Nutrient Management Strategy Science Plan Report

The San Francisco Bay (SFB) estuary receives large inputs of the nutrients nitrogen and phosphorous from anthropogenic sources, and has the potential to suffer negative impacts from nutrient overenrichment. Nutrient concentrations in SFB exceed those in other estuarine ecosystems where degradation is strongly expressed. To date, SFB has shown resistance to some of the classic symptoms of nutrient over-enrichment, such as excessive phytoplankton biomass as chlorophyll-a (chl-a) and low dissolved oxygen (DO). Recent observations, however, suggest that SFB’s resistance to nutrient enrichment is weakening, and have generated concern that SFB may be trending toward, or may already be experiencing, adverse impacts due to its high nutrient loads. In response to these concerns, the San Francisco Bay Regional Water Quality Control Board (SFBRWQCB) worked collaboratively with stakeholders to develop the San Francisco Bay Nutrient Management Strategy (NMS).¹ The NMS lays out an overall approach for developing the underlying science to support nutrient management decisions.

This report presents a Draft Science Plan for implementing the SFB NMS. The report’s main goals include:

1. 1. 1. Lay out a multi-year Science Plan representing a logical sequence of studies to inform major management decisions, assuming a time-line of 10+ years.
      2. Develop an approach and rationale for sequencing and prioritizing among studies, and identify specific high-priority studies, in particular those that should proceed in FY2016- 2018.
      3. Provide realistic estimates of the time-frame and funding needed to support a Science Plan that will successfully inform management decisions.

The Draft Science Plan was developed in 2014-15 with input from science advisors (Table 1.1), the NMS Steering Committee, and the NMS Nutrient Technical Work Group (Fig. 1.1). Projects are described in more detail in the first 1-3 years, and in increasingly less detail over time, recognizing that the Science Plan will be iteratively refined based on new insights gained as work progresses.