Abstract

The potential of an express enzymological indicator – phosphatase activity index (PAI) – for assessment of different types of pollution and self-purification potential in running waters was evaluated for three river subcatchments, representative for different ecological situations and impacts. According to the values of correlation coefficients, a significant positive correlation existed among PAI and total microbial count, organic loading and phosphate concentrations. The enzyme activity is useful tool for early identification of risks from point discharge of different wastewaters (treated or non-treated). The role of PAI as an indicator is significant at case of disinfection after treatment of wastewaters in treatment plant – the aquatic microbial community at the discharge point is suppressed but not at a functional level. The results allow classical microbiological and chemical parameters (state variables) to be related directly to the dynamics of the transformation processes by functional variable – PAI.

INTRODUCTION

The organic loading and nutrient-related pollution of inland waters are global ecological problems with high risk level for non-achievement of criteria for good ecological state of surface waters according to environmental legislation (Sutton et al. 2013; Bouraoui et al. 2014). Despite that the field of pollution indication is well-developed for surface waters and variety of indicators is widely used, there is a deficit in early identification of risk situations by function indicators directly related to the pollutants fate and main transformation processes in the ecosystem. The imperative step for prevention, control and effective management of pollution is an application of system of early warning indicators for assessment of type and degree of organic and nutrient loading, and further revealing the self-purification capacity of ecosystem.

The existing network of different transformation processes of pollutants is an essential element for natural improvement of the quality of waters and maintenance of a healthy ecosystem. A leading biotic factor in these processes is the realization of biodegradation, mineralization and nutrient cycling from aquatic microbial assemblages (Hill et al. 2012). Due to their wide polyenzymatic profile and flexible adaptation to different physicochemical conditions and substrates, microorganisms respond quickly to organic/nutrient loading fluctuation, primary by changing the level of their enzyme activities (Dao 2011). The focus on enzyme activities as suitable indicators for the level of pollution and self-purification comes from the fact that heterotrophic microorganisms produce a wide range of extracellular enzymes to cleave their target substrates outside the cell to sizes small enough for uptake (Ziervogel et al. 2012; Arnosti et al. 2014). These complex enzyme activities of microbial populations determine the functionality and give the information for the mechanisms and rate of metabolic processes on ecosystem level. Extracellular phosphatases (enzymes that hydrolyze phosphate groups from a wide variety of organic substrates) are a significant component of most algae and bacteria and play an essential role in the recycling of P-containing organic matter. Phosphatases seem to be inducible catabolic ectoenzymes, as are most other hydrolytic ectoenzymes of aquatic microorganisms (Hoppe 2003). Activity of these extracellular enzymes are therefore a good measure for the initial step of carbon cycling in natural microbial assemblages (Arnosti 2011), and are used as indicators of heterotrophic microbial function in contaminated different types of waters, soils and sediments (Duarte et al. 2012; Sanchez-Hernandez et al. 2017). Phosphatase activities are considered to exist in every aquatic systems, soils and sediments as integral parts of complex enzyme profile and give information about effect of nutrients, organics and pollutants concentration on microbial activities (Chróst & Siuda 2002; Arnosti 2003; Wilczek et al. 2005). Bacterial extracellular enzymatic activity is regulated at the ecosystem level by environmental factors and at the microenvironment level by enzyme-substrate interactions (Cunha et al. 2010).

The previous studies found and validated the positive correlation between activity of phosphatase enzymes and chlorophyll concentration, viable bacterial count, total phosphate concentration, inorganic phosphate concentration, and temperature. The phosphatase activities are applicable to estimation of organic pollution, phosphorus limitation, eutrophication processes (Matavulj et al. 1990; Chróst 1991; Boavida et al. 1997; Hill et al. 2012) and hazardous pollution in soils and sediments (Todorova et al. 2016; Sanchez-Hernandez et al. 2017). But the potential of this indicator was not exploited from the aspect of dynamics and effectiveness of self-purification processes. The aim of this study is to apply and evaluate the complex enzyme indicator – phosphatase activity index (PAI) – for assessment of functional microbial response and self-purification effectiveness at different types of pollution in running waters.

MATERIALS AND METHODS

Experimental design and description of selected case studies

For assessment and verification of the potential of phosphatase activities as a functional indicator, the research strategy was extended on large spatial scale and investigations were carried out at three different river subcatchments representative for different ecological situations, types of pollution and impact. The river sectors belong to Iskar River and Ogosta River catchments (both from Danube basin). Study areas are shown on Figure 1.

Figure 1

Location of studied river subcatchments: 1 –Upper Iskar (UI), 2 – Middle Iskar (MI), 3 – Leva River (L).

Figure 1

Location of studied river subcatchments: 1 –Upper Iskar (UI), 2 – Middle Iskar (MI), 3 – Leva River (L).

The first river subcatchment studied (UI) was the upper part of Iskar River and its tributaries before Iskar Dam. This part of the river experiences low level of anthropogenic impact and good ecological/chemical state of surface waters. Only the Palakariya River tributary had a possible risk for pollution with organics and nutrients (Todorova & Topalova 2014). One point source of pollution – discharge of municipal wastewater treatment plant (WWTP) of a small town was registered in this sector.

The second studied sector (MI) was in the middle part of the Iskar River with a high level of different impacts – hydromorphological deterioration and pollution with organics, nutrients and xenobiotics (poor ecological state). This part of the river is a long-term receptor of treated and non-treated urban and industrial sewage from the Sofia area (capital of Bulgaria) and the pollution results in contamination of waters and sediments. In the same time, the construction of the Middle Iskar Cascade of 9 small hydro power plants (SHHP) with barrages and power stations has been started since the 2000's. Flow regulation combined with other anthropogenic impacts deepen the environmental and technological problems in the lotic ecosystem (Todorova et al. 2014; Todorova et al. 2016).

The third river sector was part of the Leva River (L) near to town of Vratsa with specific point pollution from the dairy industry, combined with discharge of non-treated municipal wastewaters from nearby villages and intensive agriculture activities (moderate ecological state in the whole sector and very poor in the zone of discharge) (Schneider & Topalova 2009).

The assessment of significant environmental risks categorizes the Upper Iskar subcatchment as ‘not in risk’ and as ‘potential risk’; the river sectors of Middle Iskar and Leva River are ‘in risk’ from organics, nutrients and hazardous substances.

The sampling strategy with periods, sampling sites, number of samples and a brief description of sites is given in Table 1.

Table 1

Sampling details for the three case studies: Upper Iskar (UI), Middle Iskar (MI) and Leva River (L)

Case study Sampling period Sampling scale Sampling sites; number of samples Codes and descriptions of sites 
Upper Iskar (UI) Winter and summer low flow periods of 2004 Large – subcatchment 10 sites (7 at main stream and 3 at tributaries); 20 samples UI1 – Beli Iskar River upstream of village Beli Iskar 
UI2 – Beli Iskar River downstream of village Beli Iskar 
UI3a – Cherni Iskar River below Govedarci 
UI3 – at confluence of Beli and Cherni Iskar 
UI4a – Borovishka Bistrica River 
UI4 – below Samokov and its WWTP 
UI5 – near the village of Dragoshinovo 
UI6 – before inflow of Palakariya River 
UI7a – Palakariya River 
UI7 – before Iskar Dam 
Middle Iskar (MI) Summer low and spring high flow periods of 2013–2014 Medium - 33 km sector 4 sites; 16 samples MI1 – at Prokopanik below Sofia, before the Middle Iskar cascade and Svoge 
MI2 – at Cerovo below Svoge and SHPP Cerovo 
MI3 – at Lakatnik, before SHPP Lakatnik 
MI4 – at Gabrovnitza, below the cascade 
Leva River Summer low flow of 2008 Small < 1 km 5 sites; 5 samples L1 – before the dairy wastewaters discharge 
L1a – in the area of water mixing 
L2 – 5 m after discharge 
L3 – 50 m after discharge 
L4 – 100 m after discharge 
Case study Sampling period Sampling scale Sampling sites; number of samples Codes and descriptions of sites 
Upper Iskar (UI) Winter and summer low flow periods of 2004 Large – subcatchment 10 sites (7 at main stream and 3 at tributaries); 20 samples UI1 – Beli Iskar River upstream of village Beli Iskar 
UI2 – Beli Iskar River downstream of village Beli Iskar 
UI3a – Cherni Iskar River below Govedarci 
UI3 – at confluence of Beli and Cherni Iskar 
UI4a – Borovishka Bistrica River 
UI4 – below Samokov and its WWTP 
UI5 – near the village of Dragoshinovo 
UI6 – before inflow of Palakariya River 
UI7a – Palakariya River 
UI7 – before Iskar Dam 
Middle Iskar (MI) Summer low and spring high flow periods of 2013–2014 Medium - 33 km sector 4 sites; 16 samples MI1 – at Prokopanik below Sofia, before the Middle Iskar cascade and Svoge 
MI2 – at Cerovo below Svoge and SHPP Cerovo 
MI3 – at Lakatnik, before SHPP Lakatnik 
MI4 – at Gabrovnitza, below the cascade 
Leva River Summer low flow of 2008 Small < 1 km 5 sites; 5 samples L1 – before the dairy wastewaters discharge 
L1a – in the area of water mixing 
L2 – 5 m after discharge 
L3 – 50 m after discharge 
L4 – 100 m after discharge 

The analyses of three groups of indicators were included in the experimental design:

  • (1)

    Water quality parameters for assessment of organics and nutrients loading at sampling sites – gives information about the ‘substrates and products’ of biotransformation processes;

  • (2)

    Total microbial count (TMC) as the most frequently used monitoring parameter for the structural and functional state of microbial assemblage – information for the ‘biotic factor’ of self-purification;

  • (3)

    Index of phosphatase activities measured as a total activity – indicator for the functioning of the microbial community and the realization of transformation processes on the enzyme level.

Sampling and analytic procedures

Water samples were collected, transferred into bottles or sterile containers, stored (at 4°C) and processed within 4 hours. The physicochemical parameters (temperature, oxygen concentration, and pH) of water have been analyzed in situ immediately after sampling with portable Oxy-meter Handylab Ox1/set and pH-meter Handylab pH11/set (Schott Instruments, Germany).

After transfer to the laboratory, the samples were analyzed in triplicate for determination of COD (Chemical Oxygen Demand – dichromatic ЕPA 410.4/ISO 6060 method). The ammonium, nitrate and phosphate concentrations were measured after filtering of the samples (pore size 0.45 μm) and by colorimetric methods according to the BNS-EN-ISO standards. The TMC (CFU mL−1) was determined by the use of count-plate technique on Nutrient agar for 24–48 h at 35°С.

PAI was determined as an average value of activities of acidic, neutral and alkaline phosphatases. The method was based on transformation of p-nitrophenolphosphate (Matavulj & Flint 1987).

The data were means of three or more repeats with associated standard deviations. A Spearman correlation was used to investigate the relationships between the enzyme activity and other indicators.

RESULTS AND DISCUSSION

Case study of Upper Iskar subcatchment

The organic content and phosphate concentrations in the surface waters of Upper Iskar subcatchment were the highest in site UI4 for both seasons (Figure 2). This site was situated immediately downstream the WWTP discharge point. The high nitrogen concentrations, especially ammonium, also indicated typical pollution from municipal wastewater (Table 2). But the microbial count at this site was low – less than 1,000 CFU mL−1 comparable to a mountain zone. The microbial community in UI4 site was affected by the disinfection of treated wastewaters in WWTP – near the discharge the bacteria were inhibited by the disinfectants. In the next site (only 500 m downstream) the microbial count was the highest during both seasons – the structural microbial parameters reacted to the high nutrient and organic content in the surface waters but with a replacement downstream. At site UI5 the dissolved oxygen was lower and corresponded to the high microbial activity and intensive aerobic transformation processes. But the PAI had a different dynamics that strictly followed the variations of organic substrate and phosphate concentrations – the highest values, 39.957 ± 12.034 and 30.358 ± 17.550 μM pNPP min−1L−1, were measured at the discharge of the WWTP during the winter and summer low flow seasons (Figure 3). The biota responded to high organic content primarily on the functional level with an increase of extracellular enzyme activities. This express self-purification reaction of hydroecosystem on the enzyme level was attendant with the slow change of the microbial count and a delayed response on the population level. At the discharge of the WWTP the less adaptive microorganisms were eliminated from the community structure while the remaining exhibited high biotransformation potential and an intensified enzyme profile. These high adaptive bacteria realized the first reaction of biocenose and their effective functioning eliminated the initial high organics concentration. The PAI was a better indicator than microbial count for this type of risk situation – discharge of treated disinfected wastewaters in a clean ecosystem.

Table 2

Basic chemical parameters of waters in the Upper Iskar subcatchment

Site UI1 UI2 UI3a UI3 UI4a UI4 UI5 UI6 UI7a UI7 
рН 
 Winter 6.98 7.07 7.40 7.22 7.60 7.50 7.57 7.99 7.56 7.61 
 Summer 7.15 7.28 7.45 7.49 7.96 7.07 7.53 7.32 7.62 7.78 
Oxygen, mL−1 
 Winter 11.21 11.40 11.51 11.87 11.79 11.63 8.23 11.50 11.43 11.21 
 Summer 8.33 7.56 8.25 8.61 8.04 8.20 8.13 7.82 8.75 8.40 
N-NO3, mL−1 
 Winter 0.299 1.801 1.419 1.394 0.986 1.928 1.394 1.126 1.572 1.884 
 Summer 0.031 0.050 0.025 0.031 0.038 0.064 0.063 0.089 0.076 0.095 
N-NH4, mL−1 
 Winter 0.107 0.143 0.143 0.173 0.891 2.988 0.450 0.373 0.430 0.432 
 Summer 0.017 0.083 0.120 0.191 0.222 2.004 0.300 0.463 0.162 0.258 
Site UI1 UI2 UI3a UI3 UI4a UI4 UI5 UI6 UI7a UI7 
рН 
 Winter 6.98 7.07 7.40 7.22 7.60 7.50 7.57 7.99 7.56 7.61 
 Summer 7.15 7.28 7.45 7.49 7.96 7.07 7.53 7.32 7.62 7.78 
Oxygen, mL−1 
 Winter 11.21 11.40 11.51 11.87 11.79 11.63 8.23 11.50 11.43 11.21 
 Summer 8.33 7.56 8.25 8.61 8.04 8.20 8.13 7.82 8.75 8.40 
N-NO3, mL−1 
 Winter 0.299 1.801 1.419 1.394 0.986 1.928 1.394 1.126 1.572 1.884 
 Summer 0.031 0.050 0.025 0.031 0.038 0.064 0.063 0.089 0.076 0.095 
N-NH4, mL−1 
 Winter 0.107 0.143 0.143 0.173 0.891 2.988 0.450 0.373 0.430 0.432 
 Summer 0.017 0.083 0.120 0.191 0.222 2.004 0.300 0.463 0.162 0.258 
Figure 2

Dynamics of phosphate concentration, organic content (COD) and total microbial count (TMC) in waters of the Upper Iskar subcatchment.

Figure 2

Dynamics of phosphate concentration, organic content (COD) and total microbial count (TMC) in waters of the Upper Iskar subcatchment.

Figure 3

Phosphatase Activity Index (PAI) in waters of the Upper Iskar subcatchment.

Figure 3

Phosphatase Activity Index (PAI) in waters of the Upper Iskar subcatchment.

Case study of Middle Iskar cascade

The organic content of surface waters in Middle Iskar cascade measured as COD was low (under 15 mg O2 L−1) without large spatial and seasonal variations (Figure 4). This part of the river was also affected by the discharge of one large WWTP but the effect of treated wastewaters was not clearly presented because of the 30 km distance. In the river sector there are many other nonpoint sources of pollution – villages without sewages, intensive agriculture and this mixed type of pollution was reflected in the nitrogen and phosphorus dynamics (Table 3 and Figure 4). The measured concentrations were high and indicated a serious nutrient loading on surface waters. The microbial community was also presented with high abundance from 3,000 to 50,000 CFU mL−1 (Figure 4). The high microbial count was potentially related to intensive bacterial activity and high rates of main transformation processes. At the same time, the construction of the SHPP cascade based on modification of stream hydraulics and dam compartmentalization of the river channel, created an additional system for retention of nutrients and fast utilization of easy biodegradable organic substrates.

Table 3

Basic chemical parameters of waters in the Middle Iskar River sector

Site MI1 MI2 MI3 MI4 
рН 
 Spring'13 7.45 nd 7.68 7.61 
 Summer'13 7.72 7.73 7.97 8.21 
 Spring'14 7.47 7.34 7.71 7.86 
 Summer'14 7.38 7.65 7.76 7.60 
Oxygen, mL−1 
 Spring'13 7.45 no data (nd) 9.50 9.34 
 Summer'13 7.50 7.06 9.93 9.94 
 Spring'14 7.20 7.31 7.84 7.20 
 Summer'14 8.70 11.52 10.32 9.40 
N-NO3, mL−1 
 Spring'13 0.922 nd 2.195 3.080 
 Summer'13 2.737 3.055 4.538 4.958 
 Spring'14 1.142 2.423 3.006 3.493 
 Summer'14 3.508 3.042 3.144 2.860 
N-NH4, mL−1 
 Spring'13 1.143 nd 0.461 0.362 
 Summer'13 4.184 3.153 1.363 0.796 
 Spring'14 0.222 0.656 0.336 0.276 
 Summer'14 1.223 0.800 0.529 0.324 
Site MI1 MI2 MI3 MI4 
рН 
 Spring'13 7.45 nd 7.68 7.61 
 Summer'13 7.72 7.73 7.97 8.21 
 Spring'14 7.47 7.34 7.71 7.86 
 Summer'14 7.38 7.65 7.76 7.60 
Oxygen, mL−1 
 Spring'13 7.45 no data (nd) 9.50 9.34 
 Summer'13 7.50 7.06 9.93 9.94 
 Spring'14 7.20 7.31 7.84 7.20 
 Summer'14 8.70 11.52 10.32 9.40 
N-NO3, mL−1 
 Spring'13 0.922 nd 2.195 3.080 
 Summer'13 2.737 3.055 4.538 4.958 
 Spring'14 1.142 2.423 3.006 3.493 
 Summer'14 3.508 3.042 3.144 2.860 
N-NH4, mL−1 
 Spring'13 1.143 nd 0.461 0.362 
 Summer'13 4.184 3.153 1.363 0.796 
 Spring'14 0.222 0.656 0.336 0.276 
 Summer'14 1.223 0.800 0.529 0.324 
Figure 4

Dynamics of phosphate concentration, organic content (COD) and total microbial count (TMC) in waters of the Middle Iskar cascade.

Figure 4

Dynamics of phosphate concentration, organic content (COD) and total microbial count (TMC) in waters of the Middle Iskar cascade.

In this type of pollution, the PAI was well presented – 12.46 to 51.17 μM pNPP min−1L−1 and this showed intensive transformation processes of P-containing organics and good self-purification capacity of the ecosystem (Figure 5). The spatial variations of PAI followed the change of microbial count and phosphate concentration.

Figure 5

Phosphatase Activity Index (PAI) in waters of Middle Iskar cascade.

Figure 5

Phosphatase Activity Index (PAI) in waters of Middle Iskar cascade.

Case study of the Leva River

The third case study – a sector of the Leva River was affected by the discharge of untreated dairy wastewaters. At the first unaffected sampling site, the bacterial abundance, phosphates and organics were very low – indicating a good ecological state of the ecosystem and clean surface waters. At the point of discharge (site L1a), the chemical and microbial parameters had typical dynamics for this type of pollution and the values of COD, nutrients, microbial count increased very extremely (Table 4, Figure 6). TMC values were more than 1,000 times higher, COD – 30 times, phosphates – 5 times compared to the values at site L1. The PAI also increased more than 1,000 times and the value in surface waters of site L1a was 3,390.27 ± 106.01 μM pNPP min−1L−1 (Figure 7). Only 5 m further downstream from the wastewater discharge, the all studied parameters decreased sharply. This indicates a rapid elimination and utilization of organic pollution, adequate functional response of ecosystem and high effectiveness of self-purification processes.

Table 4

Basic chemical parameters of waters in the Leva River

  L1 L1a L2 L3 L4 
рН 7.78 6.98 7.65 6.98 7.56 
Oxygen, mL−1 7.8 6.7 7.5 5.7 7.9 
N-NO3, mL−1 0.852 0.531 0.768 0.596 0.382 
N-NH4, mL−1 0.148 2.731 0.525 1.071 0.422 
  L1 L1a L2 L3 L4 
рН 7.78 6.98 7.65 6.98 7.56 
Oxygen, mL−1 7.8 6.7 7.5 5.7 7.9 
N-NO3, mL−1 0.852 0.531 0.768 0.596 0.382 
N-NH4, mL−1 0.148 2.731 0.525 1.071 0.422 
Figure 6

Dynamics of phosphate concentration, organic content (COD) and total microbial count (TMC) in the Leva River.

Figure 6

Dynamics of phosphate concentration, organic content (COD) and total microbial count (TMC) in the Leva River.

Figure 7

Phosphatase Activity Index (PAI) in the Leva River.

Figure 7

Phosphatase Activity Index (PAI) in the Leva River.

Relations between pollution indicators

Phosphatases are essential ectoenzymes for realization of P cycling in aquatic environment, take part in mineralization of organic P and release phosphates for macrophytes and algae. This functional role determines the direct relationships of the enzyme activity with the concentration of organics (substrate) and phosphates in the system (product from the enzyme reaction). The analysis of relationships between parameters was done for any particular case and for the all data set (Table 5). PAI correlates positively with high statistical significance with TMC, organic loading and phosphates concentration in all cases studied. The correlation coefficients for the entire data set are rPAI/TMC = 0.973; rPAI/COD = 0.985; rPAI/PO4 = 0.624 respectively. The positive correlation with phosphates is stronger in the Upper Iskar subcatchment – r = 0.790. Berman & Moses (1972) specified three available sources of phosphates in surface waters: (1) ortho-phosphates released from ectoenzymes; (2) intracellular microbial reserves; and (3) inorganic phosphates incoming in waters from pollution. The first source is the most important in clean waters with phosphorus limitation as in the case of the mountainous upper parts of the rivers. Many authors determined an inverse or no correlation between phosphatase activity and phosphates but in lakes and seas where the dominant producers of extracellular phosphatases are algae and the enzyme synthesis is a response to low orthophosphate in the environment and phosphorus competition (Nausch 1998; Wetzel 2001). For the dominant bacterial metabolism phosphatases is produced in response to organic carbon limitation rather than phosphate limitation (Chróst 1991).

Table 5

Spearman correlation matrix between parameters (values are different from 0 with significance level = 0.05)

  PAI – Upper Iskar PAI – Middle Iskar PAI – Leva Iskar Total data set 
TMC 0.638 0.616 0.969 0.973 
COD 0.684 0.788 0.993 0.985 
PO43− 0.790 0.697 0.725 0.642 
  PAI – Upper Iskar PAI – Middle Iskar PAI – Leva Iskar Total data set 
TMC 0.638 0.616 0.969 0.973 
COD 0.684 0.788 0.993 0.985 
PO43− 0.790 0.697 0.725 0.642 

CONCLUSIONS

The indicative potential of phosphatases was widely used in past two decades for estimation of eutrophication processes, nutrient limitation, organic pollution in small ponds, fishponds, lakes, soils, streams. The analyses of these enzyme activities have been part of complex assessment of biotic integrity in aquatic ecosystems based on periphyton assemblages and data have been collected for many US streams (Hill et al. 2003). In Europe, the indicator has been applied successfully for assessment of water quality and as an additional parameter for categorization of surface waters in some parts of Danube's watershed. Our study expands the possible use of phosphatases as functional indicator with high potential for differentiation of type and degree of organic pollution and for self-purification effectiveness. This enzyme activity is useful tool for early identification of risks from point discharge of different wastewaters (treated or non-treated) and for additional assessment of organic and nutrient loading in running waters. The role of PAI as an indicator is significant for the case of disinfection after treatment of wastewaters in WWTP the aquatic microbial community at discharge points is suppressed but not on the functional level. The results allow classical microbiological and chemical parameters (state variables) to be related directly to the dynamics of the transformation processes by sensitive enzyme indicator PAI (functional variable).

ACKNOWLEDGEMENT

The authors gratefully acknowledge the PVB Power Bulgaria and VEC Svoge for their long-standing support. The authors thank L. Kenderov, PhD and E. Daskalova for their valuable contribution for this work. Comments by the anonymous reviewer also improve the presentation of this paper and we are very grateful for careful reading and useful suggestions.

REFERENCES

REFERENCES
Arnosti
,
C.
2003
Microbial extracellular enzymes and their role in dissolved organic matter cycling
. In:
Aquatic Ecosystems: Interactivity of Dissolved Organic Matter
(
Sinsabaugh
,
R. L.
ed.).
Academic Press
,
San Diego
,
USA
, pp.
315
342
.
Arnosti
,
C.
2011
Microbial extracellular enzymes and the marine carbon cycle
.
Annual Review of Marine Science
3
,
401
425
.
Arnosti
,
C.
,
Bell
,
C.
,
Moorhead
,
D. L.
,
Sinsabaugh
,
R. L.
,
Steen
,
A. D.
,
Stromberger
,
M.
,
Wallenstein
,
M.
&
Weintraub
,
M. N.
2014
Extracellular enzymes in terrestrial, freshwater, and marine environments: perspectives on system variability and common research needs
.
Biogeochemistry
117
,
5
21
.
Boavida
,
M.-J.
,
Hamza
,
W.
,
Ruggiu
,
D.
&
Marques
,
R. T.
1997
Eutrophication: alkaline phosphatase revisited
.
Memorie Dell'Istituto Italiano Di Idrobiologia
56
,
15
21
.
Bouraoui
,
F.
,
Thieu
,
V.
,
Grizzetti
,
B.
,
Britz
,
W.
&
Bidoglio
,
G.
2014
Scenario analysis for nutrient emission reduction in the European inland waters
.
Environmental Research Letters
9
,
125007
.
Chróst
,
R. J.
1991
Microbial Enzymes in Aquatic Environments
.
Springer-Verlag
,
New York
.
Chróst
,
R. J.
,
Siuda
,
W.
2002
Ecology of microbial enzymes in lake ecosystems
. In:
Microbial Enzymes in the Environment Activity, Ecology and Applications
(
Burns
,
R. C.
&
Dick
,
R. P.
, eds).
Marcel Dekker Inc.
,
New York
, pp.
35
72
.
Cunha
,
A.
,
Almeida
,
A.
,
Coelho
,
F. J. R. C.
,
Gomes
,
N. C. M.
,
Oliveira
,
V.
&
Santos
,
A. L.
2010
Bacterial extracellular enzymatic activity in globally changing aquatic ecosystems
. In:
Current Research, Technology and Education Topics in Applied Microbiology and Microbial Biotechnology
(
Mendez-Vilas
,
A.
ed.).
Formatex Research Center
,
Badajoz
,
Spain
, pp.
124
135
.
Hill
,
B. H.
,
Herlihy
,
A. T.
,
Kaufmann
,
P. R.
,
DeCelles
,
S. J.
&
Vander Borgh
,
M. A.
2003
Assessment of streams of the eastern United States using a periphyton index of biotic integrity
.
Ecological Indicators
2
,
325
338
.
Hill
,
B. H.
,
Elonen
,
C. M.
,
Seifert
,
L. R.
,
May
,
A. A.
&
Tarquinio
,
E.
2012
Microbial enzyme stoichiometry and nutrient limitation in US streams and rivers
.
Ecological Indicators
18
,
540
551
.
Hoppe
,
H. G.
2003
Phosphatase activity in the sea
.
Hydrobiologia
493
,
187
200
.
Matavulj
,
M.
&
Flint
,
K. P.
1987
A model for acid and alkaline phosphatase activity in a small pond
.
Microbial Ecology
13
(
2
),
141
158
.
Matavulj
,
M.
,
Bokorov
,
M.
,
Gayin
,
S.
,
Gantar
,
M.
,
Stoyilkovicy
,
S.
&
Flint
,
K. P.
1990
Phosphatase activity of water as a monitoring parameter
.
Water Science & Technology
2
(
5
),
63
68
.
Sanchez-Hernandez
,
J. C.
,
Sandoval
,
M.
&
Pierart
,
A.
2017
Short-term response of soil enzyme activities in a chlorpyrifos-treated mesocosm: use of enzyme-based indexes
.
Ecological Indicators
73
,
525
535
.
Schneider
,
I.
&
Topalova
,
Y.
2009
Structural and functional changes in river microbial communities after dairy wastewater discharge
.
Biotechnology & Biotechnological Equipment
23
(
2
),
1210
1216
.
Sutton
,
M. A.
,
Bleeker
,
A.
,
Howard
,
C. M.
,
Bekunda
,
M.
,
Grizzetti
,
B.
,
de Vries
,
W.
,
van Grinsven
,
H. J. M.
,
Abrol
,
Y. P.
,
Adhya
,
T. K.
,
Billen
,
G.
,
Davidson
,
E. A.
,
Datta
,
A.
,
Diaz
,
R.
,
Erisman
,
J. W.
,
Liu
,
X. J.
,
Oenema
,
O.
,
Palm
,
C.
,
Raghuram
,
N.
,
Reis
,
S.
,
Scholz
,
R. W.
,
Sims
,
T.
,
Westhoek
,
H.
&
Zhang
,
F. S.
2013
Our nutrient world: the challenge to produce more food and energy with less pollution global overview of nutrient management
. In:
Centre for Ecology and Hydrology, Edinburgh on Behalf of the Global Partnership on Nutrient Management and the International Nitrogen Initiative 2013, Edinburgh, UK
.
Todorova
,
Y.
,
Lincheva
,
St.
&
Topalova
,
Y.
2014
Risk management scenario for multiple heavy metal contamination at river sediments in the Middle Iskar cascade
.
Bulgarian Journal of Agricultural Science
20
(
1
),
100
104
.
Todorova
,
Y.
,
Lincheva
,
S.
,
Yotinov
,
I.
&
Topalova
,
Y.
2016
Contamination and ecological risk assessment of long-term polluted sediments with heavy metals in small hydropower cascade
.
Water Resources Management
30
(
12
),
4171
4184
.
Wetzel
,
R. G.
2001
Limnology: Lake and River Ecosystems
.
Academic Press
,
San Diego
,
USA
.
Ziervogel
,
K.
,
McKay
,
L.
,
Rhodes
,
B.
,
Osburn
,
C. L.
,
Dickson-Brown
,
J.
,
Arnosti
,
C.
&
Teske
,
A.
2012
Microbial activities and dissolved organic matter dynamics in oil-contaminated surface seawater from the Deepwater Horizon oil spill site
.
PLoSONE
7
(
4
),
e34816
.
doi:10.1371/journal.pone.0034816
.