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Is photosynthesis faster in aquatic plants rather than terrestrial plants?

Is photosynthesis faster in aquatic plants rather than terrestrial plants?


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For example : In which of these two plants photosynthesis is faster and why? water hyacinth or sedge?


Aquatic CAM photosynthesis: A brief history of its discovery

Aquatic CAM photosynthesis was discovered in study of biochemical anaerobic metabolism.

CAM is universal in all aquatic species of Isoetes and non-existent in terrestrial Isoetes.

CAM has a limited occurrence in three other families, including the Crassulaceae.

Discovery led to studies of terrestrial Isoetes relatives with carbon uptake from sediment.

CAM in all plants provides an internal source of CO2 for photosynthesis during the day.


What are Land Plants?

Land plants belong to the category of terrestrial plants where the plants are found in soil based environments. Land plants have a strong root system that can either be a tap root system or a fibrous root system. Plants require water and nutrients for its survival. Land plants use their root system to absorb water and nutrients from the soil. In addition, the root system also anchors the plant to the ground. The main requirement of land plants is to conserve its water content.

In order to fulfil this, land plants have special adaptations such as having a thick, waxy cuticle and special leaf anatomical characteristics, etc. The stomata of the land plants can be found along the underside of the leaf (lower epidermis) to minimize or prevent transpiration. The land plants have much stronger stems with greater diameters. This is mainly due to the excess deposition of lignin that makes the plants rigid and erect. This allows the plant to stay erect even under harsh terrestrial conditions.

Figure 01: Land Plants

The reproduction and the fertilization process of land plants in a complex process. Pollinating agents such as wind and insects are essential to facilitate fertilization in land plants. The male gametes or pollens should be transferred on to the female gamete for fertilization. In land plants, this process should be facilitated by an agent.


Underwater Photosynthesis – Approaches and Methods

Conventional infrared gas analyzer (IRGA) systems following CO2 exchange in air do not work under water, so dedicated measuring systems are required to quantify underwater net photosynthesis and dark respiration. DIC can be measured by injection of small aliquots of water into concentrated acid in a bubble chamber purged with gaseous N2 carrying the released CO2 into an IRGA (Vermaat and Sand-Jensen, 1987). However, photosynthesis measurements based on DIC determinations are thus based on discrete measurements at selected times and can be complicated because of the large and variable combined pool of DIC in water (See Underwater Photosynthesis in Submerged Aquatic plants and Recent Advances and The CO2 Equilibria in Water). Indirect methods to track DIC changes can be based on continuous measurements of pH in solution (Maberly, 1996). The DIC technique to measure photosynthess has potential errors if: (i) DIC is removed by external carbonate precipitation, (ii) internal DIC accumulates in tissues or colony gels, (iii) DIC dissolution of solid carbonates occurs, or (iv) DIC is released from internal pools (McConnaughey et al., 1994 Sand-Jensen et al., 2009). External measurements of pH to estimate DIC changes have the same potential errors as above and, moreover, also due to direct exchange of protons from tissues not always being closely coupled to DIC exchange. Therefore, most methods for studies of underwater net photosynthesis are based upon O2 detection.

In contrast to gas exchange measurements of photosynthesis by leaves in air using open systems and CO2 detection, underwater measurements commonly use closed systems and detection of O2. In addition to the rationale for O2 detection described in the preceding paragraph, O2 detection also enables measurements in waters of substantially different DIC concentrations (e.g., softwater lakes up to 100 μmol L 𢄡 , ocean approximately 2000 μmol L 𢄡 and hardwater lakes up to 10000 μmol L 𢄡 ). The drawback of closed systems is that these are non-steady-state (i.e. DIC declining and O2 increasing with time). Use of open systems with O2 detection is constrained by reliable continuous detection of differences in O2 concentrations between incoming and outgoing solutions from an appropriate chamber.

Changes in O2 concentration over time are straightforward to measure with Clark type amperometric electrodes or more recently by use of O2 sensitive optodes. Oxygen partial pressure (pO2) or dissolved O2 can be continuously monitored in water with an accuracy of 0.01 kPa or 0.2 μmol L 𢄡 (Strickland and Parsons, 1972). Photosynthesis determined from changes in O2 and DIC pools dissolved in the surrounding water requires that those are much greater than changes in such pools within the plant tissue (Sand-Jensen and Prahl, 1982). This is best achieved by having large incubation volumes relative to plant volumes. Alternatively, changes in tissue pools can be measured (Sand-Jensen et al., 2005) or be deduced by establishment of true steady state where tissue concentrations remain constant or quasi steady state where tissue concentrations changes proportionally to external concentrations (Sand-Jensen and Prahl, 1982). Measurements of underwater photosynthesis based upon O2 evolution can include great error when plants with highly porous tissues (perhaps variable in volume and having much higher “solubility” of O2 than water See Medium and Tissue) are incubated in small chambers (Hartman and Brown, 1967 Richardson et al., 1984). On the other hand, measurements of underwater photosynthesis based upon changes in DIC can include extreme error when plant tissues (or colony matrices in the case of algae and cyanobacteria) hold very large pools of DIC that do not change in concert with those in the surrounding water. For example, DIC in the colony gel of Nostoc zetterstedtii continues to support photosynthesis after water pools have been exhausted, and in darkness respiratory CO2 replenishes this internal pool before being released to the water (Sand-Jensen et al., 2009).

Measurements of radioactive labeling of the DIC pool with 14 C and the use of pulse amplitude modulated (PAM) fluorometry are also methods to measure photosynthetic performance under water these technique are beyond the focus of the present paper so readers are referred to e.g., Adams et al. (1978) or Kemp et al. (1986) for methods on 14 C and to Silva et al. (2009) or Suggett et al. (2011) and chapters therein for PAM approaches.

The CO2 Equilibria in Water

Understanding the chemistry of dissolved DIC and the proportional changes in its three constituents (CO2, HCO 3 - and CO 3 2 - ) depending on ionic strength, temperature, and primarily pH (Mackereth et al., 1978) is essential because it determines the availability of the preferred CO2 source and the supplementary HCO 3 - source for underwater net photosynthesis. When CO2 dissolves in water, the following equilibrium is established:

CO2’s reaction with water (H2O) forming carbonic acid (H2CO3) is a time dependent process which in some organisms is catalyzed by the enzyme carbonic anhydrase. H2CO3 can dissociate immediately into a proton (H + ) and bicarbonate ( HCO 3 - ) so the dissolution of CO2 into water causes pH to drop. At high pH, HCO 3 - can further dissociate into a second H + and carbonate ( CO 3 2 - ). The relative distribution of the three main inorganic carbon species with pH is shown (Figure 5). The pKa1 is 6.532 and is referred to as the apparent pKa1 as only little CO2 is converted into carbonic acid (hence the brackets in Eq. 4) while the majority remains in solution as CO2(aq) also referred to as free CO2 pKa2 is 10.329 (Schwarzenbach and Meier, 1958 Stumm and Morgan, 1996 Gutz, 2012). Below pH 6, most of the DIC is present as CO2, which is usually more readily used for underwater photosynthesis than HCO 3 - . Between pH 7 and 10, HCO 3 - dominates, a carbon species that can be used as an additional carbon source among species in most taxonomic groups of aquatic plants except for pteridopytes and mosses (Raven and Hurd, 2012). Only at pH higher than 10, a significant proportion of the DIC is in the form of CO 3 2 - which apparently is not taken up by any phototrophs in ionic form but can perhaps be made available in acid zones on plant surfaces by back titration with released protons (conversion toward the left in Eq. 4).

Figure 5. Relative speciation (%) of carbon dioxide (CO2), bicarbonate ( HCO 3 - ), and carbonate ( CO 3 2 - ) in water as a function of pH. The example given is at 20ଌ and electrical conductivity of 250 μS cm 𢄡 . Data were calculated using Gutz (2012) with the apparent pK1 = 6.532 and pK2 = 10.329 (Schwarzenbach and Meier, 1958).

In freshwaters and seawater, the alkalinity (sum of alkaline ions buffering added H + units in mequiv. L 𢄡 or mmol L 𢄡 for monovalent HCO 3 - in water which is in air equilibrium of negligible OH − and CO 3 2 - ) is almost entirely controlled by the carbonate systems with insignificant contribution from silicate and phosphate, and with some contribution by borate in seawater. At pH above 9, OH − has a significant contribution to alkalinity being 0.074 mmol L 𢄡 at pH 10 and 0.74 mmol L 𢄡 at pH 11 at an alkalinity of 2 mmol equivalents L 𢄡 (Table 3). It is thus convenient to distinguish between the total alkalinity (TA) and the CA (Dickson, 1981 Stumm and Morgan, 1996). The chemical species contributions to the two alkalinities are:

Table 3. Distribution of DIC, CO2, HCO 3 - , CO 3 2 - , and OH − as a function of pH at constant total alkalinity of 2 mmol H + equivalents L − 1 at 20ଌ.

Purging an aqueous solution with pure CO2 alters the CA through the addition of ionic carbon species and also through pH related shifts in the partitioning of carbon species already present in the solution (Eqs 4 and 5). However, the TA is not affected by bubbling with CO2 as every negatively charged ion is balanced by a proton (Eq. 6). For example, water fresh from the tap often contains CO2 above air equilibrium and so bringing it to equilibrium by purging with atmospheric air would thus lower pCO2 until a new equilibrium has been reached. According to Eq. 5, CA would decrease slightly as both CO 3 2 - and HCO 3 - decrease equivalent to the rise of OH − and pH.

For experimental purposes, an aqueous photosynthesis solution is usually prepared with a certain amount of DIC and then pH is adjusted with acid or base to that required to achieve the desired concentration of 𠇏ree” (i.e. dissolved) CO2 and HCO 3 - . Table 3 lists the relationship between pH and amounts of CO2, HCO 3 - , CO 3 2 - , and OH − at 20ଌ and a fixed TA, calculated from Gutz (2012). The examples provided in the sections below demonstrate how to apply all the above information in practice.

In the next sections (See “The Rotating Wheel Incubator” to “The Open Natural System”) we describe methods in use for measurements of underwater photosynthesis. The methods scale from phytoelements to communities. The approaches involve laboratory and field techniques and so have different levels of control of key environmental variables influencing photosynthesis.

The Rotating Wheel Incubator

Principle: Leaf samples or algal thalli are incubated in glass vials of a known concentration of CO2 in an aqueous medium, and the sealed vials of known volume are rotated on an incubator under well defined light and temperature conditions. O2 produced during incubation is measured by an electrode/optode and underwater net photosynthesis can be calculated based on e.g., leaf area, fresh mass, dry mass, and/or chlorophyll. Alternatively, consumption of DIC can be used as a photosynthetic measure. Incubation in darkness provides data on dark respiration.

Medium and tissue

The choice of medium is basically between an artificial medium with a well defined ion and gas composition or ambient water with the ion and gas composition of natural habitats (essential chemical parameters such as pH, DIC, and alkalinity should be characterized). An example of an artificial medium is the Smart and Barko (1985) general purpose culture medium. This medium contains (mmol L 𢄡 ) 0.62 Ca 2+ , 0.28 Mg 2+ , 0.28 SO4 2−, and 1.24 Cl − and KHCO3 (sometimes mixed with NaHCO3) is used to generate the required DIC. HCl, NaOH (or KOH), atmospheric air or gas mixtures of known pCO2 can be used to adjust pH to a required value based on the desired amount of free CO2. Since all incubations are short term, there are no micro nutrients or vitamins in this medium. Some studies have also used submergence solutions or 𠇊mbient” water from streams or lakes in order to establish a rate of photosynthesis under specific conditions (Sand-Jensen et al., 1992 Nielsen, 1993 Sand-Jensen and Frost-Christensen, 1998) and these can also be adjusted to predefined pH, CO2 and/or O2 levels. Any production of O2 by microalgae or consumption by microbial organisms in ambient water is accounted for in the blanks micro-filtration of water is commonly used to remove background microflora.

Photorespiration, as previously demonstrated for rice (Setter et al., 1989) and the aquatic pteridophyte, Isoetes australis, (Pedersen et al., 2011), during incubation is a potential issue as the evolved O2 is trapped in solution of the closed glass vial. The risk of photorespiration is increased during experiments at high temperature (Long, 1991) and with very low DIC and CO2 concentrations leading to low ratios of CO2 to O2 at the site of Rubisco (Maberly and Spence, 1989 Sand-Jensen and Frost-Christensen, 1999). Therefore, the starting partial pressure of O2 (pO2) should be brought down to approximately 50% of air equilibrium, i.e., 10 kPa. This is sufficient to address the issue of photorespiration (provided that incubation do not last long periods so that O2 produced increases above air equilibrium) and at the same time there is still enough O2 in the medium to prevent tissue anoxia before photosynthesis starts producing O2 (Colmer and Pedersen, 2008). In practice, equal volumes of medium (including all ions) are bubbled with either air or N2. After mixing the two solutions, the pO2 will be approximately 10 kPa and HCO 3 - can be added to the medium and pH adjusted accordingly to achieve the desired amount of free CO2 (see example below).

In some situations, an organic buffer may be used to maintain a constant pH in the medium during incubation. In practice, however, HCO 3 - is a natural and often sufficient buffer in itself and we do not recommend using buffers if the CA is above 1 mmol L 𢄡 as HCO 3 - would be sufficient to buffer against large pH fluctuations during incubation (Sand-Jensen et al., 1992 Colmer and Pedersen, 2008). Moreover, organic buffers can also modify membrane porters and pH at plant surfaces modifying HCO 3 - use and influx/efflux of CO2 (Price and Badger, 1985 Larsson and Axelsson, 1999 Moulin et al., 2011). pH of the medium should be measured in a sample taken of the initial solution and then also in vials after incubations. With the ongoing advancement of optodes, pH may even be measured without opening the vials if applying pH sensitive microdots (See “O2 Measurements” for description of O2 sensitive microdots). If additional buffering is required, i.e. pH measurements after incubation show unacceptable drift in pH, then MES or TES buffers may be used, e.g., at a concentration of 5 mmol L 𢄡 (Pedersen et al., 2009, 2010), though the possible influence of these buffers on HCO 3 - use must be kept in mind.

The vials (10� mL glass vials with ground glass stoppers) are filled with medium using a siphon. By siphoning the medium into the bottom of each vial, exchange of O2 and particularly CO2 with the atmosphere is minimized prepare sufficient medium to flush the vials at least twice the volume, and fill the vials completely. An air bubble can hold 36-fold more O2 as the same volume of deionized (DI) water at 25ଌ, so bubbles in the vials introduce significant error to the net photosynthesis measurements. A set of vials without tissue serves as blanks and is incubated along with the vials containing tissue samples in the rotating incubator. The blanks serve to provide the starting pO2 in the vials and also to correct for any O2 production or consumption (e.g., by algae, bacteria, or chemical processes) if ambient water is used as medium. Glass beads (Ø = 3𠄵 mm two in each 25 mL vial) are added to each vial to provide mixing as the vials are rotating in the incubator.

The amount of tissue added to each vial depends on the activity of the tissue, the amount of DIC and free CO2, the light level (PAR), and the temperature. At saturating light and CO2 levels and at 25ଌ, 0.5 mg fresh mass mL 𢄡 medium is often a good choice as this will result in a rise of pO2 by approximately 2𠄵 kPa within an hour of incubation providing reproducible and accurate determination of O2 regardless of the technique employed (see below). However, both microelectrodes and optodes have a resolution of approximately 0.01 kPa so a change in 1 kPa could also be sufficient. At lower CO2 and/or light levels, more tissue may be required or alternatively, longer incubation times are needed. However, small tissue samples are preferred to prevent self shading and to promote good mixing in the vials so that tissues are well exposed to light and chemicals during incubation.

Example 1: Preparation of artificial floodwater with CA of 2.0 mmol L 𢄡 and 200 μmol free CO2 L 𢄡 . Prepare a solution of DI water containing Ca 2+ , Mg 2+ , SO4 2− , and Cl − at the concentrations described above. Divide the solution into two containers and bubble one half of the solution with air and the other half with N2 for 20 min and then mix the two solutions. Add the required amount of DIC (Table 3, highlighted in yellow for this example) which is 2.2 mmol L 𢄡 . Add the DIC in the form of KHCO3, NaHCO3 or a mixture, and acidify the solution to pH 7.35 using HCl. This results in a solution with a CA of 2 mmol L 𢄡 (in mmol L 𢄡 : 1.995 HCO 3 - + 0.002 CO 3 2 - ) and 200 μmol L 𢄡 CO2 (Table 3).

Incubator with light and temperature control

The incubator provides constant temperature and mixing throughout the incubation. It consists of a vertically rotating wheel where glass bottles or vials can be clipped on facing the light source. The wheel rotates at about 10 rpm in a tank with temperature controlled water and a transparent glass or Perspex wall for illumination at various irradiances (Figure 1C).

The rotating wheel incubator was originally invented for photosynthesis measurements in phytoplankton (Steemann Nielsen, 1952) and the typical light source in commercially available models consists of a rack of fluorescent tubes. However, it is hard to achieve PAR levels much above 500 μmol photons m 𢄢 s 𢄡 with fluorescent light so high pressure metal halide lamps (mercury or sodium) or light emitting plasma lamps are required to provide the levels of light needed to light saturate net photosynthesis by leaves of many terrestrial species and some macroalgae with thick thalli.

Photosynthesis versus light curves (i.e. light response curves) are obtained by: (i) regulating light intensities by varying the distance of the light source to the incubator, (ii) placing neutral shading filters in front of the light source, (iii) placing a box with neutral shading filters of variable transmission in front of individual vials, or (iv) by wrapping the vials in layers of neutral shading mesh, or by a combination of these various approaches.

O2 measurements

The O2 produced or consumed during incubation can be measured directly in the glass vials using O2 electrodes or optodes. In the absence of good electrodes or optodes, the Winkler titration can also be applied see Strickland and Parsons (1972) for details.

Contemporary methods for O2 measurements in water involve either Clark type electrodes or optodes. A Clark type O2 electrode measures pO2 as molecular O2 transverses a membrane before the electrochemical reaction on the cathode results in a current which is linearly proportional to the pO2 of the medium. Since the electrode consumes O2, a conventional large O2 electrode is quite stirring sensitive and it is thus much more convenient to use an O2 microelectrode which consumes little O2 to address the stirring issue during measurements O2 microelectrodes can have a stirring sensitivity of less than 1% (Revsbech and Jørgensen, 1986 Revsbech, 1987). Oxygen microelectrodes typically have a temperature coefficient of approximately 1𠄳%ଌ 𢄡 (Revsbech, 1987 Gundersen et al., 1998) so temperature control during measurements is essential. The temperature effect on electrodes (and optodes, see below) is primarily caused by changes in diffusion and electrochemistry. In addition, temperature also influences solubility of gases, and metabolic rate of the tissues.

The measuring principle of optodes is quite different from that of a Clark type electrode. In the optode, light excites a fluorophore coated onto the tip of fiber optics and the excited light is subsequently transmitted back and measured by a spectroradiometer (Klimant et al., 1997). Alternatively, the fluorophore can be coated onto tiny plastic patches which (microdots) can be mounted directly in the medium where O2 is to be measured the microdot with the fluorophore is then illuminated from the outside through the transparent wall of the container. Molecular O2 quenches the florescence so that the transmitted signal can be calibrated toward O2 in the medium the relationships between quenching and pO2 is non-linear. Optodes do not consume O2 and are thus completely insensitive to stirring. However, O2 optodes can have higher temperature coefficients than Clark type microelectrodes and require even better temperature control during measurements (Kragh et al., 2008). On the other hand, optodes can be built into the individual glass vials (microdots glued onto the glass wall inside the vial) and the O2 concentration can be measured in a non-destructive manner (Kragh et al., 2008). The great advance of this approach is that vials can remain sealed and be returned to the rotating wheel if a preliminary reading shows that longer incubation is required in order to obtain the necessary accuracy, or O2 evolution can be followed over time to ensure quasi steady state measurements or to elucidate possible temporal patterns.

Supporting measurements and calculations

After measuring O2 of each vial, the tissue must be processed according to standard procedures to establish the area, the fresh mass or dry mass, the chlorophyll concentration, or all of the above. The underwater net photosynthesis is calculated as the net O2 evolution rate per unit tissue per unit time. In practice, the change in O2 content in each vial (change in O2 concentration multiplied by the volume of the vial individual volumes of vials (i.e. minus the volume of the glass beads, etc.) must be established) divided by the incubation time and divided by the amount of tissue (i.e., mass, area or any other of the above mentioned parameters used to scale photosynthesis per sample unit). An example of a CO2 response curve established with the technique described here in Section “The Rotating Wheel Incubator” is shown in Figure 6.

Figure 6. Underwater net photosynthesis versus CO2 concentration in the medium for excised leaf segments of Hordeum marinum. Leaf segments (30 mm) were incubated in 35 mL glass vials with various well defined CO2 concentrations on a rotating wheel with PAR of 350 μmol photons m 𢄢 s 𢄡 at 20ଌ (see Figure 1C). O2 evolution was measured with a Clark type O2 microelectrode and underwater net photosynthesis was calculated as O2 evolution per projected area per unit time (See “The Rotating Wheel Incubator”). Data (mean ± SE, n=5) from (Pedersen et al., 2010). Note: leaves of H. marinum are superhydrophobic and so possess a gas film when underwater.

The Closed Chamber with Injection Ports

Principle: a leaf or algal thalli sample is incubated in a closed chamber with internal mixing and possessing injection ports and fitted with an electrode/optode that follows O2 concentration. The amount of free CO2 can be manipulated by injection of acid or base while a fitted pH electrode allows calculation of the exact CO2 level. The approach enables production of a complete light or CO2 response curve based on the same sample, and underwater net photosynthesis can be calculated based on e.g., leaf area, fresh mass, dry mass, and/or chlorophyll concentration. Incubation in darkness can provide data on dark respiration.

Chamber with light and temperature control

The chamber for measurements of underwater net photosynthesis enables measurements with light, temperature, and CO2 manipulations in water, with monitoring of O2 with time. Chambers are commercially available for underwater photosynthesis measurements on macro algae, phytoplankton, or isolated chloroplasts and these are made from glass, acrylic glass, or acetal. These chambers can also be custom built to match specific electrodes, light sources, and fitted with extra ports for temperature and PAR sensors and injection of acid/bases or inhibitors. The chamber must be made from a material the can be sterilized and also have a least one transparent side to enable illumination of the sample. The light source can be diode based (650 nm red diode) or 𠇏ull spectrum” halogen light to simulate white sunlight. Pay attention to the fact that some lighting devices are unable to produce sufficient light to saturate the photosynthesis of some terrestrial leaves or thick macroalgae thalli. Illumination (even by means of fiber optics) produces heat, so cooling of the chamber by a water jacket is crucial.

A light sensor small enough to measure inside the chamber is also essential. The spherical PAR sensor US-SQS/L (Walz, Effeltrich, Germany) is of a size (Ø = 3.7 mm) that enables permanent installation in most chambers.

Finally, the issue of mixing must be addressed. The simplest solution is to use a glass coated stir bar (avoid Teflon coated stir bars as these can hold O2) which is isolated from the sample with a coarse mesh to prevent contact with the tissue. It may be necessary to fix the tissue in the swirling current if the tissue rotates with the water current in the chamber, the DBL will be larger than if the tissue is fixed. The thicker DBL increases the apparent resistance to CO2 uptake or O2 escape.

O2 and pH measurements

O2 measurements in the closed chamber are similar to O2 measurements in the vials described in Section “O2 Measurements.” An O2 sensor (Clark type electrode or optode) is fixed in the chamber in one of the ports, or if an optode is used, a patch with fluorophore can be glued onto the interior wall. A pH electrode is fitted in a second port and the signals from both sensors are logged onto a computer with data acquisition software. Calibration of both O2 and pH sensors should be performed in the chamber to avoid stirring related artifacts to the calibrations. Remember to pay extra attention to temperature if using O2 optodes. It may take a while for the temperature of the solution inside the chamber to equilibrate with that of the cooling jacket, and working in a constant temperature room or keeping solutions in a thermostated water bath will significantly reduce the time it takes before a temperature steady state is obtained always measure temperature directly in the chambers. Temperature influences electrode or optode performance, solubility of gases, and metabolic rate of the tissues (see Section “O2 Measurements”). After insertion of tissue and filling of the chamber with medium (see below), pH can be manipulated by injection of small amounts of acid or base through one of the injection ports. Fit a 27G needle in one of the injection ports and let it function as “over pressure valve” to prevent pressurization during injection of acid or base (or inhibitors) the needle may be left in the stopper during the experiment as diffusion of gases in water is too slow to result in experimental artifacts.

As described in Section “The Rotating Wheel Incubator” for incubations of tissues in closed vials on the wheel, substantial photorespiration can occur if O2 is allowed to build up in the medium. Therefore, the susceptibility to photorespiration should initially be established for each tissue type. The linearity of O2 production with increasing external pO2 is easily tested the following way: a medium with total DIC of 5.0 mmol L 𢄡 is prepared from KHCO3 in a 5.0 mmol L 𢄡 TES buffer adjusted to pH 8.00 and with a pO2 of 10 kPa. The tissue is then allowed to photosynthesize up to a pO2 of 30 kPa. Here, approximately 500 μmol O2 has been produced from 500 μmol CO2 and because of the TES buffer the pH has remained at 8.0. Although the DIC pool has declined to 4.5 mmol L 𢄡 , free CO2 has changed by only 10% from 110 to 100 μmol L 𢄡 . If the O2 evolution occurs linearly in this range, it means that the approximately threefold lower CO2:O2 in the medium, with likely even greater changes in internal CO2:O2, has not increased photorespiration. If the curve exhibits a saturation tendency (i.e. declining rate of net O2 production with increasing pO2), photorespiration has probably increased with increasing pO2 in the chamber.

Medium and tissue may be prepared as described in Section “Medium and Tissue.” However, as a CO2 response curve in the closed photosynthesis chamber often involves conversion of HCO 3 - into free CO2 (dissolved), e.g., by manipulation of pH, enough HCO 3 - must initially be present in the medium to produce the required levels of free CO2. Following injection of small amounts of acid or base to manipulate free CO2, the rate of net photosynthesis changes accordingly so that a new rate of net O2 production (slope of dissolved O2 with time) is established at each dissolved CO2. However, pH may also change slightly in the time interval because CO2 is extracted from the system as it is fixed via photosynthesis (Eqs 1 and 4). Hence, for every rate of underwater net photosynthesis determined in a time interval, the mean CO2 concentration must be calculated in order to present the CO2 response curve of the tissue.

Example 2: average free CO2 concentration in the pH range from 7.25 to 7.30 in a medium with total DIC of 2.0 mmol L 𢄡 . According to Gutz (2012), CA of such a solution at pH 7.25 would be 1.77 mmol L 𢄡 having 223 μmol CO2 L 𢄡 at pH 7.30 CA would be 1.80 mmol L 𢄡 and have 203 μmol CO2 L 𢄡 . Consequently, the average free CO2 concentration in the pH range was 213 μmol CO2 L 𢄡 .

After each experiment, the incubated tissue must be characterized to enable calculation of underwater net photosynthesis rates the supporting measurements are as those described in section “Supporting Measurements and Calculations.”

PH Drift Approach to Establish CO2 Compensation Points

Principle: Leaf or algal thalli samples are incubated in glass vials for 16� h where after pH and CA or DIC are measured. CO2 compensation points and carbon extraction capacity of tissues can be calculated. The method is also used as a diagnostic test for bicarbonate ( HCO 3 - ) use in underwater photosynthesis.

These long term incubations are used to test how far net photosynthesis of a given plant sample at saturating light can extract DIC, i.e. to deplete CO2 and HCO 3 - and drive up pH. Because the objective is to determine the ultimate DIC extraction capacity and maximum upper pH in a standardized way, all incubation vials are prepared to have an equal standard DIC concentration (usually 1𠄲 mmol L 𢄡 for alkaline waters and 0.1𠄰.3 mmol L 𢄡 for softwaters) and a pH, CO2, and O2 concentration corresponding to air equilibrium (Sand-Jensen et al., 1992, 2009). Artificial media and natural waters can be applied. However, to minimize O2 build up and the risk of photorespiration during extended incubation the initial O2 can be reduced to 20�% of air equilibrium. To ensure the maximum possible DIC depletion, the amount of plant material is typically three times larger than in the incubations described in Sections “The rotating Wheel Incubator” and “The Closed Chamber with Injection Ports” though it must still be able to move freely in the vials to ensure adequate mixing.

The initial and final DIC and pH must be determined in order to calculate the DIC extraction capacity during incubation and the CO2 compensation point after incubation. Provided no internal pools of DIC and protons interfere with conditions in the water/medium and no precipitation or dissolution of carbonates takes place, DIC can be determined in the medium from CA, pH, temperature, and ionic strength CA in turn can be determined by acidimetric titration (Stumm and Morgan, 1996). The risk of carbonate precipitation is small in artificial media of KHCO3 and much larger in natural waters and artificial media where Ca(HCO3)2 dominates, the reason being that K2CO3 is highly soluble and CaCO3 is poorly soluble. Calcium carbonate precipitation is likely to take place in pH drift experiments where final pH exceeds 10. Therefore, it is always recommended to directly measure DIC. This can be done by injecting of small water samples into concentrated acid in a bubble chamber purged with N2 gas carrying the released CO2 into an IRGA (Vermaat and Sand-Jensen, 1987). Water samples may need to be filtered (with no atmospheric contact) if minute CaCO3 crystals have been formed in the external water of high pH. It is generally recommendable to determine (or check) CO2 compensation points by depletion experiments in media of low initial DIC (㱐 μmol L 𢄡 ) and low pH (φ.5) where the interference by HCO 3 - is low and CaCO3 is not formed.

The pH drift technique has also been used to determine DIC consumption at intervals during the ongoing drift of pH upwards (Maberly and Spence, 1983 Spence and Maberly, 1985). DIC, pH, the proportion of carbon species and O2 change during the time of incubation. Because all parameters may influence photosynthesis, and exchange with internal DIC and proton pools in the incubated tissue may interfere with calculations, we cannot recommend the procedure for determining rates of net photosynthesis considering the much more accurate and straightforward methods being available today (as described in this review).

Community Photosynthesis in Large Chambers

Principle: Community photosynthesis is measured in large closed chambers with linear dimensions of 0.5𠄰.6 m, or larger, to minimize edge effects and make certain that natural changes of plant density, tissue capacity and irradiance through the canopy are maintained. Photosynthetic rates are measured by O2 and DIC, as for phytoelements in small chambers (See The Closed Chamber with Injection Ports), but photosynthetic parameters and their dependence on DIC and temperature are markedly different for communities than phytoelements.

Submerged aquatic plants grow in communities of variable density where the spatial structure and self shading are prominent features (Sand-Jensen, 1989). Light limitation is substantial and the efficiency of photosynthesis at low light is therefore important (Binzer and Sand-Jensen, 2002a,b). The photosynthetic chamber needs to be large enough to include tall communities (Binzer et al., 2006 Middelboe et al., 2006). It is made of glass or transparent acrylic glass and viewed from above, the shape of photosynthetic chambers can be cylindrical, rectangular, or quadratic. The cylindrical shape can be advantageous because the surface area of side walls relative to chamber volume is smaller than in rectangular or quadratic chambers, and these two latter types may also have � corners” with stagnant waters. The light sources are high pressure metal halide lamps (mercury or sodium) or light emitting plasma lamps because only those provide a sufficiently high irradiance (� μmol photon m 𢄢 s 𢄡 ). The light sources must be placed more than 0.5 m above the photosynthetic chamber and the light path both above the chamber and around the chamber walls are surrounded by totally reflecting material to reduce the influence of distance with depth in the chamber both when plants are absent or present. Irradiance is measured with depth in the water and through canopies of different densities using a small spherical PAR sensor. To ensure statistically reliable determinations of vertical attenuation a series (e.g., 10) of measurements are performed at different positions (Middelboe et al., 2006). Temperature, O2, DIC, and pH are set and measured as described in Section “The Closed Chamber with Injection Ports,” while mixing is provided by large submersible pumps ensuring current velocities above 2 cm s 𢄡 . Temperature control is attained by direct cooling and warming of the water in the incubation chamber or by placing it in a larger temperature controlled holding tank. In the latter case some temperature variations (1𠄳ଌ) is difficult to avoid between light and darkness.

Algal communities for measurements can be collected attached to stones or established over a period of one or several years on artificial tiles of desired size set out in the field and later brought to the laboratory for measurements in the photosynthetic chamber (Binzer et al., 2006 Middelboe et al., 2006). Rooted submerged plants can be harvested from natural stands with the 3D structure kept intact when roots and rhizomes are interwoven. In other cases, individual plants are placed in a homogeneous pattern on the chamber bottom in small plastic bags surrounding the root system. Alternatively the individuals are tied to a frame on the chamber bottom. Plant density is determined as fresh mass, dry mass, or plant surface area normalized to bottom area. Leaf area indices (LAI) ranging from 1 to 12 are useful for comparisons among species. Vertical distribution of plant biomass and surface can be determined by cutting the plants sequentially in well defined strata starting at the top of the canopy.

The setup is suited to evaluate the influence on community photosynthesis by variable irradiance, temperature, DIC (including variable CO2 and HCO 3 - ), canopy density, and spatial structure (Sand-Jensen et al., 2007).

Community photosynthesis can also be determined over longer periods of time by employing the large chambers in an open mode. This allows for exchange of O2 and CO2 with the atmosphere to prevent that the chambers undergo too extensive accumulation and depletion in the water during several days of alternating light or dark periods. For calculation of photosynthesis and respiration, exchange rates between air and water must be determined. The flux (Fexch, mol m 𢄢 s 𢄡 ) between water and air for O2 is given by the equation:

where K is the exchange coefficient (piston velocity, ms 𢄡 ), Cact is the actual and Cequ is the equilibrium concentration of O2 (mol m 𢄣 ) in water at the actual temperature (Staehr et al., 2012b). Piston velocity is controlled by surface turbulence and can, therefore, be considered a constant for a given mixing regime determined by the strength and location of the pumps and the dampening influence of the plant community. Thus, K must be directly measured for a given plant density and mixing regime. This is best done in the dark, where only dark respiration (mol m 𢄢 s 𢄡 ) takes place, by modifying Cact to for example 10 or 30 kPa and measuring the total O2 flux (F) over time as a result of respiration and exchange with the atmosphere above from time changes in O2 concentrations in the water:

From 30 kPa the actual pO2 will first rapidly decline as a combined result of respiration and loss to the atmosphere and gradually decline less rapidly as pO2 approaches equilibrium with the atmosphere and respiration alone drives pO2 further downwards. Calculations of pO2 changes over time in relation to differences in the pO2 gradient between water and air produces a straight line (Eq. 8) permitting calculation of R and K assuming that they remain constant for a given mixing intensity and plant density.

Community measurements operated in an open mode have the main advantage for future application that fluxes of O2, DIC, Ca 2+ , H + , and nutrient ions (NH4 + , NO3 −, and PO4 3− ) can be determined during repeated diel light dark cycles for several weeks while the submerged plants may also grow. Combined field measurements have been operated in open chambers and mesocosms under a strict mixing regime under natural temperature and light conditions both for phytoplankton (e.g., Markager and Sand-Jensen, 1989), submerged aquatic plants (e.g., Liboriussen et al., 2005), and flooded terrestrial plants (e.g., Setter et al., 1988).

The Open Natural System

Principle: Natural ecosystems dominated by submerged aquatic plants have free undisturbed gas exchange with the atmosphere and input/output of water. Determination of ecosystem metabolism by open water measurements requires accurate calculations of atmospheric exchange of O2 and CO2. The main advantages of the ecosystem approach is that environmental conditions and processes are natural and temporal patterns can be followed over months or years, while allowing plant density and acclimation to gradients in light, DIC, and other environmental variables to develop.

Photosynthesis of submerged aquatic plants derived from analysis of ecosystems can only be determined when rooted plants or macroalgae are the main phototrophs responsible of more than 90% of ecosystem photosynthesis. Only then can the patterns obtained be referred to the metabolism of macrophytes accepting that a minor error (㰐%) due to photosynthesis of microalgae may be present. The dominance of submerged aquatic plants can be realized in shallow plant rich ponds, lakes, streams, and coastal lagoons. Open water measurements are used to follow changes in O2, DIC, pH, temperature, and irradiance, and enable calculation of ecosystem net production, plant gross production, and community respiration assuming fully mixed conditions (Odum, 1956 Staehr et al., 2012a). Meteorological observations of wind direction, wind velocity, atmospheric pressure, etc., in standing waters and current velocity, water depth, slope, and bed roughness in flowing waters, can be used to estimate physical exchange coefficients of gases (i.e. piston velocities) and thus calculate fluxes between water and atmosphere using empirical models (Sand-Jensen and Staehr, 2011). Flow chambers, floating chambers, inert gases, and coverage of water surfaces by impermeable floating plastic can be used for direct determination of exchange coefficients which are critical in all determinations of ecosystem metabolism (Staehr et al., 2012a,b). Rooted plants with gas filled lacunae formation and release of gas bubbles can introduce error. Oxygen storage may delay establishment of steady state exchange of O2 following dark light switches by some 10� min for most rooted plants (Westlake, 1978) and loss of bubbles is negligible in swift flowing waters, while bubble release may account for 10% of net O2 release in slow flowing waters (Kragh et al., unpublished data).

The strength of these measurements is that they provide natural rates under fully realistic and undisturbed environmental conditions. They can reveal the coupling between O2 and carbon metabolism, the natural precipitation and dissolution of carbonates and the direct involvement of accumulation and release of acids in the photosynthetic process. Measurements have shown fast exchange rates of protons between macrophytes and water following diurnal light dark switches partly uncoupled from exchanges of DIC during photosynthesis and respiration a phenomenon that is not unraveled in short term laboratory measurements with detached phytoelements (Kragh et al., unpublished data). Ecosystem measurements can also reveal how early summer growth in biomass and late summer senescence influence plant metabolism and how ongoing desiccation of ponds may suddenly stop photosynthesis and accelerate decomposition, while refilling may restart photosynthesis and growth (Christensen et al., 2013). Modeling approaches, as successfully used for canopy level understanding of terrestrial systems systems (Ainsworth and Long, 2005), should also be applied more widely in studies of aquatic systems (e.g., Binzer and Sand-Jensen, 2002a,b). All techniques for measuring and calculating ecosystem process are basically available (Staehr et al., 2012a) and awaits broad scale application.


Is photosynthesis faster in aquatic plants rather than terrestrial plants? - Biology

Life on Earth as we know it would not be possible without the evolution of plants, and without the transition of plants to live on land. Land plants (also known as embryophytes) are a monophyletic lineage embedded within the green algae. Green algae as a whole are among the oldest eukaryotic lineages documented in the fossil record, and are well over a billion years old, while land plants are about 450–500 million years old. Much of green algal diversification took place before the origin of land plants, and the land plants are unambiguously members of a strictly freshwater lineage, the charophyte green algae. Contrary to single-gene and morphological analyses, genome-scale phylogenetic analyses indicate the sister taxon of land plants to be the Zygnematophyceae, a group of mostly unbranched filamentous or single-celled organisms. Indeed, several charophyte green algae have historically been used as model systems for certain problems, but often without a recognition of the specific phylogenetic relationships among land plants and (other) charophyte green algae. Insight into the phylogenetic and genomic properties of charophyte green algae opens up new opportunities to study key properties of land plants in closely related model. This review will outline the transition from single-celled algae to modern-day land plants, and will highlight the bright promise studying the charophyte green algae holds for better understanding plant evolution.


C4 photosynthesis boosts growth by altering physiology, allocation and size

C4 photosynthesis is a complex set of leaf anatomical and biochemical adaptations that have evolved more than 60 times to boost carbon uptake compared with the ancestral C3 photosynthetic type(1-3). Although C4 photosynthesis has the potential to drive faster growth rates(4,5), experiments directly comparing C3 and C4 plants have not shown consistent effects(1,6,7). This is problematic because differential growth is a crucial element of ecological theory(8,9) explaining C4 savannah responses to global change(10,11), and research to increase C3 crop productivity by introducing C4 photosynthesis(12). Here, we resolve this long-standing issue by comparing growth across 382 grass species, accounting for ecological diversity and evolutionary history. C4 photosynthesis causes a 19-88% daily growth enhancement. Unexpectedly, during the critical seedling establishment stage, this enhancement is driven largely by a high ratio of leaf area to mass, rather than fast growth per unit leaf area. C4 leaves have less dense tissues, allowing more leaves to be produced for the same carbon cost. Consequently, C4 plants invest more in roots than C3 species. Our data demonstrate a general suite of functional trait divergences between C3 and C4 species, which simultaneously drive faster growth and greater investment in water and nutrient acquisition, with important ecological and agronomic implications.


All wet or dried up? Real differences between aquatic and terrestrial food webs

Ecologists have greatly advanced our understanding of the processes that regulate trophic structure and dynamics in ecosystems. However, the causes of systematic variation among ecosystems remain controversial and poorly elucidated. Contrasts between aquatic and terrestrial ecosystems in particular have inspired much speculation, but only recent empirical quantification. Here, we review evidence for systematic differences in energy flow and biomass partitioning between producers and herbivores, detritus and decomposers, and higher trophic levels. The magnitudes of different trophic pathways vary considerably, with less herbivory, more decomposers and more detrital accumulation on land. Aquatic–terrestrial differences are consistent across the global range of primary productivity, indicating that structural contrasts between the two systems are preserved despite large variation in energy input. We argue that variable selective forces drive differences in plant allocation patterns in aquatic and terrestrial environments that propagate upward to shape food webs. The small size and lack of structural tissues in phytoplankton mean that aquatic primary producers achieve faster growth rates and are more nutritious to heterotrophs than their terrestrial counterparts. Plankton food webs are also strongly size-structured, while size and trophic position are less strongly correlated in most terrestrial (and many benthic) habitats. The available data indicate that contrasts between aquatic and terrestrial food webs are driven primarily by the growth rate, size and nutritional quality of autotrophs. Differences in food-web architecture (food chain length, the prevalence of omnivory, specialization or anti-predator defences) may arise as a consequence of systematic variation in the character of the producer community.

1. Introduction

The search for commonalities and contrasts among ecosystems has yielded some of the most informative patterns and insights in ecology. Ideas about trophic structure, diversity, energy flow and nutrient cycles percolate freely across systematic and disciplinary boundaries. However, large differences in emphasis persist among ecologists working in different environments. For instance, evidence for the role of bottom-up factors (abiotic resources like nutrients, energy and water) in controlling terrestrial primary productivity is unequivocal, while that for trophic interactions is much more sparse. Aquatic ecologists have long recognized the importance of bottom-up forces, but have also shown major influence of top-down processes like herbivory and indirect effects of higher trophic levels (e.g. trophic cascades). The different histories and trajectories of aquatic and terrestrial ecology suggest either that different processes are at work in these systems, or that social and disciplinary forces constrain the thinking of scientists and lead to divergent lines of inquiry. Ecologists have often claimed that ecosystems vary in their underlying structure and the processes that govern their dynamics (Elton 1927 Lindeman 1942 Strong 1992 Hairston & Hairston 1993 Chase 2000). However, only recently has sufficient data for direct quantitative comparison become available (Cyr & Pace 1993 Cyr et al. 1997 Cebrian 1999 Elser et al. 2000 Shurin et al. 2002 Cebrian 2004 Cebrian & Lartigue 2004).

Elton (1927) first proposed a ‘pyramid of numbers’, where primary producers dominate and consumer densities decrease as organisms become more remote from the base of production. This generality apparently applies well to most terrestrial systems, but aquatic ecosystems often violate Elton's rule with inverted biomass pyramids, or ratios of heterotroph-to-autotroph biomass (H : A) greater than 1 (Del Giorgio et al. 1999). To explain the differences in biomass partitioning between aquatic and terrestrial ecosystems, Lindeman (1942) hypothesized systematic contrasts in trophic efficiency and energy flow by observing the successional transitions of lakes from lacustrian to bog mats to terrestrial states.

The relative absence of massive supporting tissues in plankters and the very rapid completion of their life cycle exert a great influence on the differential productivities of terrestrial and aquatic systems. The general convexity of terrestrial systems as contrasted with the concavity of aquatic substrata results in striking trophic and successional differences. (Lindeman 1942, p. 402)

Lindeman identified two salient system properties that may generate contrasts in trophic transfer efficiency and biomass partitioning among different parts of the food web. The first is that primary producers in pelagic systems (and some benthic habitats) are predominantly unicellular, whereas terrestrial plants are multicellular and structurally complex. This contrast in organismal size between phytoplankton and plants has major implications for life history parameters, rates of biomass turnover and allocation to tissues with different chemical compositions and nutritional qualities (Peters 1983 Brown & West 2000). The second difference Lindeman proposes is that aquatic systems lie at low positions in the landscape and, therefore, accumulate nutrients and detritus through runoff, whereas limiting mineral elements like nitrogen (N) and phosphorus (P) leach out of soil and into lakes, streams and ultimately the oceans. Aquatic systems may therefore be more nutrient-rich and receive more inputs of allochthonous detritus than their terrestrial counterparts.

Size structure. Pelagic food webs are more strongly size-structured than terrestrial, with clear positive correlations between organismal body size and trophic position. Terrestrial consumers range in size from much larger (e.g. ungulate grazers) to much smaller (e.g. forest lepidoptera) than the plants they consume. Benthic food webs share characteristics of both pelagic and terrestrial, with some multicellular (e.g. macrophytes) and some unicellular (e.g. benthic diatoms) producers.

Growth rate. Producer communities in different ecosystems fix carbon at similar absolute rates however, less material is stored in living biomass in phytoplankton communities than in forests or grasslands (Cebrian 1999). Primary producers therefore replace their tissues at a faster rate in water than on land. Macrophytes have higher mass-specific growth rates than terrestrial plants, indicating that the contrast is not solely a product of allometry.

Nutrient stoichiometry. Because they lack structural and transport tissues, phytoplankton are composed almost entirely of nutrient-rich (high N and P) photosynthetic material. Heterotrophs in all systems have high demands for N and P relative to supply in primary producers and therefore face nutritional deficit. However, terrestrial consumers experience greater imbalance than those in aquatic systems (Elser et al. 2000).

We propose that the above demonstrated contrasts lead to a number of emergent properties that constrain the pattern of feeding links in food webs, the degree of omnivory, the distribution of body sizes, the vertical flow of materials from producers to consumers, and reciprocal top-down effects of consumers and predators. They also have implications for global chemical cycles and the responses of aquatic and terrestrial ecosystems to anthropogenic changes like N deposition or elevated CO2.

2. The patterns

(a) Bottom-up control

Ideas about trophic flow of energy and materials can be traced to classic studies from both terrestrial and aquatic systems (Elton 1927 Lindeman 1942 Odum & Odum 1955 Hutchinson 1959 Odum et al. 1962). These studies share the perspective that the configuration of food webs (the number and identities of important pools and fluxes, their relative sizes and the connections among them) is an emergent property of the supply of energy or nutrients entering the system, and the efficiencies of trophic transfer among the compartments. According to this view, apparent contrasts between aquatic and terrestrial ecosystems arise from differences in energy or nutrient availability, or the efficiency with which energy or materials are exchanged through trophic linkages. Although rates of net primary production are similar across ecosystems (Cebrian 1999), herbivorous zooplankton in lakes remove a three to four times greater proportion of primary productivity than grazers in terrestrial systems (Cyr & Pace 1993 Hairston & Hairston 1993 Cebrian 1999), and aquatic consumers can be anywhere from six to sixty times more abundant on an areal basis within similar body size classes (Cyr et al. 1997). These data suggest that systematic variation in trophic structure is not due to differences in the amounts of energy or nutrients supplied by photosynthesis. Rather, the efficiencies of herbivores at removing plant material and converting it to their own biomass are greatest in lake plankton, lowest in forests and intermediate in grasslands. These patterns imply that differences in the plant–herbivore link rather than the overall supply of energy govern trophic structure variation across systems.

Hairston & Hairston (1993) present a contrasting view that the number of trophic levels present and the partitioning of biomass among them are not constrained by energetics or nutrition, but are consequences of evolutionary traits such as body size and feeding mode. Hairston & Hairston (1993) argue that terrestrial food webs contain only three functional trophic levels (plants, herbivores and primary predators), while the pelagic zones of lakes often have abundant piscivorous fishes that occupy a fourth trophic level. They invoke size-structured predation and gape limitation as explanations for varying numbers of trophic levels. Grazing zooplankton remove a greater fraction of primary productivity than terrestrial herbivores (Cyr & Pace 1993 Cebrian 1999), and may suffer lower levels of predatory losses (Hairston & Hairston 1993). Hairston & Hairston (1993) argue that these differences occur because terrestrial primary predators suppress carbon flow through the herbivorous pathway, causing more biomass to be diverted toward detrital accumulation and away from the classical food chain. They based their arguments on the largest data compilation available at the time, which was limited to a few studies in temperate forest, grassland and lentic systems. More recent syntheses of larger data sets have upheld their conclusion that the rate of grazing differs substantially between aquatic and terrestrial systems. However, their contention that the grazing contrast reflects differences in food chain length is not supported by evidence from trophic cascade experiments (see §2b).

Cebrian and co-workers (Cebrian 1999, 2004 Cebrian & Lartigue 2004) synthesized an extensive data set on the fate of carbon fixed by primary productivity across ecosystem types. The data reveal marked contrasts between aquatic and terrestrial environments in a number of important trophic pathways (figure 1). First, net primary productivity ranges over more than two orders of magnitude across all systems, but does not vary consistently between aquatic and terrestrial environments. Second, pools of both detritivore and herbivore biomass accumulate with increasing primary productivity. The slope of the scaling relationship is similar across ecosystems but the intercept varies considerably. The patterns of biomass partitioning among food-web components are therefore consistent along productivity gradients. Thus, the entire food web swells as more inorganic resources become available at the base. The different components increase at similar rates that vary consistently between the aquatic and terrestrial spheres. These differences persist across the entire global range of primary productivity from deserts and oligotrophic lakes and oceans to productive forests and eutrophic aquatic systems.

Figure 1 Differences in pathways of carbon flow and pools between aquatic and terrestrial ecosystems. The figure summarizes the patterns demonstrated in Cebrian (1999, 2004) and Cebrian & Latrigue (2004). The thickness of the arrows (flows) and the area of the boxes (pools) correspond to the magnitude. The size of the pools are scaled as log units since the differences cover four orders of magnitude. The C's indicate consumption terms (i.e. CH is consumption by herbivores). Ovals and arrows in grey indicate unknown quantities.

Rates of carbon flux between producer, herbivore and detritivore pools also contrast markedly among ecosystems and show consistent variation across levels of basal productivity. Cebrian (1999) showed that, on average across levels of productivity, the turnover rate of phytoplankton is on the order of 1000 times that of forests, 100 times faster than grasslands and 10 times faster than multicellular aquatic producers. Since net primary productivity does not vary by system, less carbon is stored in the living autotroph biomass pool and producer biomass is consumed by aquatic herbivores at four times the terrestrial rate. Although detritivores consume similar quantities of detrital carbon in the two ecosystems (figure 1), decomposers are much more abundant in terrestrial systems. This suggests that aquatic decomposers suffer greater losses to predation and/or recycle nutrients into the inorganic pool at faster rates as they accumulate less biomass despite similar consumption levels. Energy flow from the detrital loop to consumers with higher trophic positions (e.g. zooplankton eating bacteria) has been proposed as one explanation for steeper biomass pyramids in oligotrophic than eutrophic lakes (Del Giorgio et al. 1999 Prairie et al. 2002). The patterns suggest that terrestrial decomposers may be nutrient limited and, therefore, less efficient than their aquatic counterparts (Swift et al. 1979). The detrital pathway may also be more of a dead end from the perspective of higher trophic levels on land (e.g. accumulation of refractory carbon).

(b) Top-down control

Evidence for bottom-up control is shown by correlations in abundance or biomass between consumers and their resources, and in rates of fluxes along productivity gradients. Ideas about top-down control are more difficult to evaluate. For instance, top-down control cannot operate the same way in herbivorous and detritivorous chains because decomposers cannot influence the renewal rate of the detritus except by indirect means (e.g. nutrient recycling Moore et al. 2003). The rate of biomass movement from one pool to another is one measure of the strength of top-down control by consumption. However, the rate of flux is not necessarily a good indicator of a consumer's effect on standing biomass of its resource. Consumption can either stimulate or suppress production of the prey population (De Mazancourt et al. 1998), or have no impact (i.e. donor-control De Angelis 1975). Consumption rate and population impact measure different aspects of interaction strength (Berlow et al. 1999). Field measurements indicate that consumption of living plant biomass by herbivores is three to four times greater in water than on land, and that aquatic decomposers consume more than ten times as much detritus on a mass-specific basis (figure 1). Top-down effects are greater in water in the sense that first-order consumers (herbivores and decomposers) remove carbon at a faster rate than those on land (Cebrian 1999). Their effects on standing stocks can be assessed by removal experiments. Below we review evidence for systematic differences in top down control by predators via herbivores from trophic cascade experiments.

Whether the top-down impact of consumers and trophic cascades (indirect effects of predators) vary among ecosystems is a subject of active debate in ecology (Strong 1992 Polis & Strong 1996 Polis 1999 Chase 2000 Polis et al. 2000 Schmitz et al. 2000 Halaj & Wise 2001). Recent meta-analyses of the literature on trophic cascade experiments found considerable variation among ecosystems and between habitats within systems (Shurin et al. 2002 Borer et al. 2005). The biomass response of plant communities to removal of primary predators was larger in aquatic systems than terrestrial. This result supports evidence from observational measurements of the flow and accumulation of carbon through trophic links that aquatic and terrestrial food webs differ systematically in their structure and function (figure 1). Greater herbivory in aquatic habitats leads to stronger impact of consumption on the standing stock of primary producers, and larger indirect effects of predators. Lesser top-down control observed in terrestrial ecosystems is a consequence of weakness in the herbivore–plant link. That is, terrestrial predators have comparable impacts on their herbivore prey to those in many aquatic systems however, the reduced grazer community elicits a relatively weak response at the level of primary producers. This result contrasts with the contention of Hairston & Hairston (1993) that longer aquatic food chains drive aquatic–terrestrial contrasts. If primary predators on land are under weaker top-down regulation (fewer secondary predators), then we expect their removal to have smaller effects on herbivores. Examples of webs with four functional trophic levels have been shown in freshwater (Drenner & Hambright 2002), marine (Estes et al. 1998) and terrestrial (Letourneau & Dyer 1998) ecosystems however, empirical quantification of their dynamical significance remains to be performed.

The meta-analyses of trophic cascade experiments also reveal large variability within systems, and several limitations and biases in the existing experimental literature. First, aquatic systems vary considerably in the magnitude of the expression of trophic cascades (see figure 1 in Shurin et al. 2002). Marine and freshwater benthic habitats have some of the strongest cascades, whereas marine plankton shows negligible phytoplankton responses to planktivore removal. Observed differences among marine and freshwater pelagic systems may arise from greater omnivory by calanoid copepods in the ocean than by the cladocerans that dominate zooplankton in many lakes (Stibor et al. 2004). Second, the terrestrial literature is limited in the range of habitats where predator manipulations have been attempted, and where effects are measured at the level of primary producer biomass. Nearly all studies where plant community biomass was assessed occurred in grassland and agricultural systems (Shurin et al. 2002). Studies in forests are rare due to methodological and timescale difficulties, and generally measure response by single plant species (‘species cascades’ sensuPolis et al. 2000) or responses such as leaf damage which are not directly comparable with other systems (Schmitz et al. 2000). Although the present literature indicates stronger trophic cascades in water, the range of terrestrial systems considered is limited. Moreover, there has been little attention accorded to trophic structure in belowground systems (but see Mikola & Setälä 1998 Moore et al. 2003), even though underground standing biomass and primary production can exceed the levels aboveground (Jackson et al. 1997).

Data syntheses indicate prominent differences in the strengths of top-down and bottom-up forces between aquatic and terrestrial environments. The studies of Cebrian (1999, 2004) and Cebrian & Lartigue (2004) show clear variation in carbon flow and accumulation, but not assimilation from the inorganic pool. Synthesis of trophic cascade experiments indicates that reciprocal top-down control via herbivores and indirect effects of predators are also greater in aquatic ecosystems (Shurin et al. 2002 Borer et al. 2005). Thus, aquatic herbivores remove more carbon from the autotroph community, exert greater influence on the biomass of primary producers and transmit stronger indirect effects from higher trophic levels. We now turn our attention to evaluating candidate hypotheses for the striking contrasts in food-web structure across ecosystems.

3. The mechanisms

(a) Size

Lindeman's (1942) first proposed cause of aquatic–terrestrial variation is that unicellular producers dominate many aquatic ecosystems but are virtually absent on land. Size clearly has different implications for ecological performance in the two environments. Large phytoplankton suffer greater losses due to sinking and have less surface area (per unit biomass) over which to absorb nutrients from their environment (Sommer 1989). However, size also confers resistance to planktonic herbivores that are often gape-limited in the maximum particle size they can ingest. This may explain why more productive pelagic environments in lakes and the ocean are dominated by larger phytoplankton (Watson & McCauley 1988 Sommer 2000 Stibor et al. 2004). Under oligotrophic conditions, large algae are at a disadvantage because their low surface-to-volume ratio reduces their capacity to absorb limiting nutrients, whereas grazing losses become more important in productive environments. By contrast, large terrestrial plants may be better able to compete for nutrients or water in the soil and for light by overtopping their neighbours (Falster & Westoby 2003). Size may be less of a defence against herbivory on land since most grazers consume parts of plants rather than entire individuals. Competition for resources therefore creates selection for small size in planktonic autotrophs and large size in land plants.

Autotroph size also places unique selection on herbivores in water versus land. Pelagic herbivores are virtually all larger than the phytoplankton they consume (Cohen et al. 2003), whereas terrestrial herbivores range from much smaller (e.g. forest lepidoptera) to much larger (e.g. ungulates) than their plant resources. On balance, predators in all systems are generally larger than their prey (Cohen et al. 1993), although parasites, pathogens and cooperative hunters are obvious exceptions. The correlation between body size and trophic position extends across all organisms in pelagic systems, but breaks down at the autotrophic and herbivorous end of terrestrial webs. The large size of terrestrial plants has a number of important consequences that may influence the structure of the entire web. Terrestrial plants are less productive per unit standing biomass because growth rate declines with size in primary producers (Nielsen et al. 1996). Allometric constraints may explain the faster turnover time of phytoplankton relative to terrestrial plants. However, aquatic macrophytes also exhibit faster growth than terrestrial plants (Cebrian 1999). This suggests that allometry is not the whole explanation for aquatic–terrestrial differences in turnover rates (see §3b).

Allometric considerations make predictions about how relative sizes of producers and consumers should affect the vertical flow of energy and top-down impact of consumption. Since small producers have high mass-specific growth rates (Nielsen et al. 1996 Niklas & Enquist 2001), consumers derive greater nutritional benefit from them. Biomass that is removed from a fast-growing plant community is replaced at a greater rate, therefore faster turnover times can sustain more secondary productivity. Larger consumers, similarly, have lower mass-specific metabolic rates (Peters 1983) and therefore are more efficient at converting food to their own tissues. Metabolic rate is also greater in vertebrates than invertebrates, and in endotherms than ectotherms. A metabolically constrained food chain model derived by Yodzis & Innes (1992) predicts that the strength of herbivore control over producers and trophic cascades are greatest when the ratio of consumer-to-producer size is highest (Shurin & Seabloom 2005). Since pelagic herbivores are virtually all larger than their algal resources (Cohen et al. 2003), this condition is common in many aquatic ecosystems. In addition, the largest terrestrial herbivores are endotherms (mammals) with high metabolic demands. The energetics of size, therefore, may help understand why aquatic food webs support higher secondary production, steeper biomass pyramids and stronger trophic cascades.

Size also has important implications for the spatial scale of patchiness at which organisms experience their environment (Ritchie & Olff 1999), which in turn may influence differences in food-web structure and strength of interactions between systems. Since many terrestrial plants are larger than their herbivores, they may respond to spatial patchiness at broader scales. For instance, a tree is affected by the nutrient conditions encountered by its roots and the light reaching its leaves, whereas a folivorous insect may live its entire life on one leaf. In aquatic ecosystems, trophic position is positively correlated with both body size and scale of individual movement. McCann et al. (2005) showed that more spatially confined consumers exerted stronger top-down effects than wider ranging ones that encounter multiple dispersed prey populations. Pelagic cascades tend to be stronger in lakes than in marine systems (Shurin et al. 2002), perhaps explained in part by the relative confines of space for top predators (McCann et al. 2005). Moreover, home ranges of piscivorous fish tend to be smaller, and increase with body size more slowly, than mammals or birds of similar biomass (Cyr et al. 1997). Differences in the scale of patchiness between aquatic and terrestrial environments may have consequences for energy flow and the transmission of top-down effects that have not yet been fully explored.

(b) Stoichiometry

A second consequence of life in aquatic environments lies in the chemical composition of autotrophs. Terrestrial plants have prominent structural and transport (xylem and phloem) tissues that consist largely of cellulose and lignin and are, therefore, carbon-rich (Polis & Strong 1996). Unicellular aquatic producers, macrophytes and macro-algae contain much more photosynthetic tissue that is rich in N and P (Cebrian 1999 Sterner & Elser 2002 Cebrian & Lartigue 2004). Since heterotrophs in all systems have high demands for N and P, terrestrial grazers face a greater nutritional imbalance than those in water (Elser et al. 2000). Low food quality may explain why herbivores consume less plant matter and decomposers degrade less detritus on land than in water. Producer nutrient content (percentage N and P) and the rate of herbivory are positively correlated both within and among systems, as are detritus quality and the rate of decomposition (Cebrian & Lartigue 2004). Thus, autotroph nutritional quality stands out as a consistent indicator of the importance of first-order consumers (herbivores and detritivores) as pathways for carbon flow relative to refractory detrital accumulation. These patterns suggest that differences between aquatic and terrestrial systems are driven greatly by characteristics of the primary producer community, the relative similarity of its elemental composition to that of the consumers, and the quality of detritus that it produces.

4. Emergent properties: food-web topology and complexity

(a) Food-web topology

The characterization of food webs as discrete trophic levels originally introduced by Elton (1927), Lindeman (1942) and Hairston et al. (1960) has been in equal parts influential and criticized in ecology (Murdoch 1966 Ehrlich & Birch 1967 Cousins 1987 Burns 1989 Polis 1991 Strong 1992 Polis & Strong 1996 Chase 2000 Polis et al. 2000). Strong (1992) proposed that the depiction of food webs with small numbers of aggregated feeding guilds (e.g. trophic levels) by Hairston et al. (1960), applies only to simple aquatic ecosystems in lakes. He argued that terrestrial food webs resemble a ‘trophic tangle’ which prevents community-wide trophic effects on primary producers (trophic cascades). Differences in food-web configuration or trophic complexity between ecosystems are intriguing possibilities that are surprisingly difficult to subject to empirical evaluation.

One criticism of the concept of trophic levels and simplified food-web diagrams is that omnivory blurs the distinction between trophic levels, affects the vertical flow of energy and materials, and dampens top-down control (Polis 1991). Gruner (2004) showed that effects of bird predators in tropical forests were dampened by omnivory and did not cascade to tree biomass. Stibor et al. (2004) suggested that greater omnivory leads to weaker trophic cascades in marine plankton than freshwater, as meta-analysis has shown (Shurin et al. 2002). However, community-wide cascades have been observed in other speciose systems with abundant omnivores. Terborgh et al. (2001) found that mammalian carnivore exclusion on small islands increased herbivore density and plant damage in tropical forests with many omnivores. Frank et al. (2005) showed cascading effects of over-fishing of cod in the Scotian Shelf through four trophic levels despite rampant omnivory at every stage. Omnivory clearly influences the expression of trophic cascades and bottom-up control in many cases. However, analysis of food-web data provide no indication that its prevalence varies systematically between aquatic or terrestrial ecosystems (Thompson et al. submitted).

One way of assessing the community-wide importance of omnivory is to examine the distribution of trophic position in food webs. Thompson et al. (submitted) used 60 published webs from marine pelagic, stream, lake and terrestrial ecosystems to test whether discrete trophic levels were apparent in topological food webs (maps of patterns of feeding links among species) or if trophic position varied continuously with no tendency to aggregate around particular values. They found that discrete trophic levels occurred among plants and herbivores while omnivory was more common among higher trophic positions, leading to a more continuous distribution of trophic positions among predators. Trophic positions tended to occur near integer values (trophic levels) more often in real data than in randomizations of the food webs, indicating that real webs are non-randomly structured. The degree of structure or discreteness varied among ecosystems, but was not consistently greater in water than on land. Omnivory was most common in marine pelagic systems, least common in streams, and intermediate in lakes and terrestrial systems. However, topological webs that contain no information on abundance or interaction strength may overemphasize the importance of rare interactions for the structure or dynamics of food webs. A recent analysis of several well-resolved energetic webs argued for the utility of trophic levels, and suggested that omnivory is functionally less important than topological webs might suggest (Williams & Martinez 2004). The available data on topological food webs provide no indication that terrestrial food webs are more structurally complex, or that omnivory is more prevalent on land.

(b) Food-web diversity

Related to food-web topology is the question of whether aquatic and terrestrial food webs differ in diversity within trophic levels. There is remarkably little evidence for such a difference, mainly due to difficulties in reliably estimating species richness and trophic links in the unicellular and small metazoan parts of aquatic (Schmid-Araya et al. 2002) and terrestrial invertebrate and soil food webs (Mikola & Setälä 1998). These uncertainties inhibit a direct comparison of species richness across ecosystems. However, indirect evidence suggests that terrestrial food webs contain more species. First, the most speciose plant (angiosperms) and animal (insects) phyla are primarily terrestrial. Second, terrestrial systems show steeper species-area curves than aquatic ones (Cyr et al. 1997 Drakare et al. in press) and terrestrial latitudinal gradients on local scales are steeper than their aquatic counterparts (Hillebrand 2004), both indicating higher species turnover through space in terrestrial systems. Finally, higher terrestrial diversity may reflect a greater degree of trophic specialization. If terrestrial environments are in fact more diverse, this could have important implications for the transmission of top-down and bottom-up effects. Recent studies highlight the important role of plant or herbivore diversity for the strength of trophic interactions in aquatic (Leibold et al. 1997 Duffy et al. 2003 Hillebrand & Cardinale 2004 Bruno & O'Connor 2005 Gamfeldt et al. 2005 Steiner et al. 2005) and terrestrial food webs (Mikola & Setälä 1998 Finke & Denno 2004).

(c) Specialization, defences and edibility

Specialization may impede the vertical flow of energy if consumers feed on only a limited subset of species or tissues within individuals. Many aquatic consumers (e.g. filter-feeding mollusks, planktivorous and piscivorous fish) discriminate mainly on the basis of prey size and are therefore trophic generalists. Although there are examples of generalist terrestrial consumers (e.g. ungulates), many terrestrial metazoans feed on a restricted set of potential resources in a given ecosystem. For example, lepidopteran larvae often specialize on a single plant family (Novotný & Basset 2005), and many hymenopteran parasitoids are specific to a single host species (Godfray 1994). It is therefore possible that aquatic food webs contain more generalists, and that terrestrial webs are more specialized. A second possibility is that terrestrial plants are better defended than aquatic autotrophs (Strong 1992). Variable edibility and defensive properties of prey species have the effect (similar to specialization) of dampening the strength of trophic interactions at the community level. Unicellular algae may have limited structural or chemical defences against herbivores compared to terrestrial plants that can elaborate long-lived tissues and accumulate secondary compounds over longer periods. Aquatic macrophytes have abundant chemical defences (Toth et al. 2005) but limited structural defences. In comparison, terrestrial plants have both abundant chemical and structural defence strategies (Koricheva et al. 2004). Coley et al. (1985) suggested that allocation to defensive compounds and structures is favoured when biomass turnover is low, i.e. when lost biomass is costly to replace. If this argument is correct, then aquatic autotrophs, which show high biomass turnover (figure 1), should have limited defensive ability compared to terrestrial plants. However, this possibility remains to be demonstrated.

(d) Habitat coupling and subsidies

Lindeman's (1942) second hypothesis for emergent structural differences between ecosystems suggests that aquatic systems may receive more allocthonous resource subsidies (both organic and inorganic) than terrestrial because they lie low in the landscape. Although the rates of net primary production are similar in the two systems, detritus and nutrients arriving in downstream habitats represent a second source of energy for higher order consumers in addition to local primary production. Pelagic habitats in lakes are linked to littoral and benthic food webs through predation and nutrient relocation by mobile predators (Schindler & Scheuerell 2002), and to terrestrial habitat by detrital input from plants (Pace et al. 2004). Some terrestrial systems also receive resource inputs such as marine wrack and seabird guano deposited to littoral and island systems (Polis et al. 1997 Sánchez-Piñero & Polis 2000), and emerging aquatic insects to insectivorous birds in riparian systems (Nakano & Murakami 2001). Externally derived detritus may support higher levels of secondary production and contribute to steeper biomass pyramids in aquatic ecosystems (Del Giorgio et al. 1999 Pace et al. 2004) and to stronger top-down control of autotrophs (Vander Zanden et al. 2005). If such resource subsidies are more important in water (as Lindeman's ‘concavity’ argument suggests), then they may contribute to the tendency for greater secondary production and consumption in water. Decomposers accumulate much less biomass in water than on land (Cebrian 2004 figure 1), suggesting that aquatic detritivores may support more predators in the classical food web and are more efficient at recycling detritus.

5. Conclusions

Syntheses of data across ecosystems indicate that aquatic and terrestrial food webs show unambiguous differences in their structure and function. Aquatic producers support more consumption and are regulated by top-down forces to a greater degree. Two categories of explanation for these patterns have been proposed. The first is that autotrophs in water and on land differ in size, allocation to different tissues, growth rate, chemical composition and nutritional quality. Evidence for these contrasts are compelling, and have profound implications for food-web structure which are just recently beginning to be explored. The second class of explanations is that systems differ in patterns of feeding links, their degree of trophic complexity, omnivory, defences and specialization. This is an intriguing suggestion, but one that has proven remarkably difficult to test. We argue that aquatic–terrestrial differences in the strength of top-down and bottom-up forces reflect variation in the selective constraints imposed on the producers. Differences due to food-web architecture and complexity are intriguing possibilities that remain to be tested.


Hands-on Activity Bubbling Plants Experiment to Quantify Photosynthesis

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Summary

Bubbles can be produced by many things, even plants.

Engineering Connection

Students perform data analysis and reverse engineering to understand how photosynthesis works. Both are important aspects of being an engineer.

Learning Objectives

After this activity, students should be able to:

  • Explain that photosynthesis is a process that plants use to convert light energy into glucose, a source of stored chemical energy for the plant.
  • Describe photosynthesis as a set of chemical reactions in which the plant uses carbon dioxide and water to form glucose and oxygen.
  • Describe a simple experiment that provides indirect evidence that photosynthesis is occurring.
  • Describe the effects of varying light intensity on the amount of photosynthesis that occurs.

Educational Standards

Each TeachEngineering lesson or activity is correlated to one or more K-12 science, technology, engineering or math (STEM) educational standards.

All 100,000+ K-12 STEM standards covered in TeachEngineering are collected, maintained and packaged by the Achievement Standards Network (ASN), a project of D2L (www.achievementstandards.org).

In the ASN, standards are hierarchically structured: first by source e.g., by state within source by type e.g., science or mathematics within type by subtype, then by grade, etc.

NGSS: Next Generation Science Standards - Science

5-LS1-1. Support an argument that plants get the materials they need for growth chiefly from air and water. (Grade 5)

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MS-LS1-6. Construct a scientific explanation based on evidence for the role of photosynthesis in the cycling of matter and flow of energy into and out of organisms. (Grades 6 - 8)

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Science knowledge is based upon logical connections between evidence and explanations.

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The chemical reaction by which plants produce complex food molecules (sugars) requires an energy input (i.e., from sunlight) to occur. In this reaction, carbon dioxide and water combine to form carbon-based organic molecules and release oxygen.

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Common Core State Standards - Math

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International Technology and Engineering Educators Association - Technology
  • The engineering design process involves defining a problem, generating ideas, selecting a solution, testing the solution(s), making the item, evaluating it, and presenting the results. (Grades 3 - 5) More Details

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State Standards
North Carolina - Math

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North Carolina - Science
  • Explain the significance of the processes of photosynthesis, respiration, and transpiration to the survival of green plants and other organisms. (Grade 6) More Details

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Materials List

  • 5 liters (about 1¼ gallons) of aged tap water (tap water in an open container that has been allowed to sit for 36-48 hours to eliminate the chlorine used in municipal water supplies)
  • 15-20 total Elodea plants these are hardy freshwater aquarium plants sold in bunches at pet stores and suppliers such as Carolina Biological Supply Company (www.carolina.com)
  • string, yarn or twist ties for tying Elodea plants into bunches
  • small rocks or similar objects to serve as weights to hold the Elodea plants underwater
  • 500-ml beakers, 1 per team
  • baking soda, a few tablespoons (sodium bicarbonate)
  • timers or watches with second hands, 1 per team
  • small adjustable desk lamps that can be set up so that their light bulbs are a few inches above the beakers and shine vertically down onto them flashlights with strong beams that are mounted on ring stands also work 1 light source per team

More Curriculum Like This

Through a teacher-led discussion, students realize that the food energy plants obtain comes from sunlight via the plant process of photosynthesis. By counting the number of bubbles that rise to the surface in a five-minute period, students can compare the photosynthetic activity of Elodea in the pre.

Students learn about photosynthesis and cellular respiration at the atomic level and study the basic principles of electromicrobiology—a new field of research that may enable engineers to harness energy at the molecular level.

Pre-Req Knowledge

An understanding of photosynthesis, as presented in the associated lesson, Do Plants Eat?

Introduction/Motivation

(Get the class' attention and ask them to do as you say.) With one hand, pinch your nose closed. Raise your other hand high in the air. Now take a deep breath and hold it for as long as you can. When you cannot hold your breath any longer, lower your raised hand and unpinch your nose. (Once all hands are down and no one is left holding their breath, move on.) Why did you need to start breathing again? (From their elementary school studies, expect students to be able to tell you that their bodies need air in order to survive.)

What, exactly, is in air? (Students may not know that air contains more than oxygen.) Most of the air we breathe—the atmosphere—consists of nitrogen gas (about 78%). Oxygen is the next largest component (about 21%) and a tiny part (1%) is made up of argon (an inert gas), water vapor and carbon dioxide.

So, specifically what component(s) of air do our bodies need? (Expect them to be able to answer that it is oxygen.) And what do our bodies do with oxygen? That's right, oygen from the air is picked up in the lungs by the blood and carried to all parts of the body, where it is used by muscles and the brain and all the other organs and tissues of the body. We cannot live without it.

From where did the oxygen in the atmosphere come? (They may know or be able to reason that it is the result of all the plants that have lived on the Earth and have been doing photosynthesis for many millions of years.) Today, you will work in teams to conduct an experiment to see if the amount of light plants receive can affect this production of oxygen.

Procedure

  1. In a class discussion format, students establish a hypothesis to be tested by the class in the experiment.
  2. Working in teams, students set up and conduct the experiment. Each team conducts two trials: one with the plants lit only by the ambient light available in the classroom when some or all of the room lights are turned off, and one with the plants receiving bright light from the desk lamps. The data collected are the number of bubbles of oxygen that are given off by the plants in a five-minute period, first at low-light levels, and then at high-light levels.
  3. Then the groups come together to pool their data from each of the two trials. From these data, students individually determine the mean, median and modes for the numbers of bubbles produced during the two different light conditions.
  4. Then students individually graph the data, using bar graphs that show the mean numbers of bubbles and the ranges for each test condition.

Part 1: Generating a Hypothesis

Explain to the class that before researchers start experiments, they first create a prediction about the expected outcome of the experiment. This prediction is known as a hypothesis. A hypothesis is not simply a guess, however. Instead, it is a prediction based on prior knowledge of or experience with the subject. For example, if a gardener wanted to find out if it was really necessary to fertilize zucchini plants, they might grow 12 zucchini plants, but fertilize only half of them. In this case, the hypothesis being tested might be: Fertilized zucchini plants produce more zucchinis than unfertilized zucchini plants. The data collected to support or refute the hypothesis would be the total number of zucchinis produced by the fertilized plants, compared to the total number produced by the unfertilized plants.

Point out that in the zucchini experiment, the gardener collected data that involved numbers. In science, this is usually the case, because numbers can easily be compared and are cumulative for many things that actually happen, as opposed to things that the experimenter thought might happen.

Then, explain briefly how the photosynthesis experiment will be set up and ask the class to determine a hypothesis to be tested. It shouldn't take them long to come up with a statement such as: The plants that receive more light produce more bubbles than the plants that receive less light.

Part 2: Setting up the Experiment

Perform the following steps with some or all of the classroom lights turned off. Ideally, the room should not be brightly lit, nor should it be dark adequate light should be present for students to easily see.

  1. Each team fills a beaker with about 500 ml of aged water for the Elodea. To this water, add a scant one-quarter teaspoon of sodium bicarbonate (baking soda) to provide a source of carbon dioxide for the plants, since they cannot get it from the atmosphere like terrestrial plants do. Stir the water until the sodium bicarbonate is dissolved and the water looks clear.
  2. Each team obtains enough sections of Elodea plants so that it has about 18-24 inches of total plant length. Arrange them so that all of the plants are at least 1½" under the water in the beaker. Use string or twist ties to hold them together, and then add a small rock to keep the plants from floating to the surface. Point out that the more area exposed to the light above the plant, the more photosynthesis can occur within the leaves. If students form clumps of Elodea, many of leaves will be shaded by those above, and thus may not be able to perform as much photosynthesis. It is best to form the plants into loops that cover the entire bottom of a beaker, instead of a single clump in the middle of the beaker.

Part 3: Running the Experiment

  1. As soon as the plants are arranged in the beakers, have the team start timing for five minutes. Direct two team members to have their eyes glued to the beaker for those five minutes, watching for bubbles to rise to the water surface. Announce to the third team member the sighting of any bubbles that rise, so s/he can keep count (using tally marks is helpful) and monitor the time, indicating when the five minutes are up. The bubbles are fairly large, about 2 mm in diameter, and so are easily seen when they rise to the surface.
  2. When all teams have counted bubbles for five minutes (it is quite possible that some teams see no bubbles at all), turn on the room lights and have students position the desk lamps directly above the beakers with the light bulbs only be a few inches above the beakers. Once the lights are in place, have the teams again begin timing and counting/recording bubbles for five minutes.

Part 4: Pooling and Analyzing the Data

  1. Make a large chart on the classroom board in which teams can fill in the number of bubbles they counted during each of the two light conditions.
  2. Once the chart is filled in, have students work individually to determine the mean, median, mode and range of each of the two data sets. Allow enough time so that all students arrive at the same answers.
  3. Provide students with grid paper and direct them to make vertical bar graphs that compare the mean number of bubbles in the two light conditions. Be sure that students include titles, axes labels and legends if different colors are used for the two bars. Then show them how they can indicate the ranges of the data by adding a vertical line segment to the center top of each bar, with the lower end of the line segment situated at the lowest number of bubbles observed by a team, and the upper end of the line segment at the highest number of bubbles observed.

Part 5: Interpreting the Data

  1. As a class, examine all the data and graphs and revisit the hypothesis. What do these numbers tell us about the amount of photosynthesis that occurred in each of the two light conditions. In other words, was the hypothesis the class tested supported or not?
  2. Continue with a class discussion to analyse the data. How do you know that the bubbles you saw rise to the surface were bubbles of oxygen? Students may answer that they know photosynthesis produces oxygen, so the bubbles must have been oxygen. However, without a way to determine the chemical composition of the bubbles, it is only an assumption that the bubbles contain oxygen. They might just as well have been bubbles of nitrogen or carbon dioxide, or some other gas from some other process that was occurring in the plants instead of photosynthesis. Nevertheless, since the plants were exposed to light, the bubbles were most likely made of oxygen. Point out that it is important for researchers to make sure they recognize the difference between what they know about an experiment and what they assume about it.

Vocabulary/Definitions

mean: The sum of all the values in a set of data, divided by the number of values in the data set also known as the average. For example, in a set of five temperature measurements consisting of 22 ºC, 25 ºC, 18 ºC, 22 ºC and 19 ºC, the mean temperature is 106 ºC divided by 5, or 21.2 ºC.

median: Tthe middle value in a set of data, obtained by organizing the data values in an ordered list from smallest to largest, and then finding the value that is at the half-way point in the list. For example, in a set of five temperature measurements consisting of 22º C, 25º C, 18º C, 22 º C, and 19º C, the ordered list of temperatures would be 18º C, 19º C, 22º C, 22º C, and 25º C. The middle value is the third value, 22º C. If the data set consists of an even number of values, the median is determined by averaging the two middle values. For example, in a set of six temperature measurements consisting of 20 ºC, 22 ºC, 25 ºC, 18 ºC, 24 ºC and 19 ºC, the middle values are 20 ºC and 22 ºC. Thus, the median value is the average of 20 ºC and 22 ºC, which is 21 ºC.

mode : The value in a set of data that occurs most frequently. For example, in a set of five temperature measurements consisting of 22 ºC, 25 ºC, 18 ºC, 22 ºC and 19 ºC, the measurement of 22 ºC occurs most frequently, so it is the mode. It is possible to have two or more modes in a set of data, if two or more values occur with equal frequency.

Assessment

Questions: Evaluate students' comprehension by asking them questions such as:

  • What "things" are needed in order for photosynthesis to occur?
  • What are the products of photosynthesis?
  • Where in the plant does photosynthesis occur?
  • Why do plants need water in order to survive?

Graph Analylsis: Provide a graph of data from an experiment similar to the one students just performed, and ask them to draw conclusions from it. For example, the data could represent the heights of corn plants, half of which were grown in the shade of a forest and half of which were grown in an open field.

Investigating Questions

  • What do you think would happen if you left some plants in a completely dark closet for two or three weeks? Why do you think that?
  • Why is it important for crop plants to receive enough rainfall?
  • The Earth's atmosphere did not always contain as much oxygen as it does now. In fact, at one time it probably contained no oxygen at all. How do you think the oxygen in the Earth's atmosphere got there? Why do you think that?

Activity Extensions

The light that comes from the sun consists of light waves of many different wavelengths. In the visible spectrum of light, these range from red with the longest wavelength, to violet with the shortest wavelength. Chlorophyll does not respond equally to all wavelengths, or colors of light. Have students use the same experimental setup to determine what color or colors of light result in the most photosynthetic activity. The only modification they need to make is to loosely cover the beaker with colored plastic wrap or cellophane during the five minutes of bubble counting. Since blue wavelengths are the best for most plants, be sure that this is one of the colors available. If possible, have red and one other color available as well.

Copyright

Contributors

Supporting Program

Acknowledgements

This content was developed by the MUSIC (Math Understanding through Science Integrated with Curriculum) Program in the Pratt School of Engineering at Duke University under National Science Foundation GK-12 grant no. DGE 0338262. However, these contents do not necessarily represent the policies of the NSF, and you should not assume endorsement by the federal government.


Why study photosynthesis?

Because our quality of life, and indeed our very existence, depends on photosynthesis, it is essential that we understand it. Through understanding, we can avoid adversely affecting the process and precipitating environmental or ecological disasters. Through understanding, we can also learn to control photosynthesis, and thus enhance production of food, fiber and energy. Understanding the natural process, which has been developed by plants over several billion years, will also allow us to use the basic chemistry and physics of photosynthesis for other purposes, such as solar energy conversion, the design of electronic circuits, and the development of medicines and drugs. Some examples follow.

Photosynthesis and agriculture. Although photosynthesis has interested mankind for eons, rapid progress in understanding the process has come in the last few years. One of the things we have learned is that overall, photosynthesis is relatively inefficient. For example, based on the amount of carbon fixed by a field of corn during a typical growing season, only about 1 - 2% of the solar energy falling on the field is recovered as new photosynthetic products. The efficiency of uncultivated plant life is only about 0.2%. In sugar cane, which is one of the most efficient plants, about 8% of the light absorbed by the plant is preserved as chemical energy. Many plants, especially those that originate in the temperate zones such as most of the United States, undergo a process called photorespiration. This is a kind of "short circuit" of photosynthesis that wastes much of the plants' photosynthetic energy. The phenomenon of photorespiration including its function, if any, is only one of many riddles facing the photosynthesis researcher.

If we can fully understand processes like photorespiration, we will have the ability to alter them. Thus, more efficient plants can be designed. Although new varieties of plants have been developed for centuries through selective breeding, the techniques of modern molecular biology have speeded up the process tremendously. Photosynthesis research can show us how to produce new crop strains that will make much better use of the sunlight they absorb. Research along these lines is critical, as recent studies show that agricultural production is leveling off at a time when demand for food and other agricultural products is increasing rapidly.

Because plants depend upon photosynthesis for their survival, interfering with photosynthesis can kill the plant. This is the basis of several important herbicides, which act by preventing certain important steps of photosynthesis. Understanding the details of photosynthesis can lead to the design of new, extremely selective herbicides and plant growth regulators that have the potential of being environmentally safe (especially to animal life, which does not carry out photosynthesis). Indeed, it is possible to develop new crop plants that are immune to specific herbicides, and to thus achieve weed control specific to one crop species.

Photosynthesis and energy production. As described above, most of our current energy needs are met by photosynthesis, ancient or modern. Increasing the efficiency of natural photosynthesis can also increase production of ethanol and other fuels derived from agriculture. However, knowledge gained from photosynthesis research can also be used to enhance energy production in a much more direct way. Although the overall photosynthesis process is relatively wasteful, the early steps in the conversion of sunlight to chemical energy are quite efficient. Why not learn to understand the basic chemistry and physics of photosynthesis, and use these same principles to build man-made solar energy harvesting devices? This has been a dream of chemists for years, but is now close to becoming a reality. In the laboratory, scientists can now synthesize artificial photosynthetic reaction centers which rival the natural ones in terms of the amount of sunlight stored as chemical or electrical energy. More research will lead to the development of new, efficient solar energy harvesting technologies based on the natural process.

The role of photosynthesis in control of the environment. How does photosynthesis in temperate and tropical forests and in the sea affect the quantity of greenhouse gases in the atmosphere? This is an important and controversial issue today. As mentioned above, photosynthesis by plants removes carbon dioxide from the atmosphere and replaces it with oxygen. Thus, it would tend to ameliorate the effects of carbon dioxide released by the burning of fossil fuels. However, the question is complicated by the fact that plants themselves react to the amount of carbon dioxide in the atmosphere. Some plants, appear to grow more rapidly in an atmosphere rich in carbon dioxide, but this may not be true of all species. Understanding the effect of greenhouse gases requires a much better knowledge of the interaction of the plant kingdom with carbon dioxide than we have today. Burning plants and plant products such as petroleum releases carbon dioxide and other byproducts such as hydrocarbons and nitrogen oxides. However, the pollution caused by such materials is not a necessary product of solar energy utilization. The artificial photosynthetic reaction centers discussed above produce energy without releasing any byproducts other than heat. They hold the promise of producing clean energy in the form of electricity or hydrogen fuel without pollution. Implementation of such solar energy harvesting devices would prevent pollution at the source, which is certainly the most efficient approach to control.

Photosynthesis and electronics. At first glance, photosynthesis would seem to have no association with the design of computers and other electronic devices. However, there is potentially a very strong connection. A goal of modern electronics research is to make transistors and other circuit components as small as possible. Small devices and short connections between them make computers faster and more compact. The smallest possible unit of a material is a molecule (made up of atoms of various types). Thus, the smallest conceivable transistor is a single molecule (or atom). Many researchers today are investigating the intriguing possibility of making electronic components from single molecules or small groups of molecules. Another very active area of research is computers that use light, rather than electrons, as the medium for carrying information. In principle, light-based computers have several advantages over traditional designs, and indeed many of our telephone transmission and switching networks already operate through fiber optics. What does this have to do with photosynthesis? It turns out that photosynthetic reaction centers are natural photochemical switches of molecular dimensions. Learning how plants absorb light, control the movement of the resulting energy to reaction centers, and convert the light energy to electrical, and finally chemical energy can help us understand how to make molecular-scale computers. In fact, several molecular electronic logic elements based on artificial photosynthetic reaction centers have already been reported in the scientific literature.

Photosynthesis and medicine. Light has a very high energy content, and when it is absorbed by a substance this energy is converted to other forms. When the energy ends up in the wrong place, it can cause serious damage to living organisms. Aging of the skin and skin cancer are only two of many deleterious effects of light on humans and animals. Because plants and other photosynthetic species have been dealing with light for eons, they have had to develop photoprotective mechanisms to limit light damage. Learning about the causes of light- induced tissue damage and the details of the natural photoprotective mechanisms can help us can find ways to adapt these processes for the benefit of humanity in areas far removed from photosynthesis itself. For example, the mechanism by which sunlight absorbed by photosynthetic chlorophyll causes tissue damage in plants has been harnessed for medical purposes. Substances related to chlorophyll localize naturally in cancerous tumor tissue. Illumination of the tumors with light then leads to photochemical damage which can kill the tumor while leaving surrounding tissue unharmed. Another medical application involves using similar chlorophyll relatives to localize in tumor tissue, and thus act as dyes which clearly delineate the boundary between cancerous and healthy tissue. This diagnostic aid does not cause photochemical damage to normal tissue because the principles of photosynthesis have been used to endow it with protective agents that harmlessly convert the absorbed light to heat.


IV. Conclusion

Improving the rapidity of stomatal responses could greatly improve A and Wi and aid plant productivity. Although many studies have investigated the rapidity of stomatal responses and attributed differences to anatomical features, a full mechanistic understanding is still lacking. Guard cell membrane transport and channel activity are key to balancing ionic fluxes for stomatal movement however, the manipulation of a single channel is unlikely to increase the rapidity of gs, as coordination of multiple channels is required, as well as coordination of fluxes at both the plasma membrane and tonoplast. Further studies are therefore needed to generate extensive data sets on stomatal kinetics from existing mutants, as well as the identification of new targets for guard cell manipulation. Restricting studies to a single genus will minimize genetic effects, reducing the complexity of responses, and may be the most effective procedure for screening and selecting for faster stomata (Drake et al., 2013 ).