Size Spectrum Research Articles

Comparison between Liquid Immersion, Laser Diffraction, PDPA, and Shadowgraphy in Assessing Droplet Size from Agricultural Nozzles

Spray droplet diameters play a key role in the field of liquid plant protection product (PPP) application technology. However, the availability of various measurement techniques, each with its unique operating principles for evaluating droplet size spectra, can lead to different interpretations of spray characteristics. Therefore, in this study, four measurement techniques—Liquid Immersion (LI), Laser Diffraction (LD), Phase Doppler Particle Analysis (PDPA), and Shadowgraphy (SG)—were utilized to evaluate the droplet size distribution of agricultural spray nozzles. Additionally, PDPA and SG were used to assess the average velocity of spray droplets. Experiments were conducted in three different laboratories with the main aim of comparing results obtained with various types of equipment utilized under ordinary practical conditions. Spraying tests were carried out using three flat fan nozzles and an air-induction flat fan nozzle. As a general trend, the lowest values for droplet diameters were measured using the Laser Diffraction technique, followed by Shadowgraphy. The PDPA technique provided the highest values for mean diameters (D10, D20, and D30) and the numeric median diameter (Dn0.5), whereas the Liquid Immersion method yielded the highest values for the Sauter mean diameter (D32) and volumetric diameters (Dv0.1, Dv0.5, and Dv0.9). Importantly, all measurement techniques were able to discriminate the four nozzles based on their Dv0.5 diameter. Average droplet velocities showed a similar pattern across the four nozzles with the PDPA and the SG measurement techniques. The differences in diameter values observed with the four measurement techniques underline the necessity of always including reference nozzles in spray quality assessments to base classifications on relative rather than absolute values.

DHAFormer: Dual-channel hybrid attention network with transformer for polyp segmentation.

The accurate early diagnosis of colorectal cancer significantly relies on the precise segmentation of polyps in medical images. Current convolution-based and transformer-based segmentation methods show promise but still struggle with the varied sizes and shapes of polyps and the often low contrast between polyps and their background. This research introduces an innovative approach to confronting the aforementioned challenges by proposing a Dual-Channel Hybrid Attention Network with Transformer (DHAFormer). Our proposed framework features a multi-scale channel fusion module, which excels at recognizing polyps across a spectrum of sizes and shapes. Additionally, the framework's dual-channel hybrid attention mechanism is innovatively conceived to reduce background interference and improve the foreground representation of polyp features by integrating local and global information. The DHAFormer demonstrates significant improvements in the task of polyp segmentation compared to currently established methodologies.

The Overarching Cost of Beauty in Mauritania

This research paper outlines the risks women in Mauritania - including girls at the extremely young age of five years old - take to secure marriage and appear attractive to those who are male-identifying. Over time, the United States has become more inclusive with a broader spectrum of sizes that they carry in stores. However, not much long ago, the beauty standard in American society was to look as thin as possible (Wiseman et al., 1992). Girls in the United States would undergo dangerous diets, supplements, and bizarre exercises to stay thin, where in Mauritania, their beauty standard revolved around the complete opposite (Wiseman et al., 1992). Instead, girls in Mauritania grew up in environments where the standards of beauty perpetuated obesity. Mauritanian men claimed that skinny women looked like skeletons and they’d prefer not to sleep with “a bag of bones” (Esposito, 2022). Obesity in Mauritania was seen as a status symbol as many people believed larger women were wealthy because their husband had the financial means to gorge her on copious amounts of food. Therefore, women who were looking for potential suitors would try to become as large as possible to appear desirable to other men.

Perceptual error based on Bayesian cue combination drives implicit motor adaptation.

The sensorimotor system can recalibrate itself without our conscious awareness, a type of procedural learning whose computational mechanism remains undefined. Recent findings on implicit motor adaptation, such as over-learning from small perturbations and fast saturation for increasing perturbation size, challenge existing theories based on sensory errors. We argue that perceptual error, arising from the optimal combination of movement-related cues, is the primary driver of implicit adaptation. Central to our theory is the increasing sensory uncertainty of visual cues with increasing perturbations, which was validated through perceptual psychophysics (Experiment 1). Our theory predicts the learning dynamics of implicit adaptation across a spectrum of perturbation sizes on a trial-by-trial basis (Experiment 2). It explains proprioception changes and their relation to visual perturbation (Experiment 3). By modulating visual uncertainty in perturbation, we induced unique adaptation responses in line with our model predictions (Experiment 4). Overall, our perceptual error framework outperforms existing models based on sensory errors, suggesting that perceptual error in locating one's effector, supported by Bayesian cue integration, underpins the sensorimotor system's implicit adaptation.

Direct effect of artificial warming on communities is stronger than its indirect effect through body mass reduction

Theory predicts that morphological and bioenergetic constraints due to temperature‐induced body size reduction can modulate the direct effects of warming on biotic interactions, with consequent effects on trophic cascades and biomass distribution. However, these theoretical predictions have rarely been tested empirically. Our aim was to distinguish the indirect effects of warming‐induced body size reductions from the direct effects of warming on community structure. We conducted a mesocosm experiment manipulating factorially 1) body size reduction in the medaka fish Oryzias latipes using two populations raised for several generations under contrasted climate conditions and 2) warming (+4°C), to test their independent and interactive effects on the structure of prey and primary resource communities, the predator–prey biomass ratio and the biomass size spectra. We further dissected the effects of seasonal temperature variation from the effects of constant artificial warming. We found that the indirect effects of warming (i.e. fish body size reduction) on composition and structure of communities as well as their biomass size spectra were of marginal amplitude compared to the direct effects of seasonal temperature variation and constant warming. There were no changes in community composition in response to fish body size reduction or constant warming. However, the density of macroinvertebrates and zooplankton were maximal at intermediate seasonal water temperatures and lower in constantly‐heated mesocosms. Contrastingly, phytoplankton was not strongly affected by seasonal temperature or warming, but rather responded to grazing effects of zooplankton. Finally, we found a reduction in predator–prey biomass ratio under warming and at the warmest seasonal temperature, inducing a steeper slope of the biomass size spectra under increasing seasonal (but not constant) temperature. We conclude that the direct effects of climate change on freshwater communities are stronger than its indirect effects mediated by body mass reduction.

First release of the Pelagic Size Structure database: global datasets of marine size spectra obtained from plankton imaging devices

Abstract. In marine ecosystems, most physiological, ecological, or physical processes are size dependent. These include metabolic rates, the uptake of carbon and other nutrients, swimming and sinking velocities, and trophic interactions, which eventually determine the stocks of commercial species, as well as biogeochemical cycles and carbon sequestration. As such, broad-scale observations of plankton size distribution are important indicators of the general functioning and state of pelagic ecosystems under anthropogenic pressures. Here, we present the first global datasets of the Pelagic Size Structure database (PSSdb), generated from plankton imaging devices. This release includes the bulk particle normalized biovolume size spectrum (NBSS) and the bulk particle size distribution (PSD), along with their related parameters (slope, intercept, and R2) measured within the epipelagic layer (0–200 m) by three imaging sensors: the Imaging FlowCytobot (IFCB), the Underwater Vision Profiler (UVP), and benchtop scanners. Collectively, these instruments effectively image organisms and detrital material in the 7–10 000 µm size range. A total of 92 472 IFCB samples, 3068 UVP profiles, and 2411 scans passed our quality control and were standardized to produce consistent instrument-specific size spectra averaged to 1° × 1° latitude and longitude and by year and month. Our instrument-specific datasets span most major ocean basins, except for the IFCB datasets we have ingested, which were exclusively collected in northern latitudes, and cover decadal time periods (2013–2022 for IFCB, 2008–2021 for UVP, and 1996–2022 for scanners), allowing for a further assessment of the pelagic size spectrum in space and time. The datasets that constitute PSSdb's first release are available at https://doi.org/10.5281/zenodo.11050013 (Dugenne et al., 2024b). In addition, future updates to these data products can be accessed at https://doi.org/10.5281/zenodo.7998799.

SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits

Key messageHyperspectral features enable accurate classification of soybean seeds using linear discriminant analysis and GWAS for novel seed trait genes.Evaluating crop seed traits such as size, shape, and color is crucial for assessing seed quality and improving agricultural productivity. The introduction of the SUnSet toolbox, which employs hyperspectral sensor-derived image analysis, addresses this necessity. In a validation test involving 420 seed accessions from the Korean Soybean Core Collections, the pixel purity index algorithm identified seed- specific hyperspectral endmembers to facilitate segmentation. Various metrics extracted from ventral and lateral side images facilitated the categorization of seeds into three size groups and four shape groups. Additionally, quantitative RGB triplets representing seven seed coat colors, averaged reflectance spectra, and pigment indices were acquired. Machine learning models, trained on a dataset comprising 420 accession seeds and 199 predictors encompassing seed size, shape, and reflectance spectra, achieved accuracy rates of 95.8% for linear discriminant analysis model. Furthermore, a genome-wide association study utilizing hyperspectral features uncovered associations between seed traits and genes governing seed pigmentation and shapes. This comprehensive approach underscores the effectiveness of SUnSet in advancing precision agriculture through meticulous seed trait analysis.

Direct measurements of sea spray particle fluxes using a high temporal resolution optical particle counter over the coastal ocean

ABSTRACT Sea spray particles play a key role in transferring momentum, heat, and gas across the atmosphere–ocean interface at high wind speeds and represent an important source of cloud condensation nuclei which affect the genesis, chemistry, and radiative properties of marine clouds. Here, we present direct measurements of sea spray particle fluxes obtained using an eddy covariance technique through the use of a newly developed high temporal resolution optical particle counter. With this instrumentation measurements were made over the coastal ocean during a 5-week field campaign conducted at an observation pier from November to December 2021. Our optical particle counter was capable of measuring size spectra at a rate of 10 Hz in 8 channels covering a range of mean radii between 0.3 and 15. The power spectra of particle number density followed the Kolmogorov −2/3 power law. The shape of the cospectrum of the particle number density flux was basically similar to that of the cospectra of the heat and gas fluxes. The measured sea spray particle fluxes at mean wind speeds of up to 21 m s−1 were dominated by an upward flux, which likely represents aerosol production caused by the bursting of bubbles at the ocean surface.

Mathematical modeling of multi-component aerosol droplet evaporation and growth in indoor environments

Multi-component droplets from daily activities and production processes severely degrade indoor air quality. Their health hazards and removal efficiency depend on size and composition, significantly affected by evaporation and growth. The phase transition process is complex, involving a broad spectrum of droplet sizes with diverse heat and mass transfer characteristics. Components within the droplets experience simultaneous phase transitions at differing rates and mass transfer directions. This study aims to refine the existing evaporation model of single-component droplets in continuous flows by theoretically integrating the effects of varying droplet sizes and multiple components. A multi-component droplet evaporation/growth model that spans the entire range of droplet sizes has been developed, and predictions have been made based on this model. Utilizing MATLAB, this model accurately predicts the indoor dynamics of multi-component droplets, with deviations under 16 % from experiments. It improves accuracy by over 25 % across droplet sizes via dimensionless transfer coefficients and boosts precision by over 24 % for multi-component droplets with zero-diffusion transport. The radius of the droplet after phase change can reach 8.42 × 10−6 m and remains suspended in the air for an extended period. This study establishes a solid theoretical foundation for accurately predicting the indoor distribution of multi-component droplets.

System-level variation in evidence-based multidisciplinary cancer care delivery.

11064 Background: Widespread health system integration of hospitals continues to reshape the landscape of U.S. healthcare delivery. While complex cancer care has become centralized to high-volume centers, care for common cancers happens across the spectrum of hospital sizes, with known variation in receipt of evidence-based practice (EBP) based on system affiliation. Strategies are needed to evaluate system performance in order to identify system characteristics and processes that contribute to high-quality cancer care. Methods: Using a novel data linkage between the National Cancer Database and AHRQ Compendium of U.S. Health Systems, adult patients treated for breast, colon, melanoma, and thyroid cancers between 2010 and 2020 at Commission on Cancer (CoC) hospitals were identified. Systems were categorized based on number of CoC hospitals (small, 2-3; medium, 4-9; large, 10+). Eight EBP measures were developed using national multidisciplinary guidelines, and measure-specific cohorts were extracted to calculate system-level EBP performance and within-system variation using mixed effects multivariable logistic regression models. Systems were then ranked across all measures for performance and variation, and average rankings were compared by system size. Results: 3,052,453 patients with breast (60.0%), colon (17.0%), melanoma (14.0%), and thyroid (9.0%) cancers were treated at 866 CoC hospitals in 368 health systems. The 8-measure analytic cohort had 104 systems, most of which were small systems (n=74, 71.2%). Large systems (n=9, 8.7%) had worse average performance rankings compared to medium or small systems, though this was not statistically significant (p=0.1) (Table). A significant increase in within-system variation (as measured by average ranking of variability across EBP measures) was seen with increasing system size (p<0.001). Conclusions: Significant variation in EBP performance for common cancers was noted based on health system size in this large, contemporary cohort, with greater within-system variation as system size increased. Future work will identify modifiable system characteristics associated with performance that could aid system leaders and policy makers to design, measure, and incentivize systems that employ effective cancer care delivery strategies. System rankings from 1 to 104 (best to worst), averaged over all measures; data presented as median (IQR). [Table: see text]

Interactive Association of XRCC1, XRCC2, XRCC3, and TP53 Gene Polymorphisms With Gastrointestinal Cancer Risk: Insights From a Hospital-Based Case-Control Study.

Gastrointestinal (GI) cancer presents a significant worldwide health burden, influenced by a combination of genetic and environmental factors. This study endeavors to explore the combined effects of the XRCC1, XRCC2, XRCC3, and TP53 genes that contribute to the heightened risk of GI cancer, shedding light on their combined influence on cancer susceptibility. A total of 200 histologically confirmed cases of GI cancerand an equal number of controlswere selected to examine genetic polymorphisms within the XRCC1, XRCC2, XRCC3, and TP53 genes using the polymerase chain reaction-based restriction fragment length polymorphism (PCR-RFLP). Odds ratios (OR) with 95% confidence intervals (CI) were calculated to assess the association of these polymorphisms with GI cancer susceptibility, with statistical significance (p ≤ 0.05). Logistic regression analysis confirmed strong evidence of synergistic interactions among specific variant genotypes. Notably, combinations such as heterozygous Arg/Ser+Ser/Ser genotype of TP53 Arg249Ser polymorphism with Arg/Trp+Trp/Trp genotype of XRCC1 Arg194Trp polymorphism (OR=2.64; 95% CI: 1.35-5.18; p=0.004),Arg/Gln+Gln/Gln genotype of XRCC1 at codon 399 (OR=5.04; 95% CI: 2.81-9.05; p=0.0001), Arg/His and His/His genotypes of XRCC2 Arg188His (OR=2.16; 95% CI: 1.06-4.39; p<0.032), and Thr/Met+Met/Met genotype of XRCC3 Thr242Met (OR=3.48; 95% CI: 1.79-6.77; p=0.0002) showed significant associations with GI cancer risk in the study population. The findings indicate a notable association between the combined effect of heterozygous variant genotypes of TP53 and variant genotypes of XRCC1, XRCC2, and XRCC3 on GI cancer risk. However, further research with a larger sample size and broad single nucleotide polymorphism (SNP) spectra is necessary to understand the interaction between genetic variations and environmental factors influencing GI cancer susceptibility.

A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.

The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating "silently" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms. MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall. There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases. Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms.

Synthesis of TiO2 nanoparticles using red spinach leaf extract (Amaranthus Tricolor L.) for photocatalytic of methylene blue degradation

ABSTRACT Textile industry waste such as methylene blue can pose a serious threat to health and ecosystems. One solution to overcome this problem is to utilize photocatalytic technology using TiO2 semiconductors. This research aims to make green synthetic TiO2 nanoparticles (NPs) using red spinach (Amaranthus Tricolor L.) leaf extract and used for photodegradation of methylene blue. Extraction of red spinach leaves showed that 30 min and a temperature of 95°C showed the highest phenolic content. In this research, several phenolic compounds were also identified in red spinach extract. For TiO2 NPs, the X-ray diffraction results show that TiO2 has a pure anatase phase. Electron microscope results show that TiO2 has the shape of agglomerated spherical clusters. The particle size distribution shows that TiO2 has an average size range of 77–90 nm. The methylene blue photodegradation showed that TiO2 had an efficiency of 90.36% for 180 min, higher than commercial TiO2 Evonic. This result can be attributed to the small particle size and broadband spectra so that photocatalysis is more effective.

Estimating brain and eye lens dose for the cardiologist in interventional cardiology-are the dose levels of concern?

To establish conversion coefficients (CCs), between mean absorbed dose to the brain and eye lens of the cardiologist and the air kerma-area product, PKA, for a set of projections in cardiac interventional procedures. Furthermore, by taking clinical data into account, a method to estimate the doses per procedure, or annual dose, is presented. Thermoluminescence dosimeters were used together with anthropomorphic phantoms, simulating a cardiologist performing an interventional cardiac procedure, to estimate the CCs for the brain and eye lens dose for nine standard projections, and change in patient size and x-ray spectrum. Additionally, a single CC has been estimated, accounting for each projections fraction of use in the clinic and associated PKA using clinical data from the dose monitoring system in our hospital. The maximum CCs for the eye lens and segment of the brain, is 5.47 μGy/Gycm2 (left eye lens) and 1.71 μGy/Gycm2 (left brain segment). The corresponding weighted CCs: are 3.39 μGy/Gycm2 and 0.89 μGy/Gycm2, respectively. Conversion coefficients have been established under actual scatter conditions, showing higher doses on the left side of the operator. Using modern interventional x-ray equipment, interventional cardiac procedures will not cause high radiation dose levels to the operator when a ceiling mounted shield is used, otherwise there is a risk that the threshold dose values for cataract will be reached. In addition to the CCs for the different projections, methods for deriving a single CC per cardiac interventional procedure and dose per year were introduced.

Transect walks and malaise traps differ in temperature sensitivity but reveal consistent drivers of pollinator richness

Abstract While transect walks have long been the preferred monitoring method for many flying insect taxa, malaise traps combined with DNA metabarcoding have gained growing prominence. However, it remains unclear whether both methods reveal comparable species richness and the same ecological drivers along environmental gradients. We selected three groups of pollinators (wild bees, hoverflies and butterflies) and one group of herbivores (grasshoppers) as functionally important and conservation‐relevant model groups, comparing results of both methods along an elevational gradient in the German Alps. Across the study region, both methods detected a similarly high species richness of pollinators with ~50% overlap of species pools, but transect walks revealed more species per site, especially in higher elevations and under low temperatures. Body size spectra differed between methods, with on average more large butterfly and more small bee species in transect walks. Nevertheless, temperature and flower richness were consistent drivers of pollinator richness, independent of the sampling method. Grasshopper richness from transect walks was considerably higher than from malaise traps. Both methods identified temperature and only malaise traps also identified management as drivers of grasshopper richness. We conclude that malaise traps are principally suitable substitutes for the more time‐consuming pollinator transect walks. However, the effectiveness of these passive traps is more susceptible to changes in sampling temperature, and in some pollinator groups, body size classes are presented differently, which is important to consider during analyses. For grasshoppers, transect walks appear to be more suitable to assess species richness, as considerably more species can be monitored.

Multi-channel prismatic localized surface plasmon resonance biosensor for real-time competitive assay multiple COVID-19 characteristic miRNAs

A multi-channel prismatic localized surface plasmon resonance (LSPR) biosensor was developed for quantitative and real-time detection of multiple COVID-19 characteristic miRNAs. The well-dispersed and dense gold nanoparticles (AuNPs) arrays for LSPR biosensing were fabricated through a nano-thickness diblock copolymer template (BCPT). Both theoretical and experimental analyses were conducted to investigate the effects of particle size, interparticle spacing, and surface coverage on LSPR sensing spectrum and intensity sensitivity of varied AuNPs sizes. A competitive assay strategy was proposed and used for non-amplification miRNA detection with a low limit detection of 3.41 nM, while a four-channel prismatic LSPR system enables parallel detection of multiple miRNAs. Furthermore, this sensing strategy can effectively and specifically identify target miRNA, distinguish mismatched miRNA and interfering miRNA, and exhibit low non-specific adsorption. This BCPT-based LSPR biosensor demonstrates the practicality and potential of a multi-channel, adaptable, and integrated prismatic sensor in medical testing and diagnostic applications.

Morphological characterization of some local watermelon (Citrullus lanatus L.) genotypes of Turkey

The scope of this study, some of the local Turkish watermelon genotypes were evaluated morphologically. A total of 20 local genotypes and three commercial varieties were assessed regarding their cotyledon, leaf, fruit, and seed phenotypes. An extensive morphological analysis was performed on a diverse set of genotypes. Traits such as cotyledon shape and color intensity, leaf size and lobing, and fruit size, shape, and color were measured and compared. Hierarchical clustering analysis, correlation matrices, and principal component analysis were employed to interpret the data. The study revealed significant morphological variability among the watermelon genotypes. Cotyledons ranged from narrow to broad, with a predominance of large sizes and dark green coloration. Leaf characteristics varied widely, with a notable distribution across different sizes and degrees of lobing. Fruit analysis showed a broad spectrum of shapes, sizes, and colors, indicating a rich genetic diversity. Two main genotype clusters were identified, suggesting a clear distinction based on morphological traits.

Assessing water diversion impacts on the fish community size structure in headwater stream stretches

Water diversion for hydropower plants is one of the leading causes of habitat alteration and biotic homogenization. The impacts of small hydropower plants on fish communities are usually assessed using taxonomic composition and structure indicators. Size-based indicators are useful tools to evaluate the effects of environmental factors and anthropogenic perturbations on riverine ecosystems. In this study, we investigated the impact of water diversion on fish community body size structure in 16 small hydropower plants in the upper Ter River basin (NE Iberian Peninsula). We tested the use of multiple size-based metrics under different sampling intensities (one- vs. four-pass electrofishing) and compared control vs. diverted stream stretches. Results revealed that water diversion had a negative effect on fish community average and median length, while size spectrum and size diversity metrics showed no responses to the impact. Altitude was positively related with body size metrics and was the strongest natural driver affecting them. Moreover, we found that all the size-based metrics exhibited consistent values under different sampling efforts. Our findings suggest that size-based metrics could be useful indicators for bioassessment of river flow alteration and that one-pass electrofishing was robust enough to characterize the stream fish community size structure in our study.

Influence of microplastics and biogenic particles on the size spectra of tropical estuarine and marine pelagic ecosystems

Size spectra analysis has been widely used to study pelagic ecosystems worldwide. It has a solid theoretical and empirical basis and can be used to provide useful information on ecosystem structure and trophic efficiency. The objective of this study was to obtain complete Normalized Biovolume Size Spectra (NBSS), including zooplankton, microplastics, and other suspended particles, along an estuary-shelf gradient. Plankton net samples (300 μm mesh) were obtained in the Rio Formoso Estuary, in Tamandaré Bay and on the continental shelf off Tamandaré, Brazil, during two years (from April/2013 to May/2015). Particles were identified by image analysis (ZooScan) and infrared spectroscopy (FTIR). Generally, NBSS slopes were close to −1 (i.e., between −1.09 and −0.85), except for NBSSz (zooplankton only) in the Estuary (−1.59) and in the Bay (−1.44), where the steepest slopes were observed, due to the importance of small-sized zooplankton in these areas. The NBSSz slope was significantly steeper in the Estuary and in the Bay than on the Shelf. The inclusion of particles into the NBSS (NBSSp) turned the slope significantly less steep in the Estuary and in the Bay. Intercepts were significantly higher in the Estuary than in the other areas, after including particles in the analysis (NBSSp), due to the extremely high total volume of biogenic particles in the estuary. The most relevant impacts of microplastics were detected within the larger size classes (> 2.60 mm Feret length, > 0.58 log10 mm3). In the Estuary, large-sized microplastics were similarly important (in terms of volume) as zooplankton. Large-sized polyethylene and polypropylene were more relevant in the Bay, large-sized nylon fibers on the Shelf (in the rainy season). The present study, a pioneering effort towards a synthetic analysis of zooplankton, microplastics, and other particles, highlights the importance of including non-living particles in size-based studies and ecosystem models.

Relationships Between Plankton Size Spectra, Net Primary Production, and the Biological Carbon Pump

AbstractPhotosynthesis in the surface ocean and subsequent export of a fraction of this fixed carbon leads to carbon dioxide sequestration in the deep ocean. Ecological relationships among plankton functional groups and theoretical relationships between particle size and sinking rate suggest that carbon export from the euphotic zone is more efficient when communities are dominated by large organisms. However, this hypothesis has never been tested against measured size spectra spanning the &gt;5 orders of magnitude found in plankton communities. Using data from five ocean regions (California Current Ecosystem, North Pacific subtropical gyre, Costa Rica Dome, Gulf of Mexico, and Southern Ocean subtropical front), we quantified carbon‐based plankton size spectra from heterotrophic bacteria to metazoan zooplankton (size class cutoffs varied slightly between regions) and their relationship to net primary production and sinking particle flux. Slopes of the normalized biomass size spectra (NBSS) varied from −1.6 to −1.2 (median slope of −1.4 equates to large 1–10 mm organisms having a biomass equal to only 7.6% of the biomass in small 1–10 μm organisms). Net primary production was positively correlated with the NBSS slope, with a particularly strong relationship in the microbial portion of the size spectra. While organic carbon export co‐varied with NBSS slope, we found only weak evidence that export efficiency is related to plankton community size spectra. Multi‐variate statistical analysis suggested that properties of the NBSS added no explanatory power over chlorophyll, primary production, and temperature. Rather, the results suggest that both plankton size spectra and carbon export increase with increasing system productivity.