Red Tide Semantics and Statistics
Mary C. Christman1, Jacob Tustison2, Karen A. Steidinger2,3
1
University of Florida, Gainesville, FL
Florida Fish and Wildlife Conservation Commission, St. Petersburg, FL
3
University of South Florida, St. Petersburg, FL
2
When monitoring for harmful algal blooms part of the problem is recognizing when a bloom is
occurring and what the likely trajectory is. As a result, in coastal monitoring programs for
harmful algal blooms, extensive coastlines such as Florida can be problematic for sampling
strategy. This is particularly true for species such as Karenia brevis if three dimensional sampling
is not practical because of areal expanse, depth, and rapid assessment needs. Until coastal ocean
observing systems are in place for harmful algae and/or their toxins, point sampling is the usual
strategy of data collection but its usefulness depends on location, depth, and timing. Where point
sampling has been particularly effective has been on ship cruises that sampled fixed stations
along transects from inshore to offshore, surface to bottom. Such cruises are in the Florida Fish
and Wildlife Conservation Commission’s Red Tide Database, e.g., cruises by USFWS, NASA,
Florida Department of Natural Resources, Florida Department of Environmental Regulation,
Mote Marine Laboratory, and ECOHAB. Compounding the potential difficulties of the choices of
sample station location, depth and frequency of sampling are the choices of sample and
subsample sizes for determining abundance of cells. For example, in the Florida program, up to a
one liter water sample may be collected and fixed with Lugol’s solution then a pooled 3 ml
subsample is enumerated to derive an estimate of abundance. The limit of detection for this
protocol is 333 cells L-1 and the results are scaled up with the attendant increase in the uncertainty
of the estimate. This can be an issue when one thousand cells per liter represents background
levels in the Gulf of Mexico and 5000 cells L-1 is the regulatory limit that activates closure of
shellfish beds inshore. On the other hand, red tides are detectable from satellites typically at
>50000 cells L-1 which is a developing or ongoing bloom. In addition, K. brevis blooms have
penetrated coastal waters along the bottom without surface expression until nearshore and so
would not be detectable by satellite or by data collected only in surface waters. The Florida Red
Tide database, principally from event response cruises, is composed of about 80% surface sample
results and about 20% bottom results (>90000 samples If K. brevis is not recorded in surface
samples or listed as “present” does that mean that a bloom is not somewhere around, perhaps on
the bottom? What is the probability of a K. brevis bloom being somewhere in nearby coastal
waters if a sample has a count of 20000 cells L-1? What is the probability of a bloom in nearby
coastal waters if surface water from 30 stations had “zero” records? Is a “negative” or “zero”
record a result of small sample size, e.g. 1 liter vs 10 liters, or counts less that the detection limit?
Is it necessary in the case of K. brevis to monitor at least surface and bottom rather than just
surface water samples to detect potential blooms or bloom development or is surface sampling
enough depending on what stage of the bloom is being sought and at what distance offshore?
What K. brevis surface count estimate is indicative that a bloom is developing? What is the
probability, based on a single count or a cluster of counts, that a red tide is present, if a red tide is
defined as 10000, 50000 or 100000 cells L-1? To address these questions and others, we apply
Bayesian and other i statistical approaches to data from the Florida database and results will be
discussed.