1. Long-term declines in chlorophyll a and variable phenology revealed by a 60-year estuarine plankton time series.
- Author
-
Thibodeau PS, Puggioni G, Strock J, Borkman DG, and Rynearson TA
- Subjects
- Estuaries, Ecosystem, Plankton physiology, Plankton growth & development, Biomass, Chlorophyll metabolism, Chlorophyll A metabolism, Chlorophyll A analysis, Seasons, Climate Change, Phytoplankton physiology, Phytoplankton growth & development
- Abstract
Long-term ecological time series provide a unique perspective on the emergent properties of ecosystems. In aquatic systems, phytoplankton form the base of the food web and their biomass, measured as the concentration of the photosynthetic pigment chlorophyll a (chl a ), is an indicator of ecosystem quality. We analyzed temporal trends in chl a from the Long-Term Plankton Time Series in Narragansett Bay, Rhode Island, USA, a temperate estuary experiencing long-term warming and changing anthropogenic nutrient inputs. Dynamic linear models were used to impute and model environmental variables (1959 to 2019) and chl a concentrations (1968 to 2019). A long-term chl a decrease was observed with an average decline in the cumulative annual chl a concentration of 49% and a marked decline of 57% in winter-spring bloom magnitude. The long-term decline in chl a concentration was directly and indirectly associated with multiple environmental factors that are impacted by climate change (e.g., warming temperatures, water column stratification, reduced nutrient concentrations) indicating the importance of accounting for regional climate change effects in ecosystem-based management. Analysis of seasonal phenology revealed that the winter-spring bloom occurred earlier, at a rate of 4.9 ± 2.8 d decade
-1 . Finally, the high degree of temporal variation in phytoplankton biomass observed in Narragansett Bay appears common among estuaries, coasts, and open oceans. The commonality among these marine ecosystems highlights the need to maintain a robust set of phytoplankton time series in the coming decades to improve signal-to-noise ratios and identify trends in these highly variable environments., Competing Interests: Competing interests statement:The authors declare no competing interest.- Published
- 2024
- Full Text
- View/download PDF