Search for: All records

Regime shifts have large consequences for ecosystems and the services they provide. However, understanding the potential for, causes of, proximity to, and thresholds for regime shifts in nearly all settings is difficult. Generic statistical indicators of resilience have been proposed and studied in a wide range of ecosystems as a method to detect when regime shifts are becoming more likely without direct knowledge of underlying system dynamics or thresholds. These early warning statistics (EWS) have been studied separately but there have been few examples that directly compare temporal and spatial EWS in ecosystem‐scale empirical data. To test these methods, we collected high‐frequency time series and high‐resolution spatial data during a whole‐lake fertilization experiment while also monitoring an adjacent reference lake. We calculated two common EWS, standard deviation and autocorrelation, in both time series and spatial data to evaluate their performance prior to the resulting algal bloom. We also applied the quickest detection method to generate binary alarms of resilience change from temporal EWS. One temporal EWS, rolling window standard deviation, provided advanced warning in most variables prior to the bloom, showing trends and between‐lake patterns consistent with theory. In contrast, temporal autocorrelation and both measures of spatial EWS (spatial SD, Moran's  I) provided little or no warning. By compiling time series data from this and past experiments with and without nutrient additions, we were able to evaluate temporal EWS performance for both constant and changing resilience conditions. True positive alarm rates were 2.5–8.3 times higher for rolling window standard deviation when a lake was being pushed towards a bloom than the rate of false positives when it was not. For rolling window autocorrelation, alarm rates were much lower and no variable had a higher true positive than false positive alarm rate. Our findings suggest temporal EWS provide advanced warning of algal blooms and that this approach could help managers prepare for and/or minimize negative bloom impacts.

 

Resilience was compared for alternate states of phytoplankton pigment concentration in two multiyear whole‐lake experiments designed to shift the manipulated ecosystem between alternate states. Mean exit time, the average time between threshold crossings, was calculated from automated measurements every 5 min during summer stratification. Alternate states were clearly identified, and equilibria showed narrow variation in bootstrap analysis of uncertainty. Mean exit times ranged from 13 to 290 h. In the reference ecosystem, Paul Lake, mean exit time of the low‐pigment state was about 100 h longer than mean exit time of the high‐pigment state. In the manipulated ecosystem, Peter Lake, mean exit time of the high‐pigment state exceeded that of the low‐pigment state by 30 h in the cascade experiment. In the enrichment experiment mean exit time of the low‐pigment state was longer than that of the high‐pigment state by about 100 h. Mean exit time is a useful measure of resilience for stochastic ecosystems where high‐frequency measurements are made by consistent methods over the full range of ecosystem states.

 

Ice‐off dates on lakes are some of the longest phenological records in the field of ecology, and some of the best evidence of long‐term climatic change. However, there has been little investigation as to whether the date of ice‐off on a lake impacts spring and summer ecosystem dynamics. Here, I analyzed 274 years of long‐term data from eight north temperate lakes in two climate zones to address whether lakes have ecological memory of ice‐off in the subsequent summer. Five metrics were investigated: epilimnion temperatures, hypolimnion temperatures, hypolimnetic oxygen drawdown, water clarity, and spring primary productivity. The response of the metrics to ice‐off date were variable across latitude and lake type. The northern set of lakes stratified quickly following ice‐off, and early ice‐off years resulted in significantly warmer hypolimnetic temperatures. Oxygen depletion in the hypolimnion was not impacted by ice‐off date, likely because in late ice‐off years the lakes did not fully mix. In the southern lakes, ice‐off date was not correlated to the onset of stratification, with the latter being a more dominant control on hypolimnetic temperature and oxygen. The implications of these findings is that as ice‐off date trends earlier in many parts of the world, the lakes that will likely experience the largest changes in spring and summer ecosystem properties are the lakes that currently have the longest duration of lake ice. In considering a future with warmer winters, these results provide a starting point for predicting how lake ecosystem properties will change with earlier ice‐off.

 

The data are associated with the following manuscript: Hanson, P. C., Ladwig, R., Buelo, C., Albright, E. A., Delany, A. D., & Carey, C. (2023). Legacy phosphorus and ecosystem memory control future water quality in a eutrophic lake. Lake water and ice observational data and lake bathymetry are from the North Temperate Lakes Long Term Ecological Research program. Brief abstract of the work: To investigate how water quality in Lake Mendota might respond to nutrient pollution reduction, we used computer models to simulate the elimination of phosphorus inputs from the catchment and track water quality change. The data herein are used to drive and calibrate the model. In addition, model code and simulation output are included as "other entities."