Near-term phytoplankton forecasts reveal the effects of model time step and forecast horizon on predictability.

ABSTRACT: As climate and land use increase the variability of many ecosystems, forecasts of ecological variables are needed to inform management and use of ecosystem services. In particular, forecasts of phytoplankton would be especially useful for drinking water management, as phytoplankton populations are exhibiting greater fluctuations due to human activities. While phytoplankton forecasts are increasing in number, many questions remain regarding the optimal model time step (the temporal frequency of the forecast model output), time horizon (the length of time into the future a prediction is made) for maximizing forecast performance, as well as what factors contribute to uncertainty in forecasts and their scalability among sites. To answer these questions, we developed near-term, iterative foreca

SUBMITTER: Woelmer WM 

PROVIDER: S-EPMC9786628 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature