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A Low-Cost Method of Measuring the In Situ Primary Productivity of Periphyton Communities of Lentic Waters

Published: December 16, 2022 doi: 10.3791/64078


Presented here is a cost-effective and transportable method/facility for measuring the primary productivity of microbial mats under actual in situ environmental temperature and light conditions. The experimental setup is based on widely available materials and can be used under various conditions while offering the advantages of laboratory-based models.


Measuring the in situ primary productivity of periphyton during the growing season gradient can elucidate the quantitative effect of environmental drivers (mainly phosphorus concentration and light intensity) and species composition on primary productivity. Primary productivity is mainly driven by light intensity, temperature, availability of nutrients, and distribution of the ionic species of the carbonate system in the respective depths of the euphotic zone. It is a complex system that is very difficult to simulate in the laboratory. This cheap, transportable, and easy-to-build floating barge allows measuring the primary productivity accurately-directly under the actual natural conditions. The methodology is based on measuring the primary productivity in real time using noninvasive oxygen sensors integrated into tightly sealed glass jars, enabling online oxygen flux monitoring and providing new insights into metabolic activities. Detailed seasonal in situ measurements of gross primary productivity of microbial mats (or other benthic organisms) can improve current knowledge of the processes controlling primary productivity dynamics in lentic waters.


Primary productivity is the only entry of autochthonous carbon into the aquatic systems that form the entire system food web1. Hence, the accurate estimation of primary productivity is an essential step toward understanding the functioning of aquatic ecosystems. Littoral zones are areas of high primary productivity and biodiversity. In addition to phytoplankton, periphyton (hereafter referred to as microbial mats) and macroalgae are assumed to significantly contribute to primary productivity in littoral zones2. Due to their sessile lifestyle and significant spatial heterogeneity, quantification of primary productivity is not trivial.

Primary productivity is driven mainly by light intensity, temperature, availability of nutrients, and distribution of the ionic species of the carbonate system in the respective depths of euphotic zones3,4. The depth markedly influences the spatial distribution of microbial mats. Microbial communities must cope with the adverse effects of high irradiation and pronounced seasonal temperature variations in shallow depths and with lower light intensity at greater depths. In addition to the depth gradient, dynamic trophic interactions generate multiple and complex spatial patterns at different scales5. This complex system is complicated to simulate in the laboratory. The most accurate way to infer the metabolic activity of individual primary producers from littoral zones is to set up in situ experiments.

The methodology introduced in this paper is based on the traditional chamber method2,6,7, together with a transportable and easy-to-build low-cost floating barge. This allows the measurement of primary productivity at different depths under the natural light spectrum, temperature, and different distribution of the ionic species of the carbonate system with the depth. The method is based on the principle of light versus dark bottle oxygen, which was first employed to measure phytoplankton photosynthesis6 and is still commonly used6,7. It compares the rate of change in oxygen in bottles kept in the light (which includes the effects of primary productivity and respiration) with those held in the dark (respiration only)8. The method uses oxygen evolution (photosynthesis) as a proxy for primary productivity. The measured variables are net ecosystem productivity (NEP, as a change in O2 concentration over time in light conditions) and ecosystem respiration (RE, as a change in O2 concentration over time in the dark). Gross ecosystem productivity (GEP) is the calculation of the difference between the two (Table 1). The term "ecosystem" is used here to denote that the periphyton is composed of autotrophic and heterotrophic organisms. The most significant improvement of this traditional chamber method is using noninvasive oxygen optical sensors and optimization of this primarily planktonic method for measuring periphytic primary productivity.

The technique is described in the example of measuring microbial mats in the littoral zone of newly emerged post-mining lakes in the Czech Republic-Milada, Most, and Medar. The metabolic activity of microbial mats is determined using direct in situ measurement of O2 fluxes performed directly at specific depths, where the studied communities naturally occur. Heterotrophic and phototrophic activity is measured in closed glass bottles equipped with noninvasive optical oxygen sensors. These sensors detect the partial pressure of oxygen using the fluorescence of light-sensitive dyes. The bottles with microbial mats are suspended and incubated on a floating device at the appropriate depths. The oxygen concentration inside the bottles was continuously measured during the daylight period from the small boat.

Samples of intact microbial mats are collected and placed in gas-tight incubation bottles at designated depths by scuba divers. Each bottle is equipped with a noninvasive optical oxygen microsensor, which monitors the O2 productivity/consumption over time. All measurements are done in five replicate dark/light pairs in each depth. The temperature and photosynthetically active radiation (PHAR) intensities are measured at respective depths throughout the incubation. After 6 h of in situ incubation (daylight hours), the microbial mats are harvested from the bottles and dried. O2 fluxes are normalized to microbial biomass. As a control, fluxes are corrected for changes in O2 concentration in separate light and dark gas-tight bottles (blank controls) containing lake water without microbial mat biomass. Below are detailed instructions for building the floating barge and performing the whole experiment step-by-step. This paper also presents representative results from the measurements of microbial mats at two depths (1 m and 2 m), with five replicates at each depth. Actual temperature and light intensity were measured during the whole experiment using dataloggers.

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NOTE: Before sampling, determine the degree of replications based on the overall project needs, statistical design, or expected amount of sample variability.Five replicate pairs of light and dark incubation bottles are suggested for precise statistical analysis and to account for potential sample loss or breakage. The described floating experimental barge is designed to carry five replicates plus one pair of blank controls; see Figure 1 for a technical drawing of the experimental barge.

Figure 1
Figure 1: Technical drawings of the experimental barge and the side float. (A) Top view: the frame of the barge consists of four Aluminum angle L profile pieces (blue) that are joined together by four Aluminum flat bars (grey). XPS floats (pink) are mounted to the frame at two points, each one on the parallel aluminum pieces. Chains for incubation bottles are attached to the frame on both sides using snap hooks in predrilled holes (red arrows) with 550 mm of separation between them. Chains were provided with snap-hooks at 1 m and 2 m distances for incubation bottle attachment (choose the snap-hooks position according to the experimental depth). The concrete anchor is secured to the barge's bow, where an overhang of 25 mm allows for two predrilled holes (yellow arrowheads) to serve as an attachment point for the anchor's chain and research vessel. The frame is assembled or disassembled easily via the parallel joints between the four aluminum angle pieces (green arrowheads). (B) The side view shows the suspended chains with hanging incubation bottles and concrete anchor (brown square). (C) The side XPS float: Parallelaluminum angle L pieces (blue) are joined by vertical aluminum flat bars (grey). Below the crossbar section, the XPS float (pink) is mounted with the necessary hole sizes indicated (4 mm). The suspended chains are attached with snap hooks in 8 mm holes (red arrowhead). At the barge's bow, two 8 mm holes are drilled into the overhanging aluminum, one for securing the anchor to the barge (yellow arrowhead) and another for mooring the research vessel to the barge (blue). Please click here to view a larger version of this figure.

1. Construction of the experimental barge

NOTE: The floating barge consists of two equal sections mounted together, allowing easy assembly/disassembly. All used parts can be purchased at any hobby market or store selling building materials.

  1. First, assemble the frame of the barge by joining four aluminum angle L profile pieces (40 mm x 40 mm x 3 mm; length of 2,000 mm) together using four aluminum flat bars (40 mm x 3 mm x 350 mm), 16 screws (4 mm x 15 mm with hexagonal nuts), and 32 washers (4 mm x 10 mm).
    NOTE: The distance and position of the flat bars are shown in the technical drawing in Figure 1A. The detailed attachment of the floats to the side flat bars is shown in Figure 1B.
  2. To join the two equal sections of the frame, use four 4 mm x 15 mm screws with wing nuts and eight 4 mm x 10 mm washers to screw the aluminum angle L profiles together at the ends (Figure 1A, green arrows).
  3. Use five pieces of extruded polystyrene (XPS) material (500 mm x 200 mm x 150 mm), ten 10 mm x 170 mm screws with hexagonal nuts, and twenty 10 mm x 50 mm washers to prepare five extruded polystyrene floats (500 mm x 200 mm x 150 mm each). Attach the floats to the frame at five points shown in the technical drawing (Figure 1A).
  4. Drill holes into the frame (see red arrows in Figure 1A marking the positions and distances of the holes for the chains). Attach the 12 m steel chains (wire diameter of 3 mm, inside link of 5.5 mm x 26 mm) for the incubation bottles to the holes in the frame using steel carabine hooks (50 mm x 5 mm). Provide each chain with pairs of snap hooks (50 mm x 5 mm) for installing the incubation bottles to the desired depth according to the experimental design. In this case, they were seated at 1 m and 2 m depths.
  5. For the anchor, fill the 15 L bucket with concrete. Insert an eye bolt into the concrete and allow it to dry undisturbed. Fasten the 5 m steel chain to the hook. Secure the anchor to the predrilled hole on the barge's bow (marked by yellow arrows in Figure 1A,B).
    ​NOTE: Technical drawings with the assembly description are shown in Figure 1A-C. Figure 2 shows the photo of the assembled experimental barge. Figure 3 shows the attachment of incubation bottles to the chain.

Figure 2
Figure 2: Assembled experimental barge. Photograph of the assembled experimental barge. Red arrowheads show the holes for the attachment of chains with incubation bottles. The green arrowheads point to where the two halves of the float are joined together. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Incubation bottles. Photo of two pairs of dark and light incubation bottles hanging at a depth of 1 m. One pair of bottles contains the sample of intact microbial mats still growing on the stone (red arrowhead). The second one is the blank bottle with the lake water from the respective depth. A yellow arrowhead points to the oxygen sensor spot attached to the inner wall of the incubation bottle. Please click here to view a larger version of this figure.

2. Installation in the field

  1. Use of an inflatable kayak is suggested for barge placement and conducting experiments as it is easily transportable.
  2. Select a place with an ideal depth to anchor the float. Choose the depth so that the lower incubation bottles are at least 2 m above the bottom to avoid disturbing the sediment into the water column around the incubation bottles.
  3. Attach the assembled barge behind the stern of the boat. Carefully lower the anchor along the side of the boat and align it so that it hangs slightly below the water surface so that the float can be easily towed along with the anchor to the spot with the required depth.
  4. Untie the anchor from the boat, lower it to the bottom, and secure the barge to the anchor chain.
  5. Secure the chains for attaching the incubation bottles to the barge.

3. Incubation bottle preparation

  1. Use the transparent wide-necked 0.5 L bottles with gas-tight seals.
    NOTE: It is possible to adjust the size of the bottles but remember to increase the floatation of the barge with more polystyrene sheets as well. The barge described here can reliably carry 24 0.5 L glass bottles.
  2. Attach the oxygen optical sensor spots to the inner wall of each bottle.
  3. Add an opaque layer to the dark treatment bottles by wrapping them with black electrical tape.
  4. Cut a tiny hole in the spot with the optical sensor. To prevent light from entering the bottle, make the hole slightly smaller than the diameter of the sensor.
    ​NOTE: Any opaque layer that prevents light from entering the bottle will also work. The advantage of black electrical tape is that it resists abrasion and does not peel off in water.

4. Sample collection and handling

NOTE: Divers carry out the manual collection of samples in deeper water. In shallow water, it can be done by snorkeling or wading.

  1. Place the incubation bottles in the portable box.
  2. Dive with the box to the respective depth. Avoid disturbing the sediment in the surrounding water.
  3. Fill the incubation bottles with the samples carefully. Try to disturb the biomass of the sample as little as possible, for example, by using long tweezers. If the microbial mats grow on a solid surface, such as a small stone, carefully transfer the whole stone with intact biomass into the bottle.
    NOTE: Avoid collecting big stones when sampling mats grow on stones-the glass bottles can be broken during further manipulation.
  4. Fill one pair of light/dark bottles with clean water from the respective depths to serve as blank controls.
    NOTE: The bottles without the periphyton sample serve as a control determining the oxygen production/consumption of ambient water organisms. It ensures that the calculated net or gross primary productivity of periphyton is unbiased.
  5. Ensure that the water in all incubation bottles is clean and contains no disturbing sediment.
  6. Close the bottles and bring them to the boat anchored to the floating barge.

5. Measuring the primary productivity

NOTE: The person sitting in the boat takes the box from the diver and performs the following steps.

  1. Attach the first two pairs of incubation bottles to the snap-hooks on the first chain.
  2. Measure the initial oxygen concentration in each bottle using the fiber-optic oxygen meter. Attach the optical cable of the meter to the oxygen sensor mounted inside the bottle and immediately (within a few seconds) read out the O2 concentration contactless (through the bottle wall). Record the measured value.
    NOTE: The handling time is short; from taking the bottles from the divers to the initial setting to the respective depth, it takes just a few minutes.
  3. Immediately afterward, carefully lower the chain with the attached bottles back into the water. Ensure that the incubation bottles are placed at the same depth as the biomass that was placed in them was sampled.
  4. Make another measurement from the ship after 1 h (see NOTE below). Carefully pull each chain with the bottles into the boat, read the oxygen value by attaching the optical cable to the sensor, and lower the samples into the water again.
    NOTE: Adjust the time between individual measurements during the incubation according to the intensity of O2 productivity/consumption of samples to avoid oversaturation of bottles.
  5. Repeat this procedure at least four or five times with all pairs of bottles.
    ​NOTE: The whole setup of the experiment in the field is shown in Figure 4.

Figure 4
Figure 4: Schema of the experimental setup in the field. Illustration of the anchored experimental barge on the lake surface. The incubation bottles (0.5 L) with microbial mat biomass are hung at two different depths (1 m and 2 m). The divers collected samples of microbial mats directly into the incubation bottles at the appropriate depths. Oxygen concentration in individual bottles is measured from the ship. The bottles are pulled out of the water. The oxygen concentration value is measured in a few seconds by attaching an optical cable to the oxygen sensor. The bottles are then carefully lowered back into the water. The whole procedure of measuring two pairs of incubation bottles from two depths takes ~2 min. Please click here to view a larger version of this figure.

6. Sample analyses

  1. After the end of the measurements, take the samples directly from the bottles, and transfer the biomass of the microbial mat to the small plastic flasks. If the mats grow on solid substrates (e.g., stones), scrub them with a toothbrush or a small knife.
  2. In the laboratory, filter each replicate through pre-weighed glass fiber filters to determine the dry weight9.

7. Data analyses

  1. During the incubation period, measure the oxygen concentration in the light and dark bottles and compare it with the oxygen concentration in the water column when the bottles are filled.
    NOTE: The change in oxygen in the light bottle over time is the combined result of gross ecosystem productivity (GEP) and respiration by all the organisms in the bottle (autotrophs and heterotrophs from the ambient water and the periphytic community). The decrease in oxygen in the dark bottle measures the respiratory losses of both autotrophs and heterotrophs. The change in oxygen concentration in the control (i.e., bottles without the periphyton) is only the product of heterotrophic or autotrophic organisms in the ambient water. Periphyton productivity and respiration were estimated by subtracting ambient water productivity and respiration measured in blank incubation bottles.
  2. Note down the O2 concentration in percent oxygen saturation (i.e., calibrate the oxygen sensors to 0% and 100% oxygen saturation). Before estimating the primary productivity, convert the raw data (Equation 1) to some reasonable unit.
    NOTE: In this study, the data are converted to mmol of O2 per gram of organic matter (OM) of the periphyton mass at the dry weight basis, according to Benson and Krause10.
    1. Calculate the conversion using equation (1):
      Equation 2 (1)
      Where Cp is O2 concentration in water (mg (O2) L-1) when it is fully saturated by O2, VBottle is the volume of the bottle in mL, VStones is the volume occupied by the stone in mL, is the weight of the periphyton mass in g, and 32 is the molar weight of O2.
    2. Calculate Cp using equation (2):
      Equation 3 (2)
      Where Cs is the standard O2 concentration, P is the atmospheric pressure at the lake surface, Pw is the partial pressure of the water vapor at the lake surface, and ω is water density.
    3. Calculate Cs, ω, P, and Pw from previously defined empirical equations (3-6) when lake elevation (h in km) and water temperature at the lake surface (t in °C) are known:
      Equation 4 (3)
      Equation 5 (4)
      Equation 6 (5)
      Equation 7 (6)
      NOTE: From equations (1-6), it is evident that the calculated O2 concentration is most accurate for shallow depths. As the depth increases, the calculated concentration gets more biased in terms of absolute concentration. It is optimal when the rate of change of oxygen concentration along the depth is known for each lake so that the absolute O2 concentration can be corrected if necessary. Once the O2 concentration is calculated, its change over time can be used to calculate two different fluxes of O2 at two different conditions. Under light conditions, net ecosystem productivity (NEP) is directly proportional to the change in O2 concentration over time (see below). The term "ecosystem" is used here to denote that the periphyton is composed of autotrophic and heterotrophic organisms. In the dark, the change in O2 concentration over time is proportional to the sum of respiratory losses of autotrophic and heterotrophic organisms, thus defining ecosystem respiration (RE). The difference between NEP and RE defines gross ecosystem productivity (GEP). If the respiratory losses of the heterotrophic part of the community are negligible, GEP becomes equal to gross ecosystem productivity.
  3. Determine the rate of change of O2 concentration over time by third-degree polynomial regression, as shown in equation (7).
    Equation 8(7)
    Where A0 is O2 concentration at time zero and A1-A2 are coefficients of polynomial regression.
    NOTE: The polynomial function is used because it can serve as an approximation of any differential equation. Thus, it is not necessary to know the accurate functional relationship between O2 concentration and time. Therefore, any assumption associated with the functional relationship (e.g., linearity) does not need to be controlled. By definition, the second term of polynomial regression, A1 defines the rate of change of O2 concentration at time zero (i.e., instant rate), which is independent of A0 and, thus, the absolute O2 concentration at time zero. For that reason, the estimate of O2 flux is not affected by the bias in absolute O2 concentration calculations caused by pressure change across the depth gradient. A1 has units O2 (mmol g(OM)-1) per time (1 h in this study).
    1. Calculate A1, calculated separately for bottles with and without exposure to light and containing microbial mat biomass (i.e., VStones > 0) and for control bottles with and without exposure to light and containing free water (i.e., VStones = 0).
      NOTE: Assigning these different regression coefficients notations Equation 9, Equation 10, Equation 11, and Equation 12, respectively, the equation (8) for productivity GEP calculation can be written as:
      Equation 13 (8.1)
      Equation 14 (8.2)
      Equation 15 (8.3)
      The term Equation 16 defines net ecosystem productivity (Figure 5A; i.e., net oxygen productivity ), and the term Equation 17 represents the sum of autotrophic and heterotrophic respiration (Figure 5B; RE, i.e., assuming both respirations are similar under dark and light conditions).
    2. Subtract R from NEP to obtain GEP (Figure 5C).
      NOTE: Equation (8) implicitly assumes that Equation 9 and Equation 11 are both positive, and Equation 10 and Equation 12 are both negative. If Equation 17 is positive, check the raw data carefully for outliers . Equation 16 can be theoretically negative because the respiratory losses caused by heterotrophic activity can be higher than photosynthetic activity.

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Representative Results

Figure 5
Figure 5: Net and gross ecosystem productivity of microbial mats during daylight. (A) Light bottle-net ecosystem productivity: time course data of net oxygen productivity of microbial mats from the light bottles. The oxygen concentration change in incubation bottles was measured after 1 h during daylight. Grey circles: bottles with samples of microbial mats. White circles: blank bottles with lake water only. (B) Dark bottle-respiration: the sum of autotrophic and heterotrophic respiration from the dark bottles. The change in oxygen concentration in incubation bottles was measured after 1 h during the daylight period. Grey circles: bottles with samples of microbial mats. White circles: blank bottles with lake water only. (C) Comparison of net ecosystem productivity, respiration, and gross ecosystem productivity: subtracting respiration rates from net ecosystem productivity rates results in gross ecosystem productivity of the microbial mats biomass. Abbreviations: NEP = net ecosystem productivity; RE = respiration; GEP = gross ecosystem productivity. Please click here to view a larger version of this figure.

A schematic for the experimental floating barge and incubation bottles setup is shown in Figure 1, Figure 2, and Figure 3. Figure 4 demonstrates how the experiment can be set up in the field. Figure5 shows the representative data set used to calculate the final net and gross ecosystem productivity. In Figure 5A, the change in O2 concentration (i.e., recalculated to mmol (O2) g(OM)-1) over time is shown for bottles with (denoted as "sample") or without (denoted as "control") the microbial mats that were exposed to light. The increase in O2 concentration is apparent in the control as well as in the sample. Nevertheless, the slope of increase is significantly higher in bottles with microbial mats. It shows that the signal of the microbial mat activity is detectable against the background.

The same applies to data from bottles kept in the dark, which are shown in Figure 5B. In this case, however, the slope of O2 concentration change over time in the control is not significantly different from zero. Figure 5C shows the products of data shown in Figure 5A,B, the net ecosystem productivity (NEP) and respiration (RE), respectively. By definition, the first must be positive and the latter negative. The data comply with the definition well. The sum of NPP and RE is then the gross ecosystem productivity (GEP). Notice that the error of GEP increases because it is the square root of the squared sums of errors calculated for NEP and RE. Every measurement event produces a series of O2 concentrations over daylight time for each of the monitored incubation bottles, which is the basis for estimating net and gross ecosystem productivity. Figure 5A shows the time course data of net oxygen productivity (photosynthesis and respiration) of microbial mats from the light bottles. Figure 5B shows the time course data of respiration of microbial mats from dark bottles. Subtracting respiration rates from net ecosystem productivity yields the rates of gross ecosystem productivity (Figure 5C). Figure 6 shows the results obtained from the practical application of the method in the field. The Gross ecosystem productivity of the periphytic community was measured in three post-mining lakes in the Czech Republic during the vegetation season.

Figure 6
Figure 6. Gross ecosystem productivity of periphyton in three post-mining lakes. Example of seasonal variation of gross ecosystem productivity (GEP) of periphyton biomass in three post-mining lakes in the Czech Republic (Milada, Most, Medard). Please click here to view a larger version of this figure.

Experimental unit O2 flux proxy µmol O2 g OM-1 h-1 SE
Light bottle Net ecosystem productivity (NEP) 38.6 1.98
Dark bottle Ecosystem respiration (RE) -18.1 2.3
Gross ecosystem productivity (GEP) 53.8 13.6

Table 1: A summary table of results. The results of the linear regression calculated as mean and standard error. Average estimation values from five replicates of dark and light incubation bottles. SE = standard error.

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The methodology described in this paper is based on the principle of the light and dark bottle oxygen technique in combination with the noninvasive technique of measuring O2 concentration using optical oxygen sensors. This system allows the parallel measurement of different incubation settings as the optical fiber for measuring O2 can be moved quickly from bottle to bottle. The benthic communities from various depths can differ in taxonomic composition and productivity; simultaneously measuring them in a parallel manner can save time and make the results more precise, enabling the calculation of whole-depth profiles where periphyton grow. Non-invasive oxygen sensors integrated into shake flasks enable real-time oxygen flux monitoring.

The designed experimental setup allows measurement of the primary productivity of microbial communities at respective depths where the communities naturally occur, which is difficult to simulate in the laboratory (appropriate pressure, track the changes in the diurnal course of temperature and light intensity in situ, different nutrient availability). The major improvements in the proposed method are noninvasiveness, cost-effectiveness, and the possibility of multiple simultaneous measurements at a single coordinate location near the place of sample collection. The method is environmentally friendly as all materials can be used repeatedly. It also enables the collection of large datasets without additional expenses. The introduction of highly sensitive O2 probes (i.e., detection limit 15 ppb, resolution 0.1% of 0.04 mg O2 L-1) also shifts the usage of the method to less productive aquatic environments.

Nevertheless, the proposed method also has limitations that are associated with the nature of the experimental arrangement. The first limitation is the possibility of O2 supersaturation of the closed bottles. This occurs especially during sunny days if the highly productive biomass is incubated. It can result in an underestimation of photosynthesis caused by the incomplete dissolution of O2 in the water7. High concentrations of O2 can also deactivate PSII11. To avoid supersaturation, preliminary experiments focused on biomass amount optimization are strongly recommended. Second, the exchange of produced gases can be limited by the thick diffusive boundary layer of the periphytic mat. Together with the stagnant conditions within incubation bottles, it can lead to underestimation of productivity. However, within the framework of the described methodology, the incubation bottles are manipulated every hour when pulled out from the water during the measuring time and lowered back then. During incubation, the autotrophic community could also become limited by dissolved inorganic carbon (DIC), causing a deceleration in production. Therefore, the increase in O2 is not linear over the entire incubation time. Usually, the problem is solved by selecting only the linear region of the O2 to time relationship for rate calculation. Here, we used a third-degree polynomial regression, which serves as an approximation of any differentiable function defining the rate of change of O2 over time. It allows for calculation of the rate of change at time zero; hence, the community is not yet limited by the DIC at time zero.

Studies have shown that minimal agitation for homogenization of gases between periphytic mats and overlying water is necessary12. In lentic environments, the hydrodynamics of littoral zones is not strong anyway, so mixing the water within the incubation bottle during the individual measurements can be a sufficient compromise to natural homogenization processes. Another problematic step is pulling out the periphytic sample from the physical context of the bottom, which may lead to the alteration of light exposure and gas penetration to the mat. The quantity of illumination of periphyton can be slightly modulated, especially at the edges of the collected mats. However, photosynthetic organisms face light intensity fluctuations naturally, so they are adapted to maintain such changes13,14. To avoid a greater degree of disturbance, it is recommended to carefully sample one compact piece of the periphytic mat for incubation. Samples may be exposed to more intense radiation when they are pulled out from the water during measurements. Nevertheless, the incubation time of the bottles in the respective depths is much larger than the time required to conduct O2 concentration reading. The incubation time is 4 h, and one reading takes approximately 30 s.

The presented method was invented for the lentic water ecosystems. It can also be used in running waters, but some minor technical problems must be solved. In running water, the incubation bottles can be broken more easily and anchoring the whole system would be challenging in the flow. Nevertheless, even in stagnant water, incubation bottles must be handled carefully so they do not break each other during the manipulation. Special attention must be paid if the incubation bottles include microbial mats growing on stones. It is critical not to sample big stones to avoid breaking the glass bottles.

As noted in protocol section 7, the described method provides estimates of net ecosystem productivity, ecosystem respiration rate, and their product-gross ecosystem productivity. In this method, respiration rates of heterotrophic and autotrophic parts of the microbial community cannot be distinguished. Hence, the gross ecosystem productivity is lower than gross primary productivity by a rate equal to heterotrophic respiration. Therefore, this method is not directly comparable to the frequently used method of primary productivity estimation by 14C isotope labeling15,16,17. This method is based on introducing a known amount of labeled 14C-CO2 into incubation bottles filled with water of known dissolved inorganic C concentration18. The radioactivity loss rate over time is directly proportional to gross primary productivity. The proposed method, in fact, complements the radiolabeling method because the combination of both methods theoretically allows for distinguishing all carbon fluxes, including heterotrophic and autotrophic respiration. However, the radiolabeling method also has several limitations. For example, it relies on the assumption of rapid and homogeneous incorporation of the labeled element into the periphytic mat19, which is not usually possible without the mechanical disruption of the periphyton matrix. To obtain accurate daily estimates, samples must be collected, incubated, and sampled several times throughout the day, and the method should be run under laboratory conditions to avoid radioactive contamination7. Continuous and noninvasive measurement is not possible.

Other commonly used methods for estimating primary productivity in aquatic ecosystems have the same experimental design but include different types of oxygen probes, which are less convenient, especially for estimating the primary productivity of periphyton20. The use of some types of oxygen probes can help detect the actual oxygen concentration within the periphytic mat but cannot estimate the rate of change over time unless sealed in a closed system. Sealing the oxygen probe is more prone to leakage than noninvasive optical sensors. Due to their need for wired connections, other bottle-based metabolism methods do not allow measurement of oxygen concentrations at greater depths. This makes the proposed method, which does not require a wired connection, more capable of providing accurate estimates of deep-water benthic metabolism. As each optical sensor is an independent unit, it is possible to simultaneously measure the change in oxygen concentration over time at multiple depths at a single coordinate location. As a result, the method could provide a robust dataset that even allows upscaling to the entire water body if required. The remote sensing technique, for example, is not similarly applicable because this method cannot be used at varying depths below the surface.

Detailed seasonal in situ measurements of gross productivity of periphyton (or other benthic organisms) can improve current knowledge of the processes controlling primary productivity dynamics in lentic waters. Estimating the total primary productivity in each lake's littoral zone can give a better idea of its relative importance for the whole-lake carbon metabolism. However, this method is unsuitable for measuring plankton primary productivity in oligotrophic waters. Compared to benthic communities, the plankton biomass in open water is too low. Thus, the changes in O2 concentration would be too slow to be detected simultaneously during the experiment with benthic biomass. In this case, the metabolic activity of plankton can be measured using the 14C-bicarbonate method as described by Šimek et al.21 in the same sampling time. In eutrophic waters, it is possible to use this method to measure the primary productivity of plankton as well. Each technique for measuring primary productivity mentioned above has advantages and disadvantages, which have been discussed. The best technique should be selected according to the scientific questions being investigated. Further, the method should mimic the ecological parameters of studied ecosystems as much as possible.

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The authors confirm that they have no conflicts of interest to disclose.


This study was supported by the Czech Science Foundation (GACR 19-05791S), RVO 67985939, and by the CAS within the program of the Strategy AV 21, Land save and recovery. Many thanks to Ondřej Sihelský for taking the shots in the field - without him, the filming would have been complete hell. The project would not be possible without tight cooperation with companies, Palivový Kombinát Ústí s.p. and Sokolovská Uhelná, who provided access to the studied localities.


Name Company Catalog Number Comments
Aluminum angle L profile 40 x 40 mm x 3 mm, length 2,000 mm
Aluminum flat bar 40 x 3 x 350 mm
Bucket 15 L with concrete infill 
Carabine hook with screw lock 50 x 5 mm
electric tape black
Extruded polystyrene (XPS) material 500 x 200 x 150 mm
Fibox 3 LCD trace PreSens Precision Sensing GmbH stand-alone fiber optic oxygen meter
Hondex PS-7 Portable Depth Sounder Hondex  - Honda Electronics to measures distances through water - to bottom depth measurement; https://www.honda-el.net/industry/ps-7e
KORKEN - glass tight-seal jar 0.5 L IKEA incubation bottles; https://www.ikea.com/cz/en/p/korken-jar-with-lid-clear-glass-70213545/
metal hook 
Oxygen Sensor Spot SP-PSt3-NAU-D5 PreSens Precision Sensing GmbH non-invasive optical oxygen sensor for measurements under Real Conditions
SCOUT infantable canoe GUMOTEX https://www.gumotexboats.com/en/scout-standard#0000-044667-021-13/11C
Screw 10 x 170 mm with hexagonal nuts
Screw 4 x 15 mm with hexagonal nuts
Screw 4 x 15 mm with wing nuts
Snap hooks 50 x 5 mm
Steel Carabine hook 50 x 5 mm
Steel chain with wire diameter 3 mm, inside link 5.5 x 26 mm
Steel chain, 5 m
Washer 10 x 50 mm
Washer 4 x 10 mm
Washer 4 x 10 mm



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A Low-Cost Method of Measuring the <em>In Situ</em> Primary Productivity of Periphyton Communities of Lentic Waters
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Čapková, K., Bešta, T., Mareš, J., Čapek, P., Řeháková, K. A Low-Cost Method of Measuring the In Situ Primary Productivity of Periphyton Communities of Lentic Waters. J. Vis. Exp. (190), e64078, doi:10.3791/64078 (2022).More

Čapková, K., Bešta, T., Mareš, J., Čapek, P., Řeháková, K. A Low-Cost Method of Measuring the In Situ Primary Productivity of Periphyton Communities of Lentic Waters. J. Vis. Exp. (190), e64078, doi:10.3791/64078 (2022).

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