10: The Sandy Intertidal- the microscopic Meiofauna
- Page ID
- 164668
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)The Meiofauna
Today’s lab will sample a region of Monterey Beach, from the water’s edge up the beach some appropriate distance (~10 meters). You will examine two different regions of the beach and at two different depths. You will then assess the biodiversity of each location and depth.
Your instructor will find a suitable site and lay down the transect tape. One sample site will be at the water’s edge, the other some distance up the beach. Start by getting a temperature profile from the surface down to the maximum depth of the thermometer. At each site, you will sample the surface sand (0-10 cm) and deeper sand (10-20 cm). Each sample will be a 200 ml sample of sand collected and then specially rinsed to get the meiofauna off the sand.
They don’t want to leave the sand grains and will actively hold on, so we need to shock them off with a quick rinse in freshwater. After about 5-10 seconds in freshwater, you’ll pour the water, which now contains the organisms, through a very small sieve (44-µm mesh) that will trap them on the mesh. Using seawater, quickly give them a gentle rinse to help them survive. Repeat the osmotic shock 2 more times for each sample to get all the organisms off. Then give a final rinse of the sieve with sea water and then carefully rinse the sample into white 125 ml sample bottles. Carefully label all bottles with the site and depth. Once you have taken your first samples from your site and each depth, try to take another sample from right next to the first as a replicate. This will allow you to compare the two samples and get an average, as well as compare the sites and depths.
Back in the lab, we will use the dissection and compound microscopes to examine and count the organisms found in the various samples. You will use some biotic measurements, such as density or frequency, to describe and analyze your data, and we will add in species richness and evenness, which combine to form the very useful Biodiversity Index. Calculating biodiversity is not difficult, but like most statistics, it can be very tedious and error-prone, so I recommend using a computerized Excel-based calculator that I have developed and is posted on the class website. This will not only easily determine the biodiversity of an area, but can also statistically compare two different areas and help determine if one area has a higher biodiversity than the other. Just looking at the two numbers can’t tell you if one number is higher than the other is truly significant, but the statistical test can.
Mixed meiofauna creatures. Image courtesy of Jeroen Ingels, FSUCML. NOAA. https://oceanexplorer.noaa.gov/facts...cope-hires.jpg
Flatworms
Polychaete Worms. Segmented worms that often have small setae or bristles on each segment.
Foraminifera shells. Single-celled amoebas that live inside shells.
Nematode Worms. These "round worms" are some of the more common creatures in the meiofauna.
Copepods are some of the most common arthropods in the water and the meiofauna.
A gastrotrich worm. They usually have two "toes" on the posterior end.
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Tardigrade, or "water bears".
Estimation Methods and Subsampling
We often have to come up with methods to get good estimates of populations. As we talked about in our statistics lab, if we design our study well, a carefully collected sample of the population should hopefully be able to help us answer our question. When counting microscopic organisms, we often find we can’t even count everything from the sample we took! What we need is a reasonable method for subsampling our sample. We are going to take a small, countable portion of our sample, and then use simple math to help us get an estimate of the total sample count. One of the most important issues is making sure any subsample you take is a representative subsample of the whole sample. For instance, if you had a lot of animals that settled to the bottom of your sample jar, you would want to make sure you suspended them in the sample before subsampling. A few gentle swirls or inversions of the jar are often all you need to mix the sample back up. You also need to know exactly how much sample you are working with, so your first goal will be to measure all the sample volumes with a graduated cylinder.
Splitting samples
For example, let's say we collected 40 ml of sample from our sand sampling for a site. The first option might be to put it all into a petri dish and see what we can see, but you might find out that that is too much liquid for one dish, or that there are too many creatures in the sample to count. We can subsample that 40 ml by splitting the sample into two 20 ml samples. If you then count 14 worms in your subsample, you can estimate there are 2 X 14 = 28 worms in your whole sample of 40 ml (two 20 ml samples X 14 estimated worms in each). It is not exact, but often good enough to detect differences in samples.
Subsampling the subsample
Let’s say you can’t even count a whole subsample: you look into the dissection scope and see that you can only count a few fields of view before becoming overwhelmed. You can see how many fields of view would make up a whole dish at a particular magnification, then just look at a few and multiply. For example, let’s say you find that the 16x zoom is a good magnification for seeing your creatures. At 16x, each circular field of view is 145.2 of the standard, large petri dish. So, if you counted 27 dinoflagellates, then you could estimate that there were 27 x 45.2 = 1220 dinoflagellates in the entire petri dish
MPC’s Leica dissection microscope estimation factors for different magnifications.
The more fields of view you count, the more accurate the estimation will be, so try to count as many as time will allow. The table on the next page has the multiplication values to use with 3, 5, or 10 counted fields of view.
MPC’s Leica dissection microscope estimation factors for different numbers of counts at different magnifications.
Using drops as a subsample on a compound microscope
If you need to make compound microscope slides to count very small samples, you can think of a slide as a subsample. A standard drop is 1/20th of a ml (0.05 drops per ml). If you had 53 ml of sample, and made one slide it would represent 1/1,060th of your whole sample (53 x 20 = 1,060). For example, if you counted 43 diatoms in one slide, your estimate would be 43 x 53 x 20 = 45,580 diatoms in your whole sample! These estimates are obviously very sensitive to the numbers you count, as you can end up multiplying them by huge factors. Careful counting of several replicates can give you average estimates that can moderate the lows and highs of one or two subsamples.
The Assignment:
- Using the class data posted on Canvas, calculate the average number of each type of creature for those that had more than one number in the box.
- Once you have the average number of each creature in each of the four sample locations (Beach Surface, Beach Deep, Ocean Surface, Ocean Deep), count the number of different creatures found in each location. This is called the Species Richness and is simply a count of the number of different things. So you should have a Richness # for all four sample locations.
- GRAPH the Species Richness numbers on a graph, so that the x-axis is the four locations and the y-axis is the richness value. OR
- GRAPH the total number of each creature found in the locations so that the x-axis is the four locations and the y-axis is the total number of each creature. (Bar or column graphs are best)
- What was your original hypothesis about which area you thought would have the highest biodiversity? Was it supported or refuted by the data?
- After looking at the data results, what is an interesting question that now comes to mind that you could research as a next step, if we were going to do a second experiment?
You will turn in your answers for the items above on Canvas in one document (Google or Word doc).
Data Table
Count and record the number of individuals of the different groups.
Site_______________________ Depth _____________________
Sand Sample size ___________
Taxa Count Total per 200 ml
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Polychaete worms |
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Nematodes |
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Rotifers |
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Dinoflagellates |
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Copepods |
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Flatworms |
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Foraminifera |
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Protists |
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Collembola |
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Microplastics |
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Tardigrades |
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Mites |
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Images:
Thumbnail image: “Syllidae ANN_GUAOFF13_Meiofauna” by INVEMAR_BEM, CC BY-NC-SA 2.0
Polychaete Worm: © Hans Hillewaert "Creative Commons">Creative Commons Attribution-Share Alike 4.0 International
“Spionidae ANN_GUAOFF13_Meiofauna” by INVEMAR_BEM, CC BY-NC-SA 2.0
“Foraminiferos Col10-2018 - Meiofauna” by INVEMAR_BEM, CC BY-NC-SA 2.0
\“Nematodos COL10-2018 - BoxCore - Meiofauna” by INVEMAR_BEM, CC BY-NC-SA 2.0
“Foraminiferos Col10-2018 - Meiofauna” by INVEMAR_BEM, CC BY-NC-SA 2.0
“Pontellidae” by Christophe Quintin, CC BY-NC 2.0.
Gastrotrich: MarinFaunistik, CC BY-SA 3.0 <https://creativecommons.org/licenses/by-sa/3.0>, via Wikimedia Commons.
Tardigrae: Bob Goldstein and Vicky Madden, UNC Chapel Hill, CC BY-SA 3.0 , via Wikimedia Commons
Schokraie E, Warnken U, Hotz-Wagenblatt A, Grohme MA, Hengherr S, et al. (2012), CC BY 2.5 <https://creativecommons.org/licenses/by/2.5>, via Wikimedia Commons