Associations between fish health and Pfiesteria spp. in Chesapeake Bay and mid-Atlantic estuaries

Harmful Algae 5 (2006) 352–362 www.elsevier.com/locate/hal

Associations between fish health and Pfiesteria spp. in Chesapeake Bay and mid-Atlantic estuaries P. Tango a,*, R. Magnien b, D. Goshorn a, H. Bowers c, B. Michael a, R. Karrh a, D. Oldach c a Maryland Department of Natural Resources, 580 Taylor Avenue D-2, Annapolis, MD 21401, United States National Oceanic and Atmospheric Administration, 1305 East West Highway, Silver Spring, MD 20910, United States c Institute of Human Virology, University of Maryland School of Medicine, 725 Lombard Street, Baltimore, MD 21201, United States b

Received 1 January 2006; received in revised form 24 April 2006; accepted 30 April 2006

Abstract In response to concerns that there may be an association between harmful algal bloom (HAB) species and fish health, including the widespread use of fish health as one indicator of a possible HAB warranting further investigation, evidence for such an association was evaluated in Chesapeake Bay and other mid-Atlantic estuaries (1999–2001). A statistical approach was used, without invoking causality, to test whether there is an association between the prevalence of externally-visible lesions in fish populations above background levels and the presence of Pfiesteria spp. in co-located water and fish samples. Externally visible anomalies (e.g. ulcers, necrosis, parasites, etc.) were recorded for Atlantic menhaden (Brevoortia tyrannus) and all other fish collected. Polymerase chain reaction (PCR) techniques were used to test for the presence of Pfiesteria spp. in water samples collected at routine and rapid response sampling events. No actively toxic Pfiesteria was found during this study. Fine-scale (within a given sample site) and broad-scale (estuary-wide sampling) comparisons showed positive associations between externally-visible fish lesions in menhaden populations and the presence of Pfiesteria spp. in co-located samples. Logistic regression modeling of Pfiesteria detection probabilities as a function of prevalence of menhaden with lesions was significant (P = 0.0096). Reductions in the false positive (tests indicating Pfiesteria presence when its absent) and false negative (tests indicating Pfiesteria is absent when it is actually present) rates occurred when the minimum sample size threshold increased from 1 to 30 fish (P = 0.003–0.001). This association served as a useful field indicator of potential HAB activity that could warrant further field investigation and testing. # 2006 Elsevier B.V. All rights reserved. Keywords: Chesapeake Bay; Fish health; Harmful algal blooms; Maryland; Menhaden; Monitoring; PCR; Pfiesteria

1. Introduction Harmful algal blooms (HABs) have diverse effects including human illness and mortality, fish, mammal and bird mortalities, habitat degradation, increased * Corresponding author at: Maryland Department of Natural Resources, Tawes State Office Building, 580 Taylor Ave. D-2, Annapolis, MD 21401, United States. Tel.: +1 410 260 8651; fax: +1 410 260 8640. E-mail address: [email protected] (P. Tango). 1568-9883/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.hal.2006.04.008

susceptibility to disease, losses to aquaculture industry and economic hardships for affected communities (HARRNESS, 2005). Organisms exposed to HABrelated events may also show evidence of environmental stress via behavioral effects (domoic acid on sea lions: HARRNESS, 2005, cyanotoxins on fish: Christoffersen, 1996), internal organ damage (liver damage from cyanotoxins: Christoffersen, 1996) or lesions on dead and dying fish with an infectious etiological basis (Burkholder et al., 2001a; Glibert et al., 2002). Burkholder and Glasgow (1997) reported an association

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between the presence of juvenile menhaden (Brevoortia tyrannus) with externally visible epidermal lesions and toxic Pfiesteria activity in North Carolina estuaries. Burkholder and Glasgow (1997) and later Glasgow et al. (2001), in summarizing information on Pfiesteria outbreaks, pointed out that many fish kills involving menhaden with lesions have occurred in the absence of Pfiesteria spp. They noted, as well, that within the subset of fish kills linked to toxic Pfiesteria in North Carolina waters, nearly all Pfiesteria-related kills involved a high proportion of fish with lesions. A number of states along the Atlantic Coast of the US instituted surveillance programs for harmful algae that utilize fish health to varying degrees as an indicator that could trigger more intensive sampling (Magnien, 2001). Environmental data (e.g. water chemistry and phytoplankton community assessments) are often gathered at sites of fish disease outbreaks, fish kills, or reports of human health concerns following exposure to waterways. Assessments are conducted to determine if further action is warranted to protect the public from potential risks due to water contact or consumption of seafood. One of the primary reasons that fish have been used as indicators is that major challenges exist to rapidly identify multiple HAB species and toxins in an environmental setting, although this capability is rapidly evolving. Standard assays, for example, have been developed for PSP toxins, brevetoxins and okadaic acid (Anderson et al., 2001). Analytical chromatographic methods such as liquid chromatography, HPLC or mass spectrophotometric procedures are used to detect microcystins, anatoxins and saxitoxins (Chorus and Bartram, 1999; Carmichael et al., 2001; Nicholson and Burch, 2001). Algal toxins typically require more than a decade to characterize, and appropriate standards for routine analysis and detection are not yet available for various of these toxins, including Pfiesteria toxin(s) (Burkholder et al., 2005). Relatively rapid (<24 h) molecular techniques exist in the form of polymerase chain reaction (PCR) methods for identifying HAB species in water and sediment including P. piscicida and P. shumwayae (Rublee et al., 1999; Bowers et al., 2000; Oldach et al., 2000; Rublee et al., 2000, 2001; Saito et al., 2002; Wang et al., 2005; Bowers et al., this issue), but these analyses cannot distinguish actively toxic strains. Routine water sampling using PCR has revealed that Pfiesteria spp. are distributed throughout the Chesapeake Bay and coastal bays of Maryland (e.g. Rublee et al., 2000, 2001). Until recently, laboratory fish bioassays have been the only method to determine potential toxicity when linked with cell densities of Pfiesteria spp. Standardized fish

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bioassays (Marshall et al., 2000; Burkholder et al., 2001a; Gordon et al., 2002; Gordon and Dyer, 2005) were calibrated with known toxic strains of Pfiesteria and confirmed by tests for Pfiesteria toxin production by isolates from water samples collected during the kills (Moeller et al., 2001; Burkholder et al., 2005). The time to fish death has been related to the presence of an actively toxic population at a given estuarine fish kill. However, these tests are time-intensive, spanning days to weeks, and toxicity at the time of sample collection would be more conclusively resolved if methods were available to detect Pfiesteria toxin in field samples (Burkholder et al., 2005). Faced with the need for a rapid field indication of potentially toxic activity by Pfiesteria, the state of Maryland used unexplained fish kills (i.e., those not obviously associated with severe hypoxia, anoxia, chemical spills, strandings, commercial or recreational discards, sewage spills, temperature or salinity shock, spawning stress, etc.) and the presence of higher-thanbackground prevalence of fish with lesions as indicators of possible toxic Pfiesteria spp. or other HAB activity. Literature available at the time that these protocols were established suggested an association between fish kills, fish health and the presence of toxic Pfiesteria strains within certain ranges of salinity and temperature coinciding with certain other environmental conditions (Burkholder and Glasgow, 1997; Stow, 1999; Burkholder et al., 2001a; Brownie et al., 2003). There are many causes of fish kills or expressions of compromised fish health such as epidermal lesions (see Austin and Austin, 1993; Noga, 1993; Leatherland et al., 1998), so these factors were not used as proof of toxic Pfiesteria activity. Rather, sites of unexplained fish kills, fish morbidity and higher than background levels of lesions (based on the initial field investigations) have been used to identify sites that warranted further investigation and testing. This further testing included PCR and light microscopy for determination of possible HAB species and their cell densities, fish bioassays for detection of actively toxic strains of Pfiesteria spp. (Magnien, 2001; Burkholder et al., 2001a), and other laboratory procedures (e.g., LC/MS, ELISA) for direct phycoor cyanotoxin assessment. This study evaluates the validity of using higher-than-background prevalence of external fish lesions as indicators of encountering Pfiesteria spp. Statistical tests of association were based on field assessments of fish health and laboratory identification of Pfiesteria spp. in associated water samples collected from Chesapeake Bay waters and mid-Atlantic coastal bay estuaries of Maryland between 1999 and 2001.

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2. Methods 2.1. Sampling Concurrent sampling for fish species composition including an externally-visible health assessment and analysis for Pfiesteria spp. was conducted from 1999 to 2001 at sites throughout Maryland’s Chesapeake and Coastal Bay estuaries (Fig. 1). Toxic Pfiesteria activity was not detected during the study. Health assessments classified anomalies on fish as (1) abrasions, (2) necrotic skin or fin, (3) ulcer, (4) hemorrhagic skin or fin, (5) Petechia blister/cyst, (6) tumor, and (7) ‘‘others’’ (MD DNR Fisheries Service, 1998). ‘‘Others’’ included spinal deformities, emaciation, physical damage, cataracts, pop-eye, and healing anomalies. The categories necrotic skin/fin, hemorraghic skin/fin and ulcers were grouped as ‘‘lesions’’ for the analyses. Fish classified with abrasions were considered as possibly affected by the sampling and handling effort and, along with the diversity of anomalies defined by ‘‘others’’, were otherwise considered ‘healthy’ for this analysis.

Data used in these analyses were collected through two components of a monitoring program—routine versus rapid response. A third component – healthy rapid response – was developed as a control test during summer for comparison with investigations of unexplained fish kills or morbidity events at actual Rapid Response sites. These components are described below. 2.1.1. Routine monitoring Fish sampling was conducted biweekly April–October at approximately 35 sites routinely monitored year-round for water quality and PCR analysis in the Chesapeake and Coastal Bays (Fig. 1). Fish were collected by cast net (20 casts) or beach seine and evaluated for number and types of externally visible anomalies. Water samples for PCR analysis of the phytoplankton community were collected concurrently with the fish sampling efforts. The analyses utilized routine monitoring data where at least one menhaden was collected concurrently with water samples for PCR analysis. The analyses focused on juvenile menhaden to test the suggested relationship proposed in the literature, not

Fig. 1. Study area with locations of concurrent fish and Pfiesteria PCR sampling in the Maryland portion of the Chesapeake and Coastal Bays, USA, 1999–2001.

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as a cause and effect assessment but for the development of a potential HAB indicator. Menhaden are assumed to spawn in the coastal ocean from late fall to early spring and transported to nursery grounds within estuaries (Friedland et al., 1996). During autumn, temperature changes initiate emigration of the year 0 juveniles to the coastal ocean (Frieldland and Haas, 1988). Between spring and fall the juveniles on the nursery grounds in the Neuse/Pamlico system were concentrated by phytoplankton biomass gradients throughout the estuary. Juvenile menhaden were secondarily relating to salinity gradients as a function of gradients in primary productivity (Friedland et al., 1996). Similar patterns of fish relating to biological and chemical gradients observed in Friedland et al. (1989) are assumed to exist for other east coast estuaries such as the Chesapeake and Maryland Coastal Bays. Timing of juvenile menhaden availability was summer and fall. In 1998, for example, among priority tributaries sampled, no menhaden were captured during May and June but were captured from August to October (Lukacovic et al., 1998). The period July–October was thus selected in the analysis to reflect the time period during which juvenile menhaden would be present in the region studied, vulnerable to the sampling gear, and most likely to be used as an indicator of HAB activity warranting further investigation. 2.1.2. Rapid response monitoring Rapid response monitoring was conducted in cases of unexplained fish kills or fish morbidity events involving elevated prevalence of fish with externallyvisible lesions. A rapid response activity contained a minimum of two samplings over 2 weeks at the same site. Fish communities and water for PCR analysis were sampled concurrently at 1–5 sites within the geographic extent of the event. Fish were generally sampled with cast nets and external health evaluated as during routine monitoring. Investigations were continued initially based on fish health findings from a minimum of 30 fish. Sites were revisited and resampled at least weekly until the event ended (i.e., no further evidence of an ongoing fish kill or elevated lesion prevalence). As above, analyses were limited to data collected from July through October. Fig. 1 indicates the distribution of rapid response events during 1999–2001. 2.1.3. Healthy rapid response Healthy rapid responses referred to investigations at control sites (no evidence of active fish health event in progress) locations coincident with fish health investigations in other regions for use in statistical comparisons. Three rivers in Chesapeake Bay were

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chosen for the ‘‘Healthy Rapid Response’’ sampling: the Chicamacomico River, Warwick Creek (Choptank River), and the South River. Healthy menhaden populations were sampled at all three sites as per rapid response protocols for 3 weeks during August 2001. August was chosen as a month with elevated incidence of both lesioned menhaden and positive Pfiesteria PCR results in the Bay region. Since the objective was to evaluate Pfiesteria presence at sites of healthy vs. lesioned menhaden under similar levels of sampling effort, and the level of effort associated with actual rapid response events varied greatly, we selected actual rapid response events that were similar to levels of effort in August 2001 healthy rapid response monitoring. The measures of effort were identified and four actual rapid response events were selected that met all these criteria (Table 1). 2.2. PCR analysis Water samples collected for PCR analyses were received either fixed in Lugol’s solution (>24 h postcollection, routine samples) or as live samples (<24 h post-collection, rapid response samples). A 50 ml aliquot was centrifuged (
4000 rpm, 10 min) and the pellet re-suspended in cell lysis buffer supplied with a commercial kit (Puregene1 DNA Isolation Kit, Gentra Systems, Minneapolis, MN). The manufacturer’s instructions were followed for DNA extraction. Realtime PCR assays specific for P. piscicida and P. shumwayae were performed on samples as previously described (Bowers et al., 2000; erratum 2002). 2.3. Statistical analyses 2.3.1. Fine- and broad-scale analyses Statistical analyses were conducted on two scales. ‘‘Fine-scale’’ analyses tested the null hypothesis of no significant association between the prevalence of lesioned menhaden and Pfiesteria presence on a point sample basis. ‘‘Broad-scale’’ analyses tested the null Table 1 Effort associated with healthy rapid response sampling and corresponding criteria used to select actual rapid response events for inclusion in the analysis Effort criteria per event

Healthy rapid response

Actual rapid response

Sampling period (days) Separate sampling visits Total PCR samples Total menhaden collected

19–21 8 15–23 301–1306

14–28 5–11 5–33 216–1881

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hypothesis of no significant association between the incidence of lesioned menhaden and Pfiesteria presence in the same tributary reach, up to approximately 10 km range within similar salinity zones, and over a longer time scale (weeks). It is important to note that in all cases, our analyses were limited to testing for associations, and the analyses are not capable of providing insights about the mechanisms underlying any associations. 2.3.2. Binomial probability analysis provides sample fish-health status classification Binomial probability analysis was used to develop criteria on minimum levels of effects needed to classify a sample as ‘‘healthy’’ versus significantly different from background levels of anomalies. Raw counts can vary from one to thousands of fish in a sample affecting confidence in classifying health status. Under this indicator approach to decide on the potential need for intensified investigations, uncertainty in the fish health status classification impacts confidence in decisions about the need for additional sampling. A background level of lesion prevalence was needed to reference in the analysis. Fournier and Summers (1996) examined large collections of estuarine fish from 1990 to 1992 and considered 0.5% as the background prevalence of gross external abnormalities in the mid-Atlantic region and 0.7% in Gulf Coast estuaries. Reporting by the Maryland Department of Natural Resources (MD DNR) Fisheries Service program on regional sampling efforts between 1998 and 2000 indicated annual mean presence of externally visible lesions, regardless of species, was 0.46–0.97% (Rickabaugh et al., 2001). Prevalence of lesions on menhaden ranged between 1.7% and 3.0% during this study. Given the variations in lesion prevalence among the studies, multiple boundary conditions from one lesioned fish (regardless of the percent of the total catch the one fish represented) to 20% affected fish were used. This range covered a gradient of effects that was increasingly conservative in classifying the health status of the sample. This effort helped account for uncertainty in what might be considered background levels of lesion expression well above published levels. Fish sampling efforts usually captured 100 menhaden. Among 307 samples collected in routine and rapid response events for 2000, 277 (90.2%) contained 0–100 menhaden, 4.3% contained 101–200 and the remaining 5.5% >200 menhaden. To assist field personnel in decision making, binomial probability distributions for each potential catch size from 1 to 100

were calculated using the Bernoulli formula (1) (Dowdy and Weardon, 1983) and possible background lesion expectations ranging from one fish (which will represent a variable percentage of the total catch) to 20% levels of menhaden being affected. An a = 0.01 was used for setting up rejection regions for each sample size, separating ‘‘unhealthy’’ (statistically above the background level) from ‘‘healthy’’ (
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Fig. 2. Binomial probability based thresholds for health status classification of a fish collection as a function of total catch and the lesion level considered ‘‘background’’ prevalence, a = 0.01. The curves were developed for background level thresholds of 1%, 5%, 10%, and 20% prevalence of lesioned fish in the catch. Required minimum catch of lesioned fish is to consider a sample as ‘‘unhealthy’’ (at or above the value) or ‘‘healthy’’ (below the threshold value) for the chosen threshold.

where fish health and Pfiesteria samples were collected in tandem at a sampling site were used in the analysis. Overall significance of the model is based on a Score test with a x2 probability of significance. Similarly the significance of the slope parameter associated with percent lesions is tested with a chi-square based probability. The form of the logistic model was: logitðprobability of positive PfiesteriaÞ ¼ a þ b p:

(2)

where a = intercept of the regression, b = slope parameter, p = percent menhaden with lesions. If b is positive, then the probability of a positive Pfiesteria result increases with the percent of menhaden expressing lesions in the samples. The logit model can de converted to define the probability for detecting Pfiesteria in a sample by exponentiating the equation: probability of positive Pfiesteria detection ¼

eaþb p 1 þ eaþb p (3)

where a, b and p are defined in (2) and e = base of natural logarithms The predicted value from a binary logistic model generates an estimated probability of an observation being an event, i.e. a positive Pfiesteria result in this study.

2.3.4. Broad-scale analyses Broad-scale analyses were conducted to test for associations between the presence of lesioned menhaden and the presence of Pfiesteria spp. in the same general reach of a tributary and same general time period. One concern in moving beyond the sample-bysample comparisons of the fine-scale analyses was that any observed difference in Pfiesteria spp. between healthy and lesioned menhaden samples could be an artifact of sampling design. To address this concern, we conducted ‘‘Healthy Rapid Response’’ monitoring during August 2001 to evaluate the effect of sampling effort on the likelihood of finding Pfiesteria. 3. Results Significant positive associations were found between prevalence of menhaden with externally-visible lesions and the presence of Pfiesteria spp. in co-located fish and water samples (P < 0.05; Table 2). Positive associations (rejection of null hypothesis of no association) between lesioned menhaden and detections of Pfiesteria were found in all tests for all catch sizes considered where the prevalence of externally-visible lesions was greater than 5% (Table 2). In tests evaluating the null hypotheses using a statistically-based health status classification of fish samples the association was always significant when using 10% threshold and minimum catch of 20 menhaden. For thresholds 10% and minimum catch

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Table 2 Significance testing of the null hypothesis of no association between presence of Pfiesteria and fish health for rapid response samples, 1999–2001 Rapid response (1999–2001), menhaden health status thresholds

Fishers Exact test results, one-sided test for positive association P-values given for each test Minimum catch = 1 (n = 191)

Minimum catch = 10 menhaden (n = 138)

Minimum catch = 20 menhaden (n = 118)

Minimum catch = 30 menhaden (n = 98)

Health status of a sample was classified using the statistically based required number of lesioned fish associated with sample size and a selected threshold 0.15 Any lesion = unhealthy 0.09 0.10 0.04* 1% threshold 0.41 0.22 0.04* 0.03* * * * 10% threshold 0.04 0.02 0.01 <0.01* 20% threshold 0.08 0.06 0.03* 0.02* Health status of a sample was based on percent fish with lesions in the catch compared to a threshold and no adjustments for sample size 5% threshold 0.02* 0.03* 0.01* 0.02* 10% threshold 0.03* 0.04* <0.01* <0.01* 20% threshold 0.01* 0.03* <0.01* <0.01* *

P < 0.05.

<20, P-values ranged from 0.02 to 0.08 (Table 2). For lower thresholds of lesion prevalence and fish samples sizes <20 the null hypothesis was generally not rejected. Using the logistic regression approach with all point data from routine and rapid response monitoring efforts yielded a significant model: logitðprobability of detecting PfiesteriaÞ ¼ 1:4887 þ 0:00952 ðpercent menhaden with lesionsÞ (4) P = 0.0096 (Table 3). The positive slope parameter indicates a positive relationship between the percent menhaden with lesions in a sample and the probability of detecting Pfiesteria. At a probability of P > 0.26, the model correctly classifies 71.4% of all observations using a minimum sample size = 1 fish. The false positive rate in this result was 63% suggesting the field approach to rapid responses

has thus far been highly conservative because Pfiesteria is not always found. However, the false negative rate is also at its lowest value of 18.5% suggesting sites are infrequently misclassifed as being negative for Pfiesteria based on the prevalence of lesioned menhaden. Model significance was preserved when accounting for a minimum sample size of fish in the analysis. Again, as the minimum sample size threshold increased, model results showed a greater degree of correct classification for samples detecting Pfiesteria (Table 2). The false positive and false negative rates also decline when we exclude the smallest sample sizes from consideration. There was also a significantly greater percentage of PCR samples positive for Pfiesteria spp. associated with the actual rapid response samples (57%; two samples Wilcoxon rank sums tests with continuity correction, P < 0.05, Conover, 1971; DiIorio and Hardy, 1996) compared to the healthy rapid response tests (4.3%). One potential concern with the healthy rapid response

Table 3 Logistic regression model results, all Pfiesteria and fish health data 1999–2001 Model run (cutoff for minimum sample size)

P-value on the x2 test of b = 0

1 10 20 30

0.0096 0.0029 0.0007 0.0001

Model parameters Intercept

1.4887 1.6654 1.8591 2.0752

Percent Anomalies (b, slope parameter estimate) (P = <0.0001) (P = <0.0001) (P = <0.0001) (P = <0.0001)

0.00952 (P = 0.0106) 0.0157 (P = 0.0038) 0.0208 (P = 0.0012) 0.0279 (P = 0.0004)

Best % correct classification

% False positives

% False negatives

N

71.4 75.4 77.7 80.8

63 59.5 57.7 52.6

18.5 17.6 16.5 14.6

322 224 184 156

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analysis is that August 2001 might be, in some way, an anomalous month for Pfiesteria spp. presence and, therefore, inappropriate to use as a reference period. A similar analysis was conducted comparing July through October 1999–2001 rapid response PCR results to August 6–August 27, 2001 rapid response PCR tests. Wilcoxon tests showed the data sets were not significantly different (P > 0.05) in detection of Pfiesteria via PCR and therefore we concluded that August 2001 was not anomalous in the context of our study period. The broad-scale analysis was performed first by calculating the percentage of positive routine PCR samples collected from July through October 2000– 2001 where at least one menhaden was collected (n = 135). Results were compared to the percentage of positive PCR samples collected at rapid response events July through October 1999–2001 (n = 14). The total percentage of PCR positives for Pfiesteria spp. was calculated for each event and then averaged across all events. Greater percentages of lesioned menhaden were found in rapid response events (29.0%) than during routine sampling (8.1%). At the tributary scale, the percentage of PCR samples positive for Pfiesteria spp. was 27.0% (n = 14) in the rapid response sampling, which was significantly different (Wilcoxon two sample test, P < 0.001) from 14.1% (n = 135) in the routine sampling efforts. No association between fish health and Pfiesteria spp. was found in tests solely based on Routine monitoring data where fish lesion incidences were generally close to background levels. 4. Discussion The positive association between the prevalence of externally-visible lesions in menhaden populations and the presence of Pfiesteria in co-located water and fish samples is evident at multiple scales and is, to our knowledge, the first statistically-rigorous documentation of this association in the field. This association is broadly evident when no sample size restrictions are imposed in assessing the health of fish populations. The association remains evident when conservative (i.e. minimum sample size) fish population health assessments are made and also with a gradient in the definition of possible background levels of lesion prevalence. Despite this strong association, it is important to re-emphasize that these analyses are not appropriate to suggest a cause-andeffect relationship between menhaden lesions and Pfiesteria spp. However, positive associations between the prevalence of lesions in menhaden populations and PCR results for the presence of Pfiesteria spp. support the

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use of externally-visible lesions in menhaden as a valid, if imprecise, screening tool for this genus of harmful algae, at least in the region studied. Ulcerative lesions are among the most prevalent forms of gross abnormalities in fish (Sindermann, 1988; Fournier and Summers, 1996). Examination of lesions on the menhaden collected from mid-Atlantic waters prior to (Ahrenholz et al., 1987) and during the period of this study in the Bay (Kane et al., 1998; Blazer et al., 1999; Vandersea et al., 2006) typically revealed the presence of fungal organisms, although lesions with fungi have not consistently been found in other studies (see Glasgow et al., 2001; Law, 2001). Law (2001), for example, found that fungal hyphae occurred in only 34% of lesions on
190 Atlantic menhaden examined from North Carolina estuaries, which sustained most of the reported toxic Pfiesteria outbreaks in the 1990s (Glasgow et al., 2001). Speculation as to cause-andeffect relationships between the anomalies defined as lesions and Pfiesteria spp. has been the source of considerable research and debate for more than a decade (first linked by Noga et al., 1995; Kane et al., 1998; Blazer et al., 1999, 2000; Dykstra and Kane, 2000; Noga, 2000; Law, 2001; Glasgow et al., 2001; Vogelbein et al., 2001; Kiryu et al., 2002). Several authors reported associations between the presence of Pfiesteria spp. and damage to fish epidermis, based on laboratory and field work (Noga et al., 1995; Burkholder and Glasgow, 1997; Vogelbein et al., 2002). More recently, Burkholder et al. (2005) demonstrated that epidermal lesions formed in finfish that were placed into ultra-filtered water from fishkilling Pfiesteria cultures, absent Pfiesteria cells but containing Pfiesteria toxin, in comparison to no lesion formation in unexposed control fish. Burkholder et al. (2001b) pointed out that a Pfiesteria-released toxin, together with physical damage from feeding activity of the dinoflagellates, would both damage the epidermis and allow invasion by secondary, lesion-causing pathogens. In other situations, both menhaden lesions and Pfiesteria spp. presence could be stimulated by a third, independent variable such as Aphanomyces spp. or other disease agent impacting fish health, as suggested by Burkholder et al. (2001a) and Glasgow et al. (2001). Law (2001) stated that ‘‘fish literally swim in a sea of pathogens’’ that may contain fungi, bacteria, parasites, viruses and toxins. Nutrient-enriched environmental conditions may then be suitable to other toxins, virulent strains of Vibrio spp. (Burkholder et al., 2001a) and, as evidenced by work of Blazer et al. (1999), Aphanomyces-infected fish among other infectious and pathogenic organisms.

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Fish kills and fish showing signs of stress may also be indicators of biotoxic activity of other harmful algal bloom species. With the discovery of toxicity in Karlodinium veneficum (=Gyrodinium/Gymnodinium galatheanum, Karlodinium micrum; see Bergholtz et al., 2006) in the US, Kempton et al. (2002) and Deeds et al. (2002) demonstrated hemolytic, ichthyotoxic and cytotoxic responses of both bloom samples and clonal isolates (it should be noted that the toxin(s) has not yet been fully characterized). The later publication focused on repeated fish kills associated with blooms of K. veneficum at Hyrock Fish Farm (Manokin River, Princess Anne, MD) during 1996– 1999. A retrospective analysis of Chesapeake and Coastal Bay monitoring data concluded that eight kills between 1988 and 2002 were probable, possible, or associated with K. veneficum cell concentrations that have yielded sufficient toxicity to kill fish in laboratory testing (Goshorn et al., 2004). It should be noted that the four fish kills thus far related to toxic Pfiesteria activity in Chesapeake Bay tributaries (Glasgow et al., 2001; Magnien, 2001) were associated with low levels of K. veneficum relative to the cell densities known to cause fish death (104 cells of K. veneficum ml1) (see Kempton et al., 2002). An increasing diversity of algal and cyanobacteria species are being linked with fish disease and fish kill events around the world (Glibert et al., 2005). Judicious investigations into the algal assemblages, water quality conditions and physiological condition of fish involved in these events will aid in the identification of potential relationships between fish health and HABs which can then be tested more rigorously for modes of action in controlled experiments. Acknowledgements Funding for the work was provided by NOAA Grant NA17OA1337. We thank MD DNRs Monitoring and Non-tidal Assessment and Fisheries Service sections for environmental and fisheries sampling efforts and the Sarbanes-Oxford Laboratory involved in rapid response and necropsy work. We further thank the North Carolina State University laboratory of Dr. JoAnn Burkholder (Center for Applied Aquatic Ecology) for scanning electron microscopy (SEM) to confirm species identifications and standardized fish bioassays to test for the presence of actively toxic strains; Dr. Peter Moeller at the National Oceanic and Atmospheric AdministrationNational Ocean Service Marine Biotoxins Program for related Pfiesteria toxin analysis; Dr. Karen Steidinger and the Florida Fish and Wildlife Conservation

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