Science Inventory

Spatial and Temporal Dynamics of Cyanobacterial Blooms in Rhode Island Ponds – an Update for the Friends of Warwick Pond

Citation:

Shivers, S., J. Hollister, B. Kreakie, AND W. Milstead. Spatial and Temporal Dynamics of Cyanobacterial Blooms in Rhode Island Ponds – an Update for the Friends of Warwick Pond. Friends of Warwick Pond, Warwick, RI, May 16, 2019.

Impact/Purpose:

Most data on productivity in lakes and ponds is collected infrequently and at few locations within a given lake. This presentation summarizes the first two years of a study of Warwick Pond in Warwick, Rhode Island to address this limitation. The impact of this work is that we will now be able to examine spatial and temporal variability of harmful algal blooms at scales that were previously difficult to assess. The first two years of data we have collected suggests changes to the dynamics of blooms at these finer scales. This is a progress report to the Friends of Warwick Pond lake association.

Description:

Cyanobacteria are natural components of freshwater ecosystems. When conditions are favorable (e.g., high nutrient inputs), cyanobacteria can form dense blooms that have negative effects on human and animal health, ecosystem functioning, and aesthetics. When blooms occur they can often develop rapidly requiring frequent sampling to adequately capture bloom dynamics. The purpose of this study was to investigate the spatial and temporal variation of cyanobacterial blooms in several Rhode Island ponds and in this presentation we focus on the results from Warwick Pond. Seven sites were sampled weekly or biweekly between June and November in 2017 and 2018. Physical parameters were measured at all sites, and water samples were collected for chlorophyll a and turbidity analyses. Our sampling indicated fine scale variability that may be important in better understanding cyanobacterial bloom events. The results of this study will be used to evaluate potential bloom indicators, such as temperature, and eventually develop predictive models based on how the indicators vary through space and time.

Record Details:

Record Type:DOCUMENT( PRESENTATION/ SLIDE)
Product Published Date:05/16/2019
Record Last Revised:06/28/2019
OMB Category:Other
Record ID: 345615