Interactive effects of pesticide exposure and habitat structure on behavior and predation of a marine larval fish

Coastal development has generated multiple stressors in marine and estuarine ecosystems, including habitat degradation and pollutant exposure, but the effects of these stressors on the ecology of fishes remain poorly understood. We studied the separate and combined effects of an acute 4 h sublethal exposure of the pyrethroid pesticide esfenvalerate and structural habitat complexity on behavior and predation risk of larval topsmelt (Atherinops affinis). Larvae were exposed to four nominal esfenvalerate concentrations (control, 0.12, 0.59, 1.18 μg/L), before placement into 12 L mesocosms with a three-spine stickleback (Gasterosteus aculeatus) predator. Five treatments of artificial eelgrass included a (1) uniform and (2) patchy distribution of eelgrass at a low density (500 shoots per m(2)), a (3) uniform and (4) patchy distribution of eelgrass at a high density (1,000 shoots per m(2)), and (5) the absence of eelgrass. The capture success of predators and aggregative behavior of prey were observed in each mesocosm for 10 min of each trial, and mortality of prey was recorded after 60 min. Exposure to esfenvalerate increased the proportion of larvae with swimming abnormalities. Surprisingly, prey mortality did not increase linearly with pesticide exposure but increased with habitat structure (density of eelgrass), which may have been a consequence of compensating predator behavior. The degree of prey aggregation decreased with both habitat structure and pesticide exposure, suggesting that anti-predator behaviors by prey may have been hampered by the interactive effects of both of these factors

Interactive effects of pesticide exposure and habitat structure on behavior and predation of a marine larval fish.

Coastal development has generated multiple stressors in marine and estuarine ecosystems, including habitat degradation and pollutant exposure, but the effects of these stressors on the ecology of fishes remain poorly understood. We studied the separate and combined effects of an acute 4 h sublethal exposure of the pyrethroid pesticide esfenvalerate and structural habitat complexity on behavior and predation risk of larval topsmelt (Atherinops affinis). Larvae were exposed to four nominal esfenvalerate concentrations (control, 0.12, 0.59, 1.18 μg/L), before placement into 12 L mesocosms with a three-spine stickleback (Gasterosteus aculeatus) predator. Five treatments of artificial eelgrass included a (1) uniform and (2) patchy distribution of eelgrass at a low density (500 shoots per m(2)), a (3) uniform and (4) patchy distribution of eelgrass at a high density (1,000 shoots per m(2)), and (5) the absence of eelgrass. The capture success of predators and aggregative behavior of prey were observed in each mesocosm for 10 min of each trial, and mortality of prey was recorded after 60 min. Exposure to esfenvalerate increased the proportion of larvae with swimming abnormalities. Surprisingly, prey mortality did not increase linearly with pesticide exposure but increased with habitat structure (density of eelgrass), which may have been a consequence of compensating predator behavior. The degree of prey aggregation decreased with both habitat structure and pesticide exposure, suggesting that anti-predator behaviors by prey may have been hampered by the interactive effects of both of these factors

Sampling and QA/QC: A Guide for Scientists Investigating the Occurrence of Microplastics Across Matrices

Plastic pollution is a defining environmental contaminant and is considered to be one of the greatest environmental threats of the Anthropocene, with its presence documented across aquatic and terrestrial ecosystems. The majority of this plastic debris falls into the micro (1 μm - 5 mm) or nano (1 - 1000 nm) size range and comes from primary and secondary sources. Its small size makes it cumbersome to isolate and analyze reproducibly, and its ubiquitous distribution creates numerous challenges when controlling for background contamination across matrices (e.g., sediment, tissue, water, air). Although research on microplastics represents a relatively nascent subfield, burgeoning interest in questions surrounding the fate and effects of these debris items creates a pressing need for harmonized sampling protocols and quality control approaches. For results across laboratories to be reproducible and comparable, it is imperative that guidelines based on vetted protocols be readily available to research groups, many of which are either new to plastics research or, as with any new subfield, have arrived at current approaches through a process of trial-and-error rather than in consultation with the greater scientific community. The goals of this manuscript are to a) outline the steps necessary to conduct general as well as matrix-specific quality assurance and quality control based on sample type and associated constraints, b) briefly review current findings across matrices, and c) provide guidance for the design of sampling regimes. Specific attention is paid to the source of microplastic pollution as well as the pathway by which contamination occurs, with details provided regarding each step in the process from generating appropriate questions to sampling design and collection.acceptedVersio

Sampling and QA/QC: A Guide for Scientists Investigating the Occurrence of Microplastics Across Matrices

Plastic pollution is a defining environmental contaminant and is considered to be one of the greatest environmental threats of the Anthropocene, with its presence documented across aquatic and terrestrial ecosystems. The majority of this plastic debris falls into the micro (1 μm - 5 mm) or nano (1 - 1000 nm) size range and comes from primary and secondary sources. Its small size makes it cumbersome to isolate and analyze reproducibly, and its ubiquitous distribution creates numerous challenges when controlling for background contamination across matrices (e.g., sediment, tissue, water, air). Although research on microplastics represents a relatively nascent subfield, burgeoning interest in questions surrounding the fate and effects of these debris items creates a pressing need for harmonized sampling protocols and quality control approaches. For results across laboratories to be reproducible and comparable, it is imperative that guidelines based on vetted protocols be readily available to research groups, many of which are either new to plastics research or, as with any new subfield, have arrived at current approaches through a process of trial-and-error rather than in consultation with the greater scientific community. The goals of this manuscript are to a) outline the steps necessary to conduct general as well as matrix-specific quality assurance and quality control based on sample type and associated constraints, b) briefly review current findings across matrices, and c) provide guidance for the design of sampling regimes. Specific attention is paid to the source of microplastic pollution as well as the pathway by which contamination occurs, with details provided regarding each step in the process from generating appropriate questions to sampling design and collection

Quantitative assessment of visual microscopy as a tool for microplastic research: Recommendations for improving methods and reporting.

Microscopy is often the first step in microplastic analysis and is generally followed by spectroscopy to confirm material type. The value of microscopy lies in its ability to provide count, size, color, and morphological information to inform toxicity and source apportionment. To assess the accuracy and precision of microscopy, we conducted a method evaluation study. Twenty-two laboratories from six countries were provided three blind spiked clean water samples and asked to follow a standard operating procedure. The samples contained a known number of microplastics with different morphologies (fiber, fragment, sphere), colors (clear, white, green, blue, red, and orange), polymer types (PE, PS, PVC, and PET), and sizes (ranging from roughly 3-2000 μm), and natural materials (natural hair, fibers, and shells; 100-7000 μm) that could be mistaken for microplastics (i.e., false positives). Particle recovery was poor for the smallest size fraction (3-20 μm). Average recovery (±StDev) for all reported particles >50 μm was 94.5 ± 56.3%. After quality checks, recovery for >50 μm spiked particles was 51.3 ± 21.7%. Recovery varied based on morphology and color, with poorest recovery for fibers and the largest deviations for clear and white particles. Experience mattered; less experienced laboratories tended to report higher concentration and had a higher variance among replicates. Participants identified opportunity for increased accuracy and precision through training, improved color and morphology keys, and method alterations relevant to size fractionation. The resulting data informs future work, constraining and highlighting the value of microscopy for microplastics