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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 7, Iss. 1 — Jan. 4, 2012
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Photo-physiological variability in phytoplankton chlorophyll fluorescence and assessment of chlorophyll concentration

Alexander Chekalyuk and Mark Hafez  »View Author Affiliations


Optics Express, Vol. 19, Issue 23, pp. 22643-22658 (2011)
http://dx.doi.org/10.1364/OE.19.022643


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Abstract

Photo-physiological variability of in vivo chlorophyll fluorescence (CF) per unit of chlorophyll concentration (CC) is analyzed using a biophysical model to improve the accuracy of CC assessments. Field measurements of CF and photosystem II (PSII) photochemical yield (PY) with the Advanced Laser Fluorometer (ALF) in the Delaware and Chesapeake Bays are analyzed vs. high-performance liquid chromatography (HPLC) CC retrievals. It is shown that isolation from ambient light, PSII saturating excitation, optimized phytoplankton exposure to excitation, and phytoplankton dark adaptation may provide accurate in vivo CC fluorescence measurements (R2 = 0.90–0.95 vs. HPLC retrievals). For in situ or flow-through measurements that do not allow for dark adaptation, concurrent PY measurements can be used to adjust for CF non-photochemical quenching (NPQ) and improve the accuracy of CC fluorescence assessments. Field evaluation has shown the NPQ-invariance of CF/PY and CF(PY−1-1) parameters and their high correlation with HPLC CC retrievals (R2 = 0.74–0.96), while the NPQ-affected CF measurements correlated poorly with CC (R2 = −0.22).

© 2011 OSA

1. Introduction

Chlorophyll a (Chl) is a photosynthetic pigment that plays a key role in photosynthesis [1

1. G. C. Papageorgiou and Govindjee (Eds.), Chlorophyll a Fluorescence: A Signature of Photosynthetsis, Advances in Photosynthesis and Respiration (Springer, Dordrecht, 2004).

]. All phytoplankton species, regardless of their specific group and taxonomic features, contain Chl in their photosynthetic apparatus. Chl concentration (CC) is broadly used as a useful index of phytoplankton biomass in laboratory research, oceanographic studies, and environmental surveys. In vivo measurements of Chl fluorescence (CF) are highly sensitive, fast and easy to conduct in a small sample volume at natural concentrations of the photosynthesizing microorganisms, including direct in situ measurements [2

2. T. J. Cowles, J. N. Moum, R. A. Desiderio, and S. M. Angel, “In situ monitoring of ocean chlorophyll via laser-induced fluorescence backscattering through an optical fiber,” Appl. Opt. 28(3), 595–600 (1989). [CrossRef] [PubMed]

6

6. M. J. Perry, B. S. Sackmann, C. C. Eriksen, and C. M. Lee, “Seaglider observations of blooms and subsurface chlorophyll maxima off the Washington coast,” Limnol. Oceanogr. 53(5_part_2), 2169–2179 (2008). [CrossRef]

] and LIDAR remote sensing [7

7. S. Babichenko, S. Kaitala, A. Leeben, L. Poryvkina, and J. Seppala, “Phytoplankton pigments and dissolved organic matter distribution in the Gulf of Riga,” J. Mar. Syst. 23(1-3), 69–82 (1999). [CrossRef]

10

10. F. E. Hoge and R. N. Swift, “Airborne simultaneous spectroscopic detection of laser-induced water Raman backscatter and fluorescence from chlorophyll a and other naturally occurring pigments,” Appl. Opt. 20(18), 3197–3205 (1981). [CrossRef] [PubMed]

]. CF measurements can provide information about CC, phytoplankton community structure [11

11. M. Beutler, K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U. P. Hansen, and H. Dau, “A fluorometric method for the differentiation of algal populations in vivo and in situ,” Photosynth. Res. 72(1), 39–53 (2002). [CrossRef] [PubMed]

16

16. T. L. Richardson, E. Lawrenz, J. L. Pinckney, R. C. Guajardo, E. A. Walker, H. W. Paerl, and H. L. MacIntyre, “Spectral fluorometric characterization of phytoplankton community composition using the Algae Online Analyser,” Water Res. 44(8), 2461–2472 (2010). [CrossRef] [PubMed]

], physiological status, photosynthetic efficiency and productivity [17

17. T. S. Bibby, M. Y. Gorbunov, K. W. Wyman, and P. G. Falkowski, “Photosynthetic community responses to upwelling in mesoscale eddies in the subtropical North Atlantic and Pacific Oceans,” Deep Sea Res. Part II Top. Stud. Oceanogr. 55(10-13), 1310–1320 (2008). [CrossRef]

28

28. M. P. Raateoja, “Fast repetition rate fluorometry (FRRF) measuring phytoplankton productivity: a case study at the entrance to the Gulf of Finland, Baltic Sea,” Boreal Environ. Res. 9, 263–276 (2004).

].

While CF is broadly used as a proxy of CC and phytoplankton biomass [19

19. P. Falkowski and D. A. Kiefer, “Chlorophyll-a fluorescence in phytoplankton - relationship to photosynthesis and biomass,” J. Plankton Res. 7(5), 715–731 (1985). [CrossRef]

, 29

29. Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007). [CrossRef]

32

32. C. D. Wirick, “Exchange of phytoplankton across the continental shelf-slope boundary of the Middle Atlantic Bight during spring-1988,” Deep Sea Res. Part II Top. Stud. Oceanogr. 41(2-3), 391–410 (1994). [CrossRef]

], the accuracy of quantitative CC assessments is often compromised by high, up to an order of magnitude [33

33. A. E. Alpine and J. E. Cloern, “Differences in in vivo fluorescence yield between three phytoplankton size classes,” J. Plankton Res. 7(3), 381–390 (1985). [CrossRef]

36

36. M. E. Loftus and H. H. Seliger, “Some limitations of the in vivo fluorescence technique,” Chesap. Sci. 16(2), 79–92 (1975). [CrossRef]

], variability in CF/CC ratio. The relationship between CF and CC depends on phytoplankton taxonomy, cell size, organization of photosynthetic apparatus and physiological status. Even frequent instrument calibrations cannot guarantee reliable and accurate CC fluorescence retrievals. CF photo-physiological regulation by light regime and nutrient availability is known to be one of the major factors affecting CF/CC variability (e.g [19

19. P. Falkowski and D. A. Kiefer, “Chlorophyll-a fluorescence in phytoplankton - relationship to photosynthesis and biomass,” J. Plankton Res. 7(5), 715–731 (1985). [CrossRef]

, 35

35. J. J. Cullen and M. R. Lewis, “Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensing,” J. Geophys. Res. - Oceans 100(C7), 13255–13266 (1995). [CrossRef]

]. The appropriate choice of a measurement protocol may result in the CF/CC variability reduction. Some fluorometers [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

, 17

17. T. S. Bibby, M. Y. Gorbunov, K. W. Wyman, and P. G. Falkowski, “Photosynthetic community responses to upwelling in mesoscale eddies in the subtropical North Atlantic and Pacific Oceans,” Deep Sea Res. Part II Top. Stud. Oceanogr. 55(10-13), 1310–1320 (2008). [CrossRef]

, 21

21. T. Fujiki, T. Hosaka, H. Kimoto, T. Ishimaru, and T. Saino, “In situ observation of phytoplankton productivity by an underwater profiling buoy system: use of fast repetition rate fluorometry,” Mar. Ecol. Prog. Ser. 353, 81–88 (2008). [CrossRef]

, 22

22. M. Y. Gorbunov, P. G. Falkowski, and Z. S. Kolber, “Measurement of photosynthetic parameters in benthic organisms in situ using a SCUBA-based fast repetition rate fluorometer,” Limnol. Oceanogr. 45(1), 242–245 (2000). [CrossRef]

, 37

37. T. Jakob, U. Schreiber, V. Kirchesch, U. Langner, and C. Wilhelm, “Estimation of chlorophyll content and daily primary production of the major algal groups by means of multiwavelength-excitation PAM chlorophyll fluorometry: performance and methodological limits,” Photosynth. Res. 83(3), 343–361 (2005). [CrossRef] [PubMed]

, 38

38. Z. S. Kolber, O. Prasil, and P. G. Falkowski, “Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: defining methodology and experimental protocols,” BBA.- Bioenergetics 1367(1-3), 88–106 (1998). [CrossRef]

] provide measurements of physiological parameters that potentially can be used to adjust CF magnitudes affected by photo-physiological variability.

In this article, we use a simplified biophysical model to illustrate the problems relevant to the CF photo-physiological regulation and provide some practical recommendations that may help to improve the accuracy of CC assessment from in vivo CF measurements. The analytical results and measurement protocols are evaluated using field measurements in the Delaware and Chesapeake Bays. The abbreviations and variables used in the article are listed in Table 1.

Table 1. Abbreviations and Variables

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2. Photo-physiological regulation of chlorophyll fluorescence (model analysis)

Chl molecules are incorporated in phytoplankton cells and, therefore, are not evenly distributed in the water. Nonetheless, CC is commonly accepted for estimating the average Chl biomass per unit of water volume containing phytoplankton. Most in vivo CF originates from the Chl molecules of the light-harvesting antenna of photosystem II (PSII) in the photosynthetic apparatus of phytoplankton [39

39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

]. The relationship between CF intensity and CC can be described as
CF=K*CC=NAM1VσIΦfnPSIICC=kΦf*CC. 
(1)
Here, V is the water volume containing phytoplankton and exposed to fluorescence excitation, σ is the absorption cross-section of Chl molecules, I is the excitation intensity, Φf is the PSII CF yield (CFY), nPSII is the fraction of Chl molecules associated with PSII, NA is the Avogadro constant, and M is Chl molar mass. The conventional approach to in vivo CC fluorescence measurements is determining the parameter K=NAM1VσIΦfnPSIIvia fluorometer calibration and using it for conversion of the CF measurements into the CC units: CC=K1CF. The calibration involves the measurements of CF (with the fluorometer to be calibrated) and CC (using one of the independent analytical techniques) in phytoplankton-containing water samples, and regression analysis of CF vs. CC. HPLC [40

40. T. R. Jacobsen, “A quantitative method for the separation of chlorophyll a and b from phytoplankton pigments by HPLC,” Mar. Sci. Comm. 4, 33–47 (1978).

], spectrophotometric [41

41. C. J. Lorenzen, “Determination of chlorophyll and pheo-pigments - spectrophotometric equations,” Limnol. Oceanogr. 12(2), 343–346 (1967). [CrossRef]

], or fluorometric [42

42. O. C. J. Holm-Hansen, C. J. Lorenzen, R. W. Holmes, and J. D. H. Strickland, “Fluorometric determination of chlorophyll,” J. Cons. Perm. Int. Explor. Mer. 30, 3–15 (1965).

] methods can be used for CC measurements. A similar approach works well for measuring concentration of dissolved fluorescent organic molecules, but the accuracy of CC assessments from in vivo CF measurements is often compromised. There are various structural and physiological factors and regulatory mechanisms in phytoplankton that may affect the biological variables nPSII, σ, and Φf in Eq. (1) and, respectively, the CF/CC ratio, making applicability of even frequent field calibrations problematic. A detailed discussion on this topic is beyond the scope of this article; some relevant information can be found in [1

1. G. C. Papageorgiou and Govindjee (Eds.), Chlorophyll a Fluorescence: A Signature of Photosynthetsis, Advances in Photosynthesis and Respiration (Springer, Dordrecht, 2004).

, 19

19. P. Falkowski and D. A. Kiefer, “Chlorophyll-a fluorescence in phytoplankton - relationship to photosynthesis and biomass,” J. Plankton Res. 7(5), 715–731 (1985). [CrossRef]

, 20

20. P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Aust. J. Plant Physiol. 22(2), 341–355 (1995). [CrossRef]

, 35

35. J. J. Cullen and M. R. Lewis, “Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensing,” J. Geophys. Res. - Oceans 100(C7), 13255–13266 (1995). [CrossRef]

]. Below we use a simplified biophysical model (following [19

19. P. Falkowski and D. A. Kiefer, “Chlorophyll-a fluorescence in phytoplankton - relationship to photosynthesis and biomass,” J. Plankton Res. 7(5), 715–731 (1985). [CrossRef]

, 20

20. P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Aust. J. Plant Physiol. 22(2), 341–355 (1995). [CrossRef]

, 39

39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

, 43

43. Govindje, “63 years since Kautsky - chlorophyll-a fluorescence,” Aust. J. Plant Physiol. 22(2), 131–160 (1995). [CrossRef]

]) to analyze the most relevant aspects of the CFY photo-physiological variability as one of the major factors affecting the CF/CC ratio.

The PSII CF and thermal dissipation represent two channels of energy losses accompanying the PSII photochemical reactions. The quantum yields of photochemistry and fluorescence for dark-adapted PSII can be described, respectively, as:
Φp=fAkp/(Afkp+kf+kd)
(2)
Φf=kf/(Afkp+kf+kd).
(3)
Here, kp, kf,,and kd are, respectively, the rate constants of photochemistry in functional PSII reaction centers (RCs), fluorescence and constitutive heat dissipation. The parameter f represents the fraction of the photochemically functional PSII reaction centers (RCs) (0< f < 1); A represents the fraction of the open functional PSII RCs (0<A<1). The dependence of Φp and Φf on these photochemical parameters is described in terms of photochemical quenching (PQ). The magnitude of f mainly depends on the nutrient supply and light conditions, while A is determined by the dynamic equilibrium between photochemical closing and re-opening of PSII RCs (e.g., [25

25. R. J. Olson, A. M. Chekalyuk, and H. M. Sosik, “Phytoplankton photosynthetic characteristics from fluorescence induction assays of individual cells,” Limnol. Oceanogr. 41(6), 1253–1263 (1996). [CrossRef]

]). In particular, when A = 0 (all PSII RCs are closed under the intense, PSII saturating incident light), Φf reaches its maximal magnitude, Φm:

Φm=kf/(kf+kd).
(4)

When A = 1 (all PSII RCs are open in darkness), Φf reaches its minimal magnitude:

Φo=kf/(fkp+kf+kd).
(5)

In darkness (A = 1) the Φp maximal potential magnitude can expressed via Φo and Φm as

Φpm=fkp/(fkp+kf+kd)=(ΦmΦo)/Φm
(6)

The Φom ratio can be calculated from Eq. (6) as

Φo/Φm=1Φpm.
(7)

An exposure to excessive ambient light may result in the gradual development of non-photochemical quenching (NPQ) that enhances thermal dissipation of the absorbed light energy. There are several photo-protective NPQ mechanisms (e.g., [39

39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

]). Depending on the intensity of incident light and the NPQ mechanisms involved, NPQ may develop over time scales ranging from seconds to minutes [44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

]. Recovery from NPQ action in dark conditions may require several minutes to several hours. NPQ can be described with an additional NPQ rate constant, kN [39

39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

]. The actual maximal and minimal CFY magnitudes, and the maximal potential quantum yield of PSII photochemistry for the NPQ-affected photosystem can be expressed, respectively, as

Φ'p=fAkp/(Afkp+kf+kd+kN)
(8)
Φ'f=kf/(Afkp+kf+kd+kN)
(9)
Φ'm=kf/(kf+kd+kN)
(10)
Φ'o=kf/(fkp+kf+kd+kN)
(11)
Φ'pm=fkp/(fkp+kf+kd+kN)=(Φ'mΦ'o)/Φ'm.
(12)

From Eqs. (4), (10):
Φm/Φ'm=1+kN/(kf+kd)=1+NPQ.
(13)
From Eqs. (5), (6), (11), and (12):
Φo/Φ'o=Φpm/Φ'pm=1+kN/(fkp+kf+kd)=1+(fkp/kN+NPQ1)1
(14)
 Φf/Φ'f=Φp/Φ'p=1+kN/(Afkp+kf+kd)=1+(Afkp/kN+NPQ1)1.
(15)
Here, NPQ=kN/(kf+kd),a parameter that is often used for quantitative NPQ assessment [45

45. J. C. Kromkamp and R. M. Forster, “The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology,” Eur. J. Phycol. 38(2), 103–112 (2003). [CrossRef]

]. Using Eqs. (13)(15), the relative NPQ-induced changes in the fluorescence and photochemical yields can be estimated as

(ΦfΦ'f)/Φ'f=(ΦpΦ'p)/Φ'p=(Afkp/kN+NPQ1)1 
(16)
(ΦoΦ'o) /Φ'o=(ΦpmΦ'pm) /Φ'pm= (fkp/kN+NPQ1)1
(17)
(ΦmΦ'm)/Φ'm=NPQ.
(18)

Thus, NPQ development should cause the most pronounced decrease in Φ'm. Declines in Φ'o and Φ'pm induced by NPQ are smaller and dependent on the phytoplankton physiological status (described by f in the model).

From Eqs. (7), (14), and (15) it follows that

Φf/Φp= Φ'f /Φ'p, and
(19)
Φm(1/Φpm1)=Φ'm(1/Φ'pm1).
(20)

3. Recommendations on CF measurement protocol for improved CC assessments

Thus, the phytoplankton CFY generally depends on the PSII photochemical functionality and the actual intensity of the incident light (both determine the PQ), as well as on the phytoplankton light exposure prior to the measurements that determine the NPQ. A potential range of the CFY photo-physiological variability can be estimated using the above analysis. The maximum value of Φpm ~0.65 measured in healthy phytoplankton [5

5. Z. Kolber and P. G. Falkowski, “Use of active fluorescence to estimate phytoplankton photosynthesis in-situ,” Limnol. Oceanogr. 38(8), 1646–1665 (1993). [CrossRef]

, 20

20. P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Aust. J. Plant Physiol. 22(2), 341–355 (1995). [CrossRef]

] would result in Φm/Φo ~3 (Eq. (6)). Thus, the Φf magnitude can vary up to 3-fold, depending on the actual PQ effect (Eq. (2)). Our field data show that up to a 5-fold NPQ-induced CFY decline can be observed in the subsurface water column around noon (e.g., Fig. 3A
Fig. 3 Correlation between the HPLC measurements of Chl concentration (CC) in water samples 1–20 (Figs. 1, 2) and (A) underway Chl fluorescence measurements at the sampling locations (CFU) or (B) CF measurements in the dark-adapted water samples (CFS). Diamonds and circles represent the data from the nighttime and morning portions of the transect, respectively (marked as 1–14 and 15–20 in Figs. 1, 2). The framed and unframed regression equations are calculated for nighttime and entire data sets, respectively.
), depending on the light conditions and mixing regime. The maximum range of CFY natural variability caused by both PQ and NPQ can be estimated then as 15. This estimate is markedly close to the ~12-fold CF/CC variability observed in the field (e.g., [46

46. S. I. Heaney, “Some observations on use of in vivo fluorescence technique to determine chlorophyll-a in natural-populations and cultures of freshwater phytoplankton,” Freshw. Biol. 8(2), 115–126 (1978). [CrossRef]

]), suggesting that the CFY photo-physiological regulation may be one of the major factors affecting the overall variability in the relationship between CF and CC.

During the active CF measurements, the PQ and NPQ magnitudes may depend on both ambient and CF excitation light. CF efficiency can vary a great deal, depending on environmental conditions, measurement protocols and phytoplankton physiological status. This provides unique opportunities for fluorescence assessment of phytoplankton photo-physiological characteristics (e.g., [25

25. R. J. Olson, A. M. Chekalyuk, and H. M. Sosik, “Phytoplankton photosynthetic characteristics from fluorescence induction assays of individual cells,” Limnol. Oceanogr. 41(6), 1253–1263 (1996). [CrossRef]

, 38

38. Z. S. Kolber, O. Prasil, and P. G. Falkowski, “Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: defining methodology and experimental protocols,” BBA.- Bioenergetics 1367(1-3), 88–106 (1998). [CrossRef]

]). On the other hand, CFY variability needs to be minimized or accounted for to improve the accuracy of CC fluorescence assessments.

Phytoplankton exposure to ambient light activates a complex chain of photosynthetic reactions and photo-adaptive physiological transformations and may result in NPQ development that significantly affects the CFY magnitude [39

39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

, 44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

, 47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]. If measurement conditions permit, keeping water samples in low-light conditions for at least one hour before the measurement may restore the dark-adapted Φo level of CFY, which is independent of the prior “light history” of phytoplankton. It should be noted that after phytoplankton exposure to intense irradiance, even several hours of dark adaptation may be insufficient for complete recovery from NPQ [44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

] (for example, see Fig. 3B and Discussion).

Optical isolation of the measured sample volume eliminates the PQ component associated with the ambient light thus minimizing the overall CFY variability. If ambient light is blocked, PQ is determined by the intensity of excitation light and depends on PSII photochemical functionality (determined by f in the model). The PQ component and CFY dependence on the PSII physiology can be further minimized by using the PSII saturating fluorescence excitation that dynamically closes the PSII RCs to reach the CFY~Φm at the beginning of the fluorescence measurement. This also eliminates the need for optical isolation of the measured sample volume (PQ~0 regardless of the ambient light), which may simplify the in situ CF measurements.

The physiological origin of in vivo CF results in a complex CFY time transient after initiating the excitation known as Kautsky effect (e.g [44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

, 47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]. It includes a polyphasic rise from the initial Φo level to its maximum Φm value (Φ'o and Φ'm, respectively, for light-adapted phytoplankton) followed by a polyphasic decline to some stationary CFY magnitude. The induction rise begins with a fast, photochemical phase (< 1 ms) followed by several thermal phases to reach Φm in ~100 ms under intense PSII saturating excitation [44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

, 47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]. CFY remains almost unchanged at the maximum level for several seconds and gradually declines after that over 0.1 – 1 minute due to the development of excitation-induced NPQ.

Thus, CFY may continuously vary during the in vivo CF measurement due to the physiological mechanisms involved in the Kautsky effect, and the integral CF value is usually determined by the average CFY magnitude over the measurement time (this is discussed below regarding the ALF CF measurements). Several instrumental factors (e.g., excitation intensity and duration, measurement time, sample exposure to the excitation, etc.) may affect the average CFY value and result in a variable, instrument and protocol dependent CF/CC relationship. For example, the CF magnitude may appear to be dependent on the sample flow rate through the measurement chamber (e.g., [48

48. S. T. Sweet and N. L. Guinasso, “Effects of flow-rate on fluorescence in vivo during continuous measurements on Gulf of Mexico surface-water,” Limnol. Oceanogr. 29(2), 397–401 (1984). [CrossRef]

]).

If a PSII saturating excitation is used for minimizing the PQ component of the CFY variability, it may be beneficial to limit the sample exposure to the excitation to ~1 second. Then the CF measurement will be conducted for most of the measurement time at the maximum level of CFY, independent of PSII photochemical functionality and not affected by the excitation-induced NPQ that would develop at the longer sample exposure. The actual measurement time may be longer if the measurements are conducted in a fast enough sample flow to limit the exposure time of the measured sample volume.

To summarize, the effect of CFY photo-physiological variability on the CF measurements can be reduced by the following (referred below as a “four-step measurement protocol”):

  • 1. Isolating measurement volume from ambient light to reduce its effect on the CFY variability.
  • 2. Using PSII saturating fluorescence excitation to minimize the CFY dependence on PSII photochemical functionality.
  • 3. Optimizing sample exposure to the excitation to minimize the CFY variability (~1 second exposure may be optimal for the PSII saturating excitation).
  • 4. Providing phytoplankton dark adaptation before the measurements (if conditions permit).

It is technically difficult to provide phytoplankton dark adaptation when conducting daytime in situ or flow-through underway shipboard measurements. The CF intensity may be NPQ-affected due to phytoplankton exposure to the ambient light in the water column. The NPQ effect may depend on the unknown phytoplankton “light history” and compromise the accuracy of CC fluorescence retrievals. The above model analysis shows that the PSII photochemical yield also exhibits the NPQ down-regulation (Eqs. (14), (15)). Therefore, the concurrent PY measurements may provide a potential way to adjust the CF retrievals for the NPQ effect. Equations (19) and (20) illustrate this idea, showing that the fluorescence parameters Φf/Φp and Φm(1/Φpm −1) should remain invariant regardless of the NPQ magnitude and equal to their values in the PSII dark-adapted state. There are various measurement protocols and instruments for PY assessments [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

, 37

37. T. Jakob, U. Schreiber, V. Kirchesch, U. Langner, and C. Wilhelm, “Estimation of chlorophyll content and daily primary production of the major algal groups by means of multiwavelength-excitation PAM chlorophyll fluorometry: performance and methodological limits,” Photosynth. Res. 83(3), 343–361 (2005). [CrossRef] [PubMed]

, 38

38. Z. S. Kolber, O. Prasil, and P. G. Falkowski, “Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: defining methodology and experimental protocols,” BBA.- Bioenergetics 1367(1-3), 88–106 (1998). [CrossRef]

, 49

49. R. Röttgers, “Comparison of different variable chlorophyll a fluorescence techniques to determine photosynthetic parameters of natural phytoplankton,” Deep Sea Res. Part I Oceanogr. Res. Pap. 54(3), 437–451 (2007). [CrossRef]

], so the practical implementations of this approach needs evaluation and optimization on a case-by-case basis. Below, we demonstrate with field data that the CF NPQ-adjustment using the PY measurements may provide a significant advantage over the conventional, CF-based CC assessments when it is problematic to provide phytoplankton recovery from the NPQ (e.g., in situ and flow-through underway retrievals). On the other hand, a potential dependence of the NPQ-invariant parameters on various physiological mechanisms needs to be evaluated (see Discussion).

4. Field measurements with advanced laser fluorometer

The field measurements with the Advanced Laser Fluorometer (ALF) were used to evaluate our analytical conclusions and proposed measurement protocols for improving the accuracy of CC fluorescence assessments. ALF is a compact field instrument that provides both spectrally and temporally resolved fluorescence measurements. Its design and measurement protocols are described in detail in [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

]. The ALF conducts spectral deconvolution of the laser-stimulated emission to provide measurements of Chl, phycoerythrin, and CDOM fluorescence. The fluorescence intensities are normalized to water Raman scattering to account for variability in water optical properties. The ALF measurements of variable fluorescence are spectrally corrected for the non-CF background to improve the accuracy of retrievals.

The following features of the ALF design and measurement protocols make this instrument suitable for the field test of the above analytical conclusions. The ALF measurement cell is located in the sample compartment inside the instrument case and isolated from ambient light (condition 1 in Section 3). The spot size of the 405 nm laser excitation beam used for CF and VF measurements is appropriately adjusted to saturate PSII over ~100 μs (condition 2 in Section 3), thus providing the PY retrievals at PSII single-turnover (ST) time scale (e.g., [25

25. R. J. Olson, A. M. Chekalyuk, and H. M. Sosik, “Phytoplankton photosynthetic characteristics from fluorescence induction assays of individual cells,” Limnol. Oceanogr. 41(6), 1253–1263 (1996). [CrossRef]

, 45

45. J. C. Kromkamp and R. M. Forster, “The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology,” Eur. J. Phycol. 38(2), 103–112 (2003). [CrossRef]

]). The spectral integration time with 405 nm excitation is limited to 1 second to avoid development of the laser-stimulated NPQ that happens over longer time scales (condition 3 in Section 3). About one hour of dark adaptation is provided for discrete water samples before in vivo fluorescence measurements with the ALF instrument (condition 4 in Section 3).

The results reported in this article are essentially based on comparison of the CF and PY measurements in the dark- and light-adapted states of phytoplankton photosynthetic apparatus. The ALF CF field measurements compliant with conditions 1–4 of the above measurement protocol are compared below with the independent HPLC CC retrievals. The use of PSII saturating excitation for ALF measurements of both PY and CF suggests the NPQ-invariance of parameter CF(PY−1-1) (see Eq. (20)). The invariance of this and another fluorescence parameter, CF/PY, which can be formally derived from Eq. (19), are evaluated using the ALF field measurements and discussed below.

Some aspects of the ALF CF measurements relevant to optimizing the sample exposure time need to be briefly discussed. The internal instrument pump for discrete sample analysis operates at the flow rate of 0.1 L/min [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

]. It results in ~100 ms time of phytoplankton exposure to the PSII saturating excitation (i.e. time of residence in the laser beam). This time corresponds to the PSII multiturnover time (MT) scale, and CFY exhibits a polyphasic rise typical for the Kautsky effect [44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

, 47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]. The initial, photochemical phase is identical to the ST fluorescence induction used for the ALF PY measurements. It lasts ~100 μs, during which the PSII RCs are gradually closed and CFY reaches its maximal ST magnitude Φm(ST) [45

45. J. C. Kromkamp and R. M. Forster, “The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology,” Eur. J. Phycol. 38(2), 103–112 (2003). [CrossRef]

]. This initial phase is followed by several thermal phases of continued CFY rise to reach its maximum MT level Φm(MT) ~1.5Φm(ST) [45

45. J. C. Kromkamp and R. M. Forster, “The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology,” Eur. J. Phycol. 38(2), 103–112 (2003). [CrossRef]

] at the end of 100 ms exposure time (Fig. 1
Fig. 1 A map of shipboard ALF underway flow-through measurements in the Delaware and Chesapeake Bays, April 15–16 2008. Green dots display the sampling locations for laboratory measurements of Chl fluorescence and concentration.
in [47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]). Though the ALF spectrometer integrates the laser-stimulated emission over ~1 s, the CF magnitude yielded by the ALF measurements in the sample flow reflects some average over the exposure time CFY magnitude, Φm(ST) < CFY < Φm(MT).

During the underway measurements described below in Results, the 1 L/min flow rate has resulted in 10 ms phytoplankton exposure time. Since the intense (~0.1 mol photons m−2 s−1) fluorescence excitation is used in the ALF instrument, the CFY almost reaches Φm(MT) during the 10 ms exposure and the resulting CF magnitude is only 10% lower than measured in the samples at 0.1 L/min flow rate (see Results and Discussion). Generally, this magnitude is determined by the fluorescence excitation intensity and the sample flow rate. The latter may explain the CF dependence on the flow rate often observed with field fluorometers (e.g., [48

48. S. T. Sweet and N. L. Guinasso, “Effects of flow-rate on fluorescence in vivo during continuous measurements on Gulf of Mexico surface-water,” Limnol. Oceanogr. 29(2), 397–401 (1984). [CrossRef]

]).

The underway shipboard measurements with the ALF instrument were conducted in the Delaware and Chesapeake Bays courtesy of the College of Marine Science (University of Delaware) onboard R/V Hugh R. Sharp during its non-stop transit from Lewes (Delaware) to Cambridge (Maryland) (see the map in Fig. 1). The water was continuously sampled by the shipboard sampling system at ~2 m below the water surface and directed to the ALF instrument through a 15 m silicon tube at the flow rate of 1 L/min. The delay between sampling and measuring the water was ~30 seconds.

The ALF measurement cycle included two measurements of spectral emission in 400–800 nm range using 405 and 532 nm laser excitation, respectively, and the temporally resolved measurement of CF induction over 100 μs in the spectral range of 670-695 nm using the pump-during-probe measurement protocol [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

, 25

25. R. J. Olson, A. M. Chekalyuk, and H. M. Sosik, “Phytoplankton photosynthetic characteristics from fluorescence induction assays of individual cells,” Limnol. Oceanogr. 41(6), 1253–1263 (1996). [CrossRef]

]. The spectral integration time was 1 s, and the laser excitation was turned off before and after the spectral measurements. The fluorescence induction waveforms were averaged over 5 to 10 flashes of laser excitation at 405 nm and 10 Hz repetition rate.

Twenty water samples were collected along the transect from the discharge of the flow-through system in the 500 mL dark-amber glass bottles and stored in a dark cooler filled with ice. The sampling locations are marked with numbers in Fig. 1. The ALF fluorescence measurements of the samples were conducted at Horn Point Laboratory (University of Maryland Center for Environmental Science) courtesy of Dr. Harding in about 1 hour on arrival to Cambridge. The samples were pumped at 0.1 L/min from the sample bottles through the ALF flow measurement cell. Ten sequent spectral measurements of the sample emission stimulated at 405 nm and 532 nm were conducted in the sample flow. In addition, 10 measurements of fluorescence induction, each averaged over 10 excitation shots, were conducted between the spectral measurements. The spectral and fluorescence induction measurements were averaged over the sequent acquisitions. The collected samples were also filtered for HPLC pigment analysis conducted later at the Pigment Analysis Facility of Horn Point Laboratory.

5. Results

To evaluate the applicability of the earlier instrument calibration, the CF underway transect measurements, CFU (the subscript “U” here and below denotes the underway data), were converted into CC units (dark green line in Fig. 2). The conversion equation CC=4.40CFUwas derived from the correlation (R2 = 0.93) between CC retrievals with high performance liquid chromatography (HPLC) and the ALF CF measurements of the dark-adapted water samples representing diverse coastal and estuarine waters (Fig. 7A in [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

]). As evident from comparison with the HPLC CC measurements in water samples collected along the transect (black squares in Fig. 2), the ALF CC assessments based on the nighttime or low- light measurements were in good agreement with the respective HPLC measurements(samples 1–14). On the other hand, the morning ALF fluorescence assessments showed significant, up to 5-fold, CC underestimation of the HPLC CC measurements.

Accordingly, the nighttime ALF CFU transect measurements at sampling locations 1–14 showed high correlation (R2 = 0.90) with the HPLC CC retrievals for the respective samples (diamonds in Fig. 3A), and the CC/CF ratio at these locations was close to the magnitude shown by the earlier ALF calibration for the dark-adapted samples (4.77 vs. 4.40). The morning ALF transect measurements at sampling locations 15–20 showed up to 5-fold lower and variable CFU per unit of CC (circles in Fig. 3A). That resulted in poor CFU vs. CC correlation for the entire data set that included both the nighttime and morning measurements (R2 = −0.22). Similarly, the laboratory CF measurements in samples 1–14 from the low-light or nighttime of the transect showed high correlation with the HPLC CC retrievals (diamonds in Fig. 3B). The CC/CF ratio 4.35 for these samples was very close to 4.40 from the earlier ALF calibration [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

], which was based on analysis of the dark-adapted samples. The morning samples 15–20 showed 10-30% lower and variable CFU per unit of CC (circles in Fig. 3B) that resulted in lower overall CFU vs. CC correlation (R2 = 0.80).

Figures 4A
Fig. 4 (A): Comparison of Chl fluorescence in the dark-adapted water samples (CFS) and underway measurements at the sampling locations (CFU). (B): Comparison of PSII photochemical yield measured in the dark-adapted water samples (PYS) and underway at the sampling locations (PYU). Diamonds and circles represent the nighttime (samples 1-14 in Figs. 1 and 2) and morning (samples 15-20) parts of the transect, respectively. (C) and D: Comparison of fluorescence parameters CF(PY−1-1) and CFU/PYU for the data sets displayed in panels (A) and (B).
and 4B allow direct comparison of the CFS and PYS magnitudes (the subscript “S” here and below denotes the sample measurements) measured in the dark-adapted samples and the respective underway CFU and PYU measurements at the sampling locations. Consistent with the plots in Fig. 3, the nighttime portion of the data (samples 1–14) show high correlation between the underway and sample measurements (R2 = 0.99 and 0.84 for CF and PY, respectively). The morning underway CFU and PYU magnitudes were noticeably lower than the respective CFS and PYS values, which resulted in the reduced overall correlations for the entire set of samples 1–20 (0.68 and 0.26 for CF and PY, respectively).

Assuming that the differences between the nighttime and morning portions of the data displayed in Figs. 2, 3, 4A and 4B were caused by the NPQ of CF and PY in the sampled sub-surface water in the morning hours, the NPQ invariance of the fluorescence parameters in Eqs. (19) and (20) can be evaluated. The CF(PY−1-1) magnitudes showed excellent correlation (R2 = 0.96) for the entire data set that includes both nighttime and morning samples 1–20 and the respective underway measurements at the sampling locations (Fig. 4C). Similarly high correlation (R2 = 0.95) was observed for the CF/PY parameter (Fig. 4D).

As evident from Figs. 5A
Fig. 5 (A): Correlations between the HPLC measurements of CC in water samples and fluorescence parameters CF(PY−1-1) and CF/PY calculated from Chl fluorescence (CF) and PSII photochemical yield (PY) measured in the dark-adapted water samples (B) and (D) and the underway flow-through CF and PY measurements at the sampling locations (A) and (B) marked as 1–20 in Figs. 1 and 2. Diamonds and circles represent the nighttime (samples 1-14) and morning (samples 15-20) parts of the transect, respectively.
and 5B, the CF(PY−1-1) magnitudes showed reasonably good correlation with the HPLC CC retrievals for both the underway and sample measurements (R2 = 0.74 and 0.83, respectively). The CF/PY parameter showed noticeably better correlations with the HPLC CC retrievals for both the underway and sample measurements (R2 = 0.93 and 0.96, respectively, Figs. 5C and 5D). For evaluation, the CCCF/PY transect distribution (light green line in Fig. 2) was calculated using the ALF underway transect measurements of CFU and PYU, and the regression equation CC=1.88CFU/PYUfrom Fig. 5C.

6. Discussion

6.1. Practical implementation of the four-step protocol

A four-step measurement protocol is proposed in section 3 to reduce the PQ and NPQ effects on the CF retrievals. The ALF in vivo CF measurements using this protocol show high correlation with independent HPLC CC retrievals (for example, see diamonds in Fig. 3A and 3B; see also Fig. 7A in [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

]). Recent ALF field deployments have confirmed that in vivo CF measurements compliant with the four-step protocol can indeed provide high-accuracy CC assessments. In coastal and estuarine waters that are typically dominated by diatoms and dinoflagellates, the relationship between CF and CC can be described by a simple regression equation (e.g., CC=4.40CFfor the ALF measurements [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

]) that does not show significant seasonal or regional variability. A more complex, non-linear relationship may need to be used in the offshore oceanic waters, particularly in the frontal zones that exhibit strong gradients in physical and chemical properties [50

50. A. M. Chekalyuk, Lamont Doherty Earth Observatory of Columbia University, 61 Route 9W, Palisades, NY 10964, M. Landry, R. Goericke, A. G. Taylor, and M. Hafez are preparing a manuscript to be called “Laser fluorescence phytoplankton analysis across a frontal zone in the California Current Ecosystem.”

].

Some aspects of the practical implementation of the four-step protocol are briefly discussed below. Many benchtop and some in situ fluorometers are equipped with a dark measurement chamber that provides optical isolation of the phytoplankton-containing water volume (condition # 1 of the protocol). Technically, the PSII saturating excitation (condition # 2) can be provided by selecting an appropriate light source for fluorescence excitation and through instrument design. For example, 405 and 532 nm lasers are used for this purpose in the ALF instrument. The small cross-section and low divergence of the laser beam simplifies optimization of the optical design. The narrow-bandwidth laser excitation minimizes the spectral bandwidth of the water Raman scattering and allows for spectral deconvolution of the overlapped fluorescence bands of seawater constituents [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

]. Light emitting diodes used for fluorescence excitation in various instruments, including PSII saturating fluorometers for measuring variable fluorescence, can provide a cost-efficient alternative to lasers.

Some relevant aspects of optimizing sample exposure to the excitation light (condition # 3) can be illustrated using the field data presented in Results. While both nighttime underway CF measurements and analyses of nighttime water samples showed high correlation with CC (R2 = 0.90 and 0.95, respectively in Fig. 3A, B), the slopes in the correlation equations were noticeably (~10%) different. The regression equation in Fig. 4A also suggests that the underway measurements yielded 10% lower CF magnitudes than the sample measurements. As discussed in section 4, this difference can be explained by shorter exposure of phytoplankton to the excitation due to the 10-fold faster flow rate used for the underway measurements. Much stronger CF dependence on the sampling flow rate can be observed under less intense fluorescence excitation intensity used in many instruments (e.g., [48

48. S. T. Sweet and N. L. Guinasso, “Effects of flow-rate on fluorescence in vivo during continuous measurements on Gulf of Mexico surface-water,” Limnol. Oceanogr. 29(2), 397–401 (1984). [CrossRef]

]).

Generally, the sample exposure time needs to be optimized to reduce the CF dependence on the measurement protocol. For CF measurements at the MT PSII turnover scale using PSII saturating excitation, it can be optimized with regard to the Kautsky effect [44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

, 47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]. Under these conditions, a 1–3 second exposure may appear to be optimal. Then, after reaching Φm(MT) during the initial 100–200 ms of Kautsky induction (see Section 4), CFY would remain at this level during most of the exposure time. When measuring the stationary sample, the CF measurements can begin when CFY reaches Φm(MT) and end before beginning manifestation of excitation-induced NPQ, which develops after ~3 seconds under such conditions (Fig. 1 in [47

47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

]). The signal integration time can be adjusted in some range (assuming CFY is still ~Φm(MT) during the measurement) to optimize the measurement protocol. In the case of flow-through measurements, the signal integration time can be longer than the exposure time to ensure the desirable signal-to-noise ratio.

In practice, the need for prolonged (~1 hour) phytoplankton dark adaptation before the fluorescence measurements (condition # 4) limits the four-step protocol mainly to laboratory use (including shipboard measurements). For field CF measurements in stationary settings (e.g. moorings, piers, etc.), the instrument can be equipped with a sampling chamber to provide adequate dark adaptation prior to the measurements. It should be noted that, based on our field experience, even several hours of dark adaptation is often insufficient for complete recovery from the photoinhibitory NPQ [39

39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

, 44

44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

] developed in the PSII RCs in subsurface water exposed to excessive solar irradiance. For example, the “leftover” NPQ effect was evident in CF measurements of the morning surface samples discussed in Results. After 2–3 hours of dark adaptation, these samples showed an increase in CF/CC magnitudes vs. the real-time underway measurements, which were strongly affected by NPQ (circles in Figs. 3B and 3A, respectively), but these values were still variable and lower than the night-collected samples (diamonds in Fig. 3B). Only one morning sample (# 15 in Fig. 2) that had the smallest exposure to solar irradiance after sunrise and the longest (~4 hour) duration of dark adaptation, showed complete recovery from NPQ. This is indicated by the fact that the CF/CC ratio is identical to the night-collected samples (CFS = 4 in Fig. 3B). Note that the same underway and sample data showed no difference between the morning and night measurements when the NPQ-invariant fluorescence parameter was used to correlate with CC (Figs. 5C and 5D).

6.2. CF adjusting for NPQ using PY measurements

In the case of continuous underway or in situ measurements, it is practically impossible to provide dark adaptation long enough to eliminate NPQ caused by phytoplankton exposure to ambient light prior to measurement. This may result in significant uncertainty in CC fluorescence assessments using instrument calibration with dark-adapted phytoplankton (for example, see Fig. 2). Even with an adequate analytical model, it is difficult to estimate the NPQ magnitude that is determined by the usually unknown phytoplankton light history. The above analysis shows that it may be possible to adjust the NPQ-affected CF measurements using concurrent measurements of variable fluorescence that yield PY magnitudes. The field data in Results allows for evaluating the feasibility of CC assessment using the NPQ-invariant fluorescent parameters derived from CF and PY measurements. In particular, the data sets used for calculation of CF(PY−1-1) and CF/PY data in Figs. 4C and 4D included both NPQ-free and NPQ-affected data from sampling locations 1–14 and 15–20, respectively (Fig. 2). Despite significant variability in the NPQ magnitudes (Figs. 3, 4A, 4B), both CF(PY−1-1) and CF/PY variables showed strong correlation (R2 = 0.96 vs. 0.95, respectively, in Figs. 4C and 4D), thus demonstrating their NPQ invariance.

It should be noted that both CF and PY were measured using PSII saturating excitation. Under this condition for the dark-adapted phytoplankton, PY = Φpm [12

12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods 6, 591–609 (2008). [CrossRef]

] and CF is proportional to Φm (see Section 4); the same is valid for light-adapted phytoplankton with the respective change in notation, Φ'pm and Φ'm. Thus, the NPQ invariance of CF(PY−1-1) (Fig. 4C) is fully consistent with the above model analysis (see Eq. (20)). On the other hand, despite the similarity between CF/PY and Φf /Φp ratios, the PSII saturating excitation is not described by Eq. (19), which actually predicts NPQ-invariance of Φf /Φp. Therefore, the experimentally observed NPQ invariance of the CF/PY parameter (Fig. 4D) is not justified by the simplified biophysical model discussed in Section 2. Nonetheless, this observation is still reported here, as it may provide new insight for better understanding of phytoplankton photosynthetic regulation in natural conditions and assist in improving CC fluorescence assessments.

Though both parameters performed equally well in terms of NPQ-invariance (Figs. 4C and 4D), the CF/PY ratio for both underway and sample retrievals showed better correlation with the HPLC CC measurements (R2 = 0.93 and 0.96, respectively; Fig. 5). The CF(PY−1-1) parameter calculated from the underway measurements at sampling locations 1–20 also showed a dramatic improvement in correlation with the HPLC CC data as compared to the CF magnitudes for the same data set (R2 = 0.74 vs. −0.22 in Figs. 5A and 3A, respectively).

Thus, the CF(PY−1-1) parameter can be used for reasonably accurate CC assessments from NPQ-affected measurements of CF and PY. A potential downside is that this parameter may appear to be more sensitive than CF to potential variability in the PSII photochemical functionality (determined by f in our model). Indeed, according to the model, CF(PY11)~Fo/Fpm=kf/fkp,while CF does not depend on f due to the PSII-saturating excitation. In particular, the significant transect variability in PYU (and, respectively, f (see Eq. (6))) evident in the Fig. 2 might account for CF(PY−1-1) correlation with HPLC CC that was lower than for nighttime, f-independent underway CF measurements (0.74 vs. 0.90 in Figs. 5A and 3A, respectively).

This may also explain the only marginal improvement in the CF(PY−1-1) correlation with HPLC CC as compared to the CF correlation for the dark-adapted samples (R2 = 0.83 vs. 0.80 in Figs. 5B and 3B, respectively). If our interpretation is correct, the PQ variability in CF was minimized by using PSII saturating excitation, but the CF magnitudes in the morning samples were still moderately NPQ-affected because of their incomplete recovery from NPQ (empty dots in Fig. 3B). This “leftover” NPQ effect was not manifested in the CF(PY−1-1) parameter, but the overall transect variability in the PSII photochemical functionality might have affected the CF(PY11)/CCrelationship.

Similar comparisons for the CF/PY parameter revealed significant improvements in correlations with HPLC CC retrievals for both the underway and sample measurements: R2 = 0.93 vs. −0.22 in Figs. 5C and 3A; R2 = 0.96 vs. 0.80 in Figs. 5D and 3B. Though the use of CF/PY parameter was not justified by the simplified biophysical model and needs further consideration, the CF/PY ratio may be advantageous vs. the CF(PY−1-1) parameter for minimizing the effects of both NPQ and PQ variability on the accuracy of CC fluorescence assessments. For evaluation, the linear regression relationship CC = 1.88CFU/PYU between CC and underway fluorescence measurements at the sampling locations (Fig. 5C) was used to calculate the CC transect distribution (light green line Fig. 2). As evident from comparison with the independent CC sample measurements, the concurrent CF and PY measurements provided accurate high-resolution CC data despite the significant NPQ and PSII physiological variability in the water masses.

7. Conclusion

The biophysical analysis and field measurements show that significant (up to 15-fold) photo-physiological variability in fluorescence yield is one of the major factors contributing to the overall variability in in vivo chlorophyll fluorescence per unit of chlorophyll concentration. The fluorescence yield and PSII photochemical efficiency are controlled by PQ and NPQ mechanisms and depend on incident light intensity, phytoplankton “light history”, PSII photochemical functionality, and other physiological factors. Minimizing the PQ and NPQ magnitudes can help to reduce the variability and improve the accuracy of CC fluorescence assessments. This can be achieved via isolation of the measurement volume from ambient light, PSII saturating fluorescence excitation, optimization of phytoplankton exposure to the excitation, and phytoplankton dark adaptation before the measurements. If the measurement conditions do not allow for dark adaptation (e.g., in situ or flow-though underway measurements from a moving platform), concurrent measurements of variable fluorescence can be used to adjust fluorescence intensity for non-photochemical quenching developed due to prior exposure to ambient light. The field evaluation in estuarine waters of the Chesapeake and Delaware Bays showed significant potential of this approach for improved fluorescence assessments of chlorophyll concentration. Nonetheless, it needs evaluation in more diverse coastal and offshore oceanic waters. An improved biophysical model needs to be developed to account for the complexity of the photo-physiological mechanisms involved.

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T. J. Cowles, R. A. Desiderio, and S. Neuer, “In situ characterization of phytoplankton from vertical profiles of fluorescence emission-spectra,” Mar. Biol. 115(2), 217–222 (1993). [CrossRef]

14.

G. Parésys, C. Rigart, B. Rousseau, A. W. M. Wong, F. Fan, J. P. Barbier, and J. Lavaud, “Quantitative and qualitative evaluation of phytoplankton communities by trichromatic chlorophyll fluorescence excitation with special focus on cyanobacteria,” Water Res. 39(5), 911–921 (2005). [CrossRef] [PubMed]

15.

C. W. Proctor and C. S. Roesler, “New insights on obtaining phytoplankton concentration and composition from in situ multispectral chlorophyll fluorescence,” Limnol. Oceanogr. Methods 8, 695–708 (2010). [CrossRef]

16.

T. L. Richardson, E. Lawrenz, J. L. Pinckney, R. C. Guajardo, E. A. Walker, H. W. Paerl, and H. L. MacIntyre, “Spectral fluorometric characterization of phytoplankton community composition using the Algae Online Analyser,” Water Res. 44(8), 2461–2472 (2010). [CrossRef] [PubMed]

17.

T. S. Bibby, M. Y. Gorbunov, K. W. Wyman, and P. G. Falkowski, “Photosynthetic community responses to upwelling in mesoscale eddies in the subtropical North Atlantic and Pacific Oceans,” Deep Sea Res. Part II Top. Stud. Oceanogr. 55(10-13), 1310–1320 (2008). [CrossRef]

18.

A. M. Chekalyuk, F. E. Hoge, C. W. Wright, and R. N. Swift, “Short-pulse pump-and-probe technique for airborne laser assessment of Photosystem II photochemical characteristics,” Photosynth. Res. 66(1/2), 33–44 (2000). [CrossRef] [PubMed]

19.

P. Falkowski and D. A. Kiefer, “Chlorophyll-a fluorescence in phytoplankton - relationship to photosynthesis and biomass,” J. Plankton Res. 7(5), 715–731 (1985). [CrossRef]

20.

P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Aust. J. Plant Physiol. 22(2), 341–355 (1995). [CrossRef]

21.

T. Fujiki, T. Hosaka, H. Kimoto, T. Ishimaru, and T. Saino, “In situ observation of phytoplankton productivity by an underwater profiling buoy system: use of fast repetition rate fluorometry,” Mar. Ecol. Prog. Ser. 353, 81–88 (2008). [CrossRef]

22.

M. Y. Gorbunov, P. G. Falkowski, and Z. S. Kolber, “Measurement of photosynthetic parameters in benthic organisms in situ using a SCUBA-based fast repetition rate fluorometer,” Limnol. Oceanogr. 45(1), 242–245 (2000). [CrossRef]

23.

Z. Kolber, K. D. Wyman, and P. G. Falkowski, “Natural variability in photosynthetic energy-conversion efficiency - afield-study in the Gulf of Maine,” Limnol. Oceanogr. 35(1), 72–79 (1990). [CrossRef]

24.

Z. Kolber and P. G. Falkowski, “Use of active fluorescence to estimate phytoplankton photosynthesis in-situ,” Limnol. Oceanogr. 38(8), 1646–1665 (1993). [CrossRef]

25.

R. J. Olson, A. M. Chekalyuk, and H. M. Sosik, “Phytoplankton photosynthetic characteristics from fluorescence induction assays of individual cells,” Limnol. Oceanogr. 41(6), 1253–1263 (1996). [CrossRef]

26.

R. J. Olson, H. M. Sosik, and A. M. Chekalyuk, “Photosynthetic characteristics of marine phytoplankton from pump-during-probe fluorometry of individual cells at sea,” Cytometry 37(1), 1–13 (1999). [CrossRef] [PubMed]

27.

R. J. Olson, H. M. Sosik, A. M. Chekalyuk, and A. Shalapyonok, “Effects of iron enrichment on phytoplankton in the Southern Ocean during late summer: active fluorescence and flow cytometric analyses,” Deep Sea Res. Part II Top. Stud. Oceanogr. 47(15-16), 3181–3200 (2000). [CrossRef]

28.

M. P. Raateoja, “Fast repetition rate fluorometry (FRRF) measuring phytoplankton productivity: a case study at the entrance to the Gulf of Finland, Baltic Sea,” Boreal Environ. Res. 9, 263–276 (2004).

29.

Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences 4(5), 853–868 (2007). [CrossRef]

30.

M. Kruskopf and K. J. Flynn, “Chlorophyll content and fluorescence responses cannot be used to gauge reliably phytoplankton biomass, nutrient status or growth rate,” New Phytol. 169(3), 525–536 (2006). [CrossRef] [PubMed]

31.

O. C. Swertz, F. Colijn, H. W. Hofstraat, and B. A. Althuis, “Temperature, salinity, and fluorescence in Southern North Sea: high-resolution data sampled from a ferry,” Environ. Manage. 23(4), 527–538 (1999). [CrossRef] [PubMed]

32.

C. D. Wirick, “Exchange of phytoplankton across the continental shelf-slope boundary of the Middle Atlantic Bight during spring-1988,” Deep Sea Res. Part II Top. Stud. Oceanogr. 41(2-3), 391–410 (1994). [CrossRef]

33.

A. E. Alpine and J. E. Cloern, “Differences in in vivo fluorescence yield between three phytoplankton size classes,” J. Plankton Res. 7(3), 381–390 (1985). [CrossRef]

34.

J. J. Cullen, “The deep chlorophyll maximum - comparing vertical profiles of chlorophyll-a,” Can. J. Fish. Aquat. Sci. 39(5), 791–803 (1982). [CrossRef]

35.

J. J. Cullen and M. R. Lewis, “Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensing,” J. Geophys. Res. - Oceans 100(C7), 13255–13266 (1995). [CrossRef]

36.

M. E. Loftus and H. H. Seliger, “Some limitations of the in vivo fluorescence technique,” Chesap. Sci. 16(2), 79–92 (1975). [CrossRef]

37.

T. Jakob, U. Schreiber, V. Kirchesch, U. Langner, and C. Wilhelm, “Estimation of chlorophyll content and daily primary production of the major algal groups by means of multiwavelength-excitation PAM chlorophyll fluorometry: performance and methodological limits,” Photosynth. Res. 83(3), 343–361 (2005). [CrossRef] [PubMed]

38.

Z. S. Kolber, O. Prasil, and P. G. Falkowski, “Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: defining methodology and experimental protocols,” BBA.- Bioenergetics 1367(1-3), 88–106 (1998). [CrossRef]

39.

G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol. 42(1), 313–349 (1991). [CrossRef]

40.

T. R. Jacobsen, “A quantitative method for the separation of chlorophyll a and b from phytoplankton pigments by HPLC,” Mar. Sci. Comm. 4, 33–47 (1978).

41.

C. J. Lorenzen, “Determination of chlorophyll and pheo-pigments - spectrophotometric equations,” Limnol. Oceanogr. 12(2), 343–346 (1967). [CrossRef]

42.

O. C. J. Holm-Hansen, C. J. Lorenzen, R. W. Holmes, and J. D. H. Strickland, “Fluorometric determination of chlorophyll,” J. Cons. Perm. Int. Explor. Mer. 30, 3–15 (1965).

43.

Govindje, “63 years since Kautsky - chlorophyll-a fluorescence,” Aust. J. Plant Physiol. 22(2), 131–160 (1995). [CrossRef]

44.

G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res. 94(2-3), 275–290 (2007). [CrossRef] [PubMed]

45.

J. C. Kromkamp and R. M. Forster, “The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology,” Eur. J. Phycol. 38(2), 103–112 (2003). [CrossRef]

46.

S. I. Heaney, “Some observations on use of in vivo fluorescence technique to determine chlorophyll-a in natural-populations and cultures of freshwater phytoplankton,” Freshw. Biol. 8(2), 115–126 (1978). [CrossRef]

47.

A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B 104(1-2), 236–257 (2011). [CrossRef] [PubMed]

48.

S. T. Sweet and N. L. Guinasso, “Effects of flow-rate on fluorescence in vivo during continuous measurements on Gulf of Mexico surface-water,” Limnol. Oceanogr. 29(2), 397–401 (1984). [CrossRef]

49.

R. Röttgers, “Comparison of different variable chlorophyll a fluorescence techniques to determine photosynthetic parameters of natural phytoplankton,” Deep Sea Res. Part I Oceanogr. Res. Pap. 54(3), 437–451 (2007). [CrossRef]

50.

A. M. Chekalyuk, Lamont Doherty Earth Observatory of Columbia University, 61 Route 9W, Palisades, NY 10964, M. Landry, R. Goericke, A. G. Taylor, and M. Hafez are preparing a manuscript to be called “Laser fluorescence phytoplankton analysis across a frontal zone in the California Current Ecosystem.”

OCIS Codes
(010.4450) Atmospheric and oceanic optics : Oceanic optics
(140.0140) Lasers and laser optics : Lasers and laser optics
(300.0300) Spectroscopy : Spectroscopy
(280.4788) Remote sensing and sensors : Optical sensing and sensors

ToC Category:
Atmospheric and Oceanic Optics

History
Original Manuscript: September 1, 2011
Revised Manuscript: October 7, 2011
Manuscript Accepted: October 8, 2011
Published: October 25, 2011

Virtual Issues
Vol. 7, Iss. 1 Virtual Journal for Biomedical Optics

Citation
Alexander Chekalyuk and Mark Hafez, "Photo-physiological variability in phytoplankton chlorophyll fluorescence and assessment of chlorophyll concentration," Opt. Express 19, 22643-22658 (2011)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-19-23-22643


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References

  1. G. C. Papageorgiou and Govindjee (Eds.), Chlorophyll a Fluorescence: A Signature of Photosynthetsis, Advances in Photosynthesis and Respiration (Springer, Dordrecht, 2004).
  2. T. J. Cowles, J. N. Moum, R. A. Desiderio, and S. M. Angel, “In situ monitoring of ocean chlorophyll via laser-induced fluorescence backscattering through an optical fiber,” Appl. Opt.28(3), 595–600 (1989). [CrossRef] [PubMed]
  3. E. J. D'Sa, S. E. Lohrenz, J. H. Churchill, V. L. Asper, J. L. Largier, and A. J. Williams, “Chloropigment distribution and transport on the inner shelf off Duck, North Carolina,” J. Geophys. Res.- Oceans106(C6), 11581–11596 (2001). [CrossRef]
  4. C. E. Del Castillo, P. G. Coble, R. N. Conmy, F. E. Muller-Karger, L. Vanderbloemen, and G. A. Vargo, “Multispectral in situ measurements of organic matter and chlorophyll fluorescence in seawater: Documenting the intrusion of the Mississippi River plume in the West Florida Shelf,” Limnol. Oceanogr.46(7), 1836–1843 (2001). [CrossRef]
  5. Z. Kolber and P. G. Falkowski, “Use of active fluorescence to estimate phytoplankton photosynthesis in-situ,” Limnol. Oceanogr.38(8), 1646–1665 (1993). [CrossRef]
  6. M. J. Perry, B. S. Sackmann, C. C. Eriksen, and C. M. Lee, “Seaglider observations of blooms and subsurface chlorophyll maxima off the Washington coast,” Limnol. Oceanogr.53(5_part_2), 2169–2179 (2008). [CrossRef]
  7. S. Babichenko, S. Kaitala, A. Leeben, L. Poryvkina, and J. Seppala, “Phytoplankton pigments and dissolved organic matter distribution in the Gulf of Riga,” J. Mar. Syst.23(1-3), 69–82 (1999). [CrossRef]
  8. A. M. Chekalyuk, F. E. Hoge, C. W. Wright, R. N. Swift, and J. K. Yungel, “Airborne test of laser pump-and-probe technique for assessment of phytoplankton photochemical characteristics,” Photosynth. Res.66(1/2), 45–56 (2000). [CrossRef] [PubMed]
  9. J. H. Churnside and P. L. Donaghay, “Thin scattering layers observed by airborne lidar,” ICES J. Mar. Sci.66(4), 778–789 (2009). [CrossRef]
  10. F. E. Hoge and R. N. Swift, “Airborne simultaneous spectroscopic detection of laser-induced water Raman backscatter and fluorescence from chlorophyll a and other naturally occurring pigments,” Appl. Opt.20(18), 3197–3205 (1981). [CrossRef] [PubMed]
  11. M. Beutler, K. H. Wiltshire, B. Meyer, C. Moldaenke, C. Lüring, M. Meyerhöfer, U. P. Hansen, and H. Dau, “A fluorometric method for the differentiation of algal populations in vivo and in situ,” Photosynth. Res.72(1), 39–53 (2002). [CrossRef] [PubMed]
  12. A. Chekalyuk and M. Hafez, “Advanced laser fluorometry of natural aquatic environments,” Limnol. Oceanogr. Methods6, 591–609 (2008). [CrossRef]
  13. T. J. Cowles, R. A. Desiderio, and S. Neuer, “In situ characterization of phytoplankton from vertical profiles of fluorescence emission-spectra,” Mar. Biol.115(2), 217–222 (1993). [CrossRef]
  14. G. Parésys, C. Rigart, B. Rousseau, A. W. M. Wong, F. Fan, J. P. Barbier, and J. Lavaud, “Quantitative and qualitative evaluation of phytoplankton communities by trichromatic chlorophyll fluorescence excitation with special focus on cyanobacteria,” Water Res.39(5), 911–921 (2005). [CrossRef] [PubMed]
  15. C. W. Proctor and C. S. Roesler, “New insights on obtaining phytoplankton concentration and composition from in situ multispectral chlorophyll fluorescence,” Limnol. Oceanogr. Methods8, 695–708 (2010). [CrossRef]
  16. T. L. Richardson, E. Lawrenz, J. L. Pinckney, R. C. Guajardo, E. A. Walker, H. W. Paerl, and H. L. MacIntyre, “Spectral fluorometric characterization of phytoplankton community composition using the Algae Online Analyser,” Water Res.44(8), 2461–2472 (2010). [CrossRef] [PubMed]
  17. T. S. Bibby, M. Y. Gorbunov, K. W. Wyman, and P. G. Falkowski, “Photosynthetic community responses to upwelling in mesoscale eddies in the subtropical North Atlantic and Pacific Oceans,” Deep Sea Res. Part II Top. Stud. Oceanogr.55(10-13), 1310–1320 (2008). [CrossRef]
  18. A. M. Chekalyuk, F. E. Hoge, C. W. Wright, and R. N. Swift, “Short-pulse pump-and-probe technique for airborne laser assessment of Photosystem II photochemical characteristics,” Photosynth. Res.66(1/2), 33–44 (2000). [CrossRef] [PubMed]
  19. P. Falkowski and D. A. Kiefer, “Chlorophyll-a fluorescence in phytoplankton - relationship to photosynthesis and biomass,” J. Plankton Res.7(5), 715–731 (1985). [CrossRef]
  20. P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Aust. J. Plant Physiol.22(2), 341–355 (1995). [CrossRef]
  21. T. Fujiki, T. Hosaka, H. Kimoto, T. Ishimaru, and T. Saino, “In situ observation of phytoplankton productivity by an underwater profiling buoy system: use of fast repetition rate fluorometry,” Mar. Ecol. Prog. Ser.353, 81–88 (2008). [CrossRef]
  22. M. Y. Gorbunov, P. G. Falkowski, and Z. S. Kolber, “Measurement of photosynthetic parameters in benthic organisms in situ using a SCUBA-based fast repetition rate fluorometer,” Limnol. Oceanogr.45(1), 242–245 (2000). [CrossRef]
  23. Z. Kolber, K. D. Wyman, and P. G. Falkowski, “Natural variability in photosynthetic energy-conversion efficiency - afield-study in the Gulf of Maine,” Limnol. Oceanogr.35(1), 72–79 (1990). [CrossRef]
  24. Z. Kolber and P. G. Falkowski, “Use of active fluorescence to estimate phytoplankton photosynthesis in-situ,” Limnol. Oceanogr.38(8), 1646–1665 (1993). [CrossRef]
  25. R. J. Olson, A. M. Chekalyuk, and H. M. Sosik, “Phytoplankton photosynthetic characteristics from fluorescence induction assays of individual cells,” Limnol. Oceanogr.41(6), 1253–1263 (1996). [CrossRef]
  26. R. J. Olson, H. M. Sosik, and A. M. Chekalyuk, “Photosynthetic characteristics of marine phytoplankton from pump-during-probe fluorometry of individual cells at sea,” Cytometry37(1), 1–13 (1999). [CrossRef] [PubMed]
  27. R. J. Olson, H. M. Sosik, A. M. Chekalyuk, and A. Shalapyonok, “Effects of iron enrichment on phytoplankton in the Southern Ocean during late summer: active fluorescence and flow cytometric analyses,” Deep Sea Res. Part II Top. Stud. Oceanogr.47(15-16), 3181–3200 (2000). [CrossRef]
  28. M. P. Raateoja, “Fast repetition rate fluorometry (FRRF) measuring phytoplankton productivity: a case study at the entrance to the Gulf of Finland, Baltic Sea,” Boreal Environ. Res.9, 263–276 (2004).
  29. Y. Huot, M. Babin, F. Bruyant, C. Grob, M. S. Twardowski, and H. Claustre, “Relationship between photosynthetic parameters and different proxies of phytoplankton biomass in the subtropical ocean,” Biogeosciences4(5), 853–868 (2007). [CrossRef]
  30. M. Kruskopf and K. J. Flynn, “Chlorophyll content and fluorescence responses cannot be used to gauge reliably phytoplankton biomass, nutrient status or growth rate,” New Phytol.169(3), 525–536 (2006). [CrossRef] [PubMed]
  31. O. C. Swertz, F. Colijn, H. W. Hofstraat, and B. A. Althuis, “Temperature, salinity, and fluorescence in Southern North Sea: high-resolution data sampled from a ferry,” Environ. Manage.23(4), 527–538 (1999). [CrossRef] [PubMed]
  32. C. D. Wirick, “Exchange of phytoplankton across the continental shelf-slope boundary of the Middle Atlantic Bight during spring-1988,” Deep Sea Res. Part II Top. Stud. Oceanogr.41(2-3), 391–410 (1994). [CrossRef]
  33. A. E. Alpine and J. E. Cloern, “Differences in in vivo fluorescence yield between three phytoplankton size classes,” J. Plankton Res.7(3), 381–390 (1985). [CrossRef]
  34. J. J. Cullen, “The deep chlorophyll maximum - comparing vertical profiles of chlorophyll-a,” Can. J. Fish. Aquat. Sci.39(5), 791–803 (1982). [CrossRef]
  35. J. J. Cullen and M. R. Lewis, “Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensing,” J. Geophys. Res. - Oceans100(C7), 13255–13266 (1995). [CrossRef]
  36. M. E. Loftus and H. H. Seliger, “Some limitations of the in vivo fluorescence technique,” Chesap. Sci.16(2), 79–92 (1975). [CrossRef]
  37. T. Jakob, U. Schreiber, V. Kirchesch, U. Langner, and C. Wilhelm, “Estimation of chlorophyll content and daily primary production of the major algal groups by means of multiwavelength-excitation PAM chlorophyll fluorometry: performance and methodological limits,” Photosynth. Res.83(3), 343–361 (2005). [CrossRef] [PubMed]
  38. Z. S. Kolber, O. Prasil, and P. G. Falkowski, “Measurements of variable chlorophyll fluorescence using fast repetition rate techniques: defining methodology and experimental protocols,” BBA.- Bioenergetics1367(1-3), 88–106 (1998). [CrossRef]
  39. G. H. Krause and E. Weis, “Chlorophyll fluorescence and photosynthesis - the basics,” Annu. Rev. Plant Physiol.42(1), 313–349 (1991). [CrossRef]
  40. T. R. Jacobsen, “A quantitative method for the separation of chlorophyll a and b from phytoplankton pigments by HPLC,” Mar. Sci. Comm.4, 33–47 (1978).
  41. C. J. Lorenzen, “Determination of chlorophyll and pheo-pigments - spectrophotometric equations,” Limnol. Oceanogr.12(2), 343–346 (1967). [CrossRef]
  42. O. C. J. Holm-Hansen, C. J. Lorenzen, R. W. Holmes, and J. D. H. Strickland, “Fluorometric determination of chlorophyll,” J. Cons. Perm. Int. Explor. Mer.30, 3–15 (1965).
  43. Govindje, “63 years since Kautsky - chlorophyll-a fluorescence,” Aust. J. Plant Physiol.22(2), 131–160 (1995). [CrossRef]
  44. G. C. Papageorgiou, M. Tsimilli-Michael, and K. Stamatakis, “The fast and slow kinetics of chlorophyll a fluorescence induction in plants, algae and cyanobacteria: a viewpoint,” Photosynth. Res.94(2-3), 275–290 (2007). [CrossRef] [PubMed]
  45. J. C. Kromkamp and R. M. Forster, “The use of variable fluorescence measurements in aquatic ecosystems: differences between multiple and single turnover measuring protocols and suggested terminology,” Eur. J. Phycol.38(2), 103–112 (2003). [CrossRef]
  46. S. I. Heaney, “Some observations on use of in vivo fluorescence technique to determine chlorophyll-a in natural-populations and cultures of freshwater phytoplankton,” Freshw. Biol.8(2), 115–126 (1978). [CrossRef]
  47. A. Stirbet and Govindjee, “On the relation between the Kautsky effect (chlorophyll a fluorescence induction) and Photosystem II: basics and applications of the OJIP fluorescence transient,” J. Photochem. Photobiol. B104(1-2), 236–257 (2011). [CrossRef] [PubMed]
  48. S. T. Sweet and N. L. Guinasso, “Effects of flow-rate on fluorescence in vivo during continuous measurements on Gulf of Mexico surface-water,” Limnol. Oceanogr.29(2), 397–401 (1984). [CrossRef]
  49. R. Röttgers, “Comparison of different variable chlorophyll a fluorescence techniques to determine photosynthetic parameters of natural phytoplankton,” Deep Sea Res. Part I Oceanogr. Res. Pap.54(3), 437–451 (2007). [CrossRef]
  50. A. M. Chekalyuk, Lamont Doherty Earth Observatory of Columbia University, 61 Route 9W, Palisades, NY 10964, M. Landry, R. Goericke, A. G. Taylor, and M. Hafez are preparing a manuscript to be called “Laser fluorescence phytoplankton analysis across a frontal zone in the California Current Ecosystem.”

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