age (Supplementary Fig. S1 online) as substantiated by a correlation coefficient between − 0.38 and − 0.87. Hatchability also decrease with breeder age (Supplementary Fig. S1 online).In addition, storage time on farm until delivery (1 to 5 days) and storage time at hatchery until incubation starts (1 to 11 days) were included as covariates for hatchability. The incubation start date was determined as date of hatching minus 21 days. For hatchability, covariates obtained from flock production data were aggregated at the level of delivery by weighted averaging; using daily number of eggs as weights for the calculation of average egg weight, number of hatch eggs as weights for average storage time on farm, and current number of breeders as weights for average breeder age. Weighted average storage time on farm until delivery varied from 1.0 to 4.0 and was on average 2.1 days. For storage time at hatchery, deliveries had been split on one to four incubator start dates. Therefore, weighted average of storage days was calculated using number of delivered eggs as weights. Weighted average storage time at hatchery before incubation starts varied from 1.2 to 8.0 days and was on average 4.8 days.Final models were fitted with restricted maximum likelihood estimation using the lme function from the nlme package v. 3.1-152 in R version 4.0.45 and with a significance level of 0.05. Fixed effects were tested by χ2 likelihood ratio tests after maximum likelihood estimation. Model checking was carried out by examination of qq-plots for normality and scatter plots of residuals versus predicted values to look for uncovered trends and variance heterogeneity. More