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Keywords:

  • fish;
  • macrophytes;
  • nutrient;
  • oligotrophication;
  • plankton;
  • resilience

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices

1. This synthesis examines 35 long-term (5–35 years, mean: 16 years) lake re-oligotrophication studies. It covers lakes ranging from shallow (mean depth <5 m and/or polymictic) to deep (mean depth up to 177 m), oligotrophic to hypertrophic (summer mean total phosphorus concentration from 7.5 to 3500 μg L−1 before loading reduction), subtropical to temperate (latitude: 28–65°), and lowland to upland (altitude: 0–481 m). Shallow north-temperate lakes were most abundant.

2. Reduction of external total phosphorus (TP) loading resulted in lower in-lake TP concentration, lower chlorophyll a (chl a) concentration and higher Secchi depth in most lakes. Internal loading delayed the recovery, but in most lakes a new equilibrium for TP was reached after 10–15 years, which was only marginally influenced by the hydraulic retention time of the lakes. With decreasing TP concentration, the concentration of soluble reactive phosphorus (SRP) also declined substantially.

3. Decreases (if any) in total nitrogen (TN) loading were lower than for TP in most lakes. As a result, the TN : TP ratio in lake water increased in 80% of the lakes. In lakes where the TN loading was reduced, the annual mean in-lake TN concentration responded rapidly. Concentrations largely followed predictions derived from an empirical model developed earlier for Danish lakes, which includes external TN loading, hydraulic retention time and mean depth as explanatory variables.

4. Phytoplankton clearly responded to reduced nutrient loading, mainly reflecting declining TP concentrations. Declines in phytoplankton biomass were accompanied by shifts in community structure. In deep lakes, chrysophytes and dinophytes assumed greater importance at the expense of cyanobacteria. Diatoms, cryptophytes and chrysophytes became more dominant in shallow lakes, while no significant change was seen for cyanobacteria.

5. The observed declines in phytoplankton biomass and chl a may have been further augmented by enhanced zooplankton grazing, as indicated by increases in the zooplankton : phytoplankton biomass ratio and declines in the chl a : TP ratio at a summer mean TP concentration of <100–150 μg L−1. This effect was strongest in shallow lakes. This implies potentially higher rates of zooplankton grazing and may be ascribed to the observed large changes in fish community structure and biomass with decreasing TP contribution. In 82% of the lakes for which data on fish are available, fish biomass declined with TP. The percentage of piscivores increased in 80% of those lakes and often a shift occurred towards dominance by fish species characteristic of less eutrophic waters.

6. Data on macrophytes were available only for a small subsample of lakes. In several of those lakes, abundance, coverage, plant volume inhabited or depth distribution of submerged macrophytes increased during oligotrophication, but in others no changes were observed despite greater water clarity.

7. Recovery of lakes after nutrient loading reduction may be confounded by concomitant environmental changes such as global warming. However, effects of global change are likely to run counter to reductions in nutrient loading rather than reinforcing re-oligotrophication.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices

During the past 10–30 years, major efforts have been made in many countries to improve the ecological quality of lakes by combating external nutrient loading (Marsden, 1989; Sas, 1989), sometimes in combination with additional restoration measures such as biomanipulation (Benndorf, 1990; Gulati et al., 1990) or physico-chemical methods (Cooke et al., 1993). The effects of biomanipulation have been described in several recent reviews (Perrow et al., 1997; Hansson et al., 1998; Drenner & Hambright, 1999; Meijer et al., 1999; Benndorf et al., 2002; Mehner et al., 2002). Since the extensive reviews in the 80s and early 90s (Marsden, 1989; Sas, 1989), there have also been several summaries of lake responses to reductions in nutrient loading without the confounding effect of biomanipulation (e.g. Cooke et al., 1993; Van der Moelen & Portielje, 1999; Willén, 2001a; Jeppesen, Jensen & Søndergaard, 2002; Søndergaard et al., 2002). Most have focused on nutrients and phytoplankton, whereas other biological components have been only briefly covered.

The aim of this paper is to evaluate 35 case studies on lake re-oligotrophication based on information given in questionnaires filled in by scientists and in follow-up communications. We focus on changes in water clarity, nutrients, fish, plankton, submerged macrophytes, as well as resource and top-down control of phytoplankton. Based on previous studies we hypothesized that reduction in P loading, N loading or both would result in:

1 A notable delay in the reduction of in-lake total phosphorus (TP) concentrations because at least three retention times are needed to wash out 95% of the excess P pool in the water column of fully mixed lakes, unless P is permanently lost to the sediment, (Sas, 1989), and because internal loading continuously replenishes the P pool in the water column (Søndergaard, Jensen & Jeppesen, 2003; Nürnberg & LaZerte, 2004).

2 A quick response of the total nitrogen (TN) concentration to reduction in N loading, because N loss by denitrification results in negligible internal N loading (Jensen et al., 1992). Any delays might be greater in deep than in shallow lakes because of often longer hydraulic retention times in deep lakes, and a reduced denitrification capacity arising from a lower ratio of sediment area to water volume.

3 An increase in the in-lake TN : TP ratio because of an often higher TN : TP ratio of inflowing water, a decrease in internal P loading and, ultimately, when low TP concentrations have reduced primary production, reduced denitrification as organic carbon becomes limiting for denitrification (Levine & Schindler, 1989).

4 An increase in particle-bound P because P limitation of phytoplankton will gradually replace limitation by light or N (Sas, 1989), resulting in lower soluble reactive phosphorus (SRP) : TP ratios. Moreover, the number of free inorganic binding sites for P may increase (e.g. because of a higher Fe : P ratio in inflowing water), thereby facilitating precipitation of inorganic P and thus lowering the SRP : organic P ratio and consequently the SRP : TP ratio.

5 A unimodal response of the chlorophyll a (chl a) : TP ratio (McCauley, Downing & Watson, 1989). The increase in the chl a : TP ratio from high to moderate TP concentrations occurs because light limitation of phytoplankton growth by self-shading is replaced by increased P limitation because of a lower SRP : TP ratio (Sas, 1989; Reynolds, 2002). In deep lakes, a high P concentration in the hypolimnion favours motile dinophytes, which may assimilate P in the hypolimnion and transport it to the epilimnion. This, in turn, may lead to a greater chl a : TP ratio in the epilimnion when TP concentrations decrease in the illuminated water layer (Anneville, Gammeter & Straile, 2005; Dokulil & Teubner, 2005). In contrast, increased grazing (Jeppesen et al., 2003) and higher water transparency may lead to a decline in the chl a : TP ratio at low TP concentrations (Portielje & Van der Moelen, 1998).

6 A reduction in phytoplankton biomass because of a lower TP concentration and an increased importance of taxa occurring under oligotrophic conditions (e.g. Edmondson & Lehman, 1981; Wojciechowski et al., 1988; Ruggio et al., 1998; Willén, 2001b; Reynolds, 2002).

7 No consistent response of the fish fauna. There is a general perception, particularly amongst those studying shallow lakes (Scheffer et al., 1993), that the fish community responds only slowly to loading reductions because large organisms such as fish have slow growth rates and high longevity, especially key fish species in nutrient-rich turbid lakes, such as common bream (Abramis brama L.) and carp (Cyprinus carpio L. and Carassius auratus L.). This hypothesis is challenged, however, by the fast responses observed in several reservoirs (Yurk & Ney, 1989; Kalff, 2002) and natural lakes, both deep (Müller & Meng, 1992; Eckmann & Rösch, 1998) and shallow (Jeppesen et al., 2002).

8 A reduction in zooplankton biomass (Gliwicz, 1969; Bays & Crisman, 1983; Hanson & Peters, 1984; Manca & Ruggio, 1998). However, as the predation pressure by planktivorous fish is also likely to decrease, zooplankton biomass is expected to decrease proportionately less than phytoplankton biomass (Jeppesen et al., 2003). The resulting increase in the zooplankton : phytoplankton biomass ratio would augment the relative grazing pressure on phytoplankton.

9 A greater Secchi transparency and therefore a spread of submerged macrophytes. However, macrophyte recolonisation may be slow owing to, for instance, limited seed banks and/or grazing on macrophytes by waterfowl (Mitchell & Perrow, 1997).

Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices

Our analysis is founded on an elaborate questionnaire. In addition, loading data and summer and annual mean values of various lake attributes were examined for the time of maximum external loading, and every 5 years thereafter. Data were averaged from typically 3 years around each 5-year period (−1, 0, +1) to reduce the effect of inter-annual variation. In about 20% of the cases, lack of data reduced the period covered to 1–2 years or larger than 3 years (to cover more variables). Some of the case studies used in this synthesis are described in greater detail in other papers published in this special issue of Freshwater Biology (Anneville et al., 2005; Coveney et al., 2005; Dokulil & Teubner, 2005; Jeppesen et al., 2005a; Köhler et al., 2005; Moss et al., 2005; Phillips et al., 2005; Romo et al., 2005; Søndergaard, Jensen & Jeppesen, 2005).

Basic information on the lakes is given in Table 1. Our data set includes both shallow (mean depth <5 m or polymictic) and deep (mean depth up to 177 m) lakes, with trophic status prior to restoration efforts ranging from mesotrophic to hypertrophic. Included are lakes from the subtropics to the temperate zone (latitude :  28–65 °) in North America and Europe. All warm-temperate and subtropical lakes were shallow. All lakes have been subjected to a reduction in P loading, with or without additional measures to reduce N loading. The loading reductions typically began in the 1970–1980s. For most lakes nutrient reduction in the lake inlets was the only restoration measure taken, but in three lakes it was followed by a major (Lake Balaton) or moderate (Veluwemeer, Apopka) removal of fish. The recovery periods studied range from 5 to 35 years (mean = 15.6 years) but typically varied between 10 and 20 years (Table 1).

Table 1.  Basic information on the study lakes ordered by depth type and decreasing latitude
Lake typeLake no.Lake nameRecovery period included (years)CountryLongitudeLatitudeAltitude (m) Catchment area (km2) Lake area (km2)Mean depth (m)Max depth (m)Retention time (year)Summer stratificationMonths stratifiedTPsum at maximum nutrient loading (μg L−1)TPsum last year included in the study (μg L−1)
Shallow1Little Mere10England2°24′W53°20′ N363.50.030.720.2No 3500135
Shallow2Eemmeer15Netherlands5°2′E52°1′N09015.71.76.20.05No 1210210
Shallow3Gundsømagle10Denmark12°11′E55°43′N4660.321.21.90.08No 1176513
Shallow4Gooimeer15Netherlands5°1′E52°2′N010625.53.526.80.16No 620100
Shallow5Veleuwemeer25Netherlands5°4′E52°25′N0 30.51.550.14No 52844
Shallow6Søgård10Denmark9°19′E55°25′N9230.271.62.70.05No 506267
Shallow7Albufera10Spain0°21′W39°20′N091723.21.220.1No 500300
Shallow8Vesterborg10Denmark11°16′E55°51′N130.30.211.42.90.05No 424231
Shallow9Arresø10Denmark12°7′E55°58′N421639.93.15.92.2No 344157
Shallow10Barton20England1°49′W52°74′N11100.571.520.045No 33391
Shallow11Bagsværd10Denmark12°27′E55°46′ N2071.211.93.21.7No 237107
Shallow12Apopka5USA81°38′W28°37′N204871241.64.94No 212166
Shallow13Müggelsee15Germany13°39′E52°26′N3270007.34.980.17Yes1–2162149
Shallow14Damhussøen10Denmark12°28′E55°40′N7540.461.620.9No 13737
Shallow15Bryrup10Denmark9°31′E56°1′N58480.384.690.15Temporary 11662
Shallow16Ørnsø10Denmark9°31′E56°9′ N19560.4246.60.05Temporary 10680
Shallow17Balaton15Hungary17°5′E46°8′N10557755963.1114.71No 98136
Shallow18Galten35Sweden16°11′E65°80′N0.54435653.4190.05No 8946
Shallow19Okeechobee20USA80°50′W26°58′N51260017302.75.52.7No 69101
Shallow20Leven15Scotland3°22′W56°12′N10714513.33.925.50.42No 6353
Shallow21Võrtsjärv10Estonia25°85′E58°15′N33.733042702.861No 5864
Shallow22Peipsi15Estonia/ Russia25–30 E56–59 N304426035557.115.32No 2739
Deep23Rostherne Mere10England2°23′W53°20′N309.40.4913.6314Yes7350132
Deep24Tystrup10Denmark11°35′E55°21′N7682.56.629.921.70.24Yes3.5332127
Deep25Tissø10Denmark11°17′E55°34′N241712.38.213.21.5Yes 12985
Deep26Furesø10Denmark12°25′E55°48′N206967.416.53714.4Yes411175
Deep27Ekoln30Sweden16°11′E59°27′N0.533343015.7370.5Yes49737
Deep28Constance25Germany/ Austria/ Switzerland9°18′E47°39′N395105004721012524.4Yes78713
Deep29Washington35USA122°15′W47°38′N4127487.632.965.22.38Yes76114
Deep30Scharmützelsee14Germany14°03′E52°15′N911212.09929.512Yes55540
Deep31Geneva25France/ Switzerland6°32′E46°27′N372797558015330912Yes64317
Deep32Ravn10Denmark9°50′E56°6′N2257.21.815331.6Yes43023
Deep33Mondsee20Austria13°22′E47°49′N48124714.23668.31.7Yes5–6289
Deep34Maggiore20Italy/ Switzerland8°67′E45°95′N19065992131773744Yes8179
Deep35Vättern25Sweden14°14′E57°54′N88.5635918903912956Yes484

We have synthesised the questionnaire answers and data in Tables 1–4 and Appendices 1–3. The direction of change (Table 4, Appendices 1 and 3) is based in most cases on statistical tests and in a few cases on qualified evaluations given by the data supplier. In cases where the questionnaire respondent expressed reservations for the direction of change (for instance because of large inter-annual variations), the sign (plus or minus) is bracketed. We used a chi-square test for analysing whether the direction of the changes in selected variables was significantly different from the expectations (SAS Institute, 1989). As Danish lakes comprise a relatively large share of the data set (36% of the shallow and 31% of the deep lakes), and as some of our hypotheses are based on earlier observations from Danish lakes, we ran the tests with and without the data from the Danish lakes. Where percentage values were calculated, they were based on the full data set and on the reduced set excluding Danish lakes. The latter are shown in parentheses. When data were scarce or scattered, we used LOESS regression (SAS Institute, 1989) to give an indication of the direction of changes on the data set divided into shallow and deep lakes. Here the Danish data were included. The LOESS procedure allows smoothing of data but provides no firm statistical tests. In addition, we used multiple regressions (forward procedure) on log-transformed data, with data for deep and shallow lakes pooled. Although these relationships may include transient effects, we believe that they are robust because they cover a very large gradient in mean depth and nutrient status compared to the changes in nutrient loading and concentrations experienced by each lake during the study period.

Table 2.  Results from multiple linear regression analyses of selected environmental variables (P always <0.0001). The relationships assume potential hysteresis after nutrient loading reduction to be small because of the gradient in nutrients covered is larger than the one the individual lakes have gone through during the study period.
Response variableConstantPredictive variable 1Predictive variable 2Predictive variable 3r2n
  1. sum, summer averages; ann, annual averages; load, annual nutrient loading; Zmean, mean depth (m); tw, annual mean hydraulic retention time (year); Zoo, total zooplankton biomass (μg dry mass L−1); Phyto, phytoplankton biovolume (mm3 L−1). Chl a, TP, TN, DIN, and SRP = lake water concentrations of chlorophyll a, total phosphorus, total nitrogen, dissolved inorganic nitrogen and soluble reactive phosphorus, respectively, all in μg L−1. ZooPhyt = Zoosum/Chlasum/66; log = natural logarithm.

log (TN : TPsum)1.03 ± 0.30+0.35 ± 0.09 log (TN : TPload)+0.37 ± 0.05 log (Zmean) 0.4677
log (TN : TPann)1.26 ± 0.31+0.40 ± 0.08 log (TN : TPload)+0.24 ± 0.10 log (Zmean) 0.4146
log (SRPsum)−3.46 ± 0.43+1.34 ± 0.08 log (TPsum)+0.25 ± 0.07 log (Zmean) 0.80128
log (DINsum)−7.05 ± 1.17+1.55 ± 0.15 log (TNsum)−0.24 ± 0.06 log (tw)0.75 ± 0.08 log (Zmean)0.63102
log (DIN : TNsum)−2.91 ± 0.20−0.31 ± 0.06 log (tw)+0.68 ± 0.09 log (Zmean) 0.39102
log (DIN : SRPsum)6.95 ± 0.77−1.07 ± 0.44 log (TPsum)+0.30 ± 0.13 log (Zmean)−0.39 ± 0.08 log (tw)0.49121
log (Phytosum)−3.30 ± 0.28+1.12 ± 0.07 log (TPsum)  0.7598
log (Chl asum)−2.30 ± 0.56+0.93 ± 0.06 log (TPsum)+0.20 ± 0.09 log (TNsum) 0.85107
log (Chl a : TPsum)−2.14 ± 0.58+0.76 ± 0.22 log (TPsum)−0.10 ± 0.02 (log (TPsum))2−0.12 ± 0.05 log (Zmean)0.21107
log (Zoosum)4.68 ± 0.60+0.41 ± 0.11 log (TPsum)−0.28 ± 0.08 log (Zmean) 0.6280
log (ZooPhyt)0.02 ± 0.037NS−0.36 ± 0.08 log (TPsum)  0.1979
Table 3.  Results of multiple linear regression analyses of the contribution of selected phytoplankton taxa versus total phosphorus concentration in summer (TPsum; μg L−1) and mean depth (Zmean; m). The relationships assume potential hysteresis after nutrient loading reduction to be small because the gradient in nutrients covered is larger than the one the individual lakes have gone through during the study period.
Response variableConstantPredictive variable 1Predictive variable 2Predictive variable 3r2n
  1. log, natural logarithm.

log (% Chlorophyta + 1)+3.27 ± 1.01−1.08 ± 0.50 log (TPsum)+0.17 ± 0.06 [log (TPsum)]2 0.16103
log (% Cyanobacteria + 1)−1.27 ± 0.89+1.72 ± 0.44 log(TPsum)−0.16 ± 0.05 [log (TPsum)]2 0.27103
log (% Diatoms + 1)+4.45 ± 0.26−0.31 ± 0.06 log (TPsum)  0.20103
log (% Cryptophyta + 1)+2.95 ± 0.19−0.04 ± 0.01 log (TPsum)2  0.2099
log (% Chrysophyta + 1)+4.89 ± 0.64−1.69 ± 0.32 log (TPsum)+0.15 ± 0.04 [log (TPsum)]2 0.44103
log (% Dinophyta + 1)−2.38 ± 1.24+1.16 ± 0.51 log (TPsum)−0.12 ± 0.05 [log (TPsum)]2+0.54 ± 0.11 log (Zmean)0.30103
Table 4.  Answers to questions about responses of submerged macrophytes to reductions in nutrient loading. Lakes 1–22 are shallow, all others are deep.
QuestionAnswer for lake group 1Answer for lake group 2Answer for lake group 3
Does submerged macrophyte abundance increase?Yes: 1, 5, 13, (17), 26, 27, 31, 32No change: 7, 23, 29, 33Decrease: 2, 4, 25
Do the depth limits of submerged macrophytes (excluding mosses) increase?Yes: 5, 13, 20, 26, 27, 28, 32No change: 1, 2, 25, 26Decrease: none
Does percentage coverage or plant volume inhabited by plants increase?Yes: 5, 12, 14, 26, 28, 32No change: 13Decrease: 2, 4, 25
Does the re-establishment of submerged plants occur gradually or abruptly?Gradually: 13, 14, 26, (27), 32Abruptly: 1, 12, 17Exponentially: 5
Are there any changes in species richness, Simpson evenness and Shannon–Wiener diversity of submerged and floating-leaved macrophytes at the species or genus level?Increase: 4, 5, 13, 30No change: 20Decrease: 2, 31
Do changes in macrophyte variables follow patterns different from those observed at increasing nutrient loading?Yes: 4, 12, 13, 28No: 5, 20, 21, 31 

Total phosphorus

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices

Summer (1 May to 1 October or, in Florida and southern Spain, 1 May to 1 November) mean TP concentration declined in 76% (62% without the Danish lakes) of the shallow lakes and in all deep lakes. Reductions in annual mean TP concentration occurred in 86% (77%) of the shallow lakes and nearly all deep lakes (Appendix 1; Fig. 1). Loading data exist for 17 shallow and 12 deep lakes. To analyse the loading-concentration response pattern, we applied an equation developed by Vollenweider (1976) and OECD (1982):

  • image(1)
image

Figure 1. Annual mean total phosphorus (TP) concentration during the recovery period in the surface water of shallow and deep lakes versus values predicted by the Vollenweider relationship (eqn 1 – see Methods). Lines connect data points at consecutive 5-year intervals for each lake.

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where TP is the annual mean TP concentration in the lake, TPin the discharge-weighted annual mean inflow concentration, and tw the hydraulic retention time (year). During the first 5–10 years, the measured annual mean lake TP concentration was typically higher than predicted from the Vollenweider equation or higher than before the loading reduction (Figs 1 & 2), indicating enhanced internal loading. After 10–15 years, however, measured TP approached the level predicted by the Vollenweider equation or the level attained before loading reduction (Figs 1 & 2).

image

Figure 2. Ratio of annual mean total phosphorus (TP) concentration measured and predicted (eqn 1, see Methods) in the surface water of lakes at maximum nutrient loading and 5, 10, 15 and 20 years after loading reduction (a); hydraulic retention time (tw) and mean depth (Zmean) of the lakes (b); and slope (mean ± SE) of linear regressions (forced through the origin) of observed versus predicted annual mean TP concentration in different years following loading reduction in shallow lakes (c) and deep lakes (d). The slopes for 5 and 10 years in shallow lakes and after 5 years in deep lakes were significantly different from the slopes for years 0 and 15 and 10 years in deep lakes (P < 0.05, paired t-test); however, these differences must be regarded with caution as length of the time series varied across lakes.

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Total nitrogen

Summer TN concentrations declined in 83% (70%) of the shallow lakes, while no clear pattern was found for deep lakes (Appendix 1). When the Danish lakes were excluded, however, 67% of the deep lakes showed an increase in TN concentration. The marked response observed in shallow lakes may primarily reflect the decline in N loading that occurred in 73% (100%) of the shallow lakes, whereas no consistent pattern was found in N loading reductions in the deep lakes (Appendix 1).

We used an empirical model developed for Danish lakes (Windolf et al., 1996) to predict lake water TN concentration:

  • image(2)

where TN is the annual mean lake TN concentration, TNin the discharge-weighted annual mean inflow concentration, and Zmean the mean depth (m). We found no prolonged delay in the response to N loading reduction; it was typically <5 years and only in a few cases exceeded 10 years (Fig. 3).

image

Figure 3. Annual mean total nitrogen (TN) concentration in the surface water of shallow (a) and deep lakes (b) versus predicted values obtained by an equation developed for Danish lakes (eqn 2 – see Methods); and slope (mean ± SE) of linear regressions (forced through the origin) of observed versus predicted annual mean TN concentrations (eqn 2) in the lake water in different years following loading reduction. The slopes for shallow lakes of 5, 10 and 15 years after loading reduction were significantly different (P < 0.05, paired t-test) from the slope at 0; however, these differences must be regarded with caution as length of the time series varied across lakes. No significant differences were found for deep lakes. Symbols and time series as in Fig. 1.

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TN : TP ratio

Multiple regression analysis showed that the TN : TP ratio in the lakes was positively related to the TN : TP ratio in the lake inflows, both during summer and annually, and was also positively related to depth (Fig. 4; Table 2). With decreasing TP concentration, the TN : TP ratio increased markedly in both deep and shallow lakes (Fig. 4). An increase in the summer TN : TP ratio could be seen in 80% of the lakes receiving water with an increased TN : TP ratio (Appendix 1), but the TN : TP ratio even increased in a few lakes for which the TN : TP ratio of the inflowing water decreased (Appendix 1).

image

Figure 4. Ratios of annual and summer mean total nitrogen (TN) concentration to mean total phosphorus (TP) concentration versus the annual mean TN : TP ratio in the lake inlets (a, b) and versus the summer mean TP and TN concentration (c, d). The stippled line in panels (a) and (b) represents the 1 : 1 lines. The curves represent LOESS regression lines.

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SRP and the SRP : TP ratio

In all lakes except Scharmützelsee, the summer SRP concentration declined with decreasing TP concentration, while no changes or even increases were found in lakes with no changes or increases in summer TP concentration (Figs 5 & 6; Appendix 1). In the deep lakes, summer SRP concentrations approached 10 μg L−1 when TP declined below 50–70 μg L−1. In some of the shallow lakes such low concentrations of summer SRP were attained at summer TP levels of more than 400 μg L−1, although typically when TP was below 100–150 μg L−1 (Fig. 6). SRP concentrations below 10 μg L−1 are often considered to be indicative of P limitation (Sas, 1989). Multiple regression analysis revealed that the SRP concentration in summer was positively related to the summer TP concentration and mean depth, but was independent of the hydraulic retention time (Table 2).

image

Figure 5. Summary of key variables of all study lakes divided into three categories according to the direction of responses to reduced nutrient loading: increase = up, decline = down, no change = no. Details are presented in Appendices 1–3. Shallow and deep lake responses are not directly comparable, because the starting levels of total phosphorus (TP) loading and concentrations were generally higher in shallow lakes (Table 1). TN, total nitrogen; SRP, soluble reactive phosphorus; DIN, dissolved inorganic nitrogen; Chl a, chlorophyll a; CPUE, catch per unit effort by weight; Zoo, total zooplankton biomass in summer.

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image

Figure 6. Changes during the recovery period in summer mean concentrations or ratios of chemical variables versus summer mean total phosphorus (TP) concentration in the surface water of shallow and deep lakes. Symbols and length of time series as in Fig. 1. SRP, soluble reactive phosphorus; DIN, dissolved inorganic nitrogen.

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In all lakes with declining summer TP concentrations, except Scharmützelsee, the summer SRP : TP ratio also decreased markedly (Fig. 6; Appendix 1). An increased ratio, despite no significant change in TP, was found in Müggelsee, which was also subjected to a large TN reduction (Köhler et al., 2005). The different responses of Scharmützelsee and Müggelsee may reflect the fact that the reductions in TN loading exceeded the reductions in TP. Accordingly, dissolved inorganic nitrogen (DIN) decreased markedly after loading reduction in these two lakes (Appendix 1; Fig. 6). The SRP : TP ratio also declined in Lakes Peipsi and Võrtsjärv although the TP concentration remained unchanged or even increased. This may reflect the rising chl a values in these lakes (Appendix 1) despite reductions of external TP loading; the increase in chl a concentrations has been attributed to a warmer climate in recent years (Kangur et al., 2002).

DIN and the DIN : TN ratio

No clear pattern was observed for DIN in individual lakes (Appendix 1). However, the summer DIN : TN ratio increased in 76% of the shallow lakes (not significant without the Danish lakes) and in 82% (86%) of the deep lakes. This indicates a decrease in the organic N fraction of TN, most probably as a consequence of a decreasing phytoplankton biomass. Moreover, increased summer DIN concentrations were found in many of the lakes experiencing decreased N loading (Appendix 1). It is notable that DIN and TN concentrations increased in several of the deep lakes during the recovery period even when N loading remained high or declined (Appendix 1; Fig. 5). However, multiple regressions revealed that summer mean DIN concentration was positively related to the annual discharge-weighted inflow concentration (TNin), or summer TN concentration in the lake and mean depth and negatively related to tw (Table 2), while being independent of summer TP and chl a concentration. The summer DIN : TN ratio was positively related to mean depth and negatively to tw (Table 2).

DIN : SRP

In 80% (50%) of the shallow and 91% (71%) of the deep lakes, the summer DIN : SRP ratio increased with decreasing TP loading and TP concentration in the lake (Figs 5 and 6). This ratio was below 10 in the majority of the nutrient-rich shallow lakes (summer concentration of TP > 600 μg L−1), but increased substantially at TP concentrations below 300 μg L−1 in most shallow lakes, and at TP concentrations approximately below 80 μg L−1 in deep lakes (Fig. 4). However, in a few cases, ratios <10 were recorded at summer TP concentrations as low as 20 μg L−1. Multiple regressions revealed that the DIN : SRP ratio positively related to mean depth, and negatively related to the summer mean TP concentration and tw (Table 2). Interestingly, however, the relation with the TN : TP ratio in the lake inflows was not significant.

Chl a concentration and the chl a : TP ratio

In 71% (62%) of the shallow lakes and in 69% (78%) of the deep lakes, a decline was found in summer chl a concentration with decreasing summer TP concentrations. These were 76% (64%) and 64% (71%), respectively, when chl a values were averaged on an annual basis (Fig. 5; Appendix 1). A major decline in chl a concentration was found even at summer TP concentrations above 300 μg L−1 in some shallow lakes, and at concentrations of 125–200 μg L−1 in some deep lakes. This indicates that low summer mean TP concentration is not always a prerequisite for a reduction in chl a concentration. Both for summer and annual mean values the chl a : TP ratio generally increased or remained unchanged during the recovery period (Fig. 7; Appendix 1). The chl a : TP ratio was unimodally related to the TP concentration (highest at intermediate TP concentrations), as predicted, although variation among lakes was high (Fig. 7; Table 2). The decline in the chl a : TP ratio at low TP concentrations coincides well with an increase in the summer mean zooplankton : phytoplankton biomass ratio, which may suggest enhanced top-down control of phytoplankton biomass and thus chl a concentration by grazing at low TP. However, multiple regression analysis showed summer chl a concentration to be positively linearly related to the summer TP and TN concentrations (Table 2).

image

Figure 7. Changes during the recovery period in summer mean values of chemical and biological variables versus summer mean total phosphorus concentration (TP) in the surface water of shallow and deep lakes. Zooplankton : Phytoplankton refers to the ratio of summer mean zooplankton biomass (mg dry mass L−1) and summer mean phytoplankton biomass (mg dry mass L−1) estimated as Chl a × 30 (to convert to carbon) × 2.2 (to convert to dry mass). Symbols as in Fig 1. Chl a, chlorophyll a concentration.

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Secchi depth

In 77% (54%, not significant, NS) of the shallow and 82% (86%) of the deep lakes, the Secchi depth increased as nutrient loading decreased (Fig. 5; Appendix 1). In several cases the spring clear-water phase re-appeared after having been absent for many years (e.g. Eemmeer, Loch Leven, Albufera and possibly Mondsee; E.H.H.R. Lammens, L. Carvalho, S. Romo and M. Dokulil, respectively, unpublished data). The time of occurrence varied, from February in the warm temperate Albufera (Romo et al. 2005) to May in temperate Loch Leven (L. Carvalho, unpublished data). The spring clear-water phase occurred more frequently in Gooimeer, lasted longer in Müggelsee and, based on greater Secchi depths, was more pronounced in Müggelsee (Köhler et al. 2005 and unpublished data) and Lake Geneva (O. Anneville, unpublished data). However, many lakes have not yet reached a state with a spring clear-water phase (e.g. Lakes Apopka, Okeechobee, Balaton, Võrtsjärv and Galten; M.F. Coveney, K.E. Havens, I. Tatraí, P. Nõges and E. Willén, respectively, unpublished data).

Fish abundance and community structure

In most cases fish responded strongly to the reduction in nutrient loading (Fig. 5; Appendix 2). In 82% (90%) of the lakes with available fish data, decreases were noted in the catch of fish by either commercial fishermen, anglers or in fish surveys. These decreases were often substantial. In half of the lakes with quantitative data (in all when the Danish lakes were excluded), the reduction exceeded 25%, and reductions >50% were observed in 18% (83%) of the cases. In addition, the percentage of potential piscivores, such as pike (Esox lucius L.), pikeperch (Sander lucioperca L.) and perch (Perca fluviatilis L.), increased in 80% (75%, although only few data without the Danish lakes) of the case studies, but the decline was significant in deep lakes only. The density of littoral fish species like tench (Tinca tinca L.), Crucian carp (Carassius carassius L.) and rudd (Scardinius erythropthalmus L.) increased in importance in some cases (Appendix 2), which may indicate enhanced plant coverage.

Zooplankton and the zooplankton : phytoplankton biomass ratio

Zooplankton data were only available from 23 lakes with a strong bias towards Danish lakes (52% of the lakes). Multiple regression analysis revealed total biomass to increase with TP concentration and decrease with depth (Table 2; Fig. 8). However, chi-square tests only showed significant changes for shallow lakes and only when Danish lakes were included (Appendix 3). The contribution of Daphnia spp. to total zooplankton biomass increased in 81% of the shallow lakes, whereas no significant pattern was found for deep lakes. The zooplankton : phytoplankton ratio was generally low for TP concentrations >100 μg L−1 in both shallow and deep lakes, irrespective of phytoplankton community structure, but increased in many lakes below this threshold (Fig. 7). The ratio increased in 65% of the shallow lakes, while no clear pattern was found for deep lakes (Appendix 1). Multiple regression analysis showed the ratio to increase with decreasing TP concentration, whereas a significant influence of mean depth was not detected (Table 2).

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Figure 8. Summer mean zooplankton biomass and phytoplankton biovolume and proportion of major phytoplankton taxa versus summer mean total phosphorus concentration in the surface water of shallow and deep lakes. Curves represent LOESS regression lines. Data at 5-year intervals are shown from the 23 (zooplankton) or 27 (phytoplankton) lakes for which data were available.

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Phytoplankton biomass and community structure

Phytoplankton biomass followed the pattern for chl a concentration (Table 2). It declined in 71% (60%; effect not significant) of the shallow lakes and 70% (67%, NS) of the deep lakes for which data are available (Figs 5 & 8; Appendix 3). The response of the different phytoplankton classes varied among lake types. For shallow lakes, the contribution of diatoms to the total biovolume increased in 69% (63%, NS) of the lakes, and the contribution of cryptophytes and chrysophytes in 63% (50%, NS) and 64% (43%, NS) of the lakes, respectively. No significant pattern was found for the remaining phytoplankton groups. The contribution of chrysophytes also increased in 82% (100%) of the deep lakes. In addition, an increase in dinophytes was found in 75% (89%) and a decline of cyanobacteria in 80% (100%) of the cases (Appendix 3). LOESS smoothing on the entire set of data indicates that the proportion of chlorophytes declined in shallow lakes, from nearly 80% of the total biovolume at high TP concentrations to <10% of the total biovolume at TP concentrations <100 μg L−1. Deep lakes displayed the opposite tendency, with chlorophytes increasing to near 20% at low concentrations of TP. Cyanobacteria contributed substantially to the total biovolume down to 50 μg TP L−1 in shallow lakes and, in some cases, to 10–15 μg TP L−1 in deep lakes. The share of diatoms increased steadily with decreasing TP concentrations, such that they constituted the most important group in deep lakes at low TP concentrations. Dinophytes were most important at high to intermediate TP concentrations and were most important in deep lakes. Multiple regression analyses showed unimodal relationships with TP of the biomass proportion of most phytoplankton taxa (Table 3). Mean depth contributed positively for dinophytes only, and the TN concentration was never a significant predictive variable.

Macrophytes

The response of macrophytes to reductions in nutrient loading was not uniform across lakes (Table 4). In most lakes for which data were available, signs of macrophyte spread were apparent, either as an increase in macrophyte abundance, coverage, plant volume inhabited and/or, in the case of submerged macrophytes, depth distribution. These changes occurred gradually in most cases, but in a few instances exponential or abrupt changes were recorded. Species richness also increased in most lakes, although two case studies reported reduced richness. However, in several lakes no changes were observed in submerged macrophyte abundance despite raised water clarity.

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices

For both deep and shallow lakes we found clear effects of reductions in nutrient loading (Table 5). For most lakes, lake TP concentrations, chl a concentration in the surface water and phytoplankton biomass were lower and Secchi depth was higher. Internal loading apparently delayed the recovery, but in most lakes a new equilibrium between P in the sediment and water column was reached after 10–15 years, thus confirming earlier findings by Ahlgren (1978) and Sas (1989). There was a slight tendency to faster recovery in lakes with a short retention time, despite high TP concentrations when loadings were greatest, and in lakes with a long hydraulic retention time and previously low TP loading (Fig. 2; Table 1). No clear effect of lake depth on recovery was detected (Fig. 2). The latter corresponds well with results from earlier comparisons across lakes by Sas (1989) and Jeppesen et al. (1991). A plausible explanation is that lakes with short hydraulic retention times often were more heavily impacted in the past, resulting in higher P accumulation in the sediment and, following nutrient reduction, higher and/or longer internal loading, whose effects overrode the effective P removal through high flushing rates (Jeppesen et al., 1991).

Table 5.  General overview of key findings from the analysed case studies on lake re-oligotrophication. Note that the responses of shallow and deep lake cannot be fully compared as the starting TP level before loading reduction differed, being overall higher in shallow lakes (Table 1).
Response variableShallow lakes (mean depth <5 m or polymictic)Deep lakes (others)
P response time to TP loading reductionTypically 10–15 yearsTypically 10–15 years
N response time to TN loading reductionTypically <5 yearsTypically <5 years
TP summer and annualDecreased in most lakesDecreased in all lakes
TN summerDecreased in most lakesNo clear pattern
TN : TP summerIncreased in most lakes even in some lakes with lower TN : TP in the inletIncreased in most lakes
SRP summerDecreased in all lakes when TP decreasedDecreased in all but one lakes when TP decreased
SRP : TP summerDecreased in all lakes when TP decreasedDecreased in all but one lakes when TP decreased
DIN : SRP summerIncreased in most lakesIncreased in most lakes
Secchi depth summerIncreased in most lakesIncreased in most lakes
Chl a summerDecreased in most lakesDecreased in most lakes
Chl a : TP summerIncreased or no changesIncreased or no changes
Phytoplankton biovolumeDecreased in most lakesDecreased in most lakes
Phytoplankton community changesHigher importance of diatoms, cryptophytes and chrysophytesDecline in cyanobacteria and greater importance of dinophytes and chrysophytes
Fish biomass, judged from surveys, commercial catches or angling reportsDecreased in most lakesDecreased in most lakes
Percentage piscivorous fishIncreased in most lakes, thus likely resulting in enhanced top-down control of prey fishIncreased in most lakes thus likely resulting in enhanced top-down control of prey fish
Fish community changes in European lakes (examples)Cyprinids to percids plus cyprinidsCyprinids to percids plus cyprinids or Percids plus coregonids to coregonids or Coregonids to coregonids plus salmonids, depending on TP levels
Zooplankton biomassDecreasedNo clear pattern
Zooplankton : phytoplankton biomass ratioIncreased in many lakes, probably reflecting release from fish predationNo clear pattern
Submerged macrophytesNo clear patternNo clear pattern
Indications of enhanced bottom-up control of phytoplanktonNearly all lakesNearly all lakes
Indications of enhanced top-down control of phytoplanktonMany lakesNo clear pattern
SeasonalityLargest reduction in TP and chl a concentrations during spring and autumn, later in the recovery phase also in summer. Exceptions are some lakes with major reductions in N loading, showing major effects also in summer in the early recovery phaseLargest effect in summer, later in spring and autumn

The quick (<5 years) response of lakes to N loading reductions compares well with the results of other studies (Jensen et al., 1992) and may be explained by the fact that surplus inorganic N is lost to the atmosphere via denitrification rather than accumulated in the sediment. For two deep and some shallow lakes with high TN and correspondingly high TP concentrations (see below), the observed TN concentrations were often lower than predicted by the relationship established previously for Danish lakes, but approached the predicted values after 5–10 years (Fig. 3). The general increase in the TN : TP and DIN : SRP ratios in the lake water suggests that P became a more likely limiting nutrient for phytoplankton growth than before reductions in nutrient loading.

The increase in N relative to P may in part reflect that loading reductions have mainly been directed towards P. While this is a wise strategy for deep lakes (Sas, 1989), recent studies show that nitrogen may play a more important role in shallow lakes than hitherto anticipated (Moss, 2001; Gonzáles Sagrario et al., 2005; James et al., 2005). Nitrogen negatively affects both submerged macrophyte species richness (James et al., 2005) and the chances of maintaining a macrophyte-dominated state at moderately high TP levels (Gonzáles Sagrario et al., 2005). At a summer mean TP concentration of 30–150 μg L−1, submerged plants tend to disappear in shallow Danish lakes when the summer TN levels is above 1–2 mg L−1 (Gonzáles Sagrario et al., 2005), a threshold exceeded in most of the shallow lakes included in the present study (Fig. 4). Thus, to further improve the ecological quality of shallow lakes, it is important to consider not only P but also N loading (Moss, 2001; Gonzáles Sagrario et al., 2005). However, although a rapid decline in N is to be expected at reduced N loading, it may be difficult to achieve in practice because N in lakes typically derives from diffuse sources (Sharpley, Foy & Whiters, 2000).

The large increase in the summer DIN : TN ratio (Fig. 5; Appendix 1) indicates that denitrification could not fully compensate for the reduced uptake of DIN by phytoplankton. The insignificant response of DIN to TN loading reduction (Appendix 1) points in the same direction. No firm conclusions can be drawn on the underlying mechanisms. However, a possible explanation for shallow lakes is that the redox potential in the sediment rose because of lower sedimentation rates of organic matter and the resulting lower sediment oxygen demand. For deep lakes, reduced sedimentation of N to the hypolimnion and higher redox potentials may also play a role, and organic matter may have become limiting for denitrification in some of the deep lakes with low TP concentrations. Finally, an increase in atmospheric nitrogen pollution during the study period may play a role as suggested by results from Lago Maggiore (Mosello et al., 2001).

Probable explanations for the increase in the chl a : TP ratio that we found, notably in deep lakes (Lakes Geneva and Constance), include (i) excess SRP in the early recovery phase, (ii) access to P at high concentrations in the hypolimnion, as suggested by the frequent increase in dinophytes, which may migrate vertically in the water column (Reynolds, 2002), (iii) enhanced mixotrophy and greater P affinity of phytoplankton taxa (Reynolds, 2002; Anneville et al., 2005; Dokulil & Teubner, 2005), (iv) reduced self-shading, and (v), for some lakes, higher water temperatures resulting from global warming. In three lakes, summer chl a concentrations even increased, with the increase in one or two of them (Lake Võrtsjärv and possibly also Lake Peipsi) having been attributed to warmer climate (Kangur et al., 2002).

The phytoplankton generally followed patterns observed in earlier studies of oligotrophication (Willén, 2001b; Reynolds, 2002). Diatom growth is dependent on supplies of available silica, which tends to decrease with phosphorus enrichment (Schelske et al., 1986). Therefore, the shift in phytoplankton community structure towards diatoms that we observed at reduced SRP concentrations in shallow lakes may be because of a relaxation of silica limitation in addition to improved competitive capacity for phosphorus (Schelske & Stoermer, 1971). Notable is, however, also the observed shift in the shallow hypertrophic Lakes Gundsømagle and Søgård (Appendix 3), from chlorophytes to cyanobacteria despite a general major increase in the TN : TP ratio in the inflowing water and in the in-lake DIN : TN and DIN : SRP ratios (Appendices 1 and 3). Moreover, when TP concentrations declined and TN : TP ratios increased, N-fixing cyanobacteria were often replaced by heterocystous species (Jeppesen et al., 2002, 2005b; Phillips et al., 2005), indicating that the N : P ratio may be of minor importance for the response of cyanobacteria in these lakes. This is contrary to results obtained in some earlier multi-lake surveys (Smith, 1983; Smith et al., 1995) that encompassed a much narrower range of TP concentrations.

Fish communities showed major responses to reductions in nutrient loading. Catch data suggest that the fish biomass declined in most of the lakes for which quantitative data were available and the proportion of piscivores increased, indicating higher piscivores control of prey fish. In the eutrophic shallow Danish and Dutch lakes, the proportion of percids increased at the expense of cyprinids, and the contribution of pike and pikeperch rose in some cases as well (Jeppesen et al., 2005a; E.H.H.R. Lammens, unpublished data; R. Portielje, unpublished data). Furthermore, in the warm-temperate Albufera, an increase in littoral fish species and a higher contribution of piscivorous species were found during oligotrophication (Romo et al., 2005). In the deep mesotrophic to slightly eutrophic lakes, perch-coregonid communities changed to coregonid dominance (e.g. Lakes Constance and Geneva; Eckmann & Rösch, 1998). However, when TP was reduced further as in Lake Vättern, salmonids increased at the expense of coregonids (Degerman et al., 2001). These results follow the established fish-trophic state relationships (Colby et al., 1972; Persson et al., 1988). Our results suggest, therefore, that fish often respond rapidly to a P loading reduction, and in most cases major changes appeared in both community structure and biomass after <10 years. In subtropical shallow lakes, fish composition differs from that in northern temperate lakes (Schulz, Hoyer & Canfield, 1999), but oligotrophication can result in a similar pattern with a change in composition towards a higher contribution of piscivorous or omnivorous species.

The fast response of the fish community may challenge the idea of using fish manipulation as a lake restoration tool. There are good examples (although also many failures) showing that substantial removal of fish or stocking of piscivores or sometimes continuous fish management have improved the ecological state of lakes and sped up the recovery after reductions in nutrient loading (e.g. Hansson et al., 1998; Lammens, 1999; Meijer et al., 1999; Mehner et al., 2002). Our data indicate that major changes in the fish community often occur <10–15 years after the loading reduction, even without manipulation of the fish stock. Moreover, in lakes with short hydraulic retention times, reduced turbidity of the water column as a result of fish manipulation can result in higher accumulation of P in the surface sediments of the lake than if the water had remained turbid because less particulate P is leaving the lakes and because of higher retention capacity in the sediment (Søndergaard et al., 2003). This would result in lower losses of P via the lake outlet (Hansson et al., 1998; Meijer et al., 1999) and may thus delay the recovery in the long term if the lakes do not remain in the clear-water state (Søndergaard et al., 2003). Although biomanipulation can be a useful tool not least for rapidly shifting turbid shallow lakes to their clear alternative states (Jeppesen et al., 1990; Moss, 1990; Scheffer et al., 1993), we suggest that careful deliberation is needed on the benefits of such measures in the long term.

The greater zooplankton : phytoplankton biomass ratio, smaller chl a : TP ratio at summer mean TP concentrations <100–150 μg L−1 and the increased contribution of Daphnia to zooplankton biomass in shallow lakes are all signs of decreased fish predation on zooplankton and of an enhanced top-down control of phytoplankton (Brooks & Dodson, 1965; Carpenter & Kitchell, 1993; Gliwicz, 2003; Jeppesen et al., 2003). Changes in fish communities have the highest impact on zooplankton in shallow lakes where the overall predation risk appears to be higher (Keller & Conlon, 1994; Jeppesen et al., 2003). Thus, we hypothesise that the often strong response to nutrient loading reduction is a consequence of both enhanced resource and predation control of phytoplankton. Further studies are needed to test this hypothesis. Research is especially needed in the subtropics and tropics, where the dominant fish taxa can often graze both phytoplankton and zooplankton (Lazzaro et al., 2003) and fish predation on zooplankton is likely high even at low TP concentrations (Meerhoff et al., 2003; Jeppesen et al., 2005a), so that the typical trophic cascade type of effects may be less strong (Bays & Crisman, 1983; Crisman & Beaver, 1990).

We found indications of delayed responses of submerged macrophytes to increased water clarity in some case studies (Table 4). It may reflect lack of available seeds and turions and/or hindrance of establishment or spread by waterfowl grazing (Søndergaard et al., 1996) or competition with benthic filamentous algae. Pronounced fluctuations in biomass and species dominance in the early phase of plant re-establishment (Lauridsen et al., 2003) and low species richness at high nutrient levels may reduce the buffering capacity of plants against changes in environmental factors and thus enhance the risk of loss of the plants (Moss, 2001). Shallow eutrophic lakes may also rapidly switch states from clear to turbid and vice versa if water levels vary markedly (Blindow et al., 1993; Havens et al., 2001; Romo et al., 2004). As plants play key roles in shallow lakes (Scheffer et al., 1993; Moss, 2001), it is important to gain better insight into plant responses during recovery from excessive nutrient loading.

Phenological changes were not examined in the present analysis, but are addressed in several papers in this special issue (Anneville et al., 2005; Jeppesen et al., 2005a; Köhler et al., 2005; Phillips et al., 2005; Søndergaard et al., 2005). There is clear evidence that in deep lakes the period in which P limits phytoplankton gradually increases from initially only summer towards inclusion of spring and autumn later in the recovery phase (Anneville et al., 2005). In contrast, in shallow lakes the effect on P and plankton was initially greatest in spring and autumn, progressing later to the summer concurrently with a gradual reduction in internal P loading (Jeppesen et al., 2005a; Phillips et al., 2005; Søndergaard et al., 2005). In shallow lakes experiencing major reductions in external loading of both N and P, the effect on the concentration of TP and chl a in the early recovery phase may also be high in summer, despite a continued high internal P loading, because nitrogen can become limiting (Hameed et al., 1999; Köhler et al., 2005). The significant response, particularly in spring and autumn in shallow lakes in the early recovery phase, emphasises the importance of year-round monitoring when evaluating the effect of reductions in nutrient loading rather than only during summer, as is present practice in many countries.

The conclusions derived in the present analysis are based on correlation evidence and interpretation in terms of cause-and-effect relationships may therefore be complicated by confounding factors. One of those is global warming. Although the data presented here are too infrequent (5 year intervals) to elucidate the potential confounding effects of global warming on response to reductions in nutrient loading, climatic effects have been examined for some of the lakes included in the present data set (e.g. Straile & Adrian, 2000; Anneville et al., 2002; Kangur et al., 2002; Nõges et al., 2004). These analyses indicate an earlier onset of the clear-water phase (if any), stratification (if any) and fish spawning, reduced mixing in stratified lakes, and higher surface water temperature promoting higher internal P loading from sediment portions exposed to warm surface water. Moreover, in shallow and some deep lakes cyanobacteria may be more abundant and blooms may persist longer. However, the strong re-oligotrophication signals revealed by our analysis suggest that the observed changes in the lakes included in our data set reflect primarily the impacts of lower nutrient loadings rather than climate change. This conclusion is supported by results from mesocosm experiments which likewise suggest a much stronger effect of changing nutrient loadings than of changing temperatures in shallow lakes (McKee et al., 2003; Moss et al., 2003).

The general re-oligotrophication response patterns described here can be regarded only as a guideline when discussing the response of a particular lake. Each lake is unique in many respects and may exhibit a specific trajectory, as reflected in the appendices and figures presented (see also Moss et al., 2005). Further, although this study covers a wide range of lake types and climate zones, most of the lakes are situated in northern Europe and are relatively shallow Danish lakes in particular contributed importantly to the data set and had also been used previously to generate some of the hypotheses we examined. However, exclusion of the Danish lakes did not radically alter the overall pattern of response reported here. Reduction in the significance of trends was the most obvious difference, but can generally be attributed to reduced sample size (Appendices 1 and 3), although it could also reflect the greater depth gradient and climatic variation among the remaining lakes compared to the Danish lakes. For example we expect that the responses may differ between shallow cold-temperate and tropical or subtropical lakes, for instance owing to faster nutrient cycling and retention, better growth potential for submerged macrophytes, more truncated food webs and probably stronger top-down control of the zooplankton grazers in the warmer lakes (Lazzaro, 1997; Lazzaro et al. 2003; Meerhoff et al., 2003; Jeppesen et al., 2005b; Romo et al., 2005). Too few data from warm lakes were available for the present analysis to elucidate such differences in more detail. Thus, different patterns may emerge when examining warm-temperate or tropical lakes and very deep lakes, which also were poorly represented in the present data set.

Acknowledgments

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices

This study was supported by the Danish Natural Science Research Council through the research project ‘Consequences of weather and climate changes for marine and freshwater ecosystems. Conceptual and operational forecasting of the aquatic environment’ (CONWOY 2052-01-0034), by the National Environmental Research Institute, Denmark, IGBP-PAGES and the EU project EUROLIMPACS (GOCE-CT-2003-505540). We thank the following scientists for contributing data and answering specific questions in the questionnaires: Therese East, Ryan Maki, Bruce Sharfstein, John Beaver, Nadine Angeli, Rita Adrian, Vera Istvanovics, Istvan Kobor, Peter Kozerski, Andreas Nicklisch, Laszlo G. Toth, Norbert Walz, Juta Haberman, Andu Kangur, Peeter Kangur, Reet Laugaste, Anu Milius, Tõnu Möls, Helle Mäemets, Alex Kirika, Iain Gunn, Edgar F. Lowe and Lawrence E. Battoe. We also thank the other participants in the Silkeborg symposium, Carl Sayer, Helen Bennion, Li Shijie, N. John Anderson, Oliver Heiri, Peter Leavitt, Richard W. Battarbee, and Tatyana Moiseenko, for stimulating discussions. Finally, we are grateful to the Danish counties for access to data on Danish lakes. We wish to thank Mark Gessner and two unknown reviewers for most valuable comments that helped tighten up the paper. Thanks are also due to Anne Mette Poulsen for editorial assistance and to NERI's graphical workshop for their patient help with the multiple reworking of figures during the process.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices
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Appendices

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Total phosphorus
  7. Discussion
  8. Acknowledgments
  9. References
  10. Appendices
Table Appendix1.  Changes in physico-chemical variables for surface water and the zooplankton : chl a ratio during recovery of 35 lakes from excessive nutrient loading (duration – see Table 1)
Lake no.Lake nameTP summerTP annualSRP summer SRP : TP summerTN inflow annualTN summerDIN summer TN : TP inflow annual TN : TP summer DIN : TN summerChl a summerChl a annualChl a : TP summerChl a : TP annual Zoo : Chl a summer Zoo : Chl a annualSecchi depth summer
1Little Mere       +   +
2Eemmeer+++++  +
3GundsømagleNoNo++++++++
4Gooimeer+++++  +
5Veleuwemeer + ++No  +
6Søgård+++No+++
7Albufera ++  ++++No
8VesterborgNoNo++++No+
9Arresø+++++++++
10Barton  No  +No+  +
11Bagsværd No ++No+++++
12Apopka           No  +
13MüggelseeNo(−)++No+
14Damhussøen  ++No+++
15Bryrup+No++++++++
16Ørnsø++++No+++
17Balaton+++++ ++
18Galten +No +   No
19Okeechobee+++No++NoNoNoNo(−)No
20Leven(−)NoNo No  (−)NoNoNo+  (+)
21VõrtsjärvNoNo(−)No+No++No+NoNoNo
22Peipsi++No++  ++    No
23Rostherne Mere   +   (−)(−)     
24TystrupNo+++++++
25TissøNoNoNo++++No+++
26Furesø No +NoNo+++++
27Ekoln +++++ (+) No +
28Constance++++++++NoNo+
29Washington++++++
30ScharmützelseeNo+   +NoNo++   
31Geneva++++NoNo++NoNo
32RavnNoNoNo+++NoNo+
33MondseeNo  +      +
34MaggioreNoNoNo+++ No  +
35Vättern ++ ++ (+)   +
Lake typeTrendP-value of chi-square test
  1. Signs in parentheses are trends that must be interpreted with great caution. Lakes 1–22 are shallow, all others are deep. Also shown at the bottom are results of chi-square tests for differences when all three categories of trends (+, − and no change) were included and when only lakes showing either positive (+) or negative (−) changes were included.

  2. TP, total phosphorus; SRP, soluble reactive phosphorus; TN, total nitrogen; DIN, dissolved inorganic nitrogen; Chl a, chlorophyll a; Zoo, zooplankton biomass; +, increasing during recovery; −, decreasing; No, no change; empty cells, no data; NS, not significant at the 10% level; −DK, data set excluding Danish lakes.

ShallowNo, +, −0.00020.0010.002<0.00010.005<0.0001NS0.070.0070.060.00090.00020.090.060.040.060.0001
+, −0.0030.0010.0080.0010.020.0005NS0.070.030.060.0020.0010.03NSNS0.020.0003
DeepNo, +, −<0.00010.0040.0020.004NSNSNS0.02<0.00010.0030.020.020.05NSNSNS0.01
+, −<0.00010.004<0.00010.004NSNSNS0.02<0.00010.010.010.090.03NSNSNS0.01
Shallow (−DK)+, −NS0.05NS0.06<0.00010.04NSNSNSNS0.060.05NSNSNSNS0.02
Deep (−DK)+, −<0.0001<0.0001<0.00010.04NSNSNSNS<0.00010.06<0.0001<0.0001NSNSNSNS0.06
Table Appendix2.  Changes in the fish community during recovery of 25 lakes from excessive nutrient loading
Lake no.Lake nameFish catch methodPeriod covered (year)CPUECommunity change% Piscivores by weight (including small perch)
FromToFromTo
2,4Eemmeer and GooimeerTrawling20−35%Bream-(roach-smelt)Bream-pikeperch-roach 523
3GundsømagleGill nets11−29%Roach-crucian carp-tenchRoach-perch-pike-crucian carp 529
5Veleuwemeer*Trawling25−75%Bream-pikeperchRoach-perch-bream-pikeperch 
6SøgårdGill nets10+43%Roach-bream-perchBream-roach perch1623
7AlbuferaCommercial/ gill nets10 MulletsMullets 1 
8VesterborgGill nets10−33%Bream-roach-perchRoach-bream-perch-pike 925
9ArresøGill nets10−31%Bream-roachBream-roach-pikeperch 132
11BagsværdGill nets11−25%Bream-roach-pikeperchBream-roach-perch1811
13MüggelseeCommercial10 Bream-roach   
14DamhussøenGill nets11 +3%Perch-tench-roachPerch-tench-roach4639
15BryrupGill nets10 0%Roach-perchRoach-perch2627
16ØrnsøGill nets 5 −8%Bream-roach-perchRoach-bream-perch1918
17BalatonGill nets16−50%*Bream-roach  +
20LevenSport fishing (+)    
22PeipsiTrawling15−67%Pikeperch-pike-roach-perchPikeperch-ruffe-roach6970
24TystrupGill nets 9−12%Roach-bream-perchPerch-roach-bream-bleak2150
25TissøGill nets11+22%Roach-perch-breamRoach-perch-bream1534
26FuresøGill nets11−36%Roach-perch-bream-smeltRoach-perch-bream1253
27Ekoln  (−)    
28ConstanceCommercial25Perch-(whitefish)(Perch)-whitefish, decrease in perch catches and a shift of perch from pelagic to the littoral zone  
31GenevaCommercial25−40%Perch-whitefish-(roach)Whitefish-perch-(pike)  
32RavnGill nets 6−20%Perch-roach-breamPerch-roach4858
34MaggioreCommercial Major reductionWhitefish-BleakWhitefish-shad, bleak Major decline in whitefish and bleak  
35VätternCommercial 5−60%Whitefish-salmonidsIncrease in salmonids, major decrease in whitefish  
Lake typeTrendP-value of chi-square testP-value of chi-square test
  1. *Removal of planktivorous fish in addition to reduction in nutrient loading.

  2. Signs in parentheses are trends that must be interpreted with great caution. Lakes 1–22 are shallow, all others are deep. For chi-square tests at the bottom see legend of Appendix 1.

  3. CPUE, catch per unit effort (or changes in catches when the method is ‘commercial’); +, increasing during recovery; −, decreasing; empty cells, no data available.

ShallowNo, +, −0.02NS
+, −0.08NS
DeepNo, +, −0.02<0.0001
+, −0.02<0.0001
Table Appendix3.  Changes in summer mean phytoplankton biovolume, contributions by various taxa to the total phytoplankton biovolume, zooplankton biomass and contribution of Daphnia to the total zooplankton biomass during the recovery period
Lake no.Lake nameBiovolume of phytoplankton in summerPercentage of phytoplankton biovolumeBiomass of zooplankton in summerPercentage of Daphnia biomass summer
CyanobacteriaChlorophytesDiatomsCryptophytesDinophytesChrysophytes
1Little Mere + +    
3Gundsømagle+++++
6Søgård+No+NoNoNo+
7AlbuferaNo++++ No
8Vesterborg+++++
9ArresøNoNo++NoNo++
10Barton −*     
11Bagsværd+++No+++
12Apopka No+    
13MüggelseeNo+NoNo+ 
14DamhussøenNo+++NoNo+
15BryrupNo++++++
16ØrnsøNoNo+No++
17Balaton+++++
18Galten(−) + +  
19Okeechobee +(+)
21Võrtsjärv+++NoNo(+)  
22Peipsi++++++ 
24Tystrup+No++
25TissøNo+NoNo++
26Furesø++++
27Ekoln  +++(−) 
28Constance(−)+No(+)(+)
29Washington+++++(+)+
30Scharmützelsee  + +   
31Geneva + +
32Ravn++No++
33Mondsee+ +++  
34MaggioreNo+No++
35VätternNo  ++  
  1. *By number.

  2. Signs in parentheses are tendencies that must be treated with great caution. Lakes 1–22 are shallow, all others are deep. For chi-square tests at the bottom see legend of Appendix 1.

  3. All, P-value of chi-square tests for all lakes; −DK, P-values of chi-square tests for all lakes except the Danish ones.

  4. +, increasing during recovery; −, decreasing; no, no change; empty cells, no data.

Lake typeTrendAll (−DK)All (−DK)All (−DK)All (−DK)All (−DK)All (−DK)All (−DK)All (−DK)All (−DK)
ShallowNo, +, −0.01 (NS)NS (NS)NS (NS)0.007 (NS)0.03 (NS)NS (NS)0.05 (NS)NS (NS)0.009 (NS)
+, −0.02 (NS)NS (NS)NS (NS)0.07 (NS)0.02 (NS)NS (NS)0.03 (NS)NS (NS)0.04 (NS)
DeepNo, +, −0.05 (NS)0.008 (<0.0001)NS (NS)(NS) (NS)NS (NS)0.009 (0.04)0.003 (<0.0001)NS (NS)NS (NS)
+, −0.03 (NS)0.02 (<0.0001)NS (NS)(NS) (NS)NS (NS)0.01 (0.04)0.01 (<0.0001)NS (NS)NS (NS)