Conclusion & References

The study system was an oligotrophic environment where plankton were subjected to conditions of “critically phosphate-deficiency” and “severely phosphate-deficiency”

during cold-mixing and warm-stratified seasons, respectively. Seasonal variations of bulk APA and biomass normalized APA were mainly controlled by the changes of phosphate availability (i.e. mixed layer depth) and light intensity. Typhoon strength in the summers accounted for the inter-annual variations of bulk and specific APA.

Picocyanobacteria and heterotrophic bacteria were the two most abundant plankton in this system, their relative contributions to bulk APA is one of the important issues to be identified.

References

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Oceanogr. 8:166-183.

Berman T (1970) Alkaline phosphatase and phosphorus availability in Lake Kinneret Limnol. Oceanogr. 15:663-674.

Cao XY, Song CL, Zhou YY (2010) Limitations of using extracellular alkaline phosphatase activities as a general indicator for describing P deficiency of phytoplankton in Chinese shallow lakes. J. Appl. Phycol. 22:33-41.

Cao XY, Strojsova A, Znachor P, Zapomelova E, Liu GX, Vrba J, Zhou YY (2005) Detection of extracellular phosphatases in natural spring phytoplankton of a shallow eutrophic lake (Donghu, China). European Journal of Phycology 40:251-258.

Chan JCL, Liu KS (2004) Global warming and western North Pacific typhoon activity from an observational perspective. J. Clim. 17:4590-4602.

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Chrost RJ, Overbeck J (1987) Kinetics of alkaline phosphatase activity and phosphorus availability for phytoplankton and bacterioplankton in Lake Plusssee (North-German Eutrophic Lake). Microb. Ecol. 13:229-248.

Fisher TR, Peele ER, Ammerman JW, Harding LW (1992) Nutrient limitation of phytoplankton in Chesapeake Bay. Mar. Ecol.-Prog. Ser. 82:51-63.

Gage MA, Gorham E (1985) Alkaline phosphatase activity and cellular phosphorus as an index of the phosphorus status of phytoplankton in Minnesota lakes. Freshwater Biology 15:227-233.

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Healey FP, Hendzel LL (1979) Fluorometric measurement of alkaline phosphatase activity in algae. Freshwater Biology 9:429-439.

Healey FP, Hendzel LL (1980) Physiological indicators of nutrient deficiency in lake phytoplankton. Can. J. Fish. Aquat. Sci. 37:442-453.

Istvanovics V, Pettersson K, Pierson D, Bell R (1992) Evaluation of phosphorus deficiency indicators for summer phytoplankton in Lake Erken. Limnol.

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Jamet D, Amblard C, Devaux J (1997) Seasonal changes in alkaline phosphatase activity of bacteria and microalgae in Lake Pavin (Massif Central, France). Hydrobiologia 347:185-195.

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Aquatic Ecology 43:19-25.

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- 34 -

depth-integrated averages (

_DIA

)

^@

collected from the study site during the period of 2006~2009. All are significant at p <0.01.

@, T, L, MLD, DIN

_DIA

, SRP

_DIA

, N/P

_DIA

, Chl

_DIA

, CYA

_DIA

, BA

_DIA

, APA

_DIA

, and SAPA

_DIA

indicated surface temperature, weekly-averaged light intensity, and epilimnic depth-integrated averages of mixed layer depth, dissolved inorganic nitrogen (nitrate + nitrite), soluble reactive phosphorus, ratio of DIN to SRP, chlorophyll a, picocyanobacteria abundance, bacteria abundance, alkaline phosphatase activity, and specific phosphatase activity, respectively. Ln-, natural-log transformed; #, power function fit. -, zero correlation.

Parameters T L MLD DIN

DIA

SRP

DIA

N/P

DIA

Chl

DIA

Ln-CYA

DIA

Ln-BA

DIA

APA

DIA

SAPA

DIA

Units

^{℃ mE m-2 d-1 m} μM N μM P mol N mol P^-1 mg Chl m^-3 10¹¹ cells m^-3 10¹² cells m^-3 nM h^-1 nmol mg C^-1 h^-1

T 1

L 0.36 1

MLD -0.65 -0.44 1

DIN

DIA

-0.32 -0.24 0.30 1

SRP

DIA

- - - 0.25 1

N/P

DIA

- - - 0.44 -0.64 1

Chl

DIA

0.23 - - - - - 1

Ln-CYA

DIA

- - -0.28

^#

- - - 0.39

^#

1

Ln-BA

DIA

0.58

^#

- -0.53

^#

- - - - 0.41

^#

1

APA

DIA

0.48 0.47 -0.68 -0.42 -0.25 - 0.27 0.47

^#

0.44

^#

1

SAPA

DIA

0.24 0.61 -0.55 -0.32 -0.22 - na 0.28

^#

na 0.77 1

- 35 -

Table 2.2. Multiple linear regression analysis of year-to-year and pooled APA and specific APA (SAPA) over other environmental factors^@. Numerical indicated the standardized regression coefficient (Beta weight). R², coefficient of determination. na, not analyzed.

@, the same as Table 2.1.

Year T L MLD DINDIA SRPDIA ChlDIA CYADIA BADIA R² units ℃ mE m^-2 d^-1 m μM N μM P mgChl m^-3 10¹¹ cells m^-3 10¹² cells m^-3

2006 APA - - - - - 0.44 - 0.44 0.49

2007 APA - - -0.66 - - - - - 0.65

2008 APA - - -0.49 - - 0.51 - - 0.72

2009 APA - 0.62 - - - - 0.57 - 0.72

Pooled APA 0.21 -0.41 -0.22 -0.15 - 0.30 - 0.65

2006 SAPA - - - na - na 0.30

2007SAPA - - -0.69 - - na - na 0.72

2008 SAPA - - -0.58 - - na na na 0.62

2009 SAPA - 0.52 -1.50 - - na - na 0.80

Pooled SAPA -0.27 0.45 -0.40 -0.22 - na - na 0.66

- 36 -

Table 2.3. A year-to-year comparison of the averages (±SE)^# of the parameters^@ collected during the typhoon season (Jul ~ Sep).

Parameters Units 2006 (a) 2007 (b) 2008 (c) 2009 (d)

Typhoon index m² s^-1 4.3±0.9 (0)^bc 12.2±3.8 (2)^ad 13.1±6.5 (2) 2.8±1.6 (0)

Precipitation© mm 1276 1658 1819 673

T ℃ 29.3±0.5 29.6±0.4 29.4±0.4 29.3±0.3 L mE m^-2 d^-1 63±5 67±5 67±4 81±8^abc

MLD m 7±0.7 7±0.4 9±1.0 8±1.5

DINDIA μM N 17±0.6^cd 23±0.9^cd 46±1.2 41±3.9

SRPDIA μM P 0.03±0.005 0.06±0.007^acd 0.02±0.001 0.03±0.005 N/PDIA mol N mol P^-1 827±29^cd 518±101^cd 2316±79^abd 1617±332^abc ChlDIA mg m^-3 3.3±0.2^b 2.2±0.2 2.8±0.2 2.4±0.4 CYADIA 10¹¹ cells m^-3 1.5±0.15 1.4±0.10 1.3±0.11^d 1.9±0.13 BADIA 10¹²cells m^-3 2.2±0.12^bc 3.2±0.19 3.4±0.23 2.7±0.25^bc APADIA nM h^-1 50.2±3.6 47.7±4.5 47.5±5.4 53.3±6.4 SAPADIA nmol mg C^-1 h^-1 212±26 243±15 203±17 302±46

@, the same at Table 2.1. #, numeric with superscript a, b, c, and d indicate it is different from those values of year 2006, 2007, 2008, and 2009 (ANOVA). The numeral in parenthesis indicated strong typhoon number.©, the sum of precipitation during typhoon event.

- 37 -

Table 2.4. Linear correlation matrix of surface temperature (T), weekly-averaged light intensity (L), and the epilimnic (0~20m) depth-integrated averages (

DIA

)

^@

collected from typhoon seasons (Jul~Sep) during the period of 2006~2009. All are significant at p <0.01.

@, the same as Table 2.1. Ln-, natural-log transformed; #, power function fit. -, zero correlation.

Parameters T L MLD DIN

DIA

SRP

DIA

N/P

DIA

Chl

DIA

Ln-CYA

DIA

Ln-BA

DIA

APA

DIA

SAPA

DIA

℃ mE m^-2 d^-1 m μM N μM P mol N mol P^-1 mg Chl m^-3 10¹¹ cells m^-3 10¹² cells m^-3 nM h^-1 nmol mg C^-1 h^-1

T 1

L 0.40 1

MLD -0.53 - 1

DIN

DIA

- - - 1

SRP

_DIA

- - - -0.44 1

N/P

_DIA

- - - 0.89 -0.71 1

Chl

_DIA

- - - - -0.39 - 1

Ln-CYA

_DIA

0.46

^#

- - - - - - 1

Ln-BA

_DIA

0.41

^#

- - - - - - - 1

APA

_DIA

- - - - - - 0.51 0.55

^#

- 1

SAPA

_DIA

- - - - - - na na - 0.61 1

- 38 -

Table 2.5. A comparison of bulk alkaline phosphatase activity (APA; nM h^-1) derived from this and other aquatic ecosystems.

Systems Trophic status APA References

Mediterranean Reservoir (Spain) Eutrophic 500~3400 Nedoma

et al. (2006)

Rimov Reservoir (Czech) Eutrophic 7~727 Vrba et al. (1993) Baltic Sea, Kiel Fjord Mesotrophic 4~160 Hoppe (1986)

Red Sea Oligotrophic 40~150 Li et al. (1998)

East China Sea Meso to

oligotrophic <1~74 Huang

et al. (2007)

Central North Pacific Oligotrophic <1~8 Perry (1972) Subtropical Feitsui Reservoir Oligotrophic 1~95 This study

- 39 -

Table 2.6. The level of specific alkaline phosphatase activity (SAPA) as an indicator for P-starvation in this and other studies. The definition of “constitutive” here means the specific APA always exists and is independent to external or internal phosphate concentration.

References Data type Levels of SAPA (nmol mgC^-1 h^-1)

constitutive Critical

P-starvation

Severe P-starvation

Healey & Hendzel (1979) Algal cultures <40 40~200 >200 Pettersson (1980, 1985) Lake plankton 6~50 50~140 >140 Gage & Gorham (1985) Lake plankton <50 50~250 >250

FT reservoir

Mixed seasons Lake plankton 158±138 ( critical P-starvation) Stratified seasons Lake plankton 391±207 (severe P-starvation)

- 40 -  

24.53 24.55 24.57

121.34 121.36 121.38 121.40

 

Fig. 2.1. Map of the Feitsui Reservoir showing the sampling site (the dam-site, ■).

 

- 41 -

Fig. 2.2. Depth contours of (A) water temperature (℃), (B) soluble reactive phosphorus concentrations (SRP; μM P), and (C) bulk alkaline phosphatase activity (APA;

nM h^-1).

 

- 42 -

Fig. 2.3. Time series of (A) surface temperature and surface light intensity, (B) mixed layer depth, and (C) daily precipitation and typhoon impact index (★).

     

- 43 - Fig. 2.4. Time series of epilimnic (0-20m) and hypolimnic (20-90m) depth-integrated

averages of dissolved inorganic nitrogen (A; DIN), soluble reactive phosphorus concentrations (B; SRP), and epilimnion depth-integrated averages of the N/P ratios (C).

 

- 44 -  

 

2006 2007 2008 2009

J FM AM J J A S O N D J FM AM J J A S O N D J FM AM J J A S O N D J FM AM J J A S O N D

0.0 0.5 1.0 1.5 2.0 2.5

TP ( μM)

SRP

Fig. 2.5. Time series of total phosphate concentrations (TP) during 2006~2009. Data source from Taipei Feitsui Reservoir Administration Bureau.

                   

- 45 -

Fig. 2.6. The same as Fig. 2.5, but for epilimnic depth-integrated averages. (A) Chl a concentrations, (B) abundances of picocyanobacteria and bacteria, and (C) bulk APA and specific APA.

- 46 -  

   

0 20 40 60 80 100

Phytoplankton composition (%)

Others Pyrophyta Chlorophyta Bacillariophyta Cyanophyta

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D 2006 2007 2008 2009   Fig. 2.7. Time series of phytoplankton composition percentage (%) during the period of

Jan 2006~Nov 2007. Data source from the laboratory of Dr. Wo, Jiunn-Tzong, Biodiversity research center, Academia Sinica.

 

- 47 -  

15 20 25 30 35

Temperature (

^o

C)

0 2 4 6

AP A ( n M h

-1

)

2006 2007 2008 2009

Linear regression

Ln(APA) = ⁶0.08(Temp) + 1.56 ; r² = 0.23 (2006) Ln(APA) = ⁷0.11(Temp) + 0.54 ; r² = 0.22 (2007) Ln(APA) = ⁸0.14(Temp) - 0.25 ; r² = 0.34 (2008)

  Fig. 2.8. Scatter plots of Ln transformed bulk alkaline phosphatase activity vs.

temperature. Slopes were significant at p=0.05 level if shown. Superscripts 6~8 indicated slope of the given year was different from that of the other years by ANCOVA test (p<0.05).

 

- 48 -

Chapter 3

Temporal Variations of Alkaline Phosphatase Activity in Four Size Fractions

in a Subtropical Reservoir

- 49 -

Abstract

Temporal variations of APA in three particulate fractions (0.2~3 μm, 3~10 μm, and 10~100 μm; named as APApico, APAnano, and APAmicro, respectively) and dissolved fraction (<0.2 μm; APAdissol) were studied in a subtropical reservoir from 2006 to 2009.

The contribution of particulate fractions to bulk APA was high, varying 28~98% with a mean of 83±11%. Picoplankton APA (0.2~3 μm; APApico) was the major fraction (71±24%) of the particulate APA. 50% of the variation of bulk APA was determined by the changes of APApico. Multiple linear regression analysis indicated that APA (an index of P-deficient status of plankton) in different size fractions might be controlled by different mechanisms. APApico (an index of picoplankton P-deficiency) was related to the changes of mixed layer depth, light intensity, dissolved N/P ratio, and picocyanobacteria abundance. For APAnano and APAmicro (indices of nanoplankton and microplankton P-deficiency), dissolved inorganic nitrogen was the major controlling factor. APAdissol showed no relationship with any environmental factor.

- 50 -

3.1 Introduction

In Chapter 2, it was demonstrated that the plankton of the study-site were subjected to P-deficiency. Their seasonal growth was either “critically” or “severely” limited by P-availability. Because the plankton community is composed of living organisms with different sizes (picoplankton, nanoplankton, and microplankton…etc) and functions (autotrophy, heterotrophy, and mixotrophy…etc), it is of interest to know whether plankton in different size categories respond equally to P-deficiency. Studies indicated that APA of algal community were enhanced when extracellular or intracellular phosphate concentrations were low (Kruskopf & Du Plessis 2004, Ivancic et al. 2009), while repression of APA occurred under high phosphate concentrations (Robarts et al.

1998, Labry et al. 2005, Tanaka et al. 2006). In contrast, heterotrophic bacteria could maintain their high APA at high phosphate concentrations (Chrost & Overbeck 1987, Jamet et al. 1997). It is suspected that APA (an index of P-deficiency of plankton) in different size categories might respond differently at the same P-status.

Bulk APA consists of particulate and dissolved fractions. Phytoplankton, bacterioplankton, protozoans, and even zooplankton are the potential contributors of the former. The dissolved fraction may come from biogenic processes including release/excretion of cell surface phosphatases and zooplankton grazing …etc (Jansson et

al. 1988). The origins of APA in aquatic ecosystems could be quite diverse, and have

not been fully identified. For instance, the APA in mesotrophic Lake Erken of Sweden was mainly particulate (Pettersson 1980), while in oligotrophic Michigan lakes, >50%

of the bulk APA was dissolved (Stewart & Wetzel 1982). Furthermore, it has been suggested that APA could be a function of plankton composition (Chrost & Overbeck 1987, Vrba et al. 1993, Dyhrman & Ruttenberg 2006, Cao et al. 2010), and/or related to the trophic status of lakes (Olsson 1990). Berman (1970) found that phytoplankton

- 51 -

(dinoflagellate) were the significant contributors to bulk APA during bloom events occurred in Lake Kinneret, Israel. Whereas Stewart and Wetzel (1982) attributed all APA to bacteria. Seasonality effects have been reported by Chrost & Overbeck (1987) showing that ~50% of bulk APA could be attributed to phytoplankton during the period of spring to autumn, while bacteria contributed 45% of bulk APA in winter.

In this study, temporal variations of APA in four size fractions namely dissolved (<0.2 μm), pico (0.2~3 μm), nano (3~10 μm), and micro (10~100 μm) were identified.

The relationships of these four components with environmental factors and their relative contributions to bulk APA were analyzed.

- 52 -

3.2 Materials and methods 3.2.1 Study site and sampling

The geographical properties of the study site (Feitsui Reservoir), sampling frequency and period at the dam-site were described in Chapter 2.

3.2.2 Physical and chemical factors

The methods for physical (temperature, light intensity, and MLD), chemical (DIN and SRP), and biological (abundance of picocyanobacteria and bacteria) factors determination can be inferred from Chapter 2.

3.2.3 Size-fractionation of chlorophyll a

Water samples from 2 m depth of the dam-site were filtered sequentially through 10-μm, 3-μm, and 0.2-μm polycarbonate filters (dia., 47-mm). Duplicate filters of each size fraction were used for chlorophyll a determination using a fluorometer (Turner Designs, TD-700). See also Chapter 2 for details.

3.2.4 Size-fractionation of alkaline phosphatase activity (APA)

Water samples at the five depths (0, 2, 5, 10, 15, and 20 m) within the epilimnion were pre-filtered through a 100-μm mesh to remove larger organisms. The filtrates then were filtered sequentially through 10-μm, 3-μm, and 0.2-μm polycarbonate filters under low pressure (<100 mmHg). Alkaline phosphatase activity (APA) derived from the 10~100 μm, 3~10 μm, 0.2~3 μm, and <0.2 μm filtrate fractions were defined as microplankton APA (APAmicro), nanoplankton APA (APAnano), picoplankton APA (APApico), and dissolved APA (APAdissol), respectively. Bulk APA was the sum of the four above mentioned size fractions. Triplicate APA measurement was performed immediately after samples collection. See also Chapter 2 for the details of the APA method.

- 53 -

3.2.5 Statistical analysis

Statistical analyses including linear correlation analysis, multiple linear regression analysis, and one-way ANOVA were performed using the statistical software SPSS 12.0^TM.

- 54 -

3.3 Results

3.3.1 Temporal variations of size-fractionated Chl a and APA

Temporal variations of physical, chemical, and biological measurements were shown in Chapter 2. Bulk chlorophyll a (Chl a) concentrations (Fig. 3.1; range, 0.5~9.7 μg L^-1; mean, 2.4±1.2 μg L^-1) varied seasonally, and basically followed the trend of temperature (Table 2.1, r = 0.23, n = 171, p <0.01). Spring blooms hardly occurred while autumn blooms were significant as indicated by the high Chl a concentrations (>6 μg L^-1) recorded in Oct 2006 and Oct 2007. In term of relative contribution, pico-phytoplankton were the major contributor of the bulk Chl a in winter and spring (i.e.

Chlpico, ranged 30~68%, mean 55±14%), and then decreased in summer and autumn (ranged 22~46%, mean 33±11%). In autumn, bulk Chl a was dominated by nano- and micro-phytoplankton (i.e. Chlnano and Chlmicro), together they contributed 55~77% of the bulk Chl a, with a mean of 67±10%. Overall, phytoplankton biomass in cold seasons (winter and spring) was dominated by pico-phytoplankton. The system turned to be nano- and micro-phytoplankton dominated during warm seasons (summer and autumn).

Seasonal patterns of APA values of the four different size fractions were not clear except APApico, which showed a positive and a negative correlation with light and mixed layer depth, respectively (Table 3.1). Noticeable inter-annual difference was observed between the first two years (2006 and 2007) and the last two years (2008 and 2009), with a clear cutoff occurring in Nov 2007 (Fig. 3.2, Table 3.3). During the first two years, APAmicro and APAnano together contributed >40% to bulk APA, while APApico

contributed 39±11% to bulk APA. During 2008 and 2009, three-fourth (74±11%) of bulk APA came from APApico, while APAmicro and APAnano together constituted <5% of bulk APA. The contribution of APAdissol to bulk APA seemed to be constant with an average of 19±8% (Fig. 3.2, Table 3.3). Further analysis (Table 3.2) indicated that APA values in

- 55 -

all fractions changed simultaneously with bulk APA. And that the changes of bulk APA was primarily driven by the variation of APApico values, which had the highest regression coefficient (Beta = 0.80) among the three effective fractions. More specifically, it said that ~45% [0.80 / (0.33+0.40+0.80+0.24)] of bulk APA variation was determined by the changes of APApico.

The results of multiple linear regression analysis (Table 3.1) indicated that APAdissol

was not related to any environmental factors. 26% of the APAmicro variability could be explained by the combination of total dissolved inorganic nitrogen (DIN)and total Chl a.

The relative importance (Beta weight) of these two independent variables on APAmicro

were -0.27 for DIN and 0.39 for Chl

a. For APA

nano, the best-fit equation switched to DIN only, which explained 25% of the variation. The relative importance of environmental factors on APApico in order were -0.38 for mixed layer depth, 0.34 for light intensity, 0.23 for N/P ratio and 0.18 for CYA abundance. Together, these factors explained 51% of the variation. Bacterial abundance (and biomass) had no correlation with APApico. The variation of biomass normalized APApico (SAPApico) could be explained by a combination of light (Beta = 0.33), mixed layer depth (Beta = -0.31), and phosphate concentrations (Beta = -0.20).

- 56 -

3.4 Discussion

In aquatic systems, the origins of APA could be quite diverse, and the regulation mechanisms of APA could be different among plankton community with different size.

Using the cascading filtration method, it was estimated that most APA in the study site was in particulate form (82±8%), and APApico accounted for the major portion (70±25%) of the particulate APA. The APAnano and APAmicro to the bulk APA varied (0~87%) highly. The contribution of APAdissol remained low (<20%). The proportions of size-fractionated APA in this study are comparable with ranges reported in the literatures. For instance, Pick (1987) found most particulate APA in Lake Ontario associated with <5 μm particles (Pico-fraction). Berman et al. (1970) also measured a wide range (<5~70%) of >20 μm (micro-fraction) particulate activity in oligotrophic Lake Kinneret of Israel. In addition, Newman and Reddy (1993) evaluated dissolved APA only contributed less than 10% of the bulk activity in a hypertrophic reservoir. Bulk APA co-varied with the four fractions except APAmicro, and its variation was majorly determined by APApico (Table 3.2). This indicated that plankton of smaller size could be more powerful than larger organisms in determining system’s P-status. The same result was found in a subtropical system (Lil et al. 1998).

The results further indicated that the four APA size fractions might be regulated by different controlling mechanisms in this system (Table 3.1). Mixed layer depth (MLD), light intensity, N/P ratio, and picocyanobacteria abundance were the most four important factors in controlling the variation of APApico. However, for micro- and nano-fractions, DIN concentration was the most important factor controlling their variations. It is suggested that phosphate availability (as inferred from MLD) and light availability might alleviate and aggravate the P-stress of picoplankton, respectively.

However, all three particulate fractions (APAmicro, APAnano, and APApico) were more or

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less independent of phosphate concentrations. This was in consistence with the finding by Jamet et al. (1997) showing that the APA was independent of phosphate concentrations in the oligomesotrophic Lake Pavin, France. According to the results, he suggested that in an extreme P-deficient system (phosphate concentrations were closed to detection limit), constitutive (always exist and active) and repressible APA could coexist and therefore a negative correlation between APA and phosphate concentrations might be diminish.

Nutrient status (i.e. the N/P ratio) caused dramatic shift of plankton community structure has been reported in many literatures (for review, see Wetzel, 2001). However, the relation between nutrient status and the composition of size-fractionated APA has rarely been discussed. This study demonstrated apparent inter-annual changes of APA in different size-fractions (Fig. 3.2 and Table 3.3). Before Nov 2007, APApico contributed

~50% to particulate APA, but such contribution increased up to 90% afterwards. This dramatically change was coincided with a shift of N/P ratio before and after Nov 2007 (Table 3.3). The dramatic increases of N/P ratios in 2008 and 2009 were due to higher DIN (Chapter 2, Fig. 2.4A) in these two years.

Several studies suggested that high DIN concentrations (and high N/P ratio) would make the system to be more P-deficit, which might enhance the activities of plankton

Several studies suggested that high DIN concentrations (and high N/P ratio) would make the system to be more P-deficit, which might enhance the activities of plankton

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