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BULLETIN OF MARINE SCIENCE, 80(3): 805–821, 2007

HABITAT ASSOCIATIONS OF LARGE-BODIED MANGROVESHORELINE FISHES IN A SOUTHWEST FLORIDA ESTUARY AND THE EFFECTS OF HURRICANE DAMAGE Marin F. D. Greenwood, Charles F. Idelberger, and Philip W. Stevens ABSTRACT

We used 183-m seines to study the effects of canopy damage by Hurricane Charley (August 2004) on the use of red mangrove Rhizophora mangle Linnaeus shorelines by large-bodied (> ~100 mm SL) fishes in Charlotte Harbor (Florida, USA). No significant relationship was found between proportion of the shoreline that was damaged and fish-assemblage structure in the year following the hurricane; however, temperature, water depth, and salinity did influence fish-assemblage structure. Post-hurricane fish assemblages were not notably different from pre-hurricane (1996–2004) assemblages. Despite wide-ranging loss of canopy, defoliation, and mortality of red mangroves, prop-root structure remained largely intact, which may have minimized gross changes in the assemblages of large-bodied fish along the mangrove shorelines during the first post-hurricane year. The effects of habitat damage on the fish assemblages may yet be manifested due to continued deterioration of existing prop-root structure and the apparent slow rate of recolonization of red mangroves in the area. Also, the effect of widespread mangrove mortality on the many other mangrove functions (e.g., primary productivity, food-web, and nutrient dynamics) may ultimately lead to system-level changes that affect the abundance and condition of large-bodied fish.

Mangrove shorelines are important habitats for fishes (Kathiresan and Bingham, 2001), mostly because they provide areas that are valuable for feeding and refuge from predation (Manson et al., 2005a). Evidence suggests that mangrove carbon does not directly contribute to fish diets, but instead that mangroves form substrates for various epibionts (both primary producers and consumers) that fish may eat (Kieckbusch et al., 2004). Refuge from predators may be provided by canopy shade and prop-root structural complexity (Laegdsgaard and Johnson, 2001, Cocheret de la Morinière et al., 2004, Ellis and Bell, 2004). There is debate over the value of mangroves as nursery habitat, but juveniles of some species appear to be mangrove-dependent (reviewed by Manson et al., 2005a). Very few studies have documented clear links between fishery catches of finfish and extent of mangroves in adjacent areas (Manson et al., 2005b). Correlations tend to be relatively weak and merely imply enhanced nursery function without directly addressing causative factors (Manson et al., 2005a). Two recent fishery-independent studies suggested relatively high fish abundance and species richness in mangrove areas with low anthropogenic degradation (Dankwa and Gordon, 2002, Singkran and Sudara, 2005), although both studies had confounding variables (e.g., distance to sea) that may compromise the overall conclusions. One of the most destructive natural threats to mangroves is the passage of hurricanes. Hurricane-associated wind effects include defoliation, snapping of trunks/ limbs, and uprooting, all of which can lead to immediate or delayed mortality of mangroves (Baldwin et al., 2001, Sherman et al., 2001). Susceptibility to damage, mortality rates, and potential for regeneration all vary depending upon mangrove species, location (e.g., fringe or inland), and tree size (Roth, 1992, Imbert et al., 1996, McCoy et al., 1996, Baldwin et al., 2001, Sherman et al., 2001). Regardless, hurriBulletin of Marine Science

© 2007 Rosenstiel School of Marine and Atmospheric Science of the University of Miami

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cane-associated wind damage could indirectly affect mangrove fish assemblages by altering key aspects of the habitat that benefit fish. Loss of canopy and defoliation decreases shade and increases light penetration (Baldwin et al., 2001, Sherman et al., 2001), which may influence shelter quality (Laegdsgaard and Johnson, 2001; Cocheret de la Morinière et al., 2004; Ellis and Bell, 2004) and composition of the epibiont community (Farnsworth and Ellison, 1996). Mangrove mortality results in decreased tree density and basal area and ultimately a reduction in structural complexity (Roth, 1992, Baldwin et al., 2001). This could also negatively affect shelter and feeding. Other hurricane-induced effects such as lowered dissolved oxygen and salinity may also be of consequence to fish assemblages (Burkholder et al., 2004; Stevens et al., 2006). To our knowledge, no published studies have closely examined hurricane-associated changes in fish assemblages in mangrove habitats. Silverman (2006) demonstrated significant differences in nekton-community structure of Big Sable Creek (South Florida) when comparing intact mangrove areas with areas of former mangrove that were converted to mudflats by major hurricanes in 1935 and 1960. In this study, we examined the effects of Hurricane Charley on assemblages of large-bodied (> ~100 mm standard length, SL) fishes associated with red mangrove shorelines of Charlotte Harbor, southwest Florida. We sought answers to two main questions: (1) Was post-hurricane fish-assemblage structure related to degree of wind-associated mangrove damage, and (2) Was the post-hurricane assemblage of mangrove-shoreline fishes notably different from long-term (1996–2004) pre-hurricane assemblages? Methods Study Area.—Charlotte Harbor is a shallow (generally < 4 m), drowned-river-valley estuary (Sheng, 1998) located in southwestern Florida (Fig. 1) and has a surface area of about 700 km2 (McPherson et al., 1996). A shallow shelf < 1.5 m deep extends 500–1200 m from the shoreline, beyond which deeper, unvegetated habitats (i.e., sand substrates) predominate. Tidal range is typically < 0.7 m (NOAA, 2006). Principal freshwater inputs are from the Caloosahatchee, Peace, and Myakka rivers. Charlotte Harbor contains considerably large areas of vegetated habitat, including seagrass (predominantly turtle grass, Thalassia testudinum Banks and Soland. ex Koenig, shoal grass, Halodule wrightii Achers., and manatee grass, Syringodium filiforme Kuetz. and fringing mangroves (principally red mangrove, Rhizophora mangle Linnaeus). Fringing mangroves cover an area of approximately 143 km2 (L. Kish, Manatee County Geographic Information Systems Division, unpubl. data). A more detailed description of Charlotte Harbor is available from McPherson et al. (1996). Hurricane Charley.—Hurricane Charley made landfall near North Captiva Island, Florida, on Friday, 13 August 2004 (Weisberg and Zhen, 2006). The storm was notable in that its inner core was unusually compact and intense, with a path 16–24 km wide and maximum wind gusts of nearly 280 km h–1. Physical damage to Charlotte Harbor was primarily windrelated because the storm’s landfall location, direction of travel (NNE), high speed, and small eye radius kept storm surge minimal (Weisberg and Zheng, 2006). Following the storm’s passage, dissolved oxygen in one of Charlotte Harbor’s major tributaries (the Peace River) fell below 1 mg L–1, and hypoxic conditions extended approximately 15 km into the estuary (Tomasko et al., 2006). A long-term fishery-independent monitoring program (see Greenwood et al., 2006) resumed within 2 wks of the storm’s landfall and sampling was intensified in the most heavily impacted areas to document changes in fish assemblages as a result of the hurricane (Stevens et al., 2006) At the mouth of the Peace River and upper Charlotte Harbor, fish abundance decreased dramatically, and typical estuarine fish assemblages were replaced by

GREENWOOD ET AL.: POST-HURRICANE MANGROVE-SHORELINE FISH ASSEMBLAGES

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Figure 1. Map of the study area. Sampling sites from the post-hurricane study are indicated with circles, and color coding indicates degree of mangrove canopy damage based on visual assessment: white (no damage), light gray (10%–30% damaged), dark gray (40%–70% damaged), and black (80%–100% damaged). The path of Hurricane Charley’s eye wall is shown by dashed polygons (digitized by T. Walker, Southwest Florida Regional Planning Council, from local Doppler radar imaging). Dashed straight lines indicate the southern limits of the study area for the preand post-hurricane comparison analysis. Cross-hatching indicates mangrove habitat.

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Figure 2. Examples of red mangrove damage from winds associated with Hurricane Charley. Note that trunks and major branches are broken and pushed landward, but mangrove prop roots remain. (A) A 50%-damaged mangrove shoreline, with bar indicating undamaged, verdant areas; (B) a 100%-damaged area. those dominated by a few resilient estuarine and freshwater species including the mosquitofish, Gambusia holbrooki Girard, 1859; Florida gar Lepisosteus platyrhincus Dekay, 1842; and exotic armored catfishes, Hoplosternum littorale (Hancock, 1828) and Pterygoplichthys spp. Fish abundance and composition in other areas of the estuary did not noticeably differ from those expected during summer and fall, including those in the Myakka River, located only a few kilometers west of the storm track. The hypoxic event was short-lived as dissolved oxygen levels and estuarine fish assemblages recovered within a month (Stevens et al., 2006). The most conspicuous, perhaps long-lasting, effect of Hurricane Charley was the extensive mangrove damage caused by high winds (Fig. 2). Damage to mangroves included defoliation and snapping of limbs and trunks; damage was particularly substantial along the eastern edge of the hurricane’s path. Decreases in mangrove canopy density attributable to hurricane winds ranged from ~70% at < 4 km from the hurricane eye-wall to ~25% at 19 km from the eye-wall, with very little evidence of recovery in mangrove canopy density 8 mo after the hurricane’s passage (Milbrandt et al., 2006). The effects of the mangrove damage to fish assemblages in Charlotte Harbor, particularly large-bodied shoreline associates, have not been assessed until now. Sampling Methods.—Sampling sites were randomly selected on a monthly basis using established protocols of the State of Florida Fish and Wildlife Conservation Commission’s Fish and Wildlife Research Institute’s Fisheries-Independent Monitoring program (Poulakis et al., 2003). We sampled the assemblage of large-bodied fish (> ~100 mm SL) along red mangrove shorelines with 183- × 3-m center-bag haul seines (38-mm stretched mesh) set from a small research vessel in an approximate rectangle of 4120 m 2 (103-m length along shoreline and 40-m width away from shore), with the shoreline forming one of the long edges of the rectangle. The net was pulled ashore by hand and the sample was concentrated in the bag.


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Sampling effort was ~10 samples mo–1 from November 1996 to October 2004 and ~13 samples mo–1 thereafter. Each site was sampled once. Fish were identified to lowest practical taxon (generally species); nomenclature follows Nelson et al. (2004). Fish were released after data collection, except in cases when laboratory identification was necessary. Temperature and salinity were recorded at surface, bottom, and 1-m intervals between surface and bottom with Hydrolab® or YSI Inc. probes at the location of the center bag. Water depth was also recorded to the nearest 10 cm at each site near the center bag. Visual estimates of habitat characteristics at each sampling site included proportion of shoreline covered by red mangroves, whether mangroves were inundated at the time of sampling, approximate width of inundated mangrove habitat from its seaward edge to the land-water interface, type of mangrove shoreline (i.e., fringing mangrove backed by a berm or intermittent overwash island), and proportion of sampling area covered by submerged aquatic vegetation (SAV, to the nearest 10%). Tidal stage at the time of sampling was noted (Table 1). More details of sampling procedures were described by Kupschus and Tremain (2001). Following Hurricane Charley, the proportion of red mangroves damaged along the shoreline of each sampling site was visually estimated (to the nearest 10%; recorded from November 2004 onwards) (Table 1). Typical mangrove damage consisted of broken trunks and branches and leafless portions of trees or entire trees (no canopy), but prop roots remained largely intact (Fig. 2). In only a few cases were mangroves completely uprooted and toppled. Data Analysis.—We limited data analysis to shorelines with at least 80% red mangrove coverage during November 1996–October 2005. Mangrove shoreline samples extended 40 m out into adjacent nearshore habitat that often included large areas of seagrass beds. Therefore, only common species that could be considered shoreline associates were included in the analysis. The selection of these species was based upon a comparison of data collected with the 183-m haul seines and data collected away from the shoreline with 183-m purse seines (R. H. McMichael Jr., Fish and Wildlife Research Institute, unpubl. data; Wessel and Winner, 2003), as well as consideration of other relevant studies (Ley et al., 1999; Ley and McIvor, 2002; Faunce et al., 2004). Species included in analyses were striped mullet, Mugil cephalus Linnaeus, 1758; whirligig mullet, Mugil gyrans (Jordan and Gilbert, 1884); redfin needlefish, Strongylura notata (Poey, 1860); common snook, Centropomus undecimalis (Bloch, 1792); gray snapper, Lutjanus griseus (Linnaeus, 1758); striped mojarra, Eugerres plumieri (Cuvier, 1830); sheepshead, Archosargus probatocephalus (Walbaum, 1792); red drum, Sciaenops ocellatus (Linnaeus, 1766); and Atlantic spadefish, Chaetodipterus faber (Broussonet, 1782). Post-hurricane data (November 2004–October 2005) were used to address the study’s first question: Was fish assemblage structure related to degree of wind-associated mangrove damage? For each sample, abundance data were square-root-transformed to reduce the influence of unusually high catches (ter Braak, 1986). We conducted canonical correspondence analysis (CCA; ter Braak, 1986) to assess significant environmental variables correlating with assemblage structure (Table 1). The variables considered were percentage of shoreline with hurricane damage, average temperature, average salinity, water depth (square-root-transformed), submerged aquatic vegetation (SAV) coverage at the sampling site, inundation of mangrove, width of inundated mangrove habitat, type of mangrove shoreline, and tidal stage. We followed the procedure of Marshall and Elliott (1998) by initially conducting nine exploratory CCA analyses with each environmental variable included separately, in order to determine an approximate rank of explanatory power for each variable. Following this determination, variables were added to a CCA model in order of their rank, with statistical significance of each additional term to the model’s explanatory power being assessed with a permutation test incorporating 1000 random data configurations (Lepš and Šmilauer, 2003). Variables were accepted into the model if statistically significant at P < 0.05. In this manner, a final model was obtained that included only significant explanatory variables and we assessed the relationship of the fish species to the environment with a CCA biplot. A dummy species with unit abundance in all samples was added to the analysis to keep potentially important all-zero samples under consideration and allow the CCA model to calculate weighted averages for the

Factor level (% of total samples) or continuous variable seasonal means (ranges) Nov. ’04–Feb. ’05: 21.5 °C (14.2–25.1 °C); Mar. ’05–Jun. ’05: 24.6 °C (13.7–30.9 °C); Jul. ’05–Oct. ’05: 29.8 °C (19.1–34.1 °C) Nov. ’04–Feb. ’05: 93.6 cm (40–240 cm); Mar. ’05–Jun. ’05: 99.0 cm (50–250 cm); Jul. ’05–Oct. ’05: 98.6 cm (40–270 cm) Nov. ’04–Feb. ’05: 26.6 (13.6–35.4); Mar. ’05–Jun. ’05: 23.9 (4.3–34.6); Jul. ’05–Oct. ’05 : 17.9 (2.6–33.1) High, falling (15.6%); high, rising (18.8%); high, slack (5.8%); low, falling (7.8%); low, rising (14.3%); low, slack (1.3%); mid, falling (10.4%); mid, rising (26.0%) SAV coverage 0% (31.8%), 10–50% (18.8%), > 50% (49.4%) Mangrove habitat width < 1 m (24.7%); 1–2 m (32.5%); 3–9 m (26.6%); ≥ 10 m (16.2%) Mangrove shoreline damage 0% (27.3%); 10%–30% (23.4%); 40%–70% (26.0%); 80%–100% (23.4%) Inundation Inundated (91.6%); not inundated (8.4%) Shoreline type Fringing (90.3%); overwash island (9.7%)

Variable Temperature Water depth Salinity Tidal stage

Table 1. Summary of variables considered in stepwise Canonical Correspondence Analysis of Charlotte Harbor 183-m haul-seine data from November 2004 to October 2005. Levels of factors are noted with percentages of the total number of samples (n = 154) that they constituted. Means (and range of monthly means in parentheses) are shown for continuous variables. Variables are ranked in order of inclusion in models.

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nine study species (CCA uses a weighted-average algorithm that otherwise cannot include all-zero samples). We compared the post-hurricane fish assemblage with pre-hurricane assemblages to address the study’s second question: Was the post-hurricane mangrove-shoreline fish assemblage notably different from the pre-hurricane assemblage? This analysis excluded data from the more southerly portions of the study area (Fig. 1), because these areas were not sampled prior to November 2003. Abundance data from 1996 to 2005 were square-root-transformed, grouped into three 4-mo periods for each year (November–February, March–June, and July– October) and averaged (number of fish per set), generating 27 “samples” for analysis. Data were transformed prior to averaging to reduce the influence of intersample variability (K. R. Clarke, PRIMER-E Ltd, pers. comm.). The three periods were defined in this manner not only to be consistent with the period for which mangrove damage data had been collected (i.e., November 2004 onwards), but also because they were appropriate demarcations of the main meteorological seasons (November–February: cool and dry; March–June: warm and dry; July–October: hot and wet). Note that the data for the July–October period in 2004 therefore encompassed both pre-hurricane and post-hurricane conditions. The data were then subjected to correspondence analysis (CA; Lepš and Šmilauer, 2003), the unconstrained (i.e., free of environmental variables) ordination analog of CCA (see above). From the resulting CA biplot, we assessed the extent to which post-hurricane fish assemblages differed from pre-hurricane assemblages. By conducting an unconstrained analysis, we concentrated on fish-assemblage structure without regard to environmental conditions. All analyses were conducted using the vegan Community Ecology Package v. 1.6-10 (Oksanen et al., 2005), implemented in R v. 2.2.1 (R Development Core Team, 2005).

Results Overall Sample Composition.—In total, 14,230 fishes of the nine study species were collected (Table 2). This represented just over 11% of the total abundance of the 119 taxa collected during the study period. Nearly 90% of the remaining fish were one of five abundant species that could not be considered shoreline associates [pinfish, Lagodon rhomboides (Linnaeus, 1766); tidewater mojarra, Eucinostomus harengulus Goode and Bean, 1879; silver jenny, Eucinostomus gula (Quoy and Gaimard, 1824); silver perch, Bairdiella chrysoura (Lacépède, 1802); pigfish, Orthopristis chrysoptera (Linnaeus, 1766); and hardhead catfish, Ariopsis felis (Linnaeus, 1766)]. Centropomus undecimalis (Bloch, 1792) was both the most abundant and most frequently collected of the study species, contributing more than 27% of the total catch. Sciaenops ocellatus and E. plumieri were the two least abundant species, with each contributing just under 6% of the total catch. Chaetodipterus faber was the least frequently collected species and was present in just over 15% of samples. Mean sizes of fish ranged from 151 mm SL (L. griseus) to 449 mm (C. undecimalis) (Table 2). Post-hurricane Analysis: Was Fish-Assemblage Structure Related to Degree of Wind-associated Mangrove Damage?—There was no evidence that wind-associated damage affected the structure of the fish assemblages along red mangrove shorelines in Charlotte Harbor from November 2004 to October 2005. The final CCA model retained temperature, water depth, and salinity as variables that were significantly related to fish-assemblage structure. The overall model was statistically significant (P < 0.001), but explained only a modest proportion of the total inertia (data variability). The inclusion of the percentage-of-damaged-mangrove-shoreline variable did not significantly increase the explanatory power of the model including the above three covariables (P = 0.36; Table 3). CCA axis 1 explained

Striped mullet, Mugil cephalus Whirligig mullet, Mugil gyrans Redfin needlefish, Strongylura notata Common snook, Centropomus undecimalis Gray snapper, Lutjanus griseus Striped mojarra, Eugerres plumieri Sheepshead, Archosargus probatocephalus Red drum, Sciaenops ocellatus Atlantic spadefish, Chaetodipterus faber

CPUE (n = 1,105) 0.88 ± 0.07 0.84 ± 0.11 1.58 ± 0.15 3.50 ± 0.31 0.93 ± 0.09 0.75 ± 0.09 2.35 ± 0.21 0.74 ± 0.06 1.30 ± 0.27

Total number 973 926 1,744 3,873 1,030 833 2,595 821 1,435

Frequency of occurrence (n = 1,105) 31.13% 16.92% 36.29% 49.86% 24.71% 16.56% 44.43% 29.41% 15.11%

CPUE (Nov.–Feb., n = 344) 1.22 ± 0.15 1.53 ± 0.30 2.35 ± 0.037 2.75 ± 0.50 0.25 ± 0.05 0.29 ± 0.10 3.34 ± 0.57 0.94 ± 0.12 0.46 ± 0.18

CPUE (Mar.–Jun., n = 357) 0.74 ± 0.10 0.50 ± 0.09 1.37 ± 0.18 3.36 ± 0.39 0.64 ± 0.12 1.11 ± 0.22 1.55 ± 0.20 0.67 ± 0.08 0.77 ± 0.19

CPUE (Jul.–Oct., n = 360) 0.72 ± 0.11 0.50 ± 0.13 1.13 ± 0.20 4.60 ± 0.70 1.85 ± 0.22 0.89 ± 0.14 1.86 ± 0.20 0.58 ± 0.12 2.49 ± 0.73

289.9 (83–466) 180.9 (55–333) 344.4 (160–507) 449.4 (101–960) 151.1 (45–280) 159.4 (32–300) 211.3 (24–440) 394.8 (57–727) 185.4 (42–331)

SL (Mean, range)

Table 2. Catch composition of principal fish species collected along red mangrove shorelines of Charlotte Harbor, November 1996–October 2005. Catch per unit effort (CPUE) is fish per haul (± SE). Frequency of occurrence is percentage of all samples in which a species was present. Seasonal means were calculated only for areas included in the pre- and posthurricane comparison analysis. SL is standard length (mm). Sample sizes are noted in parentheses.

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Table 3. Results of stepwise Canonical Correspondence Analysis model analysis of Charlotte Harbor 183-m haul-seine data from November 2004 to October 2005. Statistically significant additions are noted in bold, with conditional variables at each step in parentheses. Constraining variables 1. (Temperature) + water depth 2. (Temperature + water depth) + salinity 3. (Temperature + water depth + salinity) + tidal stage 4. (Temperature + water depth + salinity) + SAV coverage 5. (Temperature + water depth + salinity) + habitat width 6. (Temperature + water depth + salinity) + mangrove damage 7. (Temperature + water depth + salinity) + inundation 8. (Temperature + water depth + salinity) + shoreline type

Significance of added term 0.002 0.017 0.4 0.121 0.092 0.363 0.287 0.582

7.8% of total inertia and described fish-assemblage differences attributable to temperature (Fig. 3). Species most strongly associated with lower temperatures included S. notata and M. cephalus, whereas C. faber tended to be most abundant at higher temperatures. CCA axis 2 explained 2.8% of total inertia and was related to assemblage differences caused by differing salinities. This demonstrated that E. plumieri, for example, tended to be found at very low salinities. Water depth was quite strongly associated with both of the CCA axes. Pre- and Post-hurricane Comparison Analysis: Was the Post-hurricane Mangrove-shoreline Fish Assemblage Notably Different from Pre-hurricane Assemblages?—There was little evidence of post-hurricane fish assemblages associated with red mangrove shorelines greatly differing from pre-hurricane assemblages. Post-hurricane assemblages tended to be well mixed among those found in pre-hurricane years, as seen on the CA plot (Fig. 4). The same was true of the assemblage present from July to October 2004 (i.e., encompassing August 2004 when Hurricane Charley affected the area; Fig. 4). The post-hurricane assemblage from March to June 2005 was somewhat different from this season’s assemblages in most of the remaining years, primarily because of relatively high abundance of S. notata and M. gyrans, and also because of relatively low abundance of E. plumieri, A. probatocephalus, and C. undecimalis. The March to June assemblage from 2004 was more of an outlier, however (Fig. 4). CA axis 1 explained nearly 50% of the total inertia and was related to seasonal differences in abundance: species were generally either most abundant from November to February (M. gyrans, S. ocellatus, S. notata, M. cephalus, and A. probatocephalus) or most abundant from July to October (L. griseus, C. faber, and S. ocellatus). Only E. plumieri had highest mean abundance from March to June. The centroids of C. undecimalis and A. probatocephalus were close to March to June in the biplot because their annual peaks in abundance—from July to October (C. undecimalis) and from November to February (A. probatocephalus)—were not substantially greater than during March–June. CA axis 2 explained just over 15% of total inertia and was related to interannual differences in abundance. Discussion Results of our study suggested that wind-associated damage to red mangroves along the Charlotte Harbor shoreline did not greatly affect the structure of assemblages of large-bodied fish. Detailed experimental studies of the importance of man-

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Figure 3. Canonical Correspondence Analysis species-environment biplot of the post-hurricane study to assess effects of mangrove damage on fish-assemblage structure. Only environmental variables significantly related to assemblage structure are shown. Each species label is adjacent to the point representing its centroid.

grove-habitat attributes such as shade and structure have tended to focus on the nursery function of these areas for small fishes (Primavera, 1997; Laegdsgaard and Johnson, 2001; Cocheret de la Morinière et al., 2004; Ellis and Bell, 2004). Field studies have provided more information on fishes comparable in size to those described in the present study. Ley and McIvor (2002), working in Florida Bay, observed that L. griseus were positively associated with a compound environmental axis representing increasing mangrove fringe width, increasing mangrove tree height, decreasing prop-root density, increasing water depth, and increasing SAV volume. Faunce et al. (2004) found positive correlations between L. griseus abundance and width of the prop-root habitat (and also creek depth; see below) in the southeastern saline Everglades, but found no relationship between abundance and prop-root density or diameter. Of other species that we studied in Charlotte Harbor, Faunce et al. (2004) could not establish any relationship between abundance of S. notata and any of the aforementioned features of the mangrove habitat. It is therefore apparent that while some species-habitat correlations involving mangroves exist, relationships are not consistent for different species or for the same species from different locations. In this light, it is perhaps not surprising that we did not observe any differences in fish assemblage with various mangrove habitat characteristics. The only study that we could locate addressing the relationship between changes to mangrove canopy and


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Figure 4. Canonical Correspondence Analysis species-sample biplot of the pre- and post-hurricane comparison study to assess effects of mangrove damage on fish-assemblage structure. Sample labels indicate year and period, where NF = November–February, MJ = March–June, and JO = July–October. Note that samples labeled NF represent samples from November of one year to February of the following year. Full-box labels indicate post-hurricane samples, dashed-box label indicates samples collected from July to October 2004 (i.e., encompassing Hurricane Charley in August 2004). Each label represents the mean of all 183-m seine samples collected during that period. Each species or sample label is adjacent to the point representing its centroid.

fish-assemblage structure was that of Ellis (2003). Using drop block nets, he found mangrove-canopy trimming to have no effect on overall fish assemblage structure or on abundance of large roving species (including species included in our study) in Rookery Bay, Florida. Ellis (2003) also noted that variability among samples within the same habitat is often so great that alteration to habitat may have to be substantial to produce discernible changes in fish abundance or assemblage structure. The same may have been true of our study. With regard to other features of mangrove structure that we investigated, it is important to note that larger fish will tend not to penetrate very far into inundated mangroves (Vance et al., 1996; Rönnbäck et al., 1999); this could explain why mangrove habitat width appeared unimportant in structuring the fish assemblage. To our knowledge, no attempt has been made to ascertain the differences between fish assemblages in fringing mangrove forests and those in overwash-island mangrove forests. Gilmore and Snedaker (1993) did not differentiate the two forests in terms of overall lists of fish species. Some habitat attributes of the two types of forest differ (e.g., average tree height and stand diameter; Gilmore and

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Snedaker, 1993). Our limited sampling of the overwash habitat precludes our making firm conclusions regarding any differences in the fish assemblages of these habitats. Our study demonstrated that the post-hurricane large-bodied mangrove-shoreline fish assemblage was not markedly different from pre-hurricane assemblages, suggesting a degree of resiliency to seemingly great change. Any direct mortality due to the effects of the hurricane was likely to have been minimal (cf. Tabb and Jones, 1962), but some fish kills and short-term changes to the large-bodied-fish assemblage structure were observed as a result of hypoxic conditions attributable to mangrove and riparian-vegetation defoliation (Stevens et al., 2006). These effects were temporary and apparently induced changes to fish-assemblage structure that were within the range of variability observed from 1996 to 2004. Small-bodied-fish assemblage structure also changed in the short term, but generally reverted back to a more typical composition within a period of weeks (Stevens et al., 2006). Greenwood et al. (2006) showed that the change in small-bodied shoreline fish assemblage following Hurricane Charley was outside the range of variability observed in the previous 8 yrs, with apparent declines in some vegetation-associated species. Additional years of data collection are required to examine the long-term effects of vegetation damage, both to mangroves and seagrasses, from Hurricane Charley. Regarding the lack of substantial change in the post-hurricane large-bodied mangrove-shoreline fish assemblage compared to the pre-hurricane period, it is important to note that the pre-hurricane period was rather variable in terms of environmental conditions: the winter of 1997–98 included a strong El Niño event, characterized by relatively high rainfall, followed by a period of more than 2 yrs of La Niña-influenced drought (Schmidt et al., 2004). Also, an important fishery-management measure (elimination of entangling gill nets) was enacted in July 1995 and caused a major decrease in fishing mortality of several of the species considered in this study, particularly M. cephalus. This produced increases in overall abundance over the first few years of our study period (Pierce et al., 1998). In some areas, the mortality of red mangroves following Hurricane Charley is gradually leading to the lifting of prop roots from the substrate as standing dead trees dry out and straighten; the prop roots are also gradually decaying (T.A. Tattar, University of Massachusetts, pers. comm.). In general there appears to be very poor recruitment of red mangrove saplings to damaged areas, suggesting that standing dead trees may decay quicker than fringing mangrove can recover, ultimately converting forest to mud flat. This phenomenon was observed in Big Sable Creek, Florida (Silverman, 2006). These longer-term aspects of change may eventually lead to greater effects on shoreline biotic communities than we observed in the year following the hurricane. Also, the effect of widespread mangrove mortality on the many other mangrove functions (e.g., primary productivity, food-web and nutrient dynamics) may ultimately lead to system-level changes that affect abundance of large-bodied fishes. Our continued study of Charlotte Harbor will allow us to re-evaluate the shoreline fish assemblages in the future. Our results showed that of the variables we assessed, physical attributes of the environment (temperature, water depth, and salinity) most influenced the structure of the fish assemblage. This agrees with the overall conclusions of Kupschus and Tremain (2001), who sampled the ichthyofauna of the Indian River Lagoon (east Florida) with the same gear and procedures. Some very obvious similarities existed between the fish-assemblage associations in Charlotte Harbor and those in the Indian River


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Lagoon. For example, S. ocellatus, M. cephalus, and S. notata tended to be found in cooler temperatures, whereas L. griseus and C. faber were more abundant during warmer periods and in deeper areas. The importance of temperature in structuring the fish assemblage is most likely the result of seasonal changes in abundance as opposed to avoidance of cooler areas, although the latter effect should not be discounted for some species (e.g., C. undecimalis; Pattillo et al., 1997). Ley at al. (1999) found positive associations between L. griseus abundance and increasing temperature, salinity, and water depth. Ley and McIvor (2002) and Faunce et al. (2004) also found a positive association between L. griseus and water depth. Thus it appears that greater water depth is an important factor governing abundance of L. griseus, which may be due to improved access to prey at greater depths. We did not find any association between fish-assemblage structure and SAV coverage, which was not surprising given our selection of species that are principally shoreline associates. Although Kupschus and Tremain (2001) found that SAV coverage was of importance in structuring the Indian River Lagoon fish assemblage, eight of the nine species that we considered in this study had no clear association with SAV in their study area (E. plumieri was the exception and was less common in vegetated areas). Furthermore, our study was limited to red mangrove shorelines and thus eliminated one of the major factors structuring fish assemblages in tropical and subtropical estuaries, because overhanging shorelines often have markedly different assemblages compared to beach or non-overhanging shorelines (Sheaves, 1992, 1996; Kupschus and Tremain, 2001). Regardless, the presence of red mangrove prop-root habitat may be of greatest importance in determining fish distribution; changes to the habitat may not be as important as its absence (Silverman, 2006). It is appropriate to acknowledge the study’s main limitations. Firstly, our sampling technique probably did not provide the same degree of semi-quantitative information on fishes associated with mangrove-prop-root habitats as the information obtained from studies using block nets or visual surveys (Sheridan and Hays, 2003). Although we consider the species chosen for analysis to be shoreline-oriented, we acknowledge that our sampling technique could have captured them away from the shoreline. Secondly, data from this study were collected during a fishery-independent monitoring program designed to monitor interannual trends in fish abundance—we had to subset a larger database of samples to find red mangrove shorelines meeting our criteria for inclusion, which inevitably led to a relatively low sample size and lack of control of other environmental variables. A dedicated study (perhaps with fixed sampling stations) aiming to control as many confounding environmental variables as possible may provide clearer indications of the effects of mangrove damage on fish assemblages. Thirdly, the correlations between fish assemblage structure and environment were relatively weak, although statistically significant (and fairly typical for this type of analysis). This may be because of large intersample variability in abundance (with many zero catches) or perhaps because important predictors of assemblage structure had been excluded from the analysis, e.g., food abundance or habitat structure of adjacent areas. The study should therefore be regarded as largely exploratory as opposed to predictive. Finally, the mangrove-damage metric that we employed was based on a simple visual assessment and did not attempt to quantify potentially important variables such as below-canopy light penetration or structural complexity.

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We conclude that hurricane damage to red mangrove shorelines had little apparent effect on the structure of the shoreline-associated large-bodied fishes. We focused solely on abundance—and, by extension, assemblage structure—but other potentially important aspects of change may be worthy of investigation (e.g., mean size, biomass, condition, and disease prevalence). To more accurately gauge the influence of mangrove damage on shoreline fish assemblages would require a dedicated study in which sampling gear that is more effective at accurately assessing abundance within the prop-root habitat is used (e.g., visual census [video or direct observation] or block-netting) and in which detailed measurements are made of mangrove characteristics such as prop-root density, below-canopy light penetration, and epibiont coverage. Such a study would ideally be undertaken in a relatively small geographical area to minimize the influences of differing physico-chemical conditions (e.g., salinity, distance to inlets) on assemblage structure (see Ellis, 2003). Although not without limitations (see above), our sampling regime had the strength of addressing fishery issues at broad temporal and spatial scales. For example, it was clear that recreationally important fishes included in this study (e.g., C. undecimalis, S. ocellatus) had not abandoned damaged areas and were not found solely in areas where mangroves remained undamaged. Also, populations of larger fishes were not (as yet) grossly affected by Hurricane Charley and the associated wind damage to mangroves. These issues will remain important while more is learned about the rate of mangrove decay and recovery. A comprehensive oversight of the situation will ultimately come from broad, random sampling of the estuary, which would allow the state of fisheries to be viewed from the perspective of long-term trends in abundance and habitat use on an estuary-wide scale. Acknowledgments We thank the field crews of the Florida Fish and Wildlife Conservation Commission’s Fisheries-Independent Monitoring program (Charlotte Harbor Field Laboratory) for collecting and processing the data. Support for this study was provided in part by funds from Florida Recreational Saltwater Fishing License sales and U.S. Department of the Interior, Fish and Wildlife Service, Federal Aid for Sportfish Restoration Project Number F-43. Thanks to J. Leiby, J. Quinn, R. McMichael, D. Blewett, and two anonymous reviewers for constructive comments on an earlier draft of the manuscript. L. French’s assistance with figure preparation is greatly appreciated.

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