The development of this protocol was founded by IPA Adriatic Cross-border Cooperation Programme 2007-2013, within the DeFishGear project (1&#176;str/00010).

1. Sampling of microplastics on the sea surface
<ol>
	<li>Deploy the manta net from the side of the vessel using a spinnaker boom or &#187;A-frame&#171; using lines and karabiners.</li>
	<li>Deploy the manta net out of the wake zone (approx. 3 - 4 m distance from the boat) in order to prevent collecting water affected by turbulence inside the wake zone.</li>
	<li>Write down the initial GPS coordinates and initial time in the data sheet.</li>
	<li>Start to move in one straight direction with a speed of approx. 2 - 3 knots for 30 min and begin the time measurement.</li>
	<li>After 30 min stop the boat and write down final GPS coordinates, the length of the route (the most correct way is to calculate the length from the GPS coordinates) and the average boat speed into the data sheet provided and lift the manta net out of the water.</li>
	<li>Rinse the manta net thoroughly from the outside of the net with seawater using a submersible pump or water from the boat water reservoir. Rinse in the direction from the manta mouth to the cod end in order to concentrate all particles adhered to the net into the cod end. 
	Note: Never rinse the sample through the opening of the net in order to prevent contamination.</li>
	<li>Safely remove the cod end and sieve the sample in the cod end through a 300 &#181;m mesh size sieve or less.</li>
	<li>Rinse the cod end thoroughly from the outside and pour the rest of the sample through the sieve. Repeat this step until there are no longer any particles inside the cod end.</li>
	<li>Concentrate all material on the sieve in one part of the sieve.</li>
	<li>With the use of a funnel, rinse the sieve into a glass jar or plastic bottle using 70 % ethanol.</li>
	<li>Close the bottle,&#160;wipe it with paper towels and label the lid and outside of the jar with the sample name and date with waterproof marker (you should also put a second label written with a pencil on velum paper in a jar to avoid the possible loss of the sample name due to the erased label on the jar). Transfer labeled plastic bottle into the cool box. 
	Note to general sampling conditions: The wind speed should not be more than 2 Beaufort, since the waves are too high and the net is not stable on the sea surface. It is important to maintain a steady linear course at a constant speed during the trawls. Half of the manta net opening should be submersed during sampling. Duration of sampling should be 30 min (in cases where there is a large amount of natural material, e.g. plankton bloom, the duration of sampling can be shorter). Avoid the use of plastic tools and containers. Avoid synthetic clothing (e.g. fleece), ropes and contact of manta net with vessel to prevent contamination of the sample. Be very careful not to damage the manta net or the boat hull while deploying and capturing the net.</li>
</ol>
2. Separation of microplastics from the sea surface samples
<ol>
	<li>If the sample does not contain any items larger than 25 mm and appears to be clean, continue directly with step 3.</li>
	<li>Pour sample through the sieve (&#8804;300 &#181;m mesh size) and remove all natural or artificial litter objects of a size &#62;5 mm (macro and mezzo litter) from the sample, using visual identification and tweezers. Be careful to rinse each removed object carefully with distilled water in order to remove any microplastic litter adhered to it. Store all natural and artificial litter objects in separate containers. Dry all natural and artificial litter objects in a desiccator (or in the open air, but in a closed dish) and weigh them. Identify all litter objects &#62;25 mm (macro litter) according to the Master List of Categories of Litter Items16.</li>
	<li>After removing all larger objects, concentrate all remaining pieces in one part of the sieve using squirt bottles or tap water. Pour the sample into a glass container using a minimum amount of 70 % ethanol with the help of a funnel. 
	Note: In this step the use of 70 % ethanol is crucial to preserve the sample. Also in the step of visual inspection of the sample, ethanol helps to discolor the organisms and colorful plastics therefore become easier to find.</li>
	<li>Take a small amount of the sample (subsample) and pour it into a glass Petri dish. Analyze the sample with the use of a stereomicroscope (20 - 80x zoom) and search for microplastic particles.</li>
	<li>Each microplastic particle should be categorized into one of the categories listed in Table 1 and put into a Petri dish or other glass vials, marked with a category name. The Petri dish needs to be closed at all times. 
	Note: When separating microplastics from your sample be conservative and select more rather than less particles for the analysis. The real chemical structure of particles will still be determined later on. Be sure to analyze larger objects from all sides as microplastics may be stuck and therefore hidden under larger items. It may also be helpful to move already analyzed objects to one side of the Petri dish.</li>
	<li>Put the Petri dish under the microscope with measuring equipment (ocular ruler calibrated by the micrometer slide or image analysis software) and measure the size of each particle (measure the longest diagonal), except filaments, and note its color. Each subsample should be reviewed by another person. Be careful to rinse the glass container containing the sample so that all particles adhering to the glass walls are washed into the Petri dish.</li>
	<li>Weigh the microplastic particles of each category separately by the use of analytical scale. Microplastic particles need to be dried prior to weighing. The closed Petri dish can be put in a desiccator or the samples can be left to dry in a closed dish till particles became dry (the weight of closed petri dish with particles is constant).</li>
	<li>Identify micro litter. When analyzing a sample in search of microplastics, please consider that some particles will be easily visible (color, shape, size) while others may be trickier to find. Below are a few features that identify microplastic particles in the sample: For example, no cell structure, uneven, sharp, crooked edges, uniform thickness, distinctive colors (blue, green, yellow, etc.).</li>
</ol>
3. Chemical identification of microplastics
<ol>
	<li>ATR-FTIR spectroscopy
	<ol>
		<li>Prior to the analysis clean the detection system with alcohol and a lint free cloth.</li>
		<li>Record a background spectrum. Place the sample on the sample holder and collect the spectra. Identify the obtained ATR- FTIR spectra using an automated comparison of the obtained spectrum with spectra in a database.</li>
	</ol>
	</li>
	<li>Micro ATR-FTIR spectroscopy
	<ol>
		<li>Prior to the analysis clean the detection system with alcohol and a lint free cloth.</li>
		<li>Place the sample on a glass filter. Note: Other filters can be used but their polymer nature can interfere with the characterization.</li>
		<li>Place the filter with the sample on the automatic scanning table and use the joystick to locate the sample.</li>
		<li>Record an optical image and mark an area (e.g. 20 by 20 &#181;m) where the sample will be characterized.</li>
		<li>Record a background spectrum.</li>
		<li>Place the sample on the sample holder and collect the spectra at the predefined location.</li>
		<li>Identify the obtained micro ATR-FTIR spectra using an automated comparison of the obtained spectrum with spectra in a database.</li>
	</ol>
	</li>
</ol>

<ol>
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C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastics+in+the+marine+environment:+Sources,+consequences+and+solutions.">Microplastics in the marine environment: Sources, consequences and solutions.</a> Marine anthropogenic litter. , 185-200 (2015).</li><li>Lusher, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastics+in+the+marine+environment:+distribution,+interactions+and+effects.">Microplastics in the marine environment: distribution, interactions and effects.</a> Marine anthropogenic litter. , 245-307 (2015).</li><li>Arthur, C., Baker, J., Bamford, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Proceedings of the International Research Workshop on the Occurrence, Effects, and Fate of Microplastic Marine Debris, September 9-11. , (2008).</li><li>Andrady, A. 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A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sources+and+pathways+of+microplastics+to+habitats.">Sources and pathways of microplastics to habitats.</a> Marine anthropogenic litter. , 229-244 (2015).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Marine+litter:+an+analytical+overview.">Marine litter: an analytical overview.</a> UNEP's REGIONAL SEAS PROGRAMME. , (2005).</li><li>van der Wal, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> SFRA0025: Identification and Assessment of Riverine Input of (Marine) Litter, Final Report for the European Commission DG Environment under Framework Contract No ENV.D.2/FRA/2012/0025. , (2015).</li><li>Set&#228;l&#228;, O., Fleming-Lehtinen, V., Lehtiniemi, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ingestion+and+transfer+of+microplastics+in+the+planktonic+food+web.">Ingestion and transfer of microplastics in the planktonic food web.</a> Environmental pollution. 185, 77-83 (2014).</li><li>Farrell, P., Nelson, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trophic+level+transfer+of+microplastic:+Mytilus+edulis.+(L.)+to+Carcinus+maenas+(L).">Trophic level transfer of microplastic: Mytilus edulis. (L.) to Carcinus maenas (L).</a> Environmental Pollution. 177, 1-3 (2013).</li><li>Wright, S. L., Thompson, R. C., Galloway, T. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+physical+impacts+of+microplastics+on+marine+organisms:+a+review.">The physical impacts of microplastics on marine organisms: a review.</a> Environmental Pollution. 178, 483-492 (2013).</li><li>Bakir, A., Rowland, S. J., Thompson, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transport+of+persistent+organic+pollutants+by+microplastics+in+estuarine+conditions.">Transport of persistent organic pollutants by microplastics in estuarine conditions.</a> Estuarine, Coastal and Shelf Science. 140, 14-21 (2014).</li><li>Cole, M., Lindeque, P., Halsband, C., Galloway, T. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastics+as+contaminants+in+the+marine+environment:+a+review.">Microplastics as contaminants in the marine environment: a review.</a> Marine pollution bulletin. 62 (12), 2588-2597 (2011).</li><li>Zarfl, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastics+in+oceans.">Microplastics in oceans.</a> Marine Pollution Bulletin. 62, 1589-1591 (2011).</li><li>Hanke, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> MSFD GES technical subgroup on marine litter. Guidance on monitoring of marine litter in European Seas. , (2013).</li><li>L&#246;der, M. G. J., Gerdts, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methodology+used+for+the+detection+and+indentification+of+microplastics+-+A+critical+appraisal.">Methodology used for the detection and indentification of microplastics - A critical appraisal.</a> Marine anthropogenic litter. , 201-227 (2015).</li><li>Kang, J. H., Kwon, O. Y., Lee, K. W., Song, Y. K., Shim, W. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Marine+neustonic+microplastics+around+the+southeastern+coast+of+Korea.">Marine neustonic microplastics around the southeastern coast of Korea.</a> Marine pollution bulletin. 96 (1), 304-312 (2015).</li><li>Lusher, A. L., Tirelli, V., O'Connor, I., Officer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastics+in+Arctic+polar+waters:+the+first+reported+values+of+particles+in+surface+and+sub-surface+samples.">Microplastics in Arctic polar waters: the first reported values of particles in surface and sub-surface samples.</a> Scientific reports. 5, (2015).</li><li>Shu, J. -. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transient+Marangoni+waves+due+to+impulsive+motion+of+a+submerged+body.">Transient Marangoni waves due to impulsive motion of a submerged body.</a> International Applied Mechanics. 40 (6), 709-714 (2004).</li><li>Rabaud, M., Moisy, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ship+wakes:+Kelvin+or+Mach+angle.">Ship wakes: Kelvin or Mach angle.</a> Physical Review Letters. 110 (21), 214503 (2013).</li><li>Hidalgo-Ruz, V., Gutow, L., Thompson, R. C., Thiel, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastics+in+the+marine+environment:+a+review+of+the+methods+used+for+identification+and+quantification.">Microplastics in the marine environment: a review of the methods used for identification and quantification.</a> Environmental science &amp; technology. 46 (6), 3060-3075 (2012).</li><li>L&#246;der, M. G. J., Kuczera, M., Mintenig, S., Lorenz, C., Gerdts, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Focal+plane+array+detector-based+micro-Fourier-transform+infrared+imaging+for+the+analysis+of+microplastics+in+environmental+samples.">Focal plane array detector-based micro-Fourier-transform infrared imaging for the analysis of microplastics in environmental samples.</a> Environmental Chemistry. 12 (5), 563-581 (2009).</li><li>Ioakeimidis, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+degradation+potential+of+PET+bottles+in+the+marine+environment:+An+ATR-FTIR+based+approach.">The degradation potential of PET bottles in the marine environment: An ATR-FTIR based approach.</a> Scientific reports. 6, 23501 (2016).</li><li>McDermid, K. J., McMullen, T. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+analysis+of+small-plastic+debris+on+beaches+in+the+Hawaiian+archipelago.">Quantitative analysis of small-plastic debris on beaches in the Hawaiian archipelago.</a> Marine pollution bulletin. 48 (7), 790-794 (2004).</li><li>Eriksen, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microplastic+pollution+in+the+surface+waters+of+the+Laurentian+Great+Lakes.">Microplastic pollution in the surface waters of the Laurentian Great Lakes.</a> Marine pollution bulletin. 77 (1-2), 177-182 (2013).</li></ol>

The authors have nothing to disclose.

Microplastics sampling on the sea surface by manta net is a widely used method for the sampling of microplastics on the sea surface, but to date there has been no unified methodology. A large volume of water can be filtered through the manta net, thus the possibility of trapping a relevant number of microplastics is high and the results are perceived to be reliable. Comparability of results among different samples is assured by normalization. In our case, the concentrations were related to the sampled area by multiplying trawl distance by the horizontal width of the net opening. Another option is to use a flow meter, fixed at the net opening. The use of a flow meter is possible since the manta net with its lateral wings is very stable on the sea surface and therefore hopping on the waves is minimal. A flow meter records the volume of filtered water and thus enables the normalization of results per volume of sampled water16.
The most frequently used manta nets have around 300 &#181;m mesh size and are 3 - 4.5 m long. These dimensions were optimized to avoid clogging of the net and to allow the sampling a volume of water as large as possible. Trawling speed is recommended to be between 2 - 3 knots, but it is dependent on wave height, wind speed and sea currents. It is very important that the manta net is under supervision the whole time during sampling and if it starts hopping, the trawling speed must be reduced. The trawling time is recommended to be around 30 min, but depends on seston concentrations. It can happen that seston sometimes clogs the manta net. In this case the trawling has to be stopped immediately, otherwise the microplastic particles can be lost and the net can get damaged. Manta net is the most often fixed from the side of the vessel. This is also the most suitable option, while the manta net is surely out of the wake zone. In some surveys manta net was fixed from the stern of the vessel17, 18, but in that case you have to be sure that the net is out of the wake zone. The distance, on which the trawl is set for sampling, should be determined individually, since the zone of turbulences caused by the vessel varies from the size of the vessel and from the speed of the boat19, 20.
Separation of microplastic particles from the sea surface samples is most often done just by visual identification21. Particles bigger than 1 mm can be identified easily by the naked eye, while particles smaller than 1 mm require the use of a stereomicroscope. To reduce the possibility of confusing the non-plastic particles with plastic ones, using the polarization light on stereomicroscopes is recommended. The possibility of misidentification of plastic particles gets higher with smaller particles. Thus particles &#62;0.5 mm can only be identified visually21, by the use of stereomicroscope. For particles smaller than 0.5 mm an additional, more accurate method is required e.g. micro ATR-FTIR spectroscopy21.
During the process of microplastics separation from the sample the possibility of sample contamination with the airborne filaments is very high. For this reason, control Petri dishes left open on the working table are strongly recommended for the identification of potential contaminant airborne particles. Namely, the quality of the data strongly depends on: 1) the precision of the person working with the sample, 2) the quality and magnification of the stereomicroscope, and 3) the quantity of organic matter in the sample16. After visual identification it is strongly recommended to analyze the sorted particles with one of the available techniques for chemical identification of the material8.
Several methods exist for polymer identification, among which the FTIR spectroscopy and Raman spectroscopy are the most frequently used22. FTIR and Raman spectroscopy are complementary techniques and their accuracy is similar. In our protocol, the FTIR and micro FTIR spectroscopy with &#34;attenuated total reflectance&#34; (ATR) are presented. They are simple to use and they enable fast and accurate results. Plastic polymers possess highly specific infrared (IR) spectra with distinct band patterns, thus making IR spectroscopy an optimal technique for the identification of microplastics21. The energy of IR radiation excites a specific molecular vibration when interacting with a sample, which enables the measurement of characteristic IR spectra22. FTIR spectroscopy can also provide additional information on particles, such as intensity of oxidation23 and level of degradation24. While ATR-FTIR is suitable for chemical identification of larger particles (&#62;0.5 mm), micro ATR-FTIR spectroscopy can provide information on the chemical structure of particles &#60;0.5 mm, as it combines the function of a microscope and an infrared spectrometer.
Before using FTIR and micro FTIR spectroscopy, microplastic particles have to be previously dried, since water strongly absorbs IR radiation22, and purified, in case they are covered with biofilms and/or other organic and inorganic adherents, which can influence the IR spectra. The most non-invasive way to purify samples is by stirring and rinsing with fresh water25. If this is not enough, then the use of 30 % hydrogen peroxide is recommended. All other methods can have negative effects on the microplastic particles (e.g. ultrasonic cleaning can further break particles, strong acidic or alkaline solutions can damage several plastic polymers, etc.) and therefore their use is not recommended. More promising is the use of a sequential enzymatic digestion as a plastic friendly purification step. Purification using different technical enzymes (e.g. lipase, amylase, proteinase, chitinase, cellulase, proteinase-K) has been successfully applied to reducing a biological matrix of plankton and thus proved to be a valuable technique to minimize matrix artifacts during FTIR spectroscopy measurements22.
Separation of microplastics by visual identification and chemical identification of selected particles are both extremely time-consuming processes. This work has to be done by an accurate and patient person who has experience with stereomicroscopes, not only in recognizing the plastic particles, but also in recognizing biological matter. Even an experienced person cannot discriminate all potential microplastic particles unambiguously from chitin or diatom fragments22. Therefore, the error rate of visual sorting ranges from 20 %26 to 70 %21 and increases with decreasing particle size.

Microplastic pollution in the sea represents a growing concern to contemporary society, due to the constant increase in plastic production and its subsequent disposal and accumulation in the marine environment1. Even if plastic macro litter would no longer enter the seas, microplastic pollution would continue to grow due to fragmentation of already existing plastic litter in the sea2. The majority of microplastic pollution studies were carried out in marine and fresh water ecosystems and mainly addressed sea surface pollution3.
The term microplastic refers to plastic particles smaller than 5 mm in size4. This term describes a heterogeneous mixture of particles, which can differ in size (from a few microns to several millimeters), color and shape (from very different shapes of fragments to long fibers). Microplastic particles can be of a primary or secondary origin5. Microplastic of primary origin is manufactured as small particles used in the cosmetics industry (pilling cr&#232;me etc.) or chemical industry as precursor for other plastic products (e.g. plastic pellets used in plastic industry). Microplastic of secondary origin arise via the degradation of larger plastic pieces in the environment due to physical and chemical processes, induced by light, heat, oxygen, water and organisms6. In 2015, four types of microplastic sources were defined: larger plastic litter, cleaning products, medicines and textiles6. The main source (80 %) of larger plastic litter is assumed to be land based7. Microplastic from cosmetic products, medicines and textile enters water ecosystems through sewage and storm waters6. Microplastic particles most frequently found in water ecosystems are fragments from larger plastic litter and textile fibers8. 
Microplastics have several negative effects on the environment. Their small size allows them to enter the food web through ingestion by marine organisms9, 10. Ingested particles can cause physical damage or block the digestive system of animals11. Particles can also be carriers of persistent organic pollutants (POPs). Their hydrophobic surface and favorable ratio of large surface area to small volume, enables POPs to adsorb onto the microplastics12. In the environment or digestive systems of animals who ingest them, POPs and other plastic additives can be leached from microplastic particles13. 
Previous studies reported the ubiquitous presence of microplastics in the marine environment3, from the water column to the bottom sediments. The threat of microplastic pollution was already identified by the Marine Strategy Framework Directive in the EU and, consequently, mandatory monitoring of microplastics was advised14. Accordingly, the EU Technical Subgroup on Marine Litter (TSG-ML) prepared recommendations for monitoring of microplastics in the European seas15. Thus, the video guidelines for microplastics sampling are of high importance, as they support comparative monitoring and a coherent management process all over the world.
This protocol was developed within the DeFishGear project for the first monitoring of microplastic pollution in the Adriatic Sea. Recommendations from the document "Guidance on Monitoring of Marine Litter in European Seas" by TSG-ML15 were taken into account. This protocol describes the methodology for microplastics sampling on the sea surface, separation of microplastics from the samples, and chemical analysis of microplastic particles to confirm that particles are from plastic material and to identify the type of plastic. Sampling was done by the use of a manta net, which is the most suitable equipment for sampling in calm waters16. Separation of microplastics from the samples was carried out by visual identification using a stereomicroscope. Isolated particles were later chemically identified using Fourier transform infrared (FTIR) spectroscopy and micro FTIR spectroscopy.

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			<td colspan="3" height="21" style="height:21px;width:464px;">In this protocol no specific equipment or reagents were used.</td>
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protocol for microplastics sampling on the sea surface and sample analysis

Microplastic pollution in the marine environment is a scientific topic that has received increasing attention over the last decade. The majority of scientific publications address microplastic pollution of the sea surface. The protocol below describes the methodology for sampling, sample preparation, separation and chemical identification of microplastic particles. A manta net fixed on an &#187;A frame&#171; attached to the side of the vessel was used for sampling. Microplastic particles caught in the cod end of the net were separated from samples by visual identification and use of stereomicroscopes. Particles were analyzed for their size using an image analysis program and for their chemical structure using ATR-FTIR and micro FTIR spectroscopy. The described protocol is in line with recommendations for microplastics monitoring published by the Marine Strategy Framework Directive (MSFD) Technical Subgroup on Marine Litter. This written protocol with video guide will support the work of researchers that deal with microplastics monitoring all over the world.

The first result of the described protocol are microplastic particles categorized into six categories according to their visual features (Table 1). The first category, and usually the most abundant one, are fragments (Figure 1). They are rigid, thick, with sharp crooked edges and an irregular shape. They can be in a variety of different colors. The second category are films (Figure 2). They also appear in irregular shapes, but in comparison with fragments, they are thin and flexible and usually transparent. The third category are pellets (Figure 3), usually originating from the plastics industry. They are irregular, round shapes, and normally bigger in size, around 5 mm in diameter. They are usually flat on one side and can be of various colors. The fourth category are granules (Figure 4). In comparison with pellets, they have a regular round shape and usually a smaller size, around 1 mm in diameter. They appear in natural colors (white, beige, brown). The fifth category are filaments (Figure 5). They are, next to fragments, the most abundant type of microplastic particles. They can be short or long, with different thicknesses and colors. The last category are foams (Figure 6). They most often come from large particles of styrofoam. They are a soft, irregular shape and white to yellow in color.
The main result of microplastics sampling and sample analysis is the number of microplastic particles per sample. These data can be further normalized per km2. The formula used for normalization is:
microplastic particles per sample / sampling area,
where sampling area is calculated by multiplying sampling distance by the width of the opening of the manta net (Tables 2, 3; Figure 7). In addition, particles can be analyzed with image analysis software. The results include maximum length and area of each particle (Table 4). Figure 8a show particles before image analysis and Figure 8b is after image analysis, where each particle is measured and numbered. Lastly, a chemical analysis of the total or highest possible number of particles per sample is recommended. Using Fourier transform infrared spectroscopy a spectrum of the selected particle is acquired, as shown on Figure 9. This spectrum is then compared with the spectra from the software library (Figure 10). The final result will show if a given particle is plastic or not and indicate the type of plastic from the chemical structure.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>1</td>
			<td>Fragments</td>
		</tr>
		<tr>
			<td>2</td>
			<td>Films</td>
		</tr>
		<tr>
			<td>3</td>
			<td>Pellets</td>
		</tr>
		<tr>
			<td>4</td>
			<td>Granules</td>
		</tr>
		<tr>
			<td>5</td>
			<td>Filaments</td>
		</tr>
		<tr>
			<td>6</td>
			<td>Foams</td>
		</tr>
	</tbody>
</table>
Table 1: Categories of microplastic particles.
<img alt="Figure 1" src="/files/ftp_upload/55161/55161fig1.jpg" /> 
Figure 1: Example of particles from category: Fragments.&#160; <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/55161/55161fig2.jpg" /> 
Figure 2: Example of particles from category: Films.&#160; <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/55161/55161fig3.jpg" /> 
Figure 3: Example of particles from category: Pellets.&#160; <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/55161/55161fig4.jpg" /> 
Figure 4: Example of particles from category: Granules. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/55161/55161fig5.jpg" /> 
Figure 5: Example of particles from category: Filaments.&#160; <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/55161/55161fig6.jpg" /> 
Figure 6: Example of particles from category: Foams. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Sampling distance [km]</td>
			<td>2</td>
		</tr>
		<tr>
			<td>Manta width [km]</td>
			<td>0.0006</td>
		</tr>
		<tr>
			<td>Sampling area [km2]</td>
			<td>0.0012</td>
		</tr>
	</tbody>
</table>
Table 2: Example of data from survey, used for calculation of microplastic particles per km2.
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td></td>
			<td>No</td>
			<td>No/km2</td>
		</tr>
		<tr>
			<td>fragments</td>
			<td>301</td>
			<td>250833</td>
		</tr>
		<tr>
			<td>films</td>
			<td>45</td>
			<td>37500</td>
		</tr>
		<tr>
			<td>pellets</td>
			<td>15</td>
			<td>12500</td>
		</tr>
		<tr>
			<td>granules</td>
			<td>8</td>
			<td>6667</td>
		</tr>
		<tr>
			<td>foams</td>
			<td>33</td>
			<td>27500</td>
		</tr>
		<tr>
			<td>filaments</td>
			<td>223</td>
			<td>185833</td>
		</tr>
	</tbody>
</table>
Table 3: Example of results from survey, where the categorized data into 6 groups are counted and normalized per km2 (No - number of particles).
<img alt="Figure 7" src="/files/ftp_upload/55161/55161fig7.jpg" /> 
Figure 7: Example of representative results after visual categorization of particles (No -&#160;number of particles). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>Index Region</td>
			<td>Area [mm&#178;]</td>
			<td>Maximum length [mm]</td>
		</tr>
		<tr>
			<td>1</td>
			<td>8.010</td>
			<td>5.506</td>
		</tr>
		<tr>
			<td>2</td>
			<td>10.517</td>
			<td>5.628</td>
		</tr>
		<tr>
			<td>3</td>
			<td>12.185</td>
			<td>5.429</td>
		</tr>
		<tr>
			<td>4</td>
			<td>3.367</td>
			<td>3.367</td>
		</tr>
		<tr>
			<td>5</td>
			<td>2.475</td>
			<td>2.155</td>
		</tr>
		<tr>
			<td>6</td>
			<td>1.809</td>
			<td>2.943</td>
		</tr>
		<tr>
			<td>7</td>
			<td>6.604</td>
			<td>5.238</td>
		</tr>
		<tr>
			<td>8</td>
			<td>5.779</td>
			<td>4.037</td>
		</tr>
		<tr>
			<td>9</td>
			<td>4.472</td>
			<td>3.791</td>
		</tr>
		<tr>
			<td>10</td>
			<td>16.907</td>
			<td>5.355</td>
		</tr>
		<tr>
			<td>11</td>
			<td>7.246</td>
			<td>3.733</td>
		</tr>
		<tr>
			<td>12</td>
			<td>7.867</td>
			<td>4.622</td>
		</tr>
		<tr>
			<td>13</td>
			<td>6.411</td>
			<td>5.056</td>
		</tr>
		<tr>
			<td>14</td>
			<td>3.281</td>
			<td>3.070</td>
		</tr>
		<tr>
			<td>15</td>
			<td>12.937</td>
			<td>5.554</td>
		</tr>
		<tr>
			<td>16</td>
			<td>6.709</td>
			<td>3.716</td>
		</tr>
	</tbody>
</table>
Table 4: Example of image analysis results where area [mm2] and maximum length [mm] of each particle are measured.
<img alt="Figure 8" src="/files/ftp_upload/55161/55161fig8.jpg" /> 
Figure 8: Example of image acquired a) before and b) after image analysis of particles with image analysis software. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" src="/files/ftp_upload/55161/55161fig9.jpg" /> 
Figure 9: Example of a spectra measured on a selected particle with marked peaks and their wavelengths [cm-1]. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" src="/files/ftp_upload/55161/55161fig10.jpg" /> 
Figure 10: Example of comparison of acquired spectra from selected particle to best match from the ATR-FTIR spectra library.&#160; <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55161/55161fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis at JoVE.com

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

The protocol below describes the methodology for: microplastics sampling on the sea surface, separation of microplastic and chemical identification of particles. This protocol is in line with the recommendations for microplastics monitoring published by the MSFD Technical Subgroup on Marine Litter.

Microplastic pollution in the marine environment is a scientific topic that has received increasing attention over the last decade. The majority of ...

protocol-for-microplastics-sampling-on-sea-surface-sample

Nanyang Technological University

Research

JoVE Journal

Environment

49.2K Views.  Institute for water of the Republic of Slovenia. The protocol below describes the methodology for: microplastics sampling on the sea surface, separation of microplastic and chemical identification of particles. This protocol is in line with the recommendations for microplastics monitoring published by the MSFD Technical Subgroup on Marine Litter.

Video: Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Use of Chironomidae (Diptera) Surface-Floating Pupal Exuviae as a Rapid Bioassessment Protocol for Water Bodies

Rapid bioassessment protocols using benthic macroinvertebrate assemblages have been successfully used to assess human impacts on water quality. Unfortunately, traditional benthic larval sampling methods, such as the dip-net, can be time-consuming and expensive. An alternative protocol involves collection of Chironomidae surface-floating pupal exuviae (SFPE). Chironomidae is a species-rich family of flies (Diptera) whose immature stages typically occur in aquatic habitats. Adult chironomids emerge from the water, leaving their pupal skins, or exuviae, floating on the water&#8217;s surface. Exuviae often accumulate along banks or behind obstructions by action of the wind or water current, where they can be collected to assess chironomid diversity and richness. Chironomids can be used as important biological indicators, since some species are more tolerant to pollution than others. Therefore, the relative abundance and species composition of collected SFPE reflect changes in water quality. Here, methods associated with field collection, laboratory processing, slide mounting, and identification of chironomid SFPE are described in detail. Advantages of the SFPE method include minimal disturbance at a sampling area, efficient and economical sample collection and laboratory processing, ease of identification, applicability in nearly all aquatic environments, and a potentially more sensitive measure of ecosystem stress. Limitations include the inability to determine larval microhabitat use and inability to identify pupal exuviae to species if they have not been associated with adult males.

Use of Chironomidae Diptera Surface-Floating Pupal Exuviae as a Rapid Bioassessment Protocol for Water Bodies

Rapid bioassessment protocols using benthic macroinvertebrates are often used to monitor and assess water quality. An efficient protocol involves collections of Chironomidae surface-floating pupal exuviae (SFPE). Here, techniques for field collection, laboratory processing, slide mounting, and identification of Chironomidae SFPE are described.

Rapid bioassessment protocols using benthic macroinvertebrate assemblages have been successfully used to assess human impacts on water quality. ...

Protocol for Measuring the Thermal Properties of a Supercooled Synthetic Sand-water-gas-methane Hydrate Sample

Methane hydrates (MHs) are present in large amounts in the ocean floor and permafrost regions. Methane and hydrogen hydrates are being studied as future energy resources and energy storage media. To develop a method for gas production from natural MH-bearing sediments and hydrate-based technologies, it is imperative to understand the thermal properties of gas hydrates.
The thermal properties' measurements of samples comprising sand, water, methane, and MH are difficult because the melting heat of MH may affect the measurements. To solve this problem, we performed thermal properties' measurements at supercooled conditions during MH formation. The measurement protocol, calculation method of the saturation change, and tips for thermal constants' analysis of the sample using transient plane source techniques are described here.
The effect of the formation heat of MH on measurement is very small because the gas hydrate formation rate is very slow. This measurement method can be applied to the thermal properties of the gas hydrate-water-guest gas system, which contains hydrogen, CO2, and ozone hydrates, because the characteristic low formation rate of gas hydrate is not unique to MH. The key point of this method is the low rate of phase transition of the target material. Hence, this method may be applied to other materials having low phase-transition rates.

We present a protocol for measuring the thermal properties of synthetic hydrate-bearing sediment samples comprising sand, water, methane, and methane hydrate.

Methane hydrates (MHs) are present in large amounts in the ocean floor and permafrost regions. Methane and hydrogen hydrates are being studied as future ...

Clean Sampling and Analysis of River and Estuarine Waters for Trace Metal Studies

Most of the trace metal concentrations in ambient waters obtained a few decades ago have been considered unreliable owing to the lack of contamination control. Developments of some techniques aiming to reduce trace metal contamination in the last couple of decades have resulted in concentrations reported now being orders of magnitude lower than those in the past. These low concentrations often necessitate preconcentration of water samples prior to instrumental analysis of samples. Since contamination can appear in all phases of trace metal analyses, including sample collection (and during preparation of sampling containers), storage and handling, pretreatments, and instrumental analysis, specific care needs to be taken in order to reduce contamination levels at all steps. The effort to develop and utilize "clean techniques" in trace metal studies allows scientists to investigate trace metal distributions and chemical and biological behavior in greater details. This advancement also provides the required accuracy and precision of trace metal data allowing for environmental conditions to be related to trace metal concentrations in aquatic environments.
This protocol that is presented here details needed materials for sample preparation, sample collection, sample pretreatment including preconcentration, and instrumental analysis. By reducing contamination throughout all phases mentioned above for trace metal analysis, much lower detection limits and thus accuracy can be achieved. The effectiveness of "clean techniques" is further demonstrated using low field blanks and good recoveries for standard reference material. The data quality that can be obtained thus enables the assessment of trace metal distributions and their relationships to environmental parameters.

Special care using "clean techniques" is required to properly collect and process water samples for trace metal studies in aquatic environments. A protocol for sampling, processing, and analytical procedures with the aim of obtaining reliable environmental monitoring data and results with high sensitivity for detailed trace metal studies is presented.

Most of the trace metal concentrations in ambient waters obtained a few decades ago have been considered unreliable owing to the lack of contamination ...

Modification and Application of a Leaf Blower-vac for Field Sampling of Arthropods

Rice fields host a large diversity of arthropods, but investigating their population dynamics and interactions is challenging. Here we describe the modification and application of a leaf blower-vac for suction sampling of arthropod populations in rice. When used in combination with an enclosure, application of this sampling device provides absolute estimates of the populations of arthropods as numbers per standardized sampling area. The sampling efficiency depends critically on the sampling duration. In a mature rice crop, a two-minute sampling in an enclosure of 0.13 m2 yields more than 90% of the arthropod population. The device also allows sampling of arthropods dwelling on the water surface or the soil in rice paddies, but it is not suitable for sampling fast flying insects, such as predatory Odonata or larger hymenopterous parasitoids. The modified blower-vac is simple to construct, and cheaper and easier to handle than traditional suction sampling devices, such as D-vac. The low cost makes the modified blower-vac also accessible to researchers in developing countries.

Assessment of arthropod abundance in crops is critical for investigating population dynamics and species interactions. Here we describe the modification and application of a leaf blower-vac for suction sampling of arthropods in rice.

Rice fields host a large diversity of arthropods, but investigating their population dynamics and interactions is challenging. Here we describe the ...

Protocol for Assessing the Relative Effects of Environment and Genetics on Antler and Body Growth for a Long-lived Cervid

Cervid phenotype can be placed into one of two categories: efficiency, which promotes survival over extravagant morphometric growth, and luxury, which promotes growth of large weaponry and body size. Populations of the same species display each phenotype depending on environmental conditions. Although antler and body size of male white-tailed deer (Odocoileus virginianus) varies by physiographic region in Mississippi, USA and is strongly correlated with regional variation in nutritional quality, the effects of population-level genetics from native stocks and previous re-stocking efforts cannot be disregarded. This protocol describes how we designed a controlled study, where other factors that influence phenotype, such as age and nutrition, are controlled. We brought wild-caught pregnant females and six-month-old fawns from three distinct physiographic regions in Mississippi, USA to the Mississippi State University Rusty Dawkins Memorial Deer Unit. Deer from the same region were bred to produce a second generation of offspring, allowing us to assess generational responses and maternal effects. All deer ate the same high-quality (20% crude protein deer pellet) diet ad libitum. We uniquely marked each neonate and recorded body mass, hind foot, and total body length. Each subsequent fall, we sedated individuals via remote injection and sampled the same morphometrics plus antlers of adults. We found that all morphometrics increased in size from first to second generation, with full compensation of antler size (regional variation no longer present) and partial compensation of body mass (some evidence of regional variation) evident in the second generation. Second generation males that originated from our poorest quality soil region displayed about a 40% increase in antler size and about a 25% increase in body mass when compared to their wild harvested counterparts. Our results suggest phenotypic variation of wild male white-tailed deer in Mississippi are more related to differences in nutritional quality than population-level genetics.

Phenotypic differences among cervid populations may be related to population-level genetics or nutrition; discerning which is difficult in the wild. This protocol describes how we designed a controlled study where nutritional variation was eliminated. We found that phenotypic variation of male white-tailed deer was more limited by nutrition than genetics.

Cervid phenotype can be placed into one of two categories: efficiency, which promotes survival over extravagant morphometric growth, and luxury, which ...

Dispersion of Nanomaterials in Aqueous Media: Towards Protocol Optimization

The sonication process is commonly used for de-agglomerating and dispersing nanomaterials in aqueous based media, necessary to improve homogeneity and stability of the suspension. In this study, a systematic step-wise approach is carried out to identify optimal sonication conditions in order to achieve a stable dispersion. This approach has been adopted and shown to be suitable for several nanomaterials (cerium oxide, zinc oxide, and carbon nanotubes) dispersed in deionized (DI) water. However, with any change in either the nanomaterial type or dispersing medium, there needs to be optimization of the basic protocol by adjusting various factors such as sonication time, power, and sonicator type as well as temperature rise during the process. The approach records the dispersion process in detail. This is necessary to identify the time points as well as other above-mentioned conditions during the sonication process in which there may be undesirable changes, such as damage to the particle surface thus affecting surface properties. Our goal is to offer a harmonized approach that can control the quality of the final, produced dispersion. Such a guideline is instrumental in ensuring dispersion quality repeatability in the nanoscience community, particularly in the field of nanotoxicology.

Here, we present a step-wise protocol for the dispersion of nanomaterials in aqueous media with real-time characterization to identify the optimal sonication conditions, intensity, and duration for improved stability and uniformity of nanoparticle dispersions without impacting the sample integrity.

The sonication process is commonly used for de-agglomerating and dispersing nanomaterials in aqueous based media, necessary to improve homogeneity and ...

The Hawaii Protocol for Scientific Monitoring of Coffee Berry Borer: a Model for Coffee Agroecosystems Worldwide

Coffee berry borer (CBB) is the most devastating insect pest for coffee crops worldwide. We developed a scientific monitoring protocol that is aimed at capturing and quantifying the dynamics and impact of this invasive insect pest as well as the development of its host plant across a heterogeneous landscape. The cornerstone of this comprehensive monitoring system is timely georeferenced data collection on CBB movement, coffee berry infestation, mortality by the fungus Beauveria bassiana, and coffee plant phenology via a mobile electronic data recording application. This electronic data collection system allows field records to be georeferenced through built-in global positioning systems, and is backed by a network of weather stations and records of farm management practices. Comprehensive monitoring of CBB and host plant dynamics is an essential part of an area-wide project in Hawaii to aggregate landscape-level data for research to improve management practices. Coffee agroecosystems in other parts of the world that experience highly variable environmental and socioeconomic factors will also benefit from implementing this protocol, in that it will drive the development of customized integrated pest management (IPM) to manage CBB populations.

Comprehensive monitoring of coffee berry borer and host plant dynamics is essential for aggregating landscape-level data to improve management of this invasive pest. Here, we present a protocol for scientific monitoring of coffee berry borer movement, infestation, mortality, coffee plant phenology, weather, and farm management via a mobile electronic data recording application.

Coffee berry borer (CBB) is the most devastating insect pest for coffee crops worldwide. We developed a scientific monitoring protocol that is aimed at ...

Sampling, Sorting, and Characterizing Microplastics in Aquatic Environments with High Suspended Sediment Loads and Large Floating Debris

The ubiquitous presence of plastic debris in the ocean is widely recognized by the public, scientific communities, and government agencies. However, only recently have microplastics in freshwater systems, such as rivers and lakes, been quantified. Microplastic sampling at the surface usually consists of deploying drift nets behind either a stationary or moving boat, which limits the sampling to environments with low levels of suspended sediments and floating or submerged debris. Previous studies that employed drift nets to collect microplastic debris typically used nets with &#8805;300 &#181;m mesh size, allowing plastic debris (particles and fibers) below this size to pass through the net and elude quantification. The protocol detailed here enables: 1) sample collection in environments with high suspended loads and floating or submerged debris and 2) the capture and quantification of microplastic particles and fibers &lt;300 &#181;m. Water samples were collected using a peristaltic pump in low-density polyethylene (PE) containers to be stored before filtering and analysis in the lab. Filtration was done with a custom-made microplastic filtration device containing detachable union joints that housed nylon mesh sieves and mixed cellulose ester membrane filters. Mesh sieves and membrane filters were examined with a stereomicroscope to quantify and separate microplastic particulates and fibers. These materials were then examined using a micro-attenuated total reflectance Fourier transform infrared spectrometer (micro ATR-FTIR) to determine microplastic polymer type. Recovery was measured by spiking samples using blue PE particulates and green nylon fibers; percent recovery was determined to be 100% for particulates and 92% for fibers. This protocol will guide similar studies on microplastics in high velocity rivers with high concentrations of sediment. With simple modifications to the peristaltic pump and filtration device, users can collect and analyze various sample volumes and particulate sizes.

Most microplastic research to date has occurred in marine systems where suspended solid levels are relatively low. Focus is now shifting to freshwater systems, which may feature high sediment loads and floating debris. This protocol addresses collecting and analyzing microplastic samples from aquatic environments that contain high suspended solid loads.

The ubiquitous presence of plastic debris in the ocean is widely recognized by the public, scientific communities, and government agencies. However, only ...

Data Collection on Marine Litter Ingestion in Sea Turtles and Thresholds for Good Environmental Status

The following protocol is intended to respond to the requirements set by the European Union&#39;s Marine Strategy Framework Directives (MSFD) for the D10C3 Criteria reported in the Commission Decision (EU), related to the amount of litter ingested by marine animals. Standardized methodologies for extracting litter items ingested from dead sea turtles along with guidelines on data analysis are provided. The protocol starts with the collection of dead sea turtles and classification of samples according to the decomposition status. Turtle necropsy must be performed in authorized centers and the protocol described here explains the best procedure for gastrointestinal (GI) tract isolation. The three parts of the GI (esophagus, stomach, intestine) should be separated, opened lengthways and contents filtered using a 1 mm mesh sieve. The article describes the classification and quantification of ingested litter, classifying GI contents into seven different categories of marine litter and two categories of natural remains. The quantity of ingested litter should be reported as total dry mass (weight in grams, with two decimal places) and abundance (number of items). The protocol proposes two possible scenarios to achieve the Good Environmental Status (GES). First: &#34;There should be less than X% of sea turtles having Y g or more plastic in the GI in samples of 50-100 dead turtles from each sub-region&#34;, where Y is the average weight of plastic ingested and X% is the percentage of sea turtles with more weight (in grams) of plastic than Y. The second one, which considers the food remain versus plastic as a proxy of individual health, is: &#34;There should be less than X% of sea turtles having more weight of plastic (in grams) than food remains in the GI in samples of 50-100 dead turtles from each sub-region&#34;.

The protocol focuses on the collection of sea turtle samples, describing all the steps from the animal recovery and necropsy to the classification and quantification of ingested marine litter. Moreover, the representative results show how to use the collected data to elaborate the possible thresholds for Good Environmental Status.

The following protocol is intended to respond to the requirements set by the European Union&#39;s Marine Strategy Framework Directives (MSFD) for the ...

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Satellite observations offer a great approach to investigate the features of major marine parameters, including sea surface chlorophyll (CHL), sea surface temperature (SST), sea surface height (SSH), and factors derived from these parameters (e.g., fronts). This study shows a step-by-step procedure to use satellite observations to describe major parameters and their relationships in seasonal and anomalous fields. This method is illustrated using satellite datasets from 2002&#8211;2017 that were used to describe the surface features of the South China Sea (SCS). Due to cloud coverage, monthly averaged data were used in this study. The empirical orthogonal function (EOF) was applied to describe the spatial distribution and temporal variabilities of different factors. The monsoon wind dominates the variability in the basin. Thus, wind from the reanalysis dataset was used to investigate its driving force on different parameters. The seasonal variability in CHL was prominent and significantly correlated with other factors in a majority of the SCS. In winter, a strong northeast monsoon induces a deep mixed layer and high level of chlorophyll throughout the basin. Significant correlation coefficients were found among factors at the seasonal cycle. In summer, high CHL levels were mostly found in the western SCS. Instead of a seasonal dependence, the region was highly dynamic, and factors correlated significantly in anomalous fields such that unusually high CHL levels were associated with abnormally strong winds and intense frontal activities. The study presents a step-by-step procedure to use satellite observations to describe major parameters and their relationships in seasonal and anomalous fields. The method can be applied to other global oceans and will be helpful for understanding marine dynamics.

Sea surface chlorophyll, temperature, sea level height, wind, and front data obtained or derived from satellite observations offer an effective way to characterize the ocean. Presented is a method for the comprehensive study of these data, including overall average, seasonal cycle, and intercorrelation analyses, to fully understand regional dynamics and&#160;ecosystems.

Satellite observations offer a great approach to investigate the features of major marine parameters, including sea surface chlorophyll (CHL), sea surface ...