Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Forecasting annual cyanobacterial bloom biomass to inform management decisions in Lake Erie

Filetype[PDF-1.93 MB]


Details You May Also Like

Details:

  • Journal Title:
    Journal of Applied Remote Sensing
  • Personal Author:
  • NOAA Program & Office:
    NOS (National Ocean Service)
  • Description:
    Blooms of the toxic cyanobacteria, Microcystis aeruginosa, have been both a public health and ecological concern in Lake Erie for over a decade. Although models were previously developed to forecast cyanobacterial bloom severity, the recent few years of bloom severity observations indicate the need to update these empirical models. The models that best estimate the bloom biomass use the Maumee River discharge or total bioavailable phosphorus (TBP) loading from March through July. TBP is the sum of the dissolved reactive phosphorus and the proportion of particulate phosphorus that is bioavailable, corrected for loss due to settling in the river. In years when average June water temperatures were too low for Microcystis growth (<17 degrees C), the July loads were excluded. As total phosphorus (TP) load includes much phosphorus that is not bioavailable (or reaches the lake), the load of TBP was considered, and it provided a model that better explained the blooms than the TP load. Residual discrepancies between predicted and observed blooms may involve factors such as the timing of the majority of the spring loads (e.g., most in March or most in June or July) and potential influence from an extremely large bloom in the previous year. The most extreme loads, such as seen in 2015, may cause different responses than more moderate loads. The models estimate bloom size in most scenarios observed and can serve as the foundation for setting nutrient reduction targets to decrease the occurrence of blooms in western Lake Erie. (C) 2016 Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.
  • Source:
    Journal of Great Lakes Research, 42(6), 1174-1183.
  • DOI:
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files

More +

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.26