%ABuelo, C. [Department of Environmental Sciences University of Virginia Charlottesville Virginia]%ABuelo, C. [Department of Environmental Sciences; University of Virginia; Charlottesville Virginia]%ACarpenter, S. [Center for Limnology University of Wisconsin Madison Wisconsin]%ACarpenter, S. [Center for Limnology; University of Wisconsin; Madison Wisconsin]%APace, M. [Department of Environmental Sciences University of Virginia Charlottesville Virginia]%APace, M. [Department of Environmental Sciences; University of Virginia; Charlottesville Virginia]%BJournal Name: Limnology and Oceanography Letters; Journal Volume: 3; Journal Issue: 5; Related Information: CHORUS Timestamp: 2023-08-28 05:53:26 %D2018%IWiley Blackwell (John Wiley & Sons) %JJournal Name: Limnology and Oceanography Letters; Journal Volume: 3; Journal Issue: 5; Related Information: CHORUS Timestamp: 2023-08-28 05:53:26 %K %MOSTI ID: 10074493 %PMedium: X %TA modeling analysis of spatial statistical indicators of thresholds for algal blooms %XAbstract

Predicting algal blooms both within and among aquatic ecosystems is important yet difficult because multiple factors promote and suppress blooms. Statistical indicators (e.g., variance and autocorrelation) based on time series can provide warning of transitions in diverse complex systems, including shifts from clear water to algal blooms. Analogous spatial indicators have been demonstrated with models and empirical data from vegetated terrestrial ecosystems. Here, we test the applicability of spatial indicators to algal blooms using a nutrient‐phytoplankton spatial model. We found that standard deviation and autocorrelation successfully distinguished bloom state and proximity to transitions, while skewness and kurtosis were more ambiguous. Our findings suggest certain spatial indicators are applicable to aquatic ecosystems despite dynamic physical–biological interactions that could reduce detectable signals. The growing capacity to collect spatial data on algal biomass presents an exciting opportunity for application and testing of spatial indicators to the study and management of blooms.

%0Journal Article