The ecological recovery of lakes damaged by industrial emissions could take decades longer than originally expected, even when acidity levels in many lakes have already returned to normal, according to a Queen’s study.
“Since emissions reductions started coming into effect, ecologists have been studying lakes looking for signs of recovery, and they anticipated finding these signs soon,” says Derek Gray, a graduate student in Biology. “But we’re starting to realize that there’s no straight path back to recovery. There are many other ecological processes involved in the recovery of acid-damaged lakes besides the actual pH levels.”
Mr. Gray (seen in this photo, studying the recovery of zooplankton in acid-damaged lakes in Killarney Provincial Park) recently co-authored a study demonstrating how environmental conditions like acidity levels in lakes interact with organisms’ dispersal rates. High dispersal rates mean that a species driven to extinction by acidification will arrive more frequently at recovering lakes, increasing the chances for successful recolonization.
Mr. Gray and his team ran experiments to test how the joint impacts of dispersal levels and pH levels influence zooplankton recovery in Ontario’s Killarney Provincial Park lakes. Acid-sensitive zooplankton species have started to recolonize very slowly after going extinct in some areas. After several years in lakes that have returned to level 6 pH—the supposed magic number for biological recovery—some zooplankton still seem have difficulty recolonizing lakes. Mr. Gray hypothesized that the Allee effect, a phenomenon whereby populations grow more slowly than expected at low densities, might be responsible for the slow recolonization of acid-damaged lakes.
The researchers discovered that pH levels exaggerate the Allee effect in the case of acid-sensitive zooplankton, making the recolonization of lakes with low pH levels more difficult than those with high pH levels. This helps explain the delayed recovery of zooplankton in lakes recovering from acidification.
“It would be great if we could pull this type of information together and develop models to simulate recovery. Maybe we could then avoid future problems by talking exactly about what certain management choices and behaviours will mean for the environment,” says Mr. Gray.
The study was recently published in Ecological Applications.