Rolling-SD bloom warnings in Cascade whole-lake experiments (2011–2019) follow the nutrient-driven mean rise; a linear-ramp test rejects a 1.5-fold rise in relative chlorophyll SD
Buelo et al. (2022) report that the rolling-window standard deviation (SD) of daily chlorophyll a, phycocyanin, dissolved oxygen and pH gave early warnings of algal blooms in whole-lake nutrient additions to Peter and Tuesday lakes, with Paul Lake as reference. We used the published daily data (EDI knb-lter-ntl.413.2, 2011-2019) and the original code. The code reproduced the published true-to-false alarm-rate ratios (2.6-8.3) exactly. Then we tested if the SD alarms carry information beyond the rise in mean level that the nutrients caused. On a log10 scale, the chlorophyll SD alarms fell from 56 to 9 alarm days in 332 pre-bloom nutrient days, and the phycocyanin alarms from 55 to 9 in 387 days. Without nutrients, chlorophyll SD increased as mean^1.24 (95% CI 0.90-1.73), and the mean change gave 87% of the pre-bloom log SD ratio between nutrient and reference lakes. A quickest-detection alarm on the chlorophyll mean gave alarms on 54% of pre-bloom nutrient days, with the same 4.3% false-alarm rate as the SD alarm. Surrogates that keep each lake-year's mean path and have constant (relative) noise gave 98% of the observed chlorophyll alarm days and 89-97% for the other variables (500 surrogates; 15-day trend). In synthetic data, a 3-fold rise in relative SD raised the published SD alarm count by only 23-31%, so this alarm responds mainly to the mean. The SD-of-log10 alarm is sensitive to such a rise. The observed count (9) matched the no-rise expectation (median 8) and rejects a 1.5-fold linear rise in relative chlorophyll SD by bloom start (3.5% of replicates as low) and a 2-fold rise for phycocyanin (1%). Conclusion: in these experiments the reported SD warnings are explained by the nutrient-driven rise in mean, and they do not give separate evidence of lost resilience. Limitations: 7 nutrient lake-years, 2 chlorophyll years without nutrients, one reference lake, a linear-ramp alternative model, and published definitions of bloom start and alarm periods.
early warning signals · critical slowing down · algal blooms · cyanobacteria · whole-lake experiment · variance · mean-variance scaling · quickest detection · surrogate data · Cascade lakes · North Temperate Lakes LTER · reproduction
References
6- challengesdoi:10.1002/eap.2616
We reproduce its temporal SD alarm rates exactly with its code and data, and show that the SD warnings of blooms follow the nutrient-driven rise in mean level, not a separate rise in relative variability.
- usesdoi:10.6073/pasta/5a9862187368b616bed8e20381343717
Daily chlorophyll, phycocyanin, DO saturation and pH for Paul, Peter and Tuesday lakes, 2011-2019 (EDI knb-lter-ntl.413.2, CC BY 4.0).
- usesdoi:10.5281/zenodo.5874868
Original tvsews R code (rolling-window statistics, quickest detection) and nutrient and bloom dates; GitHub commit 8d7a0fbb.
- doi:10.1002/ecm.1286
Earlier report of early warning signals before cyanobacterial blooms in the same whole-lake experiments (2013-2015).
- doi:10.1073/pnas.1612424114
Use of early warnings to stop nutrient addition in Peter Lake in 2015.
- Variance and autocorrelation trends did not improve 5-year forecasts of local disappearance beyond abundance and trend in BBS and BioTIME 2.0 count series sci:sha256:89762d1825eb305bfbd4a6020466f73808241a758601704c67378b578bdcd9c4
Related SCI result: variance and autocorrelation trends did not add forecast skill beyond abundance level and trend in bird and BioTIME count series.
Cited by
0 publicationsPublic catalog entries on Sciscape.
No incoming citations on Sciscape.