by Adam Hinterthuer – When it comes to easing a lake’s water quality woes, there’s no such thing as a quick fix. Lakes and reservoirs across the U.S. suffer from problems like excessive algal growth and deep water “dead zones,” both of which are fueled by human development, agriculture and other land use changes sending high levels of fertilizers and nutrient-rich soils running into their waters.
Keeping those excess nutrients out is the main goal of many lake conservation efforts but, according to a study in the journal JGR Biogeosciences, “water quality in lakes has shown troubling resistance to improvement, despite recognition of the problem and management action intended to reduce nutrient loads.”
But that isn’t necessarily a sign that efforts aren’t working, says Paul Hanson, a research professor at the UW-Madison Center for Limnology and lead author of the report.
In fact, he says, “resistance to improvement” can actually be one step on the road to recovery.
Hanson and his team used four decades’ worth of data on Lake Mendota in Madison, Wisconsin to inform and develop a long-term computer model that could predict water clarity, algae growth and other conditions on the lake. They then simulated scenarios of dramatic reductions in phosphorus – the nutrient most responsible for Lake Mendota’s green waters – and modeled the lake’s response over time.
What they found, Hanson says, is essentially “five phases of recovery.”
The first phase is a quick pay off. “Water clarity improves right away,” Hanson says. “If you can just reduce the load of nutrients, especially phosphorus, coming into a lake, it won’t get us to a pristine state, but it will help produce noticeably clearer waters.”
But after that initial gain, phase two kicks in, and that phase is defined by a lag in the system. Even though nutrient loading is still going down and the waters have begun to clear, excessive algae growth and oxygen-starved dead zones can persist “for decades to longer than a century under [even] the most aggressive nutrient reduction scenario,” according to the report.
The two main forces at play, Hanson says, are the long legacy of phosphorus and what he and his team call “ecosystem memory.”
Phosphorus is considered a “legacy pollutant” because it is hard to flush it out of a system once it’s in. It can build up in soils to the point that, even if no new fertilizer is being applied to the ground to grow crops, phosphorus saturated topsoil can continue washing into the lake. And, once it’s in a lake, a lot of phosphorus that settles to the bottom of the lake gets churned back up into the water column through wind and waves action in the spring. Flushing all of this excess phosphorus out of a system can take decades.
At the other end of the equation is ecosystem memory. In short, it is a way of explaining how “something that happened a while ago in the ecosystem can still have an effect on what’s happening now,” Hanson explains. For example, a nutrient-rich lake can support a lot of plant and animal life. Removing phosphorus from the equation doesn’t make those organisms disappear. They still live out their life cycle and take advantage of what nutrients are left.
Ecosystem memory and pollution legacy are important to understand, Hanson says, because they can make it seem like lake conservation efforts aren’t working even as they are a sign that the lake is in the second of its five phases of change.
If researchers and resource managers know that a lag in improvement is part of the process, they are more likely to persist in water quality improvement efforts, trusting that phase three – the acceleration of positive change in the ecosystem – is just around the bend.
Rounding out the “five phases of change” are a fourth, slower period of improving conditions until, in the final phase, the lake moves into a new state of moderate nutrient loads and fewer water quality problems.
The take home messages of the report are two-fold, Hanson says. For starters, his study underscores how long-term data is crucial to understanding lake dynamics.
Studies like Hanson’s are rare, primarily because there is a lack of real-world data to test these models against and make sure they’re accurate.
Luckily for Hanson and his team, Lake Mendota is a study site in the National Science Foundation’s North Temperate Lakes Long-Term Ecological Research program. Scientists at the UW-Madison Center for Limnology have been conducting research and routine monitoring on Lake Mendota since the 1980s and these decades of data allowed Hanson and his team to calibrate their computer models, increase their confidence in predictions and not be fooled by year-to-year variability in the lake.
The second message, Hanson says, is that it is important to keep going in freshwater conservation efforts – no change can actually be a sign that a system is shifting into a new state.
“It’s easier to break something than to fix it,” Hanson says. Or, in terms of a lake, “it’s easier for something to go in than come out.” While it may be disappointing to learn that the pay off of lake conservation efforts can be an exercise in patience, his study does lay out some guideposts for evaluating our efforts. And, it points to an important thing to remember.
“If you want some modest change [in water quality] for yourself, we can do that now,” Hanson says. “But if you want change for your grandchildren, well, now we have to be persistent.”