Biomanipulation in Lakes

The following sample Biology research paper is 2201 words long, in APA format, and written at the undergraduate level. It has been downloaded 27 times and is available for you to use, free of charge.


Biomanipulation of lakes has a long history in the field of limnology. Historically, cultural eutrophication of lakes became an issue in the 1970’s and ecosystem managers searched for solutions to the emerging issue of noxious algae blooms. A controversial idea was proposed that phytoplankton abundance could be controlled by manipulating the food web of the lake ecosystem. The idea is compelling because food web manipulation offers a self-sustaining solution to algae blooms. Once the manipulation has been performed, the system should stay in its new clear water state. The successful biomanipulation of Round Lake in Minnesota in the early 1980’s was a hallmark paper because it demonstrated that the idea had real value to management and could be successful (Shapiro & Wright, 1984). Today biomanipulation has a well-established place in lake management, however, there are new applications of the theory being developed and details and when and where it will be most effective remain unanswered (Scheffer et al., 2012, Batt et al., 2013).


The paper describing the biomanipulation of Round Lake, Minnesota is important because it is the first example of a successful lake management program based on food web manipulation (Shapiro & Wright, 1984). Round Lake had transitioned from a clear water state to one dominated by phytoplankton blooms and low water clarity. The food web of Round Lake had also changed from one being dominated by largemouth bass (M. salmoides) to one dominated by bluegill (L. macrochirus), black crappie (P. nigromaculatus), and benthivorous feeders. To restore the lake to a clear water system, the managers killed all of the fish in the lake using rotenone and then reintroduced fish in numbers that favored the piscivores. The idea was that having more piscivores would keep the levels of smaller fish that feed on zooplankton low. This in turn would lead to an increase in the biomass of zooplankton and an increase in grazing pressure on phytoplankton.

The manipulation was a resounding success; soon after the manipulation clarity in the lake increased due to declines in phytoplankton numbers. The major factor was a decrease in zooplankton abundance, but an increase in species of Daphnia, an important large bodied species of phytoplankton herbivore. Daphnia are easy to see and are a favorite target of bluegill and black crappie. With those fish in reduced numbers, the Daphnia were able to increase in density and the herbivore pressure on phytoplankton doubled (Shapiro & Wright, 1984).

Round Lake served as example where control from the top of the food web, piscivore fish, was responsible for the amount of phytoplankton, or primary production in the lake (Shapiro & Wright, 1984). In other lakes, nutrient enrichment from anthropogenic sources was causing the opposite effect, an increase in primary production from the bottom of the food web. This has sparked a long standing and continuing debate in limnology (Demelo et al., 1992): “Top down or bottom up control of lake food-webs?” There is evidence for both viewpoints so the question is more rightly posed as “Under what conditions should we expect to see top down control of production in lake ecosystems?”

Beyond the field of limnology this debate has become a central question in Ecology. Trophic cascades, as these top down effects are referred to in the modern literature, have been demonstrated in a variety of different systems besides just lakes (Hairsten & Hairsten, 1993). There is continued research into the extent of these effects and what ecosystems we can expect to find them in. Terrestrial examples include the role that wolves play in regulating ungulate feeding behavior and cascading effects into plant communities in places like Isle Royal in Lake Superior and in Yellowstone National Park.


Early observations that natural events such as winter fish kills could change the food web of a lake and subsequently affect water clarity lead to the development of the biomanipulation theory. After testing the theory in small shallow ponds, the manipulation of Round Lake was performed to determine if the idea could be applicable to larger ecosystems. Round Lake, while not huge, is 12.6 hectares in area and gets up to 10.5 meters deep. It was a manageable test system in which to try out the biomanipulation theory (Shapiro & Wright, 1984).

Following the success of the Round Lake manipulation, there was a period of debate in the field. Early proponents of biomanipulation, referring to the effect as a trophic cascade, repeated the experiment in other lakes and published their results in high profile journals. One early group of “evangelists” of the theory was the members of the cascade project lead by Stephen J. Carpenter (1985, 1987). Their publications purported that it was clear that top down control of productivity was a real phenomenon and one that was valuable to managers.

Opponents to the top-down control view point emerged quickly. The conventional wisdom was that nutrients controlled water clarity in lakes and this theory went against that. Additionally, the biomanipulation examples were only single lakes and many of them fairly small. It was argued that without statistical replication, it was hard to determine if the proposed mechanism was actually responsible for the results that were being observed. Was it truly fish predation that was driving the shifts in water clarity? Confounding issues included changes in nutrient cycling due to changes in the fish food web and competition for nutrients from benthic macrophytes (DeMelo et al. 1992).

The debate continued and evidence piled up on both sides of the fence. More and more biomanipulation experiments were performed, adding to the body of data that could be analyzed. For example, in 1999 an evaluation of biomanipulations of lakes throughout the Netherlands found that in most cases, changing the food web of a lake to one dominated by piscivores resulted in a shift to a clear water system (Meijer et al. 1999). Other efforts came to different conclusions. A similar survey across Europe found that biomanipulation had the intended effect some of the time, but that fish manipulation wasn’t always as effective as nutrient reduction. Moss et al. cautioned managers that they should focus on nutrient reduction first when managing for water clarity. Only after that had been taken care of should they shift their attention to manipulating the food web (2004).

Contemporary Work

The work by Guo et al. demonstrates new applications of the idea of manipulating food webs to achieve changes in lake productivity (2014). Taihu Lake is a major Chinese Lake that is experiencing blooms of toxic blue green algae. These algae produce toxins called microcystins that can be fatal for livestock, pets, and human swimmers. Rather than attempt to manipulate the lake by increasing the abundance of piscivores in the food web, Guo et al. attempted a different type of food web manipulation (2014). They increased the abundance of fish that directly consume phytoplankton by stocking silver and big head carp in enclosures.

The results of their small scale manipulation clearly demonstrated that this type of manipulation could potentially be effective at reducing phytoplankton and toxic blue green algae at larger spatial scales. They documented that the two species of carp significantly reduced the amount of Cyanophyta as well as the amount of zooplankton. More importantly, the amount of microcystin toxins in the enclosures was reduced by 70 – 94% relative to outside of the enclosures (Guo et al., 2014).

Similar to the long standing debates revolving around top down control biomanipulation of lake ecosystems, the work by Guo et al. is only a first step (2014). The experiment took place in enclosures and does not demonstrate whether this type of biomanipulation will be effective at the scale of an entire lake food web. Furthermore, the mechanism at play in the experiment could be fish herbivory, or it could be something tied to nutrient cycling. They recorded significant decreases in nitrogen concentrations in the enclosures, and significant increases in phosphorus concentrations. Further research is needed to disentangle the role of nutrient cycling from fish herbivory to determine exactly how the fish reduced the levels of phytoplankton and microcystin toxins.

Future of the Field

The field of biomanipulation in lakes is rich and growing. There is ongoing work on the question of when we should expect biomanipulation to be most effective and when we should focus on nutrient reduction to reduce eutrophication. In addition to work on top down control for lake management, there has been a growing desire to use this phenomenon to understand the dynamics of alternate stable states and regime shifts (Scheffer et al., 2012, Batt et al., 2013). Biomanipulation involves pushing a lake from a stable muddy water state to a stable clear water state. Without human intervention that lake should remain in whatever condition it is currently in.

Humans cause state shifts with water pollution all of the time. Cultural eutrophication of lakes is a great example. Many of the lakes that are dominated by algae and low water clarity today were at one time crystal clear. The transition from one state to another was not gradual; it tends to be very fast. Nutrient pollution continues over time and then one year the system flips from being clear water to having huge algae blooms. The new state then persists.

It has been said that an ounce of prevention is worth a pound of cure, and were we able to predict an impending regime shift than the huge cost of biomanipulation could be avoided completely. In large lakes, biomanipulation may not be feasible or cost effective. Furthermore, other types of state changes such as desertification or changes in global ocean circulation current may not within our power to reverse. With that goal in mind the early proponents of the top down control of lake ecosystems, the Cascade project based at the University of Wisconsin, Madison have been studying lake trophic cascades to determine if there are identifiable leading indicators of regime shifts.

In a recent experiment that took place in the same lakes, Peter and Paul Lakes in Michigan, where some of the original trophic cascade experiments were performed, researchers created a new trophic cascade (Scheffer et al., 2012, Batt et al., 2013). For this cascade they added the piscivores, largemouth bass, very slowly over several years to cause the system to flip to a clear water state slowly. During that period, sensors monitoring water chemistry at short time intervals, and daily sampling for fish and zooplankton gave a detailed high frequency record of the changes in the system leading up to the system flip (Scheffer et al., 2012, Batt et al., 2013).


This research showed that there are leading indicators that can tell us when a regime shift is coming (Scheffer et al., 2012, Batt et al., 2013). In the experiment, before the system changed to a clear water state, the frequency of different measures began to change. This change in frequency may herald an impending regime shift, and it could be applicable to other lakes. At the very least, this type of work could lead to improved lake monitoring to avoid shifts from clear water to eutrophic states before they occur. At most, the applications of this line of research could be far reaching beyond the field of limnology.


Batt, R.D., S.R. Carpenter, J.J. Cole, M.L. Pace, and R.A. Johnson. 2013. Changes in ecosystem resilience detected in automated measures of ecosystem metabolism during a whole-lake manipulation. Proceedings of the National Academy of Science 110:17398-17403

Carpenter, S.R., J.F. Kitchell, & J.R. Hodgson. 1985. Cascading trophic interactions and lake productivity. Bioscience 35: 634-639

Carpenter, S.R., J.F. Kitchell, J.R. Hodgson, P.A. Cochran, J.J. Elser, M.M. Elser, D.M. Lodge, D. Kretchmer, X. He, & C.N. von Ende. 1987. Regulation of lake primary productivity by food web structure. Ecology 68:1863-1876

Demelo, R., R. France, & D.J. McQueen. 1992. Biomanipulation – hit or myth? Limnology and Oceanography 37: 192-207

Guo, L., Q. Wang, P. Xie, M. Tao, J. Zhang, Y. Niu, & Z. Ma. 2014. A non-classical biomanipulation experiment in Gonghu Bay of Lake Taihu: control of Microcystus blooms using silver and bighead carp. Aquaculture Research. Online early

Hairston, N.G. & N.G. Hairston. 1993. Cause-effect relationships in energy-flow, trophic structure, and interspecific interactions. American Naturalist 142: 379-411

Meijer, M., I. Boois, M. Scheffer, R. Portielje, & H. Hosper. 1999. Biomanipulation in shallow lakes in The Netherlands: an evaluation of 18 case studies. Hydrobiologia 408/409: 13-30

Moss, B., D. Stephen, D.M. Balayla, E. Becares, S.E. Collings, C. Fernandez-Alaez, M. Fernandez-Alaez..... 2004. Continental-scale patterns of nutrient and fish effects on shallow lakes: synthesis of a pan-European mesocosm experiment. Freshwater Biology 49: 1633-1649

Scheffer, M., S.R. Carpenter, T.M. Lenton, J. Bascompte, W. Brock, V. Dakos, J. van de Koppel, I. van de Leemput, S.A. Levin, E. H. van Nes, M. Pascual, & J. Vandermeer. 2012. Anticipating critical transitions. Science 338: 344-348

Shapiro, J. & D.I. Wright. 1984. Lake restoration by biomanipulation: Round Lake, Minnesota, the first two years. Freshwater Biology 14: 371-383