Name: automatic image processing to determine the community size structure of riverine macroinvertebrates
Uploaded: 2023-01-13T12:50:00
Description: Watch this Scientific Journal Video about Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates at JoVE.com

This work was supported by the Spanish Ministry of Science, Innovation and Universities (grant number RTI2018-095363-B-I00). We thank the CERM-UVic-UCC members &#200;lia Bretxa, Anna Costarrosa, Laia Jim&#233;nez, Mar&#237;a Isabel Gonz&#225;lez, Marta Jutglar, Francesc Llach, and N&#250;ria Sellar&#232;s for their work in macroinvertebrate field sampling and laboratory sorting and David Albesa for collaborating in the sample scanning. We finally thank Josep Maria Gili and the Institut de Ci&#232;ncies del Mar (ICM-CSIC) for the use of the laboratory facilities and scanner device.

NOTE: The protocol described here is based on the system developed by Gorsky et al.27 for marine mesozooplankton. A specific description of the scanner (ZooSCAN), scanning software (VueScan 9x64 [9.5.09]), image processing software (Zooprocess, ImageJ), and automatic identification software (Plankton Identifier) steps can be found in previous references32,33. To best adjust the sizes of the benthic macroinvertebrates with respect to the me...

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The adaptation of the methodology described by Gorsky et al. 2010 for riverine macroinvertebrates allows for high classification accuracy in estimating the community size structure in freshwater macroinvertebrates. The results suggest that the protocol can reduce the time for estimating the individual size structure in a sample to about 1 hour. Thus, the proposed protocol is intended to promote the routine use of macroinvertebrate size spectra as a fast and integrative bioindicator to assess the impact of perturbations i...

Benthic macroinvertebrates are broadly used as bioindicators to determine the ecological status of water bodies1. Most indices to describe macroinvertebrate communities focus on taxonomic metrics. However, new bioassessment tools that integrate body size are encouraged to provide an alternative or complementary perspective to taxonomic approaches2,3.
Body size is considered a metatrait that is related to other vital traits such as metabolism, growth, respiration, and movement4. Furthermore, body size can determine trophic position and interactions5. The relationship between individual body size and the normalized biomass (or abundance) by size class in a community is defined as the size spectrum6 and follows the general pattern of a linear decrease in normalized biomass as individual size increases on a logarithmic scale7. The slope of this linear relationship has been extensively studied theoretically, and empirical studies across ecosystems have used it as an ecological indicator of the community size structure4. Another synthetic indicator of community size structure that has been successfully used in biodiversity-ecosystem functioning studies is community size diversity, which is represented as the Shannon index of the size classes of the size spectrum or its analog, which is calculated based on the individual size distributions8.
In freshwater ecosystems, the size structure of different faunal groups is used as an ataxic indicator to assess the response of biotic communities to environmental gradients9,10,11 and to anthropogenic perturbations12,13,14,15,16. Macroinvertebrates are not an exception, and their size structure also responds to environmental changes17,18 and anthropogenic perturbations, such as mining19, land use20, or&#160;nitrogen (N) and phosphorus (P) enrichment20,21,22. However, measuring hundreds of individuals to describe the community size structure is a tedious and time-consuming task that is often avoided as a routine measurement in laboratories due to a lack of time. Thus, several semi-automatic or automatic imaging methods to classify and measure specimens have been developed23,24,25,26. However, most of these methods are focused on taxonomic classification more than on the individual size of the organisms and are not ready to use for all kinds of macroinvertebrates. In marine plankton ecology, a scanning image analysis system has been extensively used to determine the size and taxonomic composition of zooplankton communities27,28,29,30,31. This instrument can be found in several marine institutes worldwide, and it is used to scan preserved zooplankton samples to obtain high-resolution digital images of the entire sample. The present protocol adapts the use of this instrument to estimate the macroinvertebrate community size spectrum in rivers in a rapid automatic manner without investing in creating a new device.
The protocol consists of scanning a sample and processing the whole image to automatically obtain single images (i.e., vignettes) of the objects in the sample. Several measures of shape, size, and grey-level features characterize each object and allow for the automatic classification of the objects into categories, which are then validated by an expert. The individual size of each organism is calculated using the ellipsoidal biovolume (mm3), which is derived from the area of the organism measured in pixels. This allows for obtaining the size spectrum of the sample in a rapid manner. To the best of our knowledge, this scanning imaging system has only been used to process mesozooplankton samples, but the device may potentially allow for working with freshwater benthic macroinvertebrates.
The overall goal of this study is, therefore, to introduce a method to rapidly obtain the individual size of preserved river macroinvertebrates by adapting an existing protocol previously used with marine mesozooplankton27,32,33. The procedure consists of&#160;using a semi-automatic approach that operates with a scanning device to scan water samples and three open software to process the scanned images. An adapted protocol to scan, detect, and identify digitized river macroinvertebrates to automatically acquire the community size structure and related size metrics is herein presented. The assessment of the procedure and guidelines to enhance the efficiency are also presented based on 42 scanned images of riverine macroinvertebrate samples collected from three basins in the North-Eastern (NE) Iberian Peninsula (Ter, Segre-Ebre, and Bes&#242;s).
The samples were collected at 100 m river stretches following the protocol for field sampling and laboratory analysis of benthic river macroinvertebrates in fordable rivers from the Spanish Government34. The samples were collected with a surber sampler (frame: 0.3 m x 0.3 m, mesh: 250 &#181;m) following a multi-habitat survey. In the laboratory, the samples were cleaned and sieved through a 5 mm and a 500 &#181;m mesh to obtain two subsamples: a coarse subsample (5 mm mesh) and a fine subsample (500 &#181;m mesh), which were stored in separate vials and preserved in 70% ethanol. Separating the sample into two size fractions allows for a better estimation of the community size structure, since large organisms are rarer and fewer than the small organisms. Otherwise, the scanned sample has a biased representation of the large size fraction.

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	<tbody>
		<tr>
			<td>Beaker</td>
			<td>Labbox</td>
			<td></td>
			<td>Other containers could be used</td>
		</tr>
		<tr>
			<td>Dionized water</td>
			<td>Icopresa</td>
			<td>&#160;8420239600123</td>
			<td>To dilute the ethanol</td>
		</tr>
		<tr>
			<td>Funnel</td>
			<td>Vitlab</td>
			<td>41094</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass vials 8 ml</td>
			<td>Labbox</td>
			<td>SVSN-C10-195</td>
			<td>1 vial/subsample</td>
		</tr>
		<tr>
			<td>ImageJ Software&#160;</td>
			<td>Free access</td>
			<td></td>
			<td>Version 4.41o/ Image processing software</td>
		</tr>
		<tr>
			<td>Large frame</td>
			<td>Hydroptic</td>
			<td>&#160;Provided by ZooScan</td>
			<td>24.5 cm x 15.8 cm</td>
		</tr>
		<tr>
			<td>Monalcol 96 (Ethanol 96)</td>
			<td>Montplet</td>
			<td>1050JE001</td>
			<td></td>
		</tr>
		<tr>
			<td>Plankton Identifier Software</td>
			<td>Free access</td>
			<td></td>
			<td>Version 1.2.6/ Automatic identification software</td>
		</tr>
		<tr>
			<td>Sieve</td>
			<td>Cisa</td>
			<td>26852.2</td>
			<td>Nominal aperture 500&#181; and nominal aperture 0,5 cm</td>
		</tr>
		<tr>
			<td>Tweezers</td>
			<td>Bondline</td>
			<td>B5SA</td>
			<td>Stainless, anti-magnetic, anti-acid</td>
		</tr>
		<tr>
			<td>VueScan 9 x 64 (9.5.09) Software</td>
			<td>Hydroptic</td>
			<td></td>
			<td>Version 9.0.51/ Sacn software</td>
		</tr>
		<tr>
			<td>Wooden needle</td>
			<td></td>
			<td></td>
			<td>Any plastic or wood needle can be used</td>
		</tr>
		<tr>
			<td>Zooprocess Software&#160;</td>
			<td>Free access</td>
			<td></td>
			<td>Version 7.14/Image processing software</td>
		</tr>
		<tr>
			<td>ZooScan&#160;</td>
			<td>Hydroptic</td>
			<td>54</td>
			<td>Version III/ Scanner</td>
		</tr>
	</tbody>
</table>

automatic image processing to determine the community size structure of riverine macroinvertebrates

Body size is an important functional trait that can be used as a bioindicator to assess the impacts of perturbations in natural communities. Community size structure responds to biotic and abiotic gradients, including anthropogenic perturbations across taxa and ecosystems. However, the manual measurement of small-bodied organisms such as benthic macroinvertebrates (e.g., &gt;500 &#181;m to a few centimeters long) is time-consuming. To expedite the estimation of community size structure, here, we developed a protocol to semi-automatically measure the individual body size of preserved river macroinvertebrates, which are one of the most commonly used bioindicators for assessing the ecological status of freshwater ecosystems. This protocol is adapted from an existing methodology developed to scan marine mesozooplankton with a scanning system designed for water samples. The protocol consists of three main steps: (1) scanning subsamples (fine and coarse sample size fractions) of river macroinvertebrates and processing the digitized images to individualize each detected object in each image; (2) creating, evaluating, and validating a learning set through artificial intelligence to semi-automatically separate the individual images of macroinvertebrates from detritus and artifacts in the scanned samples; and (3) depicting the size structure of the macroinvertebrate communities. In addition to the protocol, this work includes the calibration results and enumerates several challenges and recommendations to adapt the procedure to macroinvertebrate samples and to consider for further improvements. Overall, the results support the use of the presented scanning system for the automatic body size measurement of river macroinvertebrates and suggest that the depiction of their size spectrum is a valuable tool for the rapid bioassessment of freshwater ecosystems.

Acquisition of digital images of macroinvertebrate samples 
Scanning nuances: Ethanol deposition in the scan tray 
While testing the system for macroinvertebrates, several scans were of poor quality. A dark saturated area in the background prevented normal processing of the image and the measurement of the individual sizes of the macroinvertebrates (Figure 2). Several reasons have been given for the appearance of saturated areas in the background o...

Watch this Scientific Journal Video about Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates at JoVE.com

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

The article is based on the creation of an adapted protocol to scan, detect, sort, and identify digitized objects corresponding to benthic river macroinvertebrates using a semi-automatic imaging procedure. This procedure allows the acquisition of the individual size distributions and size metrics of a macroinvertebrate community in about 1 h.

Body size is an important functional trait that can be used as a bioindicator to assess the impacts of perturbations in natural communities. Community ...

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